本研究提出一套創新的體溫檢測方式，透過全新的檢測演算法架構深度解析脈搏訊號中的特徵，並結合深度學習神經網路開發一套體溫檢測的嵌入式系統。本研究基於血液共振理論，將光體積變化描計圖法擷取到的脈搏訊號處理，從中擷取共振峰值及其變化量，並開發演算法實時檢測血液循環中諧波的微小變化，改善當前分析方法著重在計算平均值，無法呈現即時狀態的缺失。本研究提出的系統和演算法所延伸的深度學習體溫檢測系統準確度在±0.16°C，同時預警系統可以擴展至多種趨勢相關的臨床症狀。此外，本系統實作出嵌入式AI技術，並且以聯邦式學習方法保障資訊安全，將資料保存於本地，上傳訓練調整後的參數到雲端，對邊緣運算領域能做出實質貢獻。

溫熱化學治療(Hyperthermic Intraperitoneal Chemotherapy, 簡稱HIPEC)，為將化療藥物加熱後灌注到腹腔內殺死癌細胞，但溫熱化學治療只能在開刀時使用，治療次數有限。為達到多次的熱化療效果，本研究開發奈米氧化鐵藥物磁性複合微粒(Nano iron oxide magnetic drug complex particles, NIOMP)，可利用開刀時包覆複合微粒於腹腔，術後用磁場加熱，加上微粒化療藥物釋放，達到多次溫熱化學治療。NIOMP以鐵氧化物奈米粒子為核心，海藻酸鈉為外殼體，利用電紡法將前其與氯化鈣交聯產生凝聚性微粒。數據顯示最佳製作條件為16 kv高電壓、距離4 cm、噴速5μm/s，可得直徑大小約為200~450 μm穩定性高微粒。藥物釋放實驗顯示，NIOMP於2~7小時藥物釋放速率較穩定。利用可變磁場之電磁效應加熱NIOMP中氧化鐵磁顆粒，可於30分鐘內快速升溫至43℃。細胞相容性測試結果得知，NIOMP對細胞無毒性。本研究改善HIPEC的治療限制，可多次針對腫瘤患部局部熱化學治療，未來將可改善病人存活率。

近年河川或海上塑膠垃圾與油汙對環境造成傷害，解決環境污染備受重視。近期荷蘭用-大氣泡屏障，成功將塑膠垃圾阻攔，因此我們興起了「尋找最佳氣泡牆模型」。本研究目的為：分析「氣泡牆形狀、氣泡間隔以及氣泡大小」是否影響攔阻效果。結果發現：1.凹向水源300弧線氣泡牆攔阻效果最佳；2.氣泡越小間距越小，攔阻效果越好，此與荷蘭研究員論點相呼應；3.相較於形狀固定的塑膠垃圾，形狀會變的油汙較難攔阻；4.具厚度氣泡牆，攔阻效果更勝多道獨立的氣泡牆；5.「緊鄰的兩道300弧線氣泡牆」的攔阻效果是目前我們所做的模型中效果最好的。因此我們建議，未來在實際運用氣泡牆攔阻汙染源時，可採用此模式解決環境污染問題。

This project aimed to study the motion which occurred from the end point on the circumference of the outermost circle by moving the center on the circumference of a preceding circle and the center of an innermost circle at origin. According to the study, when angular velocity was changed, it caused the different of loci. Based on the above information, finding the locus of the point on circumference of n-th circle that formed by moving the center of any radius circles on circumference of preceding set of circles was studied to get general equation. A set of circle and locus were created with GSP program. First, set the same radius circles on the X-axis with the first circle at origin, then found the relationship that occurred from the characteristics of locus. The result showed that if the ratios of angular velocity are 1:1:1, 2:2:2, 3:3:3, ..., …, n:n:n or 1:2:3, 2:4:6, 3:6:9, …,nw1:nw2:nw3, the characteristics of locus will be the same, while the others will be different. Finally, the equation of locus was found as follow: (x,y) = { ..........see in abstract...........} when .........see in abstract........... Where ri is the radius of i-th circle, zeta i is an angle between the radius of i-th circle and X-axis, wi is the angular velocity, t is elapsed time and alpha i is a starting angle between the radius of i-th circle and X-axis.

In the present paper I studied the winter territories of the Eurasian Wren (Troglodytes troglodytes) in the urban environment of the city of Hradec Králové. The males of this species were detected through the aggressive reactions to the playback of its conspecific call. The Eurasian Wren territories were detected at seven out of the ten observation points in the city. The frequency of the territories decreased during the observation period from October to January and it was also affected by the structure of the biotope. It seemed that the wrens preferred trees and avoided lawns and isolated growths. That illustrates how important it is to maintain wildlife corridors in the cities. Individuals of seven other bird species were seen reacting to the playback of Eurasian Wren songs or warning calls. Eurasian Wren may be applied as an indicator species of the ecological value of the urban environment. Through this species, we can access such quality also for the human inhabitants.

This work is devoted to solving the problem of orientation in the space of visually impaired people. Working on the project, a new way of transmitting visual information through an acoustic channel was invented. In addition, was developed the device, which uses distance sensors to analyze the situation around a user. Thanks to the invented algorithm of transformation of the information about the position of the obstacle into the sound of a certain tone and intensity, this device allows the user to transmit subject-spatial information in real time. Currently, the device should use a facette locator made of 36 ultrasonic locators grouped in 12 sectors by the azimuth and 3 spatial cones by the angle. Data obtained in such a way is converted into its own note according to the following pattern : the angle of the place corresponds to octave, the azimuth corresponds to the note and the distance corresponds to the volume. The choice of the notes is not unambiguous. However, we used them for the reason that over the centuries, notes have had a felicitous way of layout on the frequency range and on the logarithmic scale. Therefore, the appearance of a new note in the total signal will not be muffled by a combination of other notes. Consequently, a blind person, moving around the room with the help of the tone and volume of the sound signals, will be able to assess the presence and location of all dangerous obstacles. After theoretical substantiation of the hypothesis and analysis of the available information, we started the production of prototypes of the devices that would implement the idea of transmitting information via the acoustic channel.

本研究期望能藉由探討聲波的相關物理特性，研發出具備環保且使用安全的滅火器。研究過程中，運用程式設計與藍芽無線傳輸的方式，傳輸並測試許多低頻的頻率，並深入探討其聲壓頻譜、聲壓、聲強、聲功率分布等物理特性。經由聲壓頻譜分布可找出最佳（穩定較高）的頻率，藉由聲波物理特性的探討，可瞭解為何聲波處於低頻時具有滅火的特性，再由3D PRINT技術設計出周邊輔助的裝置，並完成研究作品。

Double Parallelogram Lifting Mechanism (DPLM) is a compact and stable lifting mechanism with a large extension range widely adopted in robot designs. Rubber bands and springs are often installed on the DPLM to lighten the motors' load and maintain its height, yet the installation positions are often obtained through trial and error. This project aims at finding the optimal rubber band installation positions for DPLM using modeling and optimization techniques. A mathematical model which describes the forces and moments acting on all the linkages of DPLM was derived based on the conditions for the static equilibrium and verified with a 3D simulation software. A genetic algorithm (GA) was implemented to optimize rubber band installation positions, which managed to find solutions with the overall root-mean-square- error (RMSE) of the net moment less than 2 for 2 to 6 rubber bands. A further statistical analysis of 50000 random rubber band samples showed that installing rubber bands in triangles is the best solution with the overall lowest RMSE. A test was conducted with a prototype of the DPLM and the results were consistent with our model and optimization. This project derived and verified a mathematical model for the DPLM, and found the optimal way and positions to install rubber bands. The results of this project provides a theoretical basis for controlling DPLM with rubber bands, allowing it to be further adopted in industrial robots that require repetitive lifting and lowering such as inspection robots and aerial work platforms.

The lack of drinking water in human settlements triggers a series of problems that are linked and affect the development of humanity: health problems, lack of water security for companies, lack of jobs, insecurity, among others. We observe this problem in the communities of the municipality of Las Vigas de Ramírez, Veracruz, where there is a great problem with the water supply, although there is a high presence of mist. Faced with this situation, we undertook the task of investigating a water harvesting method that is easy to implement, operate and maintain. We investigated and analyzed the methods of mist condensation through physical barriers, finding that the polyethylene shadow mesh was the means to achieve this, because it allows the passage of the wind, it is very light, easy to manipulate and above all that it presents the phenomenon of percolation that allows water droplets of various diameters to be accommodated therein. We designed a device that allows to present a mist catchment area through a prismatic structure enabled with meshes and condensed water receivers, portable, easy to use and maintenance and very economical with a performance of 20 liters per day. To achieve our project, factors such as air humidity, dew point, wind speed and direction, height, temperatures and available spaces must be considered.

Originally, the Tesla transformer was developed to transmit energy and messages wirelessly. But it did not prove itself for either of these applications, so today it is only used for research purposes. Over time, the Tesla transformer has evolved and improved. Today it is possible with Tesla transformers to generate powerful and highly precise controlled discharges. During operation, impressive high-voltage discharges occur at the transformer. A tesla transformer is basically a high voltage generator that achieves a voltage boost by using two magnetically coupled LC series resonant circuits of the same resonant frequency. The Dual Resonant Solid State Tesla Coil (DRSSTC) built in this work has a high power IGBT half bridge module to excite the primary resonant circuit at the resonant frequency. The IGBTs are driven in such a way that audible pressure waves, and therefore music, are generated by the electrical discharges at the high voltage electrode. Within the scope of this work were the following two questions: - How is a DRSSTC designed and built? The DRSSTC system realized in this work is about 80 cm high and reaches about one-meter-long discharges. The design, development, and construction of the transformer are documented in detail and extensively in this thesis. - How does one measure an electrical voltage of 200,000 V, which changes sign more than 100,000 times per second? Two approaches have been taken to measure the voltages. Derived from the energy balance of an ideal capacitor and an ideal coil, a secondary voltage of about 200 kV was calculated via secondary current measurement. The second approach uses a voltage measurement via an in-house developed measuring electrode and a calculated divider ratio between the measured voltage and the secondary voltage. A relatively unrealistic secondary voltage of about 750 kV was measured since the divider ratio depends on approximate values. Nevertheless, the measuring electrode can be used for investigations of the voltage curve, or the divider ratio can be calibrated via the secondary current measurement. The development of such a transformer laid the foundation for much further research and scientific analysis.

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.

Microplastics are tiny invisible plastic pieces that are piling up in the marine environment emerging as one of the many environmental issues which our planet is facing today. Researches for the removal of these particles are important because studies that have been made so far haven't come up with an effective solution. This project aimed to detect microplastics and remove them from aqueous environments with an effective and practical method then it was aimed to determine the removal amount of microplastics by optical measurements with the developed system. Firstly, the magnetic carbonanotubes (m-CNT) which is intended to hold onto the surfaces of microplastics was synthesized and added to the mixture of microplastics. Then the magnet within a glass tube was passed through the mixture and the sample was cleared of microplastics. A spectrometer was made to monitor this process and after its calibration, it was used to measure coffees with different concentrations. It has been shown that their concentrations can be determined by calculating the transmission values and Rayleigh scattering. In the end, it has shown that there are no micro or nano-sized plastic particles when removed with M-CNT, within the accountable range of the spectrometer that had been made. Hence the removal of the microplastics: an invisible threat for the environment has been studied by combining nanomaterials with unique surface properties in the removal process and an optical principle such as Rayleigh scattering, a new technique has been developed that can measure quickly, economically,