• Tunnel and Underground Space
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• v.29 no.5
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• pp.332-345
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• 2019

Maximum dip vector of individual joint plane, which can be uniquely defined on the hemispherical projection plane, has been established by considering its dip and dip direction. A new stereographic projection method for the rock slope analysis which employs the maximum dip vector can intuitively predict the failure modes of rock slope. Since the maximum dip vector is uniquely projected on the maximum dip point of the great circle, the sliding direction of discontinuity plane can be recognized directly. By utilizing the maximum dip vector of discontinuity both the plane sliding and toppling directions of corresponding blocks can be discerned intuitively. Especially, by allocating the area of high dip maximum dip vector which can form the flanks of sliding block the potentiality for the formation of virtual sliding block has been estimated. Also, the potentiality of forming the triangular-sectioned sliding block has been determined by considering the dip angle of joint plane the dip direction of which is nearly opposite to that of the slope face. Safety factors of the different-shaped blocks of triangular section has been estimated and compared to the safety factor of the most hazardous block of rectangular section. For the wedge analysis the direction of crossline of two intersecting joint planes, which has same attribute of the maximum dip vector, is used so that wedge failures zone can be superimposed on the stereographic projection surface in which plane and toppling failure areas are already lineated. In addition the maximum dip vector zone of wedge top face has been delineated to extract the wedge top face-forming joint planes the orientation of which provides the vital information for the analysis of mechanical behavior of wedge block.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.1
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• pp.22-31
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• 2001

The purpose of this study is to compare calculated pollutant loadings using pollutant load unit factors and vector type coverage, and expected mean concentration(EMC) and raster type of digital elevation model(DEM). This study is also focusing on comparison of the advantages and the disadvantages of the two methods, and seeking for a method of calculation of pollutant loadings using DEM. Estimation of pollutant inputs using pollutant load unit factors has limitations in identifying seasonal variations of pollutant loadings. Seasonal changes of runoffs should be considered in the calculation of pollutant loadings from catchments into reservoirs. Evaluation of pollutant inputs using runoff-coefficient and EMC can overcome these drawbacks. Proper EMC and runoff-coefficient values for the Koeup stream catchments of the Koheung estuarine lake were drawn from review of related papers. Arc/Info was employed to establish database of spatial and attribute data of point and non-point pollutant sources and characteristics of the catchments. ArcView was used to calculate point and non-point pollutant loadings. Pollutant loads estimated with either unit factors-coverages, i.e., pollutant load unit factors and vector coverages f point sources and land use, or EMC and digital elevation mode(DEM) were compared with stream monitoring loads. We have found that some differences were shown between monitoring results and estimated loads by Unit Factors-Coverage and EMC-DEM. Monthly variations of pollutant loads evaluated with EMC-DEM were similar to those with monitoring result. The method using EMC-DEM can calculate accumulated flows and pollutant loads and can be utilized to identify stream networks. A future research on correcting the difference between vector type stream using flow direction grid and digitalizing vector type should be conducted in order to obtain more exact calculation of pollutant loadings.

• Korean Journal of Geomatics
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• v.2 no.2
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• pp.131-137
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• 2002

The digital photogrammetric products have been increasingly used as an accurate foundation for representing information associated with infrastructure management. The technological advances in merging raster and vector data within the framework of GIS have allowed for the inclusion of DTMs and digital orthophotos with vector data and its associated attributes. This study addresses not only generating DEMs and digital orthophotos but producing three dimensional building models from aerial photos of an urban area by employing the digital photogrammetric technology. DEMs and digital orthophotos were automatically generated through the process of orientations, image matching and so on, and then the practical problems, which must be solved especially in applying to urban areas, were considered. The accuracy of produced digital orthophotos was derived by using check points. Also three dimensional visualization imagery, which is useful in the landform analysis, and 3D building models were produced. Digital photogrammetric products would be used widely not only as GIS framework data layers by using the GIS link function which links attribute and image information in the database for applying to infrastructure management and but as geospatial data for especially 3D GIS in urban areas.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.287-296
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• 2003

There has been much research focused on collaborative filtering technique in Recommender System. However, these studies have shown the First-Rater Problem and the Sparsity Problem. The main purpose of this Paper is to solve these Problems. In this Paper, we suggest the user's predicting preference method using Bayesian estimated value and the associative user clustering for the recalculation of preference. In addition to this method, to complement a shortcoming, which doesn't regard the attribution of item, we use Representative Attribute-Neighborhood method that is used for the prediction when we find the similar neighborhood through extracting the representative attribution, which most affect the preference. We improved the efficiency by using the associative user's clustering analysis in order to calculate the preference of specific item within the cluster item vector to the collaborative filtering algorithm. Besides, for the problem of the Sparsity and First-Rater, through using Association Rule Hypergraph Partitioning algorithm associative users are clustered according to the genre. New users are classified into one of these genres by Naive Bayes classifier. In addition, in order to get the similarity value between users belonged to the classified genre and new users, and this paper allows the different estimated value to item which user evaluated through Naive Bayes learning. As applying the preference granted the estimated value to Pearson correlation coefficient, it can make the higher accuracy because the errors that cause the missing value come less. We evaluate our method on a large collaborative filtering database of user rating and it significantly outperforms previous proposed method.

• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.2
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• pp.263-275
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• 1992

This study intends to provide strategic positioning of brand image analysed from the view point of perceptual dimensions of clothing consumers. Consumers are segmented on the basis of the attributes of brand image, and in each segment, perceptual map is composed according to multidimensional scaling. The results are as follows; 1. According to the Benefit Segmentation, it is statistically significant that the consumers are divided into 'product-factor oriented group 'and' image-factor oriented group'. 2. From the analysis of perceptual map upon the 'similarity of brand image,'image-factor oriented group 'perceives more differently than 'product-factor oriented group' 3. From the analysis of perceptual map with the evaluation of attributes of brand image, price, promotion and design are significant determinants in 'total consumer group'. In addition, store image is significant determinant in' image-factor oriented group' and quality is significant determinant in' product-factor oriented group'. According to the evaluation of consumers on 8 brands with determining attribute-vector, ranks of brands in each segment are similar in the vector of price and promotion but different in the vector of design between segment groups. 4. From the analysis of perceptual map upon the preference of brand image, the distribution of preference and position of ideal point are different between segment groups. 5. With evaluation of purchase habit, statistically significant differences are found between groups segmented in the degree of importance of attributes, purchasing motive, purchasing time, sources of information and expenses for clothes.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.52-56
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• 2004

The Information of classification and estimate about KOSPI200 index`s up and down in the stock market becomes an important standard of decision-making in designing portofolio in futures and option market. Because the coming trend of time series patterns, an economic indicator, is very subordinate to the most recent economic pattern, it is necessary to study the recent patterns most preferentially. This paper compares classification and estimated performance of SVM(Support Vector Machine) and Fuzzy SVM model that are getting into the spotlight in time series analyses, neural net models and various fields. Specially, it proves that Fuzzy SVM is superior by presenting the most suitable dimension to fuzzy membership function that has time series attribute in accordance with learning Data Base.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.44-58
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• 2014

In this study, a standard vector data model was developed for interoperability of river-geospatial information and for verification purpose the applicability of the standard vector model was evaluated using a model to RIMGIS vector data at Changnyeong-Hapcheon & Gangjung-Goryeong irrigation watershed. The standards from ISO and OGC were analyzed and the river geospatial data model standard was established by applying the standards. The ERD was designed based on the analysis information on data characteristics and relationship. The verification of RIMGIS vector data included points, lines and polygon to develope GDM was carried out by comparing with the data by layer. This conducting comparison of basic spatial data and attribute data to each record and spatial information vertex. The error in the process of conversion was 0 %, indicating no problem with model. Our Geospatial Data Model presented in this study provides a new and consistent format for the storage and retrieval of river geospatial data from connected database. It is designed to facilitators integrated analysis of large data sets collected by multiple institutes.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.95-106
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• 2014

In this study, the applicability of a standard vector model was evaluated using RIMGIS vector data and a portal based river-geospatial information web service system was developed using XML and JSON based data linkage between the server and the client. The RIMGIS vector data including points, lines, and polygons were converted to the Geospatial Data Model(GDM) developed in this study and were validated by layers. After the conversion, it was identified that the attribute data of a shape file remained without loss. The GeoServer GDB(GeoDataBase) that manages a DB in the portal was developed as a management module. The XML-based Geography Markup Language(GML) standards of OGC was used for accessing to and managing vector layers and encoding spatial data. The separation of data content and expression in the GML allowed the different expressions of the same data, convenient data revision and update, and enhancing the expandability. In the future, it is necessary to improve the access, exchange, and storage of river-geospatial information through the user's customized services and Internet accessibility.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.215-220
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• 2004

Satellite and aerial images are very useful means to monitor ecological and environmental situation. Nowadays more and more officials at Ministry of Environment in Korea need to access and use these image data through networks like internet or intranet. However it is very hard to manage and service these image data through internet or intranet, because of its size problem. In this paper very large image data service system for Ministry of Environment is constructed on web environment using image compression and web based image processing technology. Through this system, not only can officials in Ministry of Environment access and use all the image data but also can achieve several image processing effects on web environment. Moreover officials can retrieve attribute information from vector GIS data that are also integrated with the system.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.23-28
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• 2005

The high-dimensionality and insufficiency of gene expression profiles and proteomic profiles makes feature selection become a critical step in efficiently building accurate models for cancer problems based on such data sets. In this paper, we use a method, called Discrete Function Learning algorithm, to find discriminatory feature vectors based on information theory. The target feature vectors contain all or most information (in terms of entropy) of the class attribute. Two data sets are selected to validate our approach, one leukemia subtype gene expression data set and one ovarian cancer proteomic data set. The experimental results show that the our method generalizes well when applied to these insufficient and high-dimensional data sets. Furthermore, the obtained classifiers are highly understandable and accurate.