# 韓國

Although it is well known that, unlike the feces of a fowl, those of an ostrich\r do not produce foul smell, the impact of different enterobacteria on elimination of malodorous\r substances has not been seriously investigated. I sought to test the hypothesis that ostrich\r enterobacteria (OE) are useful to eliminate hydrogen sulfide (H2S) and ammonia (NH3), two\r important components of foul smell of the feces.

Islands far from lands use the underground or surface water as the water for living. The population of the islands is growing fast and the amount of water usage is increasing year after year. However, the amount of water usage is limited, so that people who live in islands have trouble using water. To compensate this problem, underground water is drawn from deeper underground sites. If this matter occurs continuously, sea-level may rise and then we cannot use underground water. Seawater desalination is a way to solve the water shortage, but it requires a lot of energy. It is difficult for island far away from lands to supply a lot of energy. It is considered the eco-friendly way to minimize the use of energy on the island. In order to solve the problem of water shortage on the island, it is considered fog that on the island occur frequently. It is an attempt to create water from fog, but it is a lack of research of efficiency of fog-catching nets to create water from fog. In this research, I have studied the efficiency of the fog-catching nets, a way to increase the efficiency, the amount of water that is created on the island, usage of discarded fishing net for fog-catching nets. Through this research, I found a kind of fog which can be changed into water and the difference in efficiency due to the difference in the size of the mesh size of the fog-catching nets, wind direction, wind speed, water absorption capacity of thread of fog-catching nets, installation direction of fog-catching nets, a way of installation of fog-catching nets. Also I found fog-catching nets of discarded fishing nets on the island and the possibility of usage for everyday life that the amount of water are created for a day or a month during dry season on the island.

Most football managers are not aware of the need for analysis of soccer data, which is one of the dynamic sports. In this study, we developed a statistical model with performance indicators and score indicators of individual soccer player based on various event data including dynamic features such as goal, assist, pass, etc. In this study, the correlation between the dependent variables and the explanatory variables, and each explanatory variable was confirmed through the correlation analysis to solve the problem of multiple communicability from the regression model and to analyze the statistically significant preliminary model. In addition, we analyzed the correlation between individual rating of the players and the data recorded in the soccer games, and found that there has been a problem with the rating of the soccer players evaluated by the reporters and the soccer statistics site. To solve this problem, we developed a model that best fit the performance indicators of individual soccer player using the linear regression model and the beta regression model. The performance index model of the athletes was developed by comparing the R-squared value and the mean absolute percentage error of two models, the linear regression model and the beta regression model, and found out the beta regression model is better model to use. By using the estimated regression coefficients of the regression model we made new PI model. Score Index, which is the attractive point of soccer, was developed by comparing Poisson regression model and negative binomial regression model based on AIC value, and the one using negative binomial regression model was found to be better. Through the model developed by this study, it is possible to collect the event data recorded by individual athletes for each soccer game, and obtain the PI & SI index which are the athlete performance index models. This allows us to evaluate each team's players objectively, analyze the team's deficiencies, and provide tools to find players, who can fill in the missing positions of the teams. This study can also be utilized to grasp the performance of athlete in real time by simulating the resultative model.

The growth of a city and the population movement has many correlations. However, the complex interaction causes difficulties in developing a mathematical model needed for analyzing the growth factor of a city and the movement factor of population. The model involving traditional equations cannot explain many phenomenon. The newly introduced data-science suggests possibilities to overcome these difficulties. Particularly, the abundant amount of accumulated data proposes a new solution for the problem we have. Throughout these steps, data-utilizing methodology, such as machine learning for artificial intelligence, are researched and developed with attention. In this research, data about accumulated for previous population movement and city growth are collected, and a mathematical science model based on data is developed to explain population movement and city growth by utilizing data analyzing methods such as machine learning. Especially, artificial neural network and stratified advance learning(deep learning) proves possibilities in solving many problems. This research aims to construct an artificial neural network appropriate for population movement and consequently use it in developing population movement model. Using this model, growth of many existing cities can be explained and furthermore, examining the population movement factor of a city and social factor necessary for city growth become possible. This model is expected to become the tool for resolving overpopulation and predicting and deciding factors needed for a new future city. In spite of decreasing population, it is still important to develop a model for population movement that well explains city growth and environment change.

This study completes an air vibration equation expressed wind speed slope and wind speed. First, preliminary experiments identified air vibrations when wind speed differences occurred over distance. Several air fans were connected in series and the rotational speed of the air fan was adjusted to vary the wind speed with distance. At this time, only certain pendulum oscillates during a particular wind speed slope. It was expected that the pendulum would shake because the frequency of the air due to the slope of the wind speed was equal to the natural frequency of the pendulum. In addition, relatively short pendulum swings in large wind speed slope, long pendulum swings in short wind speed slope. After calculating the natural frequency of the seasonal growth of fruit using the physical factors model, we experiment how resonant frequency was related with cone length, angular width, wind speed, velocity and secondary derivative. the actual experiment analyzed the natural frequency of the fruit and resonance from the air vibration as the linear function of the wind speed, velocity, and secondary derivative. The experiment determined that the pendulum of a specified number of frequencies resonated with a particular wind speed pattern. It is judged that the vibration of air is related to first derivative of wind speed depending on speed and distance. However, it is very difficult to express the flow of nonlinear fluids as a function of simple function, particularly the effects of air vibrations caused by wind speed second derivative, which appeared to be associated with forces. This is a task that needs to be solved through further research.