• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.321-331
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• 1997

Measurement of attributes is often highly subjective and imprecise, yet most MADM methods lack provisions for handling imprecise data. Frequently, decision makers must establish a ranking within a finite set of alternatives with respect to multiple attributes which have varying degrees of importance. The problem is more complex if the evaluations of alternatives according to each attribute are not expressed in precise numbers, but rather in fuzzy numbers. Analysis must allow for lack of precision and partial truth. The advantages of a fuzzy approach for MADM are that a decision maker can obtain efficient solutions all at once without trial and error, and that this approach provides better support for judging the interactive improvement of solutions in comparison with o decision making method. The algorithm used in this study is based on the concepts of vague set theory. Linguistic variables and vague values are used to facilitate a decision maker's subjective assessment about attribute weightings and the appropriateness of alternative versus selection attributes in order to obtain final scores which are called vague appropriateness indices. A numerical example is presented to show the practical applicability of this approach.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.557-567
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• 2005

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore are, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiperson criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interaction may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.15-32
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• 2006

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiple criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interactions may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.137-149
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• 2007

Most of hospitals, especially small-scale hospitals, have tried to get customers through the Internet as what companies have done recently. There are various attempts that increase visits to one's web-site in plastic surgery hospitals. However, in plastic surgery, there have been few studies on which an attribute contributes to increase the number of web-site visit. In order to derive the important attributes on the number of visit, we compared functional attributes of 30 high-visit plastic surgery web-sites with those of 30 low-visit web-sites using statistical and data mining methods. For analysis, three methods have conducted including Multiple Discriminant Analysis (statistical method), Decision Trees (data mining method), and Artificial Neural Network (data mining method). Furthermore, results of each method have been evaluated one another. The result of this study shows that a few attributes like 'Simulating cyber plastic surgery program', 'recommendation of information' explain the number of the visitors between high and low visit web-site. The methodology employed in this study provides an efficient way of improving satisfaction of visitors of plastic surgery website.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5A
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• pp.431-439
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• 2010

In this paper, multiple-relay cooperative communication network with multiple antennas is considered. Applying the soft-decision-and-forward protocol to this system, pairwise error probability(PEP) is derived and then symbol error rate(SER) is also calculated. However, in general, signals are transmitted through the orthogonal channel in the multiple-relay cooperative communication network for the prevention of interference, which is inefficient in terms of the throughput. For the improvement of throughput, the relay selection is considered, where the relay having the maximum instantaneous end-to-end signal-to-noise ratio is chosen. Performance of the system is analyzed in terms of PEP and SER. As the number of the relay increases, relay selection method outperforms the conventional multiple-relay transmission system where all relays participate in the second time slot.

• The Journal of Information Technology
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• v.8 no.1
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• pp.51-56
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• 2005

The Back propagation algorithm is a very effective supervised training method for multi-layer feed forward neural networks. This paper studies the decision boundary formation based on the Back propagation algorithm. The discriminating powers of several neural network topology are also investigated against five manually created data sets. It is found that neural networks with multiple hidden layer perform better than single hidden layer.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.2
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• pp.125-136
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• 2012

Wrinkle and fracture are two major defects frequently found in the sheet metal forming process. In this process there are more than one design attributes to optimize and several uncontrollable factors which cannot be ignored in determining the optimal values of design variables. Therefore, attempts to reduce defects through a traditional optimization technique are often led to failures. In this research, a new design method for reducing the wrinkle and fracture under uncontrollable factors is presented by using decision-making theory. To avoid the psychological difficulties in determining the scaling constants of the multi-attribute utility function by using the ordinary lottery questions, a pair-wise comparison procedure is adapted to avoid this problem. The effectiveness of the proposed method is illustrated through a robust design of sheet metal forming process of a side member of an automotive body.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.470-471
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• 2018

This paper presents a design method for combinational digital logic systems using time domain based multiplexing and common multi-terminal extension decision diagrams. The proposed method can reduce the 1)hardware, 2)logic levels and 3)pins. In the logic system design, we use two types of decision diagrams(DDs), that is the common binary decision diagrams and CMTEDDs. Also, we propose an algorithms to derive common multiple-terminal binary decision diagrams from CBDDs, and CMTEDDs from CMTBDDs. The CMTEDDs over CBDDs is more compactness in terms of number of non-terminal nodes, where the nodes for output selection variables are not included in the non-terminal nodes. In the logic design, each non-terminal nodes of an CBDDs and an CMTEDDs is realized by a multiplexer(MUX). In addition, we compare the proposed TDBM realization with the conventional one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.687-688
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• 2011

This paper presents a design method for combinational digital logic systems using time domain based multiplexing(TDBM) and common multi-terminal extension decision diagrams(CMTEDD). The proposed method can reduce the 1)hardware, 2)logic levels and 3)pins. In the logic system design, we use two types of decision diagrams(DDs), that is the common binary decision diagrams(CBDDs) and CMTEDDs. Also, we propose an algorithms to derive common multiple-terminal binary decision diagrams(CMTBDD) from CBDDs, and CMTEDDs from CMTBDDs. The CMTEDDs over CBDDs is more compactness in terms of number of non-terminal nodes, where the nodes for output selection variables are not included in the non-terminal nodes. In the logic design, each non-terminal nodes of an CBDDs and an CMTEDDs is realized by a multiplexer(MUX). In addition, we compare the proposed TDBM realization with the conventional one.

• Journal of Korean Academy of Nursing Administration
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• v.17 no.3
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• pp.357-367
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• 2011

Purpose: The purpose of this study was to examine the influence of decentralization, participation in decision making, job satisfaction on organizational commitment among hospital nurse managers. Method: The data were derived from the self-reported questionnaire responses of 198 nurse managers from January to March, 2006 at four general hospitals over 900 beds in Seoul and Gyungi province and analyzed by frequency and percentage, t-test, ANOVA and Sheffe's test and stepwise multiple regression. Result: Mean of decentralization was 3.53${\pm}$0.52, participation in decision making was 5.04${\pm}$0.83, job satisfaction 3.54${\pm}$0.48, and organizational commitment was 5.30${\pm}$0.76. There were significant differences between participation in decision-making and career of manager, field of practice, span of control, especially in staffing decision. A significant correlation was found between organizational commitment and decentralization (r=.22, p<.001), participation in decision making (r=.40, p<.001), job satisfaction (r=.64, p<.001). The job satisfaction has the highest significant predictor of organizational commitment ($R^2$=43%). Conclusions: Nursing managers' job satisfaction and organizational commitment will be promoted by granting participation in decision-making.