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REGIONAL SCIENCE FAIR PROJECTS |
Southside High - Center for International Studies
Southside has had a number of award winning science fair
projects as shown in the table below. Science Fair projects are not generally required at Southside but
are open to anyone who is interested.
For Info: Contact International Science and Engineering Fair Entry Forms: Forms have to be filled out for both the regional and international science fairs. Forms will vary depending on the project. Read the materials carefully and submit only the required forms. (Deadline for submission of forms to the Regional Fair- Feb.21, 2003) To enter at Southside contact Tom Rogers .
Other Science competitions:
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| Name | Project |
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2000 |
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| 1) Joey Echeveria | The Effects of
Node Number on the
Performance of a Beowulf Super Computer: Joey used Linux operating
system to linked 24 of the lab's computers into a Beowulf system so that
they functioned as though they were a single super computer. For a period
of time Southside had the fastest high school computer system in the
world. This project received media attention from local radio TV and
newspapers.
Awards: 1st Place Computer Science Div., Honorable Mention Overall, 4 special awards |
| 2) Greg Grothouse | Neural Network Vision Recognition System:
Greg designed and built a digital camera/computer system which
learned to recognize numbers by using a neural network. Wrote the neural
network software. This project made it all the way to the International
Science Fair.
Awards: 1st Place Engineering Div., 2nd Place Overall, 4 special awards |
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2001 |
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| 1) Ambica Bumb | Terraforming Mars:
This
program simulated the conditions needed to terraform Mars into a habitable
planet.
Awards: 4 special awards |
| 2) Kerry Bullerdick | Reproduction Strategies in Artificially
Created Organisms:
Awards: 3rd Place Computer Science Div., 1 special award |
| 3) Amanda Cheung | Can Computer Simulation Be
Used to Predict the Effectiveness of Different Methods to Kill Bacteria? This
study examined the possibility of using computer simulation in place of
laboratory testing during the early stages of drug development.
Awards: 2nd Place Computer Science Div., 4 special awards |
| 4) Stacy Huffstetler | Simulation to Test the Effects of Various Factors on a Population's Homicide Rate: This program created a simulation of a human population with the goal of studying the |
| 5) Nishant Meta | Artificial Neural Networks and Financial Market Prediction: Nishant wrote a neural network program which used historic financial data to predict currency exchange rates. It could predict exchange rates 5 days in advance with a 7 % error |
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2002 |
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| 1) Amanda Cheung | Awards: 2nd Place in the Biology Category |
| 2) Aaron Cheung | Awards: 2nd Place in the Computer Science Category |
| 3) Ambica Bumb | Awards: 2nd Place in the Chemistry Category |
| 4) Kathryn Miller, Britany Golden | Can the Control System for a DC Motor on a
battery Powered Vehicle be Configured to Prevent Loss of Traction? The
project evaluated a 12 volt Fisher-Price motor to see if a control system
could be built to prevent a loss of traction when using the motor to drive
a robot.
Awards: 1st Place in the Group Category |
|
2003 |
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| 1) Richard Banks |
Crystallization: The project consisted of a program that creates an ice crystal from a seed point and attaches one moving particle at a time. The purpose was to allow others to understand the formation of crystals, and to gain the ability to predict crystalline growth. This would allow someone to create a crystal faster, stronger, and with better precision. |
| 2) Zach Blaettler | Deflection of a composite beam as modeled by a computer simulation: The program was designed to calculate the deflection of a composite beam composed of wood coated with aluminum. The program used variable load equations for both cantilever and simply supported beams. The deflection values were calculated and then stored in a linked list, which could be output to a text file for graphing. The information was then tested against actual deflection statistics taken from three composite beams. |
| 3) Shalini Bumb | |
| 4) Aaron Cheung | Can a Computer
Learn by Accumulating Past Experience: This project’s purpose was to
create a artificial intelligence learning algorithm that demonstrated a
computer’s learning capabilities. The model of tic-tac-toe was chosen
and the computer demonstrated amazing learning capabilities. In effect,
the computer program learned the rules and strategies of tic tac toe with
no guidance. Awards: 4th place overall, 3 special awards |
| 5) Chas Finch | Prime Number Management Utility: The military uses large prime numbers for encoding/decoding. The problem comes in that in order to crack the code, factors of 30 to 40 digit numbers must be determined, and regular computers cannot handle numbers that large. The program stores the numbers as strings of characters, enabling one to deal with these large numbers to determine primality and factors of a large number. It also incorporates a prime number database to increase efficiency. |
| 6) Patrick McCormick | Could Picket's Charge Have Succeeded and Under What Conditions? The project simulated the Civil War battle Pickett’s Charge, in which 14,000 Confederate troops tried to rush 6,000 Union troops stationed behind embankments and Union artillery over an open field. The simulation accounted for soldier firing, accuracy, health, and movement. The program found that Pickett would have needed at least 10,000 extra troops or that the Union army would have had to be about half its actual size. |
| 7) Paul McKenney | Music Classification Using Hidden Markov Models: The project was about a music classification algorithm (an algorithm that separates music according to its styles) using hidden Markov models. The models, which are a type of statistical artificial intelligence, were trained to recognize several unique styles. The models were then used to classify sample music files whose styles were already known, and the accuracy of the classification algorithm reached 60%. |
| 8) Nhan Nguyen | Awards: 2nd place overall, 3 special awards |
| 9) Zach Reynolds | |
| 10) Tarak Upadhyaya |
Secondary Protein Structure
Prediction Using Artificial Intelligence
Awards: Honorable
mention overall, 5 special awardsThis project used a feed-forward artificial neural network to predict the three-dimensional secondary structure of proteins. The neural network was trained using protein sequences with known three-dimensional structures, and made use of the back-propagation error calculation algorithm and the gradient descent parameter optimization algorithm. The neural network used a sliding window of 7 amino acids to read in an entire protein sequence and was able to predict it's three-dimensional structure (which consists of alpha-helices, beta-sheets and coils/turns) with an accuracy of 65-70%. |
| 11) Jeremy VanderKnyff | Approximating
Multi-Body Orbits Using Kinematic Newtonian Analysis and Investigating the
Effects of Velocities Above and Below Critical Velocity on an Orbiting
Body: Using Newton’s basic laws
of motion, the program accurately models the way planets in a solar system
interact with each other. Using actual values for the masses and distances
of the nine planets and the Sun in our Solar System, the program
calculates the correct orbital patterns and periods for the planets down
to the hour. This is one of the closest approximations of orbiting bodies
performed using Newtonian analysis.
Awards: 3rd place overall, 2 special awards |
| 12) David Wells |
Did Hunting Conditions and Lack of Food Cause the Extinction of the Saber Toothed Cat? Using random number generators, which simulated the necessary probabilities of such things as a successful hunt. In increments of 500 years, the program simulated the life cycles of three species – Saber Toothed Cat, Bison, and Wooly Mammoth – as their existences interacted during the ten thousand years before and after the end of the Last Ice Age. The program recorded the final population count of the Cat after each specified increment, collecting multiple data points for each increment. This data was then used to create box plots for use on a population v. time graph. Probabilities were also altered to test their importance. |
| 13) Kirsten Coleman, Brittaney Golden | Can a Parabolic Dish to Reflect sound waves, as it Reflects Light: Just as light hits a parabolic surface, creating an area of maximum intensity at its focus, sound should create a similar area of maximum amplitude. By setting up a microphone, placed at the dish's focus, connected to an amplifier and oscilloscope, the experimenters were able to locate such an area. Experimental data shows that an area of maximum amplitude is between approximately 30 degrees to the left and right of the dish's general focus. |
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