Nowadays, cooling open spaces in hot seasons without using fossil fuels has gained a lot of attention. In this regard, natural air conditioning is a great method for conserving energy that can be used for reducing energy consumption and environmental pollution. Structures like windcatchers are used for natural air conditioning as a building component in warm climates since they are placed in the path of the wind and direct the wind to play a significant role in reducing the temperature. The main objective of the current study is to explore air conditioning in open spaces based on sustainable architecture. The current study reviews the relevant literature from credible journals, and it includes studies with relevant subjects published from 1851 to 2021. The findings show that implementing this design project can result in significant advances in terms of reducing humidity, removing dust and insects from the air, conserving energy, reducing the global temperature, using renewable energies, and producing conditioned air for the area

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.

本研究旨在研究一款自創棋類遊戲「梅花棋」，找出效率最佳的演算法及分析AI的適用性。遊戲規則如下：雙方玩家輪流在19階的棋盤上下棋，先手執黑子，後手執白子，任一方形成梅花即獲勝。隨著棋子的增加，肉眼判斷勝負愈發困難，因此希望借助電腦的力量完成它。我們透過C++編寫程式，持續改良優化演算法，提升電腦的精確度與流暢度。過程中依序提出了平均演算法、畢氏定理演算法、向量演算法、以及網狀編碼演算法。目前最新版本中，我們使用含有螺旋編碼表的網狀編碼演算法，這可使電腦快速正確地判斷勝負。得到最佳的演算法後，我們嘗試運用撰寫Minimax演算法編寫AI，並且不斷增加演算法的深度，從而提升電腦的實力。透過Victory notion的概念分析兩者間的相似度，判斷其對於梅花棋的適用性。透過不斷與Minimax演算法測試遊戲，將梅花棋規則中，先後手的優勢差距逐漸縮小。目前本研究已可順利進行單純的雙人對戰與複雜的人機對戰模式。

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.

Inhibitory effects of the secondary metabolite of actinomycete were examined on cell cycle of the yeasts of S. pombe and S. cerevisiae. The secondary metabolite was obtained from cultivation of the actinomycete isolated from the soil of Owakudani in Hakone, Japan. The fifth fraction of the secondary metabolite by ODS column separation (HK-T5), which was soluble to pure methanol, was used in the present experiments. The HK-T5 brought about the delay of forming colonies of S. pombe for about 11 days compared to that cultivated without the HK-T5. The delay of the colony formation was longer for the S. pombe cultivated with more amount of the HK-T5. The cultivation with HK-T5 also brought about the extension of the lifespan of the S. pombe for more than 10 weeks in a liquidus medium. The cell life recovered the ordinary manner by removal of the HK-T5, meaning that the activities of the HK-T5 is reversible. These facts confirm the suppression of cell cycle, and the delay of cell growth by the HK-T5. These phenomena were similarly observed for S. cerevisiae. Comparison of the action of HK-T5 with hydroxyurea, which is an anticancer drug inhibiting the cell cycle at S phase, clarified that the inhibitory action of HK-T5 worked at the phase earlier than S phase. The combined effects of HK-T5 on the cell cycle were evaluated with triamcinolone acetonide (TA), or aspirin, the former of which is a drug synchronizing cancer cells in S phase, and the latter keeping human cells in G1/G0 phases. The combined use of HK-T5 with TA synchronized the cells at the phase slightly proceeding from G1 to S phase without toxicity. On the other hand, the combined use with aspirin made the inhibitory effect of HK-T5 inactive. Hence, the HK-T5 is attractive as a drug for the extension of cell lifespan, and anticancer therapy.

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.

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

Technology is erratic. We never know what could be the next big thing. Nowadays, IoT (the internet of things) has taken over the market. Every technology created nowadays is somehow related to IoT. You should manage to connect the IoT technology with a robust area of hospitality. Catering customers' needs during peak hours at any restaurant or cafe could get overwhelmed with hectic tasks such as taking orders, fetching water, and ordering meals. We created a raw model to accommodate the limitations of the human mind. The technology-based IoT (Internet of things) can come in handy during hectic sessions. A Robot waiter is built from scratch using materials like Arduino (2), Gear DC motor (2), L298N motor driver (1), Ultrasonic sensor (2), IR sensor (2), Servo motor (4) HC-05 Bluetooth module. Desired orders are sent on a wireless network through the menu bar to the kitchen. Then, the robots transfer the food from the kitchen to the customers. The floor will be all white, while there will be a strip of black line to connect every sitting and the kitchen. For instance, if table number three is to be served, we click the number three in the app, which renders an obstacle in table 3. The motor barricades the robot, and the ultrasonic sensors sense it, and it stops. If anyone picks the plate, the ultrasonic sensor senses it, the blockage is removed, and the robot paces in the designated path. People visited the place more often to experience such stimuli. Using the robots attracted more customers and made the work very quick.

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.

Inhibitory effects of the secondary metabolite of actinomycete were examined on cell cycle of the yeasts of S. pombe and S. cerevisiae. The secondary metabolite was obtained from cultivation of the actinomycete isolated from the soil of Owakudani in Hakone, Japan. The fifth fraction of the secondary metabolite by ODS column separation (HK-T5), which was soluble to pure methanol, was used in the present experiments. The HK-T5 brought about the delay of forming colonies of S. pombe for about 11 days compared to that cultivated without the HK-T5. The delay of the colony formation was longer for the S. pombe cultivated with more amount of the HK-T5. The cultivation with HK-T5 also brought about the extension of the lifespan of the S. pombe for more than 10 weeks in a liquidus medium. The cell life recovered the ordinary manner by removal of the HK-T5, meaning that the activities of the HK-T5 is reversible. These facts confirm the suppression of cell cycle, and the delay of cell growth by the HK-T5. These phenomena were similarly observed for S. cerevisiae. Comparison of the action of HK-T5 with hydroxyurea, which is an anticancer drug inhibiting the cell cycle at S phase, clarified that the inhibitory action of HK-T5 worked at the phase earlier than S phase. The combined effects of HK-T5 on the cell cycle were evaluated with triamcinolone acetonide (TA), or aspirin, the former of which is a drug synchronizing cancer cells in S phase, and the latter keeping human cells in G1/G0 phases. The combined use of HK-T5 with TA synchronized the cells at the phase slightly proceeding from G1 to S phase without toxicity. On the other hand, the combined use with aspirin made the inhibitory effect of HK-T5 inactive. Hence, the HK-T5 is attractive as a drug for the extension of cell lifespan, and anticancer therapy.

Due to having Asperger's syndrome, I want to make a pressure vest suitable for hot and humid climates like Asia to help reduce the daily anxiety of children and adults with autism, ADHD, sensory disorders, etc. To solve this problem, I first tried using a porous material. But after seeing a pressure vest in person, I found it to be useless. Therefore, I came up with the idea of creating an active airflow cooling system between the body and the pressure vest. To experiment, I wanted to make pressure vests. However, I found that a high-frequency TPU welding machine is required. Thus, I made models of pressure vests using airbags, water-resistant nylon, and quick-drying fabric. I also made models, which came from sandwich fabric. Through this research, I discovered that the sandwich fabric design has the best passive heat dissipation, and the combination of the sandwich fabric and the active airflow cooling system has the best active heat dissipation.

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.