• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.461-464
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• 2006

With the development of internet technologies, internet has been more complexly consisted of a large amount of Web documents, science technology documents, data-base and etc. distributed system is required to support effective retrieval and management about a large amount of Web documents, science technology documents and etc. distributed system has to support for user to search quickly and exactly. distributed system has to support for manager to manage easy. This paper designed and made distributed system. these system effectively manages the science technology information documents. this paper made an experiment using a large mount of science technology information system. this paper analyzed the result of experimenting.

• Journal of Digital Contents Society
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• v.2 no.2
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• pp.191-197
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• 2001

The cyber university, which authoring systems for digital contents using multimedia technologies ate used for its courses, is highlighted to be a promising alternative for the current off-line education system. As the demand for the authoring system is constantly increasing, many systems, which emphasize the developers' convenience only, are currently used. Since the generated digital contents using these systems are failed to draw the learners' active interaction with contents, the new authoring system is expected to be existed. This paper presents, develops, and implements the new contents authoring system by using programing languages and/or software tools based on the storyboard. The presented, developed, and implemented system mimics the face-to-face education in off-line system, induces the users' active interaction with contents, and the effective evaluation system to the users.

• Genomics & Informatics
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• v.10 no.1
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• pp.33-39
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• 2012

High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.117-124
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• 2012

Recently, the trend of open innovation and web 2.0 change the information portal services. The importance of using information demand analysis is emphasized in planning service strategy. The issues of the study are how we can figure out the demand and how we can use it in enhancing service level. This study aims at presenting the result of green technology information users' interests and the service enhancement directions. For the information types, additive functions, open innovation needs, the relation between users' organization, main job title, and the involved technological area are analysed. Among them, the involved technological area of the user is correlated to the needs, so we illustrate the meaning of planning service strategy according to the technological fields. The main contribution of the study can be the customized service strategy proposal using the users' demand which can be different from one technology field to another.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.9-16
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• 2009

In ubiquitous spatial computing environments, GeoSensor generates sensor data streams including spatial information as well as various conventional sensor data from RFID, WSN, Web CAM, Digital Camera, CCTV, and Telematics units. This GeoSensor enables the revitalization of various ubiquitous USN technologies and services on geographic information. In order to service the u-GIS applications based on GeoSensors, it is indispensable to efficiently process sensor data streams from GeoSensors of a wide area. In this paper, we propose a GeoSensor data stream processing system for u-GIS computing over real-time stream data from GeoSensors with geographic information. The proposed system provides efficient gathering, storing, and continuous query processing of GeoSensor data stream, and also makes it possible to develop diverse u-GIS applications meet each user requirements effectively.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.757-766
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• 2009

This study presents an adaptive hypermedia learning system which can provide individual learning environment using a learner behavioral model. This system proposes a LBML which can manage learners' learning behavioral information by tracking down such information real-time. The system consists of a collecting system of learning behavioral information and an adaptive learning support system. The collecting system of learning behavioral information uses Web 2.0 technologies and collects learners' learning behavioral information real-time based on a SCORM CMI data model. The collected information is stored as LBML instances of individual learners based on a LBML schema. With the adaptive learning support system, a rule-based learning supporting module and an interactive learning supporting module are developed by analysing LBML instances.

• Journal of the Korea Computer Industry Society
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• v.2 no.8
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• pp.1109-1116
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• 2001

This paper describes a mechanism and its aspects for monitoring user actions and behaviors on the web operated under the layered architecture that utilizes intelligent agents, and by which personalized information services, for instance one-to-one marketing, is easily facilitated and developed. Intelligent agent is one of techniques which enables to automate the whole process for providing personalized services that includes monitoring, logging a user actions and analyzing behaviors based on his or her profiles, and then selecting, organizing customizable contents which are at last delivered to the users browser or mail box also by intelligent agents. Monitoring technologies can utilize to help better construct the process in providing personalized services in that those services require intelligence in operating. As a result, implementing effective personalized services, however, depends on how well to define various users interests and needs, and how correctly to detect and log the actions when hey are done by users.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.445-454
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• 2014

In recent days, trend technologies for cloud, bigdata, or mobile, as the important marketable keywords or paradigm in Information Communication Technology (ICT), are widely used and interrelated each other in the various types of platforms and web-based services. Especially, the combination of cloud and mobile is recognized as one of a profitable business models, holding benefits of their own. Despite these challenging aspects, there are a few application cases of this model dealing with geo-based data sets or imageries. Among many considering points for geo-based cloud application on mobile, this study focused on a performance test of mobile cloud of Bayesian image fusion algorithm with satellite images. Two kinds of cloud platform of Amazon and OpenStack were built for performance test by CPU time stamp. In fact, the scheme for performance test of mobile cloud is not established yet, so experiment conditions applied in this study are to check time stamp. As the result, it is revealed that performance in two platforms is almost same level. It is implied that open source mobile cloud services based on OpenStack are enough to apply further applications dealing with geo-based data sets.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.37-45
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• 2015

With advancement in information technologies and a better mobile environment, the paradigm of service is shifting again from web portals to networked-applications based on individual application programs. Furthermore, as more investment is being made in R&D, the efforts to enhance R&D productivity are becoming important. In this paper, we designed a personalized service model for developing a tool to assist researchers in their R&D activities. To do this, we first compared services and tools in terms of information activities of researchers in R&D. In addition, we also analyzed changes of information environment such as open expansion of information and data, enhancement of personal information protection, popularization of social networking service, very big contents, advances in web platform technology in terms of personalization, and defined some directions of developing a personalized service. Subsequently we designed a personalized service model of research support tool in the views of functions, contents, operation, and defined personalized design goals and principles for implementing it as standard, participation, and open.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1396-1405
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• 2020

Cyber threats such as forced personal information collection and distribution of malicious codes using malicious URLs continue to occur. In order to cope with such cyber threats, a security technologies that quickly detects malicious URLs and prevents damage are required. In a web environment, malicious URLs have various forms and are created and deleted from time to time, so there is a limit to the response as a method of detecting or filtering by signature matching. Recently, researches on detecting and predicting malicious URLs using machine learning techniques have been actively conducted. Existing studies have proposed various features and machine learning algorithms for predicting malicious URLs, but most of them are only suggesting specialized algorithms by supplementing features and preprocessing, so it is difficult to sufficiently reflect the strengths of various machine learning algorithms. In this paper, a system for predicting malicious URLs using multiple machine learning algorithms was proposed, and an experiment was performed to combine the prediction results of multiple machine learning models to increase the accuracy of predicting malicious URLs. Through experiments, it was proved that the combination of multiple models is useful in improving the prediction performance compared to a single model.