電腦科學與資訊工程

Nikhil’s technology studies main client told him how she had no idea about how to\r stop her children looking at all sorts of website and asked him for a solution to a\r problem he initially thought was impossible to crack. Nikhil has definitely ‘cracked’\r this one: with a dedicated website his clients can log into and monitor what is going on in any computer the little box of electronic tricks is plugged into from anywhere in the\r world. This unit controls the electronics and stores the history of the web pages that the user has visited. Not only that, the client can cut the internet (and re-connect it) to the remote computer at will. At the heart of Nikhil’s box of tricks is a web-server module (The Wiznet) and a powerful microcontroller, the AtMega32. Nikhil has designed the\r board, connected the electronics and written the code to allow it to communicate with\r the computer and remote client.

SMS.Link-INTERACTIVE is a system that facilitates the exchange\r of information between a central computer server and a remote cellular\r phone user, and allows remote modification of data in the computer\r through SMS. A cellular phone with a GSM modem is connected to the\r computer physically via a data cable. A program in the computer is\r notified whenever the cellular phone receives new messages, processes\r new messages by first authenticating the user’s identity, then checks for\r the information being asked for, as well as the changes that the user wants\r to be done. Information is then retrieved from a database in the computer\r and the appropriate changes are made. A message containing the\r requested information and a list of changes done is then sent to the user\r through SMS.\r Tests were made to get the speed of the system. Accuracy tests were\r done to determine if the program was able to ascertain the validity of the\r user correctly, return the requested data, and change the specified\r information.\r Using this system, doctors can access a patient’s data and change\r prescriptions; teachers can correct errors in grades; clubhouse personnel\r can add memberships; all these from a remote location by sending a SMS\r request to the cellular phone connected to the server.

Contains two human-computer interfaces. The first is an interface for blind people to perceive visual sensations using his tongue. Images from a webcam is processed with artificial intelligence software and is placed as a sensory matrix under the tongue. Currently the sensor placed on the tongue is about 8x8 pixels. The sight and the taste divide similar areas on the cortex so the blind person can adapt very quickly to the image sent on his tongue as an electricity matrix. Taste buds are the second sensor matrix after the eyes(as resolution) is based on the same principle of the Braile code but the information is received by tongue and it's proportional with the image from webcam and the person can receive more informations. The second interface follows the intent of motion detection of a person with disabilities. It is based on processing the neural signal of the brain taken by an handmade encephalograph and processing them with a artificial intelligence on computer. The project contains hardware and software. This project tries to suggest that the human computer interfaces can be made to support people with disabilities.

本研究以增進日光燈管使用效率為目標，設計出一套整合型的系統以減少不必要的浪費。我們將感知用的硬體設備與自行開發的軟體程式作結合，使系統能夠在感知到日光燈管的各種狀態後，做出相對應的處置。其狀況包含:1.無電時系統會警告，以避免誤判的情形；2.有電時燈管正常運作；3.有電時燈管閃爍或不亮，此時系統會切斷日光燈管的電力，並記錄資訊。以上述系統為基礎，我們搭配紅外線模組來達到有人在才開燈，無人時自動斷電；亦加入偵測環境用的光敏電阻來達到光線暗時才開燈，光線亮時會自動斷電。依據測試，閃爍的燈管會比正常燈管多消耗30%的耗電量，壞掉不亮的燈管亦會消耗正常燈管70%的耗電量，對能源越來越少的今天，我們的系統提供了另一種節能的機制。

Over the past year Conor has been developing an electronic time keeping device named Hourglass. Hourglass has a three-fold focus on functionality, intuitive design and simplicity. To simplify the device he has limited the hardware to a bare minimum. Just three buttons and an LCD screen comprise the user-interface. Although this interface is simple, the user can access many features. These include intuitive scrolling menus, countdown, lap and alarm functions, accessed through button combinations as well as multiple ways to use single buttons, such as holding or short pressing. Many functions have been integrated into the device, such as a stopwatch with lap times, a countdown, up to 99 Custom Alarms with an individual active/inactive state and a lock/unlock feature. The stopwatch is accurate to 1 second and can be started, stopped, reset and used to record lap times. When laps have been recorded, the user can then take the time value of a lap and turn it into a countdown. A countdown of up to 99 hours can be set, and will run until deactivated or until it reaches zero. Upon reaching zero the alarm is activated. The home screen displays the time, any active countdown and notifies the user if an alarm is active. It can be locked or unlocked by holding the blue button a set period of time, helping to reduce any inadvertent change in setting. All of the functions available can be operated easily with the intuitive 3 button interface method. The menu system is simple, but has been set up through clever coding. An arrow indicated which option is selected, by pressing the top button on the clock the option above the current selection is selected/the menu scrolls up. Pressing the bottom button selects the next option in the downward direction/scrolls down. The button in the centre positioned off to the left is used to activate an option. When a Yes or No prompt appears on the screen, the action corresponds with the button position. Therefore the triangle layout of the buttons is simple and intuitive. Thus Conor’s device relies on complicated, yet elegantly formulated and annotated code and simple hardware interfaces to interact with the user in a way which is intuitive and provides great functionality. It does this while being simple and easy to understand. Here these principles are applied to a clock project, but there are implications for good design that go way beyond this context.

The purpose of Computer Vision is to understand the methods by which humans\r process visual information and likewise to create computer algorithms similar to these\r processes. Through careful observation, a computer algorithm was developed to mimic\r how humans recognize logos in television commercials. After visual analysis of\r numerous commercial sequences, it was hypothesized that the key frames (frames in\r which the logo resides) could be found using the intersection of color histograms; the\r logo region could be found using the edge density within the key frames; and the logo\r could be identified utilizing a correlation method with a database of stored logos, scaled\r to different levels using Bilinear Interpolation.\r Color histograms were implemented using one-dimensional arrays with 24 bins;\r key frames were determined by calculating the intersection between consecutive frames’\r color histograms. The edge density was calculated by convolving the key frame with\r the number of edge pixels within a 21X21 area. The identification of the logo was\r determined by computing the Sum of Square Differences between the logo region and\r the database of logos on different scales; SSD values were normalized for different\r scales.\r The algorithm was tested on 14 different sequences and determined the key frame\r with 80% accuracy. By segmenting the sequence into two key frames, the algorithm\r generated 93% accuracy. The algorithm also identified the logo region with 93%\r accuracy. The identification of the logo yielded anomalous results. These data suggest\r that motion between consecutive frames in commercial segments decreases around the\r display of the logo. They also suggest that the logo region has the most visible edges\r within the key frame.\r Future study includes a complete overhaul of the logo recognition algorithm. The\r correlation algorithm (SSD) does not work accurately enough to be used. Therefore, the\r next step is possibly to look at the edge information about the key frames. As the Canny\r algorithm determines the edges of an image, it has to determine the direction (or\r orientation) of the edges. Therefore, a proposed study includes utilizing an edge\r orientation histogram of the database of the logos and the key frames. This would mean\r that the algorithm would identify the logo in the key frames by matching edge\r orientation histograms.

File compression has become a very important tool in the technology field because it allows faster data transfer rates over the internet and decreased file size on data disks. File compression aims to reduce file size while still retaining the quality of the file. Lossy file compression methods are not very efficient because the compressed files end up losing more data than what is usually intended causing a considerable loss in quality. Lossless file compression methods, on the other hand, take time to process since they require decompression to retrieve the original file. In this study, a lossless algorithm which does no require decompression was created. The resulting Fractal File Compression (FFC) algorithm contains two parts, the IFS algorithm and the Huffman Tree generator. Both algorithms were created using Java language and JCreator. The finished program was tested on an image file with 2542 x 1944 pixels dimensions. The image file was compressed using JPEG, BMP, PNG and FFC formats. For each method, the image file was compressed at three different resolution settings; low, medium and high. All the compressed images were then viewed under 500% zoom using Adobe Photoshop CS2. In an area of 40 by 40 pixels, the number of distinct boxes, which served as a measurement of image quality, was determined. Compressed images for JPEG, BMP, and PNG for both the low and medium settings have low image qualities, while the fractally-compressed images have a high image quality. For the high resolution setting, both JPG and fractally-compressed images have Page 2 of 2 high qualities while BMP and PNG still have low qualities. Based on the measurements obtained from the box-counting method and the file sizes, the absolute image quality for each compressed image was calculated. The absolute image qualities of the compressed images used for each setting were then compared. Coupled with large file size and small pixels per area count, the conventional methods have lower absolute image quality than the images compressed using the FFC method. This was true for the low and medium settings, however, JPG compression has a higher absolute image quality than the fractally-compressed images. This meant that JPG compression is more efficient than fractal compression when an image has a high resolution. The resulting FFC algorithm is lossless since it uses pattern searches and replacements in order to decrease the file size. To make the program more suitable for high resolution images, the FFC algorithm may be modified. Most of the changes in the FFC algorithm should be done in the IFS generator. High resolution images can be compressed fully if the pattern that was used for compression is more representative, but even shorter. A more representative bit pattern would create a high quality, high resolution image with a smaller file size.

傳統的類神經網絡人工智慧多半是以受控訓練為主。然而在本次研究中，我們先建構出一套以類神經網絡模型為基礎的人工智慧，再利用社群網站噗浪（Plurk）上使用者與此系統的互動，訓練類神經網絡，以期驗證社群網站作為訓練來源的效率與準確度。我們利用分析詞、句的方式，促使系統做出自動的回應，同時並收集相關資料作為統計與修正之用。經過漸進式的調整與精進後，我們成功利用高度模組化的人工智慧系統，達成「利用社群網站資料自我修正」的目標，且其準確度呈現遞增的趨勢。我們相信只要充分掌握社群文化，社群網站做為資料來源對學術研究必有所裨益，且能為自然語言領域帶來更多可能性。

在台灣公共場合快速成長下，例如：大賣場、百貨公司、展覽會場，這些公共大型場合都有很好的消防設施，但始終有人葬身於火場？ 原因就是幾乎所有的人都不會去特別注意逃生平面圖，導致花太多的時間尋找出口，這樣生存機率就大大降低。火場裡面有太多的致命因素，像是：高溫的空氣，毒氣、濃煙…等，所以必須把握每一分每一秒。為了加快逃生速度，我們將所有的通道都設有導引警示器，逃生者只要順著導引警示器就可以安全到達出口。為了因應公共場合有龐大的人群，所以逃生路線不能只有一條，因此我們設計上是有多條路線，一、可以解決龐大人群，二、可以加快速度。;With the rapid growth of public places in Taiwan, evacuation system is of more and more importance. Actually, public places, such as hyper malls, department stores and exhibitions, are not without fire-fighting equipment, but why is that there are still people getting killed in a fire? The reason is that almost no one actually pays attention to the evacuation plans. As a result, it often takes too much time to find the exits, which lowers the possibility of survival. In a fire, there are usually too many fatal factors, which could lead to death, such as high temperature and heavy smoke; therefore time is precious when escaping from a fire. To fasten the speed of evacuation, we set guiding alarms in every passageway. By following the guiding alarms, people can get to the exits safely. Besides, owing to the huge amount of population in public places, there can’t be only one route out. With regard to this, we design many routes in order to enable and fasten the speed of evacuation of huge amount of population.

國立自然科學博物館推出《數位博物館》，內含大量生物圖鑑及豐富館藏文物之圖文資 料，無論用於資料查詢或提供進階研究資料皆有極大貢獻。但經使用後發現，其檢索架構仍 只提供關鍵字搜尋及分類瀏覽，無法精確檢索出欲查詢之資料，尚有改進之處。 於是針對現有之影像檢索系統，我們跳脫出傳統以文字為檢索之依據，而設計出一連串 之改進方案，如下： 1. IRHI 色調辨識影像檢索，針對色調相近之影像類群提供良好檢索架構。 2. IRCI 輪廓辨識影像檢索，針對輪廓相近之影像類群提供良好檢索架構。 3. IRHCI 色調暨輪廓辨識影像檢索，綜合前述兩種方法之優點所設計。 A while ago, the National Museum of Natural Science put forth the “Digital Museum,” which contains great amount of biological pictographs and abundant collections of textual as well as pictorial materials. This has contributed tremendously to information search and advanced research. However, after employing them, we come to discover that its retrieval paradigm only provides key-word search and categorization browse, without enabling us to precisely pick out the desired data. Thus, this paradigm leaves something to be desired. To make up for the insufficiency of the existing system, we have escaped from the concept of searching by texts. Instead, we have designed a series of improvements. They are as follows: 1. IRHI(Image Retrieval by Hue Identification): Providing a sound paradigm for the image groups composed of similar hues. 2. IRCI(Image Retrieval by Contour Identification): Providing a sound paradigm for image groups composed for similar contours. 3. IRHCI(Image Retrieval by Hue and Contour Identification): Combining the strengths of the above two paradigms.