• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1553-1556
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• 1991

This paper deals with a problem on the selection of alternative tools in a flexible manufacturing system (FMS) where a lot of tools are required to produce a large variety of product items. An approach using branch and bound method is proposed to minimize a total number of tools required through the optimal use of the alternative tools. In this approach, tools are initially divided into tool subgroups based on graph theory for the purpose of the effective search of the optimal solution. A small example is also presented to highlight the effectiveness of the proposed approach.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.45-55
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• 1989

This paper deals with development of a computer-aided process selection and sequencing technique and its software for metal cutting processes of rotational parts. The process selection procedure consists of selection for proper machining operations and machine tools suitable for the selected operations. Machining operations are selected based on machining surface features and machine tools are selected by employing a conversion table which converts machining operations into machine tools. The process sequence is determined by the proper manipulation of the precedence relation matrix. A computer program for the proposed technique is developed by using Turbo-Pascal on IBM PC/AT compatible system. The proposed technique works well to real problems.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.2
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• pp.213-238
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• 2004

Book review Is a mean that provides Qualitative evaluation and at the same time it plays a role as selection tools for libraries. Therefore, this study Identified various media providing reviews on children's books, evaluated whether the reviews in the media were useful as selection tools of current books, and a desirable model for the book review media that would reform the existing problems was suggested. The efforts to make up for the above suggestions are needed, so that the current children's book review media can properly play a role as selection tools. Above all, at this point in time, it is necessary to publish review media made in the view of libraries and librarians.

• Interdisciplinary Bio Central
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• v.6 no.1
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• pp.1.1-1.6
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• 2014

A growing body of evidence shows that most psychological traits are polygenic, that is they involve the action of many genes with small effects. However, the study of selection has disproportionately been on one or a few genes and their associated sweep signals (rapid and large changes in frequency). If our goal is to study the evolution of psychological variables, such as intelligence, we need a model that explains the evolution of phenotypes governed by many common genetic variants. This study illustrates simple statistical tools to detect signals of recent polygenic selection: a) ANOVA can be used to reveal significant deviation from random distribution of allele frequencies across racial groups. b) Principal component analysis can be used as a tool for finding a factor that represents the strength of recent selection on a phenotype and the underlying genetic variation. c) Method of correlated vectors: the correlation between genetic frequencies and the average phenotypes of different populations is computed; then, the resulting correlation coefficients are correlated with the corresponding alleles' genome-wide significance. This provides a measure of how selection acted on genes with higher signal to noise ratio. Another related test is that alleles with large frequency differences between populations should have a higher genome-wide significance value than alleles with small frequency differences. This paper fruitfully employs these tools and shows that common genetic variants exhibit subtle frequency shifts and that these shifts predict phenotypic differences across populations.

• Korean Journal of Computational Design and Engineering
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• v.3 no.3
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• pp.177-182
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• 1998

The computer related techniques have been developed rapidly in the field of metal removal industry. The electronic catalog for mechanical elements is one of such developments realized in recent years. As the emergence of the electronic catalogs in the 90s, it breaks the restriction of the traditional catalog and becomes a helpful and efficient tool in the field. In this paper, we develop an electronic catalog for the cutting tools of the Korea Tungsten Co. Ltd. The catalog consists of three parts: a preprocessor for tool selection, a database for tool, and a postprocessor for search result. A preprocessor for tool selection is developed under a user-friendly consideration. A database for tool consists of milling, drilling, and reaming tools with a list of cutters, inserts, and components. A postprocessor for search result consists of weight, dimension. drawing, product order number etc. of the tools. It also suggests the optimized cutting condition of the selected tool using a neural network technique which is done by an independent research group.

• KIISE Transactions on Computing Practices
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• v.24 no.1
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• pp.46-52
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• 2018

Software metrics as a way to evaluate software play a significant role in reducing software development costs and improving quality. However, the emergence of various software metrics creates the problem that the user must select the correct metric. Various strategies have been studied to solve this problem. However, existing studies still have difficulties in selecting metrics by requiring high user interventions. Therefore, in this paper, we propose a method that helps to select the right metric and the metric tools by using their various characteristics as selection criteria, instead of using weighted expressions to minimize user intervention.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.345-350
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• 1999

The effectiveness of software error compensation for thermally induced machine tool errors relies on the prediction accuracy of the pre-established thermal error models. The selection of optimal sensor locations is the most important in establishing these empirical models. In this paper, a methodology for the selection of optimal sensor locations is proposed to establish a robust linear model which is not subjected to collinearity. Correlation coefficient and time delay are used as thermal parameters for optimal sensor location. Firstly, thermal deformation and temperatures are measured with machine tools being excited by sinusoidal heat input. And then, after correlation coefficient and time delays are calculated from the measured data, the optimal sensor location is selected through hard c-means clustering and sequential selection method. The validity of the proposed methodology is verified through the estimation of thermal expansion along Z-axis by spindle rotation.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.9
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• pp.101-110
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• 1998

In process planning for 3D pocket machining, the critical issues for the optimal process planning are the generation of cutting layers and the tool selection for each cutting layers as well as the other factors such as the determination of machining types, tool path, etc. This paper describes the optimal tool selection on a single cutting layer for 2D pocket machining, the generation of cutting layers for 3D pocket machining, the determination of the thickness of each cutting layers, the determination of the tool combinations for each cutting layers and also the development of an algorithm for determining the machining sequence which reduces the number of tool exchanges, which are based on the backward approach. The branch and bound method is applied to select the optimal tools for each cutting layer, and an algorithmic procedure is developed to determine the machining sequence consisting of the pairs of the cutting layers and cutting tools to be used in the same operation.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.49-58
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• 1997

In process planning for pocket machining, the selection of tool size, tool path, overlap distance, and the calculation of machining time are very important factors to obtain the optimal process planning result. Among those factors, the tool size is the most important one because the others depend on tool size. And also, it is not easy to determine the optimal tool size even though the shape of pocket is simple. Therefore, the optimal selection of tool size is the most essential task in process planning for machining a pocket. This paper presents a method for selecting optimal toos in pocket machining. The branch and bound method is applied to select the optimal tools which minimize the machining time by using the range of feasible tools and the breadth-first search.

• The Journal of Information Systems
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• v.28 no.2
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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.