• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.102-107
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• 2009

Window system is an essential component for lighting, ventilation and thermal environment in buildings. Moreover, as balcony extension in apartment houses become legalized, the performance requirements of window systems in balcony space are getting complicated. However, at this moment, five properties of the windows are used to represent the performance aspects of the system, including wind resistance, air tightness, water tightness, sound insulation, thermal resistance. And such single properties are not capable to express the performance of a space with the window systems in terms of performance concept. A performance analysis with wholistic approach is required to see the effect of the window system in built environment. Thus, performance-based approach should be established, which will be able to evaluate the goal/function and comfort of occupants/owners. As the first step to develop the performance indicator for the window systme for balcony space, this study conducts a survey to find the required performance aspects. A complete set of performance-based indicators will be developed with verification methods in the later stage of research.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.11
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• pp.1605-1614
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• 2002

The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality. In order to implement the purpose of this study, Jeans market had been segmented by the mixture regression model, and price response function was calibrated for each segment. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables. Data were co]looted from the sample of the 23o undergraduate and graduate students in Seoul. For the data analysis, mixture regression model, conjoint analysis, and t-test were used. As a result, jeans market was divided into 5 segments. Segment 1,2,3 were allocated into the group not using the level of price as the quality indicator while segment 4,5 were done into the other group. Significant differences existed between two groups in product attributes, not in demographic variables. Mixture model and conjoint analysis were proved to be an effective set of tools in market segmentation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.123-129
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• 2013

The aim of this study is to design an intelligent pattern-based real-time trading system (PRTS) using rough set analysis of technical indicators, dynamic time warping (DTW), and genetic algorithm in stock futures market. Rough set is well known as a data-mining tool for extracting trading rules from huge data sets such as real-time data sets, and a technical indicator is used for the construction of the data sets. To measure similarity of patterns, DTW is used over a given period. Through an empirical study, we identify the ideal performances that were profitable in various market conditions.

• BMB Reports
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• v.47 no.6
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• pp.348-353
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• 2014

The speed of sound (SOS) value is an indicator of bone mineral density (BMD). Previous genome-wide association (GWA) studies have identified a number of genes, whose variations may affect BMD levels. However, their biological implications have been elusive. We re-analyzed the GWA study dataset for the SOS values in skeletal sites of 4,659 Korean women, using a gene-set analysis software, GSA-SNP. We identified 10 common representative GO terms, and 17 candidate genes between these two traits (PGS < 0.05). Implication of these GO terms and genes in the bone mechanism is well supported by the literature survey. Interestingly, the significance levels of some member genes were inversely related, in several gene-sets that were shared between two skeletal sites. This implies that biological process, rather than SNP or gene, is the substantial unit of genetic association for SOS in bone. In conclusion, our findings may provide new insights into the biological mechanisms for BMD.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.4
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• pp.414-419
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• 2019

JC polyomavirus (JCPyV) is a human pathogenic virus belonging to the family Polyomaviridae, a viral group containing dsDNA nucleic acid. A recent recommendation is to apply the presence of JCPyV as a fecal indicator for water contamination in environments like sewage, and techniques to monitor JCPyV in water are being proposed. To date, the conventional PCR system has been applied as a diagnostic method for detecting JCPyV. There is a need for a more rapid and sensitive JCPyV diagnostic detection method in clinical and environmental samples. In this study, we developed a loop-mediated isothermal amplification (LAMP) primer set for the detection of JCPyV. Our results indicate that the LAMP method using a specific primer set shows about 10-fold higher detection sensitivity than the conventional PCR system. The effectiveness of the LAMP method developed in this study has been validated by PCR product digestion using the HaeIII restriction enzyme. We, therefore, propose that the LAMP method using a specific primer set can be applied as a rapid and sensitive detection method for monitoring JCPyV in clinical and environmental samples.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.382-387
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• 2002

In this paper, we propose a geostatistical approach incorporated to the Bayesian data fusion technique for supervised classification of multi-sensor remote sensing data. Traditional spectral based classification cannot account for the spatial information and may result in unrealistic classification results. To obtain accurate spatial/contextual information, the indicator kriging that allows one to estimate the probability of occurrence of classes on the basis of surrounding observations is incorporated into the Bayesian framework. This approach has its merit incorporating both the spectral information and spatial information and improves the confidence level in the final data fusion task. To illustrate the proposed scheme, supervised classification of multi-sensor test remote sensing data set was carried out.

• Ocean Science Journal
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• v.41 no.1
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• pp.31-41
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• 2006

Seasonal changes of abundance of the main phytoplankton groups of species (diatoms, dinoflagellates, chrysophytes, small flagellates and cryptophytes) and a set of environmental parameters were investigated in coastal and pre-estuarine waters of Peter the Great Bay (East/Japan Sea) in May-October of 1998 and 1999. Three periods of mass development were revealed: spring, summer and autumn blooms, with successive change of species. The conditions favourable for each group of species were determined. Driving mechanisms of the succession include nutrients transport through seasonal pycnocline by turbulent mixing, terrestrial nutrients supply by monsoon floods, nutrients supply by upwellings, and light control by the thickness of upper mixed layer. Summer succession could be explained by a simple SST-MLD diagram similar to Pingree S-kh diagram with sea surface temperature as indicator of stratification (S) and mixed layer depth as indicator of light availability (kh).

• Korean Journal of Environmental Agriculture
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• v.24 no.3
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• pp.303-313
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• 2005

Agricultural environmental indicators (AEIs) are useful tool for evaluating environmental performance induced by agri-environmental policy measures. General and specific criteria have been set to assess the linkages between policy measures and environmental states. In addition, a number of specific AEIs such as nutrient balance indicators and farm management indicators have been posit to review environmental performance associated with agri-environmental policy measures. The proposed environmental subjects encompass soil quality, qualities of underground and surface water, water resource preservation, species and genetic diversity, diversity for wildlife habitats, and agricultural landscapes. The developed AEIs may contribute to establishment or adjustment of environmental targets and ex-ante or ex-post evaluation for environmental performance associated with policy measures. In addition, the AEIs may be useful to consider introduction of new agri-environmental measures and enhance policy efficiency by assessing environmental performance, considering specific locality, and harmonizing support measures.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.59-69
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• 2005

Data mining is the method to find useful information for large amounts of data in database It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. We analyze Gyeongnam social indicator survey data by 2001 using association rule technique for environment information. Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. We can use to environmental preservation and environmental improvement by association rule outputs