• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1044-1047
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• 2005

In this paper, we present the strategy of object search for distributed autonomous robotic systems (DARS). The DARS are the systems that consist of multiple autonomous robotic agents to whom required functions are distributed. For instance, the agents should recognize their surrounding at where they are located and generate some rules to act upon by themselves. In this paper, we introduce the strategy for multiple DARS robots to search a hidden object at the unknown area. First, we present an area-based action making process to determine the direction change of the robots during their maneuvers. Second, we also present Q learning adaptation to enhance the area-based action making process. Third, we introduce the coordinate system to represent a robot's current location. In the end of this paper, we show experimental results using hexagon-based Q learning to find the hidden object.

• IE interfaces
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• v.16 no.4
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• pp.473-484
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• 2003

In this paper we deal with the logistics brokerage process in which a logistics agent intermediates between vehicle owners and shippers for matching empty vehicles and freights. Based on the Multi-Criteria Decision Making (MCDM) methodology, the proposed agent system matches the most preferred empty vehicle to the shipper and the most preferred freight to the vehicle owner. In the proposed agent system, an MCDM based sensitivity analysis is also used for supporting decision makers under negotiations. Among various MCDM methodologies, Analytic Hierarchy Process (AHP) is utilized in this paper. Although AHP is one of the most popular MCDM methodologies, AHP needs a number of pair-wise comparisons for assessing alternatives and hence may give excessive decision making burden to the decision makers. In this paper, in order to reduce the decision making burden, a preference function based estimation method is proposed. We can expect that the MCDM based logistics brokerage agent can be used as an efficient and effective tool for e-logistics marketplaces on the internet.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.4
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• pp.19-35
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• 2012

The Semantic Web technology, purporting to share, to reuse and to process by machines data stored in the Web environment, incessantly evolves to help human decision making; in particular, decision making based on data, or quantitative decision making. This trend drives researchers to fill the gap with strenuous efforts between the current state of the technology and the terminus of this evolution. The Semantic Web Constraint Language (SWCL) together with SWRL is one of these endeavors to achieve the goal. This paper focuses particularly on how to express the piecewise linear form in the context of SWCL. The importance of this ingredient can be fortified by the fact that any nonlinear expression can be approximated in the piecewise linear form. This paper will also provide the information of how it will work in the decision making process through an example of the Internet shopping mall problem.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.6
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• pp.89-96
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• 2001

This paper presents a decision making technique of reasonable $O_2$quantity needed to resolve organic matter via microbe in wastewater treatment. Decision making system of inferring reasonable $O_2$quantity consists of three parts. The first part is to compute reasonable $O_2$quantity with given process data. The second part is to find output features of processed wastewater using process model when $O_2$quantity is changed to a value inferred from decision making system. The third part is to show the results of decision making system. In order to verify performance of proposed decision making system computer simulation was done with process data gathered during 40 days. Simulation result shows that $O_2$quantity can be reduced over 10% under the condition of satisfying the specifications for processed wastewater.

• Korean System Dynamics Review
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• v.9 no.1
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• pp.57-71
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• 2008

This research paper describes a complex and vague settings in which organization makes a decision and explains a role of decision maker's learning process. The original paper, written by Cohen, March, Olsen in 1972, said that all members of organization depended on the technology taken through trials and errors, which is the 'learning' process literally. But they intended to exclude the learning process in their simulation model because their PORTRAN model couldn't replicate the learning concept. As a result, they couldn't explain how all agents of garbage can simulation model resolve the problem dynamically. To overcome this original paper's limitations, we try to rebuild a learning process simulation model using by system dynamics approach that can capture the linkage between organization leanings and agents-based decision-makings. Our learning simulation results reveal two points. First, decision maker's leanings process improves the efficiency of decision making in complex situation. Second, group learning shows a superior efficiency to an individual learning because group members share organizational memory and energy.

• Asia pacific journal of information systems
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• v.11 no.3
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• pp.127-147
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• 2001

This paper presents an analysis of Korean middle managers' decision-making processes. The sample included the observations of decisions made by 17 groups with 5 to 7 members each. The 5 hour-long, in average, decision processes were analysed by a modified system of Fisher's(1970) Interaction Process Analysis. The results showed that Korean managers followed alternative-focused decision processes, as opposite to value-focused ones. That is, the decision-making groups showed a strong trend to elaborate on alternative generation and evaluation right after the situation analysis. They tended to discuss the objectives of decision and relevant criteria only to resolve conflicts arisen during the evaluation process of alternatives. The analysis also showed that a decision proposition was more frequently followed by negative responses than positive ones and by interpretative evaluations than substantiative ones. The lessons from this study suggest a direction for the development of group decision support systems tailored for Korean cultural characteristics. This study is also meaningful as the first observation and empirical analysis of Korean middle managers' decision-making processes.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1209-1214
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• 2006

This paper presents an application of Dividing Wall Column(DWC) to the recovery of the waste solvent from the film making processes. The waste solvent feed contains MEK(Methyl-Ethyl-Ketone), Toluene, Cyclohexanone, and water. The commercial software $HYSYS^{TM}$ was used for rigorous simulation and analysis. Sensitivity analysis for several major design variables were carried out to achieve the optimal design of the process. Distribution of the internal vapor and liquid flows to the prefractionator and main sections is shown to be the most dominant design factor for energy saving efficiency in the DWC process. The simulation results also show that the solvent recovery process using the DWC significantly improves both the energy efficiency and the compactness of the solvent recovery process.

• Journal of the Korean Institute of Rural Architecture
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• v.10 no.4
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• pp.49-56
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• 2008

Through a case study on The making of communities driven by citizen autonomy in Cheongju, The study is to figure out how it proceeded and how many were finished by project. These projects completed in 2007 and 2008 for "Campaign of making beautiful communities" were driven by people at community center in Cheongju city. This paper consisted of research on establishment and operation of community center, the developing process of "Campaign of making beautiful communities" and an analysis of each project. This study was based on the interviews of the official of Cheongju city for having ideas about establishment and operation of community center and the developing process of "Campaign of making beautiful communities" and also visits each center for investigating actual programs accomplished.

• Journal of the Korea Safety Management & Science
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• v.7 no.4
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• pp.165-177
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• 2005

Supply Chain Management(SCM) system is a critical investment that can affect future competitiveness and performance of a company. Selection of a right SCM system is one of the critical issues. This paper provides the characteristic factors of SCM system selection and the SCM system evaluation and selection model based on Analytic Hierarchy Process(AHP). The proposed model can systematically construct the objectives of SCM system selection to support the business goals. A empirical example demonstrates the feasibility of the proposed model and the model can help a company to make better decision-making in selecting SCM system.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.173-178
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• 2007

This paper is to establish an appropriate model for predicting the temperature decreases in the batch transferred from the refining process to the caster in steel-making companies. Mathematical modeling of the temperature decreases between the processes is difficult, since the reaction mechanism by which the temperature changes in a molten steel batch is dynamic, uncertain and complex. Three soft computing techniques are examined using the same data, namely the multiple regression, fuzzy regression, and neural net (NN) models. To compare the accuracy of these three models, a limited number of input variables are selected from those variables significantly affecting the temperature decrease. The results show that the difference in accuracy between the three models is not statistically significant. Nonetheless, the NN model is recommended because of its adaptive ability and robustness. The method presented in this paper allows the temperature decrease to be predicted without requiring any precise metallurgical knowledge.