2013年

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.

高分子分散型液晶(Polymer Dispersed Liquid Crystal，簡稱PDLC)是由高分子聚合物包覆的液晶微滴所組成，透過電場量值的改變能有不透光與透光的變化。然而目前PDLC的閾值電壓相對於傳統液晶而言較高，成為發展的阻礙之一，因此我們希望透過摻雜有機溶劑的方式來降低PDLC的閾值電壓。 我們先探討不同製程變因對PDLC的影響，以建立影響PDLC光電性質的理論模型，接下來我們嘗試摻雜不同的有機溶劑，並發現以乙醇的效果最佳，於是我們便進行不同重量百分率的摻雜實驗以及調整摻雜方式。我們發現酒精的摻雜可以大幅降低PDLC的閾值電壓，摻入25％的酒精約可使閾值電壓降低50％，除此之外，酒精的摻雜似乎可以降低PDLC的遲滯效應，而PDLC的初始光穿透率與摻入酒精的重量百分率約成正相關。這樣的結果相信對於PDLC在節能省電的應用方面將有很大的幫助。

商家或是店家常常為了保持魚肉的鮮紅色澤使其看似新鮮可口，往往會利用CO氣體進行處理。CO對於魚肉中的肌紅蛋白有很強的結合力，可保持鮮紅色澤不易腿去。為了簡易、快速又有效的偵測魚肉中CO氣體之有無及含量，我們自製電化學CO偵測器，並以不同種類的溶劑以及不同濃度之酸，探討肌紅蛋白中CO氣體逸出的機制。此外，我們也討論如何有效增進CO氣體的偵測。我們由一氧化碳感測器(SnO2)、花茶罐、鑽洞的器材、三通閥、電池及電路板，完成自製偵測CO氣體電化學儀器，不僅方便攜帶，更能取代市售昂貴CO氣體偵測器及改善偵測器體積太大的問題。實驗中我們加上pasco電壓偵測及電腦裝置，利於我們進行實驗觀察。而且本儀器也利於在硫酸、醇類及高溫的環境下進行實驗，且高溫的環境下有利於促進CO從魚肉中逸出並偵測。

基因陷阱(Gene trap)和增強子陷阱(enhancer trap)在近年來被廣泛應用於斑馬魚的研究上。 因此，本實驗利用實驗室現有的增強子陷阱，包含熱休克蛋白（Hsp-70）促進子和綠螢光蛋白基因(GFP)及兩端的Tol2重複序列，得到不同位置發亮的斑馬魚。其中，本實驗選用側線細胞之套細胞（mantle cell）和中間神經肥大細胞（Interneuromast cell）表現綠色螢光蛋白的斑馬魚（HG7L）進行研究，推測sortilin-related VPS10 domain containing receptor 3 (sorcs3)為部份的被取代基因。另外，將HG7L互相交配後，進行被取代基因對側線組織再生之功能的實驗，發現雙股皆被取代的斑馬魚的毛細胞（hair cell）再生較遲緩且排列凌亂，推測被取代基因對側線發育有影響。再者，藉由被標定的套細胞觀察側線組織的發育，並模仿前人的實驗方法，觀察得知側線的發育過程不只與套細胞更和中間神經肥大細胞有關。

由於奈米科技與OLED相關工業的蓬勃發展，近來設計出應用於電子元件的有機分子已成為一項熱門的研究主題。本研究合成出兩種分別可以放出藍色與綠色螢光的有機分子，化合物 1 可以放出藍色螢光，而化合物 2 則可以放出綠色螢光。這兩個分子都是由中間的核心共軛分子與兩側的雙尿素辨識基團所組成。 我們所合成出的化合物 1 之放光波長與化合物 2 之吸收波長有重疊，因此可以觀察到兩分子在奈米尺度下之有機溶劑中的能量轉移，即激發化合物 1 使其放出藍光後，能量傳遞至化合物 2 ，使藍光被淬熄並產生綠色螢光。另外，此二分子皆具有π-π作用力、氫鍵作用力與凡德瓦力，而在不同的溶劑下可以強化或弱化這些作用力，從我們的研究成果中，分子可以在四氫呋喃中轉變成直徑約400 nm的均勻奈米球型結構，並且能在顯微鏡下觀察到其奈米尺度下的能量轉移行為。 根據這兩種有機螢光分子的光物理性質與自組裝能力，在未來的發展與應用中，我們希望能使用在OLED顯示器與可撓式面板上。

The research is based on the production of biodegradable plastic-like material by only using household materials. Also, it can be made at home and it causes no harm to the environment. The biodegradable plastic-like materials made by different ratio of amylose, amylopectin, glycerol and water has different use. The finished product has smooth surface, highly transparency and well flexibility. Also, it can support strong load and be able to be deformed under stress. Ratios of components are tested on: 1. Easy to injection mold 2. Flexibility 3. Tensile strength and ductility & 4. Water resistance. It is found that the ratio of tapioca starch: glycerol: water = 1.5: 0.5: 9 can withstand 13N of force and 1.5: 0.93: 9 with high ductility. To improve water resistance, more amylopectin should be added to amylose. The best water resistance ratio is glutinous rice flour: tapioca starch: glycerol: water = 0.6:0.91:0.5:9 can withstand 16N force, while 0.6:0.91: 0.93:9 and 1.35:0.16: 0.5:9 with high ductility. All materials are available in supermarkets. Higher ratio of tapioca starch can produce bookmark, with laminate effect. More tough, higher ratio of glutinous rice flour can make cups, spoons and dishes.

本實驗乃研究超順磁性流體薄膜在通入垂直場後磁顆粒的動力學過程，以及排列的結構、磁鍊的幾何性質。我們使用了兩種創新的方法，分別是改良傳統磁性流體製造方法，避免磁性流體因凝聚而造成干擾；另一個是除了以往以電場或顯微鏡探討磁鍊的性質，使用Rayleigh scattering以及光遮蔽的方法，以CCD量測雷射透射光強度的時變率，改變不同變因(磁場大小、磁性流體樣本厚度、磁性流體濃度)，由於其結構性質影響了透射光強度，故分析透射光強度與諸變因間的關係，並與顯微鏡下的觀察結果比較，做出磁致散射動力學過程詮釋。

本作品為一種可選定不同時間地點模仿朝陽/夕陽之情境照明系統，包括複數個發光裝置、濾光及擴散片，選擇接近朝陽/夕陽頻譜的波長，亦即複數個發出紅光、黃光及紅外線的發光元件。本作品提出新的控制法則，透過計時器、繼電器與時序間隔調整控制器，連接各發光元件，控制它們的發光狀態，提供旭日東升、夕陽西下等模式，使用者可調整發光顏色變換的時間間隔，延長夕陽下山前一刻的美好畫面，可讓使用者充分領略夕陽之美。本研究並且可以依某一筆特定時空資料，計算情境變化過程之每一時間點對應於色度圖之軌跡點，即時比對特定時空資料其對應於色度圖之軌跡線，而得到與該軌跡點間兩種累計誤差為最小距離之計算值，並啟亮與該軌跡點相對應之該發光元件組合，如此達到不同時間地點之模仿朝陽/夕陽及雲彩之最佳情境照明效果。

This science project is designed to answer a question of whether or not a chemical reaction is needed to produce industrial quantities of carbon nanostructures by exposing dry ice to a high temperature that is at least 3100°C. A small carbon arc furnace powered by an electric welder is used to produce the high temperature. During control runs, the carbon arc furnace is energized for a predetermined time, after which the carbon arc furnace is de-energized and any carbon particles within the furnace are collected. During carbon nanostructures synthesis runs, dry ice is placed within the carbon arc furnace. The carbon arc furnace is energized and the dry ice is consumed for the predetermined time. Carbon nanostructures synthesized during the synthesis runs are collected once the carbon arc furnace is de-energized and allowed to cool. The volume of the carbon particles collected during the control runs is compared to the volume of the carbon nanostructures produced by the synthesis runs. This science project has discovered that on average at least 16 times more carbon nanostructures are produced during synthesis runs consuming dry ice as opposed to the control runs. Moreover, the synthesis runs did not rely on chemical reactions. Further still, samples of the synthesized carbon nanostructures were imaged using a transmission electron microscope (TEM). The TEM images clearly show high-quality carbon nanostructures that include carbon nanotubes, faceted carbon nanospheres, and the super-material graphene.

本研究為近海岸浮體式波浪發電設計，選擇理論推導與真實造波水槽測試，浮體式波浪發電設計概念，藉由一浮動載台將波浪運動能轉換為電能，而載台設計上利用浮體浮力，透過時規皮帶在浮體與活動掛重兩者中，產生時規皮帶的張力差，此刻的張力差與波浪的波高、週期與活動掛重三者產生連動效應，並有效率的將波能轉換為有用的機械能，最終再轉換為電能，本研究的波浪發電系統，當週期為1.5s、波高4公分時，有最佳週期平均發電效率為65%，依據模型相似理論縮尺為1/50，預估未來原型機組的最佳發電效率將發生在波浪週期10.6s、波高2公尺。