• The KIPS Transactions:PartA
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• v.14A no.6
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• pp.363-370
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• 2007

The ubiquitous computing environment could provide better service to users by adapting to changing contexts. In this paper, we developed a context adaptation system, which enables an ubiquitous program to adapt to different contexts, following its adaptation rules. Using this system, programmers can develop ubiquitous programs suitable for changing contexts, by describing the context adaptation policy. The context adaptation engine of this system fits the ubiquitous program to the current context based on the context adaptation rules. This system was implemented using JCAF, context-aware programing framework based on java. A simulator is also provided to simulate ubiquitous programs by changing contexts.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.2
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• pp.1-7
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• 2009

This paper proposes a context gathering system that obtains user's environment information from sensor and generates user's context profile. To design the system, we classify context and design context model based on traditional context-aware computing. The proposed system supports contexts adaptation service by gathering user's environment characteristics and biological characteristics and generating user profile.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.112-120
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• 2011

This research aims to show that the context adaptation system can be used to develop practical context-aware applications by developing a restaurant recommendation system based on location-awareness. In this research, we have designed and implemented a location-aware restaurant recommendation system which provides a customized restaurant recommendation service based on the user's current context. The context-adaptation engine adapts the application program according to the policy file as contexts are changed, and the application provides restaurant recommendation service based on the changed context like location.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.39-47
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• 2011

Adapting content services to the needs of the users requires content adaptation for context and sensibility. Adapting to context may necessitate distinguishing between video delivery to a PC versus a smart phone, while adapting to sensibility may necessitate between video delivery outside, in a quiet environment, or at home, or offering different movie choices on a sunny summer day, a cold winter day or a holiday season. One key area to address in providing adaptive content services is the design of the delivery system architecture of the adaptive content server. This paper describes several alternatives for this architecture, and outlines some additional concerns that must be considered when the chosen architecture is implemented.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.727-739
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• 2003

In this paper, we propose a generation method of regression classes for adaptation in the HM-Net (Hidden Markov Network) system. The MLLR (Maximum Likelihood Linear Regression) adaptation approach is applied to the HM-Net speech recognition system for expressing the characteristics of speaker effectively and the use of HM-Net in various tasks. For the state level sharing, the context domain state splitting of PDT-SSS (Phonetic Decision Tree-based Successive State Splitting) algorithm, which has the contextual and time domain clustering, is adopted. In each state of contextual domain, the desired phoneme classes are determined by splitting the context information (classes) including target speaker's speech data. The number of adaptation parameters, such as means and variances, is autonomously controlled by contextual domain state splitting of PDT-SSS, depending on the context information and the amount of adaptation utterances from a new speaker. The experiments are performed to verify the effectiveness of the proposed method on the KLE (The center for Korean Language Engineering) 452 data and YNU (Yeungnam Dniv) 200 data. The experimental results show that the accuracies of phone, word, and sentence recognition system increased by 34∼37%, 9%, and 20%, respectively, Compared with performance according to the length of adaptation utterances, the performance are also significantly improved even in short adaptation utterances. Therefore, we can argue that the proposed regression class method is well applied to HM-Net speech recognition system employing MLLR speaker adaptation.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.521-525
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• 2021

An essential area is the creation of a single digital market between the EU and Ukraine through information technology. Purpose: to investigate and analyze civil law relations in the field of adaptation of Ukrainian civil law to civil law regulations of the EU. The object of research: Ukrainian civil law and civil law of the EU. The subject of the study is civil law in the context of adaptation of civil law to the legislation of the EU. The following methods of scientific cognition were used during the research: semantic, historical, comparison, analysis and synthesis, generalization. The results of the study show that the harmonization of the legal system of Ukraine with EU law is caused by several goals: successful integration of Ukraine into the EU, legal reforms based on the positive example of EU countries, promoting access of Ukrainian enterprises to the EU market; attracting foreign investment, increasing the welfare of Ukrainian citizens. The adaptation includes three stages, the final of which is the preparation of an expanded program of harmonization of Ukrainian legislation with EU legislation. In the process of adaptation, it is important to take into account the legal history, tradition, features and mentality of Ukraine and before borrowing legal structures to analyze the feasibility of their application in the Ukrainian legal field.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.127-135
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• 2015

Context-aware mobile cloud computing is a new promising paradigm that allows to improve user experience by analyzing contextual information such as user location, time of the day, neighboring devices and current activity. In this paper we provide performance study of context-aware mobile cloud computing system with Volare middleware. Volare monitors the resources and context of the device. and dynamically adapts cloud service requests accordingly, at discovery time or at runtime. This approach allows for more resource-efficient and reliable cloud service discovery, as well as significant cost savings at runtime. We also have studied the performance of context-aware mobile cloud computing for different quality of service (QoS) adaptation policies. Our simulations results show that when battery level is low and CPU usage is high and user cannot maintain the initial QoS, service cost is decreased according to current adaptation policy. In conclusion, the current adaptation policy suggested in this paper may improve user experience by providing a dynamically adapted service cost according to a situation.

• Korean Journal of Community Nutrition
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• v.19 no.5
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• pp.459-467
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• 2014

Objectives: The purpose of this study was to suggest the strategies for improvement of home-delivered meal services for the elderly, to identify reasons for recipients to get started with the services and to evaluate the attitude, acceptability and adaptation of recipients to the services from the perspective of life context. Methods: The data was collected through face-to-face in-depth interviews with eighteen low-income elderly recipients of home-delivered meals and analyzed using a qualitative research method. Results: The results were deduced as four themes which comprised of long-term vulnerable socioeconomic contexts resulted in entry to the services, conflicting acceptability to the services, passive adaptation to taking the services, and positive practices to cope with supplement free meals or other services. The service participation was initiated because of a combination of prolonged, vulnerable socioeconomic contexts, including poverty and unexpected life events such as diseases, disability, living alone, aging and unemployment. With regard to taking the services, conflicting acceptability was observed: positive aspects including saving living cost and good quality of meals, and negative aspects including lack of a tailored service and feeling of stigma. Although the recipients needed an individualized service, they did not express their needs and demands for the services and they accepted the unavailability as an accustomed, prolonged vulnerable socioeconomic context. With regard to lack of tailored services, either self-solution such as modification of eating patterns or community-based network and services were used. Conclusions: We suggest that a system to concretely identify recipients' attitude, acceptability and adaptation for home-delivered meal services should be developed in the establishment of a tailored nutrition support system for the low-income elderly.

• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.171-181
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• 2007

Ubiquitous computing is a vision of our future computing lifestyle in which computer systems seamlessly integrate into our everyday lives, providing services and information in anywhere and anytime fashion. Augmented reality (AR) can naturally complement ubiquitous computing by providing an intuitive and collaborative visualization and simulation interface to a three-dimensional information space embedded within physical reality. This paper presents a service framework and its applications for providing context-aware u-car maintenance services using augmented reality, which can support a rich set of ubiquitous services and collaboration. It realizes bi-augmentation between physical and virtual spaces using augmented reality. It also offers a context processing module to acquire, interpret and disseminate context information. In particular, the context processing module considers user's preferences and security profile for providing private and customer-oriented services. The prototype system has been implemented to support 3D animation, TTS (Text-to-Speech), augmented manual, annotation, and pre- and post-augmentation services in ubiquitous car service environments.