• The KIPS Transactions:PartD
• /
• v.15D no.1
• /
• pp.41-46
• /
• 2008

In ubiquitous computer environment, by improving the computer's access to context information for dynamic service adaptation, we can increase richness of communication in human computer interaction and make it possible to produce more useful computational services. We need new data structure in order to flexible apply dynamic information to current context information repository and enhance the communication ability between human and computer. In this paper, we proposed to C-A-V (Category-Attribute-Value) context metadata structure required to support dynamic service adaptation for increasing communication ability in user-centric environments. We also classify the context metadata, as well as define its relationship with other context information on the basis of the application services, changes in the external environments.

• KIISE Transactions on Computing Practices
• /
• v.22 no.8
• /
• pp.387-392
• /
• 2016

Context-aware systems require sensor data collecting model and context representing model to provide user-demand services. Sensor data collecting model consists of sensor access information, sensor value, and definition of value types. Context representing model involves certain keywords to symbolize environmental information including the field from sensor data collecting model that is described in markup language such as XML. However, duplicated keywords could be assigned to different contextual information by service developers. As a result, the system may cause misunderstanding and misleading wrong situational information from unintended contextual information. In this paper, we propose a context classification model for collecting appropriate access information and defining the specification of context.

• The KIPS Transactions:PartA
• /
• v.16A no.2
• /
• pp.135-142
• /
• 2009

With the development of ubiquitous computing technology, the number of HCI applications is increasing, where they utilize various contexts to provide adaptive services to users according to the change of contexts, and also, technologies for collecting various sensor data and generating integrated contexts get more important. However, the research on the collection and integration of multi-sensor data is not sufficient when we consider the various utilization areas of the integrated contexts. In particular, they have some problems to be solved such as duplication of the context data and the high system load. In this paper, we propose an integrated context generation scheme based on Ant Colony System. Proposed scheme generates the context data as a form of XML and avoids the generation of unnecessary context information by detecting the repeated sensor information based on the ant colony system. As a result of detections, we reduce wasted resources and repositories when the integrated context is created. We also reduce the overhead for reasoning.

• Journal of Information Processing Systems
• /
• v.16 no.3
• /
• pp.612-628
• /
• 2020

This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects' behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.5
• /
• pp.655-660
• /
• 2009

The context prediction algorithms are not suitable to provide real-time personalized service for users in context-awareness environment. The algorithms have problems like time delay in training data processing and the difficulties of implementation in real-time environment. In this paper, we propose a prediction algorithm with user modeling to shorten of processing time and to improve the prediction accuracy in the context prediction algorithm. The algorithm uses moving path of user contexts for context prediction and generates user model by time-series analysis of user's moving path. And that predicts the user context with the user model by sequence matching method. We compared our algorithms with the prediction algorithms by processing time and prediction accuracy. As the result, the prediction accuracy of our algorithm is similar to the prediction algorithms, and processing time is reduced by 40% in real time service environment.

• Journal of The Korean Association For Science Education
• /
• v.26 no.3
• /
• pp.406-414
• /
• 2006

This study investigated 7th grade students' context dependency on explanations about propagating path of light in three different contextual problems: observation of an object, observation of an object's image in a mirror, and observation of one's own face reflection in a mirror. Researchers examined student response in each context through interviews. The students were classified into four groups according to their explanations for the three different contexts. Each group was redivided into two or three subgroups in accordance with their conceptual features. After that, researchers investigated the characteristics of each subgroup. Main findings of the study indicated that (1) group 1 students' conceptions differed in each context; (2) group 2 students showed scientific conceptions in C1 context but in C2 context they showed visual ray conceptions or image misconceptions; (3) group 3 students did not show scientific conceptions in C3 context by strong misconceptions about one's own face reflection in the mirror. Also, this paper discussed the educational implications of the results.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2004.05a
• /
• pp.288-289
• /
• 2004

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2005.10a
• /
• pp.116-117
• /
• 2005

• Proceedings of the Korea Multimedia Society Conference
• /
• 2004.05a
• /
• pp.583-586
• /
• 2004

유비쿼터스 컴퓨팅 환경에서 사용자의 상환인식 서비스 구축은 일반 응용서비스와는 달리 사용자 요구를 만족시키기 위해 차별화된 처리를 요구한다. Context Toolkit은 상황인식 서비스 구축을 제공하는 프레임워크이며, 입출관리 시스템은 사용자의 위치인식과 방문자목록 가입을 토대로 서비스를 제공해주는 시스템이다. 본 논문에서는 사용자의 방문을 효과적으로 관리할 수 있는 방문관리를 위해 Context Toolkit을 기반으로 한 방문관리 시스템을 설계하고 적용한다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.1
• /
• pp.205-211
• /
• 2012

In this paper, we proposed a context-aware augmented reality platform for mobile augmented reality to support user-oriented virtual world information for smartphone user. We designed the platform architecture and 6 subsystems which are derived from the analysis of existing augmented reality applications and platforms. The proposed architecture includes a context reasoning service subsystem for the context-aware information filtering, and separates the inner platform from the outer virtual world network containing virtual information to resolve interoperability issue of POI(Points of Interest) data.