2022年

Harmful microorganisms in food can cause deterioration of human health, poisoning and in some cases even death. Especially fresh meat and chicken products create a suitable environment for the growth of microorganisms in terms of the nutrients it contains, water activity and pH level. For this reason, detection of microorganisms in meat products is an important issue in terms of food safety and human health. In this project, it is aimed to detect live microorganisms in meat products, especially chicken meat, in a simple, non-destructive, non-contact and fast way using laser speckle method. Laser speckle images of healthy and stale chicken meat were taken, contrast parameter and correlation analysis of the obtained patterns were made. It was observed that the contrast parameter for staled chicken meat increased by approximately 3 times compared to fresh chicken. This increase provides an understanding of the difference between contaminated chicken and fresh chicken. Speckle density changes over time in relation to the movements of living microorganisms. Thus, the correlation in laser speckle density patterns taken from contaminated tissues is disrupted. In the measurements taken with photodiode, by analyzing the change of light intensity of the speckle patterns on fresh and contaminated tissues over time, the detection of microorganisms was made easier and more precisely without the need for image processing. The proposed measurement system is a new method that detects meat contamination with laser speckle imaging. It can be developed and made portable and can be used easily in homes. Since it is a simple, non-destructive and fast method, it can be used to determine the shelf life of meat in food distribution places and markets. In addition, it has the potential to be calibrated and used for other food products other than meat products. The system developed with this study is cheap and easy to use, and the laser speckle imaging method is used in a different field other than biomedical, contributing to the literature.

本實驗藉由操控目標字鄰群大小及是否最高頻兩項變因，研究國、高中生在是否具有「聲旁規則性」與「鄰群發音一致性」的情況下，兩群漢字的辨識歷程，由實驗可知： 一、 國、高中生對於具有「聲旁規則性」及「鄰群發音一致性」，與不具有「聲旁規則性」及「鄰群發音一致性」兩種情況下的漢字辨識歷程中，大鄰群目標字的辨識時間較小鄰群目標字長，即「大鄰群」因素在其漢字辨識歷程中產生了「抑制作用」。 二、 本實驗中，「非最高頻」鄰群目標字的辨識時間較「最高頻」鄰群目標字長。即「最高頻」因素在國、高中階段的漢字辨識歷程中未產生「抑制作用」。 三、 國、高中階段受試者雖皆呈現出「大鄰群」的「抑制作用」且未顯示「最高頻」因素的「抑制作用」，但兩者相較之下，可由Naming之實驗發現，高中生的漢字辨識歷程已更趨近於成人。

This paper represents IOT Based Automatic Water Temperature Adjustor. IoT (Internet of Things) refers to the network of physical objects that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. This system is for adjusting water temperature according to the possible surroundings such as home temperature, atmosphere temperature, etc. To solve problems like high water temperature while using, time-consuming waiting for water to heat and cool, high power consumption, and not satisfying water temperature this system offers the feature for automatically adjusting the temperature. Arduino, DHT11 (Temperature-Humidity Sensor), Bread Board, DS18B20 (Water Temperature Sensor), Jumper Wires, Resistor, I2C OLED, Water Heating Coil, Relay and LED are used for operating this system. The application of this system is very vast as it can be implemented in power plants, hospitals, mountain regions, local homes, and lodges. This system is time-saving, cost-efficient, easy to implement, provide automatic features, less power consumption, safety, and many more. Compared to other water geyser systems it has the feature of automatically detecting the environmental temperature and adjusting the temperature of the water accordingly. This system is still in its developing phase.

Introduction: Using advanced technologies such as nanotechnology in the food and fishery industry, as one of the most important industrial sectors of countries, has received too much attention. Traditionally, fishing and hunting have been considered important sources of supplying food. The subject and methodology: The study aims to investigate nanotechnology for detecting fish hatching time. This is a review article that collects the information from databases such as Sid, civilica, and Google Scholar. In the end, 22 papers were studied for extracting and collecting the required information from the abovementioned scientific database. Finding: After examining the food, drug, and agricultural-related papers published from 2009 to 2020, it was concluded that small Nano-sensors, controlling & monitoring systems made from nanotechnology can be installed on fishing nets, fishing rods, and other fishing equipment. These devices (Nano-sensors and controlling & monitoring systems) will help fishes so that they don’t get caught. In this way, as a fish gets close to the fishing equipment, it will receive sound, smell, or heat-based alarm. Therefore, the fish will stay away from the fishing equipment. The result: according to the finding of this study, it can be concluded that excessive fishing in the hatching time will be avoided by the application of nanotechnology in the fishing equipment. As a result, the following advantages will be secured: 1- There are lots of opportunists who misuse fish during the hatching time. With the application of nanotechnology, they will be stopped. 2- Opportunists are ambushing in different time points to misuse fish. Also, the guards might be ignorant. With the application of nanotechnology, guards are no longer required. 3- This plant is cost-effective too.

In this project, we evaluate the effectiveness of Random Shuffling in the Cross Lingual Information Retrieval (CLIR) process. We extended the monolingual Word2Vec model to a multilingual one via the random shuffling process. We then evaluate the cross-lingual word embeddings (CLE) in terms of retrieving parallel sentences, whereby the query sentence is in a source language and the parallel sentence is in some targeted language. Our experiments on three language pairs showed that models trained on a randomly shuffled dataset outperforms randomly initialized word embeddings substantially despite its simplicity. We also explored Smart Shuffling, a more sophisticated CLIR technique which makes use of word alignment and bilingual dictionaries to guide the shuffling process, making preliminary comparisons between the two. Due to the complexity of the implementation and unavailability of open source codes, we defer experimental comparisons to future work.

This paper represents IOT Based Automatic Water Temperature Adjustor. IoT (Internet of Things) refers to the network of physical objects that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. This system is for adjusting water temperature according to the possible surroundings such as home temperature, atmosphere temperature, etc. To solve problems like high water temperature while using, time-consuming waiting for water to heat and cool, high power consumption, and not satisfying water temperature this system offers the feature for automatically adjusting the temperature. Arduino, DHT11 (Temperature-Humidity Sensor), Bread Board, DS18B20 (Water Temperature Sensor), Jumper Wires, Resistor, I2C OLED, Water Heating Coil, Relay and LED are used for operating this system. The application of this system is very vast as it can be implemented in power plants, hospitals, mountain regions, local homes, and lodges. This system is time-saving, cost-efficient, easy to implement, provide automatic features, less power consumption, safety, and many more. Compared to other water geyser systems it has the feature of automatically detecting the environmental temperature and adjusting the temperature of the water accordingly. This system is still in its developing phase.

本研究對磁攪拌子的懸浮做出一連串的實驗探究與數值模擬法的建模。透過觀察實驗，分析磁攪拌子與驅動磁鐵的互動，提出磁攪拌子跳起與穩定懸浮的原因。建立運動方程式，並使用數值模擬法預測各種變因的影響，也編寫程式語言使模擬的結果以動畫呈現。依照理論的預測，設計實驗驗證數值模擬法的適用性；探討懸浮的動能，發現耦合性質。 在應用方面，懸浮運動是攪拌與懸浮的結合，應可為黏度差異大之化學反應提供穩定反應的攪拌系統。本研究為增進「懸浮式攪拌」的實用性，以數值模擬法測試多極驅動系統的可行性，並成功達成；探討長度對攪拌效率的影響，提供在弱驅動系統中達成懸浮的辦法。為了在應用層面上有更好的發展，透過理論模型提出控制懸浮高度的方法，而實驗結果指出此方法的可行性。為尚不明確有何應用的「磁攪拌子懸浮運動」提供明確的發展方向。

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。

核塌縮超新星(Core-Collapse Supernova，CCSN)，又名II型超新星(type II supernova)，是宇宙中最重大的爆炸現象之一，在天文物理學上有許多探索與應用。核塌縮超新星被認為源自於大質量恆星的死亡，但是目前尚不清楚大規模恆星演化及有關核塌縮超新星的物理學，為獲取有關核塌縮超新星的知識與應用，我們使用一維程式碼Modules for Experiments in Stellar Astrophysics (MESA)執行大質量的恆星演化模型。對於此次研究中我們模擬大質量恆星從零齡主星序(zero age main sequence，ZAMS)演化為核塌縮超新星，並透過考慮不同質量祖星(progenitor)上的各種爆炸能量、金屬量(metallicity)、角動量(angular momentum)展示其演化狀態，討論這些恆星演化的物理參數如何影響超新星爆炸及呈現的光變曲線。我們的模擬結果與觀測數據相當符合，可解釋其祖星的起源及物理意義。

本研究針對學習圖論演算法的需求，設計一套使用者友善的繪圖軟體Graphene。Graphene繪圖程式除了提供高可讀性的繪製結果，作為輔助繪圖的工具外，也可直接輸入競賽題目的文字格式測試資料產生繪圖結果，並結合現有繪圖演算法，改善、優化樹與類樹圖的繪製結果。此外，也加入時間軸、自訂外觀、參數調整、匯出圖片等功能，幫助學習者理解圖論演算法，亦可幫助教師製作教材，有助於圖論演算法教學。 Graphene採用的繪圖演算法以force-directed graph drawing演算法為基礎，實作節點的分布。然而初始的節點分布會影響繪圖結果，因此我們利用biconnected component、block-cut tree等圖論結構對圖的繪製進行優化。首先找出圖的biconnected component及關節點，重新定義block-cut tree裡的block，接著利用radial tree的布局方式配置每個block，再套用force-directed graph drawing演算法，得到最後的布局結果。如此可以減少不同block之間的交錯，得到較佳的結果。