本研究以廢棄的蚵殼和回收紙作為研究材料，先將鍛燒後的蚵粉溶於水後，噴灑於手機螢幕與電腦鍵盤，並利用ATP生物冷光儀檢測微生物的殘存量，研究發現10ppm與100ppm濃度的自製蚵粉水在手機與鍵盤皆可達98.14%與96.08%以上的殺菌效果。之後再將自製蚵粉水與市售蚵粉水、自製文蛤粉水、水，在門把上做殺菌效果的比較，結果顯示殺菌效果最佳的是100ppm的自製蚵粉水，可達93.23%以上的殺菌效果。接著利用回收紙製作環保鞋墊，並加入自製蚵粉，用以探討加入自製蚵粉後的鞋墊中是否具有抑菌的效果，結果顯示加入5公克自製蚵粉微生物最佳可達89.5%的殺菌效果。

本研究係運用多項式擬合技術，表示出股價的年週期循環特性及趨勢，製作出可顯示個股股價年週期循環趨勢的應用程式。 先觀察市面上常見的股票技術分析，接著用Octave進行研究，最後運用Python製作出包含使用者介面的應用程式，並將分析結果量化及輸出，本研究將此應用程式稱為「股價年週期循環技術分析應用程式」。

本研究旨在應用立體思維解決循環式的最大流量問題，於教師介聘中，可提出擁有品質保證之方法，並求得介聘成功人數之區間。教師介聘應為一限制的網路流（每個節點至少一入一出），試著求出最大循環流量。 教師介聘為學校間之教師調換作業，透過志願選填與其他參與者進行交換。以110年的介聘規則而言，介聘順序為單調→五角調→四角調→三角調→互調，相同者以積分高為優先。現有制度受限於作業期程、業務人員能力，約略簡化問題原型，但即使如此，介聘處理的結果仍不提供數據分析，導致無從分析其品質及過程，因此介聘的結果、數量和方法皆仍有很大的研究空間。 此研究除了可使媒合數量最大化外，進而由原模型衍伸出多種策略，可以透過調整參數並於結果與時間中取得平衡。單志願介聘中，透過使用不同模型使準確率（介聘成功人數/最多成功人數）介於88～100%，運算時間與準確率成正相關。多志願介聘以自訂規則作為範例，套用單志願介聘模型呈現效果。

The number of natural disasters has risen significantly in recent years, and with climate change there is no end in sight. Consequently, the demands on rescue forces around the world are increasing. For this reason, I asked myself what I can do to improve the work of rescue teams. Advances in artificial intelligence and drone technology enable new possibilities for problem solving. Based on the technological advances mentioned above, an autonomous Search and Rescue drone was developed as part of this project. The system assists rescue workers in searching for survivors of natural disasters or missing people. This paper also suggests a method for prioritizing survivors based on their vitality. The system was implemented using a commercial Parrot ANAFI drone and Python. The software was tested on a simulated drone. To simplify the development, the whole system was divided into the following subsystems: Navigation System, Search System and Mission Abort System. These subsystems were tested independently. The testing of solutions and new concepts were performed using smaller test programs on the simulated drone and finally on the physical drone. The Search and Rescue system was successfully developed. The person detection system can detect humans and distinguish them from the environment. Furthermore, based on the movements of a person, the system can distinguish whether the person is a rescuer or a victim. In addition, an area to be flown over can be defined. If something goes wrong during the mission, the mission can be aborted by the Mission Abort System. In the simulation, the predefined area can successfully be flown over. Unfortunately, controlling the physical drone does not work. It stops in the air after takeoff due to the firmware of the drone. It does not change the flight state of the drone, which results in all subsequent commands from the system being ignored. This paper shows that artificial intelligence and drone technologies can be combined to deliver better rescue services. The same system can be applied to other applications.

本研究探討平面中三圓的關係，其中圓O固定不動，圓O1以逆時針方向滾動且繞行圓O；而圓O2同時也以逆時針方向滾動且繞行動圓圓O1。其中圓O1與圓O2上各有一動點P、Q。三圓一開始為圓O2分別與圓O和圓O1外切，且O 、Q、P三點成一直線，Q點介於O 、P兩點之間。當 ̅OO1與x軸夾角為θ時，先以繪圖軟體了解動點的軌跡；其次以三角比的概念求得P、Q兩點的坐標；最後再以電腦繪圖軟體，製作當三點共線時之θ值，並藉由函數圖形了解三點之中何者介於其他兩點之間。本研究由原本的三圓外切的情形，邁向討論三圓外離的情況，猶如恆星、行星、衛星三者的運行，進而以各圓半徑、兩圓連心距、繞行角度為變數，歸納合理的數學式，以利日後進行更廣泛的研究。

本研究旨在改善聽障人士無法完整接收影音類型資訊的狀況，探討各種影片處理技術，尋找、嘗試並比較各種方法，整合出最適合的系統自動替影片嵌入情境化字幕——用視覺的方式呈現影片聽覺訊息，讓聽障人士便於理解各種類型的影片內容與資訊。 為此，我們呈現的情境化字幕有主要幾個特點： 1、將聲音對話轉為字幕標記在說話者旁，透過畫面中語句位置就可以了解跟語者的對應關係。 2、畫面中字幕會以漸漸上飄消失的泡泡字幕來呈現，使觀影者有充足時間閱讀字幕理解內容。 3、將環境音效如電話聲、雷聲與貓叫聲等各種能傳達資訊的聽覺訊息標示在畫面中。 藉由這些處理使畫面呈現更豐富的影片資訊，最終達到改善聽障人士資訊接收權益不平等的目標。

「溫室效應」會造成地球暖化，使地球環境惡化。但「溫室效應」並非顯而易見，因此不易理解，現在結合自然科學與科技課程，於微型玻璃屋中，探討二氧化碳對溫室效應的影響。 首先在玻璃屋外進行「空白試驗」，再於玻璃屋內進行溫室實驗。打氣幫浦輸出的氣體經由三通管控制「繞流」(Bypass)，通過氯化鈣去除水氣，約略可視為「零空氣」(Zero Air)，以人工光源照射充滿「零氣體」的玻璃屋作為「對照組」，再比較充滿不同濃度的二氧化碳氣體作為「實驗組」，應用Arduino開發板、感測器、液晶螢幕與記憶卡，能即時顯示數據、記錄資料，再以Excel繪製圖表，也可連接電腦進行現場環境監測。 從數據分析，「溫室效應」確實發生，所以應該儘量減少二氧化碳排放至大氣中。

Triage is the process by which nurses manage hospital emergency departments by assigning patients varying degrees of urgency. While triage algorithms such as the Emergency Severity Index (ESI) have been standardized worldwide, many of them are highly inconsistent, which could endanger the lives of thousands of patients. One way to improve on nurses’ accuracy is to use machine learning models (ML), which can learn from past data to make predictions. We tested six ML models: random forest, XGBoost, logistic regression, support vector machines, k-nearest neighbors, and multilayer perceptron. These models were tasked with predicting whether a patient would be admitted to the intensive care unit (ICU), another unit in the hospital, or be discharged. After training on data from more than 30,000 patients and testing using 10-fold cross-validation, we found that all six models outperformed ESI. Of the six, the random forest model achieved the highest average accuracy in predicting both ICU admission (81% vs. 69% using ESI; p<0.001) and hospitalization (75% vs. 57%; p<0.001). These models were then added to an Android application, which would accept patient data, predict their triage, and then add them to a priority-ordered waiting list. This approach may offer significant advantages over conventional triage: mainly, it has a higher accuracy than nurses and returns predictions instantaneously. It could also stand-in for triage nurses entirely in disasters, where medical personnel must deal with a large influx of patients in a short amount of time.

本研究主要整合實驗測量、田口實驗與人工智慧機器學習等方法，發展優化泵浦旋葉技術。首先以3D列印開發多種相異外型族群與不同葉片數目共計82種設計，以實驗探討旋葉構造形狀與泵浦之流量、揚程及效率，進而找出效率較佳的旋葉並作為基底，過程中應用電腦輔助分析軟體進行旋葉內部流場與應力場分析驗證，搭配透明運轉泵浦觀察不同轉速下旋葉內部流體流動狀態，田口法研究結果發現由信躁比與均值分析結果顯示入口斜率為最重要的影響參數、其次分別為旋葉數與出口斜率，影響最小則是上蓋厚度，且優化設計旋葉T3C-10-2-4-4最佳。機器學習方面，經由多元線性回歸訓練模型預測出未知的旋葉效率(Y值)，訓練完成後得到平均絕對誤差Mean Absolute Error (MAE)皆小於1.5。

本研究旨在探討層雲結構產生上的一些物理機制，一般情況為地表附近空氣經由日照加熱而對流上升，而後與冷空氣混和凝結，我們藉由建立一些相關的模型來探討此一現象，利用水中紊流模擬大氣，設計密度界面模擬大氣中密度層變界面，透過染劑以及雷射誘導螢光等技術來觀察，而後探討紊流穿透界面或與界面上溶液混和時的相關現象，並利用一些計算，例如達西-魏斯巴赫方程或渦量方程式等，去解釋這樣的模型，配合電腦程式輔助分析紊流的速度及形狀等特性的關係,，再用不確定度去評估實驗精確性，連結這個紊流模式與大氣流體中的現象，並可推廣至諸如海底火山噴泉或是工廠汙染物排放。

騎士過城堡是一款棋盤模式的電腦遊戲，棋盤是由14格棋盤格組成之圖形，以騎士棋的斜日式走法，選擇棋盤格上的任意棋盤格作起點，跳完棋盤格上的14格棋盤格，每個棋盤格子僅能跳一次，跳完全部棋盤格回到起點即過過關。研究動機是希望能找出符合過關條件的其他棋盤格圖形以增加遊戲樂趣。研究目的在5X5與6X6的棋盤格範圍內，探討以「基礎圖形擴張法」找出其延伸的棋盤格圖形，與圖形中具多條可解路徑之規律性。研究過程中下指令Chatgpt生成Python程式碼，跑出基礎圖形延伸之棋盤格路徑。研究結果在5X5以8格基礎圖形其延伸圖形有14個、5X5與6X6以6格基礎圖形其延伸圖形分別有306與14535個，而圖形的中多條可解路徑由1-多條主迴圈與1-2條次迴圈所構成之規律性。

The number of natural disasters has risen significantly in recent years, and with climate change there is no end in sight. Consequently, the demands on rescue forces around the world are increasing. For this reason, I asked myself what I can do to improve the work of rescue teams. Advances in artificial intelligence and drone technology enable new possibilities for problem solving. Based on the technological advances mentioned above, an autonomous Search and Rescue drone was developed as part of this project. The system assists rescue workers in searching for survivors of natural disasters or missing people. This paper also suggests a method for prioritizing survivors based on their vitality. The system was implemented using a commercial Parrot ANAFI drone and Python. The software was tested on a simulated drone. To simplify the development, the whole system was divided into the following subsystems: Navigation System, Search System and Mission Abort System. These subsystems were tested independently. The testing of solutions and new concepts were performed using smaller test programs on the simulated drone and finally on the physical drone. The Search and Rescue system was successfully developed. The person detection system can detect humans and distinguish them from the environment. Furthermore, based on the movements of a person, the system can distinguish whether the person is a rescuer or a victim. In addition, an area to be flown over can be defined. If something goes wrong during the mission, the mission can be aborted by the Mission Abort System. In the simulation, the predefined area can successfully be flown over. Unfortunately, controlling the physical drone does not work. It stops in the air after takeoff due to the firmware of the drone. It does not change the flight state of the drone, which results in all subsequent commands from the system being ignored. This paper shows that artificial intelligence and drone technologies can be combined to deliver better rescue services. The same system can be applied to other applications.