• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.11
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• pp.1753-1758
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• 2013

A debate over the association between dietary patterns and obesity is not settled in the literature. Some studies suggest that there are significant differences in the mean body mass index (BMI) across dietary patterns, while others refute the result. Therefore, we extended this line of study to examine whether the influence of dietary pattern is strong enough to affect the incidence of obesity based on the criterion, BMI=25. We identified 3 dietary patterns using a cluster analysis of food intake data obtained from the food frequency survey conducted as a part of Korean genome epidemiologic study: 'variety', 'unrefined grain', and 'rice' dietary patterns. A Cox Hazard regression result showed that the all the dietary pattern variable parameters were not significant. Hence, it was concluded that the dietary patterns do not affect the incidence of obesity under the control of variables, such as age, energy intake, and etc.

• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.649-652
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• 2010

교육시설에 BTL사업이 활성화됨에 따라 해당 사업의 규모가 급격히 확대되고 있다. 이에 교육시설 설계에 있어서 창의적이고 효율적인 대안설계를 제안해야함에 따라 설계VE 영역의 중요성이 부각되어 활발하게 진행되고 있다. 현재의 설계VE 진행절차는 준비단계, 분석단계, 실행단계로 이어지며 각 단계별로 다양한 운용기법과 분석방법으로 진행되고 있다. 특히 그동안 진행되었던 다수의 교육시설 설계VE 사례를 살펴본 바에 의하면, 설계VE 과정에서 VE대상 선정 시 동일하거나 유사한 방법이 나타나고, 최종 대안 역시 프로젝트 별로 유사한 패턴을 보이고 있음에도, 기존 설계VE의 전 과정이 반복적으로 진행되고 있다. 따라서 본 연구는 이처럼 동일하거나 유사하게 나타나는 대안들을 유형화 하여 설계VE 절차를 간소화함으로써 VE활동 기간을 단축시켜 효율성을 높이고자 한다. 이를 위해 기존 교육시설 설계VE 사례들을 통해 다양한 VE대안들을 분석하여 유형별로 정리한다. 그 결과로 유사한 패턴이 나타나는 최종 대안들을 교육시설의 공간과 각 공간에 따른 공종별로 구분하여 유형화하고자 한다. 이는 교육시설 설계VE 활동 시 유형화 된 대안을 활용하여 기능분석 등의 단계를 생략함으로써 설계VE 활동 기간 단축과 투입 노력을 축소시키는 효과를 얻을 수 있을 것이며, 설계VE에 있어서 보다 효율적인 운용이 가능하게 될 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1673-1675
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• 2013

인간 활동의 전 영역을 총괄하는 대뇌정보기능을 대표하는 뇌파는 대뇌피질에서 발현된다고 알려져 있다. 의학적인 연구 결과에 의하면 인지 사고 등의 역동적인 지식 활동, 다양한 감성 행동, 및 고차원적인 정신활동까지도 뇌파 분석을 통해서 어느 정도는 기계적인 인식이 가능한 것으로 알려져 있다. 뇌-컴퓨터 인터페이스는 인간 중심의 시스템을 위한 핵심 연구로서 뇌파 신호 분석에 의한 사용자 의도 인식 시스의 개발을 목표로 한다. 이에 따라서, 범용적으로 적용 가능한 뇌파신호 분석 기법 및 자동 처리 시스템에 관한 연구가 활발히 진행 중이다. 특히, 뇌는 부위별로 그 기능이 세분화 되어 있으며 의식 상태와 정신활동에 따라 뇌파가 수시로 변하면서 특정한 패턴을 갖는다. 이러한 뇌의 정보처리 메커니즘을 밝혀내면 전자장치와의 통신 인터페이스를 통해 기기를 제어할 수 있다. 본 논문은 사용자의 의도를 분석하는 방법과 이를 통해 다른 장치의 인터페이스를 제어할 수 있는 시스템을 설계했다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.1-16
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• 2018

Changes in the life style might vary trip purposes, ultimately leading to the change in the travel behavior. Therefore, this study analyzed the factors affecting travel time change by using the time use survey data in Seoul, surveyed by the Statistics Korea in 1999~2014. We developed multiple linear regression models for travel time, considering individual, household and time-related variables as independent variables. The models were separately estimated weekday and weekend. the model results show that the household, individual, and time related variables have an significant effect on the travel time. In addition, travel time is more influenced by individual characteristics thn household ones. Each activity time positively affects the travel time, indicating that travel is derived demand. The variable that have the greatest influence on the travel time is the activity time for leisure.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.31-43
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• 2012

Domestic road type-and period-specific driving pattern measurement was required as Korea's participation in developing "Worldwide harmonized light-duty vehicle emission test procedure (WLTP/DHC)" studied by UN WP29. This study measured road driving data reflecting road and traffic conditions of Korea, and analyzed seven types of representative road type-and period-specific driving patterns with driving pattern standardization methodology proposed by WP29. PAMS (Portable Activity Monitoring Systems) equipment was used to collect enormous (35,410km) road driving data. There are significant difference among seven derived driving patterns.

• Spatial Information Research
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• v.23 no.2
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• pp.69-81
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• 2015

If one can infer the residential area of SNS users by analyzing the SNS big data, it can be an alternative by replacing the spatial big data researches which result from the location sparsity and ecological error. In this study, we developed the way of utilizing the daily life activity pattern, which can be found from timeline data of tweet users, to infer the residential areas of tweet users. We recognized the daily life activity pattern of tweet users from user's movement pattern and the regional cognition words that users text in tweet. The models based on user's movement and text are named as the daily movement pattern model and the daily activity field model, respectively. And then we selected the variables which are going to be utilized in each model. We defined the dependent variables as 0, if the residential areas that users tweet mainly are their home location(HL) and as 1, vice versa. According to our results, performed by the discriminant analysis, the hit ratio of the two models was 67.5%, 57.5% respectively. We tested both models by using the timeline data of the stress-related tweets. As a result, we inferred the residential areas of 5,301 users out of 48,235 users and could obtain 9,606 stress-related tweets with residential area. The results shows about 44 times increase by comparing to the geo-tagged tweets counts. We think that the methodology we have used in this study can be used not only to secure more location data in the study of SNS big data, but also to link the SNS big data with regional statistics in order to analyze the regional phenomenon.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.6
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• pp.1315-1324
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• 2012

Security visualization is a form of the data visualization techniques in the field of network security by using security-related events so that it is quickly and easily to understand network traffic flow and security situation. In particular, the security visualization that detects the abnormal situation of network visualizing connections between two endpoints is a novel approach to detect unknown attack patterns and to reduce monitoring overhead in packets monitoring technique. However, the session-based visualization doesn't notice a difference between normal traffic and attacks that they are composed of similar connection pattern. Therefore, in this paper, we propose an efficient session-based visualization method for analyzing and detecting between normal server activities and attacks by using the IP address splitting and port attributes analysis. The proposed method can actually be used to detect and analyze the network security with the existing security tools because there is no dependence on other security monitoring methods. And also, it is helpful for network administrator to rapidly analyze the security status of managed network.

• Journal of Korea Technology Innovation Society
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• v.21 no.1
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• pp.92-129
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• 2018

In general, a technology and innovation strategy has been established first. Then, the technology and innovation activities are conducted accordingly. The literature on the technology management process points out that the technology and innovation activities exist in some sequences, nonlinear or linear pattern. However, it is also argued that a certain technology and innovation activity can be occurred or disappeared at certain timing. In this paper, it has been analyzed and clarified how the technology and innovation activities are performed and working together with the technology and innovation strategies in certain context especially when the handset market moves from feature phone to smartphone during a last decade. Empirical results show that the starting point of the technology and innovation activity changes according to the technology and innovation strategies. And, technology innovation activities exhibit multi-layer architecture types. It is confirmed that technology and innovation activities follow a specific pattern. However, if there are some changes in the technology and innovation strategy due to the external environment change, some technology and innovation activities can be skipped because the priority of the technology and innovation activities would be changed. If the firm which has the strategy type of 'innovators' fails to adapt to the fast changing external environment and has the inadequate technology and innovation activities, it is required to change the technology and innovation strategy. It will have a huge impact on the firm's survival.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.795-798
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• 2017

근래에 들어, 웨어러블 기기의 발전으로 사람의 움직임에 대한 측정이 손쉬워 지면서, 워킹, 러닝, 사이클링 등의 인간의 신체 활동 상태를 감지하여 더 효율적인 운동을 할 수 있도록 정보를 획득, 제공하려는 연구가 계속되고 있다. 본 연구에서는 웨어러블 기기중 하나인 스마트 인솔을 통해서 수집되는 가속도 정보와 압력 정보를 사용하여 운동시에 사람의 운동 자세를 감지하고 측정하는 시스템을 구현하였다. 사람이 헬스센터에서 수행하는 각각의 자세는 운동의 특성에 따라 시계열 신호의 표현 패턴이 다르게 나타나며 이 패턴을 통한 정확한 자세의 감지를 위해서 본 연구에서는 다양한 신호처리 알고리즘을 사용하였으며 이 경우 더 정확한 자세를 측정할 수 있음을 알 수 있었다. 따라서 본 연구에서는 정확한 자세의 감지를 위해 운동의 특징에 따라 알고리즘을 선택하여 시계열 정보를 처리 분석 하는 시스템을 제안하였으며 이를 통해 보다 정확하게 사람의 신체활동을 분석할 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1340-1346
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• 2018

There have been researches on game continuance intention based on consumer behaviour theory of management science. Such macro access of computer game analysis might be insufficient to draw valuable results due to complex subsystem structure of recent computer games. In this paper, we choose 'Blade and Soul' game that was first published in 2012 and has been within top 20 MMORPG in Korea but known as a 'long time users' only game'among game players recently. Three user groups - long loyalty, concentrated, casual - are classified based on their play history and play time per day of Blade and Soul. The first survey with 222 subjects revealed that the real strength of the game was not the combat - Dungeon, Arena, Battleground competition - but very cohesive game community Blade and Soul has. Thus, we conduct another survey on the game community issues among 148 long time users (over 3 years playing history) and analyze their traits and behaviour patterns.