• 한국컴퓨터정보학회논문지
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• 제22권11호
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• pp.1-7
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• 2017

In this paper, we introduce three monitoring filtering techniques which reduce the overheads of dynamic data race detection. It is well known that detecting data races dynamically in multi-threaded programs is quite hard and troublesome task, because the dynamic detection techniques need to monitor all execution of a multi-threaded program and to analyse every conflicting memory and thread operations in the program. Thus, the main drawback of the dynamic analysis for detecting data races is the heavy additional time and space overheads for running the program. For the practicality, we also empirically compare the efficiency of three monitoring filtering techniques. The results using OpenMP benchmarks show that the filtering techniques are practical for dynamic data race detection, since they reduce the average runtime overhead to under 10% of that of the pure detection.

• 한국철도학회논문집
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• 제10권1호
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• pp.7-15
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• 2007

Since human errors are being recognized as one of the primary issues in railway safety, there is a definite need for human error analysis techniques that can identify the types of errors and their causes and derive effective countermeasures to help reduce their future probability. But, for some reasons, there are not yet systematic procedures or techniques for analyzing human errors in the Korean railway industry. This paper introduces several techniques that have been developed and utilized for analyzing human errors in Korean and overseas nuclear power aviation railway, offshore oil industry, etc., and summarizes the strengths and weaknesses of each technique. Based on the Investigation of the techniques, the paper also discusses the implications for the development of a human error analysis system for the Korean railway industry.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권5호
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• pp.376-385
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• 2009

그린 IT의 중요성이 부각되면서 저전력의 소프트웨어 개발에 대한 요구사항이 증가하고 있다. 본 논문에서는 임베디드 소프트웨어 개발과정에서 사용되는 기존의 전력분석기법들을 살펴보고, 이들 기법이 제공하는 분석 접근방법의 특성을 추출하였다. 이들 특성을 분류하고 체계화하여 전력분석기법에 대한 특성 모델(characteristic model)을 제안하였다. 제안한 특성 모델을 임베디드 소프트웨어 개발단계와 매핑하여 단계별 전력분석의 주안점이 무엇인가를 살펴보고, 이들이 갖는 의미를 스파이더 다이어그램을 이용하여 해석하였다. 본 연구는 임베디드 소프트웨어의 전력분석 기법에 대한 이해를 높이고, 분석방법의 선택에 대한 가이드라인을 제공할 뿐만 아니라 향후 전력분석을 위한 적용 기술의 변화를 예측할 수 있도록 하는 장점을 제공할 것으로 보인다.

• Mass Spectrometry Letters
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• 제6권4호
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• pp.85-90
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• 2015

This article reviews recent analytical techniques using inductively coupled plasma-mass spectrometry (ICP-MS) immunoassay for clinical and bio analysis. We classified the techniques into two categories, direct and indirect analysis, which depend upon a guideline of whether tagging materials are used or not. Direct analysis is well known, and generally used in conjunction with various other techniques, such as laser ablation, chromatographic separations, etc. Recently, indirect analysis using tagging elements has intensively been discussed because of its importance in future applications to bio and clinical analysis, including environmental and food industries. The method has shown advantages of multiplex detection, excellent sensitivity, and short analysis time owing to signal amplification and magnetic separation. Now, it expands the application field from small biomolecules to large cells.

• 자원환경지질
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• 제29권2호
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• pp.207-214
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• 1996

For many years oxygen and hydrogen isotope analysis have been used as one of the most valuable research tools to investigate many geological processes. There are many sample preparation techniques of oxygen and hydrogen isotope analysis for various geological samples. We introduce here several important sample preparation techniques for oxygen and hydrogen isotope analysis and discuss the problems of each method in detail.

• 진공이야기
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• 제2권4호
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• pp.27-32
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• 2015

Plasma diagnosis and multivariate analysis techniques for plasma processes are reviewed. The principles and applications of optical emission spectroscopy (OES) and VI probe are discussed briefly. The research results of principal component analysis (PCA), one of the widely used multivariate analysis techniques for plasma process monitoring is discussed in this article.

• Journal of the Korean Statistical Society
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• 제5권1호
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• pp.29-34
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• 1976

The techniques about the analysis of variance for quantitative variables have been well-developed. But when the variable is categorical, we must switch to a completely different set of varied techniques. R.J. Light and B.H. Margolin presented one kind of techniques for categorical data in their paper, where there are G unordered experimental groups and I unordered response categories.

• 정보화정책
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• 제24권4호
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• pp.68-78
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• 2017

악성코드는 나날이 복잡해지고 다양화되어 단순한 정보유출에서부터 시스템에 대한 심각한 피해를 유발하는 실정에 이르렀다. 이러한 악성코드를 탐지하기 위해 코드분석에 역공학을 이용하는 많은 연구가 진행되었지만, 악성코드 개발자도 분석방법을 우회하는 다양한 기법을 활용함으로써 코드분석을 어렵게 하였다. 특히, 악성코드의 감염여부조차 판단하기 어려운 루트킷 기법들이 진화하고 있고, 악성코드가 이 기법들을 흡수함으로써 그 문제의 심각성은 더욱 커지고 있다. 따라서 본 논문에서는 분석기법들을 우회하는 악성코드에 재빠르게 대응하기 위한 분석 프로세스를 설계하였다. 설계된 프로세스를 통하여 악성코드의 탐지를 더욱 효율적으로 할 수 있을 것으로 사료된다.

• 한국수자원학회논문집
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• 제37권12호
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• pp.993-1007
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• 2004

허스트 지수를 산정하기 위하여 기존에 여러 방법론들이 제안되어 왔다. 그러나, 이들 방법론들은 시계열들의 지속성에 대하여 각기 다른 특성들을 보이고 있음을 기존의 연구에서 알 수 있다 따라서 본 연구에서는 수문학에서 주로 이용하고 있는 보정용량, 조정용량, 수정조정용량 방법 이외에 생리학 분야와 전자 분야 등에서 이용되고 있는 1/f 파워 스펙트럼 밀도 분석, DFA, AVT 방법, 최우도법 등을 이용하여 허스트 지수를 산정하여 보았다. 즉, 단기간과 장기간 기억을 가진 카오스와 추계학적 시계열들에 대하여 각각의 방법들을 적용하여 비교 분석하고자 하였으며, 각 방법론들에 대한 장점 및 단점 그리고 한계에 대하여 논의하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.611-612
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• 2006

Many data mining techniques have been proved useful in revealing important patterns from large data sets. Especially, data mining techniques play an important role in a customer data analysis in a financial industry and an electronic commerce. Also, there are many data mining related research papers in a semiconductor industry and an automotive industry. In addition, data mining techniques are applied to the bioinformatics area. To satisfy customers' various requirements, each industry should develop new processes with more accurate production criteria. Also, they spend more money to guarantee their products' quality. In this manner, we apply data mining techniques to the production-related data such as a test data, a field claim data, and POP (point of production) data in the automotive parts industry. Data collection and transformation techniques should be applied to enhance the analysis results. Also, we classify various types of manufacturing processes and proposed an analysis scheme according to the type of manufacturing process. As a result, we could find inter- or intra-process relationships and critical features to monitor the current status of the each process. Finally, it helps an industry to raise their profit and reduce their failure cost.