• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10A
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• pp.1494-1500
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• 1999

In order to provide high speed multimedia data rate service, Multi-Code CDMA has been proposed which converts high speed serial data stream into N parallel low speed data streams with orthogonal PN codes for spreading. However this signal has multi level and causes interferences to be increased at the neighboring cell boundary in the reverse link. Therefore in order to solve the above mentioned problem, M/B-MC/CDMA, in which multi level signal is converted to binary level signal using M/B conversion, is proposed and the performance is compared with MC-CDMA.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.33-40
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• 2023

Machine-learning techniques are discovering effective performance on data analytics. Classification and regression are supported for prediction on different kinds of data. There are various breeds of classification techniques are using based on nature of data. Threshold determination is essential to making better model for unlabelled data. In this paper, threshold value applied as range, based on min-max normalization technique for creating labels and multiclass classification performed on rainfall data. Binary classification is applied on autism data and classification techniques applied on child abuse data. Performance of each technique analysed with the evaluation metrics.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.133-136
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• 2002

This paper presents a new method of Huffman decoding which gives a significant improvement of processing efficiency based on the reconstruction of an efficient one-dimensional array data structure incorporating the numeric interpretation of the accrued codewords in the binary tree. In the Proposed search method, the branching address is directly obtained by the arithematic operation with the incoming digit value eliminating the compare instruction needed in the binary tree search. The proposed search method gives 30% of improved Processing efficiency and the memory space of the reconstructed Huffman table is reduced to one third compared to the ordinary ‘compare and jump’ based binary tree. The experimental result with the six MPEG-2 AAC test files also shows about 198% of performance improvement compared to those of the widely used conventional sequential search method.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.1-16
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• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• Journal of the Korean Statistical Society
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• v.29 no.4
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• pp.407-422
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• 2000

This article is concerned with the selecting predictor variables to be included in building a class of binary response t-link regression models where both probit and logistic regression models can e approximately taken as members of the class. It is based on a modification of the stochastic search variable selection method(SSVS), intended to propose and develop a Bayesian procedure that used probabilistic considerations for selecting promising subsets of predictor variables. The procedure reformulates the binary response t-link regression setup in a hierarchical truncated normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. In this setup, the most promising subset of predictors can be identified as that with highest posterior probability in the marginal posterior distribution of the hyperparameters. To highlight the merit of the procedure, an illustrative numerical example is given.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.794-796
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• 2000

This paper analyzes the method of cascading 74LS163 4-Bit Binary Counters. The 74LS163 4-Bit Binary Counter has synchronous LD. CLR functions and especially ENT, ENP, RCO to cascade some chips in order to count more 4bit binary number. The maximum operating frequency may vary according to the method of cascading. The Data sheet from Texas Instruments introduces two methods, The Ripple Carry Mode Circuit and The Carry Look Ahead Circuit, and shows that The Carry Look Ahead Circuit is more efficient than the other. However, there are only little information for user to understand and apply this to other circuits. Thus, we not only analyzed the two methods but also compared with each other in the point of performance.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.65-72
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• 2011

A binary integration is one of sub-optimal pulse integration which decides detection based on discriminating m successful detections out of n trials in radar systems using multiple pulse repetition frequencies. This paper introduces target measurement error reduction technique to reduce azimuth errors in suboptimal binary integration radar which applies the near value by m rather than the optimal m and verifies the performance by analyzing the experimental data measured from real radar.

• International journal of advanced smart convergence
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• v.1 no.1
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• pp.27-33
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• 2012

In this paper, we analyze and simulate performance of space time block coded (STBC) binary pulse amplitude modulation-direct sequence (BPAM-DS) ultra-wideband (UWB) systems with double binary turbo code in indoor environments for various ubiquitous healthcare (u-healthcare) applications. Indoor wireless channel is modeled as a modified Saleh and Valenzuela (SV) model proposed as a UWB indoor channel model by the IEEE 802.15.SG3a in July 2003. In the STBC encoding process, an Alamouti algorithm for real-valued signals is employed because UWB signals have the type of real signal constellation. It is assumed that the transmitter has knowledge about channel state information. From simulation results, it is shown that the STBC scheme does not have an influence on improving bit error probability performance of the BPAM-DS UWB systems. It is also confirmed that the results of this paper can be applicable for u-healthcare applications.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.47-51
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• 2009

The low latency encoder for high data rate duo-binary turbo codes with tail biting trellises is considered. Encoder hardware architecture is proposed using inherent encoding property of duo-binary turbo codes. And we showed that half of execution time as well as the energy can be reduced with the proposed architecture.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.162-172
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• 1997

In this paper, we investigated the performance of a binary feedback switch algorithm for the ABR(Available Bit Rate) service in ATM networks. A binary feedback switch is also called EFCI(Explicit Forward Congestion Indication) switch and can be classificed into input cell processing(IP) scheme according to processing methods for the EFCI bit in data-cell header. We proposed two implementation methods for the binary feedback switch according to EFCI-bit processing schemes, and analyzed the ACR(Allowed Cell Rate) of source and the queue length of switch for each scheme in steady state. In addition, we derived the upper and lower bounds for maximum and minimum queue lengths, respectively, and investigated the impact of ABR parameters on the queue length.