TITLE: Fixing The Y2K Millennium Bug
STUDENT RESEARCHER: Rajin Shahriar
SCHOOL ADDRESS: Hedrick Middle School
Lewisville, TX 75067
GRADE: 7th
TEACHER: Casey Hall
I. STATEMENT OF PURPOSE AND HYPOTHESIS:
The purpose of this project was to investigate the Y2K problem for home computers and apply a suitable fix to solve the problem. If there was a program (software) that could run when the computer boots up, recognized the incorrect date and time, and adjusted it before the user could see it, then the Y2K transition problem would be solved. Updating the system BIOS could also eliminate the problem. There are expansion cards available that "act" like the BIOS and effectively "become" the BIOS of the system. As for the Y2K bug in the software system itself, the only choice is to replace the software with a newer version. My hypothesis states that most home computers can be rescued from the Y2K bug using software patches.
II. METHODOLOGY:
Materials:
a. 3 old computers with a: (1) BIOS made before 91, for AMIBios BIOS (2) BIOS made before 96, for Award BIOS
b. 3 new computers with a: with a (1) BIOS made before 91, for AMIBios BIOS (2) BIOS made before 96, for Award BIOS
c. 1 display monitor
d. A Y2K Fix (such as one at "http://www.wsnet.com/~designer/holmesfx/".)
Research:
I searched different web sites looking for information about the Y2K problem. In this process, I had to investigate related concepts such as BIOS, RTC, system clock, and DOS operating system. I had to look for possible fixes for the problem. In addition, I also read some magazines collected from the local library.
Procedure of experiment:
Part I: Investigating Rollover to the Year 2000.
Part II: Installing a Y2K Fix
Part III: Testing the fix
Repeat Part I: Investigating Rollover to the Year 2000.
III. ANALYSIS OF DATA:
Without Y2K Fix:
| Computer # | Initial Date \ Time | Final Date \ Time |
| 1 | 12-31-99 11:59:00 PM | 1-1-00 12:00:06 AM |
| 2 | 12-31-99 11:59:03 PM | 12-31-99 12:00:04 PM |
| 3 | 12-31-99 11:59:02 PM | 1-1-00 12:00:01 AM |
| 4 | 12-31-99 11:59:04 PM | 12-31-99 12:00:08 PM |
| 5 | 12-31-99 11:59:07 PM | 1-1-00 12:00:05 AM |
| 6 | 12-31-99 11:59:06 PM | 12-31-99 12:00:09 PM |
With Y2K Fix:
| Computer # | Initial Date \ Time | Final Date \ Time |
| 1 | 12-31-99 11:59:01 PM | 1-1-00 12:00:02 AM |
| 2 | 12-31-99 11:59:02 PM | 1-1-00 12:00:06 AM |
| 3 | 12-31-99 11:59:06 PM | 1-1-00 12:00:01 AM |
| 4 | 12-31-99 11:59:09 PM | 1-1-00 12:00:05 AM |
| 5 | 12-31-99 11:59:07 PM | 1-1-00 12:00:09 AM |
| 6 | 12-31-99 11:59:06 PM | 1-1-00 12:00:08 AM |
IV. SUMMARY AND CONCLUSION:
It appears from this study that most home computers can be rescued from the Y2K bug using both software and hardware patches. I also found out, form this particular experiment, computer # s 2, 5, and 6 were non Y2K compliant. That was so because computer # s 2, 5, and 6 had older BIOS. By applying Y2K fixes to the non compliant computers, the Y2K problem was solved.
V. APPLICATION:
I listed some of these fixes in the results section. The easiest one is to apply a software fix that will remember the date for all practical purposes. It seems that the home computers worldwide are not in real danger because most of them were made after 1985. There are many Y2K solutions to choose from. The most important, however, is to educate the home users about this problem so that they can choose the right solution.
Title: Water Evaporation of Plants
Student Researcher: Miho Iino
School: Edgemont Jr./Sr. High School
Scarsdale, New York
Grade: 7
Teacher: Ms. Russo
I. Statement of Purpose and Hypothesis:
I wanted to know more about the process of transpiration of plants. Transpiration is the evaporation of water through the leaves of plants. Plants absorb water through their roots and lose it through transpiration. The water evaporates from the stomata, which are tiny pores. I wanted to find out where the water evaporates from or what part of the plant had the most stomata. My hypothesis stated that the back side of the leaves had the most stomata, so water would evaporate the most from the back side.
II. Methodology:
First, I wrote my proposal, conducted some library research on photosynthesis, and developed my hypothesis. I then got eight stems with eight leaves, each about the same size. I had two stems that had Vaseline on the front side of all leaves, two that had Vaseline on the back side of all leaves, two that were left untouched, and two that didn't have leaves. I got eight 20 ml test tubes, water, and oil. The manipulated variable was the location of the coating placed on the leaves. The responding variable was the amount of water lost. The controlled variables were the size of the plants, the size of the test tubes, the amount of water and oil, the temperature, the location, and the amount of sunlight. I put 18 cm of water from the bottom of each test tube and put one stem of plant per test tube.
Next, I put 0.5 cm of oil on top of the water to make sure water wouldn't evaporate from anywhere else other than the stomata. I put these test tubes on my windowsill and kept them there for five days. I recorded the total loss of water each day on my data chart. Next, I conducted an analysis of my data. Finally, I accepted or rejected my hypothesis and wrote my summary and conclusion. Then I applied my results to the world outside my classroom.
III. Analysis of Data:
I observed that stems' lose of water everyday and my data showed that the stems that had nothing added onto the leaves, lost the most water. Then the stems which had Vaseline on the front side, which enabled the water to evaporate only from the back side, had the second most amount of loss. The stems that were left untouched lost up to 6.4 cm in five days. Compared to that, the stems that had no leaves lost only 0.8 cm. The stems with Vaseline on the front lost 5.35 cm and the stems that had Vaseline on the back lost 4 cm in five days.
IV. Summary and Conclusion:
The stems that had nothing on the leaves had the greatest loss of water. The stems which had Vaseline on the front side, had the second greatest loss of water. So there was a greater loss of water which evaporated from the back side than from the front side. This shows that there are more stomata on the back side of the leaves. I also found out that transpiration does not occur on the stems because there was hardly any loss on the stems without the leaves. I accepted my hypothesis because transpiration occurred mostly on the back side of the leaves.
V. Application:
I can apply this information to my life in the following way. My Mom does flower arrangement. Sometimes there are special occasions such as a flower arrangement show. When my Mom arranges the flowers, I can tell her that she should not cover the back side of the leaves because photosynthesis will stop when the flow of water does not go smoothly. Then all the flowers would die.
Title: Color Choice - Preference or Programming?
Student Researcher: Marissa Lalli
School Address: Edgemont JR/SR High School
Scarsdale, New York
Grade: 7
Teacher: Maria Russo
I. Statement of Purpose and Hypothesis:
I wanted to discover if gender or personality impacted color choice and preference. I've always wondered if color choice was pre-determined genetically resulting in the stereotypical selections of blue for boys and pink for girls or if it is affected by surroundings, personality or gender. I assumed that color choice was a personal thing depending on your character. To define personality, I used the Myers-Briggs study.
Under my hypothesis, individuals with bright personalities would choose bright, lively colors while more inner, thoughtful personalities would choose more muted, pastel shades.
Therefore, "Introvert" and "Extrovert" color selections would reflect the two extremes because extroverts focus on the outer world of people and things while introverts focus on the inner world of impressions and ideas.
I predicted "Sensors" would tend toward muted colors because they favor concrete information of the present versus "Intuiters" who focus on the bright possibilities of the future and therefore would select bright colors.
Next, the "Thinkers" would lean toward clear, concrete, bright colors but "Feelers" would select less clear, more muted shades.
I hypothesized that organized "Judgers" would choose muted colors while flexible, spontaneous "Perceivers" would frequently choose brighter colors.
Finally, I hypothesized that girls would select muted pastels while boys would pick bright colors.
II. Methodology:
First, I selected a topic of interest to me and conducted some basic investigation on the Internet, which helped me to define human personality types by the Myers-Briggs approach. Next, I decided to frame my study around color selection and its link to two manipulated variables, namely gender and the four personality indicators as defined by Myers-Briggs. . Then I gathered or created the controlled variables including the color stimuli (paint chips of 6 colors on the color wheel and their pastel versions), and my survey which included various product categories for "coloring" which I wrote and distributed to the similarly aged (all adolescent) sample. I then developed my starting hypotheses. After collecting the surveys, I organized the responding variable of data charts from my color surveys. From these data charts I created graphs, compared the findings to my original hypotheses and drew conclusions.
III. Analysis of data:
From the identical completed surveys I gathered the results and organized them into data charts & graphs of:
Overall Color Preference by Sample Surveyed
Color Preference by Gender- the most frequently chosen colors (among all choices) by boys and girls.
Personality Type by Gender the incidence of the four personality indicators
Color Preference by Personality- 4 graphs of color selections among the four-personality indicator measures Extroverts vs. Introverts
Sensing vs. Intuition
IV. Summary and Conclusion:
Contrary to my hypotheses, the data strongly shows that Blue, followed by red and light blue are the most popular color choices regardless of either gender or personality measures.
Blue, Light Blue and Red were the top three color choices chosen by the total sample surveyed, regardless of gender, consistent with my Internet finding that blue is the most popular color overall among Americans
Girls' and boys' color preferences were almost identical around nearly every color, contrary to my original hypothesis with only a few exceptions: Blue was overwhelmingly popular among boys while girls although still selecting blue as their first choice, also liked purple and the pastels which were unpopular among boys
Again disproving my detailed hypothesis by the four Myers-Briggs personality indicators, opposite personality types DID NOT vary their color choices and closely followed the general pattern
It is interesting to note that certain personality patterns resulted among the sample surveyed with girls and boys displaying opposite characteristics on 3 of the 4 measures except for "Thinking" in which they were quite similar.
The main limitation of my study was the small male sample size. In order to compensate for this, I converted all of my data to percentages. Another limitation is that all the subjects were similar in that they attend the same school, live in the same community, and have similar social experiences and backgrounds.
V. Application:
My study indicates that predicting behavior or stereotyping by gender or personality is not accurate in relation to color preferences. But it does strongly indicate that product manufacturers and marketers should investigate and understand which colors are best suited for their products and preferred by their current and future customers. Since research has shown that color communicates emotion, creates moods and affects energy level, smart marketers know that manipulating color selections creates an appropriate personality for their products and can influence purchasing decisions. This can result in business success by causing consumers to select their product more often than competing products.
Title: Bones and the Effect of Different Liquids on Their Strength
Student Researcher: Scott Barsky
School Address: Edgemont Jr./Sr. High School
Scarsdale, New York 10583
Grade: 7
Teacher: Ms. Russo
I. Statement of Purpose and Hypothesis:
I wanted to see the effect of different types of liquids on the strength of bones. The strength is the hardness of the bone. The harder the bone, the less flexible it is. My hypothesis was that vinegar would have the greatest effect on the bone strength. This made sense because vinegar is a substance that eats away at other substances because it is acidic. I also suspected that milk would make the strength better.
II. Methodology:
First, I picked my topic idea and planned out how I would do my experiment. I then collected all my liquids and the jars to put the bones in. I purchased chicken with bones and boiled them in water. I then took the chicken off the bones and put the bones in the different jars and closed the lids. I then put them all into the refrigerator.
The manipulated variables were the different types of liquids, which included bleach, orange juice, milk, vinegar, Cola soda, and water. The responding variable was the different bone strengths. The controlled variables were all the steps in the set-up, bones from the same chicken, boiled for the same amount of time, same jar, and amount of liquid. I watched the bones for 12 days, testing the strength every day by bending the bones and seeing how flexible they were. I used a scale from one to ten and all the bones started at 10. The more flexible the bone was, the lower the number. I recorded the flexibility on a computer and just kept updating the sheet. Then I analyzed the data and made a display board that included my conclusion, data, graphs, pictures and the actual bones.
III. Analysis of Data:
I observed all of the bones and tested their strength. I found that milk added to the strength and because the scale only went up to 10, the bone soaked in milk was a ten plus. The bones soaked in the other liquids, except water, were mostly all five's and six's. The strength of the bones soaked in water stayed the same and remained at ten. After a few days, the bone in vinegar broke.
IV. Summary and Conclusion:
The milk added to the strength of the bones and the vinegar did the most damage. All of the other liquids had about the same effect on the bones. The milk added to the strength of the bone, because it has calcium in it, which the bones are able to absorb. This is how the bone in milk became stronger. The vinegar is an acid so it is able to dissolve substances. This means that it eats away at the bone, making it lose strength. Therefore, I accepted my hypothesis, which stated that milk would increase strength and vinegar would decrease the strength the best.
V. Application:
I can apply this information to my life in two ways. I love dogs. I can soak bones in milk and give it to dogs. This would save me money on bones and would decrease the money spent on the dog. Paleontology is also something I enjoy studying. This information could be used to find a way to preserve bones. If scientists found out how the milk made the bones stronger, museums could make them last for a longer time.
Title: The Effect of TV on Human Eyes
Student Researcher: Sipra Rathi
School: Edgemont Junior/Senior High school
Scarsdale, NY
Grade: 7
Teacher: Ms. Russo
I. Statement of Purpose and Hypothesis:
I wanted to know if TV had any affect on human eyes. I had heard many people say that watching too much TV can be harmful to your eyes. So, I decided to see if this was a myth or true. My hypothesis was that TV did not have any affect on the human eye.
II. Methodology:
I decided to test my hypothesis by interviewing 100 people about their TV habits. I chose 50 people with glasses and 50 people without. I then compared the data to reach a conclusion. The children I interviewed were all ages 12 to 13 years old, that was my controlled variable. I started by asking them what their age was. Then I asked how much TV they watched a day, the manipulated variable. Finally, I asked them about the condition of their eyes, which was the responding variable. After collecting all this data, I analyzed it.
III. Analysis of Data:
The results showed that people with glasses watched an average of 1 hr 40-min of TV a day, and people without glasses watched an average of 50 min per day. It was also found that 50% of children with glasses watched over 2 hrs of TV, while 8% of children without glasses watched over 2 hrs a day. I also found that only 6% of children with glasses watched no TV vs. 26% of children without glasses.
IV. Summary and Conclusion:
The data lead me to unquestionably believe that TV does have an adverse affect on the human eye. This proves my hypothesis wrong. The reason I concluded this was because my data clearly showed that over 98% of the time people with glasses watched more TV than people without.
I know that there are lots of chance issues concerning my study and the 50 people I interviewed with glasses might not all have glasses because of their TV habits. Other factors like genetics, and nutrition might have played a role on their eyes. I think, to eliminate more of the chance factor, I could have a bigger sample size, more people, and varied group ages. But I also know that the data I collected showed a statistical difference and was not purely coincidental.
V. Application:
I learned from this project that I should be more aware of the amount of TV I watch because it does have a great impact on my eyesight. I realize that this study might also make other people aware of the effects of TV and hopefully they will take this into consideration the next time they feel like sitting in front of TV for 6 hrs. If the public is informed about the negative impact of TV watching on eyesight, parents may be more likely to regulate the amount of time children spend watching TV.
Title: Blood Pressure of Physically Fit and Physically Un-fit
People
Student Researchers: Cyndi Benedict, Julie Mead, Laura Hendrickson,
and Jill Anderson
School Address: Parker High School
Janesville, WI 53545
Grade: 9
Teacher: Mrs. Lippincott
I. Statement of Purpose and Hypothesis:
We wanted to find out if people who are in sports have a lower heart rate than people who are not in sports do. Our hypothesis states that the more active you are the lower your heart rate will be.
II. Methodology:
First, we took our resting pulse. Then we each ran for five minutes and after the five minutes we took our pulse rate.
III. Analysis of Data:
People more active in sports had lower heart rate than people who do not participate in any at all.
IV. Summary and Conclusion:
If you are active in a sport, you would probably have a lower heart rate than if you were not active in anything.
V. Application
If you don't want to have a higher chance of having a heart
attack, you should be as active as you can. To keep your heart
rate at a healthy pace, you could walk or run regularly. A few
different changes you could make to the experiment would be: bike
instead of run; power walk instead of run.
Title: Pulse Reactions
Student Researchers: Ruth Ledger & Rachel Tadt
School Address: Parker High School
Janesville, WI 53545
Grade: 9
Teacher: Mrs. Lippincott
Mrs. Newton
I. Statement of Purpose and Hypothesis
We wanted to see if listening to different types of music would effect people's pulse. Our hypothesis stated that people's pulse would change with the music.
II. Methodology
We tested our hypothesis by testing different people's pulse while listening to seven different selections of music. Our materials consisted of a section of jazz music, a section of rock music, slow contemporary, rap, country, hard rock, and an oldie for thirty seconds. First, we stated the person's age and name, and then we checked their regular normal pulse for thirty seconds. Second, we tested the person's pulse listening to the first song for thirty seconds. Third we tested the person's pulse listening to the second song for thirty seconds, and so on. Finally, one minute after each test, we checked the person's pulse for thirty seconds listening to no music at all.
III. Analysis of Data
In our research project each person's pulse changed with the music. Their pulses quickened as the music did. It showed listening to calmer music slowed down a person's heart rate, and listening to more up beat music caused a person's heart rate to go up.
IV. Conclusion & Summary
We found that listening to different types of music affected a person's heart rate. When a person listens to faster music, heart rate is faster. When he or she listens to slower music his/her heart rate is slower. We accepted our hypothesis.
V. Application
Having too high or too low a heart rate can cause problems. When these problems arise, a diagnosis could possibly be to change the type of music the patient listens to. If their heart rate was high, they could listen to softer, calmer music. If a person's heart rate is low, they could listen to faster more up-beat music. The same is true for listening to softer or classical music when you're studying or trying to concentrate.