• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.11-26
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• 1995

We have used various information technologies (IT) in group decision-making for increasing effectiveness and satisfaction of group decision-making process. Recently, a new form of IT so called Group Decision supprot System (GDSS) was introduced into group decision-making process. Previous experimental studies about effectiveness of GDSSS have been inconsistent and the results were mixed. There was no empirical studies about GDSS in Korea. In this study, we divide two groups-GDSS supported group and traditional face-to-face group and investigate impacts of GDSS on group decision-making processes and outcomes. An idea generation task for operational action plan development, implementing GEO's strategic vision, served as the decision-making context. Supported GDSS is GroupSystems V, which had been developed by Univ. of Arizona. It was translated by Korean. According to the results, Number of nonredundant ideas in GDSS group is two or three times more than Non-GDSS grop. GDSS group feel more equal status, have better interpersonal relationship, have more confidence on group decision than Non-GDSS group. But satisfaction of participants on decision-making process and outcome has not showed a significant difference between two groups. Because all of participants in GDSS group were novice to GDSS. With this results we suggest further studies on transforming western type GDSS to Korean decision-making culture. It will be cornerstone for development of GDSS in Korean desision-making culture. It will be cornerstone for devlopment of GDSS in Korean decsion making culture environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.4
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• pp.416-422
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• 2011

In this paper, we use hard decision method for cooperative spectrum sensing. Sensing performance adopting hard decision is lower than soft decision but system load is low and the process is relatively simple when the combining scheme is hard decision compared to soft decision. In order to improve sensing performance, we propose optimal hard decision method applying weight that is based on a probability of individual sensing. Unlike conventional hard decision, we try to improve sensing performance applying weight and show the performance of the proposed method from the simulation results and performance analysis. The signal of licensed user is OFDM signal and the wireless channel between a licensed user and CR systems is modeled as Gaussian channel.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.171-178
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• 2018

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.163-176
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• 2021

This study tries to examine the impact relationship between the organizational justice perceived by the employees and the information system quality on the decision quality through absorption capabilities in order to find the factors that influences the corporate decision making in the rapidly changing market environment. With regards to this, 239 copies of survey data were collected subjecting the employees of the SMEs, and the hypothesis of this study was verified using SPSS 22.0 and PLS 3.0. As the result of the study, the organizational justice and information system quality has individually shown a positive (+) effect on the absorption capability, and the absorption capability has shown positive (+) effect on the decision quality. Through this study, a theological foundation for the organizational justice and information system quality was prepared as a prerequisite for the absorption capacity, and this study targets to suggest a theological and practical implications which secures the competitiveness by increasing the decision quality of the SMEs through comprehensive analysis of the organizational justice and information system quality which motivates the human resource. Future study requires additional research regarding the information system quality and finds various studies on the performance part due to necesssary decision quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.12
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• pp.1797-1805
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• 1993

An algorithm for the threshold decision from the maximum mismatching correlation value in a direct-sequence spread-spectrum system is presented. This algorithm is named the TDMMC(Threshold Decision from the Maximum Mismatching Correlation value). The purpose of the algorithm is to set the decision threshold in the system which will provide large probability of signal detection. Using this algorithm, the proper setting of the threshold for various SNRs is possible. An additional block called the Threshold Block is used to improve the system performance. The result from the computer simmulation has shown that appling the TDMMC to the noncoherent DS/SS-CSK system can achieve performance improvement.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.4
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• pp.13-23
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• 2007

This paper focuses on providing a practical approach for decision making in Performance-Based Design (PBD). Satisfactory performance is defined by several performance objectives that place limits on direct (monetary) loss and on a tolerable probability of collapse. No specific limits are placed on conventional engineering parameters such as forces or deformations, although it is assumed that sound capacity design principles are followed in the design process. The proposed design procedure incorporates different performance objectives up front, before the structural system is created, and assists engineers in making informed decisions on the choice of an effective structural system and its stiffness (period), base shear strength, and other important global structural parameters. The tools needed to implement this design process are (1) hazard curves for a specific ground motion intensity measure, (2) mean loss curves for structural and nonstructural subsystems, (3) structural response curves that relate, for different structural systems, a ground motion intensity measure to the engineering demand parameter (e.g., interstory drift or floor acceleration) on which the subsystem loss depends, and (4) collapse fragility curves. Since the proposed procedure facilitates decision making in the conceptual design process, it is referred to as a Design Decision Support System, DDSS. Implementation of the DDSS is illustrated in an example to demonstrate its practicality.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.5
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• pp.526-538
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• 2007

Since air quality monitoring data sets are important base for developing of air quality management strategies including policy making and policy performance assessment, the environmental protection authorities need to organize and operate monitoring network properly. Air quality monitoring network of Busan, consisting of 18 stations, was allocated under unscientific and irrational principles. Thus the current state of air quality monitoring networks was reassessed the effect and appropriateness of monitoring objectives such as population protection and sources surveillance. In the process of the reassessment, a GIS-based decision support system was constructed and used to simulate air quality over complex terrain and to conduct optimization analysis for air quality monitoring network with multi-objective. The maximization of protection capability for population appears to be the most effective and principal objective among various objectives. The relocation of current monitoring stations through optimization analysis of multi-objective appears to be better than the network building for maximization of population protection capability. The decision support system developed in this study on the basis of GIS-based database appear to be useful for the environmental protection authorities to plan and manage air quality monitoring network over complex terrain.

• Journal of Sensor Science and Technology
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• v.11 no.4
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• pp.230-238
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• 2002

In this paper, we designed a fuzzy system using the wavelet coefficients to detection the PVCs effectively and to increase the accuracy of decision of the arrhythmia. In the proposed Fuzzy system, the QRS complex of ECG signal is divided into 6th level frequence bands by wavelet transform using Haar wavelet. The MIT/BIH database for the source of input signal is used in order to evaluate the performance of the proposed system. From the simulation results, the decision of membership functions for PVCs and heart rates by using Fuzzy rules, we detected the abnormal values effectively by application of leaned from neural network and we also found results in classification ratio of 95% the decision of arrhythmia.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.111-117
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• 2002

In most machining companies, operators decide the cutting condition, a pair of spindle speed (5) and table federate (F) by experience and subjective judgment. As cutting conditions are determined by operators' experience and ability, inconsistent cutting conditions are given in same operating conditions. The objective of this study is to develop the cutting condition decision system which utilizes shop data and predicts tool life by neural network and eventually leads to the optimal cutting condition. The production time per piece is considered for an optimization object. We will discuss the process of an optimal cutting condition decision by neural network. By this process, a series of shop data is stored. And neural network is constructed for prediction of tool life and the optimal cutting condition is recommended from a cutting condition decision system using the stored shop data. The results show that the developed system is rational in searching the optimal cutting conditions on job operations.