• 대한인간공학회지
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• 제29권4호
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• pp.435-444
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• 2010

To identify and evaluate the risk factors in WMSD work, a number of ergonomic workload evaluation methods have been developed. In the legal examination of WMSD risk factors, simple observational workload evaluation methods are widely used instead of using costly measurement equipments such as EMG and motion analyzer. The simple workload evaluation methods can be categorized into three groups; risk factor checklist methods, posture observation methods, and manual material handling task evaluation methods. In terms of the categories, this survey summarized several representative workload evaluation methods and compared them each other. Then some industrial application cases referring each the workload evaluation methods were surveyed. Due to the characteristics of each method, the selection and application procedure of workload evaluation method should be appropriate for the corresponding work. Therefore, some guidelines for the selection and application procedure of workload evaluation method were suggested.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2004년도 추계학술대회
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• pp.81-85
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• 2004

Companies adopted a program called Six Sigma, in order to make fundamental changes in the way the company operated to fulfill customers' expectations. Six Sigma reduces the occurrence of defects. This approach derives the overall process of selection the right projects based on their potential to improve performance metrics and selection and training the right people to get the business results. However, in the course of Six Sigma process steps, companies are in the face of problems. This study is to solve the problems using TP(Thinking Process) of TOC(Theory of Constraints). TOC is methodology for solving key problem in system which is called Constraints. Nowadays, its application is going to be wide and its concept is being implemented. In this paper, it is showed possibility of application TOC to Six Sigma.

• Journal of the Korean Statistical Society
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• 제19권1호
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• pp.24-44
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• 1990

The purpose of this paper is to extend the idea of Tamhane and Bechhofer (1977, 1979) concerning the normal means problem to some general class of distributions. The key idea in Tamhane and Bechhofer is the derivation of the computable lower bounds on the probability of a correct selection. To derive such lower bounds, they used the specific covariance structure of a multivariate normal distribution. It is shown that such lower bounds can be obtained for a class of stochastically increasing distributions under certain conditions, which is sufficiently general so as to include the normal means problem as a special application. As an application of the general theory to the scale parameters problem, a two-stage elimination type procedure for selecting the population associated with the smallest variance from among several normal populations is proposed. The design constants are tabulated and the relative efficiencies are computed.

• 디지털산업정보학회논문지
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• 제13권1호
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• pp.197-211
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• 2017

In recent years, it is natural that the development and the maintenance of information systems are strongly dependent on outside service providers for economic reasons, especially in public sector. There has been an unexpected growth in the number of selection activities for outsourcing related works. At this time, selection of the contractor generally considers the proposals received based on the RFP(requested for proposal) and determines the ranking by experts committee. However, it is difficult even for expert giving a specific numeric score in weighting criteria or rating alternatives. In this context, an extended fuzzy TOPSIS method is applied for selection problem of IT proposals. A numerical illustration is also provided to demonstrate the applicability of the approach. This approach is very practical to help decision makers in assessing proposals during the selection phase under uncertainties.

• Journal of information and communication convergence engineering
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• 제12권1호
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• pp.8-13
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• 2014

We consider the sensor selection problem in large sensor networks where the goal is to find the best set of sensors that maximizes application objectives. Since sensor selection typically involves a large number of sensors, a low complexity should be maintained for practical applications. We propose a geometry-based sensor selection algorithm that utilizes only the information of sensor locations. In particular, by observing that sensors clustered together tend to have redundant information, we theorize that the redundancy is inversely proportional to the distance between sensors and seek to minimize this redundancy by searching for a set of sensors with the maximum average distance. To further reduce the computational complexity, we perform an iterative sequential search without losing optimality. We apply the proposed algorithm to an acoustic sensor network for source localization, and demonstrate using simulations that the proposed algorithm yields significant improvements in the localization performance with respect to the randomly generated sets of sensors.

• 한국컴퓨터정보학회논문지
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• 제23권9호
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• pp.7-13
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• 2018

Recent advancement in data gathering technique improves the capability of information collecting, thus allowing the learning process between gathered data patterns and application sub-tasks. A pattern can be associated with multiple labels, demanding multi-label learning capability, resulting in significant attention to multi-label feature selection since it can improve multi-label learning accuracy. However, existing evolutionary multi-label feature selection methods suffer from ineffective search process. In this study, we propose a evolutionary search process for the task of multi-label feature selection problem. The proposed method creates large set of offspring or new feature subsets and then retains the most promising feature subset. Experimental results demonstrate that the proposed method can identify feature subsets giving good multi-label classification accuracy much faster than conventional methods.

• 한국정보시스템학회지:정보시스템연구
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• 제28권2호
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• pp.25-52
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• 2019

Purpose Despite the recent increase in the use of selection tools using artificial intelligence (AI), far less is known about the effectiveness of them in recruitment and selection research. Design/methodology/approach This paper tests the impact of AI-based initial screening and interview on intentions to apply. We also examine the moderating role of individual difference (i.e., reliability on technology) in the relationship. Findings Using policy-capturing with undergraduate students at a large university in South Korea, this study showed that AI-based interview has a negative effect on intentions to apply, where AI-based initial screening has no effect. These results suggest that applicants may have a negative feeling of AI-based interview, but they may not AI-based initial screening. In other words, AI-based interview can reduce application rates, but AI-based screening not. Results also indicated that the relationship between AI-based initial screening and intentions to apply is moderated by the level of applicant's reliability on technology. Specifically, respondents with high levels of reliability are more likely than those with low levels of reliability to apply for firms using AI-based initial screening. However, the moderating role of reliability was not significant in the relationship between the AI interview and the applying intention. Employing uncertainty reduction theory, this study indicated that the relationship between AI-based selection tools and intentions to apply is dynamic, suggesting that organizations should carefully manage their AI-based selection techniques throughout the recruitment and selection process.

• 경영정보학연구
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• 제16권1호
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• pp.73-88
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• 2014

스마트폰 보급과 사용의 일상화로 사용자들은 다양한 모바일 앱을 사용하고 있으며 다수의 신생 기업들이 설립되어 모바일 앱을 개발하고 있다. 앱을 개발하고 있다. 모바일 산업 분야에서 고객의 특성을 파악하고 모바일 산업 분야에서 고객의 특성을 파악하고 고객 선호도에 맞춘 모바일 앱과 관련 서비스를 제공 하는 것은 모바일 시장에서 해당 앱의 경쟁력을 향상시키고 유통을 촉진시킬 수 있으며 나아가 모바일 시장 경제를 활성화시키는 효과가 있다. 본 연구에서는 사용자의 스마트폰앱 선택 기준에 따라 고객군을 나누고, 각 고객군의 특성에 대하여 고찰하였다. 즉, 고객군별로 앱을 이용하는 특성과 앱을 구매하는데 영향을 미치는 요인을 비교 분석하였다. 분석 결과, 적극 사용자그룹, 편리성 추구 그룹, 중간 사용자 그룹 등 3개의 그룹으로 구분되었으며 각 그룹에서 이용 특성과 앱 구매요인의 차이가 발견되었다. 이와 같이 개별 고객군의 앱 사용 특성과 앱 구매요인을 분석하는 것은 앱 소비자에 대한 이해를 증진시켜 소비자가 선호하는 앱을 기획, 설계, 개발하여 제공할 수 있고 마케팅 전략 수립시 고객의 앱 이용 특성 정보를 활용하는 효과가 기대된다.

• 정보처리학회논문지A
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• 제13A권6호
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• pp.533-540
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• 2006

본 논문에서는 분산 환경 상에서 CFD(Computational Fluid Dynamics) 분석 프로그램을 편리하게 수행할 수 있도록 하는 그리드 시스템 META(Metacomputing Environment using Test-un of Application)의 설계 및 구현에 관하여 기술한다. 그리드 시스템 META는 CFD 프로그램 개발자들이 네트워크에 분산된 계산 자원들을 단일 시스템처럼 사용할 수 있도록 한다. 그리드 컴퓨팅과 관련하여 연구주제로는 고장허용, 자원 선택, 사용자 인터페이스 설계 등이 있다. 본 논문에서는 MPI(Message Passing Interface)로 작성된 SPMD(Single Program, Multiple Data) 구조의 병렬프로그램을 실행시키기 위한 자동 자원 선택방법을 활용하였다. 본 논문에서 제안한 자원 관리기법은 네트워크상의 전송지연 시간과 시험수행을 통해 얻어진 핵심루프의 경과시간을 이용한다. 전송지연시간은 병렬 프로그램이 복수의 시스템에 분산되어 수행될 때 수행 성능에 큰 영향을 주는 요인이다. CFD 프로그램들의 공통적인 특성 때문에 핵심루프 경과시간은 전체 수행시간을 예측할 수 있는 지표가 된다. 핵심루프는 CFD 프로그램의 전체 수행시간 중 90% 이상을 차지한다.

• 한국경영과학회지
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• 제41권3호
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• pp.1-21
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• 2016

The Markowitz portfolio selection model uses estimators to deduce input parameters. However, the estimation errors of input parameters negatively influence the performance of portfolios. Therefore, this model cannot be reliably applied to real-world investments. To overcome this problem, we suggest an algorithm that can exclude stocks with large estimation error from the portfolio by applying a tracking signal to the Markowitz portfolio selection model. By calculating the tracking signal of each stock, we can monitor whether unexpected departures occur on the outcomes of the forecasts on rate of returns. Thereafter, unreliable stocks are removed. By using this approach, portfolios can comprise relatively reliable stocks that have comparatively small estimation errors. To evaluate the performance of the proposed approach, a 10-year investment experiment was conducted using historical stock returns data from 6 different stock markets around the world. Performance was assessed and compared by the Markowitz portfolio selection model with additional constraints and other benchmarks such as minimum variance portfolio and the index of each stock market. Results showed that a portfolio using the proposed approach exhibited a better Sharpe ratio and rate of return than other benchmarks.