2022年

According to CNN Indonesia 2020, the demand for e-Commerce in Indonesia has nearly doubled during this pandemic. This surge in demand calls for a time-efficient method for warehouse order-picking. One approach to achieve that goal is by incorporating automation in their warehouse systems. Globally, the market of warehouse robotics is expected to reach 12.6 billion USD by 2027 (Data Bridge Market Research, 2020). In this research, the warehouse system studied would utilize AMR (Autonomous Mobile Robots) to lift and deliver movable shelf units to the packing station where workers are at. This research designed a heuristic algorithm called A.N.T.s (Algorithm for Navigating Traffic System) to conduct task assigning and pathfinding for AMR in the automated warehouse. The warehouse layout was drawn as a two-dimensional map in grids. When an order is placed, A.N.T.s would assign the task to a robot that would require the least amount of time to reach the target shelf. A.N.T.s then conducted pathfinding heuristically using Manhattan Distance. A.N.T.s would help the robot to navigate its way to the target shelf unit, lift the shelf and bring it to the designated packing station. A.N.T.s algorithm was tested in various warehouse layouts and with a varying number of AMRs. Comparison against the commonly used Djikstra’s algorithm was also conducted (Shaikh and Dhale, 2013). Results show that the proposed A.N.T.s algorithm could execute 100 orders in a 27x23 layout with five robots 9.96 times faster than Dijkstra with no collisions. The algorithm is also shown to be able to help assign tasks to robots and help them find short paths to navigate their ways to the shelf units and packing stations. A.N.T.s could navigate traffic to avoid deadlocks and collisions in the warehouse with the aid of lanes and directions.

近年來由於電腦視覺的蓬勃發展，物件辨識模型被廣泛運用在生活中，例如自動駕駛、醫療影像、農作物檢測等等。對於要在戶外運作的模型，由於檢測物體的背景會隨著時間、地點、季節、光照強弱等因素不斷改變，通常需要大量且多元的資料才能避免模型過擬和，然而取得多元的資料需要花費大量的人力與時間在收集以及為這些新資料標籤。 本研究利用影像風格轉換模型作為資料增強的方法，將於晴天拍攝的街景圖轉成夜晚及雨天，使原本只有晴天的資料集有更多元的資料。結果證實使用風格轉換模型生成的影像訓練的物件辨識模型的準確率在某些情況下有顯著的提升。此方法的優點在於能夠快速產生多樣風格的資料，由於是對影像的風格做轉換，影像的內容沒有改變，因此能夠沿用原有的標籤，同時節省了蒐集及為新影像標籤的人力及時間。

本研究利用合成生物學技術開發的創新基因組篩檢平台PRISM(v2.0)，採用合成轉錄因子(crispr-TF)辨認DNA但不進行剪切，透過修改CRISPR/Cas的PAM-interacting (PI) domain序列打破其辨認限制，由原本NGG序列變成可以結合NAG的序列，提升crispr-TF在高通量基因組的篩選能力，期待未來可以做出辨認NNN序列，以此技術初步成功建構Chk2/Rad53所參與的基因網絡，讓失去Chk2/Rad53功能的酵母菌能在DNA損傷的情況生存。Chk2/Rad53蛋白磷酸酶在DNA修復的訊息傳遞中調控龐大的基因網絡，其中潛在大量不同調控路徑聯結的組合性，過去的研究都無法有效地分析且重建完整的DNA修復機制。未來將進一步探討Chk2/Rad53調控的下游基因組，並以此新技術和研究應用於複雜腫瘤與老化疾病的預防及治療。

As the world has become concerned about the global waste crisis and global warming, there has been a surge of research within materials science to find materials that would replace plastic, such as bioplastics or biodegradable materials, in order to reduce environmental pollution. Plastics generates the microplastics that allowed them to become cross contamination enter the ocean through land, sea and river. Science research found (Lusher et al. (2017)) over 220 species of marine animals ingested microplastic, half of them are considered relevant for commercial purpose and increasing the risk of human consumption as it can induce immune response, oxidative stress, cytotoxicity, alter membrane integrity and cause differential expression of genes. Thailand is also experiencing such a challenge, as seen by the overabundance of plastic waste that might take centuries to decompose. For example, around 1680 million personal hygiene products such as diapers, sanitary napkins, and tampons are used each year. This study highlights the use of naturally accessible absorbent fibers from malva nut (Scaphium scaphigerum) (G. Don) Guib & Planch.), which is widely available and biodegradable in nature and has a low carbon footprint. This study also aimed to develop natural absorbent pads using compostable spun, external layers, and biodegradable glue. A prototype sanitary napkin with biodegradable absorbent pads was developed and evaluated for absorption ability, absorption rate, pH, and biodegradability. The absorbent material absorbed up to 19 times its weight in 2 minutes and 33 times its weight in 2 hours, which is enough for an average of 80-150 mL of menstrual blood. The prototype napkin deteriorated within 99 days, based on naked eye observation. Some signs of degradation and microorganisms growing on the prototype were also observed from scanning electron microscopic images. According to the findings, natural absorbent pads made from malva nut have the potential to be converted into sanitary napkins. Furthermore, it is proposed that the components, which include superabsorbent renewable materials, spinning compostable layer, external compostable layer and biodegradable glue, may be used in a variety of goods, including adult diaper pants, incontinence pads, and laboratory bench mats.

This research is motivated by the differences in the people's perceptions, mainly youth about the omed-omedan tradition. The difference is that many people think that the omed-omedan tradition violates the norms of decency and is also called the pornography tradition. The purpose of this study is to, 1) describe the mechanism of applying omed-omedan tradition recognition attitudes through augmented reality-based card games, 2) analyz the impact resulting from the application of omed-omedan tradition recognition attitudes through augmented reality-based card games, and 3) analyze about the feasibility of application resulting from the application of omed-omedan tradition recognition attitudes through augmented reality-based card games. This research is a type of R&D research conducted at Bali Mandara State High School from July 1-September 6, 2021. The subjects of this study were the teenagers of Kaja Sesetan Indigenous Village and the object of this study was the omed-omedan tradition through augmented reality-based card games. The data collection method used is the literature studies, questionnaires, interviews, and validation questionnaires. Data is processed based on qualitative descriptive approach and quantitative descriptive approach. The results showed that the mechanism of implementing the omed-omedan tradition originated from the download of assistive devices, namely android studios and applications from AR, the impact of augmented reality-based card games was seen as very helpful in the introduction of the omed-omedan tradition and was seen as able to help increase the love of local culture, besides that the media used was also very popular by players because it was seen as interesting and very helpful. Based on the feasibility tests that have been calculated, this game is considered very feasible to implement and researchers hope that the innovations that have been created can effectively provide understanding to help out the local community about omed-omedan tradition.

台灣火災地點以建築物占最大比例，在火災現場時常為了逃生及救火而打破門窗，造成建築物內部濃煙流動面積擴大，而釀成更大的災害，故本作品目的為研究「方形結構四周開口大小與數量對火焰與煙霧燃燒狀況的影響」，本研究從熱力學、流體力學、結構學三個角度探究此議題，並以煙囪效應與煙層逆流效應為理論基礎，使用壓克力搭建方形盒子來模擬建築物，並以四面壓克力上的開口大小及數量進行實驗，使用火焰及煙霧作為實驗介質，火焰方面以高度與溫度作為應變變因，煙霧方面則以MQ-2煙霧氣體感測器於結構內部進行濃度測量，同時也使用CFS-MODEL的FDS進行結構內部模擬，綜合實體實驗及各結果可發現，與一般想像不同，並不是開啟門窗就能撲滅火勢，甚至可能因為湧進過多氧氣而導致火勢更加嚴重，開口面積與火焰強度關係成二次函數曲線，本研究可供建築物搭建時的火災防範參考以及防災的宣導，並有進階研究的可能性。

在歐氏幾何和射影幾何中，相異五點可決定一圓錐曲線。若給定任意四邊形，是由四邊形的四個頂點及異於此四頂點的第五點來決定圓錐曲線，則稱此四邊形為圓錐曲線内接四邊形。 圓冪定理是一個圓內接四邊形的幾何定理，包含相交弦定理、割線定理、切割線定理等三個定理，我們將圓冪定理推廣至圓錐曲線內接四邊形。首先由圓錐截痕推廣圓內兩交弦定理，是考慮兩垂直交弦，進而推導出圓冪定理推廣一式及區分圓錐曲線種類。接著利用圓錐曲線的方向直徑、邊或對角線斜率及平行邊的切線長推導出圓冪定理推廣二式、三式及四式，推廣式是採統一與歸納方式呈現。 其次，由解析幾何推導另一種圓冪定理推廣式(推廣五式)，加上圓錐曲線直徑性質，論證出二種圓錐曲線及其内接四邊形的作圖及其判定條件。最後也證明圓錐曲線內接四邊形判定定理及有趣的錐線中心軌跡圖形。

本研究討論以酒精、沙拉油、飽和醋酸鈣溶液，尋找最佳酒精凝膠的穩定度，增加凝膠穩定度方法：(1)密閉系統，(2)飽和醋酸鈣溶液：酒精以1：5的比例，(3)添加沙拉油時，穩定度會下降，但添加使用過的廢油時，穩定度會增加。 沙拉油或回收廢油皆無法直接點燃做為燃料，但若溶入酒精凝膠中，則可製成再生固體燃料，本研究結論：回收廢油10克、酒精10 mL、飽和醋酸鈣溶液2 mL，於室溫經簡單混合，就可製得燃燒效能與市售酒精塊相仿、大於200 cal/ g的自製固體燃料；若是成分較簡單的回收廢油，除酒精及飽和醋酸溶液，若再添加適量硬脂酸亦可製得固體燃料。本研究讓「回收廢油」產生新的再利用的機會，對環境、綠能有所貢獻。

網路上常常會使用驗證碼(CAPTCHA)防止自動化程序取得網站資源，而一般而言，若驗證碼是可以輕易取得，十分容易被深度學習網路破解。然而，對抗式攻擊(adversarial attack)可以騙過許多深度學習網路。因此，本研究目的為建立能夠破解對抗式攻擊的深度學習網路。主要包含三個部分：建立Captcha breaker、使用對抗式攻擊影響breaker、防禦對抗式攻擊。Captcha breaker的部份使用模擬的目標驗證碼作為訓練資料，以解決訓練資料不足以及人工標籤的問題；而破解adversarial attack會使用adversarial training以及random noising的技術進行。

本研究的腦波辨識基於特徵提取，可應用於身分認證，具有不能被仿冒的優點。我們用低成本高便利性的腦波儀，自行撰寫程式讀取原始腦波，建立一致性的實驗程序。首先用腦波專心度的高低來控制智能車，再用腦波來測謊，有隱藏說謊行為時會觸發高電位腦波，在兩項前期研究後發現可用腦波特徵進行身分認證。三位受測者於不同日期提取10份腦波，每份腦波紀錄5120筆數據。接著我們反覆嘗試組合數十種統計函數進行特徵提取，找到兩項最佳特徵，達成將大量凌亂腦波資料降低維度又具有辨識力。我們腦波辨識分類方法使用近鄰演算法，測試程序用盲測交叉驗證法，辨識正確率百分百。最後我們用Arduino板來展示腦波辨識應用於腦波身分認證，資料庫中只要儲存每位受測者的腦波特徵值，就能在數秒內正確辨識說出受測者身分，顯示每個人腦波是不同的，而且能用特徵將其分辨出來。