1. COURSE
SBI3013
INFORMATION & COMMUNICATION TECHNOLOGY IN BIOLOGY
GROUP ASSIGNMENT
SIMULATION AND MODELING
STELLA SOFTWARE
PREPARED BY:
NUR AMALINA BINTI CHE AJID
D20162076166
NURAFIQAH BINTI HAMZAH
D20162076167
NURUL AMIRAH BT RODZI
D20162076159
GROUP: A
PROGRAM
AT11 – ISMP BIOLOGY
CHECKED BY
EN AZMI IBRAHIM
FACULTY OF SCIENCE AND MATHEMATICS
UNIVERSITI PENDIDIKAN SULTAN IDRIS
2. INTRODUCTION
Modeling and Simulation
Model is a representation of an object, a system or an idea in some from other than that of
the entity itself. Two types of model are physical (scale model, prototype plants) and
mathematical (analytical queuing models, linear programs, simulation).
Simulation of system is the operation of a model, which is a representation of that
system. The model is amenable to manipulation which would be impossible, too expensive or too
impractical to perform on the system which it portrays. The operation of the model can be
studied and from these properties concerning the behavior of the actual system can be inferred.
Simulation modeling is the process of creating and analyzing a digital prototype of a
physical model to predict its performance in the real world. Simulation modeling is used to help
designers and engineers understand whether, under what conditions and which ways a part could
fail and what loads it can withstand.
Applications
1. Designing and analysis manufacturing systems.
2. Evaluating a new military weapons system tactics.
3. Determining ordering policies for an inventory system.
4. Designing communication systems and message protocol for them.
5. Designing and operating transportation facilities such a freeways, airports, subways or
ports.
6. Evaluating designs for service organizations such as hospitals, post offices or fast-food
restaurants.
7. Analyzing financial or economic systems.
3. Stella
STELLA (System Thinking Experiment Learning Laboratories with Animation) was
created by Robert Webb of Australia is a computer program that available in three versions
which are Great Stella, Small Stella d Stella4D. The programs contain a large library for
polyhedral which can be manipulated and altered in various way.
Stella is a flexible computer modeling package with an easy, intuitive interface that
allows users to construct dynamic models that realistically simulate biological systems. The
program, distributed by ISEE systems (formerly High Performance Systems) allows users to run
models created as graphical representations of a system using four fundamental building blocks.
Stella has been used in academic as a teaching tool and has been utilized in a variety of research
and business application. Stella software also used to predict the consequences of any action in
data details. This means, we can predict the result by just adjusting or clicking the related
variable and run the process the simulation software will directly predict the results. By using
stimulation we can save the time on collecting data and run any experiment or research.
In this case, the Stella software was used to manipulate data for Biosawit experiment to
see the relationship between palm production, rat and owl. This relationship between these three
are the using the concept of food chain where there is producer, primary consumer and secondary
consumer. The rats eat palms, the owl eat rats. When the population of rat decreases, the palms
produce is increases because there is small number of palms consumer.
4. RESULTS OF BIOSAWIT EXPERIMENT USING STELLA SOFTWARE
1. Graph 1
Figure 1: Graph shows the relationship between Owl: 5 and Rat: 5,000
Figure 1 show the simulation results in graph form for Biosawit experiment. In Figure 1, we
set the number of owl at five and the number of rat at 5,000 then, we run the simulation. This
simulation calculates the data of palm produced, number of owl, and number of rat within 25
years. As the year past, the production of palm increase according to the graph for just about 20
years. After 20 years the production of palm was recorded decreasing as the population of rats
increases. We take a look at the data details cart, in first half year the population of owl
drastically dropped from five to zero and from there the rat population begins to increase. As the
results the production of palms is ascending at first 20 years and began to drop years later. The
production of palms recorded at the first half year is 20,789,213.14 tan. However at the end of
year 25th the production of palm predicted is 554,810.14 tan which is decreasing 266%. The
5. number of rats is increase from 5000 rats to 1,955,082 rats in 25 years. In this experiment the
ratio of owl over rat is 1:100.
2. Graph 2
Figure 2: Graph shows the relationship between Owl: 5 and Rat: 10,000
In figure 2 show the simulation results in graph form for Biosawit experiment. In Figure 2,
we set the number of owl at five and the number of rat at 10,000 then, we run the simulation.
This simulation calculates the data of palm produced, number of owl, and number of rat within
25 years. As the year past, the production of palm constantly increase according to the graph in
25 years. Through all the years the production of palm was recorded increasing as the population
of rats increase and decrease throughout the years. The population of owl also went up and down
during all the years. We take a look at the data details cart, in first two years the population of
owl drastically dropped from five to three and from there the rat population begins to increase.
But when the rat population increases the owl population begins to increase and as the owl
6. population increases the population of rats decrease once again. As the results the palm
production is constantly increased. The pattern repeated approximately every five to six years
based on the graph. The production of palms recorded at the first half year is 20,787,614.14 tan.
However at the end of year 25th the production of palm predicted is 108,208,184.61 tan which is
increasing 520%. The number of rats is increase from 10,000 rats to 10,615 rats in 25 years. In
this experiment the ratio of owl over rat is 1:200. The relation we can conclude here is the owl
migrates to other places as the rat decreases because of the survival. When the owl migrate the
rat increases and the owl migrates to the palm estate again and the rat decreases again.
3. Graph 3
Figure 3: Graph shows the relationship between Owl: 5 and Rat: 20,000
figure 3 show the simulation results in graph form for Biosawit experiment. In Figure 3,
we set the number of owl at five and the number of rat at 20,000 then, we run the simulation.
This simulation calculates the data of palm produced, number of owl, and number of rat within
7. 25 years. As the year past, the production of palm constantly increase according to the graph in
25 years. Through all the years the production of palm was recorded increasing as the population
of rats increase and decrease throughout the years. The population of owl also went up and down
during all the years. We take a look at the data details cart, in first four to five years the
population of owl dropped from five to four and from there the rat population begins to increase.
But when the rat population increases the owl population begins to increase and as the owl
population increases the population of rats decrease once again. As the results the palm
production is constantly increased. The pattern repeated approximately first four years and the
pattern repeated around 12 years later based on the graph. The production of palms recorded at
the first half year is 20,789,213.14 tan. However at the end of year 25th the production of palm
predicted is 106,913,578.83 tan which is increasing 514%. The number of rats is decrease from
20,000 rats to 15,244 rats in 25 years. In this experiment the ratio of owl over rat is 1:400. The
relation we can conclude here is the owl migrates to other places as the rat decreases because of
the survival. When the owl migrate the rat increases and the owl migrates to the palm estate
again and the rat decreases again.
8. 4. Graph 4
Figure 4: Graph shows the relationship Owl: 5 and Rat: 30,000
In figure 4 show the simulation results in graph form for Biosawit experiment. In Figure 4,
we set the number of owl at five and the number of rat at 30,000 then, we run the simulation.
This simulation calculates the data of palm produced, number of owl, and number of rat within
25 years. As the year past, the production of palm constantly increase according to the graph in
25 years. Through all the years the production of palm was recorded increasing as the population
of rats increase and decrease throughout the years. The population of owl also went up and down
during all the years. We take a look at the data details cart, in first four to five years the
population of owl drastically dropped from five to three and from there the rat population begins
to increase. But when the rat population increases the owl population begins to increase and as
the owl population increases the population of rats decrease once again. As the results the palm
production is constantly increased. The pattern repeated approximately the first four to five years
and 14 years later based on the graph. The production of palms recorded at the first half year is
20,781,230.02 tan. However at the end of year 25th the production of palm predicted is
9. 106,112,952.00 tan which is increasing 510%. The number of rats is decrease from 30,000 rats to
17,446 rats in 25 years. In this experiment the ratio of owl over rat is 1:600. The relation we can
conclude here is the owl migrates to other places as the rat decreases because of the survival.
When the owl migrate the rat increases and the owl migrates to the palm estate again and the rat
decreases again.
For all four graphs we were fixed the number of owl but the number of rat was different.
From this simulation we can conclude that the population of rat affected the population of owl
and also the production of palms. In Figure 2, 3 and 4 shows the same pattern when the palms
production increased in percent because the presence of owl from first year to 25th years that still
can control the population of rat. Even though, there is still palm damaged but the number not as
much as good production of palm. However in Figure 1, we can see the palms production
decreased in percent because the absence of the owl at first year because the population of rat
decreased. The owl migrates to other place to survive. As the year past, the population of rat
increase but there is still no presence of owl. This makes the palm damaged and production
decreased.
5. Table 1
Year Number of Rat Number of Owl Palm Production
(tan)
Percentage
Palm
Production
½
24
5,000
1,955,082
5
0
20,789,213.14
554,810.14
Decreased 266%
1
24
10,000
10,615
5
3
20,787,614.14
108,208,184.61
Increased 520%
1
24
20,000
15,244
5
4
20,789,213.14
106,913,578.83
Increased 514%
1
24
30,000
17,446
5
3
20,781,230.02
106,112,952.00
Increased 510%
Table 1: Table shows the relationship between palm production, rat and owl for 24 years
10. Advantage and Disadvantage
The main advantages of using simulation in teaching and learning is the process becomes
more interesting and exciting as the learners can explore everything in various types of
experiments. If students and teachers have the software of simulation, they can explore it early
when they are not in the class. These can make them more inspiring to study and discover a new
thing. Besides, simulation also can help the teachers to teach the abstract content to the students.
It is meant that, the simulation can make the students easy to understand as they can use the
simulation and not just imagine on what have been taught by the teacher. Other advantages of
using simulation are very quick development of complex models, short learning cycles and no
programming is needed. So, only minimal errors will occur.
However, this simulation also can give disadvantages to the students that do not have
computer or limited availability of computers. They will not have the opportunity to explore after
they have learnt in the class. Their learning process will happen only in the class. In addition, this
simulation also can give a big problem to the users that do not know how to use computer. The
users need to do two things in one time, which are learning about the computer and also learning
about the simulation. So, may be the user will be lag behind the others. Besides, many
simulations require intensive pre simulation lesson preparation. So, it takes time if we want to
use the simulation in a short period. High cost of software also include as the disadvantage of the
simulation. Only the trial one can be used by the users. But after 30 days, it cannot be used
anymore. In addition, limited scope of applicability and also limited flexibility. This is because
the variation of the topics is not too many. Some of them may not fix with the users specific.
Conclusion
Simulation is suitable to be used in the school because it can motivate students in
learning. Simulation motivate students by keeping them actively engaged in the learning process
through requiring that problem solving and decision making skills be used to make learner is
involved. Thus, participant in simulations enables students to engage in systems thinking and
enhances their understanding of systems as well as of science concepts.
11. Simulation can be considered as a powerful tool in active learning experiences. It can
provide a kind of lab-like experiences. So, the students will become more exciting and inspiring
in study because most of the students like to do something rather than just hearing to something.
Finding a good simulation in teaching is a challenge for the teachers in order to integrate them
into the content and objectives of the course chosen. However, if the teachers know what their
students need, it is easier for them to choose a suitable simulation.
References
1. 20170331100320Sawitbio
2. Modeling and Simulation using Stella
https://www.slideshare.net/farhana25/modelling-and-simulation-using-stella
