• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.157-164
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• 2006

The Recently, most of Internet attacks are zero-day types of the unknown attacks by Malware. Using already known Misuse Detection Technology is hard to cope with these attacks. Also, the existing information security technology reached the limits because of various attack's patterns over the Internet, as web based service became more affordable, web service exposed to the internet becomes main target of attack. This paper classifies the traffic type over the internet and suggests the Threat Management System(TMS) including the anomaly intrusion detection technologies which can detect and analyze the anomaly sign for each traffic type.

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.169-176
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• 2000

This paper presents ENIG Agent can gather distributed educational newspaper information in the web as well as provide teachers and student those information for the NIE. ENIG Agent gleans newspaper headline of appropriate educational news portal site for real-time provision of those information. The optimized extraction of headline is performed through the pre-process of educational news site, information noise filtering, pattern matching. The educational newspaper headline information that is gotten through previous process will be shown to students by web-browser. To increase the usage of those information, intelligent education methods and visualized classification techniques are used. By experiment, the performance of this ENIG Agent was evaluated.

• Journal of Digital Contents Society
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• v.2 no.1
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• pp.21-30
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• 2001

This paper presents the automated component generation system to support development of web application by the Model 2 framework on distributed environment. Model 2 framework is based on MVC(Model View Controller) model and this model capsulate the functionality of web application and have the benefits like extensibility, maintainability, resuability. In this paper, we propose a framework which is adapted in JSP environment and implement the automated component generation system. This system can efficiently utilized for web application development which require extensibility, maintainability, resuability as well as rapid web application development.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.225-228
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• 2021

본 연구는 스마트폰 중독과 관련된 다양한 분석을 위한 스마트폰 사용 앱과 관리자 웹을 개발하고자 한다. 연구방법으로 이전 연구에서 중요한 변수로 작용되었던 '화면 켠 횟수', '실사용시간-인지사용시간' 변수를 분석할 있도록 적용하여 스마트폰 사용시간, 사용량, 사용 앱, 화면 잠금을 해제한 횟수 등 다양한 데이터 수집이 가능한 앱을 개발한다. 관리자 웹은 수집된 데이터를 저장, 분석할 수 있는 공간으로 사용할 것이다. 앱에서 수집된 데이터는 서버에 전송한 후, 시각화 분석 기능을 제공하는 관리 프로그램으로 개발하여 스마트폰 중독 연구에 사용한다. 향후 데이터 수집과 사용 목적에 동의한 사용자를 모집하여 데이터를 수집하고 스마트폰 사용 패턴, 데이터마이닝, 중독 등과 관련된 다양한 분석을 할 것이다. 이를 통해 보다 정확하고 효과적인 스마트폰 중독 진단이 가능해질 것과 나아가 스마트폰 중독 치료방안 연구에 기여할 것으로 기대한다.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.505-517
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• 2008

This paper proposes a rewriting algorithm of OWL-DL ontology query in SPARQL. Currently, to obtain inference results of given SPARQL queries, Web ontology repositories construct inference ontology models and match the SPARQL queries with the models. However, an inference model requires much larger space than its original base model, and reusability of the model is not available for other inferrable SPARQL queries. Therefore, the aforementioned approach is not suitable for large scale SPARQL query processing. To resolve tills issue, this paper proposes a novel SPARQL query rewriting algorithm that can obtain results by rewriting SPARQL queries and accomplishing query operations against the base ontology model. To achieve this goal, we first define OWL-DL inference rules and apply them on rewriting graph pattern in queries. The paper categorizes the inference rules and discusses on how these rules affect the query rewriting. To show the advantages of our proposal, a prototype system based on lena is implemented. For comparative evaluation, we conduct an experiment with a set of test queries and compare of our proposal with the previous approach. The evaluation result showed the proposed algorithm supports an improved performance in efficiency of the inferrable SPARQL query processing without loss of completeness and soundness.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.121-128
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• 2010

K-means clustering is an iterative algorithm in which items are moved among sets of clusters until the desired set is reached. K-means clustering has been widely used in many applications, such as market research, pattern analysis or recognition, image processing, etc. It can identify dense and sparse regions among data attributes or object attributes. But k-means algorithm requires many hours to get k clusters that we want, because it is more primitive, explorative. In this paper we propose a new method of k-means clustering using a center of gravity for grid-based sample. It is more fast than any traditional clustering method and maintains its accuracy.

• Korean Journal of Cognitive Science
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• v.15 no.3
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• pp.35-44
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• 2004

As the use of internet becomes proliferated, a great amount of information is provided through diverse channels. Users require effective information providing service and we have studied the conversational agent that exchanges information between users and agents using natural language dialogue. In this paper, we develop a question answering agent providing the corresponding answer by analyzing the user's intention using artificial intelligence techniques such as pattern matching and Bayesian network We work out various problems in knowledge representation of users by constructing keyword synonym database. The proposed method is applied to designing an agent for the introduction of a fashion web site, which confirms that it responds more flexibly to the user's queries.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.224-231
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• 2013

Defining the concept of prominent audio content as the most informative audio content from the users' perspective within a given unstructured audio segment, we propose a simple but robust intensity-based attack/release pattern features to detect the prominent audio content. We also propose a web-based annotation procedure to retrieve users' subjective perception and annotated 18 hours of video clips across various genres, such as cartoon, movie, news, etc. The experiments with a linear classification method whose models are trained for speech, music, and sound effect demonstrate promising - but varying across the genres of programs - results (e.g., 86.7% weighted accuracy for speech-oriented talk shows and 49.3% weighted accuracy for {action movies}).

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.463-471
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• 2010

The purpose of this study is to articulate learning model based on achievement level in blended learning environment. In order to investigate the variables and mechanisms in the blended learning environment, we started by attempt to develop two questionnaires using the components of web-based instruction and self-regulated learning. And its results were implemented to represent the topology and directed merging path within components. 154 students at a high school were required to take each web course respectively for two weeks. And questionnaires data, achievement levels data were collected and analyzed. Various statistical analysis methods such as correlation analysis, classical multidimensional scaling, multiple regression analysis, were applied to the data. As an result, the topology and directed path within factors of blended learning process were derived and revised as a final model.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.473-480
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• 2006

Recently, remote education systems for web-based teaching-studying are rapidly increased. Also, a request for customized courseware suitable for individual learner's level and learning pattern is increasing. But, most remote education systems do not provide customized learning service fit for each learner's level and lots of learners easily lose their interest in studying. Therefore, a lot of researchers have tried to provide personalized customized learning service by analyzing leaner's level and learning pattern automatically with agents. In this paper, we designed and implemented a customized courseware for studying the computer application. There are four agents such as professor, assistant, student, and monitor agent in CCA and they cooperate with each other to provide learning contents suited to each learner's level.