• Journal of the Korea Society of Computer and Information
• /
• v.22 no.11
• /
• pp.1-7
• /
• 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.

• Journal of the Korean Society for Railway
• /
• v.10 no.1 s.38
• /
• pp.7-15
• /
• 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.

• Journal of KIISE:Software and Applications
• /
• v.36 no.5
• /
• pp.376-385
• /
• 2009

Increasing the importance of Green IT brings low-power consumption requirements for embedded software into relief. This paper focus on the power analysis techniques of embedded software along with the trend. We survey the existing research on the power analysis techniques performed during the last decade, and find out some features or characteristics from the analysis approaches of those techniques. Also we summarize those characteristics into a systematic model, and then apply the model to embedded software development process using spider diagram. Our suggestion gives such benefits as improving the understanding of power analysis techniques, guiding the choice of an appropriate technique to their Power analysis, and forecasting the direction of technology changes in embedded software power analysis.

• Mass Spectrometry Letters
• /
• v.6 no.4
• /
• pp.85-90
• /
• 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.

• Journal of the Korean Statistical Society
• /
• v.5 no.1
• /
• pp.29-34
• /
• 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.

• Economic and Environmental Geology
• /
• v.29 no.2
• /
• pp.207-214
• /
• 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.

• Vacuum Magazine
• /
• v.2 no.4
• /
• pp.27-32
• /
• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2006.05a
• /
• pp.611-612
• /
• 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.

• Journal of Fashion Business
• /
• v.23 no.2
• /
• pp.48-61
• /
• 2019

The objective of this study was to derive a list of creative thinking techniques applied with the requirements of the appropriate technique for the task of fashion design development among the process of fashion product planning. This was done through the analysis of thinking techniques by the type of thinking and idea method. Also, the study presented how each creative thinking technique derived is applied to the task of developing fashion design. The scope of the study was 'Fashion Design Development Task', which corresponds to the design sketch of a fashion item based on the seasonal design concept derived through the fashion design planning stage. Research on the thinking techniques consisted largely of the process of idea thinking, the elements of creative thinking, the patterns and types of thinking. Four studies by Makoto, Michalko, De Bono, and Cox suggesting that the patterns and types of thinking techniques were analyzed for the purpose of this study as empirical studies through FGI of a group of five fashion experts. The analysis results showed that the thinking techniques suitable for the development of fashion design were derived from the technique of fractionation, attributive listing, scamper, morphological analysis, mind mapping, lotus blossom, pattern language, provocative operation, and forced connection. In particular, it can be confirmed that the scamper was treated as an efficient and practical technique in the many studies.

• Journal of Korea Water Resources Association
• /
• v.37 no.12
• /
• pp.993-1007
• /
• 2004

There are many different techniques for the estimation of the Hurst exponent. However, the techniques can produce different characteristics for the persistence of a time series each other. This study uses several techniques such as adjusted range, resealed range(RR) analysis, modified restated range(MRR) analysis, 1/f power spectral density analysis, Maximum Likelihood Estimation(MLE), detrended fluctuations analysis(DFA), and aggregated variance time(AVT)method for the Hurst exponent estimation. The generated time series from chaos and stochastic systems are analyzed for the comparative study of the techniques. Then this study discusses the advantages and disadvantages of the techniques and also the limitations of them.