• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.115-125
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• 2006

A concept hierarchy represents the knowledge with multi-level form, which is very useful to categorize, store and retrieve the data. Traditionally, a concept hierarchy has been built manually by domain experts. However, the manual construction of a concept hierarchy has caused many problems such as enormous development and maintenance costs and human errors such as inconsistency. This paper proposes the automatic creation of concept hierarchies using the predefined hypernym relation. To create the hierarchy automatically, we first eliminate the ambiguity of the senses of data values, and construct the hierarchy by grouping and leveling of the remaining senses. We use the WordNet explanations for multi-meaning word to eliminate the ambiguity and use the WordNet hypernym relations to create multi-level hierarchy structure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.1
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• pp.25-32
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• 2011

Under limited resources such as budgets and experts, it is essential to set promotion priorities for standardization work items on IPv6 (Internet Protocol version 6) multi-networking technologies. Opinions of domain experts are surveyed and analyzed utilizing a multi-criteria decision making tool, the Analytic Hierarchy Process (AHP). Weights of ten evaluation criteria are identified and applied to calculating importance degree of eight work items. According to descending order of importance degree, priorities of work items are determined. The processes and results of this study may provide not only an approach of setting promotion priorities for standardization work items but also a practical guide of implementing of a multi-criteria decision analysis.

• Korean Management Science Review
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• v.24 no.2
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• pp.57-72
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• 2007

Many Applications of scientific research have coupled with functional data signal clustering techniques to discover novel characteristics that can be used for the diagnoses of several issues. In this article we present an interpretable multi-scale cluster hierarchy framework for clustering functional data using its multi-aspect frequency information. The suggested method focuses on how to effectively select transformed features/variables in unsupervised manner so that finally reduce the data dimension and achieve the multi-purposed clustering. Specially, we apply our suggested method to mutual fund returns and make superior-performing funds group based on different aspects such as global patterns, seasonal variations, levels of noise, and their combinations. To promise our method producing a quality cluster hierarchy, we give some empirical results under the simulation study and a set of real life data. This research will contribute to financial market analysis and flexibly fit to other research fields with clustering purposes.

• ETRI Journal
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• v.34 no.2
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• pp.199-209
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• 2012

In transport networks, a multi-ring architecture is very useful to facilitate network planning and to design and provide more resilient services for customers. Unlike traditional synchronous optical network multi-rings, the service resiliency of Ethernet-based multi-rings is significantly impacted by the ring hierarchy because a link or node failure in a certain level ring triggers filtering database flush actions in all higher level rings as well as in the ring with the failure, and consequently a large amount of duplicated data frames may be flooded. In this paper, we investigate how the ring hierarchy impacts the service resiliency of multi-ring networks. Based on extensive experiments on various single- and multiple-link failures, we suggest two effective inter-ring connection rules to minimize the transient traffic and to ensure more resilient multi-ring networks. In addition, we consider a flush optimization technique called e-ADV, and show that the combination of e-ADV and multi-ring structures satisfying our inter-ring connection rules results in a more attractive survivability performance.

• Korean Journal of Agricultural Science
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• v.38 no.1
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• pp.183-190
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• 2011

The paper is to analyze multi-attributes for expanding new renewable energy in agricultural sectors which have environmental, technical, economic, and social factors consisting of 15 attributes which have both positive and negative impacts. We applied the analytic hierarchy process (AHP) to data from opinion polls. As a result of the AHP survey, the overall results indicate that the respondents more weight on economical factor than environmental, technical, and social factors for expanding new renewable energy. At the lowest level, a comparison of individual 15 attributes within three factors shows that fixed cost highest in multi-attributes, followed by operating cost, technical superiority. To achieve the public acceptance about expanding new renewable energy in agricultural sectors, the policy-makers should take all relevant factors into account through the decision-making process by the public opinions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.148-151
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• 2003

Recently school food service operations are confronted with the wide spread pressures for accountability and the need to increase productivity. This paper is concerned with the make-or-buy decision framework for school food service systems considering the multi-attributes in the decision making. For the purpose of considering the multi-attributes analysis method in decision making for the school foodservice, we developed a make-or-buy decision framework using the multi-attribute analysis method, analytic hierarchy process, AHP method for school food service system. Finally, we developed a systematic and practical solution builder for a three-step decision support system in the view of 1) brainstorming for the idea generation, 2) analytic hierarchy process, AHP as a multi-attribute structure ed analysis method, and 3) aggregation logic model to integrate the results of reviewers. We developed web based program and applied it to a school foodservice problem.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.378-385
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• 2010

The explosive increase in the use of email has made to need email classification efficiently and accurately. Current work on the email classification method have mainly been focused on a binary classification that filters out spam-mails. This methods are based on Support Vector Machines, Bayesian classifiers, rule-based classifiers. Such supervised methods, in the sense that the user is required to manually describe the rules and keyword list that is used to recognize the relevant email. Other unsupervised method using clustering techniques for the multi-category classification is created a category labels from a set of incoming messages. In this paper, we propose a new automatic email multi-category classification method using NMF for automatic category label construction method and dynamic category hierarchy method for the reorganization of email messages in the category labels. The proposed method in this paper, a large number of emails are managed efficiently by classifying multi-category email automatically, email messages in their category are reorganized for enhancing accuracy whenever users want to classify all their email messages.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.352-357
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• 1998

Conventional marketing research generally focuses on a single layer's benefit. A notable example is the consumer layer providing managers with partial market information to evaluate relevant strategies. As generally known, marketing management encounters complex supply and demand behaviors, thereby necessitation that a successful marketing strategy adopt multi-layer considerations, such as the consumer layer, channel-retailer layer, and marketing planner layer. In light of above situation, this study applies fuzzy theory and the analytic hierarchy process(AHP) technique to analyze the performances of marketing strategies under multi-layer benefits, In addition, conventional marketing research has difficulty in efficiently allocating the limited budget so that each desired criterion can be significantly enhanced by a group of events. Therefore, a weighting structure among the goal, layers, criteria, and strategies(i.e. a group of events) is also developed herein to trace the influential process and assist marketing managers in efficiently allocating resources(i.e.budget).

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.557-562
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• 2009

Weapon system currently considers the research about effect analysis including cost effectiveness methodology for a budget management and an achievement of the military strategy goal. So that, this study considers the theoretical background, strength and weakness of several Multi-Criteria Decision Making, and an effect analysis of weapon system. And AHP(Analytic Hierarchy Process) is selected for the best effect analysis methodology of weapon system. Therefore, we applied AHP to the case study of the new generation Multiple Launcher Rocket System, performing the analysis of cost effectiveness methodology. Using AHP and cost effectiveness methodology, we propose the actual and proper decision making result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1437-1459
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• 2020

Wireless Sensor Networks (WSN) is a distributed Sensor network whose terminals are sensors that can sense and check the environment. Sensors are typically battery-powered and deployed in where the batteries are difficult to replace. Therefore, maximize the consumption of node energy and extend the network's life cycle are the problems that must to face. Low-energy adaptive clustering hierarchy (LEACH) protocol is an adaptive clustering topology algorithm, which can make the nodes in the network consume energy in a relatively balanced way and prolong the network lifetime. In this paper, the novel multi-objective LEACH protocol is proposed, in order to solve the proposed protocol, we design a multi-objective coupling algorithm based on bat algorithm (BA), glowworm swarm optimization algorithm (GSO) and bacterial foraging optimization algorithm (BFO). The advantages of BA, GSO and BFO are inherited in the multi-objective coupling algorithm (MBGF), which is tested on ZDT and SCH benchmarks, the results are shown the MBGF is superior. Then the multi-objective coupling algorithm is applied in the multi-objective LEACH protocol, experimental results show that the multi-objective LEACH protocol can greatly reduce the energy consumption of the node and prolong the network life cycle.