• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.118-128
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• 2017

Uncertain factors in finical markets make the prediction of future returns and risk of asset much difficult. In this paper, a model,assuming the admissible errors on expected returns and risks of assets, assisted in the multiperiod mean variance portfolio selection problem is built. The model considers transaction costs, upper bound on borrowing risk-free asset constraints, cardinality constraints and threshold constraints. Cardinality constraints limit the number of assets to be held in an efficient portfolio. At the same time, threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Because of these limitations, the proposed model is a mix integer dynamic optimization problem with path dependence. The forward dynamic programming method is designed to obtain the optimal portfolio strategy. Finally, to evaluate the model, our result of a meaning example is compared to the terminal wealth under different constraints.

• Knowledge Management Research
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• v.13 no.3
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• pp.55-77
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• 2012

Selecting promising technology is becoming more and more difficult due to the increased number and complexity. In this study, we propose hybrid AHP/DEA-AR method and hybrid AHP/DEA-AR-G method to evaluate efficiency of technology alternatives based on ordinal rating data collected through survey to technology experts in a certain field and select efficient technology alternative as promising technology. The proposed method normalizes rating data and uses AHP to derive weights to improve the credibility of analysis, then in order to avoid basic DEA models' problems, use DEA-AR and DEA-AR-G to evaluate efficiency of technology alternatives. In this study, we applied the proposed methods to clean technology and compared with the basic DEA models. According to the result of the comparison, we can find that the both proposed methods are excellent in confirming most efficient technology, and hybrid AHP/DEA-AR method is much easier to use in the process of technology selection.

• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.53-68
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• 2017

The response sensitivity method in time domain has been applied extensively for damage identification. In this paper, the relationship between the error of damage identification and the sensitivity matrix is investigated through perturbation analysis. An index is defined according to the perturbation amplify effect and an optimal sensor placement method is proposed based on the minimization of that index. A sequential sub-optimal algorithm is presented which results in consistently good location selection. Numerical simulations with a two-dimensional high truss structure are conducted to validate the proposed method. Results reveal that the damage identification using the optimal sensor placement determined by the proposed method can identify multiple damages of the structure more accurately.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.94-98
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• 2009

In this paper, we propose a new channel estimation scheme for amplify and forward cooperative diversity with relay selection. In order to select best relay, it is necessary to know channel state information (CSI) at the destination. Most of the previous works, however, assume that perfect CSI is available at the destination. In addition, when the number of relay is increased it is difficult to estimate CSI through all relays within coherence time of a channel because of the large amount of frame overhead for channel estimation. In a proposed channel estimation scheme, each terminal has distinct pilot signal which is orthogonal each other. By using orthogonal property of pilot signals, CSI is estimated over two pilot signal transmission phases so that frame overhead is reduced significantly. Due to the orthogonal property among pilot signals, estimation error does not depend on the number of relays. Simulation result shows that the proposed channel estimation scheme provides accurate CSI at the destination.

• Journal of Gifted/Talented Education
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• v.11 no.2
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• pp.107-126
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• 2001

This study is focused on the selection program of mathematical gifted children on the middle school. To fulfill this purpose, I consider the testing program using cyber system. If we use the cyber system, we can survey mathematical play(for example, puzzle) and several mathematical activity of gifted children. Cyber system will be help as a subsidiary selection tool.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.209-216
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• 2014

Cognitive radio (CR) has been proposed to solve the spectrum utilization problem by dynamically exploiting the unused spectrum. In CR networks, a spectrum selection scheme is an important process to efficiently exploit the spectrum holes, and an efficient channel allocation scheme must be designed to minimize interference to the primary network as well as to achieve better spectrum utilization. In this paper, we propose a multichannel selection algorithm that uses spectrum hole prediction to limit the interference to the primary network and to exploit channel characteristics in order to enhance channel utilization. The proposed scheme considers both the interference length and the channel capacity to limit the interference to primary users and to enhance system performance. By using the proposed scheme, channel utilization is improved whereas the system limits the collision rate of the CR packets.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.191-194
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• 2002

In this paper, a new GA-based methodology with information granules is suggested for construction of the fuzzy classifier. We deal with the selection of the fuzzy region as well as two major classification problems-the feature selection and the pattern classification. The proposed method consists of three steps: the selection of the fuzzy region, the construction of the fuzzy sets, and the tuning of the fuzzy rules. The genetic algorithms (GAs) are applied to the development of the information granules so as to decide the satisfactory fuzzy regions. Finally, the GAs are also applied to the tuning procedure of the fuzzy rules in terms of the management of the misclassified data (e.g., data with the strange pattern or on the boundaries of the classes). To show the effectiveness of the proposed method, an example-the classification of the Iris data, is provided.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.280-284
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• 2008

In this paper, a best channel matrix selection scheme(BCMS) is proposed to approximate maximum likelihood(ML) detection for a multiple-input multiple-output system. For a one stage BCMS scheme, one of the transmitted symbols is selected to perform ML detection and the other symbols are detected by zero forcing(ZF). To increase the diversity of the symbols that are detected by ZF, multi-stage BCMS detection scheme is used to further improve the system performance. Simulation results show that the performance of the proposed BCMS scheme can approach that of ML detection with a significant reduction in complexity.

• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.22-37
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• 2004

An integrated heuristic approach based on genetic algorithms (GAs) is proposed for solving the container selection and loading problems. The GA for container selection solves a two-dimensional knapsack problem, determining a set of containers to minimize the transportation or shipment cost. The GA for container loading solves for the weighted coefficients in the evaluation functions that are applied in selecting loading positions and boxes to be loaded, so that the volume utilization is maximized. Several loading constraints such as box orientation, stack priority, stack stability, and container stability are also incorporated into the algorithm. In general, our computational results based on randomly generated data and problems from the literature suggest that the proposed heuristic provides a good solution in a reasonable amount of computational time.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.215-223
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• 2016

Design of personnel teams has been studied from diverse perspectives; the most common are the people and systems requirements perspectives. All these point of view are linked, which is the reason why it is necessary to study them simultaneously. Considering this gap, a decision making model is developed based on factors, models, and requirements mentioned in the literature. The model is applied to a real case. The findings indicate that the Personnel Behavior Based Lean model (PBBL) can be converted into a decision making model for the selection of team members. The study is focused not only on the individual candidates' knowledge, skills, and aptitudes, but also on how the model considers the company requirements, conflicts, and the importance of each person to the project.