• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.847-854
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• 2001

The Web continues to grow fast rate in both a large aclae volume of traffic and the size and complexity of Web sites. Along with growth, the complexity of tasks such as Web site design Web server design and of navigating simply through a Web site have increased. An important input to these design tasks is the analysis of how a web site is being used. The is paper proposes a Page logging System(PLS) identifying reliably user sessions required in Web mining system PLS consists of Page Logger acquiring all the page accesses of the user Log processor producing user session from these data, and statements to incorporate a call to page logger applet. Proposed PLS abbreviates several preprocessing tasks which spends a log of time and efforts that must be performed in Web mining systems. In particular, it simplifies the complexity of transaction identification phase through acquiring directly the amount of time a user stays on a page. Also PLS solves local cache hits and proxy IPs that create problems with identifying user sessions from Web sever log.

• Korean Journal of School Psychology
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• v.18 no.3
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• pp.317-349
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• 2021

This study was conducted to examine the reliability and validity of the internet (IOS-Q), Game (GOS-Q), and Smartphone (SOS-Q) Overuse Screening Questionnaires in a large community sample of adolescents. To achieve this goal, data from 9,336 middle school students (male: 4,796, female: 4,540) was divided into two groups and analyzed by conducting confirmatory factor analysis and exploratory factor analysis, respectively. We conducted another confirmatory factor analysis on a separate sample of data from 4,536 elementary school students (male: 2,260 male, female: 2,276) and 6,551 middle school students (male: 3,013, female: 3,538) from other populations. As a result of factor analysis, IOS-Q was consisted of 17 items, GOS-Q was consisted of 19 items, and SOS-Q was consisted of 18 items. The IOS-Q and GOS-Q factors were psychological dependence, failure to control use despite recognizing problems, dangerous use, and reduced interest in other areas while the SOS-Q factors were dangerous and obsessive use, failure to control use despite recognizing problems, reduced interest in other areas, and withdrawal/tolerance. Each factor reflected the major facets of behavioral addiction or impulse control disorder, and the questionnaires had good internal consistencies of .880-.915. Latent profile and ROC analyses were conducted to determine cutoff points for screening high-risk groups. Lastly, theoretical and practical implications as well as the limitations of this study were discussed.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.587-595
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• 2022

In this study, in order to understand the social psychological characteristics of college male students majoring in beauty, PAI tests were conducted on 163 university students located in Gyeonggi-do and Chungnambuk area in 2020. First, when comparing the average scales of men who majored in beauty and men who majored in general, the major male students of beauty showed an overall high clinically recognized type compared to students who majored in beauty, and a negative impression on a valid scale (NIM) considered treatment for physical complaints (SOM), depression (DEP) and drinking problems (ALC) on a clinical scale, and a significant difference was shown on a suicide idea (SUI) scale. Secondly, in order to navigate the PAI scale that significantly predicts beauty major male students, a stepwise regression analysis was performed using 15 significant scales as search factors in comparison between beauty major male and general major male students. As a result, physical complaints (SOM) and depression (DEP) scales were extracted, which became a factor that can predict male students in beauty major. Therefore, it can be understood that the male students in the beauty major have behavior patterns that are more obsessed with and more impulsive to physical problems than the male majors. These results will provide a lot of suggestions for the selection of future male students in beauty major, selection, management, education, consultation materials, and selection of occupations after graduation.

• Journal of the Korea Knowledge Information Technology Society
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• v.13 no.5
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• pp.607-614
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• 2018

Oryeong-san is a prescription widely used for diseases where water is stagnant because it has the effect of circulating the water in the body and releasing it into the urine. In order to investigate the mechanisms of oryeong-san, we in this paper construct and analysis the compound-target network of medicinal materials constituting oryeong-san based on a systems pharmacology approach. First, the targets related to the 475 chemical compounds of oryeong-san were searched in the STITCH database, and the search results for the interactions between compounds and targets were downloaded as XML files. The compound-target network of oryeong-san is visualized and explored using Gephi 0.8.2, which is an open-source software for graphs and networks. In the network, nodes are compounds and targets, and edges are interactions between the nodes. The edge is weighted according to the reliability of the interaction. In order to analysis the compound-target network, it is clustered using MCL algorithm, which is able to cluster the weighted network. A total of 130 clusters were created, and the number of nodes in the cluster with the largest number of nodes was 32. In the clustered network, it was revealed that the active compounds of medicinal materials were associated with the targets for regulating the blood pressure in the kidney. In the future, we will clarify the mechanisms of oryeong-san by linking the information on disease databases and the network of this research.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.362-371
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• 2005

Similarity indexing and searching are well known to be difficult in high-dimensional applications such as multimedia databases. Especially, they become more difficult when multiple features have to be indexed together. In this paper, we propose a novel indexing method called the GB-index that is designed to efficiently handle complex similarity queries as well as relevance feedback in high-dimensional image databases. In order to provide the flexibility in controlling multiple features and query objects, the GB-index treats each dimension independently The efficiency of the GB-index is realized by specialized bitmap indexing that represents all objects in a database as a set of bitmaps. Main contributions of the GB-index are three-fold: (1) It provides a novel way to index high-dimensional data; (2) It efficiently handles complex similarity queries; and (3) Disjunctive queries driven by relevance feedback are efficiently treated. Empirical results demonstrate that the GB-index achieves great speedups over the sequential scan and the VA-file.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4780-4785
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• 2012

As many mobile devices such as smart phones and tablets are widely spread, optimized mobile video encoder used during video recording application is needed. In this paper, we implemented H.264/AVC base profile video encoder on a mobile device and empirically optimized control parameters of the encoder. As the experiment, we more than 100 test cases were designed with varying Lagrangian optimization, Hadamard Transform, search range, I-frame period, and reference frames. During the experiment, we measured picture quality, bit-rate, encoding time, motion estimation time, and power consumption. From the result, we can determine optimal values for the H.264 control parameters.

• Spatial Information Research
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• v.20 no.2
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• pp.117-127
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• 2012

The purpose of this study is to develop the auto-building algorithm of the Geometric Network Model(GNM), a topology model including geometric information because of the need to reflect the features' geometric characteristic into the topology model, which is for development of indoor 3D virtual model enabling queries. As the critical algorithm, the Straight Medial Axis Transformation(SMAT) algorithm is proposed in order to automatically extract the medial axis of features. The SMAT algorithm is generalized from the existing S-MAT algorithm and a range of target features where applicable is extended from simple polygons to weakly simple polygons which mean the polygons containing the inner ring inside. The GNM built automatically is finally printed out as the .csv file for easy access and w ide application in other systems. This auto-building algorithm of the GNM is available for plenty of cases such as finding a shortest path, guiding a route in emergency situation, and semantic analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.49-58
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• 2011

Recently, GIS(Geographic Information System) has been developed to personalized service for providing the specialized services that is aimed to personal user based on mobile communication. The existing GIS system provides comprehensive and simple information but GIS System for personalized service must provide the adjustive information through the personal interest profile based on POI(PoInt of Interest). This paper describes the intelligent retrieval geographical information service module for providing personal oriented geographic information service. Our proposal model consists of user preference profile, acquisition of POI through hybrid network (Wireless LAN, CDMA), service platform and implementation of prototype system. Implementation model can apply to the life information service like restaurant, oil station, convenient store and etc.

• Information Systems Review
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• v.10 no.2
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• pp.195-209
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• 2008

Customers' needs change every moment. Profitability of stores can't be increased anymore with an existing standardized chain store management. Accordingly, a personalized store management tool needs through prediction of customers' preference. In this study, we propose a recommending procedure using dynamic customers' preference by analyzing the transaction database. We utilize self-organizing map algorithm and association rule mining which are applied to cluster the chain stores and explore purchase sequence of customers. We demonstrate that the proposed methodology makes an effect on recommendation of products in the market which is characterized by a fast fashion and a short product life cycle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2067-2075
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• 2017

Lately big data processing is considered as an emerging issue. As a huge amount of data is generated, data processing capability is getting important. In processing big data, both Hadoop distributed file system and unstructured date processing-based NoSQL data store are getting a lot of attention. However, there still exists problems and inconvenience to use NoSQL. In case of low volume data, MapReduce of NoSQL normally consumes unnecessary processing time and requires relatively much more data retrieval time than RDBMS. In order to address the NoSQL problem, in this paper, an interworking scheme between NoSQL and the conventional RDBMS is proposed. The developed auto-mapping scheme enables to choose an appropriate database (NoSQL or RDBMS) depending on the amount of data, which results in fast search time. The experimental results for a specific data set shows that the database interworking scheme reduces data searching time by 35% at the maximum.