「拈」是我國民間一種流行很廣的遊戲，甚至在歐美地區亦廣為風行，由於曾在坊間數學趣談的書籍中，了解其中的一些理論架構，與電腦邏輯的思考模式頗為接近，遂興起了設計電腦程式的念頭。

為協助建立良好用電習慣，讓家中省下可觀的電費，本研究製作的家庭電力監控系統，即時的圖表顯示家中電力耗損的情形，可監視家庭成員的用電，協助改變用電習慣，進而達到省電的目的。在安全方面，當電流過大時，也可發出警訊或切斷電力，免於走火的危險。使用軟體控制各電力迴路，設定旅行、睡眠…等程序，以便在這時候，確實切斷非必要電力。本電路設計使用霍爾元件感測電流，電流值經A/D 轉換後，將資料透過USB I/O 卡寫入電腦，儲存於資料庫，藉以產生圖表資訊，呈現各插座的用電狀況。將系統所計算的電流值及度數，比對理論值、瓦時計及數位電流表的測量值，並做具體校正。經實測證明可提供可靠的數據，能夠即時提供用電狀況，做為家庭節能策略的依據。

近年來在熱聲效應方面的研究產生了許多新發明，如冰淇淋冰箱與太空梭溫控系統等。然而，將熱能轉換成聲能的熱聲引擎，在散熱方面的效用只有被提起而從未被實際應用。本研究參考美國賓州大學「聲學雷射」裝置來研究熱聲引擎的特性，並提出一個以熱聲效應改善微電子器材散熱的裝置。它的優點是由電子裝置產生的熱即可啟動熱聲效應，而熱聲效應所加強的熱對流可降低該電子零件的溫度。實驗中發現透過熱聲效應的強烈散熱，可以大為降溫，由200℃降為50℃左右，這正是當代電腦內中央處理器（CPU）的工作溫度範圍。未來的研究可以針對陣列式的熱聲散熱裝置進行測試。In this project, the characteristics of the thermoacoustic engine were first studied using the “Acoustic Laser” concept. A passive thermoacoustically enhanced convection engine capable of improving the cooling effect of microelectronic devices was then proposed. This design has the advantage that no additional energy input is required, a contrast to the usage of mini-fans in today’s computers. A testbed combining a heated NiCr wire with a glass tube was used to examine the overall cooling effect. In order to evaluate its performance, we measured the following parameters: radiation, convection, conduction, and acoustic radiation. We found that the heat caused by today’s microelectronic devices is sufficiently high to trigger the thermoacoustic effect. Based on this finding, we designed a new configuration to utilize this thermoacoustically enhanced convection to significantly lower the temperature. Our approach has a potential application to tackle the heat problems caused by the rapidly advancing microelectronic devices.

本實驗用了業務用排風扇，並加上整流段，使氣流更加平穩、集中。裝上自製調速器以控制風速，並且改良出微型風速計，以測試棒球上下的氣流流速。棒球部分，則利用家裡面常會用到的圓形保鮮盒，改裝成測試架。此測試架可同時測到水平力、垂直力及阻力，不儘大大地突破過去的測試限制，更可以任意改變旋轉的角度及轉速，以及不同的旋轉軌跡。如此，幾乎所有的變化球都可以模擬出來了！也可藉此找出新種的變化球。為了測量打者揮棒時間，我們利用了電腦軟體(威力導演)，將打者的打擊影片進行連續的分析，以求得球路判斷點，最後利用電腦做0.01秒為間隔的力量分段分析，使數據更加精確，更有助於棒球軌跡的完整呈現。

Purpose of Research\r Colour blind individuals make up a large part of the population but are not usually considered. I aim to design an interactive guide that can be used when designing websites, social networking pages and various digital presentations to ensure that they are legible to colour blind individuals, by determining which colours generally confuse both red-green and blue-yellow colour blind people.\r Procedures\r I e-mailed my test, which consisted of 240 slides depicting every possible combination of the 16 basic web colours in the form of a frame, a heading-appropriate sized text and a paragraph-appropriate sized text, to a group of red-green and blue-yellow colour blind individuals, as well as an equally sized control group. I asked them to flip through the slides at a comfortable pace and note the slides that were difficult to read offhand, thus getting an idea of which colour combinations are not suitable for colour blind individuals, as well as the combinations that are not visible to those with normal colour vision.\r Data\r I wrote up my results using tables and stacked column graphs to determine which colour combinations were not visible to an unusually great number of test subjects. I then represented the information I collected in the form of a flash guide. This interactive guide allows one to choose a background colour from a wheel of 16 colours, and then be given a choice of appropriate text colours. The user is also presented with an example of the combination that was chosen, showing how the text appears on the background. The guide is easy to navigate and understand, can be posted on the internet or e-mailed, and is not overly technical so it can be used by designers as well as ordinary internet users.\r Conclusion\r Colour blind people are easily confused by colour combinations which might seem clear to us. My hypothesis was proved as I was able to set up a guide that would make it possible for both colour blind individuals and those with normal colour vision to read the text on websites, social networking pages and digital presentations.

本實驗透過影像軟體的協助，擷取ＲＧＢ值與灰階值，來分析布料種類、布料前處理、光照、洗劑處理、媒染劑如何影喜植物染色的效果，結果發現：１.布料前處理的影響根據布料種類而有差異，人造布料較需要布料前處理。２.布料種類以植物性布料染色效果最好，植物性布料次之，人造布料最差。３.光照、洗劑處理均會改變染布色澤，甚至會造成退色現象。４.媒染劑會使原本的染色色調改變，效果因煤染劑與染材種類而異。

本實驗用了業務用排風扇，並加上整流段，使氣流更加平穩、集中。裝上自製調速器以控制風速，並且改良出微型風速計，以測試棒球上下的氣流流速。棒球部分，則利用家裡面常會用到的圓形保鮮盒，改裝成測試架。此測試架可同時測到水平力、垂直力及阻力，不儘大大地突破過去的測試限制，更可以任意改變旋轉的角度及轉速，以及不同的旋轉軌跡。如此，幾乎所有的變化球都可以模擬出來，也可藉此找出新種的變化球。為了分析打擊時機，我們利用了電腦軟體(威力導演)，將打者的打擊影片進行連續的分析，以求得球路判斷點，最後利用電腦做0.01秒為間隔的力量分段分析，使數據更加精確，更有助於棒球軌跡的完整呈現。最後，再透過升力係數、阻力係數和自旋比的關係圖，發現高轉速下與馬格努斯經驗公式相違背的部分。

此研究之重點在於如何建構一套人工智慧方法，人工智慧含多種進行方式，例如以類神經網路訓練近似於人腦之結構，而專家系統係於不同的科學領域內以自己之所知判斷。我們先以 John Holland 的 Genetic Algorithm （暫譯基因演算法，以下暫稱GA）的理論來實作出一套人工智慧系統之方法。Genetic Programming 係以ＧＡ為基礎之實作方法，主要的內容不出基本的演化定義；在這次的試驗中，首要為先定出程式欲演化成何種類型，在此我們先定義為排序型的演算法，經過分析實際程式之結構後定出適合基因元件的資料結構，分化為兩個部份進行，一為產生器，亦為突變，交配器，一為評審程式，亦為執行器，兩者使用相同之基本元件，再以不斷的交配和突變以達到全域最佳化。我們將兩種部份完成後，加上現有的PVM 分散運算函式庫來增加演算的速度。 Abstract The research mainly discusses AI. AI, involves in several types, for example, neural network(NN),which adopts human-like training method; Expert systems determine and make decision by what it has known. We will use John Koza's Genetic Programming theory to implement an AI system.Genetic Programming theory is based on GA. In our experiments, we have to define what kind of applications we want : a sorting application, which is divided into two parts - a producer (along with crossover and mutation operations) and an executor (along with judging operations), is an easyimplemented algorithm. Our program, also with PVM, will approaches global optimal after evolutions.

本實驗不在驗證筊杯與神明旨意之間的真實性，而是以物理學的觀點，找出筊杯的角度、形狀、大小、材質與掉落情形之間的關連性。此外，為了減少人為因素造成的實驗偏差，我們以鋁夾作為擲筊臂，以樂譜架作支架，製作出擲筊器，盡量使每次擲筊動作達到一致，並經由反覆的擲筊，探究不同角度、形狀、大小與材質的筊杯，驗證人稱的「聖杯」，其機率是否真為二分之一。且應用牛頓三大運動定律，觀察筊杯掉落時的不同狀態，如速度和落地點及筊杯間與地的接觸狀況，尋覓聖杯的成因。我們也應用電腦軟體繪製筊杯的3D圖，計算陰面及陽面的表面積，並以陽面與陰面的比值，製成曲線圖，觀察表面積的比值與形成聖杯的關聯性。

本文藉由模糊數學理論所提的分類方式，來設計一套對於DNA序列的分類方法，並利用了40筆人工已分完的樣本，分別作為測試及學習樣本。\r 發現可以順利的將每筆DNA序列中的鹼基每3個一組轉成胺基酸序列，再利用模糊分類方式將所有胺基酸序列進行分類，最後並利用原先滾動方式的環狀排列方式，來對同一筆鹼基的3組胺基酸資料進行檢核，發現可以有效提高分類的正確性。\r 之後我們再利用182筆自然樣本進行檢檢，也發現模糊分類方式亦可正確完成此次分類結果。

在我們週遭環境中常可見到許多種類的植物，然而可以叫出名字的卻少之又少，或許我們可以查閱植物百之類的書籍，但是這類書籍通常多不在手邊，就算有了植物百科，也不易翻到顯示該種植物的正確章節。假如我們可以將想要認識的植物葉片影像取得後，透過網路將該影像傳送至植物葉片資料庫查詢，經過電腦的自動分析辨識後，再將結果傳送回來，這樣不是比查閱植物百科方便多了嗎？本研究提出一種利用輸入葉片的影像來進行植物資料庫辨識查詢的方法，藉著兩階段處理的策略及最佳權重組合式的特徵值來調校系統，以達到較佳的整體辨識效能，從實驗測試的結果得知，我們的策略與方法確實有效，有82%的查詢葉片可以被精確的辨識出來，而每次查詢的平均反應時間只要17.22 秒。In our living environment, there are many kinds of plants, but we can only name a few. We may consult an encyclopedia about plants, we always can’t find any encyclopedia with us. Besides, even if we have one, it won’t be easy to find out the proper section or the exact page immediately. How should we solve this problem? One significant improvement can be expected if the plant recognition can be carried out by a computer. First, we take a picture of the unknown plant’s leaf. Then, we transmit this image into a leaf database to recognize. After the recognition we will get the answer easily. By using a computer-aided leaf recognition system, non-professionals can also identify many plant species. Isn’t it much more convenient than checking the encyclopedia? In this study, we present an efficient method for leaf database retrieval by inputting leaf images. We use a two-stage approach and combined features with optimized weight to adjust the system to get the best system performance. The result of the experiment shows that our approach is workable and efficient. 82% leaves of the query images can be recognized accurately. And in general, the average response time only takes 17.22 sec per query.