• ETRI Journal
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• v.24 no.2
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• pp.161-171
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• 2002

This paper proposes a novel decision feedback differential phase detection (DF-DPD) for M-ary DPSK. A conventional differential phase detection method for M-ary Differential Phase Shift Keying (DPSK) can simplify the receiver architecture. However, it possesses a poorer bit error rate (BER) performance than coherent detection because of the prior noisy phase sample. Multiple-symbol differential detection methods, such as maximum likelihood differential phase detection, Viterbi-DPD, and DF-DPD using L-1 previous detected symbols, have attempted to improve BER performance. As the detection length, L, increases, the BER performance of the DF-DPD improves but the complexity of the architecture increases dramatically. This paper proposes a simplified DF-DPD architecture replacing the conventional delay and additional architecture with an accumulator. The proposed architecture also improves BER performance by minimizing the current differential phase noise through the accumulation of previous differential phase noise samples. The simulation results show that the BER performance of the proposed architecture approaches that of a coherent detection with differential decoding.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1350-1353
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• 1993

A fuzzy control system typically requires“tuning,”or adjuctment of the parameters defining its linguistic variables. Automating this process amounts to applying a second“metacontrol”layer to drive the controller and plant to desired performance levels. Current methods of automated tuning rely on a single crisp numeric functional to evaluate control system performance. A generalization of Box's complex algorithm allows more realistic tuning based on lexicographic aggregation of multiple ordinal scales of performance, such as effectiveness and efficiency. The method is presented and illustrated using a simple inverted pendulum control system.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05b
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• pp.237-243
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• 1997

The ultimate object of our study is to minimize the release of radioactive material into the environment and to maximize the treatable amount of the generated wastes. In planning the practical operation of the system, however, the operating cost, Process economics and technical flexibility must also be considered. For dealing with these multiple criteria decision making Problems, we used a foal programming which is a kind of multi-objective linear programming. This method requires the decision maker to set goals for each objective that one wishes to attain.

• Journal of the Korean Institute of Gas
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• v.20 no.3
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• pp.52-58
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• 2016

In this study, evaluation method for LNG plant FEED is suggested and its validity is confirmed using a well-known decision making technique of Analytic Hierarchy Process (AHP). It is a pairwise comparison technique which can be used when multiple options must be considered for a single decision making problem. In order to develop an objective decision methodology, various decision parameters, sub-parameters as well as the concept of scale of assessment were introduced, and its consistency among these parameters was also checked by calculating the consistency index (C.I.). The methodology suggested in this article will contribute in evaluation of LNG plant FEED with less bias and subjectivity associated with the decision making procedure.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.231-238
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• 2022

This study aims to investigate the effect of college students' major satisfaction on career decision-making self-efficacy and job confidence. The research method was used for analysis by surveying 335 two-year college students majoring in beauty in Seoul and Gyeonggi-do. The collected data were analyzed for frequency analysis, factor analysis, reliability analysis, and correlation between career decision-making self-efficacy and job confidence using SPSS 26.0, and multiple regression analysis was conducted to confirm the effect between each variable. As a result of the study, first, a statistically significant positive (+) correlation between college students' major satisfaction was confirmed between career decision-making self-efficacy and job confidence. Second, as the effect of major satisfaction on self-efficacy, statistically significant effects were confirmed in self-evaluation, problem-solving, and goal selection. Fifth, it was confirmed that major satisfaction had a statistically significant effect on job confidence. Fourth, it was confirmed that career decision-making self-efficacy had a statistically significant effect on job confidence.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.119-125
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• 2010

The most important part in the decision making is to decide the weight of attributes which indicate the relative importance of the properties to be estimated with different criteria respectively. In this study, the new MCDM method which consider typical preexisting methods all together is proposed. For doing those, Weighted Utopian Approach is newly suggested by combining typical 7 weighting methods and distance-based Utopian Approach which is one of the MCDM methods. The suggested method has the advantage of accomplishing representativeness and universality of the MCDM methods because it incorporates multiple weighting methods of diverse characteristics. It also yields not only the one final result but also the results calculated from each weighting method, broadening the options of the choice to the alternatives. The application of the new model to virtual engineering problems show that we can perform the decision making and the assessment of priority order more objectively with it and that it has high applicability to the practice, giving us simple calculation process.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.5
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• pp.171-180
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• 2003

CDMA(Code Division Multiple Access) mobile communication systems require accurate channel estimation in the receiver to compensate the fading distortions. Instantaneous channel estimates are obtained by dividing the received symbol by the transmitted symbol and then refined by filtering to reduce the estimation variance. In the channel estimation filter, the determination of the filter size is a very important task which greatly affects the estimation quality. While conventional methods usually use only velocity estimators to determine the channel estimation filter size, this paper proposes a filter size determination method for decision-directed channel estimators considering the symbol error rate and the signal-to-noise ratio in addition to the velocity of the mobile station. This paper shows that the symbol error rate and the signal-to-noise ratio are important factors for the determination of the channel estimation filter size.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.93-103
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• 2019

This study analyzed the impact of smartphone usage on walking speed during walking on two pedestrian walkways in Daejeon Metropolitan City. For the analysis, the video data about the actual use of smartphone was acquired and the walking speed was calculated based on the walking density of the pedestrian Level Of Service(LOS) presented in the Road Capacity Manual. Multiple regression analysis and decision tree using machine learning were used to analyze the impact of smartphone usage on walking speed, and as the explanatory variables, gender, disable smartphone, use of smartphone using auditory function, use of smartphone using visual function, LOS A, LOS B, LOS C were adopted. The result showed that LOS C had the highest impact on walking speed change and the women's group using their visual function was founded to have the slowest walking speed in LOS C. In particular, the author found that walking speed significantly decreased in the case of use of visual function rather than listening to music or the hearing on the phone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2376-2394
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• 2013

In order to ensure both of the whole system capacity and users QoS requirements in heterogeneous wireless networks, admission control mechanism should be well designed. In this paper, Multi-agent Q-learning based Admission Control Mechanism (MQACM) is proposed to handle new and handoff call access problems appropriately. MQACM obtains the optimal decision policy by using an improved form of single-agent Q-learning method, Multi-agent Q-learning (MQ) method. MQ method is creatively introduced to solve the admission control problem in heterogeneous wireless networks in this paper. In addition, different priorities are allocated to multiple services aiming to make MQACM perform even well in congested network scenarios. It can be observed from both analysis and simulation results that our proposed method not only outperforms existing schemes with enhanced call blocking probability and handoff dropping probability performance, but also has better network universality and stability than other schemes.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.203-210
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• 2014

This study proposes adaptive decision making method having feed-back structure of regression and simulation models to support the quick decision making of production managers by managing and integrating the mutual relationship among historical data. For that, from historical data that have extracted and accumulated from each process, we first selected major constraint resources that are used as independent variables in regression model. The regression model is designed by using the dependent variables (objectives) that defined above by managers and independent variables selected in previous step and simulation model that are composed of constraint resources is designed. In process of simulation run, we obtain the multiple feasible solutions (alternatives) by using meta-heuristic method. Each solution is substituted by regression equation and we found the optimal solution that is minimum of difference between values obtained by regression model and simulation results. The optimal solution is delivered and incorporated to production site and current operation results from production site is used to generate new regression model after that time.