• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1921-1929
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• 2015

The smart substation is the heart of a transmission system, which is particularly emphasized as the most significant composition of smart grids in China. In order to assess the functionality performance of substation technologies, this paper presents methods used to identify the most promising solutions for smart substation design and to evaluate the technical levels of available technologies. The multi-index optimization model is presented to address the issue of smart substation planning. A mathematical model of the planning decision problem is established with multiple objectives consisting of economic, reliability, and green key indices, and many kinds of concerns including physical and environmentally friendly operations are formulated as a set of constraints. With respect to the assessment of the technical level regarding integration of advanced technologies into a substation, a modified grey whitenization weight function is adopted to structure a novel grey clustering method. The proposed grey clustering approach is used to overcome the difficulty of insufficient quantitative assessment capacity for traditional methods. The evaluation of technical effects provides the classification definition for the development phase and the maturity level of the smart substation. The effectiveness of the proposed approaches in planning decision-making and evaluation of construction efforts is demonstrated with case studies involving the actual smart substation projects of Wenchongkou substation in China Southern Power Grid (CSG) and Mengzi substation in State Grid Corporation of China (SGCC).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2866-2879
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. Previous studies on game bot detection have proposed many methods to find out discriminable behaviors of bots from humans based on the fact that a bot's playing pattern is different from that of a human. In this paper, we look at the chatting data that reflects gamers' communication patterns and propose a communication pattern analysis framework for online game bot detection. In massive multi-user online role playing games (MMORPGs), game bots use chatting message in a different way from normal users. We derive four features; a network feature, a descriptive feature, a diversity feature and a text feature. To measure the diversity of communication patterns, we propose lightly summarized indices, which are computationally inexpensive and intuitive. For text features, we derive lexical, syntactic and semantic features from chatting contents using text mining techniques. To build the learning model for game bot detection, we test and compare three classification models: the random forest, logistic regression and lazy learning. We apply the proposed framework to AION operated by NCsoft, a leading online game company in Korea. As a result of our experiments, we found that the random forest outperforms the logistic regression and lazy learning. The model that employs the entire feature sets gives the highest performance with a precision value of 0.893 and a recall value of 0.965.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.125-137
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• 2011

This study aims to know whether the Accreditation of Hospitals can help to improve productivity of hospital and affect the conversion factor. Based on the Malmquist productivity Index, the productivity of accredited hospital improves. There exists an tendency that as the scores of Accreditation rises, productivity increases. Also the higher the productivity, the lower the conversion factors in the rigid statistical evidence. This evidence is independent of hospital classification, geographical distribution, grouping. This evidence supports the productivity index can be included in the fee negotiations. It also means that rather than static efficiency, the multi-year change of productivity information can be usefully combined to set a conversion factor in Korean National Insurance Contract especially in the discussion of the structural change of payment system.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.749-754
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• 2016

Extended follow-up of Hodgkin lymphoma (HL) survivors indicates that these patients are at high risk of secondary malignant neoplasms (SMNs) contributing to increased morbidity and mortality. This study examined the characteristics of HL survivors who developed SMNs with the aim to report any correlation with radiotherapy (RT) dose. In this retrospective multi-center cohort study of HL patients treated between 1990 and 2011 at three major teaching hospitals in Lebanon, classification was into two groups including those treated with combined modality (RT and chemotherapy-CHT) and those treated with CHT alone. Approval from the University Institutional Review Board (IRB) was obtained. Of the 112 patients evaluated, 52.7% (59) received the combined modality while 47.3% (53) received CHT alone. There were 6 cases of SMNs in the combined modality cohort and 5 cases in the CHT cohort. The mean RT dose in the combined modality cohort was 34.5 Gray (Gy) ($SD{\pm}5.3$). A statistically significant increase (1.5 fold) in the risk of developing SMNs was observed among patients who received a dose higher than 41 Gy compared to a dose between 20 to 30 Gy (OR= 1.5; 95% confidence interval= 0.674 to 3.339, p=0.012). The risk of SMNs was not significantly higher among patients who received extended field compared to involved field RT (p=0.964). This study showed that the risk of developing SMNs is higher among patients treated with RT dose greater than 31 Gy, independent of the RT type used.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.277-286
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• 2014

In this paper, we propose a texture feature-based language identification by fusion of Gabor, MDLC (multi-lag directional local correlation), and co-occurrence features. In the proposed method, for a test image, Gabor magnitude images are first obtained by Gabor transform followed by magnitude operator. Moments for the Gabor magniude images are then computed and vectorized. MDLC images are then obtained by MDLC operator and their moments are computed and vectorized. GLCM (gray-level co-occurrence matrix) is next calculated from the test image and co-occurrence features are computed using the GLCM, and the features are also vectorized. The three vectors of the Gabor, MDLC, and co-occurrence features are fused into a feature vector. In classification, the WPCA (whitened principal component analysis) classifier, which is usually adopted in the face identification, searches the training feature vector most similar to the test feature vector. We evaluate the performance of our method by examining averaged identification rates for a test document image DB obtained by scanning of documents with 15 languages. Experimental results show that the proposed method yields excellent language identification with rather low feature dimension for the test DB.

• Korean Journal of Veterinary Service
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• v.32 no.3
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• pp.265-273
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• 2009

A cross-sectional survey was undertaken to identify risk factors and clinical signs associated with parasitic helminth infections of cattle in Mymensignh district of Bangladesh. A nonrandom convenience sampling method was used to select 138 animals from 40 farmers/herds. The eggs per gram of faeces (epg) for nematodes and trematodes were determined by McMaster and Stoll's methods respectively. Animal-level and herd-level data were recorded by means of a questionnaire. Multi-collinearity amongst explanatory variables were assessed using $2{\times}2{\times}\;X^2$ test and one variable in a pair was dropped if $P{\leq}0.05$ formultiple logistic regression models. Association study between outcome and explanatory variables was conducted using classification tree, random forests and multiple logistic regression. A positive epg was considered as infected. Analyses were performed using $STATA^{(R)}$, version 8.0/Intercooled and $R^{(R)}$, Version 2.3.0. Seventy eight percent of the cattle were found to be infected with at least one type of helminth. Twenty four pairs of combinations of explanatory variables showed significant associations. Male animals (OR=3.3, P=.006, 95% CI=1.4, 7.7) were associated with significantly increased prevalence of nematode infection. Female cattle of the study area are mostly cross-breed, kept indoor, fed relatively good diet and not used for draught purpose. Males are used for draught purpose thereby more exposed to nematode infective stage and provided with relatively poor diet. So stressed male cattle may become more susceptible to nematode infection. All of the three statistical techniques selected gender and lumen motility as most important variables in association with nematode infection in cattle. The result of this survey can only be extrapolated to the periurban cattle population of traditional management system.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.67-82
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• 2013

Railway is paid attention as a means of environment-friendly transportation and logistics. Efforts to enhance the competitiveness by IT convergence, for railway vehicle market share of the world, has been promoted. This study proposes a technology development plan of railway IT convergence. We analyzed the results of legacy researches and technology patents related with railway IT convergence and derived the target tasks in accordance with our technologies classification. By adopting the multi-attributes utility theory methodology and using survey of experts, we selected the core research issues. The result of this study could help policy making and R&D planning about railway IT convergence.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.13-22
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• 2005

This paper classifies the topography of the Saemangeum Tidal flats based on Landsat TM satellite images by unsupervised ISODATA method, and analysis of the spatiotemporal changes of the classified shapes. The sedimental topography represents various properties according to the Saemangeum Tidal Embankment progress. We well proceed this study of the sedimental changes and distributions. By specifying the topographic characteristics of inner sea areas respectively, the investigation on the case study area according to the changes of the tidal will be useful in the establishment of land reclamation plan and the land use of the reclaimed area. In addition, the estuary image can be divided into tidal flats and sea surfaces using the band 4, also the detailed topography using the band 5, respectively among Landsat TM 7 bands. This paper contributes to the efficient image processing of the spatiotemporal sedimental changes.

• Journal of Ecology and Environment
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• v.39 no.1
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• pp.71-80
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• 2016

The main goal of this study is to develop a multi-metric fishway assessment model (M_m-FA) and evaluate the efficiency of fishway. The M_m-FA model has three major fishway components with nine metrics: structural characteristics, hydraulic/hydrologic features, and biological attributes. The model was developed for diagnosing and assessing fishway efficiency and tested to Juksan Weir at the Yeongsan River Watershed. Structural characteristics of fishway included slope of the fishway (M₁), ratios of fishway width to stream width (M₂), and the proportion of orifice clogging and orifice size (M₃). Hydraulic/hydrologic characteristics included depth of fishway entrance head (M₄), depth of exit tail (M₅), and current velocity of inner fishway (M₆). Biological characteristics included fish species ratio of inner fishway to upper-lower weir (M₇), fish length distribution (M₈), and the proportion of migratory fish species to the total number of species (M₉). Overall, the assessment of fishway efficiency showed the total score of the M_m-FA model was 25 in the Juksan Weir, indicating "good condition" by the criteria of the five-level classification system. The M_m-FA model may be used as a key tool for the assessment of fishway efficiency, especially on the 16 weirs constructed for the "Four Rivers Restoration Project" after a partial calibration of M_m-FA model.

• The Transactions of the Korea Information Processing Society
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• v.2 no.2
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• pp.199-208
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• 1995

In this paper, a neural network architecture which can extract map symbols by being based on the results of physiological and neuropsychological studies on pattern recognition is proposed. This network is composed of multi-layers and synaptic activities of combining layers are implemented by spatial filters which approximate receptive fields of optic nerve cells. In pattern recognition which is followed by color classification for extracting of map symbols from input image, this network is searching for candidatepoints in lower layers (layer 2, 3) by using local features such as lines and end-points and then processing symbols recognition on those points in upper layer(layer 4) by using global features.