• 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.

• Journal of Satellite, Information and Communications
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• v.12 no.2
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• pp.38-41
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• 2017

Reception performance in land mobile satellite is decreased by obstacle. It is compensated with Diversity technique. In this paper, performances are analyzed with two type of method Equal Gain Combining(EGC) and Selcetive Combining(SC). To analyze, measured data using On-The-Move(OTM) terminal are used. In conclusion, SC method can increase performance. However, EGC method can improve perforamance only in rural region, but performance are decreased in urban region.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.195-201
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• 2006

In multicarrier code division multiple access(MC-CDMA), the total system bandwidth is divided into a number of sub-bands, where each subband may use direct-sequence(DS) spreading and each subband signal is transmitted using a subcarrier frequency. In this paper, the system performance analysis of MC-CDMA using to gain combining(EGC) and maximal ratio combining(MRC) method over frequency selective Nakagami-m fading channel is analyzed. In the proposed system, a data sequence is serial-to-parallel converted, and MC-CDMA is used on each of the parallel data streams. The data streams are spread at both the symbol fraction level and at the chip level by the transmitter. In this paper, the compare to analysis,two standard diversity combining techniques, EGC and MRC, The good performance of system using to MRC more than EGC

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.5
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• pp.44-51
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• 2015

The deployment of high capacity backhaul is required due to explosive growth in mobile data services. For rapid backhaul deployment, point to point microwave is a much easier and cheaper technology. The space diversity scheme is used in point to point microwave links. The purpose of space diversity is to overcome fading by combining signals from two separate receiver antennas. For signal combining algorithm, maximum power and minimum distortion methods were used and these algorithms were reported not to be good enough for robustness in selective fading. In this paper, a more practically efficient signal combining scheme from the main and diversity branch is proposed and evaluated in selective fading channel. The proposed algorithm has shown significant performance improvement in terms of signal spectrum.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.125-136
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• 2007

The study on query relaxation which provides approximate answers has received attention. In recent years, some arguments have been made that semantic relationships are useful to present the relationships among data values and calculating the semantic distance between two data values can be used as a quantitative measure to express relative distance. The aim of this article is a hierarchical metricized knowledge abstraction (HiMKA) with an emphasis on combining data abstraction hierarchy and distance measure among data values. We propose the operations and the query relaxation algorithm appropriate to the HiMKA. With various experiments and comparison with other method, we show that the HiMKA is very useful for the quantified approximate query answering and our result is to offer a new methodological framework for query relaxation.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.51-61
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• 2007

Ridge regression (RR), principal component regression (PCR) and partial least squares regression (PLS) are among popular regression methods for collinear data. While RR adds a small quantity called ridge constant to the diagonal of X'X to stabilize the matrix inversion and regression coefficients, PCR and PLS use latent variables derived from original variables to circumvent the collinearity problem. One problem of PCR and PLS is that they are very sensitive to overfitting. A new regression method is presented by combining RR and PCR and PLS, respectively, in a unified manner. It is intended to provide better predictive ability and improved stability for regression models. A real-world data from NIR spectroscopy is used to investigate the performance of the newly developed regression method.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.479-481
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• 2007

COMS will transmit its observed data, Sensor Data, through L-Band with linear polarization. To avoid link loss caused by polarization discrepancy between satellite and SOC DATS, the L-Band antenna at SOC DATS should be linearly polarized. However, SOC DATS is supposed to share single antenna with SOC TTC, so the antenna should be circularly polarized. To cope with about 3dB loss, SOC DATS is designed to receive Sensor Data through two orthogonal circular polarizations, RHCP (Right-Hand Circular Polarization) and LHCP (Left-Hand Circular Polarization). Eventually, SOC DATS can obtain 2.6dB of combining gain through diversity combiner in MODEM/BB. This paper presents the verification on the diversity combining of SOC DATS with test configuration and results in depth.

• Journal of Information Management
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• v.38 no.1
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• pp.1-19
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• 2007

This study investigates the effect of data fusion on the retrieval effectiveness by performing an experiment combining multiple representations of Web documents. The types of document representation combined in the study include content terms, links, anchor text, and URL. The experimental results showed that the data fusion technique combining document representation methods in Web environment did not bring any significant improvement in retrieval effectiveness.

• 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 KIISE:Software and Applications
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• v.36 no.4
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• pp.273-282
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• 2009

Missing data is one of the common problems in building analysis or prediction models using software project data. Missing imputation methods are known to be more effective missing data handling method than deleting methods in small software project data. While K nearest neighbor imputation is a proper missing imputation method in the software project data, it cannot use non-missing information of incomplete project instances. In this paper, we propose an approach to missing data imputation for numerical software project data by combining K nearest neighbor and maximum likelihood estimation; we also extend the average absolute error measure by normalization for accurate evaluation. Our approach overcomes the limitation of K nearest neighbor imputation and outperforms on our real data sets.