• Journal of the Korean Statistical Society
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• 제19권2호
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• pp.105-112
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• 1990

Let (X, Y) be a pair random variables and let f denote the regression function of the response Y on the measurement variable X. Let K(f) denote a derivative of f. The least squares method is used to obtain a tensor spline estimator $\hat{f}$ of f based on a random sample of size n from the distribution of (X, Y). Under some mild conditions, it is shown that $K(\hat{f})$ achieves the optimal rate of convergence for the estimation of K(f) in $L_2$ and $L_{\infty}$ norms.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1997년도 추계학술대회논문집; 한국과학기술회관; 6 Nov. 1997
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• pp.345-351
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• 1997

The motion of an aircraft landing gear over rough runway at variable speed is nonstationary. hi this paper, a method for the computation of nonstationary response variance is presented which uses a state space form for the combination of landing gear and runway excitation. The dynamic characteristics of the landing gear under nonstationazy random excitations has also been analyzed using the proposed method. The formulation is for linear systems of arbitrary order and allows any deterministic velocity history.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권1호
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• pp.81-98
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• 2013

Since Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA) were introduced, many revised or extended topic models have appeared. Due to the intractable likelihood of these models, training any topic model requires to use some approximation algorithm such as variational approximation, Laplace approximation, or Markov chain Monte Carlo (MCMC). Although these approximation algorithms perform well, training a topic model is still computationally expensive given the large amount of data it requires. In this paper, we propose a new method, called non-simultaneous sampling deactivation, for efficient approximation of parameters in a topic model. While each random variable is normally sampled or obtained by a single predefined burn-in period in the traditional approximation algorithms, our new method is based on the observation that the random variable nodes in one topic model have all different periods of convergence. During the iterative approximation process, the proposed method allows each random variable node to be terminated or deactivated when it is converged. Therefore, compared to the traditional approximation ways in which usually every node is deactivated concurrently, the proposed method achieves the inference efficiency in terms of time and memory. We do not propose a new approximation algorithm, but a new process applicable to the existing approximation algorithms. Through experiments, we show the time and memory efficiency of the method, and discuss about the tradeoff between the efficiency of the approximation process and the parameter consistency.

• 한국산학기술학회논문지
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• 제19권2호
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• pp.676-682
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• 2018

WSN을 포함하는 IoT 세상이 발전할수록, IoT를 적용하는 주위환경에 따라 정보를 센싱하는 센서 시스템의 수가 매우 가변적이다. 이러한 복잡한 환경에서 각각의 센서 시스템들에 대한 보안을 수행하기 위하여 보안모듈들도 가변적으로 증감을 수행해야 한다. 이러한 문제점은 시스템 효율성과 해킹/크래킹을 고려하였을 경우, 하드웨어/소프트웨어적인 구현을 어렵게 한다. 그러므로 본 논문은 이러한 문제점을 해결하기 위하여 센싱 노드들의 수와 상관없이 일정한 주기를 가지는 의사난수를 발생시키며 이상현상을 탐지할 수 있는 기능을 가진 고정 길이 탭을 가진 의사 난수 발생기(FLT: Pseudo-random Number Generator with Fixed Length Tap unrelated to the variable sensing nodes) 구조를 제안하였다. 제안된 FLT-LFSR 구조는 IoT 환경에서 하드웨어/소프트웨어 구현에 대하여 보안레벨 및 전체 데이터 포맷팅을 일정하게 유지시킬 수 있도록 하였다. 그러므로 제안된 FLT-LFSR 구조는 센서 시스템 구현의 용이성 및 센싱 노드들의 수와 상관없이 네트워크의 확장성을 강조할 수 있도록 하였다.

• 대한의용생체공학회:의공학회지
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• 제33권3호
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• pp.148-154
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• 2012

Hemorrhagic shock is a primary cause of deaths resulting from injury in the world. Although many studies have tried to diagnose accurately hemorrhagic shock in the early stage, such attempts were not successful due to compensatory mechanisms of humans. The objective of this study was to construct a survival prediction model of rats in acute hemorrhagic shock using a random forest (RF) model. Heart rate (HR), mean arterial pressure (MAP), respiration rate (RR), lactate concentration (LC), and peripheral perfusion (PP) measured in rats were used as input variables for the RF model and its performance was compared with that of a logistic regression (LR) model. Before constructing the models, we performed 5-fold cross validation for RF variable selection, and forward stepwise variable selection for the LR model to examine which variables were important for the models. For the LR model, sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (ROC-AUC) were 0.83, 0.95, 0.88, and 0.96, respectively. For the RF models, sensitivity, specificity, accuracy, and AUC were 0.97, 0.95, 0.96, and 0.99, respectively. In conclusion, the RF model was superior to the LR model for survival prediction in the rat model.

• 한국콘텐츠학회논문지
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• 제6권5호
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• pp.29-34
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• 2006

본 연구에서는, Banach 공간의 값을 갖는 확률요소들의 합 $S_n=\sum_{i=1}^nV-i$ 수렴하는 경우에, Tail 합 $T_n=S-S_{n-1}=\sum_{i=n}^{\infty}V-i$에 대한 대수의 법칙을 고찰하여 $S_n$이 하나의 확률변수 S로 수렴하는 속도를 연구한다. 좀 더 구체적으로 말하자면, 확률변수들의 Tail 합과 확률요소들의 Tail 합에 대한 극한 성질의 유사성을 연구하여, Banach 공간에서 독립인 확률요소들의 Tail 합에 대한 약 대수의 법칙과 하나의 수렴법칙이 동등함을 기술하는 기존의 정리를 다른 대체적인 방법으로 증명한다.

• Structural Engineering and Mechanics
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• 제91권1호
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• pp.25-38
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• 2024

After the mainshock, whether the train can be allowed to pass the bridges plays an important role in ensuring the transport of supplies and rescue works for example, in the "12 May" earthquake in China, after evaluation, the bridge was still used for transportation in rescue at a very slow speed, engineers usually evaluate whether the train can pass the bridge safely based on the experience, lacks sufficient calculation basis and does not fully consider the risk caused by aftershocks. To address this issue, this paper comprehensively considers the randomness of track irregularity, the randomness of aftershock intensity and other multiple random sources in train-bridge interaction system (TBIS). The sensitivity of train to various random parameters after earthquake is analyzed from the perspective of probability, the most sensitive random variable in this paper is PGA of aftershocks, both for bridge and trailer car, With the increase of epicentral distance, the sensitivity of PGA will decrease, and correspondingly, for trailer car, the sensitivity of other random variables will increase, research in this paper provides a basis for the subsequent random analysis of post-earthquake driving safety.

• 수산경영론집
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• 제47권2호
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• pp.15-32
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• 2016

The Association of Southeast Asian Nations(ASEAN) has been the most essential organization in Asia. In spite of the world economic crisis, Southeast Asian countries have shown fast economic growth since 2000, and they have been actively expanding investments and trades especially with major countries. Research on competitiveness in ASEAN market has spawned an increasingly large literature, but empirical research on the determinants of Korea's export to ASEAN is limited. The purpose of this study is to draw out the determinant of Korean fisheries export to ASEAN by carrying out a panel analysis. For achieving such a purpose, pooled OLS, Hausman Test, Fixed Effect, Random Effect are performed. The last 20 years' data over the period of 1995 to 2014 concentrated on the ASEAN 6 countries such as Indonesia, Malaysia, Philippine, Singapore, Thailand, Vietnam is used in this study. Amount of aquatic products export to ASEAN is used as the dependent variable; real exchange rate, real GDP, relative price level and GDP per capita are used as the explanatory variables and FTA as dummy variable. Empirical results show that fixed-effect analysis is the best model among all the models. As the fixed effect model shows, real exchange rate, real GDP, GDP per capita and dummy variable(FTA) play positive and statistically significant roles in fisheries export to ASEAN, while price variable plays a negative and statistically significant role to the dependent variable.

• 국제지역연구
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• 제15권2호
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• pp.151-173
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• 2011

본 연구의 목적은 1979년부터 2008년까지 30년 기간 동안 중국에 있어서 경제성장에 영향을 미치는 중요 요소와 요소별 기여수준을 파악하기 위한 것이다. 이를 위하여 고정효과모형과 확률효과모형을 활용하였으며, 적합모델을 선택하기 위하여 Hausman 검정을 활용하였다. 본 연구의 결과 지역금융변수(rsav)가 6개 모형에서 그리고 사회간접자본변수(rsoc)가 2개 모형에서 경제성장에 대해 부(-)의 관계를 보였으나 나머지 3개 변수는 전 모델에서 경제성장에 대해 정(+)의 관계를 보이고 있는 것으로 나타나고 있다. 그리고 노동력 변수의 영향은 서부지역과 동북지역의 경우를 제외하고는 기여율이 상당히 낮은 것으로 파악되었다. 본 연구는 중국의 1인당경제성장률에 대한 각 성장요인의 의미를 찾았는데, 전국모형의 경우 자본의 기여율이 35.9%로 나타난 반면 노동기여율은 4.7% 수준에 불과한 것으로 분석되었다. 그리고 모든 모형에서 자본(rcap)이 중국경제 성장에서 가장 중요한 요인으로 입증되었다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 추계학술대회
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• pp.239-247
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• 2003

Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, etc. CHAID(Chi-square Automatic Interaction Detector), is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. In this paper we propose and CHAID algorithm by cube-based sampling and explore CHAID algorithm in view of accuracy and speed by the number of variables.