• Journal of Satellite, Information and Communications
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• v.11 no.1
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• pp.55-57
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• 2016

In this paper, we present an algorithm to determine the abnormal behavior through a CCTV-based behavioral recognition and a pattern of hand using ConvexHull. In the existing way that using CCTV for crime prevention, facial recognition is mainly used. Facial recognition is the way that compares the faces that are seen on the screen and faces of criminals for determining how dangerous targets are, however, this way is hard to predict future criminal behavior. Therefore, to predict more various situations, abnormal behaviours are determined with targets' incline of arms, legs and bodys and patterns of hand movements. it can forecast crimes when an acting has been getting within common normality out, comparing whose acting patterns with the crime patterns.

• Journal of the Korean Society of Clothing and Textiles
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• v.2 no.2
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• pp.253-260
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• 1978

The purpose of this study was to investigate whether or not the clothing behavior of house-wives in Seoul vary depending on their socioeconomic status. The null hypotheses tested in this study were as follows: 1) There are no differences in housewives' attitudes toward the importance of clothing according to their socioeconomic status. 2) There are no differences in housewives' criteria of clothing choice according to their socioeconomic status. 3) There are no differences in housewives' clothing taste according to their socioeconomic status. 4) There are no differences in the pattern of housewives' clothing purchase according to their socioeconomic status. In order to test these null hypotheses, questionnaires on clothing behavior and socioeconomic status were distributed to a sample of 243 purposively selected housewives in Seoul, Korea. The factor analysis, correlation and analysis of variance techniques were employed for the statistical analysis of data. The results indicated that: 1) The attitudes toward the importance of clothing was related to socioeconomic status. 2) The criteria of clothing choice (aesthetics-practicality), clothing taste (individuality-conformity), and the pattern of clothing purchase (a degree of rationality) were not related to socioeconomic status. 3) The criteria of clothing selection was related to housewives' level of education. 4) Clothing taste was related to housewives' age.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.183-190
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• 2012

PURPOSES : The fundamental diagram provides basic information necessary in the analysis of traffic flow and highway operation. When traffic flow is congested, the density-flow points in the fundamental diagram are widely scattered and move in a stochastic manner. This paper investigates the pattern of density-flow point transitions and identifies car-following behaviors underlying the density-flow transitions. METHODS : From a microscopic analysis of 722 fundamental diagrams of NGSIM data, a total of 20 transition patterns of fundamental diagrams are identified. Prominent features of the transition patterns are explained by the behavior of the leader and follower. RESULTS : It is found out that the average speed and the speed difference between the leader and the follower critically determine the density-flow transition pattern. The density-flow path is very sensitive to the values of vehicle speed and spacing especially at low speed and high density such that most fluctuations in the fundamental diagram in the congested regime is due to the noise of speed and spacing variations. CONCLUSIONS : The result of this study suggests that the average speed, the speed difference between the leader and the follower, and the random variations of speed and spacing are dominant factors that explain the transition patterns of a fundamental diagram.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.361-371
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• 2017

The increase in user data stored in the device implies the increase in threats of users' sensitive data. Currently, smartphone authentication mechanisms such as Pattern Lock, fingerprint recognition are widely used. Although, there exist disadvantages of inconvenience use and dependence that users need to depend on their own memory. User behavior based authentication mechanism have advantages of high convenience by offering continuous authentication when using the mobile device. However, these mechanisms show limitations on low accuracy of authentication and there are researches to improve the accuracy. This paper proposes improved authentication mechanism that uses user's smartphone application usage pattern which has not considered on earlier studies. Also, we analyze performance of proposed mechanism with collected datasets from actual use of smartphone applications.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.61-74
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• 2012

As the retail industry has been challenged by stiff competition, the retailer becomes more interested in better understanding consumers' in-store behavior to gain and sustain competitive advantage. Consumers' shopping paths provide valuable clues to understanding customers' in-store behavior, which has been a long standing research issue in business. This study is to explore the shopping path patterns in a grocery using RFID technology and clustering method. To this end, we designed the RFID systems, affixing active RFID tags to the bottom of grocery carts. The tag emit signal that is received by receptors installed at various location throughout the store. The RFID systems provide the time and location of the cart while consumers shop around the store. The point of sale data are matched with the cart movement records to provide a complete picture of each shopping path. To find the distinctive patterns of consumers' shopping paths, we proposed the distance-index matrix using dijkstra method and normalization method to conduct the clustering in order to handle the problem in measuring the similarity among shopping paths, which is raised by the spatial nature of consumer movement in a grocery. After analyzing the RFID data obtained in one of the groceries in a major Korean retailer, we could successfully identify several distinctive patterns of shopping paths, which prove to provide the valuable implications for store management.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.64-71
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• 2006

Electronic mail (E-mail) is an integral part of communication for the recent Internet users. However, e-mail has also come to serve as a means to support flood of unwanted spam mails and junk mails having bad purposes. This paper was conducted in order to develop an intelligent e-mail system using user behavior pattern that can prevent these unnecessary information and enable the user to enjoy communication via e-mail in a cleaner environment. The concentrated analysis of the user behavior in terms of using e-mail functions has resulted in better classification between unnecessary and necessary information, thereby facilitating faster disposal of spam mails.

• Journal of the Korean Society of Food Culture
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• v.20 no.2
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• pp.172-185
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• 2005

This study was carried out to investigate the information concerning dietary patterns and analysis of the various factors that influence obesity. The subjects of this study were 1,020 middle and high school students in Seoul. Subjects were classified into under weight, normal weight and over weight group by body mass index. We investigated eating habits, life habits, food behavior and food consumption. Data were collected by questionnair and analysed with the SAS program. The results of this study way are summarized and concluded as fellows; In the case of dietary pattern, over weight group showed significantly higher in skipping a meal than the other group. Also over weight group tend to eat fast. There were significant differences of food intake frequency score by body mass index. From the results of factor analysis of variable related to obesity, 4 factors were generated and the factors were named 'Food behavior related to obesity', 'Snack consumption pattern', 'Life habit', 'Family environment related to food habit'. These factors were associated with obesity. To maintain nutritional balance and health, we should implement to ensure good dietary patterns.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.4
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• pp.104-112
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• 1999

Tensile behavior in concrete has been neglected until recently. However, the effect of tensile stresses in concrete must be considered where the member primarily carries tensile forces or when ultimate strength is affected by the cracking history. In this paper, a series of experiments were performed with a reinforced rectangular beams of 15 specimens in order to investigate the effect of tension stiffening into the nonlinear analysis and cracking behavior. The experimental results were analyzed in terms of load-deflection curves and strain fracture energy with respect to the main experimental variables such as types of specimen, strength of concrete and steel ration. The results from experiments and finite element analysis were compared in terms of load-deflection relationship and cracking pattern. The results are as follows ; The tension stffening effects of reinforced concrete beams were observedc up to yielding of members after cracking showing strain energy difference of 35 % at the beam of 0.57% steel ratio compared with that of beam ignoring the tension stiffening effect. The tension stiffening of concrete strength 400kgf/$\textrm{cm}^2$ and 600kgf/$\textrm{cm}^2$ increased by 8% and 13%, respectively, compared with that of concrete strength 200kgf/$\textrm{cm}^2$. The tension stiffening effects were greater at a ductile member rather than a brittle one. The load-deflection results of finite element analysis showed very similar results from experiment. The crack growth and pattern might be predicted from the nonlinear finite element analysis considering concrete stiffening.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.139-146
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• 2008

It is very important to identify useful web user group and induce their behavior pattern in eCRM domain. Inducing user group with a similar inclination, a reliability of user group decreases because there is an uncertainty in online user data. In this paper, we have applied the 2-tier clustering, which uses the outcome of interaction with data from other tiers. Also we propose a method which induces user behavior pattern from a cluster and compare C4.5 with our method.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.520-537
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• 2019

This paper proposes a system that can detect the data leakage pattern using a convolutional neural network based on defining the behaviors of leaking data. In this case, the leakage detection scenario of data leakage is composed of the patterns of occurrence of security logs by administration and related patterns between the security logs that are analyzed by association relationship analysis. This proposed system then detects whether the data is leaked through the convolutional neural network using an insider malicious behavior graph. Since each graph is drawn according to the leakage detection scenario of a data leakage, the system can identify the criminal insider along with the source of malicious behavior according to the results of the convolutional neural network. The results of the performance experiment using a virtual scenario show that even if a new malicious pattern that has not been previously defined is inputted into the data leakage detection system, it is possible to determine whether the data has been leaked. In addition, as compared with other data leakage detection systems, it can be seen that the proposed system is able to detect data leakage more flexibly.