• Proceedings of the Korean Information Science Society Conference
• /
• 2000.10c
• /
• pp.493-495
• /
• 2000

인터넷의 급속한 증가는 네트워크상의 트래픽 형성에 중요한 변화를 가져오게 되었다. 통신 성능 향상을 지원하는 과정에서 여러 가지 통신상의 이상 현상들이 발생하게 되었으며, 그로 인한 통신상의 성능 문제에 부딪히게 되었다. 본 논문에서는 이러한 네트워크상의 비정상적인 트래픽의 예 중에서 비순서적 도착(Out-of-Order)에 대해서 실험을 하였으며, 트래픽 컨디셔너라는 개념과 이 개념을 도입한 독립형 구현 모델을 이용해서 네트워크상의 통신 성능을 개선하는 방법에 대해서 설명한다.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.23 no.2
• /
• pp.116-124
• /
• 2003

• Journal of the Korean Society of School Health
• /
• v.23 no.2
• /
• pp.256-265
• /
• 2010

Purpose: The purpose of this study was to identify the psychological problems of the children in early stage and provide basic data for develop the children's mental health promotion programs. Methods: There were 270 subjects who were fist and forth grade of elementary school and the data was collected through their parents. This study use Child Problem-Behavior Screening Questionnaire that was divided into five sub-scales, including internal problems, external problems, cognitive problems, abuse problems and psychosomatic problems. Each sub-scales have one cutting points, children whose scores above the cutting points means abnormal in correspond subscale. Results: 1) The most appearing problems was psychosomatic problems with 10.8% of subjects and next internal problems with 8.6% of subjects in elementary school student. 2) For distribution of mental behavior development according to gender, there was significant difference in psychosomatic problems between male and female (p =.009). 3) For distribution of mental behavior development according to grade, the results showed that significant difference in internal problems (p =.000) and total scores of CPSQ (p =.012) between first grade and forth grade. Conclusion: When we develop children's mental health promotion program, it is necessary to considerate the gender and grade characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.5
• /
• pp.978-985
• /
• 2003

The implementation of abnormal behavior detection IDS is more difficult than the implementation of misuse behavior detection IDS because usage patterns are various. Therefore, most of commercial IDS is misuse behavior detection IDS. However, misuse behavior detection IDS cannot detect system intrusion in case of modified intrusion patterns occurs. In this paper, we apply data mining so as to detect intrusion with only audit data related in intrusion among many audit data. The agent in the distributed IDS can collect log data as well as monitoring target system. False positive should be minimized in order to make detection accuracy high, that is, core of intrusion detection system. So We apply data mining algorithm for prediction of modified intrusion pattern in the level of audit data learning.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.248-255
• /
• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels. however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results are clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the firstpart are used to prepare a set of data for learning process. Tunnel behavior especially the displacements of the lining has been exclusively investigated for the back analysis.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.5 no.3
• /
• pp.191-201
• /
• 2001

In spite of the increasing construction of segmental PSC box girder bridges, the techniques associated with real-time monitoring, construction control and safety assessment during construction have been less developed compared with the construction techniques. Thus, the development of an integrated system including real-time measurement and monitoring, control and safety assessment system during construction is necessary fur more safe and precise construction of the bridges. This study presents a prototype integrated monitoring system for preventing abnormal behavior and accidents under construction stages, that consist of behavior control system for precise construction, reliability-based safety assessment system, and structural analysis. Also, a prototype software system is developed on the basis of the proposed model. It is successfully applied to the Sea-Hae Grand Bridge built by FCM. The integrated system model and software system can be utilized for the safe and precise construction of segmental PSC bridges during construction.

• Korean Journal of Community Nutrition
• /
• v.5 no.4
• /
• pp.608-614
• /
• 2000

The purpose of this study was to evaluate the relative importance among various biological and environmental factors on refractive errors. Various factors such as diseases, health related behavior such as drinking, smoking and exercise, as well as dietary factors were considered as a possible determinant. Surveys of 492 residents over 20 years of age in Kuri city were conducted during 1998. The survey included a refractive error test adopting a autokerato-refractometer, dietary survey using a 24 hour recall method, disease survey including blood and other diagnosis tests, and a health behavior survey using questionnaires with variables of smoking, drinking, and exercise. A stepwise logistic regression analysis was adopted to analyse the relative importance among independent variables of health behaviors, disease, and dietary factors on ametropias. As a result, in the case of myopia, liver dysfunction appeared to be the most important factors followed by the health related behavior of smoking and exercise as the second most important factors. Nutrient factors such as carotene and protein appeared to be the third most important factors. Similar results had been shown in the case of the hyperopia. In summary, liver dysfunction and the health related behaviors of drinking and smoking appeared to be more influential factors on abnormal eye sight of myopia and hyperopia than dietary factors.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.10
• /
• pp.219-228
• /
• 2021

The study examines the behavior of stock prices after large price changes. It further examines the effect of firm size on stock returns, and the presence of the disposition effect. The study employs the event study methodology using daily price data from Pakistan Stock Exchange (PSX) for the period January 2001 to July 2012. Furthermore, to examine the factors that explain stock price behavior after large price movements, the study employs a two-way fixed-effect model that allows for the analysis of unobservable company and time fixed effects that explain market reversals or continuation. The findings suggest that winners perform better than losers after experiencing large price shocks thus showing a momentum behavior. In addition, the winners remain the winner, while the losers continue to lose more. This suggests that most of the investors in PSX behave rationally. Further, the study finds no evidence of disposition effect in PSX. The investors underreact to new information and the prices continue to move in the direction of initial change. The pooled regression estimates show that firm size is positively related to post-event abnormal returns while the fixed-effect model reveals the presence of unobservable firm-specific and time-specific effects that account for price continuation.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.27 no.4
• /
• pp.181-186
• /
• 2023

In this study, considering the expansion/contraction behavior of the upper structure at all times and the abnormal behavior of the receiving friction elements that allow horizontal movement during earthquakes, a port receiving test body simulating the protrusion of the friction elements was created and the modulus performance was evaluated. In order to confirm the influence of the friction element's projection, the friction element's degree of separation was divided into four stages, and the shear behavior of the test specimen and the friction coefficient were confirmed. As a result of the experiment, it was found that the friction load increases as the protrusion degree of the friction element increases. On the other hand, as the degree of protrusion of the coefficient of friction increases, the coefficient of friction also increases. It was confirmed that damage to the friction elements during use increases the coefficient of friction, hinders smooth expansion and contraction of the upper structure, and causes stress concentration at the fixed-end support.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.9
• /
• pp.1266-1271
• /
• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.