本研究區域為蘭陽溪口溼地與五十二甲溼地，各選擇5和6個採樣點，檢測水體中的溶氧度、pH值、導電度、總固體溶解量(TDS)、水溫以及濁度並記錄當時氣溫。 在蘭陽溪口溼地中我們發現越靠近出海口，導電度、TDS越高。採樣點4濁度為最高，猜想可能與位置有關。五十二甲溼地中則以採樣點6的導電度、TDS為最高，濁度、pH值及溶氧量則是採樣點3最高。我們還藉由五十二甲濕地分區使用圖，比較人為因素對水質的影響。採樣點3為遊客休憩區，測得的濁度、pH值皆較高，採樣點6為生態區，測值相對較小，推測人為因素與水質有關聯。最後，在10月10日的數據中，發現蘭陽溪口溼地的導電度特別高，推測潮汐現象為可能造成此現象的因素，也是未來研究的方向。

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.

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.

To investigate the reproduction success and natural recruitment of several Cyprinidae fish and Claridae fish species in the Allemanskraal Dam. The purpose of the project included investigating whether each individual fish species studied has a successful 2020/2021 spawning season in comparison with each other. Sections of the seine net were measured along with a distance of 10 along the shoreline. The ends of the seine nets were attached to one foot and the top of the net was held by hand. Both volunteers moved in unison while covering the 10m. The volunteer in the “deep end” moved towards the shoreline creating a semi-circle while the other volunteer remained stationary. The two ends of the net were then pulled onto the shore and the fish were collected. The results found that the Labeo Umbratus and Cyprinus carpio had the most successful spawning seasons with the highest recorded numbers. These high numbers of the Labeo Umbratus can be due to the fact that the species lays a large number of eggs. The high numbers of the Cyprinus carpio is due to the lower numbers of the other fish species as previous studies have shown that the species negatively impacts the environment which could in turn negatively impact the other fish species. The Claridae gariepinus and Labeobarbus aeneusas were the lowest. The low numbers of the Labeobarbus aneusas may be due to their slow growth and late maturity rate. The Labeo capensis had an average number relative to the other species and this is due to the fact that during the sampling period the dam was at 100% capacity as this is essential for the survival of the juvenile fish. The hypothesis was accepted as the Labeo Umbratus, Cyprinus carpio and Labeo capensis all have a successful spawning season. However, due to the size of the Cyprinus carpio, they would be most suited for a small scale fishery.

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。

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。

A variant of the coronavirus (2019-nCoV or COVID-19) was reported in Wuhan, China on December 31, 2019, spreading rapidly around the world. Owing to a plan to reactivate the economy, the Mexican government, requested to implement protective measures to enter establishments with confined spaces: wear a mask, provide alcohol-based hand rub and the measurement of body temperature, allowing problem when not have a fever; however, these measures cause long waiting lines, causing contagion risk. To support this problem, applied and experimental research was used, generating as a result, the creation of a robot that moves autonomously thanks to a line follower sensor. Dispenses alcohol-based hand rub and determines the temperature by means of an infrared sensor, checking that the distance is adequate, with an ultrasonic sensor, using a buzzer that emits a sound of half a second when it performs a normal detection, but, if it is equal to or greater os 38 ° C, emits a sound for 10 seconds asking the person to leave the line and go to a medical service, helping to reduce problems infections in lines

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。

The aim of this research was to investigate whether the ecology and biology of the Orange River mudfish Labeo capensis were suitable for the species to be used in fisheries. Three fleets of the gill nets were set, parallel to the shore. One fleet was lifted, and the fish were collected by hand. The two remaining fleets were lifted the next day. The seine net was pulled for 10 metres within the littoral zone. The net was then pulled towards the shore of the dam and the procedure was repeated four times. The four fyke nets were set parallel to the shore and were left for two nettings nights and then lifted. All fish caught were collected by hand and placed into buckets. The majority (82.93%) of the fish caught were within the 0-100 mm size class. The 101-200mm and 201-300mm size classes contain similar numbers of fish, while no fish were caught in the 301-400mm size class. The hypothesis was accepted. Allemanskraal Dam, as of the study period, has a very small juvenile fish population of L. capensis, as only 7 out of 41 fish individuals caught were within the 101- 300mm fork length size class. These results show that the population of L. capensis is not established as of yet, as the research did was right after their breeding season. Historical research has shown that sexually mature individuals of the L. capensis species tend to be a minimum of 300mm SL, 4-6 years after hatching. The population was largely young-of-the-year and may develop into an established population in 3-4 years (after sexual maturity). The L. capensis population in Allemanskraal Dam has the potential to be a fishery species if suitable conditions are maintained. Establishing this species’ potential will therefore allow economically viable fisheries to utilise them sustainably and to their full economic potential.