• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.9
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• pp.403-407
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• 2005

Most of the loads in industrial power distribution systems are balanced and connected to three power systems. However, voltage unbalance is generated at the user's 3-phase 4-wire distribution systems with single & three phase. Voltage unbalance is mainly affected by load system rather than power system. Unbalanced voltage will draws a highly unbalanced current and results in the temperature rise and the low output characteristics at the machine. It is necessary to analyse correct voltage unbalance factor for reduction of side effects in the industrial sites. Voltage unbalance is usually defined by the maximum percent deviation of voltages from their average value, by the method of symmetric components or by the expression in a more user-friendly form which requires only the three line voltage readings. If the neutral point is moved by the unbalanced load at the 3-phase 4-wire system. Line and phase voltage unbalance leads to different results due to zero-sequence component. So that it is difficult to analyse voltage unbalance factor by the conventional analytical method, This paper presents a new analytical method for phase and line voltage unbalance factor in 4-wire systems. Two methods indicate exact results.

• Journal of the Korean Institute of Navigation
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• v.20 no.2
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• pp.51-58
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• 1996

For the smooth flow of traffic vehicles and its effective management, it is necessary to have an exact information on traffic condition, i.e., the volume of traffic, velocity, occupancy and classification of vehicles. In particular, for classification of vehicles, there has been only image processing method using camera, where the method can obtain much information but rather expensive. In this paper, an algorithm for the measurement of velocity and total length of vehicles has been proposed to develop a general traffic management system, which is necessary to discriminate the class of vehicles. In order to realize the proposed algorithm, we have developed an ultrasonic spatial filtering method, which has better performance than that of using the traditional vehicle detector. To have this system to be constructed, we have introduced three sets of ultrasonic devices where each has one transmitter and two receivers which are arranged to obtain the spatial difference of objects. The velocity of vehicles can be measured by analyzing the occurrence time of pulses and their time differences. The total length of vehicles can be given by multiplying velocity with time interval of pulses sequence. To confirm the effectiveness of this measuring system, the experiment by the spatial filtering method using the ultrasonic sensors has been carried out. As the results, it is found that the proposed method can be used as one of measurement tools in the general traffic management system.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.84-92
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• 2018

For large wireless sensor networks running on battery power, the time synchronization of all sensor nodes is becoming a crucial task for waking up sensor nodes with exact timing and controlling transmission and reception timing. However, as network size increases, this synchronization process tends to require long processing time consume significant power. Furthermore, a naïve synchronization scheduler may leave some nodes unsynchronized. This paper proposes a power-efficient scheduling algorithm for time synchronization utilizing the notion of density, which is defined by the number of neighboring nodes within wireless range. The proposed scheduling algorithm elects a sequence of minimal reference nodes that can complete the synchronization with the smallest possible number of hops and lowest possible power consumption. Additionally, it ensures coverage of all sensor nodes utilizing a two-pass synchronization scheduling process. We implemented the proposed synchronization algorithm in a network simulator. Extensive simulation results demonstrate that the proposed algorithm can reduce the power consumption required for the periodic synchronization process by up to 40% for large sensor networks compared to a simplistic multi-hop synchronization method.

• Korean Institute of Interior Design Journal
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• v.15 no.1 s.54
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• pp.47-54
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• 2006

Stages, in the theatrical spaces, were space, which incorporates aspects of cities. Hence, the stages have been constituted to materialize sequence of city, which has exact number, proportion and order of ideal city. In addition, it has accomplished change, which depends on type of performance with the social condition and culture of generation, city has. However, the original form of theatrical space were forgotten on account of the various changes of theatrical form with modem movement since the end of 19th century, and theatrical space, which does not relate with its space of city, was started to constitute. Particularly in contemporary society, the theatre can give vitality to the citizens, and also theatrical architecture as a commercial code has been a general form, though it takes important role, which improves cultural value with technical improvement of cities development of society. Thus, this study analyzed urbanity ,which theatres have incorporated historically, and deduced a correlativity from to be based on constitution of space in visual, perceptual, spatial constitution and functional role. Focused on published SPAC international competition, it was interpreted by contemporary focus, therefore, this experiment suggests constitution of theatrical spaces of information, takes urbanity, through to analyze visual, perceptual, spatial constitution and functional role in context of contemporary city.

• Molecular & Cellular Toxicology
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• v.2 no.1
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• pp.60-66
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• 2006

Methylmercury (MeHg), one of the heavy metal compounds, can cause severe damage to the central nervous system in humans. Many reports have shown that MeHg is poisonous to human body through contaminated foods and has released into the environment. Despite many studies on the pathogenesis of MeHg-induced central neuropathy, no useful mechanism of toxicity has been established so far. This study, using of suppression subtractive hybridization (SSH) method, was peformed to identify differentially expressed genes by MeHg in SH-SY5Y human neuroblastoma cell line. We prepared to total RNA from SH-SY5Y cells treated with solvent (DMSO) and $6.25\;{\mu}M\;(IC_{50})$ MeHg and performed forward and reverse SSH. Differentially expressed cDNA clones were screened by dot blot, sequenced and confirmed that individual clones indeed represent differentially expressed genes with real time RT-PCR. These sequences were identified by BLAST homology search to known genes or expressed sequence tags (ESTs). Analysis of these sequences may provide an insight into the biological effects of MeHg in the pathogenesis of neurodegenerative disease and a possibility to develop more efficient and exact monitoring system of heavy metals as ubiquitous environmental pollutants.

• Journal of Life Science
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• v.17 no.5 s.85
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• pp.714-718
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• 2007

The high-throughput sequencing of a lot of genomes has resulted in the relatively rapid accumulation of an enormous amount of genomic sequence data. In this context, the problem posed by the detection of promoters in genomic DNA sequences via computational methods has attracted considerable attention in recent years since exact promoter prediction can give a clue to the elucidation of overall genetic networks. In this study, applications of support vector machine(SVM) to promoter prediction are explored to show a right approaches to discriminate between promoter and non-promoter regions by means of SVM. The results of various experiments show that encoding method, encoding region and learning data constitution can play an important role in the performance of SVM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2028-2041
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• 2019

Compressed sensing (CS) is a new theory. With regard to the sparse signal, an exact reconstruction can be obtained with sufficient CS measurements. Nevertheless, in practical applications, the transform coefficients of many signals usually have weak sparsity and suffer from a variety of noise disturbances. What's worse, most existing classical algorithms are not able to effectively solve this issue. So we proposed an efficient algorithm based on smoothed ${\ell}_0$ norm for sparse signal reconstruction. The direct ${\ell}_0$ norm problem is NP hard, but it is unrealistic to directly solve the ${\ell}_0$ norm problem for the reconstruction of the sparse signal. To select a suitable sequence of smoothed function and solve the ${\ell}_0$ norm optimization problem effectively, we come up with a generalized approximate function model as the objective function to calculate the original signal. The proposed model preserves sharper edges, which is better than any other existing norm based algorithm. As a result, following this model, extensive simulations show that the proposed algorithm is superior to the similar algorithms used for solving the same problem.

• Genomics & Informatics
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• v.20 no.2
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• pp.17.1-17.11
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• 2022

Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.177-186
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• 2020

This paper deals with the car paint sequencing problem (CPSP) that the entrance sequence is to same colored group with maximum sequenced cars for the buffer arriving cars from the body shop. This problem classified by NP-complete problem because of the exact solution has not obtained within polynomial time. CPSP is aim to minimum pugging number that each pugging must be performs at color changing time in order to entirely cleaning the remaining previous color. To be obtain the minimum number of moving distance with window concept and minimum number of pugging, this paper sorts same color and arriving sequence. Then we basically decide the maximum length section color time to winner team using stage race method. For the case of the loser team with no more racing or yield to loser team and more longer stage in upcoming racing, the winner team give way to loser team. As a result, all cars(runners) are winner in any stage without fail. For n cars, the proposed algorithm has a advantage of simple and fast with O(nlogn) polynomial time complexity, this algorithm can be get the minimum number of moving distance and purging for all of experimental data.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.249-255
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• 2014

Copy number variations(CNVs) are a recently recognized class of human structural variations and are associated with a variety of human diseases, including cancer. To find important cancer genes, researchers identify novel CNVs in patients with a particular cancer and analyze large amounts of genomic and clinical data. We present a tool called CNVDAT which is able to detect CNVs from NGS data and systematically analyze the genomic and clinical data associated with variations. CNVDAT consists of two modules, CNV Detection Engine and Sequence Analyser. CNV Detection Engine extracts CNVs by using the multi-resolution system of scale-space filtering, enabling the detection of the types and the exact locations of CNVs of all sizes even when the coverage level of read data is low. Sequence Analyser is a user-friendly program to view and compare variation regions between tumor and matched normal samples. It also provides a complete analysis function of refGene and OMIM data and makes it possible to discover CNV-gene-phenotype relationships. CNVDAT source code is freely available from http://dblab.hallym.ac.kr/CNVDAT/.