• The KIPS Transactions:PartC
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• v.17C no.6
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• pp.471-484
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• 2010

In the wireless communication systems, the power consumption of a mobile device is very important issue due to its battery limitations. Hence most of the standards for wireless networks including a mobile WiMAX system are supporting their own power saving mode in way that a mobile device is able to reduce its energy usage while in the mode. However, those standards just define the arrangement of special time intervals, called a paging listening interval, during which the device needs to receive the paging-related control messages, and they do not specify how to effectively reduce the power in many different network environments. This means the amount of power spent by the device is very dependent on the implementations of individual device-vendors, and undesirable paging loss may happen according to the channel conditions. To reduce unnecessary power usage and the risk of paging loss, this paper proposes the effective frequency/BS selection algorithm applicable to a mobile device operating in the power saving mode, which serves the device with better BS based on the tracking for channel variation. This algorithm consists of the channel estimation phase during each paging listening interval, the tracking phase for the measured results, the frequency reselection phase based on the tracking activity, and the preferred BS reselection phase. Thus the proposed method can improve the paging performance while the device is moving in the network. Also the simulation result shows that the presented scheme is superior to other candidates in energy efficiency due to the channel-adaptive frequency/BS selection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.1013-1022
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• 2014

Correlation Power Analysis (CPA) is a type of Side-Channel Analysis (SCA) that extracts the secret key using the correlation coefficient both side-channel information leakage by cryptography device and intermediate value of algorithms. Attack performance of the CPA is affected by noise and temporal synchronization of power consumption leaked. In the recent years, various researches about the signal processing have been presented to improve the performance of power analysis. Among these signal processing techniques, compression techniques of the signal based on Principal Component Analysis (PCA) has been presented. Selection of the principal components is an important issue in signal compression based on PCA. Because selection of the principal component will affect the performance of the analysis. In this paper, we present a method of selecting the principal component by using the correlation of the principal components and the power consumption is high and a CPA technique based on the principal component that utilizes the feature that the principal component has different. Also, we prove the performance of our method by carrying out the experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1251-1259
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• 2007

A scheme for selecting the mode with the maximum system capacity is proposed for cooperative relaying. Three possible modes are presented based on decode-and-forward relaying, and the time required by each mode is evaluated. Based on these results, a method is then developed for selecting the optimal mode with the minimum time duration (or maximum channel capacity). Computer simulations confirm that the optimal mode outperforms the other modes.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.410-421
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• 2019

Distributed compressed sensing (DCS) states that we can recover the sparse signals from very few linear measurements. Various studies about DCS have been carried out recently. In many practical applications, there is no prior information except for standard sparsity on signals. The typical example is the sparse signals have block-sparse structures whose non-zero coefficients occurring in clusters, while the cluster pattern is usually unavailable as the prior information. To discuss this issue, a new algorithm, called backtracking-based adaptive orthogonal matching pursuit for block distributed compressed sensing (DCSBBAOMP), is proposed. In contrast to existing block methods which consider the single-channel signal reconstruction, the DCSBBAOMP resorts to the multi-channel signals reconstruction. Moreover, this algorithm is an iterative approach, which consists of forward selection and backward removal stages in each iteration. An advantage of this method is that perfect reconstruction performance can be achieved without prior information on the block-sparsity structure. Numerical experiments are provided to illustrate the desirable performance of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.199-203
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• 2016

A brain-computer interface or BCI provides an alternative method for acting on the world. Brain signals can be recorded from the electrical activity along the scalp using an electrode cap. By analyzing the EEG, it is possible to determine whether a person is thinking about his/her hand or foot movement and this information can be transferred to a machine and then translated into commands. However, we do not know which information relates to motor imagery and which channel is good for extracting features. A general approach is to use all electronic channels to analyze the EEG signals, but this causes many problems, such as overfitting and problems removing noisy and artificial signals. To overcome these problems, in this paper we used a new optimization method called the Fruit Fly optimization algorithm (FOA) to select the best channels and then combine them with CSP method to extract features to improve the classification accuracy by linear discriminant analysis. We also used particle swarm optimization (PSO) and a genetic algorithm (GA) to select the optimal EEG channel and compared the performance with that of the FOA algorithm. The results show that for some subjects, the FOA algorithm is a better method for selecting the optimal EEG channel in a short time.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.141-144
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• 2023

Recently, a joint channel estimation, channel quantization, feedback, and precoding system based on deep-neural network (DNN) was proposed. The corresponding system achieved a joint optimization based on deep learning such that it achieved a higher sum rate than the existing codebook-based precoding systems. However, this DNN-based procoding system is not directly applicable for the environments with many users such that a specific user selection can potentially increase the sum rate of the system. Thus, in this letter, we study an appropriate user selection method suitable for DNN-based precoding.

• Asia Marketing Journal
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• v.17 no.2
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• pp.97-125
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• 2015

In this study, we tried to evaluate the relative importance and find out the differences in consumer perceptions regarding service recovery strategies and the service provider in the distribution industry by using AHP (Analytic Hierarchy Process) analysis method. Therefore in this study, we tried to systematize various recovery strategies which were considered very important during service failure process in the distribution industry and analyze the relative importance for each recovery strategy. We set hierarchy composed of four items of monetary, action-oriented, psychological, and assured level as primary selection criteria and a total of 16 items(indemnity, refund, gift, gift certificate, prompt resolution, exchange, manager support, explanation, apology, empathy, acknowledge, kindness, assortment, after service, manage subcontractor, manage employee) as secondary selection criteria. We tried to take one step further from the service sector and study service recovery strategies specialized in distributor services. This study suggests various implications about service recovery strategies of distributors. First, this study can provide practical implications - e.g. service recovery efforts should be applied differently depending on service channels. There is a perceptual difference with respect to the importance of the types of service recovery strategies between service provider and final customer. Second, we can find theoretical implications in terms of identifying the priorities through hierarchy design of new recovery strategies and comparison of each element from the classifications of the current fractional recovery strategies. We hope to help service providers to build more efficient recovery strategy system based on the results of this study.

• Analytical Science and Technology
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• v.24 no.6
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• pp.533-543
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• 2011

The hERG (human ether-a-go-go related gene) ion channel is a main factor for cardiac repolarization, and the blockade of this channel could induce arrhythmia and sudden death. Therefore, potential hERG ion channel inhibitors are now a primary concern in the drug discovery process, and lots of efforts are focused on the minimizing the cardiotoxic side effect. In this study, $IC_{50}$ data of 202 organic compounds in HEK (human embryonic kidney) cell from literatures were used to develop predictive 2D-QSAR model. Multiple linear regression (MLR), Support Vector Machine (SVM), and artificial neural network (ANN) were utilized to predict inhibition concentration of hERG ion channel as machine learning methods. Population based-forward selection method with cross-validation procedure was combined with each learning method and used to select best subset descriptors for each learning algorithm. The best model was ANN model based on 14 descriptors ($R^2_{CV}$=0.617, RMSECV=0.762, MAECV=0.583) and the MLR model could describe the structural characteristics of inhibitors and interaction with hERG receptors. The validation of QSAR models was evaluated through the 5-fold cross-validation and Y-scrambling test.

• ETRI Journal
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• v.39 no.5
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• pp.683-694
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• 2017

Several studies have focused on multimedia transmission over wireless sensor networks (WSNs). In this paper, we propose a comprehensive and robust model to transmit images over cognitive radio WSNs (CRWSNs). We estimate the spectrum sensing frequency and evaluate its impact on the peak signal-to-noise ratio (PSNR). To enhance the PSNR, we attempt to maximize the number of pixels delivered to the receiver. To increase the probability of successful image transmission within the maximum allowed time, we minimize the average number of packets remaining in the send buffer. We use both single- and multi-channel transmissions by focusing on critical transmission events, namely hand-off (HO), No-HO, and timeout events. We deploy our advanced updating method, the dynamic parameter updating procedure, to guarantee the dynamic adaptation of model parameters to the events. In addition, we introduce our ranking method, named minimum remaining packet best channel selection, to enable us to rank and select the best channel to improve the system performance. Finally, we show the capability of our proposed image scrambling and filtering approach to achieve noticeable PSNR improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1513-1527
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• 2011

This paper investigates the capacity rate problems for a joint decode-and-forward (JDF) based two-way relaying with network coding. We first characterize the achievable rate region for a conventional three-node network scenario along with the calculation of the corresponding maximal sum-rate. Then, for the goal of maximizing the system sum-rate, opportunistic relay selection is examined for multi-relay networks. As a result, a novel strategy for the implementation of relay selection is proposed, which depends on the instantaneous channel state and allows a single best relay to help the two-way information exchange. The JDF scheme and the scheme using relay selection are analyzed in terms of outage probability, after which the corresponding exact expressions are developed over Rayleigh fading channels. For the purpose of comparison, outage probabilities of the amplify-and-forward (AF) scheme and those of the scheme using relay selection are also derived. Finally, simulation experiments are done and performance comparisons are conducted. The results verify that the proposed strategy is an appropriate method for the implementation of relay selection and can achieve significant performance gains in terms of outage probability regardless of the symmetry or asymmetry of the channels. Compared with the AF scheme and the scheme using relay selection, the conventional JDF scheme and that using relay selection perform well at low signal-to-noise ratios (SNRs).