• Journal of Navigation and Port Research
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• v.28 no.5
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• pp.455-462
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• 2004

Recently, according to the increase of personal income and enough time to spare. people demand the expansion of waterfront space in the city and the development of waterfront's possibility. In this study, which takes a place of the Jeol-young seaside park in young-do investigated for the user's pattern of seaside park located in coastal area And analyzed into user's attributes and a feeling of satisfaction The results of this study were as follows ： 1) The Jeol-young seaside park is facilitated for taking a walk. It also tends to be preferred for the ocean view, jogging, relaxation, and so on 2) The Jeol-young seaside park has to be ensured with its safety and convenience of esplanade. In order to provide the user's high satisfaction, more facilities of expansion and parking area are demanded to be developed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.11
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• pp.934-936
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• 2013

A routing scheme for a group of mobile users for wireless ad-hoc networks is presented. The proposed scheme mines social activity patterns from wireless traces, and exploits social user group for efficient data routing among users based on a data publish approach. Simulation results based on real-world wireless traces show that our routing scheme reduces routing cost for a large mobile user group with a factor of 1.8 compared to a baseline counterpart.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1726-1732
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• 2007

The rapid proliferation of wireless networks and mobile computing applications has changed the landscape of network security. Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. This paper presents an efficient rough set based anomaly detection method that can effectively identify a group of especially harmful internal attackers - masqueraders in cellular mobile networks. Our scheme uses the trace data of wireless application layer by a user as feature value. Based on this, the used pattern of a mobile's user can be captured by rough sets, and the abnormal behavior of the mobile can be also detected effectively by applying a roughness membership function with the age of the user profile. The performance of the proposed scheme is evaluated by using a simulation. Simulation results demonstrate that the anomalies are well detected by the proposed scheme that considers the age of user profiles.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.476-479
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• 2005

The information available on the Internet has become widely used, primarily due to the ability of Web based E-Commerce and M-Commerce Retrieval Engines to find useful information for users. However, present day Commerce Retrieval Engines are far from perfect because they return results based on simple user keyword matches without any regard for the concepts in which the user is interested. In this thesis, we design and evaluate a Recommender system for web context aware based information retrieval using user profiles. Also, we designed personalization framework in ubiquitous environment based both e-commerce and m-commerce and presented the interaction of user profile including User XQuery pattern in semantic web.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.315-326
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• 2007

The rapid proliferation of wireless networks and mobile computing applications has changed the landscape of network security. Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. This paper presents a dynamic anomaly detection scheme that can effectively identify a group of especially harmful internal masqueraders in cellular mobile networks. Our scheme uses the trace data of wireless application layer by a user as feature value. Based on the feature values, the use pattern of a mobile's user can be captured by rough sets, and the abnormal behavior of the mobile can be also detected effectively by applying a roughness membership function with both the age of the user profile and weighted feature values. The performance of our scheme is evaluated by a simulation. Simulation results demonstrate that the anomalies are well detected by the proposed dynamic scheme that considers the age of user profiles.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.553-556
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• 2000

This paper suggests the way to perform the handover by predicting the movement route of the mobile terminal by considering the movement pattern of the user. By considering the fact that the most users has the constant movement pattern, the channels needed fur the handover can be reserved, and the required quality of service (QoS) is maintained during handover. The suggested algorithm makes the channel allocation schemes more efficient.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.838-841
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• 2005

DNA Chip is able to show DNA-Data that includes diseases of sample to User by using complementary characters of DNA. So this paper studied Neural Network algorithm for Image data processing of DNA-chip. DNA chip outputs image data of colors and intensities of lights when some sample DNA is putted on DNA-chip, and we can classify pattern of these image data on user pc environment through artificial neural network and some of image processing algorithms. Ultimate aim is developing of pattern classifying algorithm, simulating this algorithm and so getting information of one's diseases through applying this algorithm. Namely, this paper study artificial neural network algorithm for classifying pattern of image data that is obtained from DNA-chip. And, by using histogram, gradient edge, ANN and learning algorithm, we can analyze and classifying pattern of this DNA-chip image data. so we are able to monitor, and simulating this algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.598-602
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• 2001

Recently, due to the widely use of personal computers and internet, many computer users requested intelligent system that can cope with various types of requirements and user-friendly interfaces. Based on this background, researches on the intelligent agent are now activating in various fields. In this paper, we modeled, designed and implemented an intelligent agent system for pattern classification by adopting intelligent agent concepts. We also investigated the pattern classification method by utilizing some pattern classification algorithms for the common data. As a result, we identified that 300 3-dimensional data are applied to three pattern classification algorithms and returned correct results. Our system showed a distinguished user-friendly interface feature by adopting various agents including graphic agent.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.1
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• pp.173-200
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• 2015

This study is to seek a development plan in the borrowed book and current condition of operation of J-do provincial library. Based on library use card issuer 30,072 people and the number of lending books 705,447(2012 to 2013) of J-do provincial library, it was to analyzed elemental and comparative research for library development plan and user satisfaction. Method of analysis used SPSS statistics 21. This confirmed provincial library user's library user behavior and usage pattern of data. Based on the results of analytics, it indicated a development plan of J-do provincial library.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.21-26
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• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the user's access pattern to web site and their following purchasable items and improves their web page on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning, it employs Apriori algorithm, which is a method that searches the association rule. It reasons the web pages by considering the user's access pattern and time by using the web log and reasons the user's purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of user's web pages and displays the inferred goods on user's web pages.