• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.10A
• /
• pp.760-768
• /
• 2009

In this paper, we propose the energy efficient transmission parameter selection method for Wireless Personal Area Network (WPAN) system which is applied to e-Navigation system considering various ship models environment. An appropriate selection of transmission parameters of HR-WPAN system is very essential to be considered for saving WPAN devices' energy consumption, when HR-WPAN system is applied to ship area network (SAN). Therefore, we propose an energy consumption model for a ship area network employing IEEE 802.15.3 based CSMA/CA HR-WPAN model and analyze the effect of transmission parameter selection on the performance of energy consumption. In particular, the path loss is the major performance decision parameter for the SAN employing HR-WPAN system, since it varies according to the material of shipbuilding such as steel(for large ship), FRP(for medium size ship) and compound wood(for small ship). Thus, we analyze and demonstrate that the proper transmission parameter selection of transmit power, PHY data rate and fragment size for each ship model could guarantee energy efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2004.05b
• /
• pp.391-394
• /
• 2004

Change of paradigm of network attack technique was begun by fast extension of the latest Internet and new attack form is appearing. But, Most intrusion detection systems detect informed attack type because is doing based on misuse detection, and active correspondence is difficult in new attack. Therefore, to heighten detection rate for new attack pattern, visibilitys to apply human immunity mechanism are appearing. In this paper, we create self-file from normal behavior profile about network packet and embody self recognition algorithm to use self-nonself discrimination in the human immune system to detect anomaly behavior. Sense change because monitors self-file creating anomaly detector based on Negative Selection Algorithm that is self recognition algorithm's one and detects anomaly behavior. And we achieve simulation to use DARPA Network Dataset and verify effectiveness of algorithm through the anomaly detection rate.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.21 no.1
• /
• pp.46-53
• /
• 2001

The purpose of this paper is to develop a new feature selection method for AE signal classification. The neural network of back propagation algorithm is used. The proposed feature selection method uses the difference between feature coordinates in feature space. This method is compared with the existing methods such as Fisher's criterion, class mean scatter criterion and eigenvector analysis in terms of the recognition rate and the convergence speed, using the signals from the defects in welding zone of austenitic stainless steel and in the metal contact of the rotary compressor. The proposed feature selection methods such as 2-D and 3-D criteria showed better results in the recognition rate than the existing ones.

• ETRI Journal
• /
• v.32 no.1
• /
• pp.139-141
• /
• 2010

In this letter, closed-form approximations for outage probability and symbol error rate are presented for a selective decode-and-forward relay network with partial channel information. An independent but not identically distributed Rayleigh fading environment is considered. Numerical and simulated results demonstrate the validity of the analytical results.

• The Journal of the Korea Contents Association
• /
• v.20 no.4
• /
• pp.591-600
• /
• 2020

The decrease in the number of school-age population, the introduction of university evaluation and educational capacity enhancement projects have made the enrollment rate and employment rate important indicators. Accordingly, universities are making great efforts to improve the competitiveness of their universities by increasing students' major satisfaction. The purpose of this study is to find out whether art and music students major selection motivsion of affects major satisfaction for career preparation behavior. For this survey, students of arts and physical education at K University in Gyeonggi-do were surveyed and 197 questionnaires were used as analysis data. As a result of the study, it was found that major selection motivation had a significant static effect on career preparation behavior and major satisfaction, and major satisfaction was analyzed to have a complete mediating effect on the effect of major selection motivation on career preparation behavior. With on the results of this study, in the future, universities will need an efficient curriculum to enhance students' majors satisfaction. To that end, we should develop the theoretical and practical curriculum so that students can actively participate, operate programs such as operation of comparative subjects and on-demand education, and raise the level of education. To this end, the interest and active support of the industry-academia-research are required.

• The Korean Journal of Applied Statistics
• /
• v.31 no.1
• /
• pp.41-65
• /
• 2018

In Korea, as the mortality rate improves in a shorter period of time than in developed countries, it is important to consider the selection of the time series as well as the model selection in the mortality projection. Therefore, this study proposed a method using the multiple regression model in respect to the selection of the time series period. In addition, we investigate the problems that arise when various time series are used based on the Lee-Carter (LC) model, the kinds of LC model along with Lee-Miller (LM) and Booth-Maindonald-Smith (BMS), and the non-parametric model such as functional data model (FDM) and Coherent FDM, and examine differences in the age-specific mortality rate and life expectancy projection. Based on the analysis results, the age-specific mortality rate and predicted life expectancy of men and women are calculated for the year 2030 for each model. We also compare the mortality rate and life expectancy of the next generation provided by Korean Statistical Information Service (KOSIS).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.4C
• /
• pp.321-329
• /
• 2008

H.264/AVC video coding standard enables a considerably higher improvement in coding efficiency compared with previous standards such as MPEG-2, H.263 and MPEG-4. To achieve this, for each macro-block in H.264/AVC, Rate-Distortion Optimization (RDO) technique is employed to select the best motion vector, reference frame, and macro-block mode. As a result, computational complexity is increased significantly whereas RDO achieve higher improvement. This paper presents fast intra mode selection algorithm based on constraints of frequency characteristics which are derived from intra coding modes of H.264/AVC. First of all, we observe the features of each intra mode through the frequency analysis of image. And then proposed Frequency Error Costs (FECs) are calculated to select the best mode which has minimum cost. Computational complexity is considerably reduced because rate-distortion costs only calculate the candidate modes which are set of best mode and its neighbouring two modes. Experimental results show that proposed algorithm reduces the complexity dramatically maintaining the rate-distortion performance compared with H.264/AVC reference software.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.3
• /
• pp.773-782
• /
• 2007

The statistical process control charts are very extensively used for monitoring of process mean, deviation, defect rate or reject rate. In this paper we consider a control chart to monitor the process reject rate in the high yield process, which is based on the observed cumulative probability of the number of items inspected until r defective items are observed. We first propose selection of the optimal value of r in the CPC-r charts, and also consider the usefulness of the chart in high yield process such as semiconductor or TFT-LCD manufacturing process.

• Horticultural Science & Technology
• /
• v.35 no.2
• /
• pp.232-242
• /
• 2017

The goal of marker-assisted backcrossing (MAB) is to significantly reduce the number of breeding generations required by using genome-based molecular markers to select for a particular trait; however, MAB systems have only been developed for a few vegetable crops to date. Among the types of molecular markers, SNPs (single-nucleotide polymorphisms) are primarily used in the analysis of genetic diversity due to their abundance throughout most genomes. To develop a MAB system in Chinese cabbage, a high-throughput (HT) marker system was used, based on a previously developed set of 468 SNP probes (BraMAB1, Brassica Marker Assisted Backcrossing SNP 1). We selected a broad-spectrum TuMV (Turnip mosaic virus) resistance (trs) Chinese cabbage line (SB22) as a donor plant, constructing a $BC_1F_1$ population by crossing it with the TuMV-susceptible 12mo-682-1 elite line. Foreground selection was performed using the previously developed trsSCAR marker. Background selection was performed using 119 SNP markers that showed clear polymorphism between donor and recipient plants. The background genome recovery rate (% recurrent parent genome recovery; RPG) was good, with three of 75 $BC_1F_1$ plants showing a high RPG rate of over 80%. The background genotyping result and the phenotypic similarity between the recurrent parent and $BC_1F_1$ showed a correlation. The plant with the highest RPG recovery rate was backcrossed to construct the $BC_2F_1$ population. Foreground selection and background selection were performed using 169 $BC_2F_1$ plants. This study shows that, using MAB, we can recover over 90% of the background genome in only two generations, highlighting the MAB system using HT markers as a highly efficient Brassica rapa backcross breeding system. This is the first report of the application of a SNP marker set to the background selection of Chinese cabbage using HT SNP genotyping technology.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.37 no.1
• /
• pp.9-25
• /
• 2014

It is very important to select the best employees who are suitable for their jobs and duties as considering the efficiency and productivity of the firms' performance. As a result, many kinds of selection methodologies and systems have been developed. Among them is the selection system based on the core competencies which is known as the superior selection systems that can increase the predictive validity who is the right people, compared to the traditional selection system based on the job analysis. Hence, the former has been focused in the complex business situation in recent years. In this case study, we examine the selection system case based on the core competencies of OSS team in Company A, which is one of the largest telecommunication firms and we suggest the implications. According to the results of this case study, defining the core competencies of the job and selecting the right people who had the related competencies not only decreased the turnover rate of OSS team in Company A, but also increased the employees' loyalty and satisfaction for the organizations. This study will be a benchmark to other departments that don't use competency selection system of Company A as well as the firms that want to adapt the selection system based on the core competencies. Also, this case study has a contribution that shows us an alternative model how can the firms identify and select the best right employees.