• Current Optics and Photonics
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• v.1 no.4
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• pp.289-294
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• 2017

A high-performance time-division multiplexing (TDM) -based multiuser (MU) multiple-input multipleoutput (MIMO) system for efficient indoor visible-light communication (VLC) is presented. In this work, a MIMO technique based on RGB light-emitting diodes (LEDs) with selection combining (SC) is utilized for data transmission. That is, the proposed scheme employs RGB LEDs for parallel transmission of user data and transmits MU data in predefined slots of a time frame with a simple and efficient design, to schedule the transmission times for multiple users. Simulation results demonstrate that the proposed scheme offers an approximately 6 dB gain in signal-to-noise ratio (SNR) at a bit error rate (BER) of $3{\times}10^{-5}$, as compared to conventional MU single-input single-output (SISO) systems. Moreover, a data rate of 66.7 Mbps/user at a BER of $10^{-3}$ is achieved for 10 users in indoor VLC environments.

• Journal of electromagnetic engineering and science
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• v.11 no.4
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• pp.262-268
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• 2011

In this paper, we evaluate the outage performance of cooperative transmission in two-dimensional random networks. Firstly, we derive the joint distributions of the source-relay and the relay-destination links. Secondly, the outage probability for the decode-and-forward relaying system is derived when selection combining (SC) is employed at the destination. Finally, we calculate the average outage probability of the system and then attempt to express it by a simple approximate expression. The simulation results are presented to verify the accuracy of the derivations. Similar to deterministic networks, the cooperative transmission in random networks outperforms direct transmission at a high signal-to-noise ratio (SNR).

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.6 no.3
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• pp.75-79
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• 1995

This paper derives the symbol error rate (SER) for quadrature amplitude modulation (QAM) with L-fold selection combining (SC) space diversity in Rayleigh fading channel. No analysis has been reported yet for theoretical SER performance of QAM with SC space diversity in Rayleigh fading channels. The formula is obtained by averaging the symbol error probability of M-ary QAM in an additive white Gaussian noise channel over the distribution of the maximum signal-to-noise ratio among all of the diversity channels. By giving the order of diversity, L, and the number of signal points, M, we have been able to obtain the SER performance of QAM with general SC space diversity. Analytical results show that the probability of error decreases with the order of diversity. We can also see that the incremental diversity gain per additional diversity decreases as the number of branches becomes larger.

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.147-157
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• 2015

We consider a sparse high-dimensional linear regression model. Penalized methods using LASSO or non-convex penalties have been widely used for variable selection and estimation in high-dimensional regression models. In penalized regression, the selection and prediction performances depend on which penalty function is used. For example, it is known that LASSO has a good prediction performance but tends to select more variables than necessary. In this paper, we propose an additive sparse penalty for variable selection using a combination of LASSO and minimax concave penalties (MCP). The proposed penalty is designed for good properties of both LASSO and MCP.We develop an efficient algorithm to compute the proposed estimator by combining a concave convex procedure and coordinate descent algorithm. Numerical studies show that the proposed method has better selection and prediction performances compared to other penalized methods.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.9-16
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• 2015

In this paper, selection criterions on selection diversity are researched. The diversity is applied to the multiple antenna system based on wireless access in vehicular environment (WAVE) standard for rapid varying channel. Least squares (LS) based decision feedback equalizer (DFE) are used for channel equalization. Received signal is regenerated by means of the decision feedback path. In the selection diversity, the regenerated signal as well as the received signal is selected according to selection criterion. The decision feedback algorithm can follow the fast speed of WAVE fading channel. To control the tracking speed of the time-varying channel, simple low pass filter is used. Finally, the estimated channel value recovers the distorted payloads. Signal power before automatic gain control (AGC) in analog stage can be used as a selection criterion. In the digital stage, signal power after AGC, noise power after AGC, signal to noise ratio after AGC and cross-correlation method can be used as selection criterions. According to the simulation results, the performance of the selection diversity is improved in comparison with that of the combining diversity for the WAVE fading channel.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.471-483
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• 2012

One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".

• Journal of Communications and Networks
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• v.18 no.3
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• pp.288-298
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• 2016

Proactive relay selection in cognitive radio networks has recently received considerable attention. However, its outage probability analysis is limited to partially-identical fading distributions, uncorrelation among received signal-to-noise ratios (SNRs), and no direct channel. This paper completes this literature deficiency by generalizing the existing analysis for non-identical fading distributions, correlation among received SNRs, and with direct channel. Numerous results demonstrate that relay selection with a direct channel achieves a higher diversity order and superior performance than that without a direct channel at virtually no cost of power and bandwidth. Further, proactive relay selection suffers an error floor at either a large maximum transmit power or large maximum interference power; however, the error floor level can be significantly remedied with an increase in the number of relays.

• Journal of Embryo Transfer
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• v.28 no.2
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• pp.79-85
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• 2013

The recent development in genetic assisted selection (combining traditional- and genome assisted selection method) and reproduction technologies will allow multiplying elite cow in Hanwoo small farm. This review describes the new context and corresponding needs for genome assisted selection schemes and how reproductive technologies can be incorporated to get more genetic gain for cow genetic improvement in Hanwoo. New improved massive phenotypes and pedigree information are being generated from commercial farm sector and these are allowing to do genetic evaluation using BLUP to get elite cows in Korea. Moreover cattle genome information can now be incorporated into breeding program. In this context, this review will discuss about combining the reproductive techniques (Multiple Ovulation Embryo Transfer; MOET) and genome assisted selection method to get more genetic gain in Hanwoo breeding program. Finally, how these technologies can be used for multiplication of elite cow in small farm was discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3A
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• pp.198-204
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• 2011

Acoustic communication system is a transmission technology sending sound and data simultaneously. However, data signal can be audible in this system when data is transmitted with high transmission power. The more transmission power is reduced, the more distance that can transmit data is shortened. Therefore, the study that increase the transmission distance is needed. In this paper, we would like to increase transmission distance by adapting receive diversity in acoustic communication system. We measure received performance of both proposed system and Single Input Sing Output (SISO) system according to distance with same transmission power. When SISO satisfies Bit Error Rate (BER) of $7{\times}10^{-3}$ at about 2m, Selection Combining (SC) technique satisfies 2 meters, and Equal Gain Combining (EGC) technique satisfies 4 meters.