• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.27-34
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• 2010

This paper presents a methodology for classifying left and right motor imagery using a neural network with weighted fuzzy membership functions (NEWFM) and wavelet-based feature extraction. Wavelet coefficients are extracted from electroencephalogram(EEG) signal by wavelet transforms in the first step. In the second step, sixty numbers of initial features are extracted from wavelet coefficients by the frequency distribution and the amount of variability in frequency distribution. The distributed non-overlap area measurement method selects the minimized number of features by removing the worst input features one by one, and then minimized six numbers of features are selected with the highest performance result. The proposed methodology shows that accuracy rate is 86.43% with six numbers of features.

• Applied Chemistry for Engineering
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• v.9 no.4
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• pp.469-474
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• 1998

Poly (vinyl alcohol) (PVA) membranes crosslinked with poly (styrene-co-maleic anhydride) (PSMAn) have been prepared by the solution method. To investigate the separation behavior of the crosslinked PVA/PSMAn membranes in the pervaporation process, the selective sorption experiment and swelling measurements of the membranes in ethanol-water mixtures of 30~90 wt % ethanol contents were conducted with equipment that was able to measure the concentration and amount of the liquid absorbed in the membranes. The membranes prepared in this study exhibited good selectivity toward water component in sorption and permeation. Also, in the feed containing ethanol more than 50 wt %, the permeation selectivity of the membrane showed better correlation with the sorption selectivity than that with the swelling ratio changing toward the crosslinking content. This behavior was consistence with a solution-diffusion model correlating permeation and sorption selectivity, and led to the conclusion that the permeation selectivity was determined by sorption step rather than by diffusion step in the membrane.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.1-14
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• 2009

The Capacitated Vehicle Routing Problem (CVRP) is the problem that the vehicles stationed at central depot are to be optimally routed to supply customers with demands, satisfying vehicle capacity constraints. The CVRP is the NP-hard as it is a natural generalization of the Traveling Salesman Problem (TSP). In this article, we propose the heuristic algorithm, called the bisection seed detection method, to solve the CVRP. The algorithm is composed of 3-phases. In the first phase, we work out the initial cluster using the improved sweep algorithm. In the next phase, we choose a seed node in each initial cluster by using the bisection seed detection method, and we compose the rout with the nearest node from each seed. At this phase, we compute the regret value to decide the list of priorities for the node assignment. In the final phase, we improve the route result by using the tabu search and exchange algorithm. We compared our heuristic with different heuristics such as the Clark-Wright heuristic and the genetic algorithm. The result of proposed heuristic show that our algorithm can get the nearest optimal value within the shortest execution time comparatively.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.457-465
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• 2012

The purpose of this study is to analyze the association between indicators and to find statistical models based on important indicators at 'College Notifier' in Korea Council for University Education. First, Pearson correlation coefficients are used to find statistically significant correlations. By variable selection method, the important indicators are selected and their coefficients are estimated. As variable selection method, backward and stepwise methods are employed.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.430-437
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• 2013

The present study examined whether sentence perception scores were changed under various conditions of time alteration (compression and/or expansion) and selective word stress in normal hearing listeners. Twenty young normal hearing adults (ten males) were participated. As stimuli, Korean standard-sentence list for adults (KS-SL-A) modified to semantically anomalous sentences was newly recorded by a female speaker. Seven different time-altered conditions (e.g., ${\pm}60%$, ${\pm}40%$, ${\pm}20%$, 0 %) were controlled. To see the effect of selective word stress (i.e., the emphasis of specific syllables in the sentence), all subjects were tested twice 2 weeks apart. The results showed 1) there was significantly different sentence perception scores among the different time-altered conditions, yet only in the 60 % compression condition; 2) there was no significant difference of the sentence perception scores in the effect of stress; however, there was a positive effect of the selective word stress in the sentences consisting of 6 ~ 7 syllables at the 40 % compression condition; 3) there was no significant gender difference. The pattern of results suggests that the combination of time compression and selective word stress is more effective to understand speech, instead of only using time expansion condition. However, further studies should be needed for standardization.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.509-521
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• 2016

A novel Samples Balanced Genetic Algorithm combined with Extreme Learning Machine (SBGA-ELM) for Parkinson's Disease diagnosis and detecting bio-markers is presented in this paper. Proposed approach uses genes' expression data of 22,283 genes from open source ParkDB data base for accurate PD diagnosis and detecting bio-markers. Proposed SBGA-ELM includes two major steps: feature (genes) selection and classification. Feature selection procedure is based on proposed Samples Balanced Genetic Algorithm designed specifically for genes expression data from ParkDB. Proposed SBGA searches a robust subset of genes among 22,283 genes available in ParkDB for further analysis. In the "classification" step chosen set of genes is used to train an Extreme Learning Machine (ELM) classifier for an accurate PD diagnosis. Discovered robust subset of genes creates ELM classifier with stable generalization performance for PD diagnosis. In this research the robust subset of genes is also used to discover 24 bio-markers probably responsible for Parkinson's Disease. Discovered robust subset of genes was verified by using existing PD diagnosis approaches such as SVM and PBL-McRBFN. Both tested methods caused maximum generalization performance.

• Environmental and Resource Economics Review
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• v.23 no.3
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• pp.409-434
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• 2014

This paper estimates household demand for electricity using a micro-level household expenditure data set. A two-stage estimation method where the endogenous block price estimates are obtained from a discrete block choice model is used. This method successfully identifies a downward sloping conditional demand function with the data, while both the usual two-stage method with instrumental variable estimation and the Hewitt-Hanemann discrete-continuous model fail to do that. The paper simulates the impacts of two hypothetical pricing reforms that reduce the number of blocks and make the price gap smaller. It is shown that the reform may increase the overall consumer benefit, but is regressive.

• 전기의세계
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• v.41 no.4
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• pp.35-41
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• 1992

GIS구조상 내부에 금속 PAERICLE이 존재하면 절연 내력의 저하가 발생하므로 금속 PARTICLE이 내부에 흔입되지 않게 제조, 운송, 설치시에 방진관리를 하는 것이 최선책이나, 최종단계에서 금속성 PAERICLE이 내부에 잔존하지 않음을 확인하기 위해서는 현장 내전압 시험이 필요하다. 현장 내전압 시험은 현장의 여건에 따라 가능한 경우도 있고 불가능한 경우도 있는 여러가지 요소가 있으므로 시험 방법의 선택은 현지 여건, 경제성, 전원설비, 시험기의 크기등을 고려하여 GIS의 제조회사와 구매자간의 사전 협의를 하여 진행시켜야 하겠다.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.2
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• pp.55-76
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• 1998

The first part of this article investigates the general characteristics and the advantages and disadvantages of the analytico-synthetic classification over the enumerative one. The second part analyzes the general steps and related problems in compiling an analytico-synthetic scheme, and investigates the steps further including facet analysis , choosing order in main classes, citation order and order in array : and adding notations, through an illustrative scheme for a matrimonial agency's records.

• Tunnel and Underground Space
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• v.11 no.2
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• pp.120-121
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• 2001

The purpose of this study is to investigate concrete flaw using seismic first arrival and various inversion method. Seismic wave propagation was calculated using finite element method in theoretical modelling and tomogram was made using various inversion methods in theoretical and experimental modelling. Five steps of seismic first arrival were selected from FEM results and these data were used to calculate seismic velocity section. According to the results, exact seismic first arrival picking method was proposed and experimental modelling was conducted.