• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.103-105
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• 2006

일정관리는 업무 능률을 높이기 위해 일정의 작성, 변경, 조정을 하는 것으로 체계적인 관리를 위해서는 많은 시간과 노력이 필요하다. 일정관리를 대행해주는 지능형 에이전트가 존재한다면 개인의 시간 관리에 많은 도움이 된다. 이미 Calendar Manager, Office Tracker, MS Out look 등의 많은 응용 어플리케이션이 개발되었으나, 이들은 사용자의 성향을 학습하지 않고 수동적인 관리만 하므로 일정관리에 있어서 큰 도움을 주지 못한다. 본 논문에서는 베이지안 네트워크를 이용하여 실시간으로 사용자의 행동 패턴을 모델링하는 사용자 적응적인 지능형 일정관리 에이전트를 제안하고, 정성 정량적 실험을 통해 제안하는 방법의 유용성을 보인다.

• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.135-152
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• 2008

The purpose of this study is to research psychological and social devices to foster self-regulated learning of Korean adolescents. This study investigated metacognitive, motivational, and behavioral factors of self-regulated learning through current research. In terms of metacognitive factors, we reviewed the importance of cognitive and metacognitive learning strategies of adolescents for better self-regulated learning. Especially we gave a great emphasis on the role of comprehension monitoring metacognitive strategy for the learning to read in this review. For motivational factors, recent research of self-regulated learning has tended to focus on self-efficacy and goal orientation. The current research examining behavioral factors of self-regulated learning has tended to focus on time management and academic procrastination. Research findings in the motivational aspect suggest that we need to develop the program to improve adolescents' self-efficacy and recognize new re-conceptualization of the goal theory. Research findings in the behavioral aspect recommend practical tips and strategies to improve time management skills and to overcome academic procrastination. Finally, future directions for research are discussed.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.655-656
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• 2023

반려동물 웨어러블 시장의 성장함에 따라 반려동물의 행동 패턴을 측정하고 분석할 수 있는 센서데이터가 활용되고 있다. 본 논문에서는 반려동물 수면 패턴 모니터링을 위한 행동 분류 모델을 제안한다. 6축 센서 데이터를 활용한 가속도 및 자이로센서 데이터를 입력 데이터로 사용한다. 제안된 모델은 ResNet을 통해 시간에 따라 가속도 및 자이로센서 데이터의 특징을 추출한 후 LSTM을 사용하여 시계열 정보를 고려한 행동 분류를 수행한다. 이러한 과정을 통해 정확한 행동 패턴 분석이 가능하게 되며 반려동물의 건강 관리 및 수면 질 개선에 기여할 것으로 기대한다.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.40-48
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• 2014

As CBR(Chemical, Biological, and Radiological) attack increases, the importance of CBR protective facilities is being emphasized. When CBR warfare emerges, a task force team, who exist outside of CBR protective facility, should enter the CBR protective facility through neutralizing process in CCA(Contamination Control Area) and TFA(Toxic Free Area). If a bottleneck occurs in the process or zones, the task force team cannot enter the CBR protective facility efficiently and may cause inefficiency in its operation performance or result in casualties. The current design criteria of the CBR protective facility is only limited to ventilation system and it does not consider how much time it takes to enter the facility. Therefore, this research aims to propose the entering time estimation model with discrete event simulation. To make the simulation model, the procedure performed through CCA and TFA is defined and segmented. The actual time of the procedure are measured and adapted for the simulation model. After running the simulation model, variables effecting the entering time are selected for alternatives with adjustments. This entering time estimation model for CBR protective facility is expected to help take time into consideration during the designing phase of CBR protective facility and help CBR protective facility managers to plan facility operation in a more realistic approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.712-717
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• 2011

Recently, diverse schedule management agents are being researched for the efficient schedule management of smart devices users, but they remain at a confirmatory level. In order to efficiently manage user's schedules, execution of planned schedules should be monitored to help users properly execute their schedules, or feedback must be given so that when setting up new schedules, users can plan their schedule according to their schedule establishment patterns. This research proposes a schedule management agent that infers the user's behaviors by using acquired user context, and provides schedule related feedback depending on the user's behavior patterns, when users are executing their schedules or planning new schedules. For this, collected user context information is preprocessed and user's behavior is inferred by Bayesian network. Also, in order to provide feedbacks necessary for confirming the user's schedule execution and new schedule establishment, a context tree pattern matching method for the user's schedule, location and time contexts was applied, then verified with 6 weeks of user simulation in a mobile environment.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.23-47
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• 2003

Traditional studies for customer relationship management (CRM) generally focus on static CRM in a specific time frame. The static CRM and customer behavior knowledge derived could help marketers to redirect marketing resources fur profit gain at that given point in time. However, as time goes, the static knowledge becomes obsolete. Therefore, application of CRM to an online retailer should be done dynamically in time. Customer-based analysis should observe the past purchase behavior of customers to understand their current and likely future purchase patterns in consumer markets, and to divide a market into distinct subsets of customers, any of which may conceivably be selected as a market target to be reached with a distinct marketing mix. Though the concept of buying-behavior-based CRM was advanced several decades ago, virtually little application of the dynamic CRM has been reported to date. In this paper, we propose a dynamic CRM model utilizing data mining and a Monitoring Agent System (MAS) to extract longitudinal knowledge from the customer data and to analyze customer behavior patterns over time for the Internet retailer. The proposed model includes an extensive analysis about a customer career path that observes behaviors of segment shifts of each customer: prediction of customer careers, identification of dominant career paths that most customers show and their managerial implications, and about the evolution of customer segments over time. furthermore, we show that dynamic CRM could be useful for solving several managerial problems which any retailers may face.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1997.11a
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• pp.203-208
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• 1997

산업현장에 앗차 위험이 지속되고 있다. 그러나 근로자들은 너무나 앗차 위험 행동에 익숙하여 무감각하게 지나쳐 버리고 있다. 이러한 의식 구조 속에서는 안전이 활성화 될 수 없으며 사고 위험으로부터 헤어나지 못하는 기업이 될 것이다. 산업현장에서 중대재해가 발생되고 나면 신경을 별로 쓰지 않은 곳에서 발생했다고 말한다. 대수롭지 않게 묵인한 것이 대형재해로 싹트기까지는 오랜시간의 앗차경험을 겪어왔던 결과치다. 근로자들의 전사적인 안전의식을 강하게 느끼고 인식하여 안전행동을 추진하는 기업은 이와 같은 유사재해도 사전에 제거할 대응 자세가 갖춰지게 될 것이다. (중략)

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.811-819
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• 2017

A behavior pattern analysis algorithm based on descriptors consists of information of a moving object and temporal histogram is proposed. Background learning is performed first for detecting, tracking and analyzing moving objects. Each object is identified using an association of the center of gravity of objects and tracked individually. A temporal histogram represents a motion pattern using positions of the center of gravity and time stamp of objects. The characteristic and behavior of objects are figured out by comparing each coordinates of a position history in the histogram. Behavior information which is comprised with numbers of a start and end frame, and coordinates of positions of objects is stored and managed in the linked list. Descriptors are made with the stored information and the video retrieval algorithm is designed. We confirmed the higher retrieval accuracy compare with conventional methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.571-575
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• 2015

This paper propose a temporal histogram -based behavior pattern analysis algorithm to analyze the movement features of moving objects from the image inputted in real-time. For the purpose of tracking and analysis of moving objects, it needs to be performed background learning which separated moving objects from the background. Moving object is extracted as a background learning after identifying the object by using the center of gravity and the coordinate correlation is performed by the object tracking. The start frame of each of the tracked object, the end frame, the coordinates information and size information are stored and managed by the linked list. Temporal histogram defines movement features pattern using x, y coordinates based on time axis, it compares each coordinates of objects for understanding its movement features and behavior pattern. Behavior pattern analysis system based on temporal histogram confirmed high tracking rate over 95% with sustaining high processing speed 45~50fps through the demo experiment.

• Journal of the korean veterinary medical association
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• v.35 no.1
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• pp.36-42
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• 1999

감시는 유방건강자료의 알맞은 경영에 대한 기본적인 판단이다. 감시는 꼭 필요한 노력과 근원에 초점을 맞추는 것과 똑같이 엄청난(확실한) 문제점 지역에서 할 수 있다. 감시는 농장에서 장기간 유방건강관리가 필요 하다는 것에 긴장을 가져야 한다. 다른 곳으로 주의가 갈 수 있다는 것에서 많은 영향이 있을 수 있다. 감시는 정확한 행동동기가 있어야 한다. 감시는 유방염관리 권장이 적용되는 것과 같이 유질에서 향상의 직접적이고 시간 코스가 문서로 외기 위한 돌봄이 있어야 한다. 유방건강자료의 알맞은 관리 없이는 유방건강과 유질에 대한 지속적인 최고의 기록은 성취되기 힘들다.