• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.537-540
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• 1999

We propose a decision model to incorporates the values assigned by a group of experts on different factors in selecting robots. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for robot selection. A numerical example is presented to illustrate the model and to show a rank reversal when compared to a model that does not eliminate extreme values and eliminates the highest and lowest experts' values allocating the weights and the subjective factors.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.444-451
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• 1999

A diagnostic rule-base design method for enhancing fault detection and isolation performance of multiple obsever based fault detection isolation schemes (FIDS) is presented. The diagnostic rule-base has a hierarchical framework to perform detection and isolation of faults of interest, and diagnosis of process faults. The decision unit comprises a rule base and a fuzzy inference engine and removes some difficulties of conventional decision unit which includes crisp logic with threshold values. Emphasis is placed on the design and evaluation methods of the diagnostic rult-base. The suggested scheme is applied to the FDIS design for a DC motor driven centrifugal pump system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3B
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• pp.259-266
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• 2002

In the CDMA system, the Multiple access interference(MAI) causes system performance and capacity degradation. One of the MAI cancel method is a feedback detector that orthogonal decision-feedback detector(ODFD) and Deocrrelating decision-feedback detector(DDFD) have been studied by now. In this paper, we propose a blind adaptive ODFD(BA-ODFD) with blind equalizer combined ODFD, Also we simulate the operation of BA-ODFD in AWGN channel and Rayleigh (tiding channel. and compare blind adaptive ODFD with blind adaptive DDFD.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.1017-1023
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• 2021

This research aims to determine the effect of customers' threat emotion and price on the decision to purchase a certain smartphone product. This study uses a quantitative method with a type of descriptive and causal research. It employs non-probability sampling with purposive sampling, with 385 respondents to answer the questionnaires. Data analysis techniques used descriptive analysis and multiple linear regression analysis. Based on the results of descriptive analysis of emotion, price and purchasing decisions are in sync with each other. The results of multiple linear regression analysis techniques indicate the threat emotion and brand trust are influential against the positive decision to purchase smartphone products. The magnitude of the influence of emotions and price have simultaneous effect on purchasing decisions and other decision variables, which are not included in this study, also play minor role in determining purchase intention, such as product quality, brand image and others. Partially, threat emotion and brand trust have a positive effect toward purchasing decisions. The magnitude of the highest influence was the one of price, then followed by emotional threats. The findings of this study suggest that psychological and behavioral effects also play important roles in determining customers' purchase decision.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.4
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• pp.371-380
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• 2023

Purpose: The purpose of this study is to determine the relationship between nursing students' biomedical and artificial intelligence (AI) ethical awareness, ethical values, professional self-concept, and ethical decision-making confidence, and to then identify factors that can influence their ethical decision-making confidence. Methods: This study employed a descriptive research method and was conducted from June 8 to 12, 2023, with 204 students from three nursing colleges in Korea. The collected data were analyzed by frequency and percentage, independent t-test, Pearson's correlation coefficient, and multiple regression using IBM SPSS 23.0. Results: The results of the multiple regression analysis showed that the regression model was significant (F=18.88, p<.001) and that professional self-concept (β=.46, p<.001), ethics education (β=.23, p<.001), AI ethical awareness (β=.16, p=.020), and relativistic ethical values (β=.14, p=.035) explained 34.6% of the nursing students' ethical decision-making confidence. Conclusion: It is necessary to include professional self-concept, AI ethical awareness, and ethical values contents when constructing the curriculums of educational programs in order to improve nursing students' ethical decision-making confidence.

• Journal of Korean Academy of Nursing
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• v.34 no.2
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• pp.270-277
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• 2004

Purpose: The purpose of this study was to investigate the relationship between decision-making factors(theoretical knowledge, expertise, empowerment, intuition) and participation in proportion to nurses's clinical experience. Method: Data was collected by quota sampling from July 10, 2001 to August 22, 2001 from 132 clinical nurses who work for 3 General hospitals. Data was analyzed using SPSSWIN 10.0 with crosstab, ANOVA, and stepwise multiple regression. Result: Expertise(F=34.347, p=.000), empowerment(F=29.316, p=.000), and participation(F=3.276, p=.041) were significantly different among 3 clinical experience groups. Clinical experience correlated with expertise(r=.551, p=.000) and empowerment(r=.492, p=.000), and Decision-making participation also correlated with expertise(r=.351, p=.000) and empowerment(r=.265, p=.002). Decision-making participation is effected by theoretical knowledge(under 3.00yr clinical experience), expertise(3.01-5.00yr), and empowerment(above 5.01yr). Conclusion: These findings indicate that factors(theoretical knowledge, expertise, or empowerment) on decision-making participation varies as nurses's clinical experience differs. Therefore, decision-making needs bilateral agreement between staff nurses and nurse managers rather than the responsibility of one.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.1
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• pp.25-30
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• 2012

Desirability approaches have been proposed to find an optimum of multiple response problem. The existing desirability approaches use either of mean or min of individual desirability in aggregation of multiple responses. However, in order to find an optimum having high mean and low dispersion among individual desirability, the dispersion needs to be simultaneously considered with its mean. This study proposes bias and variance (BV) method which aggregates bias (ideal target-mean) and variance of individual desirability in multiple response optimization. The proposed BV method was applied to an example to evaluate its usefulness by comparing with existing methods. Evaluation results showed that the solution of BV method was a fairly good compared with DS (Derringer and Suich, 1980) and KL (Kim and Lin, 2000) methods. The BV method can be utilized to multiple response surface problems when decision makers want to find an optimum having high mean and low variance among responses.

• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.1
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• pp.14-30
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• 1985

Recently, multiple criteria decision making has been well established as a practical approach to seek a satisfactory solution to a decision making problem. Goal programming is one of the most powerful MCDM tools with satisfying operational assumptions that reflect the actual decision making process in real-world situations. In this paper we propose an efficient method implemented on a microcomputer for solving linear goal programming problems. It is an iterative revised goal simplex method using the sparsity technique. We design as interactive software package for microcomputers based on this method. From some computational experiences, we can state that the revised iterative goal simplex method using the sparsity technique is the most efficient one for microcomputer for solving goal programming problems.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.838-840
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• 2002

Presently, Analytic Network Process which evaluates man's intention and offers decision-making support is capturing the spotlight. It originates in the ability of Analytic Network Process to treat various decision-making support system. However, no detailed reference is available when dealing with the group case. This paper examines the technique, which can also cope with the group decision-making support system, and describes the validity of the technique. A characteristic feature of the proposed technique is that it can detect a group's intention in a given section, and it decomposes the sectional supermatrix into a small supermatrix and a large one. A general supermatrix treats the convergence value by taking the limiting process method of the power of an evaluation value. On the other hand, when a supermatrix has nonnegative value, it can easily be solved by the eigenvector method. The decomposition of the supermatrix has been considered in this work.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.54-62
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• 2011

Emotional reaction should be different from the purpose of the robot system. The method for emotional reaction is also different from the specification of the robot system. Therefore, emotional behavior decision model, which is applied to social robots regardless of specifications and purposes, is necessary. This paper introduces a universal emotional behavior decision model designed for applying to various social robots that have different specifications and purposes. Multiple emotions, a set of probability value of every emotion, are calculated independently and expressed according to the purpose of the robot system. Then, behavior, for emotional reaction according to the calculated multiple emotions, is decided regarding the specification of the robot system. The decided behavior is a combination of unit behaviors that indicates the smallest expressible behaviors in each expression parts. It is possible to express various undefined behaviors by generating unit behavior combinations according to multiple emotions. The universal emotional behavior decision model is applied to three kinds of social robot systems that have different specifications and purposes.