• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.578-585
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• 2011

Nowadays, wireless local area networks are widely deployed so that stations can potentially associate with an access point. The AP selection strategy is one of the significant research areas for wireless local area networks. The selection strategy solves the relevant problem is which AP can be selected and associated with a station so that the efficient resource utilization can be obtained. Rather than merely choosing the AP with the strongest received signal strength, however, we calculate effective throughput for each neighboring AP and use it as a basis for AP selection. Referencing the throughput is better than referencing the signal strength only because the network may contain a severe load imbalance. We have performed computer simulations using OPNET modeler in order to verify the performance of the proposed scheme. The results show us that the proposed selection method outperforms that of the conventional one in terms of throughput and delay.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.1092-1098
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• 2002

This paper discusses the composition of the theory of reinforcement teaming, which is applied in real-time teaming, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line teaming method. The individuals are reduced in order to team the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It is possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because of the teaming process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.4
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• pp.255-261
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• 2016

Korean Power System are operating a load shedding system to prevent voltage instability phenomenon caused by severe line contingencies. In order to apply the load shedding scheme should be selected a location, amount, delay time. Current load shedding system is load shedding amount that has been calculated in the steady-state analysis to load shed the total amount in first level, load shedding amount calculated in advance, it is possible to perform an unnecessary load shedding. In this paper, set a multi-level load shedding control strategy step-by-step selection of load shedding amount for the prevention of excessive load shedding. In addition, through a voltage resilience analysis of the power system by applying motor load ratio and sensitivity parameter to selection the multi level load shedding ratio and delay time. For this reason, to take advantage of the limit data of interchange power, by utilizing interface power flow data to set a multi-level load shedding control strategy for the stabilization of the Korean Power System.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.3849-3855
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• 2011

This study presents an efficient strategy for selecting portfolio by evaluating growth potential of a corporation based on dividend. Through preliminary experiments, we extract 4 categories to sort out prospective stocks and develop a scoring table including criteria and formulas used to calculate scores for each category. In order to show the effectiveness of the portfolio selected by scoring table, we constructed 3 portfolios for every 4 years (2007-2010) out of 927 listed companies in KRX and proved that our portfolios are superior to market portfolio in terms of rate of return.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.501-509
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• 2011

In this paper, we offer a new strategic Portfolio Model for national IT R&D project selection in Korea. A risk and return (R-R) Portfolio Model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R Portfolio Model to solve the non-strategy and subjectivity problems of the existing national R&D project selection Model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technology level Survey (TLS) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic Portfolio project and balancing the allocation of resources effectively and objectively.

• Journal of Korea Foundry Society
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• v.26 no.1
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• pp.27-33
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• 2006

Phase evolutions involving nucleation stages together with diffusional growth have been examined in order to provide a guideline for determining rate limiting stages during phase evolutions. In multiphase materials systems in coatings, composites or multilayered structures, diffusion treatments often result in the development of metastable/intermediate phases at the reaction interfaces. The development of metastable phases during solid state interdiffusion demonstrates that the nucleation reaction can be one controlling factor. Also, the concentration gradient and the relative magnitudes of the component diffusivities provide a basis for a phase selection and the application of a kinetic bias strategy in the phase selection. For multicomponent alloy systems, the identification of the operative diffusion pathway is central to control phase formation. Experimental access to the nucleation and growth stage is discussed in thin film multi layers and bulk samples.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.35-42
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• 2017

Information strategy planning(ISP) is an analysis of the organization's work, information flow, and current information systems, and planning information structures to achieve organizational strategies and objectives. In addition to the systematic promotion of the information sector in the public sector, the government is required to establish an information strategy plan in order to enhance the efficiency of the information sector. However, there are many cases in which the IT project budget is reflected without establishing the information strategy planning. The purpose of this study is to clarify the criteria for establishing the information strategy planning in order to enhance the effectiveness of the information strategy planning. For this purpose, we set up a judgment model for Information strategy planning through expert group review (FGI) and conducted questionnaires on public sector experts. In addition, we proposed a project to establish an information strategy planning and an exceptional project based on the size of iinformatization project and characteristics of informatization project.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.2
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• pp.138-145
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• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• Journal of Korean Home Economics Education Association
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• v.2 no.1
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• pp.123-142
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• 1990

The aim of this study is to apply lesson design of high school home economics to model which consists of six steps of instructional procedure among various models for instructional design, Through thesis, central content of each step was written as follows; 1) At the step of establishment of terminal instructional objectives, educational objectives, terminal instructional objectives was analyzed and specific instructional objectives was extracted. 3) At the step of diagnosis of entering behavior, ability of prior learning and ability of preliminary learning were evaluated, which was used as establishing instructional strategy and doing individual guidance. 4)At the step of determining instructional strategy, instructional strategy should be extracted by considering instructional event which is adequate to content of instruction. Instructional strategy consists of five main factor, factors, those are, activity of introduction of instruction, presentation of content of instruction and information, participation of learner and learning activity, identification of learning result, and subsequent treatment after evaluation. 5)Specific activity at the step of selection and development of instructional media consists of reidentification of instructional objectives determination of learning type, drawing up instructional media analysis sheet, synthesis of selected media, and explanatory note of selected media. In order to increase efficiency of instruction at the step of determining instructional strategy, this step should be considered simultaneously. 6)The step of try-out and evaluation of instructional design should be efficient when designed instruction was inputted at class after evaluation of each step of instructional design.