• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.270-276
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• 2012

With the increase in amount of data and information available on the web, there have been high demands on personalized information retrieval services to provide context-aware services for the web users. This paper proposes a novel dynamic multi-agent context-awareness user profile construction method based on ontology to incorporate concepts and properties to model the user profile. This method comprehensively considers the frequency and the specific of the concept in one document and its corresponding domain ontology to construct the user profile, based on which, a fuzzy c-means clustering method is adopted to cluster the user's interest domain, and a dynamic update policy is adopted to continuously consider the change of the users' interest. The simulation result shows that along with the gradual perfection of the our user profile, our proposed system is better than traditional semantic based retrieval system in terms of the Recall Ratio and Precision Ratio.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.65-75
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• 2019

Non-Functional Requirements (NFR) play a crucial role during the software development process. Currently, NFRs are considered more important than Functional Requirements and can determine the success of a software system. NFRs can be very complicated to understand due to their subjective manner and especially their conflicting nature. Self-adaptive systems (SAS) are operating in dynamically changing environment. Furthermore, the configuration of the SAS systems is dynamically changing according to the current systems context. This means that the configuration that manages the trade-off between NFRs in this context may not be suitable in another. This is because the NFRs satisfaction is based on a per-context basis. Therefore, one context configuration to satisfy one NFR may produce a conflict with another NFR. Furthermore, current approaches managing Non-Functional Requirements trade-off stops managing them during the system runtime which of concern. To solve this, we propose fragmentizing the NFRs and their alternative solutions in form of Multi-entity Bayesian network fragments. Consequently, when changes occur, our system creates a situation specific Bayesian network to measure the impact of the system's conditions and environmental changes on the NFRs satisfaction. Moreover, it dynamically decides which alternative solution is suitable for the current situation.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.165-176
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• 2012

Context-Awareness system provides an appropriate service to user by recognizing situation from surrounding environment. There are many successful studies on this framework, but still has some limitations. In this paper, we are describing a context-awareness middleware that can enhance the limitation of the previous approaches. We first defined a new concept of context-awareness environment as a social intelligence. This concept implies that intelligent objects can make relationships, can aware of situation from surrounding environment, and can collaborate to accomplish a given task. The significance of the study is as follows. First, the system is capable of multi context-awareness since it is designed with a structure that supports multiple lines of reasoning. Second, the system is capable of context planning by adapting AI planning mechanism. Third, the system is capable of making the intelligent objects as a group for collaboration, and provides adaptive service to user. We have developed a prototype of the system and tested with a virtual scenario.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.285-288
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• 2004

스마트 홈은 유비쿼터스 환경의 각종 센서와 정보가전에서 얻어지는 데이터에서 사용자의 Context를 추출하여 사용자에게 적응적인 서비스를 제공한다 지금까지의 Context는 사용자가 한 명일 경우를 가정하였지만 실제 집이라는 공간은 가족이라는 구성원이 함께 생활하는 공간으로 동시에 여러 개의 Context가 존재하며 이러한 Context는 서로 충돌할 수도 있다. 본 논문에서는 집에서 여러 Context들 간에 충돌이 일어났을 때 이를 해결하는 방법을 제안한다. 집은 여러 사용자가 공유하고 있지만 각 구성원의 침실이나 화장실처럼 한 개인의 영역이 존재한다 또한 침실은 쉬는 곳, 주방은 요리를 하고 음식을 먹는 곳, 거실은 가족끼리의 모임을 갖거나 TV 시청, 음악감상 등의 여가를 즐기는 곳 등 공간마다 나름의 용도를 가지고 있다 본 논문은 Context들간의 충돌을 조정을 위해 이러한 공간의 특성을 이용할 것을 제안한다.

• Journal of the Korea Society of Computer and Information
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• v.4 no.3
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• pp.67-72
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• 1999

The neural network is a static network that consists of a number of layer: input layer, output layer and one or more hidden layer connected in a feed forward way. The popularity of neural network appear to be its ability of learning and approximation capability. The Elman Neural Network proposed the J. Elman. is a type of recurrent network. Is has the feedback links from hidden layer to context layer. So Elman Neural Network is the better performance than the neural network. In this paper. we propose the Modified Elman Neural Network. The structure of a MENN is based on the basic ENN. The recurrency of the network is due to the feedback links from the output layer and the hidden layer to the context layer. In order to certify the usefulness or the proposed method. the MENN apply to the multi target system. Simulation shows that the proposed MENN method is better performance than the multi layer neural network and ENN.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.799-806
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• 2007

The prototypical smart environment to support the context-aware interactions between user and ubiquitous campus environment based on multi-agent system paradigm is proposed in this paper. In this model, the dynamic Bayesian is investigated to solicit and organize agents to produce information and presentation assembly process in order to allocate the resources for an unseen task across multiple services in a dynamic environment. The user model is used to manage varying user constraints and user preferences to achieve system's goals.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.89-96
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• 2001

In this paper, a noise-tolerant generalized symmetry transform(NTGST) is proposed and implemented as a context-free attention operator for efficient detection of multi-object. In contrast to the conventional context-free attention operator based on the GST in which only the magnitude and the symmetry of the pixel pairs are taken into account, the proposed NTGST additionally takes into account the convergence and the divergence of the radial orientation of the intensity gradient of the pixel pair. Thus, the proposed attention operator can easily detect multiple objects out of the noisy and complex backgrounded image. Experiments are conducted on various synthetic and real images, and the proposed NTGST is proved to be effective in multi-object detection from the noisy and complex backgrounds.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.10a
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• pp.178-179
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• 2004

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.121-144
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• 2004

Developing a personalized system on a user's behalf which is working around the Internet-based marketplace is one of the challenging issues in intelligent e-business, especially mobile commenrce. It has been highly recommended that such a mobile personalized system has to perceive the user's needs a priori by tracking user's current context such as location with activity and then to identify the current needs dynamically and proactively. Automatically and unobtrusively getting user's context is an inevitable feature for the development of autonomous mobile commenrce. However, personalization methodologies and their feasible architectures for context-aware mobile commerce have been so far very rare. Hence, this paper aims to propose a context-aware mobile commerce development methodology by applying agent and semantic web technologies for personalized reminder system, which is one of the mobile commerce support system. We revisited associationism to understand a buyer's need identification process and adopt the process as 'purchase based on association' to implement a personalized reminder system. Based on this approach, we have showed how the agent-based semantic web service system can be used to realize need-aware reminder system. NAMA(Need-Aware Multi-Agent), a prototype system, has been implemented to show the feasibility of the methodology and framework under mobile setting proposed in this paper. NAMA embeds bluetooth-based location tracking module and identify what a user is currently looking at through her/his mobile device such as PDA. Based on these capabilities, NAMA considers the context, user profile with preferences, and information about currently available services, to aware user's current needs and then link her/him to a set of services, which are implemented as web services.