2. BÖLÜM ULUSLARARASI BĠLĠMSEL …Varol, A.: ―Multi-Phase Transport In A Siphon and Jet Pump System‖, 6th Miami International Symposium On Heat and Mass Transfer, 10-12 December

2. BÖLÜM

ULUSLARARASI BĠLĠMSEL TOPLANTILARDA

SUNULAN VE BĠLDĠRĠ KĠTABINDA

(PROCEEDINGS) BASILAN BĠLDĠRĠLER

Varol, A.: ―Multi-Phase Transport In A Siphon and Jet Pump System‖, 6th

Miami

International Symposium On Heat and Mass Transfer, 10-12 December 1990,

Miami, USA

195

2.1. MULTI-PHASE TRANSPORT IN A SIPHON AND JET

PUMP SYSTEM

ABSTRACT

A combined pump system is used for vertical transportation of water

or muddy concentrated fluid from a river, sea, etc. This system has two

important parts called the injector pump and the siphon pump. The pumps

are fixed on a vertical pipe with the siphon pump located above the jet pump

at a distance that is optimized by using an iteration method on a computer.

By pumping clear water into the water injector, the mixed fluid is

raised in the vertical pipe. At the same time compressed air is injected into

the pipe, and the density of the muddy fluid is decreased. Because of the

static pressure on the pipe, a two-phase transportation occurs.

The total pressure drop in the upper part of pipe, which begins after

the siphon pump, cannot be calculated easily because there is air which is

compressible in the muddy fluid, and the air in the muddy fluid is expanded

when it flows towards the top of pipe. Therefore, the pressure drop in the

upper part of pipe is calculated by an iteration method.

In this study the theoretical and experimental results will be

discussed.

Keywords: Fluid Flow Computation, Multiphase Flow, Injector,

Siphon, Combined Pump System

INTRODUCTION

A schematic of the system is shown in Fig. 1. The system consists of

a centrifugal pump, a water injector, a siphon pump, a compressor and

several pipes.


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The injector of the system must be set under the water where the

system is used in order to realize the transportation. The greater the distance

between the water level and the injector is, is the better the efficiency of the

system. If the water is deep enough to set the siphon pump beneath the

surface, the transportation is even more efficient [1, 2].

If the clear water is pumped into the injector by using a centrifugal

pump (P), the pressure in the injector is decreased. Because of the static

pressure of the water, which exists on the pipe, the fluid level rises in the

pipe [3,4].

At the same time, compressed air is injected into the siphon pump,

where the density of the fluid has decreased. Because of the decreasing of

the fluid density and of the static water pressure on the pipe, the muddy

fluid is raised in the vertical pipe continuously [5, 6].

Fig 1: Schematic of the system


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THE CHARACTERISTIC OF THE INJECTOR

The experimental set used to show the injector‘s characteristics are

given as follows according to the references [1, 3].

(P/q)=2/r+2m2/(r

2-r) - k(1+m)

2/r

2 (1)

The meanings of the terms that are used in equation (1) are given in

the section ―Nomenclature.‖

During the transportation, the height of Hw is equal to:

Hw= w.Qp2.(P/q)/

2 (2)

PRESSURE DISTRIBUTION OF THE SYSTEM

The pressure distribution of the system is given schematically in

Fig. 2. Before the transportation occurs, the pressure on the lower end of

pipe is given as follows:

Po= Patm +m.g.(H j+Hx) (3)

The height of Hx is chosen very small; therefore, this term can be

removed from the above equation. The pressure drop between the injector

and the siphon pump occurs because of the weight, friction, acceleration and

entry pressure drops in the pipe and is given in the equation (4).

Pb = ( m/2).e. Vb

2 + (Qm/A)

2 + Ht2.g +

(/D).(Qm/A)2 (4)


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Fig 2: The pressure distribution of the system

The static pressure on the siphon pump is found as:

Ps= Patm + w.g.Hj -pb (5)

The area ratio of the air and the muddy fluid in the upper part of the

pipe is defined as follows for the system, which has a 50 mm pipe diameter

3.

a= (Qa/A).(0.16+1.081 (Qa/A)+Qm/A) (6)

The average density of the mixed fluid (muddy fluid and air) is

calculated using the equation:

x=(1-a)m+a.a (7)

The total pressure drop in the upper part of pipe, which begins after

the siphon pump, cannot be calculated easily because there is air which is

compressible in the muddy fluid, and the air in the muddy fluid is expanded


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when it flows towards the top of pipe. Therefore, the pressure drop in the

upper part of pipe is calculated by an iteration method.

The pressure drop in the upper part of pipe occurs because the

friction, the acceleration and the weight pressure drops.

x is a very small step in the upper part of pipe where it is assumed

that all variables stand constant.

For the step x, the pressure drop is found as follows:

Pu= (P/x)fu. x+(P)au.x + (P/x).x (8)

The pressure distribution between the siphon and the upper end of

the pipe is determined from equation (9), which is inferred from Fig. 2.

Psl

i

Pu= Patm (9)

where i=(Hs +Hu)/ x (10)

The pressure drop in the step x is calculated with the equation

below:

Px = (x./2.D).(m.m.Vm2 +a.a.Va

2) + 0.5

(m.m(Vm22-Vml

2))

0.5 (a.a(Va22-Va1

2)) + g (m.m +a.a).x (11)

where Vm=Qm/(A1-a)), Va=Qa/(A.a) and a+m=1

The volumetric mass of air, which is compressed, to the siphon

pump is written as follows:

Qa= Qas (Patm/Ps) (12)


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For the system used, performance is found from the equation (13)

because of the compressor and centrifugal pump.

Pu=Patm.Qas In(Ps/Patm)+Qp.w.Vp2/2 (13)

The consumed performance of the system is:

P=Pb.Qm + l

i

Px(Qm+Qa(x)) - w.g.Hj.Qm (14)

Finally, the efficiency of the system is:

=m.g.Qm(Hu+Hs+Ht)/Pu (15)

RESULTS OF THE EXPERIMENTS

The muddy fluid volume flow rate in the upper half of vertical pipe

is measured as a function of the standard air volume flow rate, which is

compressed into the system. These measurements are taken for a pipe which

has a diameter of 50 mm. Different injectors are used for this pipe, and for

each injector, multiple measurements are taken using different injector area

ratios (r).

For the injector in the 50 mm pipe system, three different injector

area ratios are used ( r = 6.12, r = 18.75, r = 33.33). The results are obtained

for this system with all other parameters such as Hj, Ht, Hs, Hu held constant.

Centrifugal pumps and injectors used in the system are selected so

that without the siphon pump there will not be any water flow in the upper

half of the pipe. The purpose of using the centrifugal pump and injector is to

raise the beginning height of Hj to Hw.

In Fig 3., the injector area ratio is r = 18.75. In this figure the muddy

fluid volume flow rate Qm in the upper half of the pipe is given as a function

of the standard air volume flow rate Qas.


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Fig 3: The transported muddy fluid volume flow rate Qm as a function of Qas

As shown in the figure, it is necessary to have an exact standard air

volume flow rate in order to realize the fluid transportation in the upper half

of the pipe. If the amount of the pumped volume water flow rate Qp is

increased, the minimum standard air volume flow rate Qas will be decreased

to transport the muddy fluid. If the standard air volume flow rate is raised

continuously, the transported muddy fluid volume flow rate will be

increased to an exact point, but after an exact point increasing the standard

air volume flow rate will be increased to an exact point, but after an exact

point, but after an exact point increasing the standard air volume flow rate

does not have any effect on the muddy fluid because the curves go

horizontally, and they even go down sharply later.

In Fig .4. the muddy fluid volume flow rate in the upper part of pipe

is given as a function of the pumped water flow rate for different standard

air volume flow rates which are compressed in the system.


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Fig 4: The relationship between the transported muddy fluid volume flow

rate and the standard air flow rate.

In these figures the injector area ratios (r) are given as parameters. If

the injector area ratio is increased the muddy fluid volume flow rate is

raised also. If Qp= 0 for the different r value, the given curves should join on

the same point of the ordinate because for the Qp=0 value, the r does not


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have any effect on the transportation. If the injector is not in use, the curves

cut the abscise instead of the ordinate for the Qm= 0 value because the

standard air volume flow rate Qas is not enough to realize the transportation.

In Fig.5. the efficiency of the system is given as a function of the

standard air volume flow rate for three different pumped volume water flow

rates Qp and for an injector area ratio r =18.75. It should be distinguished

that the efficiency of the system does not rise with the increasing of the

amount of pumped water volume flow rate Qp. For example, the efficiency

for the Qp= 2.33 m3/h is equal to 7.7%, while for Qp=3.451 m

3/h the

efficiency is equal to only 6.5%. The cause of this decrease is the friction

pressure drop in the pipe because of the raising of the pumped volume water

flow rate Qp.

The experimental and theoretical results are compared in Fig. 6. The

net transported muddy fluid flow rate Qm is given as a function of the

standard air volume flow rate Qas for different Qp and r values. The

maximum deviation between theoretical and experimental results is ±15 %.

Fig 5: The system efficiency


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As shown from Fig. 6. the experimental results support the expected

theoretical values.

Fig 6: The comparison of the theoretical and experimental results

CONCLUSION

The transported muddy fluid volume flow rate can be calculated

using the theory, which is given in this paper.

Because of expansion of the air in the upper part of pipe, the

pressure drop must be calculated using an iteration method on a computer.

Otherwise, it is not possible to find the theoretical results.

The experimental set is constructed so that the jet pump of the

system cannot transport the muddy fluid volume flow rate alone until the

siphon pump is operated. Therefore the efficiency of the system is lower

than expected. In application, the condition of the location where the system

is used can be more suitable, which affects the efficiency of the system.


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NOMENCLATURE

A Pipe cross section m2

D Pipe diameter, m

g Gravitational Acceleration, m/s2

Hj Height between the water level and the injector, m (Fig 1)

Hs Height m (Fig 1)

Ht Height between the water level and the siphon, m (Fig 1)

Hu Height, m (Fig 1)

Hx Height between the lower end of the pipe and the injector, m

(Fig 2)

Hw = Ht + Hs, m

i Integration step number, -

k Total friction factor of the injector (k=1.7)

m The mass flow ratio = Qm/Qp,-

Patm Atmospheric Pressure, Pa

Po Pressure on the lower end of the pipe, Pa

Ps Static Pressure on the siphon pump, Pa

Pu Pressure drop in the upper part of the pipe, Pa

pump, Pa

Pu Pressure drop in the upper part of the pipe (in the stepx), Pa

r The cross section ratio, -

Qa Air volume flow rate, m3/s

Qas Standard air volume flow rate, Nm3/s

Qm Muddy fluid volume flow rate, m3/s

Qp Pumped volume water flow rate, m3/s

Va Air velocity, m/s


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Vb Muddy fluid velocity between the injector and the siphon

pump, m/s

Vm Muddy fluid velocity, m/s

x Step in the upper part of the pipe, -

a Air ratio in upper part of the pipe, -

m Muddy fluid ratio in the upper part of the pipe, -

Efficiency of the system, -

Friction factor of the pipe, -

e Entry pressure drop coefficient, -

a Density of air, kg/m3

m Density of muddy flow, kg/m3

INDEX

fu friction pressure drop in the upper part of the pipe

au acceleration pressure drop in the upper part of the pipe

REFERENCES

1. Winoto, S.H.; Li, H.; Shah, D.A., Efficiency of jet pumps, Journal

of Hydraulic Engineering, Volume 126, Issue 2, 2000, Pages 150-

156

2. Preene, M., Ejector feat, International Journal of Rock Mechanics

and Mining Sciences, Volume 33, Issue 8, December 1996, Page

375A

3. Feldle, G.: Feststoffeinfluss auf Wasserstrahlpumpen beim Einsatz

zur hydraulischen Foerderung und Folgerungen fuer die


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Treibwasserpumpen. Forschungsvorhaben der KSB-Stiftung, Nr.

1052, Maerz 1977

4. Dedegil, M.Y.: Neuere Untersuchungen zum Lufthebeverfahren,

Verfahrenstechnik, Nr.4, 16. 1982

5. ASHRAE Handbook, Fundamentals, 1989, p:4.11

6. Weber, M., Störmungsfördertechnik, Krausskopf-Verlag, 1974,

p.196f. and 289f

Varol, A.; ―Ünsal, M.: Modeling and Computer Simulation of an Air Conditioning

System with a Cold Water Storage Tank‖, 6th

Miami International Symposium On

Heat and Mass Transfer, 10-12 December 1990, Miami, USA

209

2.2. MODELING AND COMPUTER SIMULATION OF AN AIR

CONDITIONING SYSTEM WITH A COLD WATER STORAGE

TANK

A. Varol 1, M. Ünsal

2

1 Technical Education Faculty, Fırat University, 23119 Elazığ,

Turkey

2 Department of Mechanical Engineering, Gaziantep University,

Gaziantep, Turkey

Abstract

Computer simulation of an air conditioning system with a cold

storage tank is the subject of this research. The cold storage tank is cooled

by low temperature nighttime atmospheric air via an air/water heat

exchanger and the air conditioning system condenser is cooled by the water

in the cold storage tank during daytime when the air conditioning system is

inoperation.

The purpose of this study is to estimate the effects of daily cold

storage on the daily energy balance of the conditioning system.

INTRODUCTION

A sketch of the system is shown in Fig. 1. The system consists of

the building (for which hourly heat loads are known), the evaporator -

compressor - condenser units (which are used to condition the environment





210

of the building), the water storage tank and the cross-flow heat exchanger

(which is used to cool the water at night). First, the energy balance for each

unit is derived by using a model. After completing the equations, the

problem is solved using a computerized finite difference approach. Daily

variations of the system temperatures and daily energy balances are

calculated. The theoretical results of operating the system with a cold water

storage tank and without a cold water storage tank are graphically compared.

Fig 1: Sketch of the air conditioning system with cold water storage.

ANALYSIS

For each subsystem in Fig. 1 the model equations are written. It is

assumed that fan coil units exist in the conditioned space.

The equations for fan-coil units were derived using reference

For the fan-coil unit

Qfc= (.Cmin)fc.(Tr -Twi) (1)

1 Two - Twi fc = (2)

If cpTr <cwTw in equation (2) then X=1, otherwise





211

X= (Cmin/Cmax)fc

For the evaporator

Qe= (.Cmin)e.(Two - Te) (3)

For the compressor,

Qc=Qe+W (4)

W

Qe = (5)

Tc/Te -

For the condenser,

Qc= - (.Cmin)c(Tw-Tc) (6)

For the water storage,

dT

Qs = wVwcw _________

+ (UA)s(Tw-T) (7)

dt

For the heat exchanger,

Qhe=(.Cmin)he(Tw - Ta) (8)

For the conditioned space,

dTr

Qld = Mcp +1Qfc (9)

dt





212

The variables q, f, R, N and w dimensionless whose meanings are

explained in section ―Nomenclature‖ are used here in order to define the

statements numbered (1) - (9). After this operation, the following equations

are obtained.

For the fan-coil units,

Nfcqfc=r - wi (10)

1 wo - wi

fc = (11)

X r - wi

If, in equation (11), cpr < cw w then X=1, otherwise

X= (Cmin/Cmax)fc

For the evaporator,

Re,fcNeqe= wo - e (12)

For the compressor,

qc = qe +w, and (13)

w

qe = (14)

c + 1

For the condenser,

Rc,fc Ncqc = -w - c) (15)

For the water storage tank,





213

dw

qs = p _________

+ Rfc,s

w (16)

d

For the heat exchanger,

Rhe,feNheqhe = w - a (17)

For the conditioned space,

dr

qld = S +1qfc (18)

d

The factor 1 in equation (18) is equal to 1 (1=1) if the

compressor is in operation, otherwise 1 is zero (1=0). Solving Equation

(11) for wo and combining the result with Equation (12) eliminates wo

term. The term qfc in equation (10) is substituted by qe, since qfc=qe. Solving

Equation (10) for term wi and combining thi derived Equation with

Equation (12) gives the following:

Rqe = r-e (19)

Using Equation (13), the term qe is eliminated from Equations (14),

(18), and (19) as follows:

e+1

qc -w =w (20)

c+1-(e+1)

dr

S = 1 (w-qc)+qld (21)





214

d

R (qc-w) = r - e (22)

Solving Equation (22) for e and putting the result into Equation

(20) gives the following:

r- R(qc - w) +1

qc - w =w (23)

c+1 - (r -R(qc-w)+1)

Finally, Equation (15) is rearranged to solve for c; the algebraic

equivalent of c is put into Equation (23). The resultant equation is solved

for qc; terms are rearranged and the equation is put into the following

general form:

qc= - (b/a) + (b/a)2 - (c/a)

1/2 (24)

The algebraic expressions for terms a, b, and c are in the

―Nomenclature‖ section of this report. Because the qs term is equal to the

difference of the term qc and qhe, for the water temperature of the storage,

the following basic differential equation is found.

dw

p + Rfc,sw = 1qc - qhe 2 (25)

d

Using the Equations (21) and (25), a computer simulation program

is prepared for the dimensionless time variation according to the storage and

space temperatures.





215

If the space temperature increases over an exact automatically

control value the compressor starts working and the term of 1 is equal to 1

(1=1). If the space temperature decreases under the automatic control

lower regulating point, then, 1=0 is obtained.

When the ambient temperature is lower than the cold water storage

tank, the circulating pump of the heat exchanger is started (2=1); if not, the

heat exchanger is cut out from the system (2=0).

The Equations (21) and (25) are solved with computer using the

Newton Method. The dimensionless time interval =1 is equal to 24

hours. There are 13 dimensionless parameters which are used in this

problem. These are: S; w; qld; ; R; Rc,fc; Nc;; p; Rfc,s; Nhe and a.

FIXING OF THE DIMENSIONLESS PARAMETERS

In this study, an air conditioning system operating in the summer is

explored. The desing heat load, the load distribution for every hour, the

ambient conditions and the dimensionless system parameters are already

known. The results of the system simulating are shown graphically after

Equations (21) and (25) are solved with a computer by using the Newton

Method.

It is assumed that the desing heat load has a value of 20 kW over an

area of 400 m2. The volume of the climate space is 1200 m

3 and has an air

mass of 1440 kg. The fan coil units are operated between 22 °C and 10 °C

where the difference is 12 °C. The fan coil units have 40 kW load capacity,

and the UA value of the fan coils is (UA)fc=40 kW/ 12°C= 3.33 kW/ °C with

these assumptions, the parameters of S are calculated:

S= (1140 kJ/°C) / ((3.33 kW/°C) (24 hr) (3600 s/hr)) = 0.0125 (-)





216

The ambient temperature Tis equal to 288 K. If the power of the

cooling compressor is chosen to be 10 kW then, the w parameter will be:

w = (10 kW) / ((3.33 kW/K) (288/K)) = 0.001 (-)

The dimensionless heat load for each hour is found by dividing the

dimensional heat load for each hour by the value of (UA)fc.T For example,

if the dimensional heat load for each hour is 4 kW, the dimensionless heat

load will be:

qld = (4 kW) / ((3.33 kW/K) (288 K)) = 0.00417 (-)

A compressor model with a motor power of 10 kW is chosen for this

study, so and are assumed as 1.04 and 0.183, respectively.

The mass of air flow and water should be equal (X=1). The

evaporation factor is assumed = (10-6) / (10-0) = 0.4 and Ne value of

evaporator is calculated as:

Ne= (UA)e/(Cmin)e = (4.96 kW/°C) /(0.4) (2.3 kg/s)(4.18 kJ/kg °C)

= 1.4 (-)

If fc = (10-6) / (22-6) = 0.25, so

Re,fc= (UA)fc /(UA)e= 3.33/4.96 = 0.67 (-)

The dimensionless R:

R= (0.67) 1.3+(1- 0.25) 1.4 = 1.9 (-)

For the maximum temperature difference of (40-20) = 20 oC, a

condenser with the capacity 50 kW is chosen. For this condenser, the

average logarithmic temperature difference is found as TLm= (20-

10)/Ln(20/10)=15°C and (UA)c = 50000/15=3.33 kW/ °C. Therefore,





217

Rc,fc= (UA) fc/(UA)c = 3.33/3.33= 1 (-)

The (Cmin)c value is calculated as follows:

(Cmin)c= 50000 (40-20)=2500 W/ °C

Nc= (UA)c / (Cmin)c=3.33/2.5=1.3 (-)

For 10 m3 tank the dimensionless p coefficient:

p = (1000) (10) (4.18)/3.33(24) 3600= 0.145 (-)

It is assumed that a 5 cm thick blanket of fiberglass surrounds the

water tank which has an external surface area of 28 m2 (UA)s=17 W/°C

Rfc,s= (UA)s/(UA)fc= 17/3333 = 0.005 (-)

Two heat exchangers each with a capacity of 3582 kJ/h are used in

order to cool the water in the Tank. Therefore,

Rhe,fc= (UA)fc /(UA) he= 3333/1800=1.9 and

Nhe = (UA)fc /(Cmin)he = (1800W/°C)/((0.362)(8000)) = 0.62 (-)

All the dimensionless parameters are:

S=0.0125, w=0.001, =1.004, =0.183, R=1.9, Rc,fc=1, Nc=1.3,

p=0.145,

Rfe,s=0.005, Rhe,fc=1.9 and Nhe=0.62

SAMPLE SIMULATION

The system simulation is realised after the Equations (21) and (25)

are solved with a computer by using the Newton method with the above

parameters.





218

The water tank has a volume of 20 m3. Using the temperature

distribution of ambient air in Fig. 2 and the above-mentioned parameters,

the temperature distribution of the water tank and the condenser are drawn

in Fig. 4 for the climate load distribution which is given in Fig. 3. The below

and above control temperature values of the 1 control parameters are

chosen as 22 °C and 24 °C in this simulation. The heat exchanger which is

used to cool the water in the tank is operated when the ambient temperature

is lower than the temperature in the water tank. The cooling load

distribution which results from simulation is given in Fig 3.

Fig 2. The distribution of the daily periodical temperature of the

outside air.

The daily COP value of the climate system is calculated as 2.15 in

this sample simulation. If the fan coil effectiveness increases from 0.25 to

0.5, the daily COP value increases to 2.30. If the heat exchanger

effectiveness increases from 0.362 to 0.724, the daily COP value increases

to 2.16 . Finally, if the evaporator effectiveness increases from 0.4 to 0.8,

the daily COP value increases to 2.22.





219

Fig 3. The daily periodical load distribution of the climate space and

exchanger.

Fig 4. The temperature distribution of the water tank and the

condenser.

CONCLUSION

After establishing a dimensionless formula for a climate system

simulation with cold water storage, and after solving this formula with

computer using the Newton Method some results, which are summarised in





220

this study were found. After using the actual dimensionless parameters of

the units found in commercial climate system and which are mentioned in

this simulation, and after integration of the economical analysis to this

simulation, a computer software toolkit can be created for use for the

improvement and optimisation of commercial systems.

NOMENCLATURE

a R + Rc,fc Nc

b (w + 1 - wRc,fc Nc - 2wR - (r + 1) + wR)/2

c -w (w + 1) + w2R + w(r +1) - w(r +1) - w

2R

C mcp, the mass of capacity

cp Specific heat of air at constant pressure, kJ/kg°C

cw Specific heat of water at constant pressure, kJ/kg °C

m Mass of flow rate, kg/s

M Mass of space air

N (UA)/(Cmin),-

p wVwcw/[ (UA)fc(24hours)]

Q Heat, kJ

R Re,fc Ne + (1-fcX) Nfc

Rx,y (UA)y/(UA)x

T Temperature

T Ambient temperature of the tank

w W/[(UA) fc T

Heat exchanger effectiveness





221

f (T - T)/ T

t/(24 hours)

SUBSCRIPTS

c Condenser

e Evaporator

fc Fan coil

he Heat Exchanger

ld Load

min Minimum

r Ambient air

w Water

wi Fan coil inlet (water side)

wo Fan coil outlet (water side)

REFERENCES

[1] Holman, J.P., Heat Transfer, McGrawHill, 1988

[2] Incropera, F.P.; Witt, D.P., Fundementals of Heat and Mass Transfer,

John Willey Sons, 1990, p.658-659

[3] ASHRAE Handbook, Fundamentals, 1989, p: 4.4





222

Varol, A.: ―Vocational and Technical Education in Turkey: Problems and

Recommendations‖, Frontiers in Education, Twenty-first Annual Conference, Purdue

University, West Lafayette, Indiana, U.S.A., Proceedings, September 21-24, 1991,

pp. 196-201, IEEE Catalog No: 91CH3069-2

223

2.3. VOCATIONAL AND TECHNICAL EDUCATION IN TURKEY:

PROBLEMS AND RECOMMENDATIONS

SUMMARY

Technical education has become very important in Turkey. Within

the last few years many two year vocational schools of higher education

have been established. But there are not enough lecturers to teach

technology in these colleges. In addition, ample tools and study materials

have not been supplied until recently.

This article will discuss the role played by engineers in technical

education, the undergraduate and graduate curricula of the technical

education facilities, the employment fields of graduates from technical

education facilities and the student selection for technical education

programs. Finally some important recommendations that are based on the

research at the Technical Education School of Firat University will be given.

TECHNICAL AND VOCATIONAL EDUCATION IN

TURKEY'S JUNIOR COLLEGES

The vocational schools of higher education that have been

established in Turkey within the last few years are the best examples of

Turkey's commitment to technical education. Although these junior colleges

were established throughout Turkey, there are not enough lecturers to teach

technology in these colleges. In addition, ample tools and study materials

have not been supplied until recently. A large number of junior colleges do

not have any buildings. Classes are conducted temporarily in other

buildings. Lack of laboratories and lack of workshops add to the above

mentioned situation; thus, people doubt the quality of the students who

graduate from these colleges. Because of a shortage of lecturers, additional





224

instructors are temporarily recruited from private industry located in same

city. It's not taken into consideration whether or not these instructors are

qualified and whether they know their subject well enough to teach.

Apparently the target is to prove only on paper that all courses have

teachers. These teachers who are recruited from companies or factories

don't keep themselves up to date in their fields because they know that they

are temporarily employed. Many of them only read their lectures from a

text book instead of preparing their own material. Some courses for which

teachers don't exist are simply cancelled. This results in many unqualified

graduates who have not completed their studies in the best way.

It should be mentioned that there are some junior colleges which have

enough instructors and enough workshops. The graduates of these schools

are well educated.

THE ASSISTANCE OF ENGINEERS IN TECHNICAL

EDUCATION

The main source of instructors for the two year junior colleges and

vocational high schools is the technical and engineering faculties. The

Higher Technical Teacher Schools became the technical education faculties

with the passage of the Higher Education Law in 1982 (Law number 2547).

There are only three technical education faculties. They belong to

Gazi University in Ankara Marmara University in Ġstanbul and Fırat

University in Elazig. In these facilities there are approximately seventeen

different teaching programs. These are named in Table 1 below.

Table 1: The teaching programs of the technical education faculties /1/.

Teaching Program Approx. Quota of Student





225

Castinwork

Computer Technology

Construction

Electrical Design and Inst.

Electronics

Industrial Machining

Heating Vent. And Air Cond.

Machine Design and constr.

Metalwork

Foundry Patterns

Motors (Automotive)

Paint Finishing

Prepared Clothing Techn.

Printing

Weaving

Woodwork

Work of Thread Maker

Gazi Marmara Fırat

43

31

63

108

72

78

43

43

63

31

52

21

52

31

126

52

78

36

52

43

33

33

33

33

52

52

52

Before 1982 it wasn't possible to promote the people who worked in

the Higher Technical Teacher Schools in their career because it was not

possible to earn a M.Sc. or Ph.D. in these fields. After these schools were

changed to technical education faculties, both degreed and other qualified

people were required; therefore, engineers were appointed to these faculties.

Engineers, technical teachers and educational lecturers all work in

the Technical Education Faculty in Firat University. This faculty has only

four departments which are called Mechanical, Metallurgy, Construction,

and Education. Only in the first three departments are there undergraduate

students. In the Education Department there are only M.Sc. and Ph.D.

students. The other two faculties (Gazi and Marmara) have more

departments that can be inferred from Table 1. Most of the department

heads in Turkey's technical education faculties graduated from engineering

schools.





226

There are four different types of courses in these faculties:

Education, general cultures, basic formation and technical fields. The

technical field courses divide into two groups. In the first group theoretical

lessons are held by the engineers. In the second group there are practical

lessons that are held in the workshop of technical education faculties, and

these lessons are taught by the technical teachers. The education lessons are

given by the lecturers with education backgrounds.

UNDERGRADUATE CURRICULA OF TECHNICAL

EDUCATION FACULTIES

The students who study in different departments of the technical

education faculty take a variety of subjects in order to complete their

undergraduate studies. There are also various credit hours in the same

program between technical education faculties. For example, Firat and Gazi

Universities have automotive (motor) programs that belong to the

Department of the Mechanical Education. Even though the automotive

program of Firat University has about 20 credit hours less than Gazi

University's, students who graduate from these automotive programs receive

the same diploma and can work at the same vocational high schools. The

Technical Education Faculty of Firat University was established after 1982

while the Technical Education Faculty of Gazi University was founded in

1937. As a result, the technical courses of the Technical Education Faculty

of Gazi University are based on the education schedule 1937 which is

scheduled to be updated to current standarts in 1991.

The Technical Education Faculty of Firat University changed its schedule

and removed some out-of-date courses from their programs and added con-

temporary courses like computer science a few years ago.

Table 2 shows the distribution of courses that belong to the

automotive program of the Department for Mechanical Education in Firat





227

University. The total credit hours of this program have the value of 122

credits that are equal to 206 hours. Theory courses are equal to one credit

hour while practical courses are equal to one half credit hour.

Table 2: Distribution of the courses in automative programs in Firat Uni/2/.

Courses Hour Rates (%)

Educational Courses

General Cultures

Basic Formation

Technical Courses

12

28

30

30

Educational courses such as'Psychology, Sociology, Measurement

and Evaluation in Education etc. are offered. General culture courses

include Principles of Atatiirk and History of Turkish Revolution, elective

courses (Physical Education, Music, Art or Printing), Turkish and Foreign

Language. Courses that belong to basic formation are Physics, Chemistry,

Mathematics, Technical Drawing, Statics, Dynamics, Strength of Materials,

Machine Elements, Materials, Thermodynamics, Fluid Mechanics,

Computer Programing, Workshop Organization, Term Paper and Hydraulic

Machinery. The other courses about automotives are included under the

technical course headings.

GRADUATE CURRICULA OF TECHNICAL EDUCATION

FACULTIES

The three technical education faculties have M.Sc. and Ph.D.

programs in order to make it possible to promote the research assistants in

their careers. The graduates who complete their master studies in any

department of the Technical Education Faculty in Firat University can

continue their doctoral degree only through the Department of Education

because the other departments have no doctoral program yet. The other two

Technical Education Faculties located in Ankara and Istanbul have doctoral





228

programs in some technical fields based on the undergraduate or master

programs.

The master program of the Technical Education Faculty in Firat

University differs from the other two faculties because at Firat University

the masters students have to take at least two educational courses which are

given by the lecturers of the Education Department while the masters

students of Technical Education Faculties of Gazi and Marmara Universities

do not take educational courses.

THE EMPLOYMENT FIELDS OF GRADUATES FROM

TECHNICAL EDUCATION FACULTIES

The technical education faculties have for their goal the education of

instructors for the vocational and technical high schools. Unfortunately, due

to low salaries of teachers in Turkey, Technical Teachers find work in

private companies or factories. Some also open workshops or start their

own business.

The newly established, two-year vocational schools of higher

education (junior colleges) are the new workplaces for technical teachers

and even for engineers. Especially the graduates of technical education

faculties who continue their master degree in a technical education faculty

take the goal to be research assistant in these junior colleges.

Technical teachers have a large number of advantages because they

can find a job easily through the Technical and Industrial Vocational High

Schools. These schools will have about 13470 vacant places for technical

and vocational teachers in 1991. This problem should be solved by three

Technical Education Faculties and by the Vocational Education Faculty

placed in Gazi University in Ankara.

THE STUDENT SELECTION FOR TECHNICAL

EDUCATION PROGRAMS





229

After finishing high school in Turkey a comprehensive entrance

exam must be passed in order to continue an educational program in a

University. Until recently, adults who wanted to study in a program of

Technical or Vocational Education Faculties could continue their studies

there without considering what kind of high school they finished, if they

could attain a high enough score on the entrance exam. This meant high

school graduates could attend a technical program of the Technical

Education Faculties. In 1989 all conditions for Technical and Vocational

Education Faculties were changed because it was belived that students who

originated from an academic High School were not capable of success in

programs of the Technical Education Faculties.

The three Technical Education Faculties had different

interpretations about the success of the students who graduated from

different programs of High Schools. Therefore, the students' success was

surveyed at the Technical Education Faculty of Firat University as shown in

Table 3.

The success of the students who originated from the academic High

Schools and who graduated from the industrial vocational or the technical

High Schools was compared with a computer. The following were

considered by this research.

1- The courses of the technical education programs were divided into

two groups. In the first group, called natural science courses, were

Physics, Chemistry, Mathematics, Statics, Dynamics, Strength of

Materials, Fluid Mechanics, etc. on which the academic High

School graduates were predicted to be much more successful while

in the second group, called technical courses, were all kinds of

Technology courses pertaining to a technical program in which the

industrial vocational and technical High Schools graduates were





230

supposed to achieve much higher than students from academic High

Schools.

2- The student who graduated from an industrial vocational or

technical High School, but continued their studies in another kind of

the Technical Education Faculty's program in Firat University were

included in the first group (Natural science courses). For example, a

student who graduates from the electric program of the industrial

vocational high school and who continues his university study in the

field of the construction program of Technical Education Faculty

was shown in the first group because this student is a stranger to the

courses of the construction (Building) program,too.

3- Although the quality of the high school and the social status affect

the success of the students, these conditions were not considered in

this work.

4- The comparison between high school graduates was done if there

were students from different high school programs the same class

and the same program. In addition, there are only three different

programs (Motor, Metals, and construction) that have students in the

Technical Education Faculty of Firat University (see Table 1).

5- The unsuccessful and expelled students were separately considered,

and the failed courses of these students were with aid of computer

fixed. After that the result were evaluated with regard to the type of

high schools that they attended.

6- The success of the other students who continued their studies in a

program of the Technical Education Faculty was evaluated by the

courses they followed in the high schools. The failed exam numbers

of each courses for each student were tabulated and for each student

the total failed exam numbers were found. The total failed exam





231

numbers were divided into the total number of the students who

were in same class. The results are shown in Table 3.

The rates of the second and third classes should be considered in

Table 3 in order to determine whether or not the graduates of the academic

high schools or the graduates of the industrial vocational or technical high

schools were more successful, because all of the 4th class students

originated from technical or industrial vocational high schools, while the

first class students were newly registered during this research.

Table 3: The total failed exam rates of per student who originated from an academic

or from a technical or industrial high school and who studied in any program of the

Technical Education Faculty of Firat University.

C

l

a

s

s

e

s

G

r

o

u

p

s

The Failed Exam Numbers/Number Of Student

First Group Courses

Natural Science Courses

Second Group Courses

Technical Courses

Motors Metals Constr Motors Metals Cons.

4

A

T

-10.38 -7.58 -3.40 -7.76 -6.41 -1.25

3

A

T

9.66

4.77

5.20

4.68

2.00

3.60

6.00

3.00

2.40

1.81

0.00

0.80

2

A

T

2.75

3.62

3.33

3.40

2.71

3.06

1.00

1.59

0.00

0.32

1.21

1.06

1

A

T

-

-

-

-

-

-

-

-

-

-

-

-





232

A= Graduates from the academic high schools

T= Graduates from the technical or industrial vocational high schools

In the second classes the failed exam rates per student for the

academic originated students were less than for the technical or industrial

vocational originated students except the Construction program. It meant

the academic originated high school graduates were much more successful

than the technical or industrial vocational originated high school graduates.

In the third class the graduates of technical or industrial vocational

high school who studied in the Motors and Metalwork programs were much

more successful than others, while the academic originated students of the

Construction program were much more successful.

After all requirements for Technical and Vocational Education

Faculties were changed in 1989, the students who want to continue their

studies in a program of the technical or vocational Education Faculties

should graduate from the same program of the technical or industrial

vocational high school, otherwise their choices are canceled.

The other changes were regarding scholarship given by the

Ministery of National Education. The students have 24 choices of different

university programs through the university entrance exam. A student who

originates from a technical, a vocational or an industrial vocational high

school and whose technical education program choice is in the first tenth

order, can obtain from the Ministery of National Education a scholarship

that covers all his study and living costs. A student who receives a

scholarship from the Ministery of National Education is employed as a

technical teacher at a technical or industrial vocational high school as soon

as s/he graduates from a Technical or Vocational Education Faculty.





233

CONCLUSION

The existing vocational schools of higher education (Junior

colleges) must be improved instead of establishing new ones. Lack of

laboratories and workshops must be corrected as soon as possible at the

junior colleges.

The number of the lecturers must be increased, and well educated

and qualified lecturers must be trained. The Vocational and Technical

Education Faculties have the most important responsibility in achieving this

goal. The Engineering Faculties should produce engineers who are

employed at the technical and vocational high schools, but these engineers

should take some educational methods courses before they begin teaching.

The junior colleges have many vacant positions for lecturers.

Especially, the Vocational and Technical Education Faculties must train

special lecturers in their M.Sc. and Ph.D. programs for junior colleges (The

Vocational Schools of Higher Education). Because there are only one

Vocational and three Technical Education Faculties in Turkey, it will not be

possible to fill vacant places of lecturers at these junior colleges. Therefore,

through the M.Sc. and Ph.D. programs of the engineering faculties, students

should be trained as specially educated lecturers.

The salaries of the technical teachers are very low at this time. As

long as the salaries of the technical teachers are not improved, graduates

will continue to find jobs outside education.

Thanks to the research results which were done at the Technical

Education faculty of Firat University it can not be claimed that the technical

or industrial vocational originated students were much more successful than

the others which can be inferred from Table 3.

All high school graduates can enter a program of the Technical

Education Faculties without considering the background they originated.





234

Students who graduated from a technical or an industrial vocational high

school can have additional points added to their university entrance exam

score in order to give them a better chance of entering a program of

Technical Education Faculties.

REFERENCES

[1] The Guide of the Students Selection and Placement in the Higher

Education, Ankara, Turkey, 1991

[2] The study Report of the Motor Program of Technical Education Faculty

in Firat University, Elazig, Turkey, 1991 (Unpublished).

Varol, A., Carabott, V., Delannoy, P., Vivet, M.: ―Control of Temperature with a

Robot‖, Matik'97, Makine Tasarım Teorisi ve Modern Ġmalat Yöntemleri

Konferansı, Gazi Üniversitesi, Teknik Eğitim Fakültesi ve Teknoloji AraĢtırma ve

Eğitim Merkezi, Ankara, 15-16 Eylül 1997, Bildiri Kitabı, 1-5

235





236

2.4. CONTROL OF TEMPERATURE WITH A ROBOT

ABSTRACT

This article is a result of a project which completed at Med-

Campus, International Summer School on Computer-Based Cognitive Tools

for Teaching and Learning. LOGO Programming Language is used to

control of a robot. Using LOGO Programming Language has some

advantages comparing to other programming languages. First of all, the

terminology of the LOGO is very easy. Controlling of a robot can be done

with any other language or symbols, too.

All kinds of the robot-movements are controlled using a number of

the procedures. In this study some important procedures will be given with

their definitions. The role of interface and Binary/Analog coding and

planning a robot in a way with different kind of function will be explained.

1. INTRODUCTION

To maintain constant temperature some materials are necessary.

They are a light/lamp which can heat when light on, a thermoresistor whose

resistance varies according to temperature and fan (propeller) which able to

blow air to cool the device. All kinds of materials which is used by this

project are available using Fischertechnik construction boxes [1,2].

A negative temperature resistance (Thermistor) is heated with the

lamp. If the temperature goes up because of light, the value of the resistance

goes down because of the NTC (Negative Temperature Coefficient) goes

down.

The fan begins to rotate in order to cool the resistance when the

temperature increases which means getting smaller for the resistance. If





237

temperature goes down too much, the NTC is heated by lighting on the

lamp.

2. PHYSICAL DESCRIPTION

The robot which is constructed has a vertical arm on where the fan

is mounted. The fan can be moved up and down by controlling with LOGO

programming language. There are two switches on vertical arm to control

the up and down movements of the fan. This allows blowing more or less

air. An interface links the computer to the robot and the robot is wired by

using a plug-box. The software to control the robot is written in LOGO. The

Picture of the mounted robot is shown in Figure 1.

Figure 1: The picture of the mounted robot for Control of Temperature

3. THE FLOW CHART OF WORK





238

The flowchart of the work is given as follows (Figure 2):

Planing the work

Defining the necessary parts

Defining of movements of motors, switches, lamps&technical decisions as

follows

Movements Motors Switches

Up M1 E1

Down M1 E1

Rotation of the fan M2

Lamp Light on/off M3

Resistance (NTC) EY?

Select the parts from Fischertechnik boxes and numbering all of parts

Mounting

Check the status of the motors and switches, step by step

Writing the part software and checking for each step

separately

Figure 2. The flowchart of the work.

4. ACTIONS AND PROCEDURES

The actions of the system can be defined as heating (light on),

cooling, movement of the fan and auto control. A flow chart of the actions is

given in Figure 3.

The actions of the systems

Heating Cooling Movement of

the fan

Auto control

1. Light on 1. Turning 1. Down

2. Light off 2. Stopping 2. Up

Figure 3. Flowchart of the actions.





239

The procedures of the system are specified under six step shown

below. At the beginning each procedure is written separately. Each

procedure means one action. If all procedures are combined in one program

together, the movement of the system will be continuous.

TO LIGHTON

MCCW "M3

END

Here is light on procedure (MCCW= Motor Counter Clock Wise)

TO LIGHTOFF

MSTOP "M3

END

The light is off.

TO HELIXLEFT :T

MCCW "M2 WAIT :T

MSTOP "M2

END

This procedure allows to turn the fan in counter clockwise direction

for T seconds. Then the M2 motor stops.

TO CONTROL1 :LV :HV

MAKE "EY EY?

IF :EY< :LV [LIGHTOFF HELIXLEFT 1] []

IF :EY> :HV [LIGHTON] []

IF AND :EY < :HV :EY> :LV [PR :EY]

CONTROL1 :LV :HV

END





240

The meanings of some parameters used in the program above are:

LV: Low value

HV: High value

EY: A value for NTC (Negative temperature coefficient)

The actual value of the captor EY, given by the function EY?, is

placed by the procedure into the variable (global) EY.

The program lets assign EY variable to EY? and EY? is functional

procedure of LOGO which gives to LOGO the value (actual on call) of the

captor (the thermoresistor in our case) via the analog input EY of the

interface. If EY value less than low value (LV) which is given by user, the

light is switched off and fan rotates counter clockwise 1 second to cool

around, but; if EY value is greater than high value (HV) also given by the

user, the light is switched on. The only EY values which are displayed on

the screen are those between LV and HV as given by the user. Then the loop

continues.

During the design and testing phase, checking the range of values

returned by the thermoresistor is useful and observing the fact that

resistance decreases when temperature increases is interesting. So a specific

tool to observe these values and phenomena can be designed and written in

LOGO.

This procedure lets work OBSERVEVALUES part program with the

parameter T and B. Here T is time as seconds and B can have two values 1

or 0. If the value of B is 1 then the fan is turning counter clockwise and

blows air else the fan is stopped.

TO OBSERVEVALUES :T :B





241

MSTOP "M2

LIGHTON WAIT :T

LIGHTOFF

IF EQUALP :B 1 [HELIXLEFT :T]

REPEAT :T/2 [PR EY? HELIXLEFT 2 WAIT 2]

END

This procedure decides whether the fan rotates or not through

controlling the M2 motor. During T seconds is light on and then the light

off, and if B has the value of 1, the fan rotates T seconds in counter

clockwise direction to cool the thermistor. In REPEAT line T/2 times EY

value will be printed on the screen and fan will rotate counter clockwise for

2 seconds waiting 2 seconds phases. This "repeat" action allows

observations of the increasing values of EY? while the temperature is

decreasing.

TO OV :T :B

OBSERVEVALUES :T :B

END

OV is used a short name instead of OBSERVEVALUES during the

debug phase.

5. CONCLUSION

The role of interface and Binary/Analog coding is very important on

Control Technology. The design of an instrument to measure phenomena

using an analog captor, making the correct choice of parts and debugging the

system. Controlling the robot with LOGO programming language can be

performed.

REFERENSES





242

[1] Manipulator Assembling Handbook, LIUM, Loboatoire d‘Informatique,

Université du Maine, B.P. 535 - 72017 LE MANs

[2] Delenoy P., Martial V.; Specifications for Cubsort, A Sorting Machine

For Cubes, Cognitive TECHnologies for Education, Med Campus, 1994

Varol, A., Carabott, V., Vivet, M., Delannoy, P.: ―Sorting Coins with Different

Diameters Through the Use of a Robot‖, Matik'97, Makine Tasarım Teorisi ve

Modern Ġmalat Yöntemleri Konferansı, Gazi Üniversitesi, Teknik Eğitim Fakültesi

ve Teknoloji AraĢtırma ve Eğitim Merkezi, Ankara, 15-16 Eylül 1997, Bildiri

Kitabı, 6-13

243





Kitabı, 6-13

244

2.5. SORTING COINS WITH DIFFERENT DIAMETERS THROUGH

THE USE OF A ROBOT

ABSTRACT

Control Technology is an exiting dynamic interdisciplinary field of

study. In recent years, interest in this field and their application in industry

has grown day to day. Robots are a part of Control Technology and major

parts of a robot are the power supply, the manipulator and the controller. A

robot can be controlled using different programming languages. In this

study, a fixed robot has been programmed to sort the coins of different

allowed diameters. Therefore, a fixed position is defined to feed the

machine and the coins are collected according to their sizes. To control of

the robot LOGO programming language is used.

1. THE GOAL OF THIS STUDY

The aim of this study is to sort 4 kinds of coins according to their

diameters namely 20, 25, 30 and 40 mm using Fischertechnik construction

boxes [1, 2]. In order to sort coins with different diameters through the use

of a robot following parts are necessary:

- Motors, switches and Fischertechnik boxes.

- A plug light with lens and with stray light cap.

- A photoresistor (LDR) with stray light cap.

- A potentiometer (LIN)

2. FUNCTIONS AND CONTROL

A fixed position is defined to feed the machine with coins of different

allowed diameters randomly. Four positions are defined in advanced to

collect the coins according to their sizes. The global process for a coin is as

follows [3, 4].

1st stage : Determination of the diameter of the coin





Kitabı, 6-13

245

2nd stage : Drop of the coin in the position corresponding to

diameter determined during stage 1.

A plug light is mounted in front of a photoresistor making a

photocell. The plug light has connection with M4 (light on) while the

photoresistor has the connection with switch 8 (E8) on the plugging box. If

the light waves a free route between the light and photoresistor then the

switch E8 has logical value 1 otherwise 0.

There are 3 additional motors lines in use. One of them is used to

drive the magnet M1 and the second one is used for the up and down

movements of M2 while the third one is used for rotating left and right

directions of M3.

8 switches are used to help in controlling the robot. The function of

the switches are as follows:

E1 Controls the up movement of the magnet in vertical

direction.

E2 Controls the down movement of the magnet in vertical

direction.

E3 Controls the position where the metallic coins with 40 mm

diameters are collected (P1).



E5 Controls the start position of robot.





E8 Controls the switch (0-1) corresponding to the photocell.

0 if the ray of light is interrupted.





Kitabı, 6-13

246

1 if no light of the lamp go freely on the LDR

A potentiometer is used to determine sizes of coins. After being

caught by the magnet the coin is moved between the light and the

photoresistor. The needed rotation to have the ray of light disappearing the

reappearing is transmitted mechanically to the potentiometer, so the

potentiometer gives values which are used to distinguish the diameters of

the coins. The value of the potentiometer is defined with a variable named

LARGE, and a procedure program with the name ASAF is written.

Only one captor is used by the system : EX which measures the

value of the potentiometer.

3. PHYSICAL DESCRIPTION

The robot has vertical arm on which a horizontal one is mounted to

hold the magnet. All movements of the robot are controlled by LOGO

program. LOGO is a general purpose artificial language. It is also based on a

simple natural syntax, without parenthesis, commas and special characters

except the quotation mark ( ― ) and colon ( : ) [1]. An interface links the

computer to the robot and the robot is wired by using a plugging box (Figure

1).





Kitabı, 6-13

247

Figure 1: The picture of a mounted robot for sorting coins

4. THE SCHEMATIC DESCRIPTION OF THE ROBOT

E3

E4

E7E6 E5

SP

E2 M2 E1M3

Pluging

box

P1

P2

P3

P4

M4 E8

Figure 2. The schematic description of the robot

Symbols Remarks

M1 Motor 1, left and right turning

M2 Motor 2, up and down movement

M3 Magnet, take the coins

M4 Light on

ACTION MOTOR SWITCHE

S

Left rotating M1

Right rotating M1

Up Movement M2 E1

Down Movement M2 E2

Magnet M3

Light on M4

Position P1 E3





Kitabı, 6-13

248

Position P2 E4

Start position E5

Position P3 E6

Position P4 E7

Photocell E8

5. THE FLOW CHART OF WORK

A flowchart of this work is necessary to be successful and to do not

waste the time. This flowchart is given in Figure 3.

Planning the work

Defining the necessary parts

Defining of movements of motors, switches, lamps and

technical decisions as described in 4

Selection of bricks from Fischertechnik boxes and numbering all of

parts

Mounting

Check the status of the motors and switches, step by step

Writing the part software and checking for each step

separately

Figure 3. The flowchart of the work

6. THE FULL PROGRAM AND THEIR MEANING

First two procedures written for intermediate tests :

Calibration of the values :

TO TES1

MAKE "X 0

REPEAT 10 [MAKE "Y SS DROP MAKE "X SUM :X :Y

PR :Y]

PR :X / 10

END

Test of the photocell on E8 :





Kitabı, 6-13

249

TO TES

MCW "M4

PR STATUS "E8

TES

END

Last procedure written : continuous work !

must be broken by CTRL+PAUSE

TO VAROL

ASAF DOWN DROP

VAROL

END

Procedure that makes the decision ; we must have only 3 separate stacks

of coins !

TO ASAF

MAKE "LARGE 2 * SS

IF :LARGE < 210 [P2 STOP]



MSTOP "M1

END

Procedure that takes a coin then measures it and gives the result

TO SS

UP SP DOWN TAKE UP

STMEAS OP MEASURE

END





Kitabı, 6-13

250

Reaching the first edge : start the measuring process

TO STMEAS

MAKE "AS "RG

MCW "M4

REACHVAL 0

MAKE "TT1 EX?

END

After the first edge is reached, reaching the second and give the

value of the difference:

TO MEASURE

REACHVAL 1

MAKE "TT2 EX?

OP :TT2 - :TT1

END

Reaching an edge : from free light to occulted or reverse, with a

step by step run on M1 for more precision.

TO REACHVAL :N

MCW "M1 MSTOP "M1

IF NOT EQUALP STATUS "E8 :N [REACHVAL :N]

END

Basic procedures for the moves : The global variable AS keeps the

value of the last move of the robot,then the following to go back to SP (start

position) is the inverse...

TO P1

MAKE "AS "LF





Kitabı, 6-13

251

MCCW "M1 WATCH "E3 MSTOP "M1

END

TO P2

MAKE "AS "LF

MCCW "M1 WATCH "E4 MSTOP "M1

END

TO P3

MAKE "AS "RG

MCW "M1 WATCH "E6 MSTOP "M1

END

TO P4

MAKE "AS "RG

MCW "M1 WATCH "E7 MSTOP "M1

END

TO SP

IF EQUALP STATUS "E5 1 [STOP]

IF EQUALP :AS "RG [MCCW "M1] [MCW "M1]

WATCH "E5

MSTOP "M1

END

TO DROP

MCW "M3

MSTOP "M3

END





Kitabı, 6-13

252

TO TAKE

MCCW "M3

END

TO DOWN


MCW "M2

WATCH "E2

MSTOP "M2

END

TO UP


MCCW "M2

WATCH "E1

MSTOP "M2

END

7. CONCLUSION

Robots are an important parts of industry in our world today. They

play important roles for a rapidly development of a country. Choosing the

type of a robot which will be used by teaching and learning as a cognitive

tools at a university is also important. Robot should be flexible for basic

concept acquisition, to keep contact between reality and the approach of

basic modeling and to train students in inductive approaches to make them

imaginative.





Kitabı, 6-13

253

REFERENSES

[1] Delannoy, P.: Technical Guidelines For Activities Based On LOGO,

Med-Campus Program, Cog-tech. 94

[2] Manipulator Assembling Handbook, LIUM, Loboatoire

d‘Informatique, Université du Maine, B.P. 535 - 72017 LE MANs

[3] Delenoy P., Martial V.; Specifications for Cubsort, A Sorting

Machine For Cubes, Cognitive TECHnologies for Education, Med

Campus, 1994

[4] Vivet, M.; WHICH Goals and WHICH Pedagogical Attitudes

Should one use with Micro-Robots in a Classroom, Med-Campus

Program; 1-13 August 1994, Side





Kitabı, 6-13

254

KuĢ, M.; Varol, A.; Oğurol, Y.; Varol, Y.: ―Verarbeitung von unsiherem Wissen mit

Fuzzy-Prolog‖, Second Turkish-German Joint Computer Application Days, 15-16

October, 1998, Konya, Proceedings, pp. 243-260

255

2.6. VERARBEITUNG VON UNSICHEREM WISSEN MIT FUZZY-

PROLOG

Zusammenfassung

Die Komplexität unserer Umwelt mit ihren zahlreich vemetzen

Subsystemen verlangt für ihre adäquate Beschreibung einen

interdisziplinären, integrierten Ansatz. Die Informatik stellt hierzu

unterschiedlichste Methoden und Werkzeuge der Wissensverarbeitung zur

Verfügung. Diese Komplexität resultiert vor allem aus der Dominanz von

unsicherem Wissen in der Umwelt. Klassische Methoden der

Wissensrepräsentation und-verarbeitung ermöglichen bisher nicht den

adäquaten Umgang mit unsicherem Wissen. Es existiert aber die

Notwendigkeit, dieses problematische Wissen mit Hilfe von KI-Methoden

angemessen zu beschreiben, um die Komplexität der entsprechenden

Domäne zu vereinfachen und damit das jeweilige Anwendungsgebiet besser

beherrschen zu können

Die Programmiersprache Prolog (Programming in Logic) zählt zu

den zentralen Sprachen auf dem Gebiet der Wissensrepräsentation und -

Verarbeitung. Daher liegt es sehr nahe, diese Sprache als Grundlage für die

Erweiterung um Konstrukte zur Verarbeitung von unsicherem Wissen zu

verwenden. Prolog basiert auf dem Prädikatenkalkül der ersten Stufe und

arbeitet auf HÖRN-Klauseln. In dieser Arbeit wurde ein Kalkül basierend

auf der Kombination der Fuzzy-Set- und der Plausibilitätstheorie verwendet.

Nach unseren Erfahrungen läßt sich feststellen, daß diese Kombination eine

gute Lösung zur Repräsentation und -Verarbeitung von unsicherem Wissen

ist.

Einführung




256

Es existieren eine Reihe von Methoden und Mechanismen zur

Formalisienmg und Repräsentation von Wissen, wie z.B. Prädikatenlogik,

Objekte/Frames, semantische Netze etc. Die für die Verarbeitung des

Wissens notwendige Softwarekomponente, die sogenannte

Inferenzmaschine, ist ein Steuerprogramm, das nach einer geeigneten

Strategie und gegebenenfalls unter Verwendung von Metawissen aus den

bereits in der Wissensbasis gespeicherten Daten, sowie im Dialog oder

anderswie erhobenen Falldaten möglichst gezielt Schlußfolgerungen

"produziert" [1]. Wissensrepräsentationsformalismen können, verbunden

mit ihren Ableitungsstrategien, als Kalküle aufgefaßt werden. Eine

Inferenzmaschine sollte daher ein korrektes und vollständiges Kalkül

implementieren, das theoretisch fundiert ist.

Ein solches Kalkül stellt z.B. die Prädikatenlogik erster Ordnung

dar. Sie ist eine theoretisch fundierte Wissensrepräsentation [2], Auf ihr

basieren eine Reihe von Programmiersprachen, deren bekanntester Vertreter

Prolog ist [3, 4]. Prolog selbst ist ein mächtiges Werkzeug zur

Wissensverarbeitung, welches sich auf Hornklauseln - eine Untermenge der

Prädikatenlogik erster Ordnungstützt. Ein Prolog-System arbeitet die

Anfragen zielorientiert ab, d.h. ausgehend von einer Anfrage wird in der

Regelbasis nach gespeichertem Wissen gesucht, welches diese Anfrage

bestätigt.

Häufig können Fakten und Regeln in einem Wissensbereich nur

"unscharf angegeben werden. Die adäquate Verarbeitung dieses Wissens

erfordert die Entwicklung neuer Konzepte. Die Methoden der unsicheren

Wissens Verarbeitung ermöglichen einen Umgang mit diesen "unscharfen"

Fakten und Regeln. Es stellt sich die Frage, wie man derartige

Unsicherheiten modelliert und wie man deren Verarbeitung, z.B. in ein

Prolog-System integriert. Die Modellierung und Verarbeitung unsicheren




257

Wissens erfordert aufgrund deren Komplexität eine formale mathematische

Vorgehensweise. Das in dieser Arbeit verwendete Kalkül basiert auf einer

Kombination der Fuzzy-Set-und Plausibilitätstheorie (Dempster-Shafer-

Theorie) [5, 6,7].

Wesentliches Verarbeitungsprinzip eines Prolog-Systems ist die

Unifikation, die in dieser Arbeit zur Verarbeitung von unsicherem Wissen

erweitert werden muß [8]. Die klassische Unifikation ist ein rein

syntaktisches Verfahren, das versucht, Terme (syntaktische Einheiten) durch

die Ersetzung von Variablen identisch zu machen. Die Ergänzung der

klassischen Unifikation um eine semantische Unifikation ist ein möglicher

Schritt bei der Erweiterung eines Prolog-Systems, um unsicheres Wissen

verarbeiten zu können [9]. Die semantische Unifikation bezeichnet dabei

den Vorgang, Terme mit ähnlicher Bedeutung (Semantik) zu unifizieren.

Die Zuordnung von Wertintervallen zu Fakten und Regeln bietet

dabei eine Möglichkeit zur Beschreibung von Unsicherheiten in

regelbasierten Systemen. Diese Wertintervalle können als ein Maß für die

Unsicherheit interpretiert werden, wobei die untere Grenze des Intervalls ein

notwendiges Kriterium und die obere Grenze ein mögliches Kriterium für

die Erfüllbarkeit darstellt [10].

Konzept

Um unsichere Regeln und Fakten modellieren zu können, muß die

klassische Sprache Prolog entsprechend erweitert werden. Es stellt sich

zwangsläufig die Frage, in welcher Form und Struktur sich die Erweiterung

der Sprache realisieren läßt, d.h. welche Theorien hierzu herangezogen

werden können. Aus den unterschiedlichsten Ansätzen der unsicheren

Wissens-verarbeitung und -modellienzng wurden Ideen aus der Fuzzy-Set-

Theorie und der Plausibilitätstheorie {Evidenztheorie) aufgegriffen. Hierbei

liefert die Fuzzy-Set-Theorie die Idee der linguistischen Variablen zur




258

Modellierung von linguistischen Unschärfen, welche sich in der

menschlichen Sprache stark widerspiegelt. Beispiele hierzu sind

Formulierungen der Art "hohe Emissions- werte", "schmutzige Gewässer"

oder "starke ÜV-Imissionen".

Wissen wird in den regelbasierten Sprachen durch Wenn ... Dann ...

Regeln formuliert. Die klassische Logik liefert nicht die Möglichkeit, einer

Implikationen einen Grad der Gewichtung, z.B. durch ein Wertintervall,

anzufügen. Betrachtet man z.B. folgendes logisches Programm;

Wertet man das obige Beispiel nach der klassischen Logik aus, hat

eine Person X die Krankheit Malaria, wenn Person X in Indien ist, Fieber

und Schüttelfrost hat. Ein Grad der Gewichtung ist hierbei nicht möglich.

Betrachtet man nun aber das folgende logische Programm in Form einer

Implikation, an der ein Grad an Gewichtung angelügt ist:




259

Wertet man diese Implikation mit einem Grad an Gewichtung, in

Form eines logischen Programms aus, würde man folgende Interpretation

erhalten: Die Person X hat zu 60%-80% die Krankheit Malaria, wenn X in

Indien ist, Fieber und Schüttelfrost hat.

Interpretiert man das Beispiel ohne Gewichtung, hat Person X zu

700% Malaria, wenn die JPrämissen der Implikation erfüllt sind. Im

letztgenannten Beispiel dagegen, hat X zu 60^>-80% Malaria, wenn die

Prämissen erfüllt sind. Sie kann aber auch zu 20%-40% eine andere

Krankheit, z.B. eine Erkaltung, haben. Das Ergebnis ist also mit einer

gewissen Unsicherheit behaftet, was für den zu modellierenden Sachverhalt

angemessener erscheint.

Um diesen Grad der Gewichtung realisieren zu können, wird ein

Konzept aus der Plausibilitätstheorie aufgegriffen. Das bietet die

Möglichkeit, Regeln und Fakten durch ein Wertintervall zu gewichten. Die

Ideen der Fuzzy-Set Theorie und Evidenztheorie lassen sich verknüpfen,

weil die Possibilitätsmaßespezielle Plausibilitätsmaße sind und Fuzzy-

Mengen als Possibiütäten interpretiert werden können. Um die Ideen der

linguistischen Variablen und Wertintervalle einzubeziehen, um unsicheres

Wissen repräsentieren und verarbeiten zu können, wird zunächst ein Kalkül




260

aufgestellt werden, welches diese Ideen aufgreift. Dieses Kalkül wird im

folgendem als Support-Logik- Kalkül und die Wertintervalle als Support-

Intervalle bezeichnet. Das Support- Logik-Kalkül basiert also auf den Ideen

der Fuzzy-Set Theorie und der Evidenz-Theorie (Abb. l) [9].

Im unserem Fuzzy-Prolog sollen diskrete und kontinuierliche Fuzzy-

Mengen erlaubt sein. Diskrete Fuzzy-Mengen lassen sich durch eine

Aufzählung der Singletons beschreiben. Kontinuierliche Puzzy-Mengen

werden auch durch diskrete Fuzzy-Mengen beschrieben, die jedoch linear

interpoliert

werden. Bei der Deklaration muß der Name der Fuzzy-Menge (bzw. des

Fuzzy-Terms) und der Name der zugehörigen Gründmenge (bzw.

Linguistische Variable) mit angegeben werden.

Beispiel:

Deklaration von. .zwei kontinuierlichen Fuzzy-Mengen (durch

einSystemprädikat):

Fuzzy_set(durchschnitt,körpergröße # [0:160, l: 170, l:

180,0:190]).

füzzy_set(groß, k0rpergr0ße# [0:180,1:190, 0:200]) (Abb. 2).




261

Deklaration einer diskreten Fuzzy-Menge (durch ein

Systemprädikat):

fuzzy_set(warni,temperatur : [0.5:21, 0,75:22, 1:23. 0.75:24,

0.5:25]) (Abb. 3).




262

Diskrete Fuzzy-Mengen verwendet man in da" Regel, wenn

Zwischenwerte nicht erfaßt werden können oder nicht existieren. Aus einer

kontinuierlichen Fuzzy-Menge kann eine diskrete Fuzzy-Menge durch

Diskretisierung der Grundmenge gewonnen werden oder umgekehrt durch

Inter polation von Zwischenwerten in eine kontinuierliche Fuzzy-Menge

verwandelt

werden.

Die Einführung von Puzzy-Mengen in Prolog macht es notwendig,

die klassische Unifikation zu erweitern. Diese Erweiterung zur semantischen

Unifikation ist Bestandteil des Support-Logik-Kalküls. Fakten und Regeln

sollen in Prolog durch Support-Intervalle gewichtet werden. Hierzu wird die

Syntax der Sprache Prolog um Support-Intervalle erweitert. Sind Fakten und

Regeln ohne Support-Intervall angegeben, wird ihnen automatisch das

Einheitsintervall [1,1] zugeordnet.

Support Logik Kalkül

Die Gewichtung von Regeln und Fakten im Fuzzy-Prolog erfolgt

durch sogenannte Support-Intervalle. Ein Support-Intervall besitzt die Form

['Nee, Pos], wobei der erste Wert des Intervalls (Nee) den notwendigen

Support (engl. necessity) und der zweite Wert (Pos) den möglichen Support

(engl. possibility) für die Auswahl einer Hornklausel angibt. Jede Klausel

wird also mit einem Support-Intervall belegt und erhält dadurch eine

Gewichtung. Die Syntax der gewichteten Hornklausel ist wie folgt definiert:

Ist eine Klausel ohne Support-Intervall angegeben, so wird sie

automatisch mit dem Intervall [1,1] belegt. L0 ist der Kopf (engl. head) und

L1, ... ,Lk der Rumpf (engl. body) der gewichteten Hornklausel. Einer

gewichteten Hornklauseln läßt sich folgende prozedurale Semantik

zuordnen ([Bald86]); Sind die Prämissen L1, ... ,Lk erfüllt, so ist die

Konklusion lq mit dem Grad Nee und -lq mit dem Grad (1-Pos) erfüllt.




263

Die Supports müssen jeweils die folgende Bedingung erfüllen: Nec

+ (l -Pos)≤.l

Ist der Rumpf einer gewichteten Hornklausel leer, so ist die Syntax

der Form: L0 $[Nec, Pos]

Der Fakt lq ist mit dem Grad Nee und die Negation — L0 mit dem

Grad (1-Pos) erfüllt, für jede beliebige Variableninstanziierung.

Bei den Support-Intervallen handelt es sich nietet um

Wahrscheinlichkeitsmaße im Sinne der klassischen

Wahrscheinlichkeitstheorie, sondern das Support-Intervall beschreibt die

Grenzen, in dem die unbekannte "Wahrscheinlichkeit" liegt. Ein Support-

Intervall von [0,1] beschreibt die totale Unsicherheit bzw. Unwissenheit

über eine Aussage.

Die Verrechnung der Support-Intervalle erfolgt durch die Definition

von kontextsensitiven Operatoren. Diese Operatoren entsprechen Fuzzy-

Operatoren, die um Support-Intervalle erweitert sind. Die Modellierung der

Operatoren ist im Kalkül nicht fest vorgegeben. In dieser Arbeit wird das

Multiplikations-Modell [11] zur Beschreibung der Negation-, Konjunktion,

Diskjunktion und Inferenzoperatoren verwendet, daß mit der Dempster-

Shafer-Theorie konform ist. Ein Alternatives Modell ist z.B. die

Beschreibung durch die klassischen Min-Max-Operatoren der Fuzzy-Set-

Theorie.

Fuzzy-Mengen

Eine Gewichtung von Regeln und Fakten mit Support-Intervallen

reicht nicht aus, um linguistische Unschärfe zu modellieren. Die

Repräsentation von Fuzzy-Mengen ist daher sinnvoll. Fuzzy-Mengen stellen

ähnlich wie Konstanten atomare Objekte dar und müssen vor der ersten

Benutzung definiert werden. Für die Definition der Fuzzy-Menge, müssen

der Name des Terms, der Name der zugehörigen Grundmenge (entspricht




264

der linguistischen Variablen) und die Fuzzy-Menge in Form einer Liste

angegeben werden.

Beispiel:

Eine Fuzzy-Menge warm. die auf der Domäne Temperatur definiert

ist, wird z.B. durch ein Prädikat fuzzy_set definiert. Die Liste beinhaltet

Singeltons, die linear interpoliert werden können.

füzzy_set(warm, temperatur # [.... ]).

Zwei Arten von Fuzzy-Mengen werden im Support-Logik-Kalkül

zugelassen. Die erste Form erlaubt die Verweildung diskreter, unscharfer

Mengen und die zweite Form erlaubt die Verwendung linear interpolierter,

diskreter, unscharfer Mengen, die wie folgt definiert sind:

Definition: Diskrete‘Fuzzy-Menge im Support-Logik-Kalkül

Eine endliche diskrete Fuzzy-Menge ist im Support-Logik-Kalkül

ein 3- Tupel (T,M,FS), wobei T der Name der Fuzzy-Menge, M der Name

der Grundmenge G und FS eine endliche Fuzzy-Menge auf G ist. Die

endliche Fuzzy-Menge erhält die Beschreibungsform FS

:= {x/µ(x) l x G}. µ(x) ist ein Wert aus dem Intervall [0,1].

Definition: Kontinuierliche Fuzzy-Menge im Support-Logik-Kalkül

Eine kontinuierliche Fuzzy-Menge wird im Support-Logik-Kalkül ist eine

diskrete Fuzzy-Menge mit linear interpolierten Elementen

Im Rahmen des Support-Logik-Kalküls werden nur Fuzzy-Mengen

zugelassen, welche die Normalisiertheitseigenschaft besitzen. Eine

Einführung von Fuzzy-Mengen beeinflußt die klassische (syntaktische)




265

Unifikation. Die Erweiterung der klassischen Unifikation .zur semantischen

Unifikation ist Gegenstand des nächsten Abschnitts.

Erweiterte Unifikation

Eine Erweiterung der logischen Programmiersprache Prolog um

Fuzzy-Konzepte erfordert eine angemessene Modifizierung der klassischen

Unifika- tionsoperation. Die rein auf der syntaktischen Ebene arbeitende

Opera-tion wird um eine semantische Ebene erweitert. Die semantische

Unifikation liefert, zusätzlich zur Substitutionsmenge, ein Support-Intervall

als Ergebnis. Das Sup- port-Intervall beschreibt den Grad der Ähnlichkeit

der zu unifizierenden Terme.

Beispiel:

Gebeben sei ein kleines Prolog-Programm mit einem einzigen Fakt

p(ca„25°C). Eine Anfrage der Form ?- p(warm) würde im klassischen

Prolog fehlschlagen, obwohl die Terme eine ähnliche Bedeutung besitzen

können. Sind die Terme ca_250C und warm Beispielsweise als Fuzzy-

Mengen über einer gleichen Grundmenge definiert, so läßt sich die Anfrage,

aufgrund der sematischen Unifikation in einem Fuzzy-Prolog-System,

reduzieren.

Fuzzy -Patter n-Matching

Die klassische Unifikation läßt sich als einfaches Pattern-Matching,

verknüpft mit Variablenbindungen, auffassen. Unabhängig von der

Bedeutung der zu unifizierenden Terme wird der Test auf Gleichheit rein

syntaktisch durchgeführt. Die Unifikation schlägt fehl, falls sich die beiden

Terme nicht durch mögliche Variablenbindungen entsprechen. Symbol für

Symbol werden zwei Tßrrne verglichen und durch eventuelle

Variablenbindung identisch gemacht [12].

Die beiden Ausdrücke "warm" und "ca_25°C" beschreiben z.B. die

Temperatur in einem Raum. Ein rein syntaktischer Vergleich wurde




266

fehlschlagen, obwohl beide Ausdrücke eine ähnliche Bedeutung besitzen.

An dieser Stelle setzt das Konzept der partiellen Übereinstimmung (Fuzzy-

Pattem-Matching) an. Die linguistischen Unschärfen lassen sich in der

Fuzzy-Set-Theorie durch Fuzzy-Mengen charakterisieren und auch als

Possibilitäts- funktionen interpretieren.

Gegeben sei ein atomares unscharfes Konzept P, dargestellt durch

eine Possibilitätsfunktion. Für das unscharfe Konzept "warm" bedeutet dies

z.B. die Möglichkeit, daß die Raumtemperatur Werte zwischen 18°C und

26°C annehmen kann (Abb. 4).

Ist P als Datum gegeben, und soll es mit einem ähnlichen Konzept D

als Muster verglichen werden, z.B. dem Konzept "ca_25°C", so will man

wissen, zu welchem Grad es möglich ist, daß ein Raum mit einer

Temperatur von "ca_25°C", Werte annehmen kann, die durch die

Temperaturen "warm" beschrieben sind. Des größtmögliche Wert ist das

Möglichkeitsmaß, gegeben

durch m(P\D). Dieses optimistische Maß bildet die obere Schranke der

Übereinstimmung der beiden Konzepte.

Definition: (P\D)




267

Sind Wp und ###^) Zugehörigkeitsfunktionen über ### für P

und D, so berechnet sich dieses Maß durch ([13]):

)).(###),(##min(#sup(### xDxpPIDx

Die Notwendigkeit .ßder auch Sicherheit, mit der Werte, die dem

gegebenen Konzept D entsprechen, dem zum testenden Konzept P

angehören, wird durch folgende Definition bestimmt.

Definition: N(PID)

Sind ###p und ###D Zugetlörigkeitsfimlitionen. über ### für P und

D, so berechnet sich dieses Maß durch ([13]);

N(P\D) =1- ###('###PID)

Hier wird die Möglichkeit betrachtet, daß P nicht eintritt, wenn D

gegeben ist. Möglichkeit und Notwendigkeit verhalten sich nach dieser

Definition dual zueinander. Dies bedeutet, daß sich die Notwendigkeit eines

Ereignisses aus der Unmöglichkeit des komplementären Ereignisses

bestimmen läßt. N(P\D) betrachtet also die Schnittmenge -P D [12].

Beispiel: Die Berechnung der Übereinstimmung der in der Abb. 4

beschriebenen Konzepte wird durch die Abb. 5 veranschaulicht.

Π(warm\ca.25°C) 0,57 und




268

N(warmi\ca.25°C) = l- (nicht warm\ca.25°C) =1 - 0,86 == 0,14

Das Ergebnis wird in Form eines Support-Intervalls [0.14, 0.57]

notiert. )ieses Support-Intervall wird in [14] als possibilistic support pair

bezeichnet. -olgende Eigenschaften sind bei diesen Maßen festzustellen

[12].

### Sind P und D scharfe Konzepte, gilt N(P,D) = l ### P ### D,

d.h. die Bedeutung von D ist in der Bedeutung von P enthalten

### Ist D ein scharfer Wert x0 und soll die Übereinstimmung eines

unscharfen Wertes P zu x0 bestimmt werden, gilt ###m(p\x0) = N(P\x0) =

### P(x)

###Im umgekehrten Fall gilt m(x0\P) = ###p(x) und N(x0\x0) = 0

Es gilt das Sicherheitsmaß ###(P\D) =###(D\P)

### Für das Notwendigkeitsmaß gilt N(P\D) ### N(D\P), weil

N(D\P) ein Maß für P ### D ist und im allgemeinen ###P ###D ###

###D###P gilt.




269

### Während ein scharfes Konzept A mit sich selbst stets zu 100%

Übereinstimmt, gilt dies im unscharfen Fall nicht vollständig. Zwar gilt ###

(A\A) = l aber N(A\A) ### 0.5. Hier wird oftmals vergessen, daß A aur

unscharf ist und der genaue Wert, den A annimmt, nicht vollständig bekannt

ist. Diese Unsicherheit muß beim pessimistischen Vergleich mit

berücksichtigt werden. Fordert man N(A\A) = l, so gilt 1- ###(###AIA) = 1,

also ###A ### A == ###. Dies gilt nur für scharfe Konzepte.

### Esgilt###(P\D),)###N(P\D).

Erweiterter Resolutionsprozeß

Die semantische Unifikation liefert als Ergebnis einer erfolgreichen

Unifikationen eine Substitution und einen Support-Intervall. Die Grundidee

der erweiterten Resolution liegt darin, die klassische SLD-Resolution um

entsprechende Konzepte zu erweitern.

Die Verarbeitung eines füzzy-logischen Programms läßt sich in 4

Schritten beschreiben:

1. Berechne eine Ableitung für ein Ziel ohne Berücksichtigung

der Support-Intervalle analog zur SLD-Ableitung.

2. Berechne das Ergebnis für die erfolgreiche Ableitung durch

Berücksichtigung der Support-Intervalle

3. Wiederhole Schritt l und 2 für alle möglichen

Ableitungspfade;.

4. Bewerte bzw.' kombiniere die Ergebnisse aus den

unterschiedlichen Ableitungspfaden nach einer bestimmten

Methode, die weiter unten beschrieben wird.




270

Die 'Bewertung bzw. Kombination aus unterschiedlichen

Ableitungspfaden kann nach unterschiedlichen Methoden realisiert werden,

wie z.B. die allgemeine Zuweisungsmethode (general assignment method)

nach [11], Max-Support-Intervall Methode nach [12] oder die modifizierte

Dempster- Shafer Kombinationsmethode [141. Die Wahl der Methoden ist

vom Anwendungsgebiet abhängig und ist daher nicht Bestandteil des

Kalküls.

Schlußbemerkung

Die semantische Unifikation ist ein mögliches Verfahren zur

integration von Fuzzy-Mengen in ein Prolog-System. Ein Nachteil der

semantischen Unifikation ist aber ihre Nichtkommutativität. Es gilt in der

Regel:

[ ( / ), ( / )] [ ( / ), ( / )]u uP D N P D P D N D P D P P D

Der Beweis der Nichtkommutativität ist durch ein (Gegen-) Beispiel

erbracht. Die semantische Unifikation der Fuzzy-Terme "warm" und

"ca_25°C" liefert einen Support-Intervall von [0.14, 0.57], hingegen die

Unifikation von "ca_25°C" mit "warm" einen Support-Intervall von [0,

0.57] als Ergebnis hat. Die Nichtkommutativität der semantischen

Unifikation bedeutet, daß der semantische Unifikator nicht eindeutig ist. Die

Beweisführung in der SLD-Resolution ist gerichtet, d.h. es wird immer

versucht ein Ziel mit einer Programmklausel zu reduzieren. Daher kann die

Eigenschaft der Kommutativität in einem Prolog-System vernächläßigt

werden. Die Nichtkommutativität muß bei der Entwicklung von

Applikationen berücksic-htigt werden.

Um eine Strategie zur Verarbeitung von gewichteten Klauseln

anzugeben, ist die Modifizierung der SLD-Resolution eine Möglichkeit. Die

Entscheidung die SLD-Resolution zu modifizieren beruht darauf, daß diese




271

Strategie in den meisten Prolog-Systemen implementiert ist. Weiterhin

können zwei heterogene Suchstrategien im selben Prolog-System zu

Problemen rühren. Beim Support-Logik-Kalkül müssen alle Lösungen einer

Anfrage (mittels der SLD-Ableitung) gefunden und in einer geordneten

Weise ausgegeben werden. Ein Problem ergibt sich im Falle von unendlich

vielen Ergebnissen oder unendlich langen Ableitungen, bei denen die

Inferenzmaschine nicht terminiert.

Literaturverzeichnis

[1] N.H.C. Thuy, P. Schnupp. Wissensverarbeitung und Experten-Systeme. R,

Oldenbourg Verlag. München, 1989

[2] F. Puppe. Einführung in Expertensysteme. Springer- Verlag. 2.Aufl. Berlin.

1991

[3] A. Colmerauer, et. al. Ün Systeme de Communication Homme-Machi'ne en

Franfais. Research Report, üniversite Aix-Marseille, 1973

[4] R. Kowalski. Predicate logic äs programming language. Information

Processing. Seite 569-574. North-Holland, 1974

[5] L. A. Zadeh. Fuzzy Sets. Information and Control, 8, Seite 338-353. 1965

[6} A. Dempster. Upper änd lower probabilities induced by a multivalued

mapping. Ann. Math. Stat, 38, Seite 325-339. 1967

[7] G. Shafer. A mathematical theory ofevidence. Princeton University Pess.

Princeton, 1976

[8] J.A. Robinson. A machine-oriented logic based on the resolution principle.

Journal ofthe ACM, 12(1). Seite 23-41. 1965




272

[9] J.F. Baldwin. A new approach to approximate reasoning using ßizzy logic.

Fuzzy Sets and Sytems, 2. Seite 193-219. Bristol, 1979

[10] D, Dubois, H.Prade. Possibility Theory. An Approach to Computerized

Processing of Üncertainty. Plenum Press.New York, 1988

[11] J.F. Baldwin. Support Logic Programming. In: AJones, etal., (Eds.)> Fuzzy

Sets Theory and Applications. Reidel Dordrecht. Boston, 1986

[12] C, Geiger. ConFuP- Concept of a parallel logic programming language

withßizzy semantics. Diploma thesis. University of Paderborn, 1993

[13] M. Cayrol, H. Farreny, H. Prade. Fuzzy Pattern Matching. In:emetes, Vol 11.

Seite 103-166. Thaies Publicaüons Ltd. 1982

OĞUROL, Y.; VAROL, A.; KUġ, M.: Anforderungen und Lösungsansätze einer

transferierbaren Entwicklungsumgebung für die medizinische Wissenverarbeitung,

Second Turkish-German Joint Computer Application Days, 15-16 October, 1998,

Konya, Proceedings, pp. 231-242

273

2.7. ANFORDERUNGEN UND LÖSUNGSANSÄTZE EINER

TRANSFERIERBAREN ENTWICKLUNGSUMGEBUNG FÜR DIE

MEDIZINISCHE WISSENSVERARBEITUNG

Yıldıray Oğurol*, Asaf Varol**, Mehmet KuĢ*

* Wissenschafliche Mitarbeiter an der Uni. Bremen, Deutschland

** Gastprofessor an der Uni. Bremen, Deutschland

Zusammenfassung

Wissensbasierte Systeme in der Medizin erfüllen in vielen

Bereichen nicht die mit ihnen verbundenen Erwartungen. Ziel ist es daher

die Entwicklung eines transferierbaren, wissensbasierten Multi-Agenten-

Systems, das die erwähnten Mängel minimiert bzw. gänzlich beseitigt.

Hierbei werden - angewandt auf die Domäne Medizin - nach Analyse der

verschiedenen Teilbereiche und deren fundamentalen Anforderungen aus

Sicht der Informatik vier voneinander unabhängige Problemklassen

differenziert:

1. Datenerfassung (Sensorik)

2. Datenverwaltung (Datenbankmanagement)

3. Dateninterpretation (Inferenz)

4. Datenpräsentation (Präsentation)

Die einzelnen Agenten (Inferenz, Datenbank, Präsentation, Sensor),

die jeweils eine Teilaufgabe aus einer Problemklasse lösen, können beliebig

kombiniert und sogar zur Laufzeit hinzugefügt bzw. ausgetauscht werden.

Die Kobination der Agenten entscheidet über die Funktionalität des

resultierenden Multi-Agenten-Systems. Sie kommunizieren über einen

zentralen Kommunikations-Koordinator (Center), wodurch eine

Unabhängigkeit untereinander gewährleistet wird. Zur Kooperation mit





274

anderen Experten bzw. Agenten und Koordination ihrer Aktivitäten wird

eine Sprache verwendet, die allen Agenten syntaktisch und semantisch

bekannt ist. Dadurch sind die Agenten in der Lage, Probleme vom Umfang

und Art zu lösen, die ein einzelner nur mit erheblichen Aufwand hätte

angehen können. Die flexible Gestaltung des resultierenden Systems erlaubt

u.a. die Integration mehrerer Wissensbasen, sowie unterschiedlicher

Inferenzsysteme. Damit ist eine Transferierbarkeit auf andere medizinische

Fachgebiete gegeben und aus Sicht der Systemarchitektur sogar eine

Transferierbarkeit auf andere Domänen möglich.

Einleitung

Die Komplexität und der Umfang medizinischen Wissens haben in

den letzten Jahren ständig zugenommen. Zur Gewährleistung einer qualitativ

hochwertigen Versorgung ist die Verfügbarkeit aktuellen medizinischen

Wissens auf allen Ebenen des medizinischen Versorgungsprozesses von

essentieller Bedeutung. Wissensbasierte Systeme besitzen das Potential

einen wesentlichen Beitrag zur Lösung dieser Probleme zu leisten. Die

Nutzung solcher Systeme ist in einigen Bereichen der Medizin schon fest

etabliert (z.B. Analyse von EKG-Untersuchungen, klinische Labors, ...).

In vielen Bereichen hingegen werden die mit wissensbasierten

Systemen verbundenen Erwartungen nicht erfüllt. Hierfür können nach der

jüngsten Studie [1] im wesentlichen vier Faktoren verantwortlich gemacht

werden:

die Nicht-Berücksichtigung der spezifischen Anforderungen des

jeweiligen medizinischen Einsatzgebietes,





275

die mit der Entwicklung wissensbasierter Systeme verbundenen

hohen Kosten,

eine fehlende Standardisierung und der damit verbundenen

Entwicklung proprietärer Lösungen und

die mangelnde Integration unterschiedlicher Methoden und

Modelle der Wissensverarbeitung, die teilweise

anwendungsabhängige Problemlösungsstärken aufweisen.

Anforderungen

Die Komplexität und der Umfang der Domäne Medizin mit ihren

zahlreichen multidisziplinären Gruppenaktivitäten bedingen

interdisziplinäre, integrierte Lösungsansätze. Mit klassischen

Lösungsansätzen wird vielfach versucht jeweils einen Teilbereich der

Domäne Medizin adäquat abzubilden. Ein Beispiel hierfür ist das System

Pro.M.D. [2], das durch die Darstellung der etablierten Strategien in

Wissensbasen und durch ihre automatisierte Anwendung vor allem in der

labormedizinischen Spezialbefund sowohl die Entscheidungen in der

präanalytischen Phase als auch die Befundinterpretation wesentlich

unterstützt [4]. Für eine umfassende Anwendung stellt die Domäne Medizin

eine Anzahl von Anforderungen, denen solche Systeme jedoch nicht ganz

gerecht werden. Bei der Mensch-Maschine-Interaktion müssen die

unterschiedlichen Bedürfnisse einer breiten Gruppe von Endanwendern mit

z.T. unterschiedlichen Rollen (Ärzte, Pflegepersonal,

Krankenhausadministration, ...) in adäquater Weise berücksichtigt werden.

Die Unterstützung medizinischer Standards für den Datenaustausch

sowie die automatische Datenakquisition – eine der Hauptanforderungen zur

Integration wissensbasierter Systeme in das medizinische DV-Umfeld –

werden häufig nicht unterstützt. Die Systeme sind oft als „Einplatzsysteme―

konzipiert, an die lediglich ein Anwender zugleich arbeiten kann. Das





276

entspricht aber nicht der Arbeitsweise des medizinischen Umfelds, in dem

Teamarbeit die Regel ist. Informationsaustausch zwischen Ärzten,

Pflegepersonal und anderem medizinischen Personal, sowie geteilte

Verantwortung, kooperative Beiträge für gemeinsame Entscheidungen sind

die Basis in der Praxis der Domäne Medizin. Dieses spiegelt sich in den

heutigen Systemen nicht in adäquater Weise wider. Eine Umsetzung der

CSCW-Philosophie (computer-supported co-operative work - CSCW) ist

daher zwingend notwendig und bedarf einer radikalen konzeptuellen

Umstellung in der Softwareentwicklung.

Abbildung -1: Einplatzsysteme vs. CSCW

Zum anderen lassen sich die Mehrzahl der erfolgreichen

Anwendungen als „flach― charakterisieren, d.h. statt Tiefenwissen, wie z.B.

modellbasiertes Wissen, nutzen sie eher einfache Arten von Wissen. Der

Vorteil liegt weniger in der Lösung prinzipiell schwieriger Aufgaben,

sondern in der Bewältigung der Komplexität, die aus dem Umgang mit

großen Wissensmengen resultiert. Hypertext- bzw. hypermedia-ähnliche

Verfahren, die sich für Schulungszwecke bestens bewährt haben, bieten





277

viele Möglichkeiten, das Wissen zu organisieren und mittels z.B.

hierarchischer Querverweise darin zu blättern. Die Wissensrepräsentation

sollte daher zumindest Hypertextfunktionen unterstützen, um so die

Kombination von beispielsweise regelbasierten und hypertextbasierten

Systemen — eine Art Hyper-Inferenz-System — zu ermöglichen (Vgl.

[3]). Im Falle regelbasierter Ansätze ist die Wissensnotation möglichst an

die Terminologie des speziellen Gebietes anzupassen, so daß keine

speziellen EDV-Kenntnisse notwendig sind und der Experte das notierte

Wissen selbst wieder versteht. Ferner sollte die Sprache zwecks einer

leichten Erlernbarkeit und Verständlichkeit, soweit es geht, an die

Umgangssprache angelehnt sein.

Ein immer wiederkehrendes Problem ist die Systemintegration. Es

ist in zwischen allgemeine Erfahrung, daß der Aufwand für ein erfolgreiches

wissensbasiertes System nur zu 10 bis 40% im eigentlichen „KI-Anteil―

liegt, während der Rest für konventionelle Aufgaben wie Datenhaltung,

Kommunikation und Benutzerschnittstelle benötigt wird. Die Integration

insbesondere mit Datenbanken spielt auch deshalb eine besondere Rolle,

weil die Konzepte der Wissensrepräsentation in natürlicher Weise als

Erweiterungen von Datenbankkonzepten zu sehen sind. Alle Fragen, die sich

aus der Handhabung großer Datenmengen ergeben, wie Effizienz,

Verteilung, Zugriffskoordinierung, aber auch semantische Aspekte wurden

für Datenbanksysteme schon ausführlich untersucht und teilweise gelöst.

Moderne wissensbasierte Systeme nutzen diese Leistungen von

Datenbanksystemen, statt sie nochmals selbst zu realisieren.

Für den praktischen Erfolg einer Applikation ist die

Benutzeroberfläche mindestens ebenso wichtig, wie die eigentliche

Systemleistung. Dementsprechend gibt es heute kaum noch Systeme, die

sich auf bloßen zeilenorientierten Dialog beschränken, sondern graphische





278

Darstellung und menügesteuerte Eingaben gelten als Standard. Wesentliche

Designprinzipien wie z.B. intuitive Bedienung (WYSIWYG, Ähnliche

Handhabung unterschiedlicher Geräte, ...), Transparenz, individuelle

Anpassung, Fehlertoleranz durch reversible Aktionen, usw. müssen

eingehalten werden.

Nach der oben angesprochenen Studie ergeben sich Probleme bei

der Entwicklung, Praxiseinführung und Wartung wissensbasierter Systeme.

Aufgrund dieser Kenntnisse müssen bei der Konzeption neuer Systeme die

Schwerpunkte darin gelegt werden, die erkannten Defizite und

Schwachstellen bereits durch ein entsprechendes System-Design zu

minimieren. Hierfür müssen jedoch die vielfältigen Anwendungsbereiche

der Domäne Medizin und ihre fundamentalen Anforderungen berücksichtigt

und verstanden werden. Darauf aufbauend kann schließlich eine

transferierbare wissensbasierte Umgebung für den medizinischen Alltag

geschaffen werden. „Transferierbar― bedeutet, die Lösung darf nicht auf

eine spezielle räumlich und zeitlich zugeschnittene Gegebenheit zielen (z.B.

Speziallabors), sondern sie muß auf die wesentlichen Bedingungen im

medizinischen Umfeld adaptierbar konzipiert werden. Die Adaption muß im

Idealfall ohne Programmiereingriffe erfolgen können. Etablierte Standards

müssen berücksichtigt werden, und im Sinne eines maximalen Nutzeffektes

in der täglichen Routine, ist eine vollständige Integration in existierende

medizinische Umgebungen notwendig. Dazu muß eine Schnittstelle zu

mindestens einem Krankenhausinformationssystem realisiert werden. Des

weiteren sollte ein optionales Nebenziel darin bestehen, zwecks

Kooperation, eine Verbindung zwischen verschiedenen wissensbasierten

Systemen zu definieren und ggf. zu schaffen.

Lösungsansatz





279

Die eingeschränkte Fähigkeit, komplexe Systeme zu verstehen und

zu konstruieren, zwingt dazu, diese Komplexität durch Zerlegung und

Abstraktion zu reduzieren. Diese Komplexitätsreduzierung ist nur möglich,

wenn im Rahmen des Gesamtproblems Teilprobleme identifiziert werden

können, deren Lösungen voneinander unabhängig sind, d.h. bei der Lösung

eines Teilproblems muß man sich nicht darum kümmern, wie ein anderes

Teilproblem gelöst wird. Nur wenn dieses Geheimnisprinzip gemäß der

Modularisierung gewährleistet ist, vereinfacht sich die Lösung der gestellten

Aufgabe. Angewandt auf die Domäne Medizin lassen sich nach Analyse der

verschiedenen Teilbereiche und deren fundamentalen Anforderungen aus

Sicht der Informatik vier voneinander unabhängige Problemklassen

identifizieren:

5. Datenerfassung (Sensorik)

6. Datenverwaltung (Datenbankmanagement)

7. Dateninterpretation (Inferenz)

8. Datenpräsentation (Präsentation)

9. Kommunikation

Es liegt nahe die Lösung zu diesen Problemklassen so zu

modularisieren, daß die resultierenden Module teilweise parallel arbeiten

können. Beispielsweise können die von der Datenerfassung ermittelten

Daten gleichzeitig gespeichert, interpretiert und präsentiert werden.

Zwischen den unabhängig arbeitenden Modulen muß zu diesem Zweck ein

Datenaustausch stattfinden, was eine schnelle und sichere Kommunikation

notwendig macht. Das Ergebnis ist ein verteiltes System bestehend aus einer

Menge von Modulen, die durch geeignete Kommunikation ihre Arbeiten

koordinieren und miteinander kooperieren. Die Module lösen jeweils ein

oder mehrere Problem(e) einer der oben genannten Problemklassen.

Erweitert man den Modulbegriff dahingehend, daß ihm

Eigenschaften wie z.B. „intelligent―, „flexibel― und „autonom― zugedacht





280

werden, so ergibt sich der Begriff des „Agenten―. Unter Intelligenz soll hier

die Fähigkeit verstanden werden, flexibel zu reagieren; ein intelligenter

Agent reagiert nicht bloß auf seine Umgebung, sondern benutzt Wissen, um

informierte Entscheidungen für sein Verhalten zu treffen. Jeder Agent kann

Probleme in seinen Domänen lösen und unabhängig arbeiten. Durch

Kooperation sind die Agenten in der Lage, Probleme vom Umfang und Art

zu lösen, die ein einzelner nur mit erheblichen Aufwand hätte angehen

können. Ein Agent ist dann in diesem Sinne eine Software, welche im

Namen und damit im Interesse des Benutzers selbständig Aufträge

bearbeitet. Es arbeitet zeitvariant und kann mentale Zustände annehmen

(wie z.B. Wissen, Absichten, Ziele). Der Benutzer spezifiziert lediglich ein

übergeordnetes Ziel, anstatt explizite Instruktionen zu erteilen. Das „Wie―

und „Wann― wird den Agenten überlassen. Zur Kooperation und

Koordination ihrer Aktivitäten verwenden die Agenten ein einheitliches aber

flexibles Kommunikationsprotokoll, d.h. die Syntax und Semantik des

Protokolls ist jedem Agenten bekannt. Das Ergebnis ist ein Multi-Agenten-

System, bestehend aus einer Menge intelligenter, kooperierender Agenten.

Berücksichtigt man die Forderung nach Unabhängigkeit der Agenten derart,

daß eine zentrale Kommunikationskoordination verwendet wird, so ergibt

sich eine Multi-Agenten-Architektur wie in Abbildung 1-2 dargestellt.





281

Präsen-

tation

Präsen-Präsen-

tationtationDaten-

erfassung

Daten-Daten-

erfassungerfassungDaten-

verwaltung

Daten-Daten-

verwaltungverwaltung

Koor-

dination

Koor-Koor-

dinationdination

Daten-

interpretation

Daten-Daten-

interpretationinterpretation

Abbildung -2: Multi-Agenten-Architektur für medizinische

Wissensverarbeitung

Die Verwendung aller Agentenklassen (die Agenten werden

entsprechend der Problemklassen klassifiziert) ist nicht obligatorisch,

sondern deren Zusammenstellung kann sich je nach Aufgabenstellung

variieren. Durch Kombination verschiedener Agenten lassen sich durch

dieses Konzept unterschiedliche Funktionalitäten realisieren:

Sensor + Präsentation = Konventionelles Monitoringsystem

Sensor + Datenbank = Konventionelles Dokumentationssystem

Sensor + Inferenz = Diagnosesystem

Sensor + Präsentation + Inferenz = Intelligentes

Monitoringsystem

Sensor + Datenbank + Inferenz = Wissensbasierte

Dokumentation

usw.

Um maximale Transferierbarkeit bzw. Flexibilität zu gewährleisten

müssen die Agenten frei konfigurierbar sein (z.B. durch Skriptsprachen).





282

Dadurch ist es möglich, die Agenten ohne Programmiereingriffe an

unterschiedliche medizinische Gegebenheiten zu adaptieren.

Die Möglichkeit mehrere Agenten der selben Problemklasse mit

evtl. unterschiedlichen Problemlösungsmethoden zu verwenden, erlaubt

beispielsweise die Simulation mehrerer kooperierenden medizinischer

Experten mit evtl. unterschiedlichen Fachrichtungen.

Das Nebenziel, nämlich die Schaffung bzw. Definition einer

Verbindung zwischen verschiedenen wissensbasierten Systemen, wird durch

die Möglichkeit der stufenweisen Erweiterung, welches die Flexibilität und

damit die Anwendungsfeldbreite des Konzeptes nochmals erhöht, ebenfalls

erreicht (siehe Abbildung 1-3).

.........

Präsen-

tation

Präsen-Präsen-

tationtationDaten-

erfassung

Daten-Daten-

erfassungerfassung Daten-

verwaltung

Daten-Daten-


Koor-

dination

Koor-Koor-

dinationdination

Daten-

inter-

pretation

Daten-Daten-

inter-inter-

pretationpretation

Präsen-

tation

Präsen-Präsen-

tationtationDaten-

erfassung

Daten-Daten-

erfassungerfassung Daten-

verwaltung

Daten-Daten-


Koor-

dination

Koor-Koor-

dinationdination

Daten-

inter-

pretation

Daten-Daten-

inter-inter-

pretationpretation

KoordinationKoordination

Abbildung -3: Stufenweiser Ausbau





283

Dieses System-Design wurde unter dem Gesichtspunkt der

Transferierbarkeit für die Domäne Medizin entwickelt. Es ergeben sich

dadurch u.a. folgende Vorteile:

die freie Konfiguration der Agenten erlaubt die Adaption des

Systems an die spezifischen Anforderungen des jeweiligen medizinischen

Einsatzgebietes.

die Transferierbarkeit des Systems bzgl. „Raum― und „Zeit―

sichert Investitionen. Da Systemkomponenten (Agenten) stets unabhängig

und damit kooperativ entwickelt werden und sich das System-Design nicht

ändert, können alte und neue Entwicklungen in einer gemeinsamen

Umgebung genutzt werden. Lediglich die Anpassung des Kommunikations-

protokolls ist evtl. notwendig.

ein solches System-Design ist durchaus geeignet Standards für

medizinische Komponenten bzw. Anwendungen zu definieren, wie z.B. ein

standardisiertes Kommunikationsprotokoll für medizinische Komponenten.

das System-Design erlaubt die gleichzeitige und kooperative

Anwendung unterschiedlicher Methoden und Modellen wissensbasierter

Systeme.

Des weiteren ergeben sich die für verteilte Systeme typischen

Vorteile (wie z.B. Fehlertoleranz, Skalierbarkeit und Parallelität) aber auch

Nachteile (wie z.B. die Komplexität oder die Gefahren bei der

Nachrichtenübermittlung).





284

[1] G. Mann, U. Kraut: Studie zur Entwicklung wissensbasierter Systeme

in der Medizin am Beispiel des BMBF-Förderschwerpunktes

MEDWIS. Medis - Institut für Medizinische Informatik und

Systemforschung, GSF-Bericht, 12/95.

[2] C. Trendelenburg, B. Pohl: Pro.M.D. - Medizinische Diagnostik mit

Expertensystemen; eine Einführung mit Disketten für die

Expertensystemschale Pro.M.D. 3. Ausgabe, Stuttgart, Thieme-

Verlag, 1990.

[3] Y. Ogurol: Eine transferierbare Entwicklungsumgebung für

medizinische Wissensverarbeitung, Diplomarbeit, Universität

Bremen, Studiengang Informatik, September 1996.

[4] Ogurol, Y. et al.: WILAS - Ein wissensbasiertes System zur

labormedizinischen Anforderung und Spezialbefundung. Informatik,

Biometrie und Epidemiologie in Medizin und Biologie 29, Heft

1/1998, 3-11, Gustav Fischer Verlag, Verlag Eugen Ulmer Stuttgart,

ISSN 0943-5581

AKPOLAT, Z., H.; GÖBULUT, M.; VAROL, A.: Fuzzy Equivalence of Classical

Controllers, ELECO‘99 International Conference On Electrical and Electronics

Engineering, E01.113/C-20, Proceedings, Electronics, 1-5 December 1999, Bursa,

pp.371-375

285

2.8. FUZZY EQUIVALENCE OF CLASSICAL CONTROLLERS

Z. Hakan Akpolat

Muammer Gökbulut

Asaf Varol

Abstract

This paper concerns the exact equivalence of second order linear

discrete controllers. The equivalence principal automatically produces a

systematic design procedure for the Fuzzy Controllers. The equivalence of the

linear controllers can also be used to implement a nonlinear control behaviour

by piecewise linear approximation. Another merit of the equivalence

principle is that it provides an opportunity to have a fair comparison

between linear and fuzzy controllers.

1. Introduction

Fuzzy logic introduced by Zadeh [1] has found wide applications in

the control of industrial systems. However, the classical linear controllers

(e.g., PI, PID) are still the most widely used controllers in the practical

applications due to their simplicity of design and implementations. This

paper addresses the fact that a Fuzzy Controller (FC) for a given input

universe of discourse can exactly represent linear discrete controllers. It may

be thought that there is no point in implementing a linear control law by a

FC; however, this can be a preliminary step in designing FCs for

deterministic systems with known non-linearity where the desired nonlinear

global behaviour is represented by piecewise linear approximation. In

addition, although there are many successful fuzzy speed and position

control applications, usually these controllers are designed by trial and error

methods [2,3]. The derivation of the fuzzy equivalence of a linear controller

generates an automatic design procedure for the FCs. Further, the




pp.371-375

286

equivalence principle provides a fair comparison between fuzzy and linear

controllers: there are many research papers presenting such performance

comparisons between fuzzy and linear controllers [3-6]. It is reasonable to

assume that to have a fair comparison, the controllers under evaluation

should give exactly or very similar closed loop output responses for same

nominal conditions [4]. Hence, when the parameters of the plant are

changed or an external disturbance is applied, one can easily see which

method gives the more robust control performance. Using the equivalence

principle, the FC under evaluation may be designed to satisfy this

comparison criteria.

2. Fuzzy Equivalence of a Second Order Linear Discrete

Controller

The fuzzy equivalence of a linear discrete PI controller has been

considered by Galichet and Foulloy in [7]. In this paper, the fuzzy

equivalence of a second order linear discrete controller which has a transfer

function

))(1(

))((

)(

)()(

czz

bzazK

ze

zuzG c

c (1)

will be considered. Note that (1) can be easily converted to a PI, PD or PID

controller if the parameters b and c are chosen properly. For example, if c is

set to zero then (1) becomes a representation of a PID controller, if b and c

are set to zero then it becomes a PI controller. If b is set to 1 and c is set to

zero then (1) becomes a representation of a PD controller. Note also that (1)

is originally a PI+lead controller (if c < b) and it can also be converted to a

lead or lag controller if the parameter a is set to 1, and b and c are chosen

according to the desired lead or lag compensation




pp.371-375

287

In the discrete time domain, the output of the controller (1) can be written as

)()1()( kukuku (2)

where

)1()()()1()( 321 kekekekucku (3)

The constants 1, 2 and 3 are given as

abbaKc )(11

abbaK c2 (4)

cabK3

and the operator is defined as

)1()()( kxkxkx (5)

In the following subsections, the fuzzy equivalence of the control

law u(k) given by (2) will be considered; however, the output of the FC will

be u(k) rather than u(k) because, in many practical applications, the

actuating signal u(k) should be limited (to protect the electronic circuits)

with an anti-windup mechanism which stops the integration in the

controller. The anti-windup mechanism can be easily implemented in (2) if

u(k) is chosen as the output of the FC (addition ,or integration, is stopped

when u(k) reaches the saturation limit, i.e., u(k) is not added to the

previous value u(k-1) during the saturation). Note that u(k) is the numerical

integration of u(k) as seen in (2) which can be easily implemented outside

the controller to obtain the actuating signal u(k).

2.1 Sugeno Type Fuzzy Equivalence




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288

In this section, the main purpose is to design a Sugeno type FC that

is precisely equivalent to the controller given by (1). A Sugeno type FC has

a rule-base consisting of the rules in the form of [8]

IF x1 is A1 AND x2 is A2 AND……AND xn is An THEN y =

g(x1,x2,….,xn).

Since the output y is a function of the input variables, any control

law can be directly implemented by choosing the output y as the desired

control law if the membership functions of the input variables are chosen so

that they provide a linear mapping between the inputs and the output of the

controller.

As mentioned in Section 2, the output of the FC will be u(k) and

u(k) will be obtained by using (2). Thus from (3), the inputs to the FC

become u(k-1), e(k), e(k) and e(k-1). In order to keep the FC as simple as

possible and to have a linear mapping, the membership functions for the

input variables are chosen as shown in Fig.1, where vi ,for i = 1 to 4,

represents the input variables u(k-1), e(k), e(k) and e(k-1) respectively. It

should be noted that the input variables are assumed to be bounded and Mi is

the maximum value that the magnitude of the corresponding input variable

can take on. In other words, Mi determines the limits of the universe of

discourse for the corresponding input variable.

The Sugeno type FC will have 24 = 16 rules since there are 4 input

variables and 2 membership functions for each input variable. The rules can

be represented in a general form as

IF u(k-1) is A1m AND e(k) is A2n AND e(k) is A3p AND e(k-1) is

A4q THEN uSU(k) = c u(k-1) + 1e(k) + 2 e(k) + 3 e(k-1)




pp.371-375

289

where the indices {m,n,p,q} = {1,2} and 1, 2 and 3 are given by

(4).

viMi-Mi

Ai21Ai1

Figure 1 Membership functions for the input variables (i = 1,..,4)

Example 1 : Consider the system shown in Fig.2 :

Gh(s)

zoh Plant

Ts = 2.5ms

y(s)e(z)

yref(z)+

-

y(z)

u(z)

Controller

Gc(z) Gp(s)

Figure 2 The control system block diagram

The transfer functions of the plant, zero-order-hold (zoh) and the

controller are given as

)10)(5(

100)(

sssG p (6)

s

esG

sT

h

s1)( (7)




pp.371-375

290

)88.0)(1(

)95.0)(9876.0(2)(

zz

zzzGc (8)

Now the aim is to design a Sugeno type FC that will be precisely

equivalent to Gc(z) and thus give exactly the same closed loop responses as

the system shown in Fig.2.

The input variables are u(k-1), e(k), e(k) and e(k-1). Their

membership functions are chosen as shown in Fig.1, where Mi is selected as

250 for i = 1 to 4 (i.e. for all the input variables). Note that the value of Mi

can be chosen arbitrarily high because, as long as the magnitude of the input

values do not exceed the corresponding Mi, the equivalence between Gc(z)

and the FC will be valid. However, in most of the practical applications, the

reference input and the control signal u(k) are usually limited. Hence, all the

input variables of the controller are bounded due to these limitations.

The number of rules are 24 = 16 (there are 4 input variables and 2

membership functions for each input variable) and the rules can be

represented in a general form as

IF u(k-1) is A1m AND e(k) is A2n AND e(k) is A3p AND e(k-1) is

A4qTHEN uSU(k) = 0.88 u(k-1) + 0.00124e(k) + 1.99876 e(k) +

1.87644 e(k-1) where the indices {m,n,p,q} = {1,2}.

Fig.3 shows the simulation results for both Gc(z) and the Sugeno

type FC. The output response (y) and the control signal (u) are exactly same

for both controllers as expected. The reference input (yref) is a unit step

function applied at t = 0.1 s.




pp.371-375

291

0 0.5 1 1.50

0.2

0.4

0.6

0.8

1

Outputs (y) Control signals (u)

0

0.4

0.8

1.2

1.6

2

Time(s)

y

u

Thick dashed : FCThin continuous : Gc(z)

Figure 3 Simulation results showing the equivalence between Gc(z) and

the Sugeno type FC

It should be noted that the use of Sugeno type FC becomes more

reasonable and meaningful when several control laws are to be implemented

in a single controller rather than implementing only one control law.

However, in this paper, the main purpose was to illustrate the equivalence

between a linear controller and a Sugeno type FC as a preliminary step for

the implementation of several control laws in a FC.

2.2 Mamdani Type Fuzzy Equivalence

Mamdani type FCs do not have algebraic equations in the THEN

part of the rules [8]; rather they have output membership functions and there

is a defuzzification process to produce a control output value. Therefore, the

control law of the linear controller can not be directly used in the Mamdani

type FCs. Since a linear control law is to be implemented, the inference

operators (AND, implication and aggregation) and the defuzzification

method should be chosen properly in order to not to lead to a non-linearity

in the FC. It is possible to find different ways for implementing a linear

control law in a FC, but one of the simplest way is to chose the algebraic

product for the AND and implication operations and to use the center-




pp.371-375

292

average-defuzzification method [8]. In the center-average-defuzzification

method, the aggregation method is not required and the centers of the output

membership functions are the quantity of interest, not the shapes of the

membership functions. Therefore, the output membership functions can be

simply chosen as singletons centred at the appropriate points as shown in

Fig.4. It should be noted that the output membership functions do not have

to be regularly distributed.

uMAM Mdu1

1 du1 …….……….……………. du8

Mdu8 …….……….……………. Mdu9

du9 …….……….……………. du16

Mdu16 …….……….…………….

Figure 4 Output membership functions

Table I The rule-base of the Mamdani type FC

uMAM u1 =A11 , e = A21 uMAM u1 = A11 , e = A22

e1 \ e A31 A32 e1 \ e A31 A32

A41 du1 du2 A41 du5 du6

A42 du3 du4 A42 du7 du8

uMAM u1 =A12 , e =A21 uMAM u1 =A12 , e =A22

e1 \ e A31 A32 e1 \ e A31 A32

A41 du9 du10 A41 du13 du14

A42 du11 du12 A42 du15 du16




pp.371-375

293

The input membership functions should also not introduce any non-

linearity. For example, if the input membership functions are chosen as

shown in Fig.1, they not only provide a linear mapping but also result in the

smallest possible rule-base (i.e. the number of the rules becomes minimum

since there are only two membership functions for each input variable).

Using the input and output fuzzy sets shown in Fig.1 and Fig.4, the

rule-base of the Mamdani type FC can be given in a tabular form as shown

in Table I. The rule-base consists of 16 rules since there are 4 inputs and 2

membership functions for each input variable.

In Table I, the symbols e, e, u1 and e1 represent the input

variables e(k), e(k), u(k-1) and e(k-1) respectively. The output is

represented by uMAM and the symbols Ai1, Ai2 (i = 1,..,4) and du1,

du2,.…..,du16 refer to the input and output membership functions shown in

Fig.1 and Fig.4 respectively.

Thus, the equivalence problem has been reduced to the

determination of the values of M1,..,M4 and Mdu1, Mdu2,…..Mdu16 for the

membership functions of the input and output variables respectively. The

selection of M1,..,M4 has been discussed for the Sugeno type FC in Section

2.1 and this discussion is also valid for the Mamdani type FC since there is

no difference between Mamdani and Sugeno type FCs in terms of the input

fuzzification process. On the other hand, the output membership function

parameters Mdu1, Mdu2,…..Mdu16 can be determined by using the desired

linear control law, the rule-base and the extreme values of the input

variables since the FC is expected to implement the desired linear control

law between the extremes of the input variables using the rules in the rule-

base. For example, from Table I, consider the rule




pp.371-375

294

IF u1 is A11 AND e is A22 AND e is A31 AND e1 is A42 THEN

uMAM is du7

which implies that if the certainty of the rule is 1 (that means all the input

values are full members of the corresponding fuzzy set, i.e. membership

degree = 1, and thus the input values are the extremes), then the output

fuzzy set du7 should have a center at

M cM M M Mdu7 1 1 2 2 3 3 4 (9)

to satisfy the equivalence between the controllers at these extreme values of

the input variables. In this manner, the parameters Mdu1,....,Mdu16 can be

calculated as shown in Table II.

Thus, if the centers of the output membership functions are chosen

as shown in Table II, the FC will provide the desired linear control

behaviour by implementing a linear interpolation between the output values

corresponding to the extremes of the input variables.

Table II The centres of the output membership functions

Mdu1 = -cM1 - 1M2 - 2M3 - 3M4 Mdu9 = -Mdu8

Mdu2 = -cM1 - 1M2 + 2M3 - 3M4 Mdu10 = -Mdu7




pp.371-375

295

Mdu3 = -cM1 - 1M2 - 2M3 + 3M4 Mdu11 = -Mdu6

Mdu4 = -cM1 - 1M2 + 2M3 + 3M4 Mdu12 = -Mdu5

Mdu5 = -cM1 + 1M2 - 2M3 - 3M4 Mdu13 = -Mdu4

Mdu6 = -cM1 + 1M2 + 2M3 - 3M4 Mdu14 = -Mdu3

Mdu7 = -cM1 + 1M2 - 2M3 + 3M4 Mdu15 = -Mdu2

Mdu8 = -cM1 + 1M2 + 2M3 + 3M4 Mdu16 = -Mdu1

Example 2 : Let us again consider the system shown in Fig.2 with the plant

and the linear controller given by (6) and (8) respectively. The aim is to

design a Mamdani type controller that is precisely equivalent to the linear

controller given by (8).

The input membership functions are chosen as shown in Example 1 since

there is no difference between Mamdani and Sugeno type controllers in

terms of the fuzzification process. Therefore, the membership functions are

as shown in Fig.1, where Mi = 250 (for i = 1 to 4) for all the input variables

(the selection of Mi has been already discussed in Example 1). The output

membership functions are chosen as shown in Fig.4 and thus the rule base is

as shown in Table I.

By comparing (1) and (8), the linear controller parameters become

Kc = 2, a = 0.9876, b = 0.95 and c = 0.88.

Using (4), the constants 1, 2 and 3 are calculated as

1 = 0.00124, 2 = 1.99876 and 3 = -1.87644.

The centers of the output membership functions are obtained by

using Table II as shown in Table III.




pp.371-375

296

Table III The centres of the output membership functions

Mdu1 = -250.89 Mdu9 = 189.11

Mdu2 = 748.49 Mdu10 = 1188.49

Mdu3 = -1189.11 Mdu11 = -749.11

Mdu4 = -189.73 Mdu12 = 250.27

Mdu5 = -250.27 Mdu13 = 189.73

Mdu6 = 749.11 Mdu14 = 1189.11

Mdu7 = -1188.49 Mdu15 = -748.49

Mdu8 = -189.11 Mdu16 = 250.89

Fig.5 shows the simulation results for the designed Mamdani type

FC in comparison with the linear controller (8). The output response (y) and

the control signal (u) are exactly same for both controllers as expected. The

reference input (yref) is a unit step function applied at t = 0.1s.

0 0.5 1 1.50

0.2

0.4

0.6

0.8

1

Outputs (y) Control signals (u)

0

0.4

0.8

1.2

1.6

2

Time(s)

y

u

Thick dashed : FCThin continuous : Gc(z)

Figure 5 Simulation results showing the equivalence between Gc(z) and

the Mamdani type FC

Conclusions




pp.371-375

297

In this paper, the fuzzy equivalence of the second order linear

controllers has been investigated. It has been shown that any second order

linear control law can be precisely implemented in a FC for a given input

universe of discourse. The equivalence may be interpreted as a sort of bridge

between the classical and fuzzy control approaches. This is an important

point because the equivalence may be used to combine the classical and the

fuzzy control approaches in a same framework and thus a controller using

the advantages of both control methods may be designed. The fuzzy

equivalence of a general controller (n-poles and m-zeros) can also be

derived in the similar manner.

References

[1] L.A. Zadeh, ―Fuzzy sets,‖ Informat. Contr., vol. 8, pp. 338-353, 1965.

[2] P. Vas, A.F. Stronach and M. Neuroth, ―Full fuzzy control of a DSP-

based high performance induction motor drive,‖ IEE Proc. Contr. Theory

Appl., vol. 144, no. 5, pp. 361-368, 1997.

[3] G.C.D. Sousa and B.K. Bose, ―A fuzzy set theory based control of a

phase-controlled converter DC machine drive,‖ IEEE Trans. Ind. Appl.,

vol. 30, no. 1, pp. 34-44, 1994.

[4] Z. Ibrahim and E. Levi, ―A detailed comparative analysis of fuzzy logic

and PI speed control in high performance drives,‖ in Proc. IEE Conf.

Pow. Electron. Var. Speed Drives, 1998, pp. 638-643.

[5] W.G. da Silva and P.P. Acarnley, ―Fuzzy logic controlled DC motor drive

in the presence of load disturbance,‖ in Proc. EPE’97, vol. 2, 1997, pp.

386-391.




pp.371-375

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[6] C.M. Liaw and J.B. Wang, ―Design and implementation of a fuzzy

controller for a high performance induction motor drive,‖ IEEE Trans.

Syst. Man Cybern., vol. 21, no. 4, pp. 921-929, 1991.

[7] S. Galichet and L. Foulloy, ―Fuzzy controllers : Synthesis and

equivalences,‖ IEEE Trans. Fuzzy Syst., vol. 3, no. 2, pp. 140-148, 1995.

[8] L.X. Wang, A Course in Fuzzy Systems and Control. Prentice-Hall,

1997.

Varol, A., Varol, C.: ―Distance Education Based on a Combination System of

Internet and Television‖, 2nd International Communication in the Millennium, A

Dialogue Between Turkish and American Scholars, In Cooperation with University

of Texas at Austin, USA, Anadolu University and Istanbul University, March 17-19,

2004, Istanbul, p.671-685

299

2.9. DISTANCE EDUCATION BASED ON A COMBINATION

SYSTEM OF INTERNET AND TELEVISION

Abstract

Thanks to the rapid development of information and communication

technology, new tools are being used by educational institutions. Using

modern technological tools changes teaching methodology. Formerly,

teachers dominated a big part of their courses while now students play a

much more active role, either through centralized learning or self-learning

methods. Distance education is a method commonly used because of the

advantages of time and place independency.

There are various ways to give a lecture from a distance. Satellites,

fiber optics, modems, routers, radio, television, computers, etc are the

components of distance learning systems. Depending on the tools that are

used, distance education can be renamed as Web Based Education,

Videoconferencing, Teleconferencing, Radio-TV Based Education, and

Distance Learning via Satellite etc. The tools that are used are very

important but the usage efficiency of the tools is questionable. It is

important to remember that better usage of the tool does not mean that a

perfect lecture can be given over a distance.

We will discuss various factors of change in the combination of

internet and television based distance education used at Firat University

since 1992. A course is held on the Internet, which was taken by other

students of other Turkish Universities. The National Informatics Committee

of Higher Education Council of Turkey accredited this course.

Because robotics is a technical subject, there is a lot of discussion

about offering this course via distance. We have proved the success of a





2004, Istanbul, p.671-685

300

technical field course like robotics using modern informatics tools. All

content of the course is held on-line using the creativeness of simulation,

animation and multi-media facilities. All exams are taken on computers,

with cameras acting as proctors, and the grading is done automatically and

immediately.

This article will discuss the advantages and disadvantages of

holding courses on line using some statistical results. This discussion will

lead to recommendations towards a development and management

framework for teaching and learning systems where the pedagogical sides of

distance education will be considered more.

Keywords: Distance education based on Internet and Television,

interactive learning environments, lifelong learning, pedagogical issues.

1. Introduction

As Heller., R.,S. (1999) says ―Distance Education is a system and a

process that connects learners with distributed learning sources and an

interaction between the learner and the instructor using one ore more

media‖.

It is a fact that Information should be spread to all people because

lifelong education is very important in developing the behavior and skills of

the population. If people want to be well educated in order to adapt to their

surroundings easily, they have to improve and develop themselves by using

different ways and tools. There is not any perfect age for learning that limits

human beings. Therefore a new concept is occurring in the world called

lifelong education (Varol, C., 2000).

Technology is developing so rapidly that it cannot be followed

easily. Especially the development in the field of communication and

information technology is so fast, every day you can meet new kinds of





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magic tools. These tools change the classical methods and thoughts of

people. For example, if we compare the latest educational system with the

oldest one, we can distinguish huge differences. The classical blackboards

have given up their place to the electronic board while the overhead has

been replaced with a web-linked projector.

The Internet, the most important of these new tools, is driven by

communication. Sending a message all over the world takes only a few

seconds. Lots of information can be obtained directly from the databases of

the Web. In the last decade five or six times more knowledge has been

stored on computers than all of the information that had been stored in all

other formats since the beginning of human life.

The majority of the developing countries have difficulties with their

educational systems. With a lack of well-organized schools and a lack of a

sufficient number of qualified teachers, education cannot continue in a

satisfactory manner. This situation brings some new ideas concerning the

use of new technologies.

Distance education is one important phenomenon that is used by a

lot of educational institutions. Distance Education began in the 19th century

where the educational materials were posted to the students. The first

application of distance education based on these posts was seen in countries

like England, France, Germany, the US, etc. (Anderson, M., & Jackson, D.

2000). This kind of distance education was used first in 1974 by some

colleges where the teachers for high schools were trained and educated in

Turkey (Varol, N., 2001).

Distance education can be applied in two different ways. There are,

a) Synchronous education

b) Asynchronous education





2004, Istanbul, p.671-685

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Synchronous distance education is held at the same time. Although

the places are different from each other, the courses are held at the same

time-period. This type of distance education can be defined as live

education. Video conferencing is a good example of synchronous distance

education, because education continues at the same time where two ways of

communication (data, voice and video) exist (Varol, C., 2002; Inoue, T., &

Ueno, H.,2001).

For asynchronous distance education, web based education is a good

example. The course notes may be accessed at any time and this process can

be repeated as much as needed (Pahl, C., 2003).

Computer supported cooperative learning (asynchronous education)

emphasizes group or cooperative efforts among faculty and students and

results in an active participation and interaction on the part of both students

and instructors. Knowledge is viewed as a social construct of self-

explanation, internalization and appropriation (see Heller., R.,S.,1999)

If an exam of the web based education is taken at the same time this

kind of education also can be defined as a synchronous education, because

events occur at the same time. It means the synchronous and asynchronous

distance education can be changed depending on the time.

After the year 1990 the usage of the Internet has been accelerated so

that a lot of educational institutions have begun to use Internet facilities in

order to give well organized courses. Some well known universities have

begun offering many courses on line related to their diploma and certificate

programs.

The following items should be considering so that well organized

course material can be offered.

The quality of the course material

The usage of the course material





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Students are supported by teachers

The administration and management of the system

The accessing onto computers

Mechanisms of feedback and multimedia

The preparation of web based course material needs more work than

a course offered in an in-class atmosphere. Animation and simulations are

the best supportive tools to explain a topic on screen. Because a web based

course is taken over the Internet, speed is very important. If the animation

and simulation have very big sizes, some constraints can be met like opening

or playing difficulties. Therefore each figure should be prepared effectively

where the size is considered.

To keep the web site up-to-date is another important point. Because

all information is given on the web, the web site should be maintained on a

daily basis if possible. Well prepared course material should offer

interactive access where the teacher and students react to each other (Pahl,

C., 2001). According to the necessity, the computer should be completely

interactive and make adjustments to simulations depending on the feedback

taken from the side of students. At that point the automation will play a big

role.

In the period from the planning stage of a web based course to the

phase of broadcast on web the following features should be considered:

Determination of the aims and targets: The target groups and the

kinds of content should be fixed.

Research: The literatures done in this field should be found and

compared.





2004, Istanbul, p.671-685

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Cooperation: Teamwork should be encouraged between related

institutions and units. Web designers, animation makers, expert

people on the topic should collaborate together.

Preparation of the course materials: The weekly curriculum and all

supportive materials should be prepared using sound, video and data

effects.

Preparation of the HTML pages: Course content should harmonize

with used tools. The course content should be kept up-to-date upon

the demands of the students.

Pedagogical aspects: The most important point in offering a course

on line is that student‘s interest must remain active during the whole

session in front of the computer screen. If the course content does

not consist of some animation that keeps the student awake and acts

as a lure centre, the course will be boring for the student and it is

possible that the concentration of the students would be lost. To

maintain this point some animation related to jokes or humor can be

added into the course pages. The visual and individual effects can

be a solution to prevent this obstacle (Varol, N., 2002).

Pages should contain some necessary sources: The students can

contact each other using e-mail, IRC, forums, e-groups facilities.

Software and Date Base Support: A database management system

should be established where all data of the student can be stored.

Access Control: The students who visit the web pages and surf

should be registered and kept on log automatically.

Testing the web site: To ensure that each part of the web site works

correctly, the content should be tested at certain intervals.

Up-To-Date of the web site: If an interactive course wants to be

held, it should be updated often.





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2. Some advantages of web based education

According to statistical results students acquire one third of all

knowledge by watching, one third by doing and the final one third by

listening. If these aspects are considered, web based education becomes

even more important because all three of these events occur during learning

from the Internet (Yılmazçoban and Damkacı, 2001).

The advantages could be sequenced as follows:

Thanks to web based education the opportunities between the

people and different communities can be balanced.

The expense of the printed materials decrease.

Compared with a text course the course that is supported with

multimedia (Sound, color, graphics, animation, simulation, etc) is

much more effective.

Education on the web has independency of time and place.

Therefore an unlimited educational atmosphere comes out (Çabuk

and Erdoğan, 2001).

The ability of the self-learning of students occurs.

The up-to-date concept of the courses offers a good facility to the

students who can reach the latest information about a variety of

topics.

Accessing the source of information can be realized easily.

Education is continued by the help of information technology.

There are a lot facilities offered between the groups (teachers-

students, students-students).

The students, who hesitate to ask questions and join team-work in

the classical classroom atmosphere, can have self-confidence and

self-esteem in the virtual word.





2004, Istanbul, p.671-685

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All presentations submitted on the web have independencies from

the atmosphere of the instructors, students and other environmental

effect, shows educational consistency.

The increasing of the interests is supplied because an individual and

interactive relationship occurs (Özdil and Çelik, 2000).

Except for the framework differences there do not occur any

cultural or social differences between the students, and therefore a

democratic and equal form of education comes out.

These are the beneficial to the student because of the costs of travel,

extra accommodation, and the production lost during the travel time

disappear through distance education.

The virtual interaction atmosphere located in different areas offers a

team work facility to the students who own different and unequal

possessions. The various aspects of the students from different

virtual atmospheres increased the challenge of the students and

brainstorming takes place.

The students who take web based courses learn to surf deeply in the

virtual world, which can change the behavior and attitudes of the

students.

3. Some disadvantages of web based education

The disadvantages of the web based distance education can be

itemed as following: (Özdil and Çelik, 2000; Yılmazçoban and Damkacı,

2001).

Because of the rapid development of communication technology it

costs a lot of money to change tools often.

The students need to be skilled using the computer.





2004, Istanbul, p.671-685

307

The students, who are not used to studying themselves, are bored to

study in front of a screen alone.

Educators who prepare web based education should be able to use

new tools or some other expert people should be in charge.

The teenagers who sit for a long time in front of a screen can feel

them isolated and some misbehave situation can come out

(Yılmazçoban and Damkacı, 1999).

If the Internet facility is not perfect, like very slow, the students

lose a lot of time to access the computers.

For some students who are not breathing the traditional classroom

atmosphere, distance education may be confusing.

Distance education may obstruct the development of the student‘s

skills.

4. Distance learning at Firat University

A project was proposed named ―The control of the satellite dishes

via computer and a case study of television broadcasting system‖ on March

23, 1991 to the Research Fund of Firat University by Varol and some his

colleagues (Varol, A., 1993).

In order to convey the news in the university and also to make

cultural and educational programs (distance education), the first of Firat

TV's own broadcasts began on October 2nd

, 1992. The programs were

increased day by day. By defining the policy of the Firat TV, it was planned

to be an association. The television broadcasting system named Firat TV is

the first local University television station in Turkey (Varol, A., 1993).

A new transmitting tower was constructed on a hill on the university

campus in 1994. And also, there is a new modern studio, established from





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308

the university's own resources, which has been in service since the

beginning of 1996.

Computer course sessions for TV broadcasting were prepared.

Computers were rented to applicants who wanted to follow the programs.

After the completion of the courses, examinations were set and the students

who passed the exam were given certificates. In June 1995, the Higher

Education Council/World Bank's Industrial Education Project's "Computer

Systems Technologies" courses were performed. In these courses the

lectures were recorded and broadcast on the same night. Hence the students

had the chance to follow the same lecture twice. These courses were

followed by 32 lecturers by students from different universities in Turkey.

The same courses were repeated for the teachers employed by The National

Education Ministry. This time 132 teachers attended these courses.

Therefore in Firat University, Distance Learning programs towards

certificate started in 1995.

Firat University has prepared all the necessary hardware background

for distance learning. One of the important tools of distance education is the

local television broadcasting system called Firat TV. All kinds of the

movies like animation and simulations related to the course materials are

prepared in Firat TV‘s studios.

Firat University has very high access to the Internet. There are a lot

of computer laboratories that have Internet access. The Internet framework

of the University was cabled by fiber optics.

5. Communication module in a virtual class

Each educational institution that wants to offer a qualified distance

education and to compete and challenge with other similar institutions

should establish a virtual class communication module (Varol, A., Türel,





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Y., 2003). This virtual class communication module should be created on

Web site by the course offered institution itself. All related people like

teachers, students, experts and supportive technicians can interact each

other in this module. These are the links of a chain that have to harmonize

correctly with each other.

Communication between students and teachers should be realized

in two ways. This module should be served 24 hours without having a

break. A new virtual communication module was created and developed by

us. One who has access into this module depending on the circumstances,

can communicate with others and can send his negotiations to the forum

using all kinds of communication styles like audio, video and data.

Depending on the wish of students, the students can use a code

name created by them to submit their ideas freely without having any

constraints. All kinds of communication are recorded and logged by tracing

software.

5.1. Used Software and Tools

Prepared course notes, animation, graphics, simulations, etc. can be

easily transferred into the module without having confusion. To increase

and improve the facilities of the module parts, a lot of automation

mechanisms were added to the software where the creativeness of the object

oriented programs used like PHP, CGI and ASP. While this software is run

by the servers, the other software called PWS, IIS and Apache must run by

the PCs. The biggest advantages of object oriented software are its packets

called script. By the design of the pages these packets are placed directly

into codes which result in saving time. The big parts of the module are

created using PHP software.





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All kinds of the data that is stored on the server have to link to each

other. Adding and deleting facilities should be easily done. All kinds of the

statistical data could be obtained from the software immediately. Hence,

MySql software was used for the database that can have some more

facilities to link PHP.

Actually Mysql is database query software. Not only can the storage

of the records but also the relations between records be stored, too. The

database management software called Phpmyadmin interface was used to

create fields in a manner of needs.

5.2. Access into Communication Module Application

A button called Communication was created in virtual class

application. Pushing this button will open the communication module. For

security reasons only those students only who have a userid and password

can access the communication module.

5.3. Chat Room Module

This room offers all facilities to the users related to communication.

The users can discuss and negotiate as if they are in a real classroom

atmosphere. If necessary a user can open his/her private chat room. This

module is very important for students because they can chat with their

friends about the course materials and other things.

All types of communication like audio, video and data done in the

chat room are stored on the server and the student can see later the formerly

recorded conversations whenever they want. To prevent of the misuse of the

chat room there are some constraints which are controlled by a manager of

the modules.

5.4. Forum and Discussion Groups Module





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Forum and discussion group module allows the students to discuss

together at the same time and share their ideas with each other. Because of

storage of all the discussions it is possible to access the old records anytime.

Forum and discussion groups module is controlled by a manager who is able

to give various restrictions to the students. In this profile it is possible to

send a student a private instant message or e-mail.

5.5. E-mail List and Form Mail Module

In this section a student can use all kinds of e-mails facilities

without giving more effort.

Form mail is a facility to send an e-mail on the web. This is very

useful for the student if they are using a computer in another place who

wants to see their mail boxes.

5.6. Classroom Notebook Module

Students can write their ideas, thoughts and knowledge in this

platform. In this platform the students who are enrolled in the same course,

can see some information of their classmates. This facility is especially

important to make known who is enrolled to the same course.

6. Robotics course held on line at the Firat University

A new regulation called ―Regulations on Inter-University Distance

Higher Education Based on Communication and Information Technologies‖

about the Distance Education came into play on December 14, 1999 (Resmi

Gazete, 1999).

The aims of distance higher education based on communication and

information technologies at the vocational, undergraduate, and graduate

levels are:

a) To facilitate academic cooperation by enabling the sharing of

educational resources among universities,





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b) To increase the effectiveness of education by making use of the

interactive medium provided by information technologies, with multimedia

features and the ability to access unlimited information,

c) To increase the efficiency of higher education and make it

available to new student audiences.

Distance Higher Education Based on Communication and

Information Technologies includes diploma programs at the vocational,

undergraduate, and graduate levels in institutions of higher education, in

which some or all of the courses are given using the Internet, other data

communication networks, or radio. In this type of education, educational

tools such as audio/video cassettes, audio/video CDs, books, and

communication devices such as telephone, television and mail may also be

used (Resmi Gazete, 1999).

A Robotics Course was one of the first web based courses that was

accredited by the Higher Education Council of Turkey in the year 2000.

This course can be taken by students of the other Turkish universities.

Because the robotics course consists of technical topics, the idea of this

course being held on the Internet is already questionable. Because subjects

of a technical course are mostly related to experiments and

implementations, one wonders how the experiments are applied in a virtual

atmosphere.

The robotics course has been held on line since the year 2000 in

Turkey. There are a lot of students who took this course at a distance from

other universities. These students built an enrollment of about 25 people

and their universities reserved a computer laboratory where they could visit

when they wanted.

Some types of laboratories were well organized and controlled by

cameras. Although you are working over a distance, you can see the





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students in the classroom via the Internet. Here two types of distance

education were used, which combined web+video conferencing together

(Varol, A.; Das, R., 2003).

The universities which give the possibility to their students to take

the robotics course at a distance entrust some instructors to help their

students to solve problems occurring during the teaching. Especially, these

people are very useful during the on line exam. They stay in the laboratory

at the exam time and monitor the students although students are traced by

the cameras.

6.1. Distance Learning Center of Firat University

A research center was built at Firat University to organize all work

related to distance education. More than 20 people are occupied at this

center. There are three main branches divided in software, hardware and

Firat TV Unit in this center. The software branch consists of the various

departments called Graphics, Animation, Simulation, Curriculum

development, Measurement and Evaluation, software supplied unit while

hardware branch consists of the departments named Maintain, Framework

and Technical Support Team Unit.

The software branch is an important part of the chain. All kinds of

visual and audio work are prepared in this unit. Each movement of a robot

is animated and stimulated by a group whose members are instructors,

expert lecturers and students. These people work together. But the big parts

of the work are done by students using the method of the student

centralized self learning system (Varol, C., 1999). The graphics group

decides web format, color of the pages, the font of the letters and links

status.

The curriculum development, Measurement and Evaluation

department has a relation with the Education Faculty‘s professors. Because





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how a course material should be taught on line is very important to

maintain the pedagogical aspects. The members of this unit analyze all

topics of the robotics course considering in pedagogical sides, because the

students should not be bored in front of the screen. Therefore they decide

where and which kind of a joke, pictures or animation should be added onto

web which has not doing with course material. The feedback of the students

is evaluated by the experts. They apply from time to time surveys in order

to figure out the not good working points of the distance education.

The software supply team decides which kind of software is

necessary for developing the best of the course material. As much as

possible the latest software is chosen. Revolving fund of the university

supplies all kind of the software and hardware needs.

The maintain, Framework and Technical Support Team Unit is

responsible all kinds of technical things. If a problem on network occurs,

this unit finds solution immediately (Das, R., Varol, C., 2002). The

computers and other instrument that are used for distance education are

decided by this team. Hardware maintains are done by this team.

Firat TV is a television broadcasting unit where all kind of videos

related to the course are prepared and broadcast on TV as mentioned above.

Some videos are prepared in Firat TV studious in order to put into web

based robotics course materials. The students take roles and play

themselves according to the scenario written by the course developer teams.

6.2. Methodology of Robotics Course Teaching

Although there have been a lot of students who took robotics

courses at a distance since 2000, there are two universities whose students

enrolled onto robotics course as a group. These Universities are named

Kahramanmaras, which is located in the southeast part of Turkey, while





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Sakarya is located in the western part of Turkey, about 100 miles from

Istanbul.

During the semesters the students could follow the weekly

activated web pages from a distance. A book called ―Robotics‖ was

published in 2000 by the Ministry of National Education. This book and a

CD contains of the videos, animation and simulation of the robotics course

were sent to the enrolled students. All exams were taken on the web and

thanks to automation the students could have their exam results

immediately (Karabatak, M., Varol, A., 2002)

During the exam in the computer laboratory an assistant supervised

the students. At the same time the laboratory was watched by cameras at a

distance of about 1200 km. The whole time of the exam was recorded on

the server that stayed at Firat University.

The multiple choice exams were delivered to the laboratories from

the main servers of Firat University. Each student has the same exam

contents but the placement of questions and selected items are changed

with help of the automation software. This was useful to help prevent

cheating.

There were fixed times at which the professor and students are on

line and students can discuss the topics. At this special time, in addition to

the web based distance education the video conferencing system were

operated in parallel. Thanks to this facility the professor could see the

laboratory at a distance while at the same time the students could see the

professor. An interactive discussion could be had, similar to the classroom

atmosphere.

There are electronic blackboards both at the laboratories where the

course was held and the laboratories where the course was followed.





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Thanks to this system the students could see what the professor wrote on

the electronic blackboard at the same time.

A lot of surveys were taken on line, which were completed by

students. These surveys were prepared by the Curriculum development,

Measurement and Evaluation Department. After analyzing the surveys this

department prepared a report which addressed the weaknesses of the

course. They prepared a solution which can better the problems.

There are some automatic evaluation systems which compare all

questions and fix the well known or worse known questions immediately. A

report related to these results is sent directly to the professor for

consideration. After having this report the professor can decide which

course notes should be repeated.

6.4. The Final Evaluation Methodology of the Robotics Course

In addition to the above mentioned evaluation system there was a

final test system to fix if the students have been taught enough. To examine

the success a special week is reserved at the university whose students are

enrolled in the robotics course. In this course the Fishertechnik robot set

was used which is a carry bar and has small pieces like motors, switch,

sensors, interface, building plastic materials etc.

This robot set has big advantages compared to classical industrial

robots. The classical robots are designed for fixed purposes while

educational robots like Fischertechnik are set flexible to mount a lot of

various automation systems. Students can decide themselves which kind of

automation system they want to mount.

The students were divided into groups in which there were 5-6

students. Each student composed a special automation project report where





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all detail should be given. The professor selects the best project to mount

by the member of each group. The team work at this point is very important

because one student prepares the power point pages while another one

prepares animation and the others mount the robots.

After mounting the robots it is important that the robot is operated

correctly by the coded computers. This is a result of the course contents. If

the course material is taught enough and if the students learned well they

should finish their mounting project successfully (Varol, A., Varol, C.;

Gur, K.; Dogan, S.; Bulut, M.; Demir, F., 2002). This point is very

important to measure the ability and skills of the students. If they learned

enough at a distance they would mount the robot set using the information

that they learned at a distance.

Statistical results showed that 85 percent of the robotics course

given at a distance takers could successfully mount an automation system

and operate it in 2000. At the beginning it was surprising to have such a

high rate of success, because it was questionable to offer a technical course

at a distance.

The following years we obtained this success again which

supported the theses that technical subject can be taught at a distance too.

To fix this result we applied a general survey to all students who enrolled

distance held robotics course.

According to the survey on the success of the students the

following items played big role:

The robotics course is a new technology in which the students

interested.

The students who enrolled in the robotics course selected this

course according to their own wishes while other face to face taken

courses were obligatory.





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Surfing in a virtual atmosphere was interesting to the students.

During the web based distance education the jokes and animation

that appeared on the screen were very exiting to them. Perhaps if

the same jokes had done in classroom atmosphere would bother the

students while on the screen they only laugh and smiled.

Working interactively on simulation encouraged the students

because they saw the results of their success on screen.

Teamwork was for the students very interesting, because according

to the Turkish education system they were not used to this kind of

methodology where they submit first time their proceedings in front

of the teachers, their friends and to the cameras which broadcast

from Firat TV.

They can see their videos later from the CD which will be a good

memorandum for them in future.

Mounting a robot was for them interesting because at the end they

showed their product as working.

To have the exam results that appeared as soon as after the

finishing of the exam was a lure points because they could see the

wrong answers at the same time which results in the learning while

taking an exam.

Because of the above mentioned survey results the demand for taking

this course increased year to year. But we have to bring a quota for

selection of the robotics course despite the crowed of students.

7. Conclusion





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Distance education can be a solution especially for the developing

countries which do not have enough instructors and well qualified

educational institutions.

A country like Turkey where only approximately 30 percent of the

students can be enrolled in the university except the Faculty of

Open Instruction, distance education in technical fields can give an

opportunity to the students who do not win the main university

entry exam.

Although there is a big university called Anatolia University

offering distance education, in general in the field of social subjects

using the governmental television broadcasting system, there aren‘t

enough technical disciplines where the students can earn a diploma

in technical areas.

If the course material that is offered on the web is prepared

carefully and considers all aspects of the pedagogical behaviors,

the technical subjects can be offered successfully using sufficient

animation, simulation and creativeness of the multimedia.

There are some Universities in Turkey that offer web based

distance education to the students at their technical colleges. But

the work facilities for two year graduate students are restricted.

Therefore distance education should be established for the four

years and more undergraduate branches.

If a cost per student is compared with a cost of distance education

per student, the distance education course cost can be cheaper than

classical education because of the quality and facility of an

institution.

Web based distance education should be encouraged in the fields

where the Turkey manpower needed.





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If the often well prepared automation systems of a web based

course exist, the beneficiary of the system will increase more.

Thanks to working on an occupational task, distance education can

encourage adults to enroll in a program where it is not necessary to

go a traditional university; because web based distance education is

independent from time and place.

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2.10. A CASE STUDY: A VIRTUAL CLASSROOM MODEL

Research Assistant Yalin Kilic TUREL

Firat University, School of Education, Department of Computer and

Instructional Tech.

Prof. Asaf VAROL

West Virginia University(US), College of Engineering & Mineral Resources

With their Distance Education Centers, universities are working on

spreading their education services to wider recipients. Distance education

has gained new dimensions with the principle of making educational

activities available to everyone, everywhere at any time, by using the

information and communication technologies in particular. Thanks to online

education and teaching, virtual classes that enable education regardless of

time and place, have made the use of many variables possible which could

not be used or had limited use in traditional classes. In virtual classes,

education can be provided synchronous or asynchronous. By using various

communication tools, student-to-student interaction, student-to-teacher

interaction as well as interaction within groups can be enabled at any time of

the day.

The value of distance learning, which has been presented as an

alternative to traditional teaching methods, has increased significantly with

the development of information technologies. The fast spreading of the

internet has made it available for use as a base for distance education. It

enables verbal, audio and video communication and interaction, as well as

making the information reachable.

The internet can also help to provide a more efficient and productive

teaching-learning environment. The educational use of internet has




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developed various terms such as Internet Supported Education, Internet

Based Education, Web Based Education, and On-line Education, all of

which serve the same purpose. While explaining the contribution of life

cones and learning lives into the behavior changing period, Dale mentions

the importance of the phenomena such as the number of the senses used in

the process, the active experimental learning skills of the person and the

basic or complex programmed learning style (Cilenti 1988). On the other

hand, the internet helps individuals use multi-media applications with

variables such as text, graphics, sound, animation, video clips etc, This

enables them to enroll in individual or group teaching activities with

applications such as e-mail, FTP, discussion groups, white boards and

forums (Demirel, Seferoglu, and Yagci 2003). Today these structures on the

internet are used heavily at universities as well as other educational

institutions, particularly in distance-education centers. The biggest

difference between classical education and internet based education is the

teaching method (Varol and Varol 1999). Due to its ability to provide fast

and interactive learning as well as more consulting services and discussion

opportunities, education through the internet has provided a student-

centered and democratic education environment that is based on individual

teaching (Keser, Demirkalfa, Gocmenler,and Sen 2001). In Turkey, many

universities such as Anadolu, Bilgi, Firat, ITU, Mersin, ODTU and Sakarya

use various applications toward online education. It is important to target

high standards in order to create a valuable distance education in Turkey

similar to developed countries. It is important to present the class notes in an

html format, however the main program requires more (Aslanturk 1999).

Every element of the program development approach must be formed by a

team of experts by paying attention to the characteristics of online education

from need analysis to evaluation.




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Virtual Class And Lesson Management System Software

The automation that provides an efficient and productive system to

apply online education is described as Virtual Class or Learning

Management Systems (LMS). The design of this type of systems is done

with the principles of ―Instructional Design‖. Instructional Design (ID) can

be defined as organized procedures that plan the special teaching activities

and determine the objectives, content and applications for teaching (Ipek

2002, 2003). During teaching design, the general steps to take into

consideration are analysis, design, development, testing, publishing,

evaluation and correction (Gustafson and Branch 1997). Today, besides TV-

based education, distance education is published by internet supported web

sites and Distance Education Platforms specially prepared for this purpose.

The necessary features of these platforms include easy registration of

students and classes into a database, suitability of presenting any kind of

electronic education material, a reporting feature that enables submission,

testing and evaluation which enables follow-up of student improvement

levels and answering the needs of the students.

There are many virtual classes and Management System Software

produced by technology firms or universities. As a solution for distance

education, software such as Lotus Learning Space, WinClass or WebCT

which are made by big companies like IBM and Microsoft are being used.

Since these programs are prepared for international institutions, they can not

meet the requirements of our education system. Nevertheless, while using

these software, METU Information Institute, which is a leading institute in

distance education, has begun to apply its own new software NET-CLASS

under the name of IDE_A (Internet Supported Education-Synchronization

Project). Since the software did not meet their requirements ODTU (METU)

has been the first Turkish University to sign a commercial protocol along




328

with a private company in producing this type of program (ODTU 2005).

Also, Sakarya University, in cooperation with IBM, provides software

services to universities that have distance education. Sakarya University

recognized the modifiability of the Lotus LearningSpace program of IBM to

fit their requirements and started distance education work in July 2000.

Within the frameworks of that project, Internet Supported Teaching Groups

have been established in both universities whose members are from

Computer, Industrial, Mechanical Engineering and Mathematics areas. The

studies are conducted by the cooperation of the technical committee of

academicians at the university and committee of the partner company.

Training was provided for the academicians who work in this group. Some

of the programs that possess virtual class or Windows based lesson

preparation and presentation qualities are given below along with their URL

addresses:

Table 1. Lesson Management Systems / Virtual Class Software (Aslanturk 1999)

LMS Name Web Address

PROQUEST http://www.umi.com/proquest

Copyright Clearance Center, Inc.(CCC) http://www.copyright.com/About/default.html

Learning Space http://www.lotus.com/learningspace

TopClass (WBT Systems) http://www.wbtsystems.com/index.html

Web Course in a Box (WCB) http://www.madduck.com/wcbinfo/wcb.html

WebCT http://www.webct.com

Web Mentor http://avilar.adasoft.com/avilar/msubwm.htm

FIRSTCLASS

Collaborative Classroom

http://www.education.softarc.com




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Mentorware Enterprise

Education Server

http://www.mentorware.com

CONVENE http://www.convene.com

BlackBoard http://www.blackboard.com/

Click2Learn http://www.click2learn.com/

Docent http://www.docent.com/

IntraLearn http://www.intralearn.com/

Moodle http://moodle.org

eduGate http://www.thembaclup.com

Saba Software Inc. http://www.saba.com/

SystemSoft http://www.systemsoft.com/

In order to provide a different approach to online education

applications and suggest alternative solutions to the software handicaps, a

Virtual Class Automation has been established to be used in Firat University

Distance Education Center (FU-UZEM). In this automation, an ergonomic

platform was targeted that is easy-to-use by both students and educators.

With the standard knowledge of computers and internet applications, the

educator can produce his or her class in an internet environment in a logical

step by step manner. The instructor can make various variables such as

project, class syllabus, and text book sources available to his/her students

and can receive feedback from the students.

FU-UZEM Software of Virtual Class Education Center

In accomplishment of distance education, the automation of the

composed distance education interface has a significant role. Ergonomics

and safety and design methods are very important in determining the

lectures given and the classes, arranging the contents of lectures and the

authorization, holding examinations and defining the test techniques of the




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exam questions in all the states of distance education.

According to the design principles of Intercollegiate Communication

and Information Technology Higher Education standing orders, the major

characteristics of software are:

1. It provides the professor the ability to set up options, to create

his/her page step by step and to open lectures to his/her name just with the

knowledge of basic computer usage.

2. It gives the option (to students and the professors) of making

corrections in their page or adding information with their passwords

whenever they want.

3. All the information about the students is recorded to the student

list showing the date and hour they attend the class so that students can

follow the lectures.

4. In a package which is formed about the lecture, there is a

detailed communication page. In this page there is a virtual café (as a chat

room), e-mail lists, argument groups and message boards. By this way,

offline and online communication is performed.

5. There‘s an exam schedule to achieve midterms, finals, make-up

examinations and tests. The participants can take the exams in one center or

by going to other defined regions. The exams can be achieved

synchronously or asynchronously by the centers which the participants are

present at.

6. There is a system director to solve all the problems. Except the

help menus which explain the usage of the program, there are connections to

send messages to system director on shared pages (Turel 2003).

Software Technology




331

In web pages, the HTML language is enough for one sided (static)

data edition. But if processing of the data is purposed by getting information

from user, database or another application, different software languages

such as ASP, PHP, JSP, Pearl, CGI or ASP.NET are needed. For execution

software, these languages are compared and PHP language is preferred

(Ullman 2001; Microsoft Pres 1988; Holzschlag 2004).

1. PHP is a C-based language. It is very simple and its command

library is very rich.

2. It runs across with no problem in most platforms such as

Windows, UNIX, OS/2 and Macintosh.

3. It works seamlessly with nearly all databases.

4. It is distributed freely because it is open source coded. Thereby

its development is faster and it becomes easy to eliminate the errors.

5. PHP works faster when it is compared to other languages. When

it works with a MySQL database, it works 10 times faster than its rival ASP.

6. It gives the opportunity to work with different web servers. For

example, it works easily with Apache, PWS, Xitami. The Apache web

server configuration is the most common.

After the selection of the language, it is required to define the web

server on which the automation works. One of the Unix-Apache, Windows-

IIS (PWS) or Windows-Apache pairs can be easily used with PHP. The

created software is adaptable to both Apache and IIS (Internet Information

Service).

The database has to keep in order all the data in the system, also it

has to have in stock all the commands needed. MySQL can respond to all

these expectancies. It is very easy to use and it has a very high performance




332

when it works with PHP (phpturkiye 2005; turk-php 2005)

Beside the fundamental elements of software, different programs are

used to make the usage of some codes, designs and processes easier and

faster. As an editor, applications like Microsoft FrontPage, Macromedia and

Dreamweaver MX are used to provide the visual sides of web pages in

HTML format, also PHPEd is used to write the codes of PHP language. In

all the processes about data records, software PhpMyAdmin is used, because

it is very fast and gives the opportunity to interface the database directly.

The animations are created by Macromedia Flash MX and the writing

effects are created by Swish 2.0. To increase the efficiency of visual

materials and to provide the optimization of photos and images, Adobe

Photoshop Software is used.

The Design of Virtual Class Automation

In designed automation systems in general, it is aimed that the

professor can open the lectures according to his workspace, enrich them

with the materials he has and use the internet components. The students also

can be registered for the lessons in the system and select one of the opened

lectures in virtual campus and attend these lectures. It is necessary to create

the most efficient but simplest platform for the professors and the students

to use the system without any problem. Also it is considered that the

technique characteristics of the computers of the professors and the students

can be under the standards so that an automation can be setup which works

easily in low speed connections and low configurations.

The design of the system is proposed in 4 basic modules so that

every part can develop independently. These are management module,

lecture presentation module, communication module and exam module.

Management Module




333

Most of the elements such as announcements, notices, schedules,

explanations, guidance, aid and lecture materials are added to the system

with the help of this module. Shared lectures, classes and the security

procedures are actualized by the director‘s approval. Users can reach the

information as their terms of reference. Also the changing, updating or

deleting of the information can be made by director or professor.

Lesson Presentation Module

By means of this module, the raw knowledge and materials

produced by the experts of that area and teachers are transferred to the

virtual environment by the web designer team/individuals according to

pedagogic formations.

Communication Module

All the communications in the class are provided by means of this

module. To keep active the relations between the tutor and student or

student and student in or out of the lecture, there are e-mails, e-mail lists,

argument groups and forums, chat rooms and class notebooks (Varol and

Turel 2003).

Exam Module

A developed system which provides taking exams on web pages

works integrated with the designed automation. The professor has the

chance to save questions about his lectures in a database. These questions

can be divided according to their subjects and grade distribution. The system

selects recorded questions according to subject distribution randomly and

holds examinations. Exams are executed in defined centers for security.

When the students signs up, they can see their grades and which exams they

have to take (Varol and Karabatak 2002).

Examples of Application




334

There are 4 types of users in automation: administrator, professor,

student and the guest. According to the user type, at registration, all the data

is recorded to the system by using the connections of ‗student registration‘

and ‗professor registration‘ where user name and password are defined.

Figure 1. Home Page of Virtual Classroom

After the data is entered into the 'name and password entry area' as

in Fig.1, the user is known automatically and directed toward the requested

page. Cookies can solve the problems caused by unauthorized entries and

the security problems which are caused by the system timing out. If nothing

is entered for a period of time, the user has to enter his name and password

again. As shown in Fig.2 and Fig.3, the page opens according to the user

type entered.




335

Figure 2. Students’ Access Page

Figure 3. Instructors Access Page

If the professor wants to open a course about his field of knowledge,

he has to fill in the 'Course Demand Form'. The course is opened if the unit

which examines the course demand form, finds it acceptable. This allows




336

the 'Open Course' link to become active (Fig.4).

Figure 4. Course Application Menu

The ‗open course‘ link provides entry to the section which allows

the professor to set up the course step by step. In this section, the course

opening form which includes the general information about the lessons,

source adding pages, and the materials about the lessons (as a file) are saved

respectively. The pages such as lesson content adder (Fig.5), the

announcement adder and useful links are completely customizable to the

tutor. In these pages, generally a standard settlement is preferred for

simplicity. Adding of data on the upper side, in the middle and on the lower

side is possible. The ability to delete data according to the entered number

of registrations is provided. Professor can edit this not only before the

course but also after the course begins. The students can also see the lists on

these pages, but don't have the ability to delete data.




337

Figure 5. Course Content Menu

After the professors' requests, administrator adds all the courses to

the system by the help of the form shown in Fig.6. It is necessary to fill in

the registration form for all users.

Figure 6. Adding Course




338

After this procedure is done and all the data about the course is

entered by the teacher, the student or teacher selects the correct course box.

Then a web page opens. In Fig.7, a student course page is shown as an

example. Here, the students can view the data entered, but the teacher has

the opportunity to edit, delete or add registrations. Students can reach the

data for the resources, lesson contents, announcements and connections by

using the buttons on this page.

During or after the registration, the data, directly entered or

automatically generated, is saved in a table. The database defined as

FIRATWEB includes the tables which are shown in Fig.8.

Figure 7. Links Page




339

Figure 8. Databases and Tables

Conclusions

It is possible to make huge reforms in education due in part to new

developments in technology. Online education has the capacity to overcome

many problems of the general system such as inequality of opportunities,

time and location limitations, not meeting the needs of the individuals,

communication restrictions and not being able to offer special teaching

styles to fit the learning speed and style of the individuals. By means of the

internet, audio and video communication can be established. Elements such

as sound, text, animation and graphics can be used to make learning a more

efficient and enjoyable process. The active participation of the individual

can be achieved by e-mail, forum or chat rooms. As a result, it may be

possible to educate the people more freely and give them more self-

confidence to allow them to express themselves openly.




340

One of the required elements of online education is a safe, easy-to-

use and effective automation that enables the application of the system. The

purpose of this study is to answer the online education software needs in

Turkey by the developed virtual class automation and therefore contribute to

the studies in this field. The software consists of four sections; management,

lesson presentation, communication and examination. These sections can be

developed independent of each other; however, they work together as an

integral combination at the same time. The presentation of the lesson

through the internet and the organization of classes and users are completely

undertaken by the automation and the users are able to accomplish their

tasks easily with simple menus. By establishing responsible groups to

conduct surveys and evaluate them objectively, the system will constantly

improve in this area. Furthermore, creating an effective and faultless

automation depends on the team work of people who are experts in their

field as well as experienced in distance education systems. The team must

include field experts, educational designers, web designers and system

administrators. It is a must to have a qualified and serious team work to

apply a good quality distance education. Not only universities but also other

educational institutions must work on web based education, give pace to

their studies on this field and put the necessary effort to develop and spread

this type of automation systems in other links of the education chain as well.




341

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Fuarı. 16-18 October 2002. Sakarya University, MEB Egitim

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http://www.tojet.net/articles/216.htm




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ÖzgeçmiĢ

Research Assistant Yalın Kılıç TÜREL

He was born in Elazığ in 1978. After he had

completed his high school education in Elazig, he

studied at Firat university, technical education

faculty, department of computer teaching between

1995-99 years. He got his master degree in 2003

after he had completed computer software master

programme at Firat University, Graduate School of Natural Applied

Sciences. He had been assigned to Kartal Vocational and Technical High

School as a computer teacher in 1999. After then, he was assigned to Elazig

Gazi Vocational and Technical High School in 2001 and he had worked as a

computer teacher and chief of department of computer for three years. He

has been assigned to Firat University, Educational Faculty, department of

Computer Education & Instructional Technology as a research assistant in

2004. He is married and have a son.

Prof. Dr. Asaf VAROL

1954 Yılı‘nda Elazığ‘da doğdu. 1972-73

yıllarında Almanya‘da dil eğitimi ve mesleki staj

çalıĢmalarını tamamladı. 1976 Yılında Federal

Almanya‘da (IAESTE) staj yaptı. 1977‘de Fırat

Üniversitesinden lisans ve 1979‘da Ġstanbul Teknik

Üniversitesinden (ĠTÜ) yüksek lisans dereceleri aldı.




344

1981-82 yıllarında Karlsruhe Üniversitesinde (Almanya) doktora

çalıĢmalarının deneylerini tamamladı (DAAD). 1983 de Karadeniz Teknik

Üniversitesinden ―Doktor‖ unvanını aldı. 1990 Yılı‘nda YÖK/Dünya

Bankası Projesi kapsamında Indiana ve Purdue Üniversitelerinde Bilgisayar

Sistemleri konusunda akademik çalıĢmalara katıldı. 1991 yılında ―Doçent‖

unvanı aldı.

1992 de Salford ve Bradford (UK) Üniversitelerinde ve 1995‘de

Oklahoma State Üniversitesinde (US) biliĢim alanında akademik çalıĢmalar

yaptı.

1997‘de Bilgisayar Sistemleri Eğitimi Anabilim Dalında ―Profesör‖

unvanını aldı. 1998 yılında Bremen Üniversitesi‘nde (Almanya) Robotik

alanında çalıĢmalar yaptı.

2000-2005 yılları arasında Fırat Üniversitesi ĠletiĢim Fakültesi

Dekanlığı görevinde bulundu. Halen West Virginia Üniversitesinde (ABD)

Robotik ve biliĢim alanlarında çalıĢmalar yapmaktadır. Evli ve iki çocuk

babasıdır. Almanca ve Ġngilizce bilmektedir. Mesleki alanda 8 kitabı ve

160‘ın üzerinde yurtdıĢı ve yurtiçinde yayınlanmıĢ makaleleri ve bildirileri

bulunmaktadır.

Türel, Y., Varol, A.: ―Sanal Sınıf Eğitim Merkezi Otomasyonu‖, BILTEK

International Informatics Congress, Proceedings CD, June 12-14, 2005, EskiĢehir

345

2.11. SANAL SINIF EĞĠTĠM MERKEZĠ OTOMASYONU

Prof. Dr. Asaf VAROL

West Virginia University, US College of Engineering&Mineral Resources

[email protected] (üniversitedeki e-postanızda yazılabilir)

ArĢ. Gör. Yalın Kılıç TÜREL

Firat University,Faculty of Education, Department of Computer and Instructional

Tech. Elazığ [email protected]

Özet

Üniversiteler, kurdukları Uzaktan Eğitim Merkezleri ile eğitim

hizmetinin daha geniĢ kitlelere ulaĢtırılması yönünde çalıĢmalar

yapmaktadır. Özellikle bilgi ve iletiĢim teknolojilerinden yararlanarak

eğitim-öğretim faaliyetlerinin, her zaman ve her yerde herkese

sunulabilmesini sağlayan bir eğitim anlayıĢı ile uzaktan eğitim yeni bir

boyut kazanmıĢtır. Çevrimiçi eğitim ve öğretim sayesinde eğitim sürecinin,

zaman ve mekândan bağımsız olarak gerçekleĢebilmesini sağlayan sanal

sınıflar, geleneksel sınıflarda kullanılması mümkün olmayan veya sınırlı

olarak kullanılabilen birçok bileĢeni kullanılabilir hale getirmiĢtir. Sanal

sınıflarda, eĢzamanlı veya eĢzamansız eğitim verilebilmekte, günün her

saatinde çeĢitli iletiĢim araçlarını kullanarak öğrenci-öğrenci, öğrenci-

öğretmen veya gruplar arası etkileĢim mümkün olabilmektedir.

Anahtar Kelimeler: Çevrimiçi Eğitim, Sanal Sınıf, Ġnternet

Destekli Öğretim

Abstract

mailto:[email protected]




346

With their Distance Education Centers, universities are working on

spreading their education services to wider recipients. Distance education

has gained new dimensions with the principle of making educational

activities available to everyone, everywhere at any time, by using the

information and communication technologies in particular. Thanks to online

education and teaching, virtual classes that enables education regardless of

time and place, have made the use of many variables possible which, could

not be used or had a limited use in traditional classes. In virtual classes,

education can be provided synchronous or asynchronous. By using various

communication tools, student-to-student, student-to-teacher interaction as

well as interaction within groups can be enabled at any time of the day.

Key Words: On-line Education, Virtual Class, Web-based

Education

1. GĠRĠġ

Geleneksel öğretime alternatif olarak sunulan uzaktan eğitim,

biliĢim teknolojilerinin geliĢimiyle önemini daha da artırmıĢtır. Ġnternet‘in

çok hızlı bir Ģekilde yaygınlaĢması, uzaktan eğitimin altyapısında da

kullanılabilmesini sağlamıĢtır. Ġnternet, yazılı, sesli ve görüntülü iletiĢim ve

etkileĢime imkan verdiğinden, bilgiye ulaĢmanın yanı sıra, sahip olduğu

donanımla etkili ve verimli bir eğitim-öğretim ortamının düzenlenebilmesine

de olanak tanımaktadır. Ġnternet‘in eğitim amaçlı kullanılması farklı

kaynaklarda Ġnternet Destekli Eğitim, Ġnternet‘e Dayalı Eğitim, Web Tabanlı

Eğitim ve Çevrimiçi (On-Line) Eğitim gibi birbiri yerine kullanılabilen, ama

aynı amaca hizmet eden kavramların oluĢmasını sağlamıĢtır. Dale, yaĢantı

konisi ile öğrenme yaĢantılarının kalıcı-izli bir davranıĢ değiĢtirme sürecine

katkısını açıklarken; iĢleme katılan duyu organı sayısı, bireyin yaparak-



347

yaĢayarak öğrenmesi ve basitten-karmaĢığa, somuttan-soyuta bir programlı

öğretim Ģeklinin benimsenmesi gibi olguların önemine değinmiĢtir (Çilenti,

1988). Ġnternet ise bireylerin, metin, grafik, hareketli resim, ses, animasyon,

video klip vb. bileĢenlerle çoklu ortam uygulamalarına, e-posta, FTP,

tartıĢma grupları, beyaz tahta, forum gibi uygulamalarla öğrenme

etkinliklerine bireysel veya grupsal olarak katılımına ve aĢamalı hazırlanmıĢ

ders materyalleri ile öğrenme hızıyla orantılı olarak bir geliĢim

gösterebilmesine yardımcı olur (Demirel, Seferoğlu, Yağcı, 2003). Ġnternet

içindeki bu yapılardan günümüzde üniversitelerde ağırlıklı olmak üzere tüm

öğretim kurumlarında özellikle de uzaktan eğitim kurumlarında

yararlanılmaktadır. Ġnternet tabanlı eğitim ile klasik eğitim arasındaki en

büyük fark, öğretme yöntemleridir (Varol, Varol, 1999). Ġnternet üzerinden

öğretim, hızlı ve etkileĢimli öğrenmeye olanak sağlaması, daha fazla

danıĢmanlık hizmetinin verilmesi, tartıĢma fırsatı sağlaması gibi özellikleri

bakımından öğrenci merkezli, demokratik ve bireysel öğretime dayalı bir

eğitim ortamı olanağı sağlamıĢtır (Keser, Demirkalfa, Göçmenler, ġen,

2001). Ülkemizde Anadolu, Bilgi, Fırat, ĠTÜ, Mersin, ODTÜ, Sakarya gibi

birçok üniversite, çevrimiçi eğitime yönelik çeĢitli uygulamalar

yapmaktadır. Çevrimiçi eğitimin dünyada birçok geliĢmiĢ ülkede olduğu gibi

Türkiye‘de de büyük önem kazanması ve diplomaya yönelik bölümlerin

açılmaya baĢlaması için, oluĢturulan sistemlerde yüksek standartların

hedeflenmesini ve bunun için gereken adımların acilen uygulamaya

konulmasını gerektirir. Çevrimiçi eğitim için ders içeriğinin html sayfası

formatında hazırlanarak hizmete sunulması önemli bir unsurdur ancak tüm

program bundan ibaret değildir (Aslantürk, 1999). Program geliĢtirme

yaklaĢımının tüm öğeleri, çevrimiçi eğitim özellikleri dikkate alınarak

ihtiyaç analizinden değerlendirmeye kadar uzman kiĢilerden oluĢan bir ekip

tarafından titizlikle oluĢturulmalıdır.



348

2. SANAL SINIF ve DERS YÖNETĠM SĠSTEMĠ

YAZILIMLARI

Çevrimiçi eğitimin uygulamaya konulmasında sistemin etkili ve

verimli olarak çalıĢmasını sağlayan otomasyon, Sanal Sınıf (Virtual Class),

Ders Yönetim Yazılımı veya Yönetim Sistemi Yazılımı (Learning

Management Systems-LMS) gibi adlarla tanımlanabilir. Bu tür sistemlerin

tasarımı ―Öğretim Tasarımı‖ ilkelerine göre gerçekleĢtirilir. Bir alan olarak

―Öğretim Tasarımı‖ (ÖT); öğrenmeyi sağlamak için özel öğretim etkinlikleri

düzenleyen, hedefleri, içeriği ve uygulamaları belirleyen organize edilmiĢ

prosedürler (iĢlemler) olarak ifade edilebilir (Ġpek, 2003, Ġpek, 2002).

Öğretim tasarımı sürecinde genellikle analiz, tasarım, geliĢtirme, test etme,

yayınlama, değerlendirme ve düzeltme aĢamaları dikkate alınmaktadır

(Gustafson, Branch, 1997). Bugün Uzaktan Eğitim, mevcut TV tabanlı

eğitim haricinde internet destekli olarak web sayfaları ve özellikle bu amaca

yönelik olarak hazırlanmıĢ Uzaktan Eğitim Platformları ile

yayınlanmaktadır. Bu platformlarda aranan özellikler; öğrenci veya

sınıfların veritabanına kolay kayıt edilmesi, her tür elektronik eğitim

materyalinin yayımına uygun olması, dönüt sağlayacak raporlama

özelliklerinin olması, öğrencilerin eğitim aĢamalarının takip edilebilmesi ve

öğrenci ihtiyaçlarına cevap verebilmesi, sınav ve değerlendirme birimi

olarak belirtilebilir.

Pek çok teknoloji firması veya üniversitelerin özel gayretleriyle

oluĢturulmuĢ ―Sanal Sınıflar‖ veya ―Yönetim Sistemi Yazılımları‖

bulunmaktadır. Uzaktan eğitim çözümlerinde bedelleri pahalı olan ve IBM,

Microsoft gibi büyük firmalar tarafından (Lotus LearningSpace, WinClass,

WebCT vb.) yazılan paket programlar kullanılmaktadır. Bu programlar

genelde yurtdıĢı eğitimlere uygun olarak hazırlandığı için, eğitim

sistemimizin gereksinimlerini bire bir karĢılayamayabilmektedir. Nitekim



349

Uzaktan Eğitim‘de belirli bir mesafe almıĢ olan ODTÜ Enformatik

Enstitüsü önceleri hazır paket programlar alıp kullanırken, yazılımların

gereksinimlerine cevap vermediğinden, kendi yapılarına uygun NET-

CLASS isimli yeni bir yazılımı ĠDE_A yani ―Ġnternet Destekli

Eğitim_Asenkron projesi‖ adı altında uygulamaya koymuĢtur (ODTU,

2005). Böyle bir programın oluĢturulmasında Türk Üniversiteleri içinde ilk

kez ODTÜ bir özel kurumla ortaklaĢa ticari bir protokole imza atmıĢtır.

Sakarya Üniversitesi de IBM firması ile iĢbirliği yaparak uzaktan

eğitim yapmak isteyen üniversitelere, yazılım hizmeti vermektedir. Sakarya

Üniversitesi, IBM firmasına ait Lotus LearningSpace programının

ihtiyaçlarını karĢılayacak ve düzenlenmeye müsait olduğunu görerek,

Temmuz 2000 de uzaktan eğitim çalıĢmalarını baĢlatmıĢtır. Hazırlanan proje

çerçevesinde, her iki üniversitemizde de üyeleri Bilgisayar, Endüstri,

Makine Mühendisleri ve Matematikçilerden meydana gelen Ġnternet

Destekli Öğretim Grupları oluĢturulmuĢtur. Üniversitenin kendi içindeki

öğretim üyelerinden oluĢan bir teknik heyet ile anlaĢma imzalanan firmanın

oluĢturduğu heyet çalıĢmaları ortaklaĢa yürütmektedir. Bu grupta yer alan

öğretim üyeleri de alanlarında ayrıca eğitime alınmıĢtır. Sanal sınıflar veya

Windows tabanlı ortamlarda ders hazırlama ve sunum özelliklerine sahip

bazı program ve adresleri Ģunlardır:

PROQUEST http://www.umi.com/proquest

Copyright Clearance

Center, Inc.(CCC)

http://www.copyright.com/About/default.html

Learning Space http://www.lotus.com/learningspace

TopClass (WBT Systems) http://www.wbtsystems.com/index.html

Web Course in a Box

(WCB)

http://www.madduck.com/wcbinfo/wcb.html

WebCT http://www.webct.com



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Web Mentor http://avilar.adasoft.com/avilar/msubwm.htm

FIRSTCLASS

Collaborative Classroom

http://www.education.softarc.com

Mentorware Enterprise

Education Server

http://www.mentorware.com

CONVENE http://www.convene.com

BlackBoard http://www.blackboard.com/

Click2Learn http://www.click2learn.com/

Docent http://www.docent.com/

IntraLearn http://www.intralearn.com/

Moodle http://moodle.org

eduGate http://www.thembaclup.com

Saba Software Inc. http://www.saba.com/

SystemSoft http://www.systemsoft.com/

Tablo-1. Ders Yönetim Sistemi / Sanal Sınıf Yazılımları (Aslantürk, 1999)

Çevrimiçi eğitim uygulamalarına farklı bir yaklaĢım ve bakıĢ açısı

getirebilmek, bu alandaki yazılım eksikliğine alternatif çözümler sunabilmek

amacıyla, Fırat Üniversitesi Uzaktan Eğitim Merkezi (FÜ-UZEM)

bünyesinde kullanılmak üzere, bir Sanal Sınıf Otomasyonu

gerçekleĢtirilmiĢtir. Otomasyonda, gerek öğretim üyelerinin gerekse

öğrencilerin çok rahat ve kolay kullanabileceği ergonomik bir platform

hedeflenmiĢtir. Standart bilgisayar ve Ġnternet kullanım bilgisi ile öğretim

üyesi, dersini Ġnternet ortamında adım adım oluĢturarak, proje, ders

programı, ders kaynakları gibi birçok bileĢeni bu ortam aracılığıyla

öğrencilerine ulaĢtırabilmekte, öğrencilerden geri dönüt alabilmektedir.

3. FÜ-UZEM SANAL SINIF EĞĠTĠM MERKEZĠ YAZILIMI

Uzaktan eğitimde oluĢturulacak arabirimlerin otomasyonu,

uygulanan uzaktan eğitimin baĢarısında önemli rol oynamaktadır. Uzaktan



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eğitim yoluyla verilecek derslerin ve sınıfların belirlenmesi, içeriklerin

uygun Ģekilde düzenlenmesi, yetkilerin ayarlanması, sınavların yapılması,

sınavlardaki soruların hazırlanmasında kullanılan test tekniklerine kadar;

tüm evrelerde ergonomi, güvenlik ve uygun tasarım yöntemleri çok önemli

hususlar olarak karĢımıza çıkmaktadır.

Üniversitelerarası ĠletiĢim ve Bilgi Teknolojilerine Dayalı Uzaktan

Yükseköğretim Yönetmeliği‘nde belirtilen tasarım ilkelerine bağlı kalarak

oluĢturulan yazılımın baĢlıca özellikleri Ģunlardır:

- Öğretim Üyesinin; sadece temel bilgisayar kullanımını bilerek,

çıkacak seçenekleri iĢaretlemesi ve adım adım kendi sayfasını oluĢturmasını,

kendi adına dersler açabilmesini sağlar.

- Öğretim üyelerine ve öğrencilere verilen kullanıcı adı ve Ģifre

sayesinde, istediğinde kendi sayfalarına girerek gerekli düzeltmeleri

yapmaları ve bilgi ekleyebilmeleri sağlanmıĢtır.

- Tüm sınıfın listesine öğrencilerle ilgili tüm bilgilerin yanı sıra

derse hangi tarihlerde ve saatlerde girdiği kayıt edilerek, öğrenci takibi

sağlanır.

- Dersin adına oluĢturulan paket içinde detaylı bir iletiĢim sayfası

bulunmaktadır. Bu sayfada sanal bir kafe (sohbet odası), e-posta listeleri,

tartıĢma grupları, mesaj tahtaları oluĢturulmuĢtur. Böylelikle çevrimiçi ve

çevrimdıĢı bir iletiĢim gerçekleĢmektedir.

- Öğrencilerin vize, final, bütünleme ve deneme sınavlarını

gerçekleĢtirmek için bir sınav modülü vardır. Katılımcılar sınava ya tek bir

merkezde ya da belirlenmiĢ bölgelere giderek katılabilir. Sınavlar eĢ zamanlı

veya eĢ zamansız olarak katılımcıların bulundukları yerlerdeki bilgisayarlar

vasıtasıyla gerçekleĢtirilebilmektedir.



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- Sistemde tüm problemleri çözebilecek bir sistem yöneticisi

bulunmaktadır. Programın kullanımını açıklayan yardım menüleri dıĢında

ortak sayfalar üzerinden de sistem yöneticisine mesaj göndermek için

bağlantılar vardır (Türel, 2003).

3.1. Kullanılan Yazılım Teknolojisi

Web sayfalarında sadece tek taraflı yani statik bir bilgi yayını için

HTML dili yeterlidir. Fakat web sayfasında kullanıcıdan, veritabanından ya

da baĢka bir platformdan bilgi alınarak bu bilginin iĢlenmesi amaçlanıyorsa,

dinamik web sayfası için ASP, PHP, JSP, Pearl, CGI veya ASP.NET gibi

farklı programlama dillerinden birine gereksinim duyulur. Uygulama

yazılımı için bu dillerin karĢılaĢtırılması yapılmıĢ ve PHP dili tercih

edilmiĢtir (Ullman, 2001, Microsoft Pres, 1988, Holzschlag, 2004).

PHP, kullanımı kolay, C tabanlı bir dildir. Komut kütüphanesi

oldukça zengindir.

Windows, Unix, OS/2, Macintosh gibi platformlarda sorunsuz

çalıĢır.

Bilinen veritabanlarının tamamına yakını ile birlikte sorunsuz

çalıĢabilir.

Açık kaynak kodlu (Open Source) olması nedeniyle; ücretsiz

dağıtılır. Böylece geliĢtirilmesi ve hatalarının giderilmesi çok daha hızlı

olur.

PHP, diğer dillere göre çok hızlı çalıĢır, veritabanı olarak MySQL

ile birlikte çalıĢırsa, en yakın rakibi ASP‘den en az 10 kat daha yüksek bir

hıza ulaĢır.

Farklı web sunucuları ile de birlikte çalıĢabilme özgürlüğünü

kullanıcılara vermektedir. Örneğin IIS, Apache, PWS, Xitami gibi herhangi



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bir sunucu ile rahatlıkla çalıĢabilir. Fakat yaygın olarak Apache web sunucu

ile kullanılır.

Dil seçiminden sonra, otomasyonun çalıĢacağı web sunucusunun

belirlenmesi gerekir. PHP ile birlikte Unix-Apache, Windows-IIS (PWS) ya

da Windows-Apache ikililerinden herhangi biri rahatlıkla kullanılabilir.

OluĢturulan yazılım, hem Apache hem de IIS (Internet Information Server)

ile uyumlu çalıĢabilecek Ģekilde düzenlenmiĢtir.

Veritabanı, sistemdeki tüm bilgileri düzenli bir Ģekilde

saklayabilmeli, aynı zamanda verilerin iĢlenebilmesi için gerekli komutları

bünyesinde bulundurabilmelidir. MySQL, bu beklentilere cevap verebilen,

kullanımı oldukça kolay ve PHP ile çok yüksek performans gösteren bir

veritabanıdır (phpturkiye, 2005, turk-php, 2005).

Yazılımın ana öğeleri yanında, kodların, tasarımın ve bazı iĢlemlerin

daha hızlı ve kolay geliĢmesini sağlayan çeĢitli programlar kullanılmıĢtır.

Editör olarak, web sayfalarının görsel bölümlerinin HTML formatında

oluĢturulmasını sağlayan Microsoft Frontpage ve Macromedia

Dreamweaver MX gibi uygulamalar, PHP dilinin kod yazımlarında ise

PHPEd editörü kullanılmıĢtır. Veritabanına doğrudan müdahale imkanı

vermesi ve hızlı çalıĢması sebebiyle veri kayıtlarıyla ilgili tüm iĢlemlerde

PhpMyAdmin yazılımı kullanılmıĢtır. Sayfalardaki animasyonlar

Macromedia Flash MX, yazı efektleri ise Swish 2.0 programlarıyla

gerçekleĢtirilmiĢtir. Görsel malzemenin etkinliğini artırabilmek, resim ve

fotoğrafların optimizasyonunu sağlamak için Adobe Photoshop yazılımı

kullanılmıĢtır.

4. SANAL SINIF OTOMASYONUNUN TASARIMI

Tasarlanan otomasyon sisteminde, en genel anlamda öğretim

üyesinin kendi çalıĢma alanına uygun seçtiği dersleri açabilmesi, bu dersleri



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elindeki materyallerle ve Ġnternet bileĢenleri desteği ile zengin bir yapıya

kavuĢturması amaçlanmıĢtır. Öğrenciler de tıpkı öğretim üyesi gibi sisteme

kayıt yaptıracak ve bu sanal yerleĢkede açılmıĢ derslerden seçim yaparak, bu

derslere devam edebileceklerdir. Öğretim üyesi ve öğrencinin sistemi rahat

ve sorunsuz kullanabilmesi için mümkün olan en basit ama en iĢlevsel

platformu oluĢturmak Ģarttır. Ayrıca, sistemi kullanacak öğrenci ve

öğretmen bilgisayarlarının teknik özelliklerinin, standardın altında

olabileceği düĢünülerek, düĢük hızlı bağlantılarda ve düĢük konfigürasyonda

kolaylıkla çalıĢabilecek bir otomasyon hazırlanmıĢtır.

Sistem tasarımı, dört temel modül halinde düĢünülmüĢ böylece her

kısmın bağımsız geliĢimine imkan verilmiĢtir. Bunlar yönetim modülü, ders

sunum modülü, iletiĢim modülü ve sınav modülüdür.

4.1. Yönetim Modülü

Duyuru, ilan, ders programı, açıklamalar, yardım, kılavuzlar, ders

materyalleri gibi bir çok öğe, bu modül yardımıyla sisteme dahil olur.

Derslerin paylaĢımı, sınıfların oluĢturulması ve güvenlik iĢlemleri yönetici

onayıyla gerçekleĢir. Kullanıcılar, girilen bilgilere yetkileri ölçüsünde

ulaĢabilir. Ayrıca, bilgilerin değiĢtirilmesi, güncellenmesi ve silinmesi de

yönetici ya da öğretmen tarafından yapılabilmektedir.

4.2. Ders Sunum Modülü

Bu modül aracılığıyla, konu alan uzmanları veya öğreticilerin

oluĢturduğu ham bilgi ve materyaller, web tasarım ile ilgili kiĢi ya da ekip

tarafından pedagojik formasyona uygun olarak sanal ortama aktarılır.



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4.3. ĠletiĢim Modülü

Sınıf içindeki her türlü iletiĢimin sağlanması bu modül üzerinden

gerçekleĢtirilir. Ders içi veya ders harici öğretmen – öğrenci veya öğrenci –

öğrenci iliĢkilerini aktif tutabilmek için e-posta ve e-posta listeleri, tartıĢma

grupları ve forumlar, sohbet odaları ve sınıf defteri gibi araçlarla

donatılmıĢtır (Varol, Türel, 2003).

4.4. Sınav Modülü

Web sayfaları üzerinden sınav yapılmasını sağlayan geliĢmiĢ bir

sistem, tasarlanan otomasyona entegre olarak çalıĢmaktadır. Öğretim üyesi

dersine ait soruları, veritabanına kaydedebilir. Sorular konu bölümlerine ve

puan ağırlığına göre ayrıĢtırılabilmektedir. Sistem, kayıtlı sorular üzerinden

dersin bölümlerine göre rasgele seçim yaparak, öğrenciye sınav

uygulayabilmektedir. Sınavlar, güvenlik açısından belirli merkezlerde

gerçekleĢtirilecektir. Öğrenci, sisteme giriĢ yaptığında hangi sınavdan kaç

puan aldığını, hangi sınavlara girmesi gerektiğini öğrenebilmektedir. Not

çizelgeleri, veritabanından çekilerek, görüntülenebilmektedir (Varol,

Karabatak, 2002).

5. UYGULAMADAN ÖRNEKLER

Otomasyonda dört tip kullanıcı bulunmaktadır: Yönetici (Admin),

Öğretmen, Öğrenci ve Ziyaretçi. Kullanıcı türüne göre sisteme ilk giriĢte

öğrenci kayıt ve öğretmen kayıt bağlantılarını kullanarak tüm bilgilerinin

veritabanına kayıt edilmesini sağlar ve kullanıcı adı ile Ģifresini belirler.



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ġekil 1. Otomasyon Ana Sayfası

ġekil-1 de bulunan kullanıcı adı ve Ģifre giriĢ ekranına girilen

bilgilerden sonra otomatik olarak kullanıcı tanınır ve uygun sayfaya

yönlendirilir. Çerez (Cookie) kullanılması, aynı anda oluĢacak yetkisiz

giriĢleri veya zaman aĢımına bağlı güvenlik sorunlarını çözebilmektedir.

Belli bir süre iĢlem yapılmadığında, kullanıcı tekrar giriĢ yapmak

zorundadır. GiriĢ yapan kullanıcı türüne göre açılan sayfa ġekil-2 ve ġekil-3

de gösterilmiĢtir.



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ġekil 2. Öğrenci GiriĢ Sayfası

ġekil 3. Öğretmen GiriĢ Sayfası

Alanıyla ilgili ders açmak isteyen öğretim üyesinin ders talep

formunu doldurması gerekir (ġekil 4.). Talepleri inceleyen birim uygun

görürse, o ders için izin verir. Böylece öğretmen sayfasındaki Ders Açma

bağlantısı aktif olur.



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ġekil 4. Ders BaĢvuru Ekranı

Ders açma bağlantısı, bir dersin adım adım oluĢturulması için

gerekli bölüme giriĢi sağlar. Burada sırasıyla dersin genel bilgilerinin

girildiği ders açma formu ekranı, kaynak kitap bilgileri ile ilgili kaynak

kitap ekleme ekranı, dersle ilgili dosya halindeki materyallerin

kaydedilebilir. Ders içeriği ekleme ekranı (ġekil 5), istenen duyuruların

eklenebildiği duyurular ekranı ve yararlı bağlantılar ekranı, tamamen

öğretim üyesinin düzenlemesine imkan tanıyan sayfalardır. Bu sayfalarda

genellikle kullanım kolaylığı açısından standart bir yerleĢim tercih edilmiĢ,

üst kısımda bilginin eklenmesi, orta kısımda eklenen bilgilerin listelenmesi

ve en alt kısımda ise girilen kayıt numarasına göre bir bilginin listeden

silinebilmesi sağlanmıĢtır. Öğretim üyesi bu iĢlemleri ders açma iĢlemi

esnasında yapabileceği gibi ders faaliyete geçtikten sonra da düzenleyebilir.

Öğrenci ise sadece bu sayfalarda bulunan listeleri görebilir. Silme ve

değiĢtirme hakkına sahip değildir.



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ġekil 5. Ders Ġçeriği Ekleme Sayfası

Yönetici, tüm dersleri öğretim üyelerinin talep etmesinden önce

ġekil 6‘daki form aracılığıyla sisteme ekler. Tüm kullanıcı iĢlemleri için

‗kayıt formu‘nun doldurulması zorunludur.

ġekil 6. Ders Ekleme Formu



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Kayıt sırasında veya sonradan, doğrudan girilen veya otomatik

olarak üretilen tüm veriler düzenli olarak uygun tablo içerisine kaydedilir.

FIRATWEB olarak belirlenen veritabanı içerisindeki tabloların genel

görünümü ġekil 7‘de gösterilmiĢtir.

ġekil 7. Veritabanı ve Tablolar

6. SONUÇ

Teknolojinin getirdiği yenilikler ıĢığında, eğitimde büyük reformlar

yapmak mümkündür. Çevrimiçi eğitim, geleneksel sistemdeki fırsat

eĢitsizliği, zaman ve mekân sınırlılığı, bireyin ihtiyaçlarına cevap verememe,

iletiĢim kuramama, bireyin öğrenme stiline ve hızına uygun öğretim yöntemi

belirleyememe gibi birçok problemin üstesinden gelebilecek güce sahiptir.

Ġnternet sayesinde sesli ve görüntülü iletiĢim gerçekleĢtirilebilir, öğrenme

sürecinin daha etkili ve zevkli hale getirilmesini sağlayan ses, yazı,

animasyon ve grafik gibi unsurlar kullanılabilir, e-posta, forum, sohbet



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odaları gibi etkileĢim özellikleri ile bireyin sürece aktif katılımı sağlanabilir.

Böylelikle daha özgür, kendine güvenli, fikrini açıkça ifade edebilen ve

kendini geliĢtirebilen bireylerin yetiĢmesine olanak tanınabilir.

Çevrimiçi eğitimde ihtiyaç duyulan bileĢenlerden birisi, sitemin

yürümesini sağlayacak, kullanımı kolay, etkili ve güvenli bir otomasyondur.

Bu çalıĢma sayesinde gerçekleĢtirilen sanal sınıf otomasyonu ile çevrimiçi

eğitimdeki yazılım ihtiyacının giderilmesine ve ülkemizdeki bu alandaki

çalıĢmalara katkı sağlanması hedeflenmiĢtir.

Yazılım; yönetim, ders sunum, iletiĢim ve sınav gibi dört farklı

birimden oluĢmuĢtur. Bu birimler birbirinden bağımsız olarak geliĢtirilebilir

ama aynı zamanda bir bütünlük içerisinde çalıĢmaktadırlar. Bir dersin,

Ġnternet üzerinden verilmesi, derslerin ve kullanıcıların organizasyonu

tamamen otomasyona devredilmiĢ, basit menülerle tüm kullanıcıların,

yapılması gereken iĢi en kolay Ģekilde yapabilmeleri sağlanmıĢtır. Sanal

sınıflarda kalitenin yükseltilmesi için yetkili gruplar oluĢturularak, anketler

uygulanması ve anketlerin bu gruplar tarafından objektif olarak

değerlendirilmesi, bu konudaki çalıĢmalarda sistemi mükemmelliğe

yaklaĢtıracaktır. Ayrıca kusursuz ve etkin bir otomasyonun

oluĢturulabilmesi, ancak alanında uzman ve ayrıca uzaktan eğitim sistemleri

konusunda deneyimli kiĢilerden oluĢan bir ekip çalıĢmasını

gerektirmektedir. Bu ekipte, konu alan uzmanları, öğretimsel tasarımcılar,

web geliĢtiriciler ve sistem yöneticileri bulundurulmalıdır. Kaliteli bir

çevrimiçi uzaktan eğitim uygulaması için kaliteli ekip ve ciddi çalıĢma

Ģarttır. Sadece üniversiteler değil tüm eğitim kurumlarının, web tabanlı

eğitim üzerine yoğunlaĢması, bu konuda çalıĢmalarını hızlandırması ve bu

tür otomasyon sistemlerinin eğitim zinciri içindeki diğer halkalarda da

geliĢmesi ve yaygınlaĢması için gereken çabayı göstermesi gerekmektedir.



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Kaynaklar

(Çilenti, 1988) Çilenti, K. (1988). Eğitim Teknolojisi ve Öğretim. Ankara:

Kadıoğlu Matbaası.

(Demirel,

Seferoğlu,

Yağcı, 2003)

Demirel, Ö., Seferoğlu, S., Yağcı, E. (2003). Öğretim

Teknolojileri ve Materyal GeliĢtirme. Ankara: Pegem

Yayıncılık

(Varol, Varol,

1999)

Varol, A.; Varol, N. ―Bilgi Teknolojilerine Dayalı Uzaktan

Yükseköğretim ve Ders Hazırlama Ġlkeleri Üzerine

Öneriler‖, BTIE'2000, BiliĢim Teknolojileri IĢığında

Eğitim Konferansı ve Sergisi, 15-17 Mayıs 1999, Bildiriler

Kitabı, S: 85-91, Ankara

(Keser,

Demirkalfa,

Göçmenler,

ġen, 2001)

Keser, H., ġen, N., Göçmenler, G. ve Demirkalfa F., ―Web

Tabanlı Öğretim Materyali Hazırlama Sürecinin Temel

Evreleri ve Ġnternet Kullanımına Yönelik Bir Uygulama

Örneği‖. I. Uluslararası Eğitim Teknolojileri

Sempozyumu, 28-30 Kasım 2001, Sakarya

(Aslantürk,

1999)

Aslantürk, O. ―Web Tabanlı Eğitimde Yönetim Sistemi

Gereksinimi ve Bir Web Tabanlı Eğitim Yönetim Sistemi

Yazılımı‖, Akademik BiliĢim 99

http://ata.cs.hun.edu.tr/~aslantur/Publications.htm

(Ġpek, 2003) Ġpek, Ġ. ―Öğretim Tasarımı Sistemleri ve Öğretim

Teknolojisi Alanlarının Bilgisayarla Öğretim Süreci

Yönünden Ülkemizdeki Uygulamaları Üzerine

DüĢünceler‖. Doğu Akdeniz Üniversitesi Uluslararasi

Eğitim Teknolojileri Sempozyumu ve Fuarı, Gazimağusa-

http://ata.cs.hun.edu.tr/~aslantur/Publications.htm



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KKTC, 28-30 Mayis 2003

(Ġpek, 2002) Ġpek, Ġ. ―Uzaktan Eğitimde Farklı Zamanlı-Gecikmeli

ĠletiĢim Konferansının Bilgisayarların BiliĢsel Araçları

Olarak Kullanımı‖, Anadolu Üniversitesi Açık ve Uzaktan

Eğitim Sempozyumu, EskiĢehir 23-25 Mayıs 2002.

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Branch, 1997)

K. L. Gustafson ve R. M. Branch. ―Revisioning Models of

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(ODTU, 2005) ODTU www.idea.metu.edu.tr, 2005

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Bilimleri Enstitüsü

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2001)

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ĠletiĢim Modülü. The Turkish Online Journal of

Educational Technology - TOJET January 2003 ISSN:

1303-6521 Volume 2, Issue 1, Article 6

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Karabatak,

2002)

Varol, A. ve Karabatak, M. (2002). Çevrimiçi Uzaktan

Eğitimde Sınav Otomasyonu, II. Uluslararası Eğitim

Teknolojileri Sempozyumu ve Fuarı (16-18 Ekim 2002),

Sakarya Üniversitesi, MEB Eğitim Teknolojileri, Ohio

University ve Iowa State University ĠĢbirliği Ġle., Sakarya.

Bayrak, C., Çelik, Ġ., Varol, A., ġeker, R., ġakarcan, A., Abdallah, M., Bissada, N.,

Finkbeiner, A.: ―Modeling and Simulation of Urodynamics‖, TASSA Annual

Conference, Proceedings CDs, Drexel University, Philadelphia, PA, 25-26 March

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2.12. MODELING AND SIMULATION OF URODYNAMICS,

CoĢkun Bayrak, Ġsmail Çelik, Asaf Varol, Remzi eker, Abdullah

akarcan, Mohammed Abdallah, Nabil Bissada, and Alex Computer Science

Department, University of Finkbeiner, Arkansas at Little Rock, Little Rock,

AR 72204, Mechanical and Aerospace Engineering Department, West

Virginia University, Morgantown WV 26506, Computer Education

Department, Technical Education Faculty, Frat Universitesi, Elazig,

Türkiye, Department of Pediatrics, University of South Carolina Medical

School, Columbia, SC, Department of Urology, University of Arkansas

Medical Sciences, Little Rock, AR, 72205.

The role of modern medical imaging is not limited to simple

visualization and inspection of anatomic structures, but goes beyond that to

patient diagnosis, advanced surgical planning and simulation, and

radiotherapy modeling. In addition, segmenting and rendering methods

currently plays an effective role in medical imaging. These methods help to

provide more accurate models and simulations especially from digital and

medical images.

Therefore, the focus of this research investigation is to build and

simulate realistic 3D environments of urodynamics to understand the

holding or storage of urine in the bladder, the way the bladder empties, and

the rate of movement of urine out of the bladder during urination. More

specifically we are interested in studying stress incontinence related

problems and provide diagnos tic tools to detect and suggest remedies to

such problems.




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2.13. A ONE DIMENSIONAL MATHEMATICAL MODEL FOR

URODYNAMICS

Ismail B Celik

West Virginia University

Asaf Varol

Firat University, Elazig, Turkey

Coskun Bayrak

University of Arkansas at Little Rock

Jagannath R Nanduri

West Virginia University

ABSTRACT

Millions of people in the world suffer from urinary incontinence and

overactive bladder with the major causes for the symptoms being stress,

urge, overflow and functional incontinence. For a more effective treatment

of these ailments, a detailed understanding of the urinary flow dynamics is

required. This challenging task is not easy to achieve due to the complexity

of the problem and the lack of tools to study the underlying mechanisms of

the urination process. Theoretical models can help find a better solution for

the various disorders of the lower urinary tract, including urinary

incontinence, through simulating the interaction between various

components involved in the continence mechanism. Using a lumped

parameter analysis, a one-dimensional, transient mathematical model was

built to simulate a complete cycle of filling and voiding of the bladder. Both

the voluntary and involuntary contraction of the bladder walls is modeled

along with the transient response of both the internal and external sphincters

which dynamically control the urination process. The model also includes

the effects signals from the bladder outlet (urethral sphincter, pelvic floor

muscles and fascia), the muscles involved in evacuation of the urinary

bladder (detrusor muscle) as well as the abdominal wall musculature. The

necessary geometrical parameters of the urodynamics model were obtained

from the 3D visualization data based on the visible human project.




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Preliminary results show good agreement with the experimental results

found in the literature. The current model could be used as a diagnostic tool

for detecting incontinence and simulating possible scenarios for the

circumstances leading to incontinence.

INTRODUCTION

Urinary incontinence has been reported to affect 35% of American

women over 50 years of age an almost 15% who have leakage on a daily

basis [1]. The common types of incontinence are (1) Stress incontinence (2)

Urge incontinence (3) Overflow incontinence and (4) Functional

incontinence. Approximately 60% of women with incontinence will have

stress incontinence [2] where the urethral sphincter is not able to hold urine

due to weakened pelvic muscles that support the bladder, or malfunction of

the urethral sphincter [3]. Urge incontinence is also a storage problem in

which the bladder muscle contracts regardless of the amount of urine in the

bladder. Urge incontinence may occur without a recognizable prior disease

or may result from neurological injuries, neurological diseases, infection,

bladder cancer, bladder stones, bladder inflammation, or bladder outlet

obstruction [4]. Overflow incontinence happens when there is an

impediment to the normal flow of urine out of the bladder and the bladder

cannot empty completely. Patients with functional incontinence have mental

or physical disabilities that impair urination, although the urinary system

itself is normal [5]. In order to understand and simulate the various

incontinence mechanisms we intend to build a mathematical model to

describe the hydrodynamic processes in the urinary tract.

We first present the anatomy of the human urinary tract. The lower

part of the urinary tract consists of a sack like muscular storage organ called

the bladder, that is found in the pelvis behind the pelvic bone (pubic




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symphysis) and a drainage tube, called the urethra, that exits to the outside of

the body. The bladder is an organ where the urine filtered by kidneys is

stored. The kidneys filter approximately 160 liters of blood a day in order to

maintain the necessary fluid balance. Water makes up approximately 95

percent of the total volume of urine, with the remaining 5 percent consisting

of dissolved solutes or wastes (i.e. urea, creatinine, uric acid and several

electrolytes). Urine is steadily excreted from the kidneys then pumped down

to the ureters to the bladder by means of muscle contractions and the force

of gravity (Figure 1). Once in the bladder, the urine is temporarily stored

until it is voided from the body through the urethra [6].

.

Figure 1 - Normal Male Genitourinary Tract [7]




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(a)

(b)

Figure 2 – Bladder of men (a) and women (b) [8]

The detrusor is a thick layer of smooth muscle which expands to

store urine and contracts to expel urine. The urethra is a small tube which

leads from the neck of the urinary bladder to the outside of the body. In men,

the urethra is approximately 20 cm long. When it leaves the bladder, it

passes downward through the prostate gland, the pelvic muscle and finally

through the length of the penis until it ends at the urethral orifice or opening

at the tip of the glans penis. In women, the urethra is approximately 4 cm

long runs in front of the vagina. The urethral orifice or meatus is the outside

opening of the urethra and is located between the clitoris and the vaginal




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opening [6]. Storage and emptying of urine in the bladder are regulated by

the internal and external urethral sphincters in response to neural signals

under normal circumstances. Sphincters are made up of ring-like band of

muscle fibers that contract or expand to regulate urine discharge. Sphincters

normally remain closed and need stimulation to open [6].

Figure 3 shows the bladder and its nerve systems. During filling of

the bladder with urine, the bladder expands to accommodate urine flow from

the kidneys. After the filling of the reservoir, signals are sent to the brain to

warn that the reservoir is full under normal circumstances voluntary voiding

occurs by sending signals from brain to the bladder to contract to the

external urethral sphincter to open [9]. Detailed mathematical models for

simulating the hydrodynamic processes in the urinary tract are scarce in the

literature. In what follows we briefly review the relevant literature that we

were able to find after an extensive search.

A mathematical model of the male urinary tract was reported by

Kren et al. [10] to model the interaction between the urethra, bladder and

urine flow. In this research, the flow is considered to be non-stationary,

isothermal and turbulent. The elastic properties of the bladder and urethra

have been modeled as a dynamic motion theory and has been created using

D‘Alambert principle. Kren et al. used a finite element mesh for their

numerical solution, and they used an iterative method to solve the problem

of bladder deformation. In this work, the flow is considered to be turbulent.

This phenomenon is questionable because the urinary flows are not always

turbulent (a typical Reynolds number Re=(ρuD)/μ range is 300-4000). Both

kinds of flows (i.e. laminar and turbulent) should be considered for creating

the model. Kren et al. focus mostly on the mathematics and numerical

methods rather than on the actual physics of urodynamics. The authors

demonstrate that the predicted urine discharge rate would be different if the




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urethra walls are treated as compliant rather than as rigid walls. This

conclusion seems to us a trivial outcome. In our opinion, this work is not

complete and more research is required to relate the dynamics of compliant

walls to urodynamics in general.

Figure 3 - The relationships between a bladder and nerve system [9]

According to the reference [7], the normal uroflow changes as

shown in Figure 4. From the figure, it is seen that the maximum volumetric

flow rate doesn‘t go up more than 240 ml/min, but this of course can change

from person to person, and depending on the pressure inside the urethra.

However, the Peak and the average flow is expressed in ml/sec. Generally

normal peak flow in females is over 20 ml/sec and in males >15 ml /sec,

normal flow can be up to 45-50 ml /sec but this is unusual. Voiding time is

defined as the total time from the beginning to the end of the micturition.

The flow time is defined as the total time when urine is actually flowing

(Figure explained by using Laplace‘s equation which relates the wall

tension, T, to the pressure, P, inside the bladder. For a sphere this equation

yields 5). When the uroflow is intermittent or abnormal, the voiding time

and flow time can not be defined precisely [7]. But the International Society

of Continence (ISC) suggested the flow time be calculated disregarding the

time intervals between flow episodes.




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One problem that we found in reviewing of such results in the

literature is that the figures are only given as sketches and they rarely have

time or length scales. This makes the interpretation of the results very

difficult. For example, Figure

6 shows a conceptual pressure distribution as a function of time.

According to this figure, after beginning of the contraction, the pressure goes

up at first and reaches a

P 2T / R (1)

maximum value and later decreases to a level of the pre- micturition

pressure although the contraction continues. The figure does not indicate

how long the filling process continues. Filling period is an important

parameter that should be measured for accurate analysis of the system. It

appears that during the contraction period, the flow rate of the urine has been

taken as constant. This is not realistic because depending on the contraction

rate, the velocity of the urine can change which may then result in an

increase of the flow rate. The urine filtered from the kidneys should also be

a function of time of the day as well as eating and drinking habits of a

person.




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Figure 4 – The diagram of normal uroflow [7]

Figure 5 – Comparing the flow and voiding times [7]

Wang et al. [11] investigated the effect of the hydrostatic pressure on

ion transport in the bladder uroepithelium. They showed that increasing

hydrostatic pressure across the mucosal surface of the uroepithelium is

accompanied by increases in ion transport. If this is true, measured electrical

activity can be used as an indicator of the detrusor pressure.

Figure 7 shows [12] the relationships between the tension and

pressure distribution based on the bladder volume. It is seen that the

increasing of the volumetric flow rate does not mean an increase in the

pressure. This phenomenon can be




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Figure 6 – Flow and Pressure distribution in the bladder

Figure 7 – Tension and Pressure Distribution in the bladder

Equation (1) indicates that as the volume decreases (i.e. the radius R

decreases) the pressure increases for a constant wall tension. It also reveals a

linear relationship between the detrusor force and the bladder circumference

as suggested by Rikken et al. [13]. However the tension in the detrusor

muscles is usually not constant. As revealed by the work of Damaser

[14] the bladder has non-linear elastic, viscous and plastic

mechanical properties. Hence, assuming a constant tension in Eq. (1) may

lead to pressure-volume variation that is contrary to that observed in clinical

trials [15], [16].

Observations [15], [16] indicate that during the filling period, the




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bladder will be expanded; at the beginning, this action will result in a

relatively rapid increase in the pressure of the bladder. As the bladder is

filled there is a mild increase in pressure followed by a rapid increase as the

bladder reaches its capacity. After the voiding begins the pressure decreases

to its normal level and the cycle repeats itself under normal circumstances.

Griffiths et al. [12] obtained pressure data from 32 men with lower

urinary tract symptoms and from 7 asymptomatic volunteers. It is concluded

that non-invasive voiding studies using the cuff inflation technique can

provide useful information on obstruction [12]. On the other hand Pel and

Mastright [17] argue that noninvasive pressure monitoring is, at present, not

sensitive enough for clinical use. The mathematical models we propose to

develop can help interpret the results from non-invasive monitoring better by

expressing pressure, volume and discharge in a functional form.

We believe that fluid dynamic models when used in conjunction with

structural dynamics models have great potential for understanding of many

complex processes that occur in the urinary trat. Such models can also be

used as function of the detrusor tension in a truly non-linear model. In order

to account for voluntary or involuntary contraction of the bladder walls we

model the tension as a sum of volumetric dependence and a voluntary

contraction of detrusor as signaled by parasympathetic nerves. The resulting

equation for the bladder/intravesical pressure is:

diagnostic tools for detecting and finding the cause of

Pb Pref (3)

Pa (3a)

symptoms or patient complaints that are difficult to understand

fimp (3b)




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by simple tests such as cystometrogram (CMG). The lack of Here Pa

is the normal abdominal pressure, is the rigorous mathematical

models and detailed numerical dimensionless volume, is the

dimensionless detrusor tension, simulations in the literature lead us to

propose new computational models for the analysis of urine flow in the and

fimp

is an appropriate impulse function. We denote the lower urinary tract. urine

influx from the kidneys by Qin t which should be

METHODOLOGY

Before any diagnosis can be made of malfunctioning, the

urodynamics of a normal person must be understood well, and the proposed

model must be able to predict the observed behavior of a normal bladder say

during a normal working day. We summarize a conceptual model to this

regard. determined empirically from collected data. This would change with

age, eating and drinking habits; it also changes depending on the time of the

day, and of course, on the condition of the kidneys. The bladder should be

functioning continuously as long as the kidneys function normally, hence the

volume, V of the bladder will be determined by

We postulate that the bladder walls are compliant, that is they

expand and contract to accommodate the volume of liquid

Qin t Qout t (4)

accumulated inside the bladder in a natural manner. This assumption

is based on the fact that the detrusor layer is made of so called ‗smooth‘ cells

that are less sensitive to impulse. There is evidence [18] of incomplete

activation of the detrusor where t is the time, and Qout t is the urine

discharge rate which is the primary unknown to be determined as a function




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of time. When the bladder volume reaches a certain critical value, muscle

during normal voiding. As depicted in Figure 3 the say which is less than the

maximum capacity of the lower urinary track is innervated by three sets of

peripheral nerves involving the pelvic parasympathetic, sympathetic, and

bladder, Vmax a signal should be sent to the brain indicating somatic nervous

systems. The neural signals supplied by this nervous system forms the bases

of a dynamic control mechanism for the urination process. Hence we allow

for the possibility that the bladder can contract in response to stimulation of

the pelvic (parasympathetic) nerve. Moreover, pressure inside the bladder

can be influenced by abdominal pressure which may increase during

coughing or sneezing etc. Further, the tension in the detrusor produces a

stress normal to the bladder walls which we denote as the detrusor pressure,

Pd; this is usually taken as the difference of bladder pressure and urge to

urinate. This signal may result from the detrusor tension reaching a critical

value. During the voluntary waiting period the filling will continue but the

pressure of the sphincter should increase. Voluntary voiding occurs by

detrusor contraction and simultaneous relaxation of the urethral sphincters.

The bladder neck and urethra internal sphincter will open and the urethra

will fill with urine. For the time being we shall assume that this later process

takes place smoothly after the critical volume is reached. Hence the cross-

sectional area of the internal sphincter is given by the abdominal pressure.

The tensile stress in the detrusor layer

Ai sph A0-sph H Vcr Vmin (5)

And Pd are related through geometrical parameters via Laplace where A0-

sph is the area of the internal sphincter at normal law (see Eq. 1). For the

preliminary model we assume that the opening, and H is a unit square wave

function such that when change in the bladder pressure Pbis determined by

theV V V ; H 0 otherwise H 1 or a sinusoidal oscillatory




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compliance equationmi function which can represent intermittent oiding.

dP c cV (2)

Equation 5 indicates that the internal sphincter relaxesdV

Where c and c are model parameters related to the compliance

(1/elasticity) of the tissues that make up the bladder wall structure, is also

a material property which expresses

the non-linear behavior of volume as a response to the detrusor

pressure. The model parameters c and c should also be functions of the

volume (e.g. stretching) itself and implicitly a naturally after receiving a

signal from the spine‘s parasympathetic nerves that there is a need for

urination and contracts when the emptying process is completed. After

opening of the internal sphincter the urethral pressure, Pu, should attain the

same value as the bladder pressure plus some negligible pressure rise caused

by gravity, hence, we write:

Before opening of the internal sphincter

Pu Pu, normal (6)

After opening of the internal sphincter

Pu Pb gh (7)

and is the viscosity of the urine. The necessary geometrical

parameters for the urodynamics model can be obtained from where the

urine density is, g is the gravitation; h is the vertical height from the

external sphincter to the top of the liquid layer inside the bladder. After the

internal sphincter opens, the control is transferred to the external sphincter,

by which the person has the option to prevent micturition (peeing) until an

appropriate time. The increase in the tension of the contracted sphincter ring




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should cause an increase in the bladder pressure through the balance of

forces as related by Laplace‘s equation. A similar pressure change is possible

by regulating the abdominal pressure (see Eq. 3). This pressurethe 3D

visualization of the environment that is based on visible human data sets.

Such data can also be obtained from cystograms. Data from the literature

obtained by way of the CT (Computed tomography), PET (Positron emission

tomography), and MRI (Magnetic Resonance Imaging) can also be used

[20].

In Eq. 9, the tubular area starting from the neck of the bladder and

extending to the external sphincter can change under pressure or as a result

of obstruction. To account for the elasticity of the urethra a constitutive

equation must be formulated such asincrease should not cause any

significant change to the bladder

A f P, , E

(12)volume as the volume of the liquid stored in it is incompressible.

The bladder volume will continue to increase as a result of the influx of

urine filtered through the kidneys.

where P is the pressure inside the tube, is the tube-wall thickness,

E is the modulus of elasticity. In a future study, this will be done following

the model proposed in [25].During this waiting period the pressure,

Pext , sph , exerted by

If the area of the urethra does not change with time,the sphincter

should increase with time. We assume a function of the form Equation 10

simply states that Q does not change with distance. By introducing similar

simplifications Equation

P t P P S (8)




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can be reduced to a balance between the pressure differential,ext , sph b

u ⎜ ⎟ wait ⎠P

Pu Patm ,Patm being the atmospheric pressure, and the Where

Pu

is the maximum pressure that can be exerted urine flow rate,

Q given by

1/ 2by the external sphincter muscles in addition to the normal

⎡ 2 P Pmin ⎤ urethral pressure, t

is the waiting period permissible till the

Q KAext , sph t ⎢ ⎥ (13)wait

⎣ fcor ⎦

urine discharge begins, and S is a function to be determined. After a

reasonable period of waiting the voiding process where

Pmin

is the minimum pressure differential required should start and continue until

the bladder is completely or for initiating flow, K is a discharge coefficient,

partially emptied. The continuation or stoppage of urination is, of course,

under the control of the person under normal circumstances. Hence, the

closing and opening of the external sphincter ring should be a control

function in the analysis given by correction factor that is a function of the

Reynolds number, and the geometrical properties of the urethra and the

external sphincter orifice.

Aext , sph t f t, Pa , Pb , Pext ,sph ,V (9)

After the external sphincter opens, the fluid dynamics of the urine




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flow inside the urethral tube can be analyzed by a one dimensional transient

model that allows compliant tube walls. The equations to be solved are

Conservation of mass:

dt dx (10)

Conservation of Momentum:

dQ

d uQ A dP w (11)

Here x is the distance along the center of the urethral tube, A is the

cross-sectional area of the urethral tube, is the perimeter of the tube-line,

and w is the shear stress exerted by the fluid on the surface of the urethra.

This shear stress can be determined using empirical information for friction

coefficient that is a function of wall roughness and the Reynolds number,

QUANTITY VALUE COMMENT

Max. bladder volume (ml) 800

Min. bladder volume (ml) 16

Min. Pressure (cm of H2O) 100

Ref. Urethral Diameter (mm) 2.5

Urethra Length (cm) 12 – 20




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Discharge Coefficient 0.10

Avg. Urine inflow rate (ml/s)

0.03

~ 35

ml/kg/day

Variable,

defined by a function

Urine Viscosity (kg/m-s) 1x10-3

Exponent γ - 4/3

Exponent m + 2/3

Table 1 – Parameter list for urodynamics model

RESULTS AND DISCUSSION

In what follows we present some preliminary results from a simple

model that is constructed along the lines of the lumped parameter analysis

described above. The physical and geometrical parameters specified for

these simulations areRe uDh , hereDh is the hydraulic diameter of the

tube, listed in Table 1.0. The correction factor fcor was calculated using

laminar pipe flow assumption. The compliance function is prescribed from

the non-linear relation, the pressure reaches a plateau just before the

maximum flow rate is attained, and then falls back to its normal level. The

c ⎛ n ⎞ (14)

simulation results (Figs. 8b & 12) are consistent with

uchobservations. Figure 9 depicts the change in bladder volume as

Where n = -1/3 (i.e. R ∼ V 1/ 3 ) (15)

a function of time. The increase in bladder volume is not linear resulting

from a non-uniform kidney output as prescribed by a sinusoidal function.

The voiding is completed in about half a minute.




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(a)

(b)

Figure 8 – Variation of bladder pressure with time (a), enlarged

(b) near voiding




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Figure 9 – Variation of bladder volume with time (a), enlarged (b) near

voiding

Figure 10 – Typical detrusor impulse function

A complete cycle of filling and voiding process is depicted in

Figures 8 & 9. The pressure variation seen in the initial part of Figure 11a

resembles closely the clinically observed trend [21] [15]. This pressure trend

was obtained by selecting an appropriate impulse function (see Eq. 3b) as

depicted in Figure 10 by trial and error. According to the diagrams shown in

[21]




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Figure 11– Variation of relative sphincter area with time

Figure 12 – Variation of urine outflow with time

The variation of the sphincter area with time is shown in

Figure 11 and the corresponding flow rate through the urethra

is shown in Figure 12. The flow rate curve and the maximum flow

rate of c.a. 30 ml/sec are in agreement with clinical observations [21] [16].

Moreover the flow-rate versus pressure diagram depicted in Figure 11 also

agrees with the average curve as presented in [16]. We have run another case

with urethra length of 20 cm (not shown here) which reduced the maximum

discharge rate to about 20 ml/sec as expected due to frictional loss. This

yielded a 50 second voiding time.

CONCLUSION

We have shown that a mathematical model can be used to simulate

various functions and inter-coupling of different components of the human

urinary tract. The purpose is to demonstrate how mathematical models of




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biological systems such as the bladder works. The key to success for realistic

predictions is the calibration of the critical physiological parameters that are

mentioned above

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2006,

390

367

2. BÖLÜM ĠÇĠNDEKĠLER

2.1. MULTI-PHASE TRANSPORT IN A SIPHON AND JET PUMP SYSTEM. 195 2.2. MODELING AND COMPUTER SIMULATION OF AN AIR

CONDITIONING SYSTEM WITH A COLD WATER STORAGE TANK ......... 209 2.3. VOCATIONAL AND TECHNICAL EDUCATION IN TURKEY:

PROBLEMS AND RECOMMENDATIONS ........................................................ 223 2.4. CONTROL OF TEMPERATURE WITH A ROBOT ..................................... 236 2.5. SORTING COINS WITH DIFFERENT DIAMETERS THROUGH THE USE

OF A ROBOT ......................................................................................................... 244 2.6. VERARBEITUNG VON UNSICHEREM WISSEN MIT FUZZY-PROLOG255 2.7. ANFORDERUNGEN UND LÖSUNGSANSÄTZE EINER

TRANSFERIERBAREN ENTWICKLUNGSUMGEBUNG FÜR DIE

MEDIZINISCHE WISSENSVERARBEITUNG ................................................... 273 2.8. FUZZY EQUIVALENCE OF CLASSICAL CONTROLLERS ..................... 285 2.9. DISTANCE EDUCATION BASED ON A COMBINATION SYSTEM OF

INTERNET AND TELEVISION ........................................................................... 299 2.10. A CASE STUDY: A VIRTUAL CLASSROOM MODEL ........................... 325 2.11. SANAL SINIF EĞĠTĠM MERKEZĠ OTOMASYONU ................................ 345 2.12. MODELING AND SIMULATION OF URODYNAMICS, ......................... 365 2.13. A ONE DIMENSIONAL MATHEMATICAL MODEL FOR

URODYNAMICS................................................................................................... 367

Documents

2. BÖLÜM ULUSLARARASI BĠLĠMSEL …Varol, A.: ―Multi-Phase Transport In A Siphon and Jet Pump System‖, 6th Miami International Symposium On Heat and Mass Transfer, 10-12 December