• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.13-20
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• 2009

Recently there is growing interest in LBS requiring real-time services and the spatial main memory DBMS for efficient Telematics services. In order to optimize existing disk-based spatial indexes of the spatial main memory DBMS in the main memory, spatial index structures have been proposed, which minimize failures in cache access by reducing the entry size. However, because the reduction of entry size requires compression based on the MBR of the parent node or the removal of redundant MBR, the cost of MBR reconstruction increases in index update and the efficiency of search is lowered in index search. Thus, to reduce the cost of MBR reconstruction, this paper proposed the RSMB (relative-sized MBR)compression technique, which applies the base point of compression differently in case of broad distribution and narrow distribution. In case of broad distribution, compression is made based on the left-bottom point of the extended MBR of the parent node, and in case of narrow distribution, the whole MBR is divided into cells of the same size and compression is made based on the left-bottom point of each cell. In addition, MBR was compressed using a relative coordinate and size to reduce the cost of search in index search. Lastly, we evaluated the performance of the proposed RSMBR compression technique using real data, and proved its superiority.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.722-729
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• 2010

Prediction problems are widely used in medical domains. For example, computer aided diagnosis or prognosis is a key component in a CDSS (Clinical Decision Support System). SVMs with nonlinear kernels like RBF kernels, have shown superior accuracy in prediction problems. However, they are not preferred by physicians for medical prediction problems because nonlinear SVMs are difficult to visualize, thus it is hard to provide intuitive interpretation of prediction results to physicians. Nomogram was proposed to visualize SVM classification models. However, it cannot visualize nonlinear SVM models. Localized Radial Basis Function (LRBF) was proposed which shows comparable accuracy as the RBF kernel while the LRBF kernel is easier to interpret since it can be linearly decomposed. This paper presents a new tool named VRIFA, which integrates the nomogram and LRBF kernel to provide users with an interactive visualization of nonlinear SVM models, VRIFA visualizes the internal structure of nonlinear SVM models showing the effect of each feature, the magnitude of the effect, and the change at the prediction output. VRIFA also performs nomogram-based feature selection while training a model in order to remove noise or redundant features and improve the prediction accuracy. The area under the ROC curve (AUC) can be used to evaluate the prediction result when the data set is highly imbalanced. The tool can be used by biomedical researchers for computer-aided diagnosis and risk factor analysis for diseases.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.1-11
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• 2009

Rapid visualization of flood area of downstream according to the dam effluent in flood season is very important in dam management works. Overlay zone of river bight should be removed to represent flood area efficiently based on flood stage which was modeled in river channels. This study applied drainage enforcement algorithm to visualize flood area considering river bight by coupling Coordinate Operation System for Flood control In Multi-reservoir (COSFIM) and Flood Wave routing model (FLDWAV). The drainage enforcement algorithm is a kind of interpolation which gives to advantage into hydrological process studies by removing spurious sinks of terrain in automatic drainage algorithm. This study presented mapping technique of flood area layer considering river bight in Namgang-Dam downstream, and developed system based on Arcobject component to execute this process automatically. Automatic extraction system of flood area layer could save time-consuming efficiently in flood inundation visualization work which was propelled based on large volume data. Also, flood area layer by coupling with IKONOS satellite image presented real information in flood disaster works.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.1-10
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• 2011

Recently, cloud computing which has provided enabling convenience that users can connect from anywhere and user friendly environment that offers on-demand network access to a shared pool of configurable computing resources such as smart-phones, net-books and PDA etc, is to be watched as a service that leads the digital revolution. Now, when business practices between departments being integrated through a cooperating system such as cloud computing, data streaming between departments is getting enormous and then it is inevitably necessary to find the solution that person in charge and find data they need. In previous studies the clustering simplifies the search process, but in this paper, it applies Hash Function to remove the de-duplicates in large amount of data in business firms. Also, it applies Bayesian Network of data mining for classifying the respect data and presents handling cloud computing based data. This system features improved search performance as well as the results Compared with conventional methods and CPU, Network Bandwidth Usage in such an efficient system performance is achieved.

• Korean Journal of Construction Engineering and Management
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• v.7 no.5
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• pp.128-137
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• 2006

This paper is to develop curtain wall process life-cycle system in high-rise buildings in order to establish effective cooperation communication channels among the diverse constituents. This paper is to provide a base toward a curtain wall life-cycle management system to support decision making and the effective flow in light of information and materials. The four objectives of the research are 1) the analysis of the current curtain wall life-cycle process, 2) the analysis and development of the curtain wall design process As-Is model, and 3) the Muda analysis of the design process As-Is model and the suggestion of the improvements, 4) the development of curtain wall design To-Be model and comparative analysis of the improvement in terms of value streams. This research indicates the wastes decrease (or the values increase) from 6.7% up to 100% in different decision criteria through the improvement by the comparative analysis between the As-ls and To-Be curtain wall design process. This research suggests the potential improvement by VSM and a curtain wall life-cycle management system in curtain wall construction for diverse constituents be significant.

• The Journal of Society for e-Business Studies
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• v.8 no.4
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• pp.129-149
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• 2003

Explosive growth of mobile devices over the past years has greatly increased commercial interests in mobile commerce, but mobile commerce has not yet seen enough increase on demand side as anticipated. Despite the slow start, mobile commerce has a lot of potential from users' perspective. In order to make this potential a reality, businesses must focus on the values from their customers' perspective, not technical competencies. This research employed Keeney's(1992) value focused thinking approach and explore values of mobile commerce from actual users' viewpoint. In depth interviews were conducted with seventy Practical users of mobile commerce. Through an extensive focus group sessions, 748 statements obtained from actual users were classified into 18 categories of means objectives and 12 categories of fundamental objectives of mobile commerce. The means-ends network diagram of values seen in mobile commerce by actual users were presented and compared to typical electronic commerce diagram. Results suggest the mobile commerce needs to be handled differently from the traditional electronic commerce.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.1
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• pp.71-81
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• 2002

The lack of specialties of the existing commercial web search systems stems from the fact that they have no capabilities to extract and gather the meaningful information from each information domain they cover. We are sure, however, that the necessity for the information integration system, not just search system, will be likely to become larger in the future. In this paper, we propose a design and implementation of an information integration system called TIC(target information collector). TIC is able to extract meaningful information from a specific information area in the internet and integrate them for the commercial service. We also show the evaluation results of our implementation. For the experiments we applied our TIC to the international procurement information area. The international procurement information is publicly and freely announced by each government to the world. To automatically extract common properties from the related source sites, we adopt information pointing technique using inter-HTML tag pattern parsing. And through the information integration framework design, we can easily implement a site-specific information integration engine. By running our TIC for about 8 months, we find out it can remove considerable amount of the duplicated information, and as a result, we can obtain high quality international procurement information. The main contribution of this paper is to present a framework design and it's implementation for extracting the information of a specific area and then integrating them into a meaningful one.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.21-27
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• 2019

Selection of feature pattern gathered from the observation of the RNA sequencing data (RNA-seq) are not all equally informative for identification of differential expressions: some of them may be noisy, correlated or irrelevant because of redundancy in Big-Data sets. Variable selection of feature pattern aims at differential expressed gene set that is significantly relevant for a special task. This issues are complex and important in many domains, for example. In terms of a computational research field of machine learning, selection of feature pattern has been studied such as Random Forest, K-Nearest and Support Vector Machine (SVM). One of most the well-known machine learning algorithms is SVM, which is classical as well as original. The one of a member of SVM-criterion is Support Vector Machine-Recursive Feature Elimination (SVM-RFE), which have been utilized in our research work. We propose a novel algorithm of the SVM-RFE with Q-learning in reinforcement learning for better variable selection of feature pattern. By comparing our proposed algorithm with the well-known SVM-RFE combining Welch' T in published data, our result can show that the criterion from weight vector of SVM-RFE enhanced by Q-learning has been improved by an off-policy by a more exploratory scheme of Q-learning.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.103-112
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• 2019

Extraction of region of interest for satellite image classification is one of the important techniques for efficient management of the national land space. However, recent studies on satellite image classification often depend on the information of the selected image in selecting the region of interest. This study propose an effective method of selecting the area of interest using the continuous digital topographic map constructed from high resolution images. The spatial information used in this research is based on the digital topographic map from 2013 to 2017 provided by the National Geographical Information Institute and the 2015 Sejong City land cover map provided by the Ministry of Environment. To verify the accuracy of the extracted area of interest, KOMPSAT-3A satellite images were used which taken on October 28, 2018 and July 7, 2018. The baseline samples for 2015 were extracted using the unchanged area of the continuous digital topographic map for 2013-2015 and the land cover map for 2015, and also extracted the baseline samples in 2018 using the unchanged area of the continuous digital topographic map for 2015-2017 and the land cover map for 2015. The redundant areas that occurred when merging continuous digital topographic maps and land cover maps were removed to prevent confusion of data. Finally, the checkpoints are generated within the region of interest, and the accuracy of the region of interest extracted from the K3A satellite images and the error matrix in 2015 and 2018 is shown, and the accuracy is approximately 93% and 72%, respectively. The accuracy of the region of interest can be used as a region of interest, and the misclassified region can be used as a reference for change detection.

• Journal of the Korea Institute of Building Construction
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• v.22 no.3
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• pp.281-291
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• 2022

This study attempts to use big data to determine the indicators necessary for a fire risk assessment of buildings. Because most of the causes affecting the fire risk of buildings are fixed as indicators considering only the building itself, previously only limited and subjective assessment has been performed. Therefore, if various internal and external indicators can be considered using big data, effective measures can be taken to reduce the fire risk of buildings. To collect the data necessary to determine indicators, a query language was first selected, and professional literature was collected in the form of unstructured data using a web crawling technique. To collect the words in the literature, pre-processing was performed such as user dictionary registration, duplicate literature, and stopwords. Then, through a review of previous research, words were classified into four components, and representative keywords related to risk were selected from each component. Risk-related indicators were collected through analysis of related words of representative keywords. By examining the indicators according to their selection criteria, 20 indicators could be determined. This research methodology indicates the applicability of big data analysis for establishing measures to reduce fire risk in buildings, and the determined risk indicators can be used as reference materials for assessment.