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急酷降溫:開發水冷式CPU散熱模組之研究
目前水冷散熱系統普遍應用在電腦CPU降溫中,雖然水的「比熱容」比空氣及大部分介質都高,但因水冷散熱系統內冷卻液的熱量,最終仍靠風扇送到機殼外,故CPU之最低溫度仍存在一個臨界值。本研究旨在對於「一體式」與「分離式」電腦水冷散熱系統及「熱電致(製)冷晶片」(Thermoelectric Cooling Module)結合進行模組開發設計,將此兩類相關元件搭配結合,以突破傳統水冷式散熱所無法降達的溫度。本研究將「致(製)冷晶片」之致冷端及水冷系統作結合,利用致冷端作為吸收CPU主要熱量,結果發現:與單純只利用風扇將熱量帶走的方式相比,本研究所開發之『第一代』一體式散熱模組與『第二代』分離式散熱模組皆成功地將頂級CPU之工作溫度再壓低,使電腦工作效率維持在最佳範圍。
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無紙袋吸塵器除塵技術運用於室內空氣清淨之研究
本研究主要是希望將「無紙袋吸塵器」之除塵技術應用在室內空氣清淨之上。 首先,選定PM2.5為空氣汙染檢測標的。然後,利用電腦課學習之Arduino套件,編寫程式並組裝SHARP PM2.5感測器。 接著,探討無紙袋吸塵器之除塵原理,並改良結構以應用於空氣清淨。 研究發現:設計良好之「氣旋除塵筒」,確實有很好的清除PM2.5效率。清除PM2.5效率良好的氣旋除塵筒:1.能產生結構札實的氣旋結構、2.直式比橫式效率高、3.加長氣旋除塵筒長度能夠增加清除效率、4.抽氣孔與進入室內空氣孔分開,並將抽氣孔位於側邊可以增進清除效率、5.增加風扇風力也可以增加清除PM2.5的效率。
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本研究目標旨在完成多人合奏、原音重現的自製樂器,透過Arduino作為傳遞訊號的中介,並以電腦對應輸出不同樂器的實際音色。在系統架構上,我們利用Arduino的類比訊號,讀取電壓值轉換成字串對應音階,實際錄製我們想要的樂音建立音源資料庫,以視覺化圖形輔助音階表現,隨時對設備進行調整,完成撥放系統的模組。實驗過程中,我們測試了兩個世代的訊號傳輸系統,最終以分壓原理為知識架構,焊接可變電阻,形成有效、穩定的訊號傳輸。其次,以生活上的紙箱素材、Cat6雙絞銅線、鋁箔紙自製耐受恢復力高、導電性高的琴鍵結構。最終,透過以上的研究歷程製作出虛實整合的電音樂團(BAND)。
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本研究以稠密式深度預測為基礎,進行環繞掃描3D還原建模。在這項研究中,我們擇手機作為唯一的外部數據提供設備。首先用手機同時錄影和記錄角度變化、位移數據後,我們同步各數據的時間點,並計算每一幀影像的位置,接著將拍攝的影像輸入深度預測模型轉換成深度圖並將其儲存為點雲,最後利用三維旋轉和平移矩陣將點雲轉回正確的位置以進行疊合。我們開發的3D還原建模系統能夠輸入影像、特定時間點的位置和角度變化來建立3D模型。此系統可以解決結構光掃描儀需要額外標記點的劣勢,且在機動性上較傳統的點對點雷射掃描儀更方便。我們希望可以在未來將這套系統集成為一個手機應用程式,方便使用者在手機上進行相關操作。
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Development of an autonomous Search and Rescue Drone
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.
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平常聽音樂時經常有種似曾相識的感覺。為了描述這種感覺,我們展開了複音音樂片段相似性度量的研究。因為曾經使用過最長公共子序列實作卻效果不如預期,我們將音樂片段正規化後,視為座標平面上的時間、音高點對的集合,使用點對應與二分圖匹配的方法,定義兩個複音音樂片段的相似度為最大權重匹配的平均邊權。我們計算了資料集(JKUPDD)中相同、相異的音樂片段的相似性,調整算法中的參數,找出最適合的參數組合,並且透過音符之間的權重,畫出自相似度矩陣,發現樂曲中的重複片段。
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Development of an autonomous Search and Rescue Drone
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.
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運用疾病軌跡搭配深度學習偵測胰臟癌風險
目的:在台灣,胰臟癌雖非癌症發生數最高,但85%為末期,五年存活率小於5%,有癌王之稱。如何早期偵測胰臟癌風險,一直是醫療上的重大議題。本研究運用時間矩陣搭配深度學習進行大量變數之胰臟癌風險偵測。 方法:健保資料庫收集國人疾病、用藥等結構化資料,可藉此反映每人健康狀態。將三年內診斷與藥物碼轉為時間矩陣,以卷積神經網路訓練,訓練組與測試組比例為9:1。 結果:共計案例組1095名及對照組10950名,訓練後測試組表現之AUROC(area under the receiver operating characteristiccurve)為0.937,六十歲以上及以下AUROC分別為0.846及0.897。 結論:結論:能將診斷、藥物、時間轉成矩陣,是以疾病軌跡預測胰臟癌風險,且能找到新特徵,未來搭配健康存摺,為低成本、快速、大量的胰臟癌數位快篩。
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本次科展主題為探究屏東與臺灣其他地區海灘樣本的差異。我們選擇了具代表性的屏東地區海灘作為主要採樣點,利用數位顯微鏡比對外觀特徵,電腦影像軟體分析色調,透過篩網分析海灘樣本顆粒大小比例,並檢測其酸鹼性、硬度和KH等性質。 結果顯示,屏東和小琉球海灘主要由珊瑚、貝殼和少量有孔蟲殼體等生物碎屑組成,呈白黃色調;而臺灣其他地區的海灘沙粒主要由岩石碎屑組成,呈灰黑色。單位體積海灘樣本的重量測量結果並無明顯差異,水溶液的酸鹼值大多呈弱鹼性,TDS數值顯示不同區域的海水組成和溶解物有所差異,但屬於珊瑚砂海灘樣本的KH值平均超過10。這些差異是臺灣地理位置、河流侵蝕搬運堆積和沿海海流等因素共同作用的結果。
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「氫」雲直上-影響氫氣火箭飛行的各項因子探討-Discuss the Factors Affecting the Flight of the Hydrogen Rockets
本實驗主要在研究各項因子對氫氣火箭的影響,我們查了許多影片和資料,發現許多氫氣火箭實驗都沒有記錄各項因子的數據及比較,在歷屆科展的火箭實驗中,將氫氣作為燃料的作品也寥寥無幾,所以決定嘗試這個題目作為本實驗的研究主題。 我們的研究使用電解製造氫氣與氧氣,進行燃料、造型實驗,並用電腦計算出飛行高度,希望能找出最佳飛行高度因子。我們發現各種因子的飛升高度與質量、質心、燃料與造型有很大的關聯。 希望能藉由這些實驗讓人們更認識氫氣火箭,也能藉由氫氣火箭的飛行實驗讓大家更認識、更熟悉火箭之中的科學原理,讓大家對科學更有興趣。
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以元啟發式最佳化演算法進行鐵路時刻表排點
鐵路時刻表排點至今為止仍十分仰賴人工作業,且排班優劣對於乘客服務品質有顯著影響。本研究採用元啟發式最佳化演算法及模擬器進行旅客列車鐵路時刻表排點,旨在找出一份針對旅客需求、提升旅客運輸成功率且降低旅途時間的時刻表。我們提出一種班表編碼機制,可依此產生班表草稿。我們研發的模擬器可將班表草稿轉換為合法無衝突之班表。最後,透過登山演算法及基因演算法來搜尋班表草稿,並以模擬器評估優劣,我們實現了一個自動化排班系統。我們也以不同的乘客測資針對於不同演算法進行比較,並試圖找出表現最好的演算法。實驗結果指出我們的模擬器能有效率產生無衝突時刻表,且所提出之演算法操作相較現行班表可提升運輸成功率和降低旅途時間。
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人人人 人人 人人人門 - 以程式模擬人群疏散
本研究旨在透過自行撰寫程式,探討人群如何盡快脫離狹小空間,主要模擬個體所受的各種吸引力與排斥力、設立衝突處理規則,分析疏散效率並比較優劣。經過測試得知減少鑽空行為、排斥人群、略為排斥牆壁或障礙、不失自身判斷追隨他人足跡,有利整體疏散。另外,若人群出現移動模式異於他人的少數者,將不利整體疏散,但少數者人數不多下,愛好爭搶、鑽入空隙、較不排斥人群有助其個體疏散。 無論是否將疏散場域外廣場人群移動納入考慮,角落出口疏散效率皆較邊上優,且出口個數呈邊際效益遞減。但廣場中人群若步行六步內便停下休息,將導致邊上廣場入口堵塞。最後,逃離疏散場域後即往廣場邊界者,疏散效率表現相當於在廣場步行十步便佇足休息。
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