• Journal of the Korean Society for Library and Information Science
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• v.43 no.4
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• pp.101-115
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• 2009

This research was based on Howard Gardner's multiple intelligences theory. The purpose of this study was to describe students' book selection preferences using the theory of multiple intelligences. We have conducted a survey of high schools in the Chung-Nam province, consisting of 100 students, 50 in the high academically achieving group and another 50 in the low achieving group, in an attempt to analyze the relationship between their book selection preferences and the types of students' multiple intelligences. We want to assist in the research data for the reading guide.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.91-105
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• 2008

Nowadays, circulation industry is taking charge of important role in improvement of competitive power on the manufacturing industry and public welfare increase of consumer, price stabilization, employment creation and so on. A lot of research have been progressing for formation of total circulation complex, but decision making for selection of location on some facility is only calculated the optimum value when correct data values are inserted. However, a lot of decision making is accomplished in situation that have little knowledge of objective and constraints and as real world is also evaluated inclusive of analyst's subjectivity about variable, indefinite and fuzzy part, so it is decreasing a reliability on evaluation result and complicating objective evaluation on various effect and negative impact. Accordingly, from under like this situation, this study is to develop location decision model of circulation complex using fuzzy theory from the intention for the most reasonable decision making in fuzzy situation based on decision making problem on conventional location and size decision that did to be satisfactory constraints necessarily.

• Spatial Information Research
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• v.7 no.2
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• pp.223-236
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• 1999

Recently, the need of wast incineratory has been recognized. However, the waste incinerator is considered the typical example of NYMB syndrome as a locally unwanted facilities. Therefore, the site selection of waste incineratory should be determined very carefully with consideration of various location factors. The purpose of this study is to provide a new decision-making process model for site selection that provides a rational and a systematic way. The fuzzy set theory and AHP theory, which have merits to overcome uncertainly and complexity of spatial data, are applied to select candidate sites for the waste incineratory. The method is able to produce a more flexible and objective solution for selecting suitability sites in comparison to rigid boolean logic. The result of this study shows that geographic information systems have clear implication for informing the spatial decision making process.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.135-140
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• 2007

Feature selection is a preprocessing technique commonly used on high dimensional data. Feature selection studies how to select a subset or list of attributes that are used to construct models describing data. Feature selection methods attempt to explore data's intrinsic properties by employing statistics or information theory. The recent developments have involved approaches like correlation method, dimensionality reduction and mutual information technique. This feature selection have become the focus of much research in areas of applications with massive and complex data sets. In this paper, we provide a feature selection method considering data characteristics and generalization capability. It provides a computational approach for feature selection based on fuzzy cluster analysis of its attribute values and its performance measures. And we apply it to the system for classifying computer virus and compared with heuristic method using the contrast concept. Experimental result shows the proposed approach can give a feature ranking, select the features, and improve the system performance.

• Korean Journal of Logic
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• v.12 no.2
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• pp.31-58
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• 2009

This paper defends Stalnaker's theory of indicative conditionals. His theory consists of selection functions and pragmatic constraints. The selection function takes a certain possible world(W) and a proposition(A) to yield a possilble world that is similar to W and in which A is true. And the pragmatic constraints plays role to make selection functions apply just to indicative conditionals. According to Stalnaker, as indicative conditionals has strong truth-value, uncontested principle always holds but passage principle does not always hold. However, his theory can explain why passage principle sometimes holds by means of pragmatic constraints. Also, this paper argues that Stalnaker's theory is the most acceptable one among others, by replying to criticisms suggested by Adamsians and the problem raised by Gibbard and other criticisms.

• Journal of Information Technology Applications and Management
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• v.13 no.3
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• pp.129-143
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• 2006

Diversity of available communication media has increased as the use of Internet and mobile technology increased rapidly. The traditional media tend to transform their roles and functionality. This change brings about the expansion of the span of media to be selected by users. In this study, we examined the characteristics of emerging communication media use based on Niche Theory. Online communication media in this study include Internet messenger, mobile phone, and e-mail. We also analyzed the relationship between the nature of task and the selection of communication media, that is, the effects of communication contexts(formal vs. informal, notification vs. request, superior vs. inferior) where by the communication partners are involved. The result of this study, mobile phone had the highest niche competitive superiority in all communication contexts, and internet messenger and e-mail made difference according to communication contexts. Also, we can notify internet messenger and e-mail have a mutual substitutive relationship by analysis of niche overlap.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.351-356
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• 2007

Factory location selection is very important to the success of operation of the whole supply chain, but few effective solutions exist to deliver a good result, motivated by this, this paper tries to introduce a new factory location selection methodology by employing the artificial neural networks technology. First, we reviewed previous research related to factory location selection problems, and then developed a (neural network-based factory selection model) NNFSM which adopted back-propagation neural network theory, next, we developed computer program using C++ to demonstrate our proposed model. then we did case study by choosing a Korean steelmaking company P to show how our proposed model works,. Finnaly, we concluded by highlighting the key contributions of this paper and pointing out the limitations and future research directions of this paper. Compared to other traditional factory location selection methods, our proposed model is time-saving; more efficient.and can produce a much better result.

• Management & Information Systems Review
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• v.3
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• pp.15-45
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• 1999

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3133-3151
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• 2012

The optimal price strategy selection of two bounded rational cognitive mobile virtual network operators (MVNOs) in a duopoly spectrum sharing market is investigated. The bounded rational operators dynamically compete to sell the leased spectrum to secondary users in order to maximize their profits. Meanwhile, the secondary users' heterogeneous preferences to rate and price are taken into consideration. The evolutionary game theory (EGT) is employed to model the dynamic price strategy selection of the MVNOs taking into account the response of the secondary users. The behavior dynamics and the evolutionary stable strategy (ESS) of the operators are derived via replicated dynamics. Furthermore, a reward and punishment mechanism is developed to optimize the performance of the operators. Numerical results show that the proposed evolutionary algorithm is convergent to the ESS, and the incentive mechanism increases the profits of the operators. It may provide some insight about the optimal price strategy selection for MVNOs in the next generation cognitive wireless networks.