Earticle

본 연구는 범죄 및 피해자 특성과 범죄피해 내용의 관련성을 확인하기 위하여 2010년부터 2018년까지 격년으로 수집된 전국범죄피해조사 자료에 랜덤포레스트 알고리즘을 적용하였다. 전체 자료 중 범죄피해경험이 있는 사례 및 관심 변인을 선별하여 분석자료를 구성하였으며, 총 3080건 자료의 성별, 연령(생애주기단계), 범죄유형, 가해자 면식여부, 반복피해 여부, 심리적 피해내용(우울함, 고립감, 극심한 두려움, 신체증상, 대인관계 문제, 사람을 피해 이사, 자살 충동, 자살 시도) 및 범죄피해 후 감정변화(자기보호 자신감, 자존감, 타인에 대한 신뢰감, 사법기관에 대한 신뢰감 및 사법제도와 법에 대한 존중감의 변화)를 나타내는 변인들이 분석자료에 포함되었다. 전통적 통계기법을 적용하기 어려운 자료의 특성을 고려하여, 본 연구는 범죄피해 내용(심리적 피해내용과 감정변화)을 이용하여 범죄 및 피해자 특성을 예측하기 위한 랜덤포레스트 알고리즘을 다섯 번 실행하고, VSURF 함수를 이용하여 범죄 및 피해자 특성을 잘 예측하는 범죄피해 내용 변인들을 선택하였다. 분석 결과, 범죄유형과 우울함, 극심한 두려움 및 신체증상의 관련성, 가해자 면식여부와 신체증상 및 대인관계 문제의 관련성, 반복피해 여부와 사법제도와 법에 대한 존중감 변화의 관련성이 확인되었다. 성별과 생애주기단계(청소년/성인/노인)는 각각 극심한 두려움과 자기보호 자신감 변화와 관련이 있는 것으로 확인되었으나 의미를 부여하기 위해서는 추가적 경험자료가 필요할 것으로 판단되었다. 본 연구의 결과는 범죄피해평가제도의 실효성을 높이기 위해 전문가 교육과정에 범죄 및 피해자 특성과 범죄피해 내용에 관한 지식과 사례교육의 제공 및 면담전략과 법률지식에 관한 교육 강화가 필요함을 시사한다.

The current study applied the random forest algorithm to Korean crime victim survey data collected biennially between 2010 and 2018 to explore the relationship between crime/victim characteristics and the victim’s criminal damages. A total of 3,080 cases including gender, age (life cycle stage), type of crime, perpetrator acquisition, repeated victimization, psychological damage (depression, isolation, extreme fear, somatic symptoms, interpersonal problems, moving out to avoid people, suicidal impulses, suicide attempts), and emotional changes after victimization (changes in self-protection confidence, self-esteem, confidence in others, confidence in legal institutions, and respect for Korean legal system/law) were analyzed. Considering the features of data that are difficult to apply traditional statistical techniques, this study implemented random forest algorithms to predict crime and victim characteristics using the victim’s criminal damages (psychological damage and emotional change) and selected good predictors using VSURF function in VSURF package for R. As a result of the analysis, it was confirmed that the relationship between the type of crime and depression, extreme fear, somatic symptoms, and interpersonal problems, between perpetrator acquisition and somatic symptoms and interpersonal problems, and between repeated victimization and changes in respect for Korean legal system/law. Gender and life cycle stage (youth/adult/elderly) were found to be related to extreme fear and changes in self-protection confidence, respectively. However, more empirical evidence should be aggregated to explain the results as meaningful. The results of this study suggest that it is necessary to enhance the experts’ knowledge and educate them on cases about the relationship between crime/victim characteristics and criminal damage. Strengthening their interview strategy and knowledge about law/rules were also needed to increase the effectiveness of the Korean victim assessment system.

As the climate problem becomes more serious, mitigating the heat island effect is becoming an important issue. To solve the problem, it is necessary to identify the areas where the heat island effect is more severe and present appropriate measures to those areas. In this paper, we divided Seoul into 573 grids and divided into four clusters by hierarchical clustering techniques to identify the current status of the city's heat island effect. Of these cluster, we chose the one with the most urban features. We extracted the variable importance with random forest models and developed the heat island index from 1) multiplication of the variable importance and 2) the sign of the correlation coefficient between temperature and 3) the corresponding variable. Furthermore we analyzed areas where the heat island effect is severe with the index. According to the analysis, the heat island effect was particularly severe in five grids, and we suggested ways to mitigate the heat island effect for the areas concerned.

The spectrum of the random space vector pulse width modulation (SVPWM) strategy is extremely complicated due to the random variable. A new algorithm based on the Monte Carlo method is proposed to optimize and customize the frequency spectrum of the random SVPWM strategy. A universal theoretical spectrum computation method is given for the SVPWM strategy firstly. In addition, the key procedure of the proposed algorithm is presented. Finally, several computation examples are provided to verify the effectiveness and feasibility. The analysis and computation examples show that the proposed algorithm has several advantages, and the results verify its convenience and feasibility.

Aiming at complicated characteristic analysis and implementation of the randomization space vector pulse width modulation (SVPWM) scheme, a new random zero-vector SVPWM scheme with a fixed randomization range is proposed. The fixed range is a linear function of the modulation index. Firstly, the principle of the new scheme is given. In addition, the implicit modulating voltages, the derivation procedure of the micro and macro harmonic distortion factor (HDF) are presented in detail, and the Monte Carlo method is proposed to efficiently analyze the HDF. Finally, the harmonic spectrum of the new scheme is analyzed compared with the commonly used symmetrical 7-segment SVPWM scheme through an example, and the result verifies its excellent performance on suppressing the cluster harmonic magnitude around the integer multiple switching frequency.

We give a series of discrete random variables which converges to a random variable whose distribution function is the Riesz-N$\acute{a}$gy-Tak$\acute{a}$cs (RNT) distribution. We show this using the correspondence theorem that if the moments coincide then their corresponding distribution functions also coincide.

The theory of random variable structures was first studied by Ben Yaacov in [2]. Ben Yaacov's axiomatization of the theory of random variable structures used an early result on the completeness theorem for Lukasiewicz's [0, 1]-valued propositional logic. In this paper, we give an elementary approach to axiomatizing the theory of random variable structures. Only well-known results from probability theory are required here.

Peak power reduction techniques in orthogonal frequency division multiplexing (OFDM) has been an important subject for many researchers for over 20 years. In this letter, we propose a side-information-free technique that is based on the concept of random variable (RV) transformation. The suggested method transforms RVs into other RVs, aiming to reshape the constellation that will consequently produce OFDM symbols with a reduced peak-to-average power ratio. The proposed method has no limitation on the mapping type or the mapping order and has no significant effect on the bit error rate performance compared to other methods presented in the literature. Additionally, the computational complexity does not increase.

본 연구에서는, 서로 독립인 확률변수들의 합 $S_n$이 수렴하는 경우에, 확률변수들의 Tail 합 $T_n=S-S_{n-1}=\sum_{i=n}^{\infty}X_i$의 극한 성질을 연구함으로써, $S_n$이 하나의 확률변수 S로 수렴하는 속도를 연구한다. 좀 더 구체적으로 말하자면, 유사-단조감소(Quasi-monotone decreasing)하는 상수(Norming constants)의 수열에 대하여, 확률변수들의 Tail 합에 대한 약대수법칙과 하나의 수렴법칙이 동등함을 정리로 기술하고 증명하여, 기존의 연구 결과를 더 넓은 부류의 상수들의 경우에 적용할 수 있도록 확장한다.

For the almost co티am convergent series $S_n$ of independent random variables, by investigating the limiting behavior of the tail series, $T_n=S-S_{n-1}=\sum_{i=n}^{\infty}X_i$, the rate of convergence of the series $S_n$ to a random variable S is studied in this paper. More specifically, the equivalence between the tail series weak law of large numbers and a limit law is established for a quasi-monotone decreasing sequence, thereby extending a result of Previous work to the wider class of the norming constants.

We in this paper study the almost sure convergence for asymptotically almost negatively associated(AANA) random variable sequences and obtain some new results which extend and improve the result of Jamison et al. (1965) and Marcinkiewicz-Zygumnd strong law types in the form given by Baum and Katz (1965), three-series theorem.

Let $X,X_1,X_2,\;{\cdots}$ be identically distributed and negatively associated random variables with mean zeros and positive, finite variances. We prove that, if $E{\mid}X_1{\mid}^r$ < ${\infty}$, for 1 < p < 2 and r > $1+{\frac{p}{2}}$, and $lim_{n{\rightarrow}{\infty}}n^{-1}ES^2_n={\sigma}^2$ < ${\infty}$, then $lim_{{\epsilon}{\downarrow}0}{\epsilon}^{{2(r-p}/(2-p)-1}{\sum}^{\infty}_{n=1}n^{{\frac{r}{p}}-2-{\frac{1}{p}}}E\{{{\mid}S_n{\mid}}-{\epsilon}n^{\frac{1}{p}}\}+={\frac{p(2-p)}{(r-p)(2r-p-2)}}E{\mid}Z{\mid}^{\frac{2(r-p)}{2-p}}$, where $S_n\;=\;X_1\;+\;X_2\;+\;{\cdots}\;+\;X_n$ and Z has a normal distribution with mean 0 and variance ${\sigma}^2$.

We present new recurrence formulas for the raw and central moments of a compound binomial random variable. Our approach involves relating two compound binomial random variables that have parameters with a difference of 1 for the number of trials, but which have the same parameters for the success probability for each trial. As a consequence of our recursions, the raw and central moments of a binomial random variable are obtained in a recursive manner without the use of Stirling numbers.

This paper presents the effects of corrosion environments of failure pressure model for buried pipelines on failure prediction by using a failure probability. The FORM (first order reliability method) is used in order to estimate the failure probability in the buried pipelines with corrosion defects. The effects of varying distribution types of random variables such as normal, lognormal and Weibull distributions on the failure probability of buried pipelines are systematically investigated. It is found that the failure probability for the MB31G model is larger than that for the B31G model. And the failure probability is estimated as the largest for the Weibull distribution and the smallest for the normal distribution. The effect of data scattering in corrosion environments on failure probability is also investigated and it is recognized that the scattering of wall thickness and yield strength of pipeline affects the failure probability significantly. The normalized margin is defined and estimated. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

The concept of entropy, introduced in communication theory by Shannon (1948) as a measure of uncertainty, is of prime interest in information-theoretic statistics. This paper considers the minimum variance unbiased estimation for the maximum entropy of the transformed inverse Gaussian random variable by $Y=X^{-1/2}$. The properties of the derived UMVU estimator is investigated.

This paper is concerned with selecting covariates to be included in building linear random effects models designed to analyze clustered response normal data. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting premising subsets of covariates. The approach reformulates the linear random effects model in a hierarchical normal and point mass mixture model by introducing a set of latent variables that will be used to identify subset choices. The hierarchical model is flexible to easily accommodate sign constraints in the number of regression coefficients. Utilizing Gibbs sampler, the appropriate posterior probability of each subset of covariates is obtained. Thus, In this procedure, the most promising subset of covariates can be identified as that with highest posterior probability. The procedure is illustrated through a simulation study.

Random effects generalised linear models are useful for analysing clustered count data in which responses are usually correlated. We propose a Bayesian approach to parameter estimation and variable selection in random effects generalised linear models for count data. A simple Gibbs sampling algorithm for parameter estimation is presented and a simple and efficient variable selection is done by using the Gibbs outputs. An illustrative example is provided.

In this paper, a new optimization method which is a kind of random searching is presented. The proposed method is called RasVal which is an abbreviation of Random Search Method with Variable Seaxch Length and it can search for a global minimum based on the probability density functions of searching, which can be modified using informations on success or failure of the past searching in order to execute intensified and diversified searching. By applying the proposed method to a nonlinear crane control system which can be controlled by the Universal Learning Network with radial basis function(R.B.P.), it has been proved that RasVal is superior in performance to the commonly used back propagation learning algorithm.

군용 항공기의 개발과정 중 전투 생존성 분석은 반드시 거쳐야 할 필수 과정이다. 군용 항공기의 전투 생존성 분석을 위한 방법은 M&S 기법 적용이 일반적이며 필요시 최종단계에서 Live Fire Test를 거친다. 본 연구에서는 비용대비 효과도를 고려하여 M&S기법을 통해 개념설계단계에서 신속하게 정성적으로 전투 생존성을 분석할 수 있는 연구를 수행하였다. 본 연구를 위하여 필수사건 및 필수요소 분석기법, 몬테카를로 시뮬레이션 등 확률, 통계기법들을 이용한 '확률변수 가중치 환산법' 알고리즘을 고안하여 제시하였다.

Aircraft combat survivability analysis is essential process for the development of combat aircraft. M&S methodology is the typical procedure for the aircraft combat survivability analysis, and the last step is the expensive Live Fire Test if it is necessary. This study introduced cost and time effective survivability analysis methodology based on the random variable weighted score algorithm in conceptual design phase. For this study, essential element and event analysis (E3A) is used to define the random variables and Monte-Carlo simulation is implemented to estimate weighted score and the final value of survivability.

현대사회는 대량 정보들을 수집하고 활용하는 정보화 사회로 현대인들에게 통계적 소양이 요구된다. 이에 따라 학교수학에서 통계적 소양의 중요성이 점차 강조되고 있으며, 현직교사나 예비교사들에 대한 통계적 소양 능력의 함양 및 지도 능력 향상이 요구되고 있다. 한편 확률변수는 통계 학습에서 가장 기초적인 개념으로 통계량을 다룰 때에 확률변수를 정의하는 과정으로부터 시작된다. 이에 본 연구에서는 고등학교 통계 영역의 기본 개념인 확률변수 개념에 대한 예비교사들의 이해 정도를 탐색해 보고자 하였다. 이를 위하여 우선적으로, 본 연구의 핵심 내용인 확률변수 개념의 이해도를 보다 정확하게 파악하기 위하여 학문적 측면에서의 정의, 상황에서 드러나는 확률변수의 의미, 그리고 현행(2007 개정) 고등학교 교과서에서의 정의 측면으로 구분하여 재탐색, 정리하고자 하였다. 이를 기반으로, 예비교사 대상의 확률변수 개념의 이해 정도를 조사하기 위한 설문 문항을 마련하였으며, 이를 통해 예비교사들의 확률변수에 대한 이해 정도를 조사하여 분석하였다. 이를 토대로 확률변수 개념 및 전반적인 통계 개념에 대한 교수-학습에 대한 시사점을 제시하고자 하였다.

This study investigated the degree of understanding pre-service teachers' random variable concept, based on the attention and the importance for developing pre-service teachers' ability on statistical reasoning in statistics education. To accomplish this, the subject of this study was 70 pre-service teachers belonged to three universities respectively. The teachers were given to 7 tasks on random variable and requested to solve them in 40 minutes. The tasks consisted of three contents in large; 1) one was on the definition of random variables, 2) the other was on the understanding of random variables in different/diverse conditions, and 3) another was on problem solving relevant to random variable concept. The findings are as follows. First, while 20% of pre-service teachers understood the definition of random variable correctly, most teachers could not distinguish between random variable and variable or probability. Second, there was a significant difference in understanding random variables in different/diverse conditions. Namely, the degree of understanding on the continuous random variable was superior to that of discrete random variable and also the degree of understanding on the equal distribution was superior to that of unequality distribution. Third, three types of problems relevant to random variable concept dealt with in this study were finding a sample space and an elementary event, and finding a probability value. In result, the teachers responded to the problem on finding a probability value most correctly and on the contrary to this, they had the mot difficulty in solving the problem on finding a sample space.