• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.129-140
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• 2002

This paper develops a dynamic structural equation model, which captures relationships among socio-demographics, activity participation(i.e., time use) and travel behavior in consideration with time variation effects. The data used in developing the model are two waves(the year 1991 and 1992) from Puget Sound Transportation Panel (PSTP). which is surveyed in Puget Sound Region in United States. The PSTP is widely used in transportation behavior analysis and includes various information of traveler's socio-economic, travel patterns, and activity participation. In the model, we use 10 endogenous variables including activity participations and travel behaviors and 10 exogenous variables composed of time variant and invariant traveler's socio-demographic variables. The empirical model shows that strong relationships exist not only between socio-demographics and travel behavior, but between waves. We also confirm needs of panel data set to identify and understand time variation effects and travel behaviors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1481-1488
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• 2018

As female gamers are rapidly increasing, the misogyny and the misandry in game playing situation are also increasing. Recent #Gamergate and GodGunbae incident exhibit that such discriminative/hate behaviour in game playing can be developed into real physical threat or crime. In this paper, we investigate and analyze young Korean game players on how the attackers group, victims group, and gender-issue-indifferent group behave differently in game playing through survey. We found that male gamers had high hostile sexism against female gamers especially on females' game attitude and streotyped hatred with respect to the gender ${\times}$ group interaction. In big-5 personality test, however, it is not clear if attackers and victims had a noticeable different personality patterns. In result, we verify that there exist gender stereotype and high hostile sexism among young Korean gamers. Active gender-equality education on their adolescent period is necessary to avoid such destructive hatred in game playing.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.21-30
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• 2021

Unlike behaviors that are generally known, information regarding unspecific behaviors is insufficient. For an education or guidance regarding the unspecific behaviors, collection and management of data regarding the unspecific behaviors of special-needs students are needed. In this paper, a consultation management model based on behavior classification of special-needs students using machine learning is proposed. It collects data by photographing the behavior of special students in real time, analyzes the behavior pattern, composes a data set, and trains it in the suggestion system. It is possible to improve the accuracy by comparing the behavior of special students photographed later into the suggestion system and analyzing the results by comparing it with the existing data again. The test has been performed by arbitrarily applying unspecific behaviors that are not stored in the database, and the forecast model has accurately classified and grouped the input data. Also, it has been verified that it is possible to accurately distinguish and classify the behaviors through the feature data of the behaviors even if there are some errors in the input process.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.171-183
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• 2007

Urban transport demand is derived from activity participation. A variety of individual daily activities based on the decisions on activity participation result in collective spatial behavior. The travel derived from the effort to overcome the spatially distributed locations of adjacent activities represents the detailed structural relationships among activities. An activity-based approach provides an important framework of analyzing contemporary urban daily life in the sense that it studies the interaction between individuals' daily decision making and social practice in time and space, on the one hand, and socio-spatial environment on the other. The current study identifies representative patterns of urban daily activity implementations and analyzes the correlation between representative patterns and individuals' characteristics and contextual characteristics. The study shows that urban daily activity patterns can be grouped in a limited number of representative patterns, which are systematically correlated with socio-spatial characteristics. The results provide related transportation policy implications.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.259-263
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• 2008

임베디드 기기에서 로그데이터란 사용자의 기기 사용 이력에 대한 하드웨어적인 기록이라 할 수 있고, 로그분석이란 이 로그데이터를 기반으로 다양한 정보를 추출해 내는 것이다. 하지만 기존 로그데이터는 사용자의 행위에 대한 모든 기록에 대한 나열에 그쳤기 때문에 실제 사용자 행동 패턴이나 사용성에 대한 분석을 하기 위해서는 방대한 로그데이터를 활용하는데 많은 어려움이 있었다. 이에 본 논문은 이러한 사용자의 행동에 대한 체계적인 분석과 임베디드 기기 S/W와 H/W 연동성을 높이기 위하여 새로운 로그데이터 포맷에 대한 연구를 수행하였다. 이는 다양한 임베디드 기기의 분석을 위한 효율성과 효과성을 증대하는데 기여할 것이다.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.1-13
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• 2009

Intrusion detection is a process that identifies the attacks and responds to the malicious intrusion actions for the protection of the computer and the network resources. Due to the fast development of the Internet, the types of intrusions become more complex recently and need immediate and correct responses because the frequent occurrences of a new intrusion type rise rapidly. Therefore, to solve these problems of the intrusion detection systems, we propose a sequential pattern miner for analysis of the alert data in order to support intelligent and automatic detection of the intrusion. Sequential pattern mining is one of the methods to find the patterns among the extracted items that are frequent in the fixed sequences. We apply the prefixSpan algorithm to find out the alert sequences. This method can be used to predict the actions of the sequential patterns and to create the rules of the intrusions. In this paper, we propose an extended prefixSpan algorithm which is designed to consider the specific characteristics of the alert data. The extended sequential pattern miner will be used as a part of alert data analyzer of intrusion detection systems. By using the created rules from the sequential pattern miner, the HA(high-level alert analyzer) of PEP(policy enforcement point), usually called IDS, performs the prediction of the sequence behaviors and changing patterns that were not visibly checked.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5B
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• pp.489-499
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• 2003

This paper is a study about Honey-pot Model using CPN(Colored Petri Nets) that is a method of intrusion detection. Suggested Honey-pot model consists of two parts : \circled1 security kernel module for active induction of hacker's intrusion, intrusion detection and behavior pattern analysis. \circled2 virtual module for activity of induced hackers. However, suggested model was compared and analysed with conventional Denning model and Shieh nodel. The Honey-pot model using CPN can classify the characteristic of intrusion pattern, modeling intrusion pattern and pattern matching procedure, detect DDoS attack through multi hosts, and provide basis of study model for analysing intrusion pattern, finally.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.11a
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• pp.39-40
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• 2011

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.62-68
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• 2012

Steady-State Visually Evoked Potentials (SSVEP) are natural response signal associated with the visual stimuli with specific frequency. By using SSVEP, occipital lobe region is electrically activated as frequency form equivalent to stimuli frequency with bandwidth from 3.5Hz to 75Hz. In this paper, we propose an experimental paradigm for analyzing EEGs based on the properties of SSVEP. At first, an experiment is performed to extract frequency feature of EEGs that is measured from the image-based visual stimuli associated with specific objective with affordance and object-related affordance is measured by using mirror neuron system based on the frequency feature. And then, linear discriminant analysis (LDA) method is applied to perform the online classification of the objective pattern associated with the EEG-based affordance data. By using the SSVEP measurement experiment, we propose a Brain-Computer Interface (BCI) system for recognizing user's inherent intentions. The existing SSVEP application system, such as speller, is able to classify the EEG pattern based on grid image patterns and their variations. However, our proposed SSVEP-based BCI system performs object pattern classification based on the matters with a variety of shapes in input images and has higher generality than existing system.

• Journal of Animal Environmental Science
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• v.12 no.1
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• pp.13-20
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• 2006

This experiment was carried out to determine the effect of breed and sex on behavioral characteristics and economic traits of performance-tested pigs. Totally 32 tested pigs in 4 different breeds were assigned for behavioral observation. Behavior was recorded for 4 hours(each 2 hours, before and after none) of tested pigs in each tested pen. The average daily gain, age at 90 kg and feed efficiency on the basis of the performance data were collected from 8,477 performance-tested pigs in which pure breeds of Duroc, Yorkshire, Landrace and Berkshire at the Korea Swine Testing Station. The results obtained in this study are summarized as follows; The effect of breed was statistically significant for all traits studied. Average daily gain were the highest(P<0.05) in Duroc and ages at 90 kg were the highest(P<0.05) in Berkshire. In feed efficiency of male, Landrace and Yorkshire were the most efficient. The average daily gain and feed efficiency were superior to those of female, however, the age at 90 kg was not different. Overally, females were superior to males in various traits examined. Berkshire breed had more proportion of time spent in ventral tying and sitting whereas the proportion of time spent in walking, drinking and eating was less than that of other breeds. The male pigs showed more time spent in standing and social behavior.