• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.227-232
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• 1994

In the performance domain, physical performance is a measure that represents some degree of system, subsystem, component or device success in a continuous sense, as opposed to a classical binomial sense (success or failure). If applicable sensing and monitoring means exist, physical performance can be observed over time, along with explanatory variables or covariables. Performance-based reliability represents the probability that performance will remain satisfactory over a finite period of time or usage cycles in the future when a performance critical limit (which represents an appropriate definition of failure in terms of performance) is set at a fixed level, based on application requirements. In the case of inadequate knowledge of the failure mechanics, this physical based empirical modeling concept along with performance degradation knowledge can serve as an important analysis tool in reliability work in product and process improvement.

• Bulletin of the Korean Mathematical Society
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• v.47 no.1
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• pp.39-51
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• 2010

In this paper we consider the uniform central limit theorem for a martingale-difference array of a function-indexed stochastic process under the uniformly integrable entropy condition. We prove a maximal inequality for martingale-difference arrays of process indexed by a class of measurable functions by a method as Ziegler [19] did for triangular arrays of row wise independent process. The main tools are the Freedman inequality for the martingale-difference and a sub-Gaussian inequality based on the restricted chaining. The results of present paper generalizes those of Ziegler [19] and other results of independent problems. The results also generalizes those of Bae and Choi [3] to martingale-difference array of a function-indexed stochastic process. Finally, an application to classes of functions changing with n is given.

• Environmental Engineering Research
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• v.14 no.2
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• pp.71-78
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• 2009

A review of stormwater quantity and quality in the urban environment is presented. The review is presented in three parts. The first part reviews the mathematical methods for stormwater quantity and has been undertaken by examining a number of stormwater models that are in current use. The important feature of models, their applications, and management has been discussed. Different types of stormwater management models are presented in the literatures. Generally, all the models are simplified as conceptual or empirical depending on whether the model is based on physical laws or not. In both cases if any of the variables in the model are regarded as random variables having a probability distribution, then the model is stochastic model. Otherwise the model is deterministic (based on process descriptions). The analytical techniques are presented in this paper.

• Journal of Technology Innovation
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• v.10 no.2
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• pp.69-90
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• 2002

This paper investigates the determinants of the firm's decision to carry out innovative activities in terms of the resource-based view(RBV) in strategic management. Two types of resources are distinguished: tangible(financial autonomy, firm size, capital intensity) and intangible(human resource, entrepreneurship, and commercial resource). R&D intensity and patent statistics are used as proxies for innovative activity. Specific hypotheses about their effect on the probability of a firm carrying out innovative activities are derived and tested on a sample of 337 listed firms in Korean manufacturing industry for the year 1999, using the logistic regression model. Empirical findings suggest that firm size and human resource are the main determinants of firm's internal innovative activities. The results show that the hypotheses concerning financial autonomy, debt ratio, capital intensity, entrepreneurship, and commercial resource are rejected.

• Journal of Korean Vacuum Science & Technology
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• v.3 no.1
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• pp.1-9
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• 1999

This paper presents a newly enhanced damage model in Monte Carlo (MC) simulation for the accurate prediction of 3-Dimensional (3D) as-implanted impurity and point defect profiles induced by ion implantation in (100) crystal silicon. An empirical electronic energy loss model for B, BF2, As, P and Si self implant over the wide energy range has been proposed for the ULSI device technology and development. Our model shows very good agreement with the SIMS data over the wide energy range. In the damage accumulation, we considered the self-annealing effects by introducing our proposed non-linear recomvination probability function of each point defect for the computational efficiency. For the damage profiles, we compared the published RBS/channeling data with our results of phosphorus implants. Our damage model shows very reasonable agreement with the experiments for phosphorus implants.

• Journal of the Korean Society of Industry Convergence
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• v.8 no.2
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• pp.85-95
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• 2005

The margin level in the futures market platys an important role in balancing the default probability with the investor's opportunity cost. In this paper, we investigate whether the movement of KOSPI200 futures daily prices can be modeled with the extreme value theory. Based on this investigation, we examine the validity of the margin level set by the extreme value theory. Moreover, we propose an expected profit-maximization model for securities companies. In this model, the extreme value theory is used for cost estimation, and a regression analysis is used for revenue calculation. Computational results are presented to compare the extreme value distribution with the empirical distribution of margin violation in KOSPI200 and to examine the suitability of the expected profit-maximization model.

• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.961-964
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• 2010

A semi-empirical fluctuation term is presented to improve a classical equation of state (EOS) for volumetric properties in the critical region. The term is based on the two assumptions: (1) The Helmholtz energy is individually divided into classical and long-range density fluctuation contribution (2) All molecules form cluster near the critical region due to long-range density fluctuation. To formulate such molecular cluster, we extended the Veytsman statistics originally developed for the cluster due to hydrogen bonding. The probability function in the statistics is modified to represent the characteristics of long-range density fluctuation vanishing far from critical region. The proposed fluctuation contribution was incorporated into the Sanchez-Lacombe EOS and the combined model with 6 adjustable parameters has been tested against experimental VLE data. The combined model is found to well represent flatten critical isotherm for methane and top of the coexistence curve for the tested components. The prediction results for caloric data are in good agreement with the experimental data.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.622-624
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• 2002

생체인식 기술은 급속도로 발전하고 있지만 개개의 생체 정보를 이용한 단일 생체인식 기술은 생체 방식에 따라 각각의 문제점이 노출되고 있는 상황이다. 이에 두 가지 이상의 생체 정보를 결합하여 단일 생체인식 기술의 문제점을 극복하고 보다 좋은 인식률을 확보하기 위해 다중 생체인식 시스템(Multi-Modal Bio-metries System)이라는 복합 시스템이 제안 되었다. 이 논문에서는 생체인식 산업의 특성 및 개인 인증 방법으로 사용중인 단일 생체인식 시스템의 문제점을 알아보고 그 해결방안으로 다중 생체인식 시스템의 확률단계(Probability Level)에서 더 좋은 성능을 보여주기 위해 각각의 시스템에 가중치(Weight)를 부여 할 경우, EER(Equal Error Rate)이 단일 생체인식 시스템에 보다 가중치를 부여 했을 때 낮아짐과 동시에 ROC 커브도 (Receiver Operating Characteristic Curve) 좋아짐을 보였다.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.133-139
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• 2017

In this paper, we describe a permutation procedure in which we compute a resampling probability value and empirical quantile limits for Split-Half measure of internal reliability. We use the Split-Half reliability coefficient given by two simple methods, the Spearman-Brown formula and the two-part coefficient alpha. The use of a permutation test for Split-Half reliability coefficient is highlighted as a valuable tool when the sample sizes are small and necessary assumptions cannot be met. The permutation tests for Split-Half reliability coefficient are illustrated with an example analysis of two survey data with a sample size of 15 and 35, respectively, and a hypothetical data with a sample size of 5.

• Nuclear Engineering and Technology
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• v.39 no.6
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• pp.717-724
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• 2007

A measurement-based time-domain noise simulation of radiation detector-preamplifier (front-end) noise in nuclear spectroscopy is described. The time-domain noise simulation was performed by generating "noise random numbers" using Monte Carlo's inverse method. The probability of unpredictable noise was derived from the empirical cumulative distribution function via the sampled noise, which was measured from a preamplifier output. Results of the simulated noise were investigated as functions of time, frequency, and statistical domains. Noise behavior was evaluated using the signal wave-shaping function, and was compared with the actual noise. Similarities between the response characteristics of the simulated and the actual preamplifier output noises were found. The simulated noise and the computed nuclear pulse signal were also combined to generate a simulated preamplifier output signal. Such simulated output signals could be used in nuclear spectroscopy to determine energy resolution degradation from front-end noise effect.