• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.12
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• pp.103-110
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• 2005

The performance of maximum likelihood(ML) detection for the given channel is analyzed in spatially multiplexed MIMO system. In order to obtain the vector symbol error rate, we define error vectors which represent the geometrical relation between lattice points. The properties of error vectors are analyzed to show that all lattice points in infinite lattice almost surely have four nearest neighbors after random channel transformation. Using this information and minimum distance obtained by the modified sphere decoding algorithm, we formulate the analytical performance of vector symbol error over the given channel. To verify the result, we simulate ML performance over various random channel which are classified into three categories: unitary channel, dense channel, and sparse channel. From the simulation results, it is verified that the derived analytical result gives a good approximation about the performance of ML detector over the all random MIMO channels.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.1001-1008
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• 2019

A high-quality pseudorandom sequence generation is an important part of many cryptographic applications, including encryption protocols. Therefore, a pseudorandom number generator (PRNG) is an essential element for generating key sequences in a cryptosystem. A PRNG must effectively generate a large, high-quality random data stream. It is well known that the bitstreams output by the CA-based PRNG are more random than the bitstreams output by the LFSR-based PRNG. In this paper, we prove that the complemented CA derived from 90/150 maximum length cellular automata(MLCA) is a MLCA to design a PRNG that can generate more secure bitstreams and extend the key space in a secret key cryptosystem. Also we give a method for calculating the cell positions outputting a nonlinear sequence with maximum period in complemented MLCA derived from a 90/150 MLCA and a complement vector.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.15-21
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• 2019

The fourth industrial revolution is noted. It is a smarter factory. At present, research on CNC (Computerized Numeric Controller) is actively underway in the manufacturing field. Domestic CNC equipment, acoustic sensors, vibration sensors, etc. This study can improve efficiency through CNC. Collect various data such as X-axis, Y-axis, Z-axis force, moving speed. Data exploration of the characteristics of the collected data. You can use your data as Random Forest (RF), Extreme Gradient Boost (XGB), and Support Vector Machine (SVM). The result of this study is CNC equipment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.75-85
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• 2010

This paper presents a robust 3D model hashing based on object feature vector for 3D content authentication. The proposed 3D model hashing selects the feature objects with highest area in a 3D model with various objects and groups the distances of the normalized vertices in the feature objects. Then we permute groups in each objects by using a permutation key and generate the final binary hash through the binary process with the group coefficients and a random key. Therefore, the hash robustness can be improved by the group coefficient from the distance distribution of vertices in each object group and th hash uniqueness can be improved by the binary process with a permutation key and a random key. From experimental results, we verified that the proposed hashing has both the robustness against various mesh and geometric editing and the uniqueness.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1550-1556
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• 1997

In this paper, we apply the evolutionary algorithm to the combinatorial optimization problem. Evolutionary algorithm useful for the optimization of the large space problem. This paper propose a method for the reuse of wastes of light water in atomic reactor system. These wastes contain several reusable elements, and they should be carefully selected and blended to satisfy requirements as an input material to the heavy water atomic reactor system. This problem belongs to an NP-hard like the 0/1 knapsack problem. Two evolutionary strategies are used as approximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method which perform the feasible test and solution evaluation by using the vectored knowledge in problem domain. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.728-737
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• 2015

Stitching algorithm obtain a descriptor of the feature points extracted from multiple images, and create a single image through the matching process between the each of the feature points. In this paper, a feature extraction and matching techniques for the creation of a high-speed panorama using video input is proposed. Features from Accelerated Segment Test(FAST) is used for the feature extraction at high speed. A new feature point matching process, different from the conventional method is proposed. In the matching process, by tracking region containing the feature point through the Mean shift vector required for matching is obtained. Obtained vector is used to match the extracted feature points. In order to remove the outlier, the RANdom Sample Consensus(RANSAC) method is used. By obtaining a homography transformation matrix of the two input images, a single panoramic image is generated. Through experimental results, we show that the proposed algorithm improve of speed panoramic image generation compared to than the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1153-1158
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• 2018

Online customer evaluations and social media information among a variety of information sources are critical for businesses as it influences the customer's decision making. There are limitations on the time and money that the survey will ask to identify a variety of customers' needs and complaints. The customer review data at online shopping malls provide the ideal data sources for analyzing customer sentiment about their products. In this study, we collected product reviews data on the smartphone of Samsung and Apple from Amazon. We applied five classification algorithms which are used as representative sentiment analysis techniques in previous studies. The five algorithms are based on support vector machines, bagging, random forest, classification or regression tree and maximum entropy. In this study, we proposed entropy score which can comprehensively evaluate the performance of classification algorithm. As a result of evaluating five algorithms using an entropy score, the SVMs algorithm's entropy score was ranked highest.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.287-297
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• 1998

RPWM(Random Pulse Width Modulation) is a switching technique to spread the voltage and current harmonics on wide frequency area. Using randomly changed switching frequency of the inverter, the power spectrum of the electromagnetic acoustic noise can be spread into the wide-band area. And the wide-band noise is much more comfortable and less annoying than the narrow-band one. So RPWM have been attracting an interest as an excellent reduction method of acoustic noise on the inverter drive system. In this paper a new RPPWM(Random Position PWM) is proposed and implemented. Each of three pulses is located randomly in each switching intervals. Along with the randomization of PWM pulses, the space vector modulation is processed on the C167 microcontroller also. The experimental results show that the voltage and current harmonics were spread into wide band area and that the audible switching noise was reduced by proposed RPPWM method.

• Journal of Life Science
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• v.23 no.2
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• pp.290-298
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• 2013

The genus Mycobacterium includes crucial animal and human pathogens such as Mycobacterium tuberculosis, Mycobacterium leprae, and Mycobacterium bovis. Although it is important to understand the genetic basis for their virulence and persistence in host, genetic analysis in mycobacteria was hampered by a lack of sufficient genetic tools. Therefore, many functional vectors as molecular genetic tools have been designed for understanding mycobacterial biology, and the application of these tools to mycobacteria has accelerated the study of mechanisms involved in virulence and gene expression. To overcome the pre-existing problems in genetic manipulation of mycobacteria, this paper reports new vector systems as effective genetic tools in Mycobacterium smegmatis. Three vectors were developed; pKOTs is a suicide vector for mutagenesis containing a temperature-sensitive replication origin (TSRO) and the sacB gene encoding levansucrase as a counterselectable marker. pMV306lacZ is an integrative lacZ transcriptional fusion vector that can be inserted into chromosomal DNA by site-specific recombination. pTnMod-OKmTs is a minitransposon vector harboring the TSRO that can be used in random mutagenesis. It was demonstrated in this study that these vectors effectively worked in M. smegmatis. The vector systems reported here are expected to successfully applicable to future research of mycobacterial molecular genetics.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.529-535
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• 2000

In this paper, we propose a new method of designing the vector quantizer which is robustness to coding results and independent of statistical characteristics of an input image in wavelet transformed image coding processes. The most critical drawback of a conventional vector quantizer is the degradation of coding capability resulted from the discordance between quantizer objective image and statistical characteristics of training sequence which is for generating representing vector. In order to resolve the problem of conventional methods, we use independent random-variables and pseudo image to which image correlation and edge component were added, as a training sequence for generating representing vector. We have done a computer simulation in order to compare coding capability between a vector quantizer designed by the proposed method and one with the conventional method using real image as same as that is objective to coding of training sequence used in codebook generation. The results show the superiority of the proposed vector quantizer method at the aspect of coding capability compared to conventional one. They also clarify the problems of conventional methods.