• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2251-2256
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• 2007

In this paper, the wavelet transform based lossless image compression algorithm is proposed. The proposed algorithm transforms the input image using 9/7 ICFB and S+P filter, and eliminates the spacious correlation of the subband coefficients, applying the context modeling predictive technique based on the multi-resolution structure and the feedback of the prediction error. The prediction context exploits the subordination and direction property of the different level subband in the vertical, horizontal, and diagonal subband coefficients. The simulation result of the high frequency images such as PEPPERS, BOAT, and AIRPLANE shows that the proposed algorithm efficiently predicts the edge area of each multi-resolution subband.

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.437-447
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• 2011

Ubiquitous Computing is required to define models for broad context information occurrence by surrounding environment and to study how to model a mechanism for selectively collecting useful pieces of context information and providing relevant intelligent services. Further, studies are also required as to process of context information, and its maintenance and reasoning. However, current context-aware research area still lacks modeling technique that reflects the characteristics of ontology effectively for providing relevant intelligent services. It has also limitation about context reasoning and interoperability among context information. Therefore, this paper proposes ontology-based context-aware modeling technique and framework enabling efficient specification of context information for providing intelligent context-aware services that support context management and reasoning.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.183-190
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• 2009

The core technique of ubiquitous computing is the context aware computing and the context aware technique is more like software so the important research work is to develop the core engines first and the adapted device for the engines. When ubiquitous computing era comes, the current existing internet shopping mall, the form of searching the direct goods and ordering the goods by the customers evolves and develops the form of system that recommends the goods by the search engine which combined with the input data and technique of case based reasoning and intelligent agent that is based on the context aware technique. In this paper, search engine which is based on the case based reasoning and intelligent agent is designed and the prototype is implemented to be adapted to the internet fashion expert shopping mall.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.289-296
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• 2015

The explosive growth of information has been difficult for users to get an appropriate information in time. The various ways of new services to solve problems has been provided. As customized service is being magnified, the personalized recommendation system has been important issue. Collaborative filtering system in the recommendation system is widely used, and it is the most successful process in the recommendation system. As the recommendation is based on customers' profile, there can be sparsity and cold-start problems. In this paper, we propose personalized movie recommendation system using collaborative filtering techniques and context-based techniques. The context-based technique is the recommendation method that considers user's environment in term of time, emotion and location, and it can reflect user's preferences depending on the various environments. In order to utilize the context-based technique, this paper uses the human emotion, and uses movie reviews which are effective way to identify subjective individual information. In this paper, this proposed method shows outperforming existing collaborative filtering methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.512-517
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• 2008

It is show that increasing of aged and handicapped people requires development of Ubiquitous computing technique to offer the specialized service for handicapped-people. For this, we need a development of Context Awareness and Service Reasoning Technique that the technique is supplied interaction between user and U-environment instead of the old unilateral relation. The old research of context awareness needed probabilistic presentation model like a Bayesian Network based on expert Systems for recognize given circumstance by a domain of uncertain real world. In this article, we define a domain of disorder activity assistant service application and context model based on ontology in diversified environment and minimized intervention of user and developer. By use this context model, we apply the structure learning of Bayesian Network and decide the service and activity to development of application service for handicapped people. Finally, we define the proper Conditional Probability Table of the structured Bayesian Network and if random situation is given to user, then present state variable of Activity and Service by given Causal relation of Bayesian Network based on Conditional Probability Table and it can be result of context awareness.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.116-119
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• 2011

Mobile devices are increasingly used, and changed persons' social habits of creating new relationship. While existed systems can not satisfied the principles of user-centered, convenient and ensure privacy. This paper describes an intelligent name-card exchange technique in context-aware smart phone, which has no verbose user operation, ability of intelligent match based on context-aware information, and privacy protection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2839-2852
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• 2013

Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.269-270
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• 2007

In previous work[1], each codeblock is coded using a context which is adaptively selected from three kinds of scanning directions after 3D DWT. But some subbands still have correlations among the coefficients in horizontal, vertical or temporal direction. In this paper, we propose a new 3D DWT-based video compression technique in which the difference of coefficients is calculated in one of three directions for every codeblocks and coded by a context adaptively selected for each codeblock. Experimental results show that the proposed compression technique outperforms measurably and visually compared to the conventional DWT-based techniques.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.287-292
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• 2012

In this paper, user personalized services through the emotion perception required to support location-based sensing data preprocessing techniques and emotion data preprocessing techniques is studied for user's emotion data building and preprocessing in V-A emotion model. For this purpose the granular context tree and string matching based emotion pattern matching techniques are used. In addition, context-aware and personalized recommendation services technique using probabilistic reasoning is studied for personalized services based on context awareness.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2463-2466
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• 2003

This paper studied the pattern recognition algorithm and feature parameters for emotion recognition. In this paper, KNN algorithm was used as the pattern matching technique for comparison, and also VQ and GMM were used lot speaker and context independent recognition. The speech parameters used as the feature are pitch, energy, MFCC and their first and second derivatives. Experimental results showed that emotion recognizer using MFCC and their derivatives as a feature showed better performance than that using the Pitch and energy Parameters. For pattern recognition algorithm, GMM based emotion recognizer was superior to KNN and VQ based recognizer