• Journal of Communications and Networks
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• v.18 no.3
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• pp.320-326
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• 2016

In existing literature on multiple-input multiple-output (MIMO) relaying communication systems, antenna selection is often implemented by maximizing the channel capacity or the output single-to-noise ratio (SNR). In this paper, we propose an energy-efficient low-complexity antenna selection scheme for MIMO relaying communication systems. The proposed algorithm is based on beamforming and maximizing the Frobenius norm to jointly optimize the transmit power, number of active antennas, and antenna subsets at the source, relaying and destination. We maximize the energy efficiency between the link of source to relay and the link of relay to destination to obtain the maximum energy efficiency of the system, subject to the SNR constraint. Compared to existing antenna selection methods forMIMO relaying communication systems, simulation results demonstrate that the proposed method can save more power in term of energy efficiency, while having lower computational complexity.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.1-14
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• 2020

Antenna selection is a method to enhance the performance of spatial multiplexing multiple-input multiple-output (MIMO) systems, which can achieve the diversity order of the full MIMO systems. Although various selection criteria have been studied in the literature, they should be adjusted to the detection operation implemented at the receiver. In this paper, antenna selection methods that optimize the post-processing signal-to-noise ratio (SNR) and eigenvalue are considered for the lattice reduction (LR)-based receiver. To develop a complexity-efficient antenna selection algorithm, the incremental selection strategy is adopted. Moreover, for improvement of performance, an additional iterative selection method is presented in combination with an incremental strategy.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.565-569
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• 1993

In this paper, a specified number of actuators are selected from a given set of admissible actuators. The selected set of actuators is likely to use minimum control energy while required output variance constraints are guaranteed to be satisfied. The actuator selection procedure is an iterative algorithm composed of two parts; an output variance constrained control and an input variance constrained control algorithm. The idea behind this algorithm is that the solution to the first control problem provides the necessary weighting matrix in the objective function of the second optimization problem, and the sensitivity information from the second problem is utilized to delete one actuator. For variance constrained control problems, by considering a dual version of each control problem an efficient algorithm is provided, whose convergence properties turn out to be better than an existing algorithm. Numerical examples with a simple beam are given for both the input/output variance constrained control problem and the actuator selection problem.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.795-801
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• 2013

Recently, support vector machine has been widely used in various application fields due to its superiority of classification performance comparing with decision tree and neural network. Since support vector machine is basically designed for the binary classification problem, output coding method to analyze the classification result of multiclass binary classifier is used for the application of support vector machine into the multiclass problem. However, previous feature selection method for output coding based support vector machine found the features to improve the overall classification accuracy instead of improving each classification accuracy of each classifier. In this paper, we propose the novel feature selection method to find the features for maximizing the classification accuracy of each binary classifier in output coding based support vector machine. Experimental result showed that proposed method significantly improved the classification accuracy comparing with previous feature selection method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6A
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• pp.494-499
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• 2009

In this paper, we provide an efficient method of user selection for achieving the maximum system throughput in downlink multiuser Multiple-Input Multiple-Output (MIMO) systems. A proposed method is for selecting a fine user set only with powers of each user channel and angles between them. This algorithm is simpler than SUS because there is no considering about the optimal value of correlation. The proposed method finds the user set toward maximizing system throughput, so it has high performance.

• IE interfaces
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• v.22 no.1
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• pp.44-55
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• 2009

We propose a method for selection of input-output factors in DEA. It is designed to select better combinations of input-output factors that are well suited for evaluating substantial performance of DMUs. Several selected DEA models with different input-output factors combinations are evaluated, and the relationship between the computed efficiency scores and a single performance criterion of DMUs is investigated using decision tree. Based on the results of decision tree analysis, a relatively better DEA model can be chosen, which is expected to well represent the true performance of DMUs. We illustrate the effectiveness of the proposed method by applying it to the efficiency evaluation of 101 listed companies in steel and metal industry.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.265-266
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• 2015

A multiple output dc-dc resonant converter topology for an independent voltage control technique is proposed, using a narrow frequency selection band-pass filters. The multi-output converter is supplied by a single source inverter with the superposed sinusoidal signals reserved for each output. A series-series parallel resonant topology is utilized to implement the narrow frequency selection channels for minimum interference. Finally the experimental setup for four output dc-dc converter is verified with the narrow channel frequencies of 26 kHz, 32 kHz, 38 kHz and 46 kHz.

• Journal of Korea Technology Innovation Society
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• v.1 no.1
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• pp.117-124
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• 1998

Corporations are pursuing maximum returns from their R&D investment. They are also interested in sound measures to quantify returns. In fact, they use various measures and criteria for measuring returns from the R&D investment. But the fundamental problem is that there is no generic and widely acceptable measures and criteria. To make things more complicated, measures are very powerful and influential to the people in the corporations. Herbert Simon already indicated that people do many things but people usually do their best for the only tasks which are measured. Many researchers, like Chester(1995), are interested in R&D productivity measures and risks because what the company measures really influence R&D people and output. This article present design concepts of the R&D project selection and evaluation system in POSCO(Pohang Iron & Steel Company). This is an output extract from the 6-month joint activities with POSRI(POSCO Research Institute) researchers and POSCO R&D personnel. Process changes, new organizations and new selection and evaluation criteria are developed to improve R&D performance and to enhance technology management of the POSCO. This article covers new selection and evaluation criteria only. We would like to share our experience about how we redesign the selection and evaluation of R&D projects. We also bring insights how we seamlessly integrate 4 different project selection and evaluation steps as a whole. We hope that this case will give you a clue to improve your R&D management.

• ETRI Journal
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• v.41 no.5
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• pp.637-647
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• 2019

Separating highly correlated users can reduce the loss caused by spatial correlation (SC) in multiuser multiple-input multiple-output (MU-MIMO) systems. However, few accurate analyses of the loss caused by SC have been conducted. In this study, we define signal-to-interference-plus-noise ratio (SINR) loss to characterize it in multiuser multiple-input single-output (MU-MISO) systems, and use coefficient of correlation (CoC) to describe the SC between users. A formula is deduced to show the accurate relation between SINR loss and CoC. Based on this relation, we propose a user selection method that utilizes CoC to minimize the average SINR loss of users in massive MU-MISO systems. Simulation results verify the correctness of the relation and show that the proposed user selection method is very effective at reducing the loss caused by SC in massive MU-MISO systems.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.349-352
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• 2003

A personal low-frequency stimulator is a portable device to relax muscle pains of a person. The stimulator generates combined low-frequency pulses to be applied to pads attached to painful muscles. This paper reports a development of such device with its characteristic analyses. The major components of our stimulator are MCU, high-voltage generating circuit part, high-voltage switching circuit part, input switch part and display unit. High-voltage generating circuit is designed by using a boost converter circuit and allows user control of the output voltage. High-voltage switching circuit, controlled by MCU, generates output voltage to be applied to pads. Input switch part is composed of power supply, intensity selection, mode selection and memory. Display unit adopts a text LCD module to display modes, Intensity, output frequency and user set-up time. Our designed safety circuit, to protect human body from possible electric shock, slowly increases the output voltage to the selected output intensity. It continuously checks the output pulse shape and disable the output when dangerous pulses are detected. This paper also shows some experimental results.