全國中小學科展

電腦科學與資訊工程

Utilizing Computer Vision And Machine Learning Algorithms To Control Smart Systems Helping Physically Disabled People.

About 15% of the world's population lives with some form of disability, of whom 2-4% experience significant difficulties in functioning. The global disability prevalence is higher than previous WHO estimates, which date from the 1970s and suggested a figure of around 10%. This global estimate for disability is on the rise due to population ageing and the rapid spread of chronic diseases, as well as improvements in the methodologies used to measure disability. This research deals specifically with the physically disabled and often people with physical disabilities feel frustrated because they cannot do activities such as: playing sports and doing exercise. Having a physical disability also changes the way a person lives their life. They may find their life changes and activities they had previously included as part of their daily routine such as brushing their teeth, washing and doing household chores suddenly become a huge effort and many people require another person's help to carry out these activities. Also, they suffer from three basic challenges like; education, economic and, communication. Firstly, Education: The results of the investigation revealed that the physically handicapped. They face a lot of problems while studying they can't learn as the normal ones and they needs someone to help in learning. Secondly, Economic: they can't work and achieve income to help in his practical life. And finally Communication: they can't communicate with others because of his disability.

偵測注音文密碼強度之研究

密碼為我們生活中常見的一項工具,它可以為我們保護我們的隱私,以免受到別人侵犯,但也同時間出現許多問題,例如:若密碼太過單純會使密碼的功能失去意義,讓其他人可以輕易存取使用者的資料。 在臺灣,注音文密碼是十分常用的密碼,因為它乍看像亂碼,其實有一定的規律存在,而這些密碼,卻容易被判斷為安全的密碼,因此,我們希望可以將這個問題改善。 在研究中,我們先研究密碼強弱,再探討注音文密碼中在一般密碼中的比例,最後達成我們希望的目標—寫出一個可以偵測加入注音文策略的程式。在研究中,我們亦討論各個密碼演算法的優點及缺點,以找出可以最準確判斷的程式,並在研究的最後,提出可以將這套方法擴充至其他語言或是輸入法的可能性。

殊途同歸—無既定模式中英文混合輸入

本研究旨在設計一個使用模式,以不切換中、英文輸入法打字的原則之下,能夠完整的自動辨識出一個包含中文(注音、嘸蝦米、倉頡)與英文完整句子。經實測結果,正確率達到94.23%以上。

中文重點文句摘取

在資訊爆炸的時代,效率閱讀、整理資料的能力越趨重要。身為高中生,學習時的閱讀量龐大,還須另外自己挑選重點句,重新整理筆記。因此我想如果可以讓電腦自動摘取文章的重點,就能幫助學生效率學習。 大多數現存的自動摘要研究適用於英文文本,本研究利用演算法抓取中文文章的摘要,使學生可以真正實用該演算法於日常學習當中。除此之外,此研究比較了不同方法摘要的準確率以及優缺點。

Imperative Programming程式碼與Functional Programming程式碼的等價性與其證明,使用Agda

本研究主要考慮在盡量保留可讀性的情況下,找出將 Imperative Programming 程式碼對應的 Functional Programming 的程式碼並證明。 結果如下: 一、if statement 等價於由 ifte 函數所構成的程式碼,其中函數ifte定義在本文內 二、某些 for-loop statement 等價於由 foldl 函數所構成的程式碼 三、某些 for-loop statement 等價於由 map 函數所構成的程式碼

以結膜影像判斷貧血之研究

全球貧血人口普遍,然許多人並不了解自身是否罹患貧血;長期患有貧血的病人,亦需定期抽血檢驗追蹤是否有貧血惡化達到需接受輸血的程度。研究顯示,結膜之顏色與貧血有絕對關係,結膜越白則貧血越嚴重,醫師也常使用結膜顏色推測是否有貧血情形。若能設計手機軟體自動分割結膜影像並分析其顏色,將有機會推測受試者是否罹患貧血。本研究收集22位無貧血者及8位貧血病人,並獲得其近期血紅素數值。以手機取得受試者之眼睛影像後,成功設計程式以深度學習完成結膜自動影像分割,對於分割影像以面積大小進行後期處理後,依其取得下眼瞼結膜之三原色平均,再利用kNN與SVM演算法判斷預測出該受試者是否具有貧血之症狀。本研究主要分為兩階段,其一為進行下眼瞼結膜分割模型訓練;其二為製作有無貧血之判斷模型。整合上述眼瞼分割模型(IoU=89.8%±0.02%)與貧血判斷模型(SVM以polynomial核函數測出 準確值93.3%±24.3%)後,可得貧血診斷準確率為80%。此結果代表AI技術有機會透過結膜影像,判斷被拍攝者是否有貧血情形,未來若能增加研究人數,將可設計網頁版或手機APP加以推測血紅素值,供大眾居家篩檢。

基於深度學習之服裝試衣系統

本研究以AI虛擬試衣系統(Virtual Try-on)為主題,透過深度學習技術,並結合幾何匹配模型,開發出試衣系統,可將使用者上傳的照片,模擬成穿著新衣的模樣。 首先,以深度學習模型將人物原始圖片取出骨架節點,並生成人體遮罩以及保留人物頭部,再結合以上三種資訊合成為高維特徵圖。接著將目標替換衣物生成出依照人體姿態扭曲後的衣物圖片。最後於Virtual Try-on模型中將人體高維特徵圖與扭曲衣物作為輸入,並經過深度學習網路合成出穿著目標衣物之人體圖像。本研究結果發現,人物站姿單純,且雙手緊貼身側,以及拍攝角度為正面、衣服款式為短袖、背景色彩對比度較高與衣服圖案單純的原始圖片,可得到較好的合成結果。

Mentor Hunt App

The Information Technology (IT) area has shown great growth in recent years, even with the economic recession that 巴西 has been through and the impact of the coronavirus pandemic. It is estimated that by 2024 the area will have a deficit of more than 290 thousand professionals. However, companies still face other difficulties in hiring, especially people who are looking for their first job in the Information Technology area. Most part of these difficulties are lack of qualified manpower and high prerequisites to fill internship or junior positions. As a result, the objective of this project is: to develop a platform that connects people who seek guidance, improvement or professional relocation in the Information Technology area with professionals that already have the experience they are seeking. The first step was a research and analysis of similar platforms in the market, whose proposal involves mentoring or professional connections, and it concluded that there are no services that fully meet the project’s proposal. In the second step, a research was done about mobile development, highlighting Flutter and Firebase platform. The third step defined the application’s features, such as suggestion of users and mentors, search for users, become a mentor, private chat, video calls, Portuguese and English languages, light and dark themes and profile customization. The suggestion of users and mentors is done by a match with the registered users, relating their areas of work (where the user has experience) and the areas of interest of each one. For the coding of the project, Flutter and Firebase technologies were used. To design the app, it followed Material Design specifications. For testing and distribution, the app was published on Play Store, Google’s Android application platform. The tests were performed by both the researcher and a selected group of users to verify if the functionalities were in accordance to what was defined in the beginning of the project. Perceiving the correct functioning of the application, the project achieved the proposed objective. In addition, it expanded its reach area, because it is possible to find users and mentors from any other area of the market.

臺南市違停的離散小波與ARIMA分析

現今逐漸有許多科學家研究出一些能夠進行預測事件的方法,諸如天氣預報、價格變化的幅度等等。在眾多生活常見的問題中,我們選定違規停車為例,作為研究主題,而我們推測違規停車是一種具有週期性的問題,有多樣的潛在變因存在,於是我們跳脫以往多以心理層面、法規制度與地理熱點等的視角去看待違規停車,以資訊科學及數學的方法,建立一套分析的模式加以進行研究。 本文以連續小波變換CWT、最大重複離散小波轉換MODWT、差分整合移動平均自迴歸模型ARIMA、混合MODWT+ARIMA模型及混合Harr離散小波變換DWT+ARIMA模型,對臺南市三個不同特性的行政里的共五個聚類點,進行預測。原始的資料以週為單位,分成全日(allDay,0~24時)及白天(Day, 08~16時)兩種型態,並以連續46週的資料預測接下來4週。結果採用方均根誤差RMSE相對平均值、標準差、最大值的比值,進行預測品質的比較。

THE BLIND'S SHINE

Nowadays, all blind people are able to read any type of text thanks to The Braille system, which is a system of reading by touch. The Braille system provides a good and important help to blind people but it’s not enough. They try to integrate into society, try to read and write the same as those blessed with sight. However, only 18% of people can actually write in Braille and doing so takes a lot of effort. While Braille techniques have existed for many years now, there isn’t one that takes advantage of the comfort and easiness of modern technology. To be fair and give more chances to the blind people, and with all the available technologies nowadays, we must find solutions and innovative ideas to fulfill this objective. And this is how our project was born. To be honest, it’s not just a project, for us it’s a dream. Our focus in this project is creating an automatic machine based on transforming our language to their language and transforming this new invention to assist the blind in writing whole texts through speaking. It will be easier than the traditional way. This part of the project will help us print Braille on paper automatically in the cheapest, fastest and easiest way, unlike the traditional method that not only takes a lot of time but also needs a professional. Our printer will only cost approximately 250$ compared to regular printers that cost 6500$! the principles of the code of the speech recognition are voice pickup in all languages as first step, second speech recognition, then speech translation, after that speech analysis and finally translation into Braille and printing it. As for the future, we will work on face, object and image recognition as a scanner to make the visually impaired people read the name of the object and recognize people’s faces like anyone else.