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

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.91-100
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• 2023

Pervasive computing is characterized by a key characteristic that affects the operating environment of services and users. It places more emphasis on dynamic environments where available resources continuously vary without prior knowledge of their availability, while in static environments the services provided to users are determined in advance. At the same time, Cloud computing paradigm introduced flexibility of use according to the user's profile and needs. In this paper, we aimed to provide Context-Aware Transactional Service applications with solutions so that it can be integrated and invoked like any service in the digital ecosystem. Being able to compose is not enough, each service and application must be able to offer a well-defined behavior. This behavior must be controlled to meet the dynamicity and adaptability necessary for the new user's requirements. The motivation in this paper is to offer design patterns that will provide a maximum of automatism in order to guarantee short reaction times and minimal human intervention. Our proposal includes a cloud service model by developing a PaaS service that allows CATS adaptation. A new specification for the validation of CATS model has been also introduced using the ACTA formalism.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1017-1024
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• 2004

Ubiquitous system requires intelligent environment and system that perceives context in a proactive manner. This paper describes proactive retrieval method using context patterns in ubiquitous computing. And as the user's contexts change, new information is delivered proactively based on user's context patterns. For proactive retrieval, we extract context patterns based on sequential pattern discovery and association rule in data mining. By storing only information to be needed in near future using the context patterns, we solved the problem of speed and storage capacity of mobile devices in ubiquitous computing. We explain algorithms and an example. Several experiments are performed and the experimental results show that our method has a good information retrieval.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.114-123
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• 2009

Context-aware systems are reactive computing systems, aware of external context. Considering various sensors and actuators connected, application programming on top of such systems is known to be much more complex than in contentional ones. This paper suggests a formal framework for context-aware systems, by extracting their common properties. That makes a useful birds-eye view for the behaviors of a whole complex system, as a base for a convenient developing environment and systematic analysis. In this framework, reactive-ness is handled by event-condition-action rules and global state-transitions, which are essential in a lot of context-aware applications. In addition, behaviors of each elementary device are modelled with its own state-transitions, and tightly bound to the entire task.

• Knowledge Management Research
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• v.10 no.1
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• pp.1-15
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• 2009

As pervasive computing technology, which aims to get linked to useful knowledge, information or services anytime, anywhere, using any devices and/or artifacts, is proliferating, desirable impacts on knowledge management systems are now available. The pervasive computing technology will potentially enable the knowledge management systems to realize individualization and socialization and ultimately increase the knowledge processing productivity. However, researchers who apply the pervasive computing methodologies to novel way of knowledge management have been very few. These result in unsatisfactory consideration of establishing pervasive knowledge management systems. Hence, the purpose of this paper is to cast the vision of pervasive knowledge management and search for a couple of possible research issues and possibilities. This paper suggests a framework of ubiDSS, an amended knowledge management system for the next generation deploying pervasive and autonomous knowledge acquisition capabilities of ubiquitous computing technologies. Also the CKAM, context-based knowledge acquisition module, is illustrated as a prototype of future knowledge management systems.

• Journal of Multimedia Information System
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• v.1 no.1
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• pp.11-22
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• 2014

This work discusses and evaluates the use of wireless and multi-sensor based technologies to develop UbiqBIOPARC, a new generation zoological park that has been created based on the zoo-immersion concept. It offers appropriate contextual information to zoo visitors, depending on their preferences and the environment in which they are positioned. It combines the flexibility of the iPhone SDK, the connectivity provided by 3G technologies, the location capabilities of GPS, and the orientation offered by a digital compass integrated in the device. In this document the overall architecture and the implementation steps followed to create this context-aware application are presented. We compare our system with respect to previous ones and demonstrate that UbiqBIOPARC is an example of how innovative context-aware applications can be built with the aid of GPS and compass features. Several real experiments have been carried out in order to evaluate performance and system behavior, and numerical results demonstrate the practicality offered by our application, while providing a quite reasonable performance in terms of delay, usability, and energy efficiency.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.90-97
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• 2014

Context-aware systems provide proper services for the user according to current contexts. However, it is not actively deployed in our daily lives as expected, due to many concerns including occurrences of exceptions. C++/C#/JAVA provide exception handling facilities for desktop computing programs, but context-aware system developers might feel far more difficult to make use of such general facilities, because it is hard to decide the timing and position of exception handling with various devices engaged. In this paper, we propose an exception detection and handling mechanism using device semantics and AspectJ so that it can constantly detect a large number of devices to allow the programmers to detect and handle exceptions with less burden.

• Spatial Information Research
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• v.19 no.1
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• pp.127-133
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• 2011

Recently, with the advances in sensor techniques and net work computing, Ubiquitous Sensor Network (USN) has been received a lot of attentions from various communities. The sensor nodes distributed in the sensor network tend to continuously generate a large amount of data, which is called stream data. Sensor stream data arrives in an online manner so that it is characterized as high-speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. The data stream has many application domains such as traffic analysis, physical distribution, U-healthcare and so on. Therefore, there is an overwhelming need of a USN middleware for processing such online stream data to provide corresponding services to diverse applications. In this paper, we propose a novel USN middleware which can provide users both context-aware service and meaningful sequential patterns. Our proposed USN middleware is mainly focused on location based applications which use stream location data. We also show the implementation of our proposed USN middleware. By using the proposed USN middleware, we can save the developing cost of providing context aware services and stream sequential patterns mainly in location based applications.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.1-12
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• 2013

Context-awareness is a computing technology that automatically delivers useful services to users based on their situation. Most previous studies on context-awareness adopted the view that the user simply is a consumer of what the developer creates. Few studies addressed catering to the need of personalized services for the user. They are either too complex for the user to grasp or unable to express many useful services due to their weak expressive power. To address these issues, we propose Dobby as a new model and architecture for user-driven context-aware service development. Dobby enables the user to create services that are more suited to his personal preferences. We argue that Dobby offers an enhanced method for defining personalized context-aware services over existing methods.