• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.271-279
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• 2001

Sequential pattern discovery is one of main interests in web usage mining. the technique of sequential pattern discovery attempts to find inter-session patterns such that the presence of a set of items is followed by another item in a time-ordered set of server sessions. In this paper, a tree-based sequential pattern finding method is proposed in order to discover navigation patterns in server sessions. At each learning process, the suggested method learns about the navigation patterns per server session and summarized into the modified Rymon's tree.

• The KIPS Transactions:PartC
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• v.11C no.6 s.95
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• pp.719-724
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• 2004

Recently, since the number of internet users is increasing rapidly and, by using the public hacking tools, general network users can intrude computer systems easily, the hacking problem is getting more serious. In order to prevent the intrusion, it is needed to detect the sign in advance of intrusion in a positive prevention by detecting the various foms of hackers' intrusion trials to know the vulnerability of systems. The existing network-based anomaly detection algorithms that cope with port- scanning and the network vulnerability scans have some weakness in intrusion detection. they can not detect slow scans and coordinated scans. therefore, the new concept of algorithm is needed to detect effectively the various forms of abnormal accesses for intrusion regardless of the intrusion methods. In this paper, SPAD(Session Pattern Anomaly Detector) is presented, which detects the abnormal service patterns by comparing them with the ordinary normal service patterns.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.6-8
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• 2022

Web log analysis is one of the essential procedures for service improvement. ScienceON is a representative information service that provides various S&T literature and information, and we analyze its logs for continuous improvement. This study aims to analyze ScienceON web logs recorded in May 2020 and May 2021, dividing them into humans and web crawlers and performing an in-depth analysis. First, only web logs corresponding to S (search), V (detail view), and D (download) types are extracted and normalized to 658,407 and 8,727,042 records for each period. Second, using the Python 'user_agents' library, the logs are classified into humans and web crawlers, and third, the session size was set to 60 seconds, and each session is analyzed. We found that web crawlers, unlike humans, show relatively long for the average behavior pattern per session, and the behavior patterns are mainly for V patterns. As the future, the service will be improved to quickly detect and respond to web crawlers and respond to the behavioral patterns of human users.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.182-186
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• 2017

Maintaining a proper lookout activity routine is integral to preventing ship collision accidents caused by human errors. Various subjective measures such as interviewing, self-report diaries, and questionnaires have been widely used to monitor the lookout activity patterns of navigators. An objective measurement of a lookout activity pattern classification system is required to improve lookout performance evaluation in a real navigation setting. The purpose of this study was to develop an objective navigator lookout activity classification system using wearable accelerometers. In the training session, 90.4% accuracy was achieved in classifying five fundamental lookout activities. The developed model was then applied to predict real-lookout activity in the second session during an actual ship voyage. 86.9% agreement was attained between the directly observed activity and predicted activity. Based on these promising results, the proposed unobstructed wearable system is expected to objectively evaluate navigator lookout patterns to provide a better understanding of lookout performance.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.843-849
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• 2003

Web usage mining is the technique of data mining that analyzes web users' usage patterns by large web log. To use the web usage mining technique, we have to classify correctly users and users session in preprocessing, but can't classify them completely by only log files with standard web log format. To classify users and user session there are many problems like local cache, firewall, ISP, user privacy, cookey etc., but there isn't any definite method to solve the problems now. Especially local cache problem is the most difficult problem to classify user session which is used as input in web mining systems. In this paper we propose a heuristic method which solves local cache problem by using only click stream data of server side like referrer log, agent log and access log, classifies user sessions and completes session.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.9-16
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• 2005

Recently, since the number of internet users is increasing rapidly and, by using the Public hacking tools, general network users can intrude computer systems easily, the hacking problem is setting more serious. In order to prevent the intrusion. it is needed to detect the sign in advance of intrusion in a Positive Prevention by detecting the various forms of hackers intrusion trials to know the vulnerability of systems. The existing network-based anomaly detection algorithms that cope with port-scanning and the network vulnerability scans have some weakness in intrusion detection. they can not detect slow scans and coordinated scans. therefore, the new concept of algorithm is needed to detect effectively the various. In this Paper, we propose a detection algorithm for session patterns and FCM.

• Journal of muscle and joint health
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• v.23 no.1
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• pp.61-69
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• 2016

Purpose: The purpose of this study was to determine the effect of the Tai Chi exercise program (Sun style 31 forms) on fatigue, anxiety, and sleep patterns in nursing students. Methods: A quasi-experimental study with a non-equivalent control group pretest-posttest design was used. Nursing students who participated in this study were assigned to an experimental group (n=24), and a control group (n=26). The experimental group participated in Tai Chi exercise program for 60 minutes per session, and 3 times a week for 7 weeks. The Tai Chi exercise program consisted of 10 minutes for warm-up, 45 minutes for main session, and 5 minutes for cooling down exercises. The data were collected prior and after the intervention using self-administered questionnaires. Data were analyzed using descriptive statistics, $x^2$-test, Fisher's exact probability, t -test, and the general linear model. Results: After the application of the program, the experimental group showed a significant difference in fatigue (F=20.62, p<.001), anxiety (F=16.96, p<.001), and sleep pattern (F=15.70, p<.001) scores. Conclusion: These findings show that the Tai Chi exercise program can be an effective nursing intervention to improve sleep pattern and to reduce fatigue and anxiety in nursing students.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7C
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• pp.971-984
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• 2004

In the coming age of information warfare, information security patterns need to be changed such as to the active approach using offensive security mechanisms rather than traditional passive approach just protecting the intrusions. In an active security environment, it is essential that, when detecting an intrusion, the immediate confrontation such as analysing the intrusion situation in realtime, protecting information from the attacks, and even tracing the intruder. This paper presents an active intrusion-confronting system using a fake session and a honeypot. Through the fake session, the attacks like Dos(Denial of Service) and port scan can be intercepted. By monitoring honeypot system, in which the intruders are migrated from the protected system and an intrusion rule manager is being activated, new intrusion rules are created and activated for confronting the next intrusions.

• PNF and Movement
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• v.14 no.2
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• pp.149-155
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• 2016

Purpose: The purpose of this study was to investigate the effects of using proprioceptive neuromuscular facilitation (PNF) exercise in the progressive sitting position on the dynamic balance ability of a patient with a cerebellar injury. Methods: The subject had ataxia due to cerebellar injury. The subject participated in a PNF bilateral scapular pattern exercise with stabilizing reversal technique during a progressive sitting position session as well as baseline for 20 minutes a day for 4 weeks. In the first session, PNF exercises were performed at a height of 40 cm for 10 minutes, and in the second session they were performed at 50 cm for 10 minutes from a lower center of gravity (COG) to a higher COG sitting position. We used the Berg Balance Scale (BBS), Five-Times-Sit-to-Stand Test (FTSST), and the Timed Up and Go Test (TUGT) to measure the subject's dynamic balance ability every two days through the entire session. Results: After participating in the program, the subject's dynamic balance ability improved compared to the first baseline, as measured by BBS (2 points increased), FTSST (5.3 sec decreased), and TUGT (2 sec decreased). The increase was also maintained in the second baseline session. Conclusion: PNF exercise using bilateral scapula patterns with a stabilizing reversal technique helps to enhance the dynamic balance ability of a cerebellar injury patient.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.403-405
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• 2001

In an EJB 1.1 specification, every method call made to the Enterprise Java Bean, is potentially remote call. Such remote invocations use the network layer regardless of the proximity of the client to the bean, creating a network overhead. Especially. because entity bean is more notable performance fail by remote call than session bean, frequency of use on Session Bean in work-site operations is much more than Entity Bean. We focus on how to improve the performance on the entity bean with Value Object, which is one of J2EE patterns suggested by Sun Microsystems. We presents related design-issues fur performance testing, the testing results compared with original entity bean and our findings.