• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.108-118
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• 2010

In this paper, we propose Context-based Music Recommendation (COMUS) ontology for modeling user's musical preferences and context and for supporting reasoning about the user's desired emotion and preferences. The COMUS provides an upper Music Ontology that captures concepts about the general properties of music such as title, artists and genre and also provides extensibility for adding domain-specific ontologies, such as Mood and Situation, in a hierarchical manner. The COMUS is music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology. Using this context ontology, we believe that the use of logical reasoning by checking the consistency of context information, and reasoning over the high-level, implicit context from the low-level, explicit information. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the application. We present some of the experiments we performed as a case-study for music recommendation.

• IE interfaces
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• v.20 no.4
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• pp.560-567
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• 2007

The opening of ubiquitous computing era prompted rapid increase in information transfer between human and computer. Such changes in computing environment requires new computing interface. In this paper, we develop a user interface prototype and framework using Avatar in Ubiquitous computing environment, which can support an active communication between human and computer based on context information. To develop the new interface, its conceptual framework with specific context information is designed in advance. In addition, this study suggests the future goal of user interface using Avatar by suggesting the requirements of constructed prototype.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2396-2413
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• 2018

Trust management is one of the most challenging issues for the highly heterogeneous Internet of Things (IoT). In the context of the IoT, it is difficult to evaluate the node's trustworthiness in the same trust model when a node provides different services. Guaranteeing the availability of the trust management service is another significant challenge because of the dynamic nature of IoT environments. With these issues in mind, this paper propose a robust and adaptive trust management system for the IoT that is able to measure the trustworthiness of nodes based on feedbacks collected from participants in a specific context and ensure the availability of trust management services. The main contributions of our system are: 1) Proposing a partly decentralized trust management framework, which improves the resiliency of the trust mechanism; 2) Proposing an adaptive trust evaluation scheme and a three-dimensional context representation makes trust evaluation more accurate and specific; 3) Enhancing the adaptive trust evaluation scheme by incorporating a bad behavior factor in trust estimation, which efficiently distinguishes misleading feedbacks from On-Off attacks. Simulation results show the good performance of the proposed system and especially show effectiveness against On-Off attacks compared to other trust mechanisms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1200-1206
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• 2009

In this paper, we propose an energy-efficient MAC(Medium Access Control) protocol for processing context information in ubiquitous sensor network environments. CASMAC(Context Aware Sensor MAC) use context information for energy-efficient operation and its operation principle is as follows. First, we make scenarios with possible prediction for CASMAC. And then we save setted context information in server. When event occur at specific sensor node, and then it send three times sample data to server. According to context information, server process sample data. If server process sample data with event, it receive continuous data from event occur node by a transmission request signal. And then server send data transmission stop signal to event occur node when it do not need to data. If server process sample data with no event, it have not reply. Through we make energy consumption tables and an energy consumption model, we simulate analysis of CASMAC performance. In a result, we gains about 5.7 percents energy reduction compared to SMAC.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.101-111
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• 2011

Due to recent development in wireless communication technologies and mobile information devices, the services on ubiquitous computing technology without time and place restriction have been spotlighted. Moreover, the interest of the Wireless Sensor Networks (WSNs) and context-awareness technologies have largely been escalating and their technologies utilization is active in the various applications such as healthcare, farm management and so on. However, the direct adaption of the existing context-awareness technique to the WSN technology has several drawbacks as follows. First, such systems waste precious energy of sensor nodes, due to unnecessary data transmissions. Secondly, since the existing work was designed to support only specific applications, it is required to implement a new context-awareness application for a specific purpose. Therefore, we, in this paper, propose a new real-time monitoring system based on context-awareness in WSNs. Our system not only enhances energy efficiency by reducing data transmissions by doing context-awareness on a sensor node, but also is scalable in terms of supporting new context-awareness functionalities through modularization.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.9-24
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• 2008

In this paper, we describes the design of software architecture supporting for healthcare context information service platform based on multi agent in home environment. In this platform, the DOGF supports the execute object and healthcare sensors and device's logical services grouping. JADE framework can support mobility in heterogeneous environment. The multi agents on platform order to support a healthcare context information service it will be able to divide. An agent collects an environment information from distributed devices. Another an agent follows mobile-device specific and it does a different service. And an agent where it manages like this. The mobile-proxy&agent is an interface part between DOGF and JADE, support data interchange or mobility pattern. For DOGF and JADE to provide healthcare context information service, we describes the design of multi agent software platform and multi agent classification by services. Finally we showed the system environments which is physical environments and prototype based on platfonn for healthcare context information services.

• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.62-68
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• 2015

The MPEG user description (MPEG-UD) which is a standard under exploration to ensure interoperability among customized recommendation services has been contributed since MPEG $104^{th}$ meeting at 2013. Twenty-two use cases that were divided into different applications have been proposed in the MEPG meetings. Most of use cases were referred to specific and restricted regarding to applications, it appears to miss an overall and explicit infra-structure. In this paper we describe a reference model, namely methodology to overcome aforementioned problems. Thereafter, we have applied reference model to context-based recommendation system to demonstrate the methodology and MPEG-UD schemas. In addition, we propose a development process of recommendation system in compliance with MPEG-UD.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.612-628
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• 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
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• v.15 no.5
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• pp.538-544
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• 2005

The service supporting structure for users in ubiquitous computing environment requires technology that divides efficiently resources shared around users according to users context. So, needs research that analyze service items and resources that is offered according to users context information and divide adaptively necessary service and resources. Therefore, in this paper we proposes an intelligent P2P mobile agent that recognizes users context using portable mobile devices and is available for intelligent service by sharing serviced item according to users' context. The proposed structure removes monopoly for specific resources, and supports effective users context-awareness and service.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.550-557
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• 2007

We predict a context of various structures by using Bayesian Networks Algorithms, Three-Dimensional Structures Algorithms and Genetic Algorithms. However, these algorithms have unavoidable problems when providing a context-aware service in reality due to a lack of practicality and the delay of process time in real-time environment. As far as context-aware system for specific purpose is concerned, it is very hard to be sure about the accuracy and reliability of prediction. This paper focuses on reasoning and prediction technology which provides a stochastic mechanism for context information by incorporating various context information data. The objective of this paper is to provide optimum services to users by suggesting an intellectual reasoning and prediction based on hierarchical context information. Thus, we propose a design of user location prediction algorithm using sequential matching with n-size flexible window scheme by taking user's habit or behavior into consideration. This algorithm improves average 5.10% than traditional algorithms in the accuracy and reliability of prediction using the Flexible Window Scheme.