• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5631-5652
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• 2019

The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.4
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• pp.428-434
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• 1997

The effect of genetic diversity in sub-populations on breeding efficiency was examined with prospect of potential crossbreeding. Simulation study of selection was performed for 20 generations with 20 replications each, comparing average breeding values and inbreeding coefficients between the two breeding systemes; single population scheme and two population scheme. The different genetic levels were assumed to be caused by different gene frequencies. Phenotypes of two traits generated polygenic effect with additive 36 loci and residuals distributed normally were selected by selection index procedure. High genetic gain with less inbreeding was clearly recognized in the single population scheme, independently of difference in genetic level, economic weight and genetic correlation. Genetic correlation after selection in the single population scheme was lower than the two population scheme. When crossbreeding between the sub-population was taken into account, superiority of the two population scheme was suggested under those restrictions; difference in genetic level is moderate, selection criterion for the two traits is not far from even economic weight, and genetic correlation is positive with low to moderate value. The use of complementarity increased the possibility of the two population scheme.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.307-312
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• 2005

In this work, we study the performance of a serial concatenated scheme comprising a convolutional code (CC) and an orthogonal space-time block code (STBC) separated by an inter-leaver. Specifically, we derive performance bounds for this concatenated scheme, clearly quantify the impact of using a CC in conjunction with a STBC, and compare that to using a STBC code only. Furthermore, we examine the impact of performing antenna selection at the receiver on the diversity order and coding gain of the system. In performing antenna selection, we adopt a selection criterion that is based on maximizing the instantaneous signal-to­noise ratio (SNR) at the receiver. That is, we select a subset of the available receive antennas that maximizes the received SNR. Two channel models are considered in this study: Fast fading and quasi-static fading. For both cases, our analyses show that substantial coding gains can be achieved, which is confirmed through Monte-Carlo simulations. We demonstrate that the spatial diversity is maintained for all cases, whereas the coding gain deteriorates by no more than $10\;log_{10}$ (M / L) dB, all relative to the full complexity multiple-input multiple-output (MIMO) system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.163-172
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• 2012

In this study, It is assumed that customers are both usage unit of spare parts and stores of displaying and selling the goods that are installation unit of having the spare parts. The demand pattern through the effective order of spare parts and issue list in installation unit is investigated based on the assumption. Current ASL (Authorized Stockage List) selection of the army has been conducted in the way of using the analysis result of real usage experiences on spare parts used during the Korea War. For this study, ASL selection criteria and procedures based on army regulations and field manuals are specified. Since the traditional method does not presents the association analysis on spare parts used for the current equipment operating and does not have the clear criterion and analysis system about the ASL selection, in order to solve these problems, it was carried out that the association rule is employed for analyzing relationship between the effective order and issue list of the spare parts in point of the spare parts between usage unit and occurring month about purchase spare parts based on the star-schema table. Finally the new ASL selection way using the analysis result is proposed.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.49-61
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• 2017

This paper proposes an R&D project selection methodology for green technology centered on developing country-oriented technology commercialization. Eight selection criteria are derived from the R&BD logic model : technology needs of developing countries, effectiveness of green technology, technological potentials, domestic technological capability, commercialization feasibility, economic benefits, business feasibility, and spillover effects of developing countries. 21 qualitative and quantitative indicators are then defined for each criterion. The analytic hierarchy process is conducted to produce relative importance of evaluation indicators and to set final priority scores of R&D project candidates. The working of the proposed methodology is provided with the help of a case study example of Green Technology Center. The proposed methodology is expected to be effectively utilized for policy practices of R&D project selection in the field of green technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1955-1971
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• 2013

This paper studies relay selection and power allocation for amplify-and-forward (AF) based two-way relay networks (TWRN) with asymmetric traffic requirements (ATR). A joint relay selection and power allocation algorithm is proposed to decrease the outage probability of TWRN with ATR. In this algorithm, two sources exchange information with the help of the relay during two time slots. We first calculate the optimal power allocation parameters based on instantaneous channel state information (CSI), and then derive a tight lower bound of outage probability. Furthermore, we propose a simplified relay selection criterion, which can be easily calculated as harmonic mean of instantaneous channel gains, according to the outage probability expressions. Simulation results verified the theoretical analyses we presented. It is shown that the outage probability of our algorithm improves 3-4dB comparing with that of other existing algorithms, and the lower bound is tight comparing with actual value for the entire signal-to-noise ratio (SNR) region.

• Korean Journal of Organic Agriculture
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• v.22 no.4
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• pp.841-854
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• 2014

This study aimed to analyze the selection criteria and priority settings for solid culture medium used in hydroponic crop production in farm households. Expert brain storming was carried out to extract solid culture medium selection criteria for hydroponic farming. As a result, 3 criteria of economy (cost), productivity, and environment, and 9 factors were extracted. A questionnaire survey of hydroponic farm households was conducted in Gyeonggi, Gangwon, and Chooncheong provinces. AHP analysis of the hydroponic solid culture medium selection criteria identified productivity as the most important criterion, chosen by 58.7% of the respondents, followed by economy (28.4%) and environment (12.9%). The 9 factors were rated by the respondents in the following decreasing order of importance: 1, crop yield (28.3%); 2, pest occurrence (18.5%); 3, maintenance/management costs (12.0%); 4, convenience of maintenance/management (13.4%); 5, initial investment cost (11.6%); 6, material energy consumption (6.5%); 7, waste recyclability (4.0%); 8, waste disposal costs (3.4%); and 9 environmental emissions (1.81%). These results imply that hydroponic farm households consider cultivation-related quality factors more important than economic factors, such as price of culture medium or installation cost.

• The Journal of Information Systems
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• v.26 no.3
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.2
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• pp.97-104
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• 2005

Mass selection (MS) is an efficient selection method to directly improve highly heritable traits. In the present study, two cycles of MS for ear length were conducted on two sweet corn populations, BC2-l0 and $BC1-10{\times}Syn-II$ after introgression of exotic germplasm. The improved populations generated from these selections were evaluated in comparison with the base populations at two locations, to determine the genetic gains and performance of the improved populations. The two base populations showed varied average realized responses to MS. In BC2-l0 derived population, the realized responses were $9.1\%$ in BC2-l0 C1 and $1.2\%$ in BC2-l0 C2, whereas in$BC1-10{\times}Syn-II$ derived population, the realized responses were$ 5.6\%$ in $BC1-10{\times}Syn-II$ C1 and $2.9\%$ in $BC1-10{\times}Syn-II$ C2. All the improved populations showed longer ears than their respective base populations and the check varieties. Ear length, which was used as the selection criterion in this study, showed high broad-sense heritability in the BC2-l0 and $BC1-10{\times}Syn-II$ derived populations, while fresh ear yield revealed low heritability, indicating that selection for ear length in these populations would be more effective than direct selection for yield. Results of this study indicate that MS conducted on BC2­10 and $BC1-10{\times}Syn-II$ had significantly increased ear length and fresh ear yield in both populations. The improved populations obtained would serve as better germplasm sources and further selection in these populations could offer better responses.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.2
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• pp.123-146
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• 2005

This study aims to find consistent strategies for feature selection and feature weighting methods, which can improve the effectiveness and efficiency of kNN text classifier. Feature selection criteria and feature weighting methods are as important factor as classification algorithms to achieve good performance of text categorization systems. Most of the former studies chose conflicting strategies for feature selection criteria and weighting methods. In this study, the performance of several feature selection criteria are measured considering the storage space for inverted index records and the classification time. The classification experiments in this study are conducted to examine the performance of IDF as feature selection criteria and the performance of conventional feature selection criteria, e.g. mutual information, as feature weighting methods. The results of these experiments suggest that using those measures which prefer low-frequency features as feature selection criterion and also as feature weighting method. we can increase the classification speed up to three or five times without loosing classification accuracy.