2021年

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.

色彩知覺是人類最重要的感官之一。由於形狀、亮度、空間頻率和色彩組成的不同，每個人對色彩的感知也有所差異。我們對此現象感到著迷，並決定進行一項研究，以識別和量化不同情況下的色彩誘導。 本研究選擇以環狀刺激作為主要圖像，以測量人類視覺色彩誘導。而本實驗主要利用紅色與綠色的誘導效果。實驗中，我們採用紅色及綠色基準做為目標環狀區域，並於其中添加可變性紅色目標，以測量受試者之視覺閾限。在色彩誘導的情況下，透過環狀刺激與測量所得之視覺閾限，我們可以識別並量化環狀刺激對色彩感知造成的影響。此外，我們也發現了環狀刺激中的單一環形如何影響人們對目標環狀區域的色彩感知。 我們利用實驗所得之結果，建立了一個預測並描述色彩錯覺與細胞反應相關性的模型，而此模型將會讓我們對人類視覺系統及神經間的側交互作用有更深一層的了解。

This is the self-driving and navigating vehicle which follows a track. This robot is made by our group. We made this robot together assembling the parts. This robot is commonly used in industries to shift goods and product. In this robot we have arranged all the things also metal detector which buzz when a metal is detected under it. This robot helps a lot in industrial life and is also easy to make if we learn the steps. This robot also needs programming to make it work. The programming software used for it is known as Arduino IDE. This is the figure of this robot in industries. Here the people are keeping goods in the pickup and shifting them. This robot can also run in white track, only if we do the programming right for the white track. Nowadays in cars too this type of system is used like example: Tesla model X. In the car this system is used and to avoid the obstacles something named Lidar is used. To make this vehicle follow its track and the motor to run different things are used like IR Sensor, and L298N motor driver module respectively.

球體在旋轉平台上的運動分三階段：進動階段、螺線振盪階段、打滑階段。進動階段、螺線振盪階段為兩個運動模式的疊加：迴旋半徑漸增的螺旋線運動、向平台中心靠近的平移運動。當迴旋半徑漸增至滑動摩擦力的上限值，球進入打滑階段並向外甩出平台。 研究紀錄球體質心運動參數，並以接觸點準靜態理論計算及滑動-滾動摩擦模型進行數值分析，找出各種變因與運動參數間的關係。 結果發現滾動階段中鋼球作迴旋運動的頻率f球和平台旋轉頻率f盤和有正比關係，且比例值和球標準化轉動慣量δ正相關。由滾動階段過渡到滑動階段的最大迴旋半徑Rmax和f球2成反比、和δ呈負相關、和滑動摩擦係數μk成正比。滾動摩擦使球向平台中心靠近，也使迴旋半徑漸增。平台傾斜或呈錐狀時，球體的運動會向水平方向偏移。

本研究開發一個新型的CRISPR-Cas9技術剪輯粒線體DNA，提供粒線體基因所造成疾病的一個有潛能之治療方式。在本研究中，我們將嵌入粒線體標的訊號序列後的 Cas9 蛋白質和 sgRNA 分子送入粒線體內，將 CRISPR-Cas9系統套用於粒線體中，並達成剪輯粒線體基因之目的。我們將 Cas9 蛋白質和 sgRNA 分子鑲嵌於同一質體上，有效導入CRISPR-Cas9系統於粒線體內，並觀察到剪輯之標的基因ND4含量下降了 32%，達到粒線體基因編輯之目標。雖然前人曾用ZFN (Zinc-finger Nuclease)和TALEN (Transcription Activator-like Effector Nucleases)成功編輯粒線體基因，但由於製作過程繁瑣和經費昂貴等種種原因，並未被廣泛使用。我們開發的新型CRISPR-Cas9粒線體基因剪輯系統將可以提供一個相對簡易且價格低廉的粒線體基因剪輯平台。

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.

手語為聾啞人士日常溝通的工具，但對一般人來說這是一種難以理解的溝通方式。本實驗使用深度學習的 Yolov3 與 Yolov4 模型訓練37個國語注音符號手勢，然後再驗證模型對圖片、影片、即時(Real time)攝影辨識的正確率。 實驗結果顯示：Yolo v3 圖片辨識度效果還不錯，但影片辨識度很差，而Yolo v4 不管在靜態的圖片或動態影片都有不錯的辨識率，另外在即時的影像辨識也有不錯的效果。 雖然有部分符號的辨識度很低，但這可能是訓練時照片拍攝的問題，如果可以改進拍攝的數量和技巧，相信可以大幅提升判讀的準確率。

從參考資料[1]可知，將凸n+2邊形利用n-1條不相交的對角線剖分成n個三角形的圖形數量即為卡特蘭數Cn。而我利用不相交的對角線把n+2邊形剖分成數個多邊形和三角形的組合，並從此類的剖分圖形與三角剖分圖形之關聯，進而由卡特蘭數的一般式推導出此類剖分圖形數量的一般式。在本研究中可得，若到把n+2邊形剖分成一個k+2邊形和多個三角形的圖形數量是(2n-k+1 n+1) ；把n+2邊形剖分成一個k+2邊形、一個m+2邊形和多個三角形的圖形數量，當m≠k，數量為n+2/2(2n-k-m+2 n+2) ，當m=k時，數量為n+2/2(2n-2k+2 n+2) ；把n+2邊形剖分成一個k1+2邊形、一個k2+2邊形、一個k3+2邊形、和n-k1-k2-k3 個三角形的剖分圖形，當k1,k2,k3兩兩相異時，數量為(n+2)(n+3)(2n-k1-k2-k3+3 n+3) ；把n+2邊形剖分成一個K1+2邊形、一個K2+2邊形、一個K3+2邊形、一個K4+2邊形和n-K1-k2-k3-k4個三角形的剖分圖形當k1,k2,k3,k4兩兩相異，數量為(n+2)(n+3)(n+4)(2n-k1-k2-k3-k4+4 n=4)。並猜測若k1,k2,...,ki兩兩相異時，把n+2邊形剖分成一個k1+2邊形、一個k2+2邊形、…、一個ki+2邊形、和n-Σkj 個三角形的剖分圖形數量為(n+i)!/(n+1)!(2n-Σkj+i n+i) 。

In Singapore’s evolving cyber landscape, 96% of organisations have suffered at least one cyber attack and 95% of organisations have been reporting more sophisticated attacks in the frame of one year according to a 2019 report[1] by Carbon Black. As such, more tools must be utilised to counter increasingly refined attacks performed by malicious actors. Honeypots are effective tools for studying and mitigating these attacks. They work as decoy systems, typically deployed alongside real systems to capture and log the activities of the attacker. These systems are useful as they can actively detect potential attacks, help cybersecurity specialists study an attacker’s tactics and even misdirect attackers from their intended targets. Honeypots can be classified into two main categories: 1. Low-interaction honeypots merely emulate network services and internet protocols, allowing for limited interaction with the attacker. 2. High-interaction honeypots emulate operating systems, allowing for much more interaction with the attacker. Although honeypots are powerful tools, its value diminishes when its true identity is uncovered by attackers. This is especially so with attackers becoming more skilled through system fingerprinting or analysing network traffic from targets and hence, hindering honeypots from capturing more experienced attackers. While substantial research has been done to defend against system fingerprinting scans (see 1.1 Related Work), not much has been done to defend against network traffic analysis. As pointed out by Symantec[2][3], when attackers attempt to sniff network traffic of the system in question, the lack of network traffic raises a red flag, increasing the likelihood of the honeypot’s true identity being discovered. In addition, the main concern with regards to honeypot deployment being their ability to attract and engage attackers for a substantial period of time, an increased ability to interest malicious actors is invaluable. Producing human-like network activity on a honeypot would appeal to more malicious actors. Hence, this research aims to build an intelligent web-surfer which can learn and thus simulate human web-surfing behaviour, creating evidence of human network activities to disguise the identity of honeypots as production systems and luring in more attackers interested in packet sniffing for malicious purposes.

濃厚氣味的中藥，吃了能讓人強健體魄，那植物服用後呢？研究發現，綠豆能感受肉桂粉中的氣味分子”肉桂醛”，並透過改變其生理與生長的發育來減緩其在鹽逆境下細胞死亡的程度，提高長期耐鹽能力。本研究顯示，熏完肉桂醛的綠豆能透過減少氣孔數、使澱粉代謝、增加根系來應對鹽逆境下的缺水問題，在生化研究方面，能透過在根部提前累積脯胺酸來應對滲透壓逆境。此外肉桂醛氣味能激發綠豆的抗氧化力，我們發現，肉桂醛能讓綠豆提前累積抗氧化物(脯胺酸、抗壞血酸)，另能提高抗氧化酵素活性(POD、APX)來應對鹽逆境下的氧化傷害。本研究發現綠豆能感受肉桂醛氣味並提升其長期耐鹽能力，期待未來能將研究成果用於農業，減少逆境對農業帶來的損失。