曲率的奧秘
我們研究的主題是曲率,且以高中所學的函數為主。雖然大學已有曲率公式,但我們將其表示成高中生較易了解的型式,並且以f(x) 的方式呈現。我們在函數曲線上取不共線三點,構成一個三角形,並求出此三角形的外接圓半徑。再將所取三點逼近,所求之半徑即為特定點的密切圓,也就是曲率半徑。而此曲率半徑的倒數,就是所求的曲率,同時我們將公式帶入高中各常見函數,以導出函數上各點曲率。;Our study is about curvature, especially about the fuctions we learn in senior high school. In university, there is a certain formula for curvature, but we hope to change it into a form that can be easily accepted by senior high school students, and express the formula with f(x), the symbol of functions. We pick three incollinear points from the curve of a function, making the three points into a triangle, and figure out the circumradius of this triangle. Then, we approximate the three points to one of them, and the circumradius will also be the radius of the osculating circle of the point. We define the radius as radius of curvature. The reciprocal of the radius of curvature will be the curvature. Then, we use the formula to figure out the curvature of the functions we learn in senior high school.
環狀網路的拓樸性質研究
In any , we prove that there exist cycles which have any length between 3 and 3n and paths which have any length between their smallest distance and longest Hamiltonian paths in any two different nodes; for any two nodes, there exist varied Hamiltonian cycles, making the two nodes locate on any possible counterpart position(only limited by the distance between the two nodes). In , there are 2n internally-disjoint spanning cycles, and 2n-1 internally-disjoint spanning paths. Besides, we also prove has no more than 2n disjoint spanning paths, and calculate its wide diameter.
本報告證明在環狀網路 中,存在有長度3到 3n 的所有迴圈;任何相異兩點都有各種不同的長度的路徑:從最短的距離到最長的漢米頓路徑;取定任意兩點,存在有各種不同的漢米爾頓迴圈,使得兩點位於所有可能的相對位置上(僅被兩點之間的距離限制)。在 中,也具有2n 個彼此不相交、經過所有點的迴圈,以及2n-1 個彼此不相交、經過所有點的路徑。除此之外,也證明了,在兩相異點間,具有個數不超過2n 且互斥的路徑,且這些路徑經過所有點。我們也估算了它的寬直徑。
Development of Models for Performance Index (PI) and Score Index(SI) of Individual players based on 5 European Soccer Leagues
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.
替機器人安排作業程序
編號1~mn 的mn 個物件已隨機置入m× n 階的矩陣中,另外有一行m 個空格的暫存區供物件暫存用。我們探討將這mn 個物件移至目標區並按照1,2,…, mn 的次序排列,所需的移動步數;每一步的移動中,只能移動每一行最頂層的物件到其他行(含暫存區)的最頂層或目標區。在這篇報告中,我們給出了一個適用於n ? m ?1時的移動方法,此方法在一般的情形下,所需的移動次數未必是最少;但是在最不利於移動的情形下,我們證明此方法所需的移動步數為最少。There are mn objects, numbered from 1 to mn, put on an m× n matrix randomly, and there is another column with m blank spaces for temporary storage purpose during moving. In each step of moving, we can only move the top object from one column to the top of another column or to the target pile. The total steps needed to move these mn objects to the target pile in increasing order from the bottom to the top is studied in this article. A general method for solving this problem when n ? m ?1 is given, and we prove that it provides an optimal solution in the worst cases. However, it may not always provide the minimal steps in all cases.