Physical Characterization of a Wide Aperture Segmented Reflector Telescope
Characterization of telescope lenses using physical optics and selection of the optimal physical parameters of a reflecting telescope’s optical units were done to improve the design, cost-efficiency, and quality of the 64-cm telescope (named Oof) housed at the National Institute of Physics. Characterization has been done through numerical modeling of the point spread function (PSF) in Python. The PSF code was based on the method of getting wave vectors by Richards and Wolf. The optimal PSF was established to be the PSF of a large monolithic mirror. The PSF of a single optical lens was compared to its counterpart segmented lenses. Through the comparison of maximum intensity, the normalized mean square error (NMSE) and the Linfoot’s criteria of correlation quality, fidelity, and relative structural content, the study has produced results which proved that highly segmented optical components produce results with less quality compared to less-segmented optical components. It was found that as the segmentation increases, the maximum intensity decreases. Higher values of maximum intensity denote higher light gathering power. The normalized mean square error of the set-ups having one to seven layers had values greater than zero but less than one. This denotes that the PSF of those set-ups are near the PSF of the optimal set-up. Higher values of correlation quality, fidelity, and relative structural content denote higher correlation, higher signal to noise ratio, higher closeness of correspondence between the optimal set-up and the segmented set-up. The number and the size of the optical components of the segmented mirror were manipulated in order to achieve a negligible difference between that of the optimal PSF and the PSF of a segmented mirror. The equivalent single lens radius in terms of maximum intensity of the current set-up of the telescope was determined to be 234.25 mm. If the optimal PSF is achieved, the physical parameters of the optical components generated may be applied to the optical components of the 64-cm telescope. The design that resulted from the study could be used in the future construction of a wide-aperture telescope, which could aid in the acquisition of knowledge about heavenly bodies.
密碼鎖
一個有3 個旋鈕，每個位置的號碼數分別是a、b、c 的密碼鎖，如果有兩個位置的數字正確就能打開，最少需要猜多少次才能保證打開這個鎖。在本論文中，我們將密碼鎖三個位置的號碼數分成：a＝b＝c＝n、a＝b＜c，a＝b＞c 和a＞b＞c 四個部份來討論。前兩部份的研究已經找到最少次數開鎖的方法 ，後兩部份則是給了一個演算法可求出開鎖次數的上界。If a combination lock with three rotate wheels can be opened when two wheels are adjusted to the correct numbers, then how many guesses does one need to make before he or she can actually open this lock? Let us say a , b and c respectively represents the numbers that should show on each wheel. In this paper, we divide the numbers into shown on the three wheels, and they are a = b = c = n , a = b c and a = b < c . The research on the first two combinations has already given us the method we can use to open he lock with the least number of trials. On the other hand, the latter two offer us an algorithm that can be uses to obtain the upper bound of tries needed to open the lock.
Reuse Waste and Save the World by Production Fiber Reinforced 'CB' made from Empty Fruit Bunch (EFB)
At present Malaysia is the largest exporter of palm oil in the international market. In the process of extraction of palm oil from oil palm fruit, biomass materials such as palm empty fruit bunch (EFB) and palm pressed fibre (PPF) are generated as waste products. Natural fibres reinforced cement-based materials have gain increasing application in residential housing components. One of the natural fibres considered is oil palm empty fruit bunches (EFB) fibres which offer advantages such as availability, renewability, low cost and the established technology to extract the fibres. This study investigates the properties of cement board incorporated with large amount of oil palm EFB fibres Among the tests conducted was compressive strength, density, water absorption and thickness swelling tests. It was found that high EFB fibres content lead to lower strength and higher absorption . The results also indicate that high EFB fibres contents reduced the self-weight of the blocks and the resulting blocks can be classified as lightweight cement blocks suitable to be used as lightweight walling materials. Our research is to study the production of cement board using Empty fruit bunch(EFB)These board were made from empty fruit bunch, cement and water. Two chemical are added is aluminium sulphate and sodium silicate. Cement : EFB mixture by weight was 2.5:1, 2.75:1 and 3.0:1 used to produces a cement board.
Finding a Better Brain Booster
The purpose of my project was to determine which activity improved academic performance the most: 10 minutes of exercise, 10 minutes of Brain Gym (cross-lateral movements), or a combination of 5 minutes exercise and 5 minutes Brain Gym. This project was conducted to find which activity would be a better learning aid in grade 4 students. There were many steps to conducting this study. First, I located teachers and classes, willing to allow the testing and determined days and times to test. Next, I created consent forms to explain the project and had permission forms from the students and their parents signed. Then I prepared 15 math and reading tests at students’ grade level. There were two tests for 15 days- labeled Before Test and After Test. When I administered the tests for the classes doing the activities, I made sure the tests were given by the classroom teacher, which kept the students motivated. Tests were given every day for 5 days. The Before Test was given at 1:00 pm. Then at 1:30 pm students did 10 minutes of the planned activity for that week. Immediately after the activity, students were given the After Test. This was done every day and was repeated for Exercise, Brain Gym, and Combination week. The control class was designed to determine if doing the test for a second time in a day improved the student’s performance. The Before Test was given at 1:00 pm and then at 1:30 pm. When the Before Tests were completed, the students continued with their daily work for 10 minutes. Then at 1:40 pm students were given the After Test. This was repeated for Exercise, Brain Gym, and Combination week. Students were given 10 minutes to complete the scheduled activity that week; either Exercises, Brain Gym or a combination of the two. During the week of Exercise, Jumping jacks, Skipping, Stride jumps, Burpies, Twisties and Jogging on the spot were completed in the 10 minutes provided. During the Brain Gym week, there were 26 Brain Gym movements. The lists of movements were rotated each day; so all movements were performed. The test results of this study were intriguing. (Bar=Standard Deviation) I concluded that 10 minutes of exercise was the better brain booster. Exercise improved academic performance by 9.8%. Brain Gym improved academic performance by 0.2% and the combination activities increased test scores by an average of 3.2%. The control class test scores decreased on average by 1.0% indicating that writing the tests twice in a day, did not improve students’ test scores. Exercising for 10 minutes improved student’s math scores by 11.0% and reading scores by 6.9%. Brain Gym math test scores decreased by 1.4%, and increased in reading by 1.8%. In the combination of the two, the math test scores decreased by 1.0%, reading test scores increased by 7.4%. Overall, the most effective and reliable brain booster was 10 minutes of mild aerobic exercise alone.
Self driving car
Autonomous car is a very new concept, being a car without any driver. Several concurrent software process data using Artificial Intelligence to recognize and propose a path which the car should follow. The goal of the project is that a driverless car can reduce the distance between the cars, lowering the degree of road loadings, reducing the number of traffic jams, avoid human errors, and allowing people with disabilities(even blind people) to travel using an autonomous car. Theoretically a car without driver in the future should be much safer, because human reaction speed is higher than 200 ms, and the computing power of the newest computers allows traffic calculations even to 10 ms. The necessary power is provided by three multi-core laptops that process with Artificial Intelligence in order to recognize traffic signs, traffic lanes , traffic car fingerprints, processing the data from a 3D radar, using particle filters to localize car in a GPS map, the management of database with traffic signs, magnetic sensors, acceleration sensors, a distributed software, a supervisory system and the software which drives the stepper motor to turn the steering wheel (acceleration and braking). Currently the software is able to recognize the traffic signs, register them in a database using Google Maps. The fields record the sign and direction of travel from that area. Each car participating in the traffic and using this software will register new signs detected and the will modify the degree of confidence of recognition for other users. Another software component is able to recognize the demarcation lines between lanes, with three cameras to calculate exactly or using probabilities where it is on the road, where the roadsides are and to propose a new direction even in the absence of traffic signs for the next seconds. Another part of the software is trying to use Artificial Intelligence to detect other car fingerprints from webcam images. The calculation was performed on 3 computers, requiring distributed processing. I developed a management information system based on semaphores that allows data processing and supervision from 3 different computers. This project presents a hardware version of a LIDAR – a 3D radar and a software for creating a 3D environment in which the car navigates and using it the car will take decision to avoid obstacles. The LIRDAR contains a total of 16 avalanche photo-detector mounted on a stepper motor that spins at a frequency of 10 Hz. The information provided by my radar is about 576.000 pixels at resolution of 10 bits. The 3D radar helps the entire software system to increase the confidence of decision.