• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.4
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• pp.441-447
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• 2015

This paper proposes a novel fuzzy-based multi-criteria decision making method and implements a footstep planner for humanoid robots with it. Humanoid robots require additional footstep planning process in addition to path planning for the autonomous navigation. Moreover, it is necessary to consider safety and energy consumption as well as path efficiency and multi-criteria decision making is indispensable. The proposed method can provide not only well- distributed and non-dominated, but also more preferable solutions for users. The planned footsteps by the proposed method were verified through simulation. The results indicate that the user's preference is properly reflected in optimized solutions maintaining solution quality.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.195-201
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• 2007

A minimum terminal path decomposition of a tree is defined as a partition of the tree into edge-disjoint terminal-to-terminal paths that minimizes the weight of the longest path. In this paper, we present an $O({\mid}V{\mid}^2$time algorithm to find a minimum terminal path decomposition of trees. The algorithm reduces the given optimization problem to the binary search using the corresponding decision problem, the problem to decide whether the cost of a minimum terminal path decomposition is at most l. This decision problem is solved by dynamic programing in a single traversal of the tree.

• Journal of Korean Academy of Nursing
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• v.48 no.5
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• pp.578-587
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• 2018

Purpose: This study aimed to understand the mechanisms of decision regret and stress of family surrogates' end-of-life decision making using an exploratory path model. In particular, the research identified the direct effects of perceptions of uncertainty and effective decisions on decision regret and stress, and examined the indirect effects of being informed, having clear values, and being supported for decision regret and the stress of end-of-life decision making through the mediating variables of perceptions of uncertainty and effective decisions. Methods: Data were collected from 102 family surrogates who had participated in end-of-life decision making for patients with terminal cancer in a tertiary hospital. Results: Perception of effective decisions was a significant direct predictor of decision regret, and uncertainty was a significant predictor of stress among the participants. Being informed, having clear values, and being supported had a significant indirect influence on decision regret through the perception of effective decisions among family surrogates. However, only having clear values had a significant indirect influence on stress through the perception of uncertainty. The model explained 63.0% of decision regret and 20.0% of stress among the participants and showed a good fit with the data, ${\chi}^2=12.40$ (df=8, p=.134), TLI=.97, and RMSEA=.07. Conclusion: Nurses can support family surrogates in end-of-life decision-making processes to decrease their decision regret by providing information about end-of-life care choices, clarifying personal values, and supporting the decision-making process, and to relieve their stress by facilitating the clarification of personal values.

• Fashion & Textile Research Journal
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• v.22 no.3
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• pp.323-334
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• 2020

This study analyzed the effects of consumers' characteristic variables on information search and purchase decisions in a decision-making process that validated the path model in purchasing apparel products. In constructing a structural equation model using AMOS 19.0., the variables including enjoyment pursuit, price pursuit, product involvement and product risk were selected as consumers' characteristic variables affecting the stage of information search. A questionnaire was distributed to consumers over 20 years old who purchased apparel products using offline and online channels within one year; consequently, we were able to analyze 468 effective data. The results were as follows. First, the path model of this research proved to be the appropriate model explaining the effects of consumers' characteristic variables on the stage of purchase decision-making. Second, enjoyment pursuit had a significant positive influence on offline information search; in addition, price pursuit and product risk affected the online information search significantly. Product involvement affected online information search as well as offline information search. Third, the offline information search affected offline purchase and online information search affected online purchase. However, consumer's channel switching behavior between the stage of information search and the stage of purchase decision was not proven. The findings suggest that companies need to develop distribution strategies according to consumers' characteristic factors that effect consumer's purchase decision-making.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.473-479
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• 2005

A key issue toward mobile multimedia communications is to create technologies for broadband signal transmission that ran support high quality services. Such a broadband mobile communications system should be able to overcome severe distortion caused by time-varying multi-path fading channel, while providing high spectral efficiency and low power consumption. For these reasons, an adaptive suboptimum decision feedback equalize. (DFE) for the single-carrier short-burst transmissions system is considered as one of the feasible solutions. For the performance improvement of the system with the short-burst format including the short training sequence, in this paper, the multiple-training least mean square (MTLMS) based DFE scheme with soft decision feedback is proposed and its performance is investigated in mobile wireless channels throughout computer simulation.

• Journal of Families and Better Life
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• v.23 no.3 s.75
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• pp.77-91
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• 2005

This study conceptualized the factors affecting college students' consumer decision-making styles from the perspective of consumer socialization. A number of antecedent variables identified by preceding studies (age, gender, place where one grew up, job experience, main reason for working, amount of allowance, family income, socio-economic status) and socialization agents such as family, peers, mass media were included in the analysis. This study extends previous studies by examining a theoretical link between the antecedent variables and socialization agents. Three hundred and forty one undergraduate students in Daejeon were participated in this study. Stepwise multiple regression md path analysis were conducted. The results of this study are as follows: 1. Six consumer decision-making styles were identified. 2. The influence of the socialization agents, especially mass media and several antecedent variables, especially gender and main reason for working, played important roles in consumer decision-making styles. 3. Several antecedent variables, especially gender and family income, were related only with the influence of socialization agents. 4. Six path-analysis models that illustrate the relationships among the antecedent variables, the socialization agents and consumer decision-making styles were proposed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.311-320
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• 2018

This study was conducted to investigate the relationship among major satisfaction (MS), clinical competence (CC), career decision-making self-efficacy (CDMS), and career decision level (CDL) for undergraduate nursing students. A self-report instrument was used to measure MS, CC, CDMS, and CDL. Questionnaires were completed by 307 nursing students in three nursing colleges, and path analysis was employed to validate the proposed model and analyze the causal relationships among variables. Four constructs (MS, CC, CDMS, and career decision) were analyzed. To build a path model, MS and CC were linked to CDMS and career decision. The initial analysis suggested that the modification needed modification; therefore, a covariance link was added. The overall goodness of fit for indices indicated satisfactory path analysis. The indices were revealed as $x^2=2412$, GFI=0.996, AGFI=0.961, and RMSEA=0.068. As a result, the proposed model was acceptable with a good fit, and there were significant direct and indirect effects of paths in the model. Specifically, MS and CC had a direct influence on CDMS, and MS and CDMS directly affected CDL. Moreover, MS and CC had indirect effects on CDL through CDMS. These results imply that students' CDMS should be seriously considered when designing counseling programs for career guidance, and substantiality of CC education is needed to improve CDMS. These results may provide a practical guideline to provide educational intervention for nursing students.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.49-56
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• 2011

This paper deals with a methodology for searching optimal route of hazard material (hazmat) vehicles. When we make a decision of hazmat optimal paths, there is a conflict between the public aspect which wants to minimize risk and the private aspect which has a goal of minimizing travel time. This paper presents Efficient Vector Labeling algorithm as a methodology for searching optimal path of hazmat transportation, which is intrinsically one of the multi-criteria decision making problems. The output of the presented algorithm is a set of Pareto optimal paths considering both risk and travel time at a time. Also, the proposed algorithm is able to identify non-dominated paths which are significantly different from each other in terms of links used. The proposed Efficient Vector Labeling algorithm are applied to test bed network and compared with the existing k-shortest path algorithm. Analysis of result shows that the proposed algorithm is more efficient and advantageous in searching reasonable alternative routes than the existing one.

• Asia pacific journal of information systems
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• v.6 no.1
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• pp.39-74
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• 1996

Most of the research on a group decision support system [GDSS] has focused on directly examining its effect on the decision outcomes. Under this research framework, however, the role of group interaction process is largely ignored. This study focuses on the effect of the group interaction process on decision-making performance when a GDSS is used as the only medium for group interaction. Specifically, this study sought to determine whether significant relationships exist between the quality of the decision and the decision functions, contingent phases, and different decision paths. Natural interaction processes of decision -making groups was simulated in an experimental setting in which volunteer subjects from several business classes were assigned to dispersed three-person groups undertook the experimental task via a decision network. A baseline GDSS was developed for this setting. The results of this study confirmed earlier studies in a non - GDSS setting to suggest significant effects of decision functions and contingent phases on the quality of decision but no significant relationship between decision path and the quality of group decision.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2450-2460
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• 2015

Recently, as interest in IoT (Internet of Things) increase, research and standardization of a new protocol which reflects the characteristics of IoT has progressed. Among them, RPL(IPv6 for Low-Power Lossy Network) is a standardized routing protocol for IoT. RPL utilizes DIO (DODAG Information Object) messages which is flooded from the sink node to the whole network for path establish and maintenance. However, in large scale networks, not only a long time is required to propagate the DIO message to the whole networks but also a bottleneck effect around the sink node is occurred. Multi-sink based approaches which take advantage of reducing routing overhead and bottleneck effect are widely used to solve these problems. In this paper, we define 'unnecessary path update problems' that may arise when applying the RPL protocol to the multi sink based IoT networks and propose two methods namely Routing Metric based Path Update Decision method and Immediate Successor based Path Update Decision method for selective routing update.