• 대한안전경영과학회지
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• 제17권3호
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• pp.205-213
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• 2015

This study aims to verify the structural correlation empirically between information security performance and information management performance. To verify the correlation, three factors such as managerial controlled activity, technical controlled activity, and physical controlled activity are divided for the information security activities variable. the security performance are divided into accident prevention and accident response variables. As a result, security organization activity is a unique factor being positively significant to information security and management performance. And three activities such as human security, security training, development security do not affect at all on both information security and management performance.

• 한국전자거래학회지
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• 제19권1호
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• pp.63-78
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• 2014

본 논문에서는 정보보호 거버넌스를 강조한 선행연구들을 바탕으로, 거버넌스 측면에서 가장 첫 번째에 해당하는 최고경영층의 정보보호에 대한 리더십이 정보보호 정책수립, 정보보호 조직과 인력 구성, 정보보호 교육 및 훈련, 기술적 대책 활동, 모니터링 및 감사활동 등과 같은 정보보호 통제활동에 어떤 영향을 주는 지에 대해 실증적으로 분석하고자 한다. 뿐만 아니라 최고경영층의 리더십과 비교되는 요인으로 조직 내에서 발생한 인터넷 침해사고 피해에 의해 정보보호 통제활동에 얼마나 차이가 있는지를 분석하여 시사점을 찾고자 한다.

• Asia pacific journal of information systems
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• 제10권4호
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• pp.37-56
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• 2000

This study proposes the concept and measurement of object-oriented systems modelling activity based on the previous research in the area of systems engineering, object-oriented modelling, and information systems. The modelling activity is related to information systems development success for exploring the correlation of each other. The object-oriented modeling activity is found to be related to user satisfaction with developed information systems, But the modeling activity does not have relation to the other successes, such as cost, development schedule, and maintenance. This study contributes to systems development modeling research, systems success, and object-oriented systems modelling research. Practically, the results support the usefulness of object-oriented modelling effort in the field in terms of user satisfaction.

• 한국컴퓨터정보학회논문지
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• 제24권8호
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• pp.95-103
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• 2019

According to the Statistics Korea in 2017, the 10 leading causes of death contain a cardiac disorder disease, self-injury. In terms of these diseases, urgent assistance is highly required when people do not move for certain period of time. We propose an unusual event detection algorithm to identify abnormal user behaviors using dust, vision and activity sensors in their houses. Vision sensors can detect personalized activity behaviors within the CCTV range in the house in their lives. The pattern algorithm using the dust sensors classifies user movements or dust-generated daily behaviors in indoor areas. The accelerometer sensor in the smartphone is suitable to identify activity behaviors of the mobile users. We evaluated the proposed pattern algorithms and the fusion method in the scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• 복식
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• 제61권7호
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• pp.51-66
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• 2011

The study is intended to suggest the differentiated and subdivided indexes of the leisure fashion market and to provide the marketing strategy establishment and in-depth understanding of leisure fashion business by looking into the correlation between and among fashion involvement, clothing selection criteria and fashion information sources. This study was conducted by the questionnaire response method and the results were derived by using the SPSS 16.0 statistics program. The results of the study were as follows; 1) As a result of researching the difference between the leisure activities consumer groups and fashion involvement, there were significant differences in emotional and cognitive involvement. In the tour activity group and social activity group, emotional involvement was found to be higher than the cognitive experience while in the hobby and sports activity group, both involvements were equally as high. 2) As a result of researching the difference between the leisure activities groups and clothing selection criteria, it was found that the intrinsic and extrinsic criteria were high in the hobby and sports activity group and that the intrinsic criteria was high in the tour activity group and social activity group. 3) In the difference between the leisure activity groups and fashion information sources, it was found that media source, observation source and experience/personal source were high in the hobby and sports activity group. In addition, the experience and personal source were high in the social activity group. 4) In the difference between and among fashion involvement, clothing selection criteria and fashion information sources, it was found that the emotional involvement, intrinsic criteria and observation source were higher in the group of females than males. 5) In the difference between and among fashion involvement, clothing selection criteria and fashion information sources depending on the ages of leisure activities consumers, it was found that the emotional involvement and observation source were high in the group of 20-24 yrs old consumers and that the emotional involvement, intrinsic criteria and observation source were high in the group of 25-29 yrs old consumers. Also, in the group of 30-34 yrs old consumers, the emotional involvement, observation source and experience/personal source were high.

• 한국산학기술학회논문지
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• 제17권11호
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• pp.302-313
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• 2016

본 연구는 기업에서 CEO의 내 외부 활동(정보, 지식경영, 학습조직)이 혁신활동(활용적, 탐색적)과 경영성과에 미치는 영향을 알아보기 위하여 국내 기업의 CEO 300명을 대상으로 설문조사를 토대로 통계분석을 하였다. 분석 결과 정보와 학습조직 활동은 활용적 혁신활동과 탐색적 혁신활동에 유의한 정(+)의 영향을 미치는 것으로 나타났으나, 지식경영 활동은 탐색적 혁신활동에서 통계적으로 유의미한 영향을 끼치지 못하였다. 또한, CEO 내 외부 활동에서 정보, 지식경영, 학습조직 활동의 영향을 받은 활용적, 탐색적 혁신활동은 기업의 경영성과에 유의한 정(+)의 영향을 미쳤으나 영향력의 세기는 차이를 보였다. 따라서 기업의 경영에서 CEO의 내 외부 활동 중에서 정보, 지식경영, 학습조직 활동에 의한 활용적 혁신과 탐색적 혁신활동 발현으로 경영성과를 극대화시키기 위한 모색은 선행 연구에서 지각된 활동을 기반으로 하여 기업의 경영 환경을 고려하여 유리한 활동을 추출하고 이를 경영 전략에 반영하는 것이 기업에서 최상의 경영성과 목표달성에 유리함을 본 연구결과에서 시사하고 있다.

• 대한안전경영과학회지
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• 제3권2호
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• pp.145-154
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• 2001

This paper deals with Activity Analysis Method that is important procedure in Activity Based Costing System Implementation. There are many existing Activity Analysis Method, for example Interview, Questionnaire, Specialist Discussion and Work Measurement. Activity Analysis Data gained through this method has high reliability but this method bring about high cost. In case that certain company needs a strategic costing system, Activity Analysis Method which has high reliability will be need. But, if companies want the costing system as a internal decision making tool only, they need to design the ABC system fast and cheaply. This paper explains that Activity Analysis using existing finn material is good alternatives. So, this paper show the feasibility of Activity Analysis using existing firm material with comparing between job description, job specification information and Activity Analysis information.

• Journal of Information Technology Applications and Management
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• 제26권2호
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• pp.111-123
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• 2019

In this paper, software activity, software activity instance, and the quality of the activity instance are defined as the 'activity which is performed on the software product by a person or a group of persons,' the 'distinctive and individual performance of software activity,' and the 'performer's evaluation on how good or bad his/her own activity instance is,' respectively. The representative values of the instance quality population associated with a product and its sub-population are defined as the (software) activity quality and activity quality characteristic of the product, respectively. The activity quality model in this paper classifies activity quality characteristics according to the classification hierarchy of software activity by the goal. In the model, a quality characteristic can have two types of sub-characteristics : Special sub-characteristic and component sub-characteristic, where the former is its super-characteristic too simultaneously and the latter is not its super-characteristic but a part of its super-characteristic. The activity quality model is parsimonious, coherent, and easy to understand and use. The activity quality model can serve as a corner stone on which a software quality body of knowledge, which constituted with a set of models parsimonious, coherent, and easy to understand and use and the theories explaining the cause-and-relationships among the models, can be built. The body of knowledge can be called the (grand) activity-centric quality model of software.

• 한국컴퓨터정보학회논문지
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• 제24권5호
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.