• Journal of Communications and Networks
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• v.15 no.1
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• pp.45-53
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• 2013

Multi-hop cellular networks (MCNs), which reduce the transmit power, mitigate the inter-cell interference, and improve the system performance, have been widely studied nowadays. The relay selection scheme is a key technique that achieves these advantages, and inappropriate relay selection causes frequent relay switchings, which deteriorates the overall performance. In this study, we analyze the conditions for relay switching in MCNs and obtain the expressions for the relay switching rate and relay activation time. Two mobile-based relay selection schemes are proposed on the basis of this analysis. These schemes select the relay node with the longest relay activation time and minimal relay switching rate through mobility prediction of the mobile node requiring relay and available relay nodes. We compare the system performances via simulation and analyze the impact of various parameters on the system performance. The results show that the two proposed schemes can obtain a lower relay switching rate and longer relay activation time when there is no reduction in the system throughput as compared with the existing schemes.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.143-155
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• 2015

The purpose of this study is to examine the differences between major satisfaction, university life adjustment, self-esteem, career identity according to the time of department selection of students in the department of occupational therapy. Frequencies, descriptive statistics, chi-square test, ANOVA was conducted using IBM SPSS Statistics 22. The major satisfaction and career identity have statistically significant difference according to the time of department selection. As the time of department selection was earlier(in high school), major satisfaction and career identity turned out to be higher than other times(before application period or application period). Thus, in order to effective life guidance and career guidance for the students in the department of occupational therapy after admission, the carrer programs that convergent the characteristics of the department of occupational therapy are needed.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.151-166
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• 2018

This paper compares the four selections of performance used in the application of genetic algorithms (GAs) to automatically optimize multispectral pixel cluster for unsupervised classification from KOMPSAT-3 data, since the selection among three main types of operators including crossover and mutation is the driving force to determine the overall operations in the clustering GAs. Experimental results demonstrate that the tournament selection obtains a better performance than the other selections, especially for both the number of generation and the convergence rate. However, it is computationally more expensive than the elitism selection with the slowest convergence rate in the comparison, which has less probability of getting optimum cluster centers than the other selections. Both the ranked-based selection and the proportional roulette wheel selection show similar performance in the average Euclidean distance using the pixel clustering, even the ranked-based is computationally much more expensive than the proportional roulette. With respect to finding global optimum, the tournament selection has higher potential to reach the global optimum prior to the ranked-based selection which spends a lot of computational time in fitness smoothing. The tournament selection-based clustering GA is used to successfully classify the KOMPSAT-3 multispectral data achieving the sufficient the matic accuracy assessment (namely, the achieved Kappa coefficient value of 0.923).

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.569-574
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• 2002

As consumer's desire becomes various, agility of mold manufacturing is most important factor for competence of manufacturer. In common works to use commercial CAM system to generate tool path, some decision making process is required to produce optimal result of CAM systems, The paper proposes a methodology for computer-assisted tool selection procedures for various cutting type, such as rough, semi-rough and finish cuts. The system provides assist-tool-items for machining of design model part of injection meld die by analyzing sliced CAD model of die cavity and core. Also, the generating NC-code of the tool size is used to calculate machining time. The system is developed with commercial CAM using API. This module will be used for optimization of tool selection and planning process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.175-179
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• 1997

As consumer's desire becomes various, agility of mold manufacturing is most important factor for competence of manufacturer. In common works to use commercial CAM system to generate tool path, some decision making process is required to produce optimal result of CAM systems. We propose tool selection procedures to aid the decision making process. The system provides available tool size for machining of design model part of injection mold die by analyzing sliced CAD model of die cavity and core. Also, the tool size information is used to calculate machining time. The system is developed with commercial CAM using API. This module will be used for optimization of tool selection and planning process.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.651-662
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• 2017

We propose an alternative procedure to select penalty parameter in $L_1$ penalized robust regression. This procedure is based on marginalization of prior distribution over the penalty parameter. Thus, resulting objective function does not include the penalty parameter due to marginalizing it out. In addition, its estimating algorithm automatically chooses a penalty parameter using the previous estimate of regression coefficients. The proposed approach bypasses cross validation as well as saves computing time. Variable-wise penalization also performs best in prediction and variable selection perspectives. Numerical studies using simulation data demonstrate the performance of our proposals. The proposed methods are applied to Boston housing data. Through simulation study and real data application we demonstrate that our proposals are competitive to or much better than cross-validation in prediction, variable selection, and computing time perspectives.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.295-304
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• 2003

In this paper, we proposed a hardware-oriented Genetic Algorithm Processor(GAP) based on subpopulation architecture for high-performance convergence and reducing computation time. The proposed architecture was applied to enhancing population diversity for correspondence to premature convergence. In addition, the crossover operator selection and linear ranking subpop selection were newly employed for efficient exploration. As stochastic search space selection through linear ranking and suitable genetic operator selection with respect to the convergence state of each subpopulation was used, the elapsed time of searching optimal solution was shortened. In the experiments, the computation speed was increased by over $10\%$ compared to survival-based GA and Modified-tournament GA. Especially, increased by over $20\%$ in the multi-modal function. The proposed Subpop GA processor was implemented on FPGA device APEX EP20K600EBC652-3 of AGENT 2000 design kit.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1071-1088
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• 2017

For dual-hop multiple-input multiple-output (MIMO) decode-and-forward relaying systems, we propose a selective relaying scheme that uses orthogonal space-time block code (OSTBC) and transmit antenna selection with maximal-ratio combining (TAS/MRC) or vice versa at the first and second hops, respectively. The aim is to achieve an asymptotically identical performance to the dual-hop relaying system with only TAS/MRC, while requiring lower feedback overhead. In particular, we give the selection criteria based on the antenna configurations and the average channel powers for the first and second hops, assuming Rayleigh fading channels. Also, the numerical results are shown for the outage performance comparison between the dual-hop DF relaying systems with the proposed scheme, only TAS/MRC, and only OSTBC.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.49-58
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• 1997

In process planning for pocket machining, the selection of tool size, tool path, overlap distance, and the calculation of machining time are very important factors to obtain the optimal process planning result. Among those factors, the tool size is the most important one because the others depend on tool size. And also, it is not easy to determine the optimal tool size even though the shape of pocket is simple. Therefore, the optimal selection of tool size is the most essential task in process planning for machining a pocket. This paper presents a method for selecting optimal toos in pocket machining. The branch and bound method is applied to select the optimal tools which minimize the machining time by using the range of feasible tools and the breadth-first search.