• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.115-124
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• 2004

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are association rules, decision tree, clustering, neural network and so on. Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. We analyze Gyeongnam social indicator survey data using association rule technique for environmental information discovery. We can use to environmental preservation and environmental improvement by association rule outputs.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.145-151
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• 2006

Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule support and confidence and lift. Association rule is an interesting rule among purchased items in transaction, but the negative association rule is an interesting rule that includes items which are not purchased. Boolean Analyzer is the method to produce the negative association rule using PIM. But PIM is subjective. In this paper, we present statistical objective criterion in negative association rules using Boolean Analyzer.

• The Journal of Fisheries Business Administration
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• v.5 no.2
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• pp.1-47
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• 1974

This is the report of a study carried out during the months of April to July in 1974, on the fisheries in regard to its labor management. At here the word of adjacent seas fisheries in Korea denotes the fisheries carried out by fishing boats for one or two boats trawling, purse seinning, shrimp trawling, and whale catching. For the objective of this above study the auther randomly selected 257 crew-members for the questionaires and direct interviews and, with this method, proceeded surveys and investigations on the following factors such as the organization and its functions, personel administration in regard to placement and merit system, regulations and rules of working, wages and salaries, welfare facilities or considerations, safety and sanitation, human relations within organization and cooperation, and thus covered the whole important factors with the modern management system. The results of the studies are; The factors above the standard level are only on those of organization and functions, merit system and placement and human relations and for the rest the judgement are to be laid as below the standard level. And particularly revealing the problems on the following factors; 1) Wages and salary particulary on the payment upon laid out, and the payment of wages in advance. 2) Welfare facilities such as of the insurance and crew members' welfare for the good use of leisure time. 3) Placement and merit system in regard to ite method of appointing or empioying 4) Regulations and rules of working in regard to the vacation or leave of absence. 5) Safety problem particularly on the matter of sanitation or hygene. 6) Coopertion on the matter of participation on the interested problems on both parties. The above points indicated are, methinks, all derived out of the out dated method of management. Therefore, for the improvement of the labor management, first of all, nothing is more urgent than to adopt the modern labor management method as well as to encourage and enlighten the social responsibilities burdened on the enterprise.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.510-512
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• 1999

In this paper, we present a method for the analysis and design of fuzzy controller for nonlinear systems. In the design procedure, we represent the dynamics of nonlinear systems using a Takagi-Sugeno fuzzy model and formulate the controller rules, which shares the same fuzzy sets with the fuzzy system, using parallel distributed compensation method. Then, after the feedback gain of each local state feedback controller is obtained using the existing optimal pole-placement scheme, we construct an overall fuzzy logic controller by blending all local state feedback controller. Finally, the effectiveness and feasibility of the proposed fuzzy-model-based controller design method has been evaluated through an inverted pendulum system.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.59-69
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• 2005

Data mining is the method to find useful information for large amounts of data in database It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. We analyze Gyeongnam social indicator survey data by 2001 using association rule technique for environment information. Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. We can use to environmental preservation and environmental improvement by association rule outputs

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.421-424
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• 1996

To provide an appropriate knowledge representation technique dependent on a particular domain, we consider the combine analytic hierachy process(CAHP). This is an extended method of the conventional AHP which is useful when two different expert groups are involved. Our problem domain is confined to human resource management including such major activities as planning, selection, placement, compensations, performance evaluation, training, and labor-management relations. We prioritize rules, frames, semantic nets, and predicate logic representation techniques best suited to each and all domains through an exploratory study.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.25-38
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• 2004

Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. In this paper we present the relation between the measure of association based on chi square statistic and the criteria of association rule for nominal database and propose the objective criteria for association.

• Asia pacific journal of information systems
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• v.7 no.1
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• pp.85-97
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• 1997

This paper is concerned with knowledge representation schemes best suited for human resource management (HRM) problem domains including human resource planing, selection, placement, compensations, performance evaluation, training and labor-management relations. In order to suggest the scheme we consider two research gods. First, we evaluate and prioritize. The knowledge representation techniques of frames rules, semantic nets and predicate logic that hove been recommended to managerial domains. The combined Analytic Hierarchy Process technique is employed to combine individual judgments effectively between two different expert groups. As a result if we are to select a single knowledge representation technique, a frame representation is best for most HRM domains and to combine frames with others is another choice. Second as a strategy for knowledge representation schemes we show some examples for each damn in terms of labeled semantic nets and two types of rules derived from the semantic nets. We propose nine knowledge components as ontologies. The labeled semantic nets con provide some benefits compared with conventional one. More clearly definea node rode information maces it easy to find the ac information. In the rule sets, the variables are the node of the semantic nets. The consistency of rules is validated by the relationship of the knowledge components.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.939-948
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• 2012

The most widely used data mining technique is to explore association rules. This technique has been used to find the relationship between items in a massive database based on the interestingness measures such as support, confidence, lift, etc. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control.In general, association rule technique generates the rule, 'If A, then B.', whereas negative association rule technique generates the rule, 'If A, then not B.', or 'If not A, then B.'. We can determine whether we promote other products in addition to promote its products only if we add negative association rules to existing association rules. In this paper, we proposed the negatively attributable and pure confidence to overcome the problems faced by negative association rule technique, and then we checked three conditions for interestingness measure. The comparative studies with negative confidence, negatively pure confidence, and negatively attributable and pure confidence are shown by numerical examples. The results show that the negatively attributable and pure confidence is better than negative confidence and negatively pure confidence.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.168-178
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• 2017

In order to prevent major and chemical accidents, some of the plants which would like to install and operate hazard chemicals handling facilities must submit Off-site Consequence Analysis due to recent arisen leak accidents since 2015. A lot of chemical industrials choose gas detectors as mitigation equipment to early detect gas vapor. The way of placement of gas detectors has two methods; Code-based Design(CBD) and Performance-based Design. The CBD has principles for gas detectors to be installed with consideration for the place that is expected to accumulate gas, and the leak locations according to legal standards and technical guidelines, and has a possibility to be unable to detect by these rules to locate gas detectors by vapor density information. The PBD has two methods; a Geographic Method and Scenario based Method. The Scenario-based Method has been suggested to make up for the Geographic Coverage Method. This Scenario-based Method draw the best optimum placement of gas detectors by considering leak locations, leak speed information, leak directions and etc. However, the domestic placement guidelines just refers to the CBD. Therefore, this study is to compare existing placement location of gas detectors by the domestic CBD with placement locations, coverages and the number of gas detectors in accordance with the Scenario-based Method. Also this study has measures for early detecting interest of Vapor Cloud and suitable placement of gas detectors to prevent chemical accidents. The Phast software was selected to simulate vapor cloud dispersion to predict the consequence. There are two cases; an accident hole size of leak(8 mm) from API which is the highst accident hole size less than 24.5 mm, and a normal leak hole size from KOSHA Guide (1.8 mm). Detect3D was also selected to locate gas detectors efficiently and compare CBD results and PBD results. Currently, domestic methods of gas detectors do not consider any risk, but just depend on domestic code methods which lead to placement of gas detectors not to make personnels recognize tolerable or intolerable risks. The results of the Scenario-based Method, however, analyze the leak estimated range by simulating leak dispersion, and then it is able to tell tolerable risks. Thus it is considered that individuals will be able to place gas detectors reasonably by making objectives and roles flexibly according to situations in a specific plant.