• Journal of Information Processing Systems
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• v.10 no.4
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• pp.581-588
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• 2014

To facilitate the implementation of a wide variety of context-aware applications based on mobile devices, general-purpose context-aware framework that applications can use by calling is needed. The context-aware framework is a middleware that performs the sensing, reasoning, and retrieving based on the knowledge base. The knowledge base must systematically represent the information required on the behavior of the context-aware framework, such as context information and reasoning information. It must also provide functions for storage and retrieval. To date, previous research on the representation of the context information have been carried out, but studies on the unified representation of the knowledge base has seen little progress. This study defines the knowledge base as the unified context information, and proposes the UniOWL, which can do a good job of representing it. UniOWL is based on OWL and represents the information that is necessary for the operation of the context-aware framework. Therefore, UniOWL greatly facilitates the implementation of the knowledge base on a context-aware framework.

• The KIPS Transactions:PartC
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• v.16C no.1
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• pp.109-116
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• 2009

Recently, there are many researches to realize context-awareness service that recognizes surrounding environments as context and provide the citizens with pervasive convenience based on ubiquitous computing technology. In the u-City, various sensors collect information as context, and citizens will receive various context-awareness service, making use of their wireless and mobile devices and the infrastructures of the u-City. We designed ontology that is useful to structure information of sensor or device that is linked to networks and use OWL (Web Ontology Language) that can express information of mutual relation and partial situation. And we propose a context-aware reasoning system for personalized u-City services based on collected context information and user's intention.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.587-592
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• 2004

Context-aware computing systems require real-time context reasoning process for context awareness. Context reasoning can be done by comparing input information from sensors with knowledge-base within system. This method is identical with it of rule-based systems. In this paper, we propose hardware rule-based system architecture which can process context reasoning in real-time. Compared to previous architecture, hardware rule-based system architecture can reduce the number of constraints on rule representations and combinations of condition terms in rules. The modified content addressable memory, crossbar switch network and pre-processing module are used for reducing constraints. Using SystemC for description can provide easy modification of system configuration later.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.907-912
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• 2007

The present level of ubiquitous computing technology have developed to the point where Home-server provides services that user require directly for user in the intelligent space. But it will need intelligent system to provides more active services for user in the near future. In this paper, we define the environment information about situation that user is in as Context, and collect the Context that stereotype as 4W1H form for construct the system that can decision service will be provide from information about a situation that user is in, without user's involvement. Additionally we collect information about user's emotional state, use these informations as nodes of Bayesian network for probabilistic reasoning. From that, we materialize Context Awareness system about it that what kind of situation user is in. And, we propose the Context-based Service reasoning model using Bayesian Network from the result of Context Awareness.

• Journal of the Korean earth science society
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• v.25 no.3
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• pp.194-204
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• 2004

The purpose of this literature review is to investigate what kinds of research have been done about scientific inquiry in terms of scientific argumentation in the classroom context from the upper elementary to the high school levels. First, science educators argued that there had not been differentiation between authentic scientific inquiry by scientists and school scientific inquiry by students in the classroom. This uncertainty of goals or definition of scientific inquiry has led to the problem or limitation of implementing scientific inquiry in the classroom. It was also pointed out that students' learning science as inquiry has been done without opportunities of argumentation to understand how scientific knowledge is constructed. Second, what is scientific argumentation, then? Researchers stated that scientific inquiry in the classroom cannot be guaranteed only through hands-on experimentation. Students can understand how scientific knowledge is constructed through their reasoning skills using opportunities of argumentation based on their procedural skills using opportunities of experimentation. Third, many researchers emphasized the social practices of small or whole group work for enhancing students' scientific reasoning skills through argumentations. Different role of leadership in groups and existence of teachers' roles are found to have potential in enhancing students' scientific reasoning skills to understand science as inquiry. Fourth, what is scientific reasoning? Scientific reasoning is defined as an ability to differentiate evidence or data from theory and coordinate them to construct their scientific knowledge based on their collection of data (Kuhn, 1989, 1992; Dunbar & Klahr, 1988, 1989; Reif & Larkin, 1991). Those researchers found that students skills in scientific reasoning are different from scientists. Fifth, for the purpose of enhancing students' scientific reasoning skills to understand how scientific knowledge is constructed, other researchers suggested that teachers' roles in scaffolding could help students develop those skills. Based on this literature review, it is important to find what kinds of generalizable teaching strategies teachers use for students scientific reasoning skills through scientific argumentation and investigate teachers' knowledge of scientific argumentation in the context of scientific inquiry. The relationship between teachers' knowledge and their teaching strategies and between teachers teaching strategies and students scientific reasoning skills can be found out if there is any.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.19-30
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• 2012

The context aware service is the service to provide useful information to the users by recognizing surroundings around people who receive the service via computer based on computing and communication, and by conducting self-decision. But CAS(Context Awareness System) shows the weak point of small-scale context awareness processing capacity due to restricted mobile function under the current mobile environment, memory space, and inference cost increment. In this paper, we propose a mobile cloud context system with using Google App Engine based on PaaS(Platform as a Service) in order to get context service in various mobile devices without any subordination to any specific platform. Inference design method of the proposed system makes use of knowledge-based framework with semantic inference that is presented by SWRL rule and OWL ontology and Jess with rule-based inference engine. As well as, it is intended to shorten the context service reasoning time with mapping the regular reasoning of SWRL to Jess reasoning engine by connecting the values such as Class, Property and Individual which are regular information in the form of SWRL to Jess reasoning engine via JessTab plug-in in order to overcome the demerit of queries reasoning method of SparQL in semantic search which is a previous reasoning method.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.80-92
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• 2007

For the pervasive computing in ubiquitous environment, it is very important to manage the context model to provide pertinent context knowledge to context-aware applications. The context model should be able to support efficiently the context knowledge reusing and sharing as well as reasoning. Previous works focus mainly on the context knowledge representation scheme for reasoning. This paper proposes a context knowledge modeling scheme especially for reusing and sharing. This scheme provides well-established principles and guides for 1) context knowledge modularization and hierarchization, and for 2) context knowledge identification and organization. Once the context models are built according to the scheme, the structure of the context model and the meanings of the context knowledge elements become clear and consistent, so that context-aware applications can share and reuse the context knowledge in easy and error-reduced manner. This paper also discusses the implementation of a context model and an application for Presentation Helper scenario running on a software middleware system (CAMUS) for ubiquitous service robots which is being developed by ETRI Korea.

• School Mathematics
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• v.17 no.3
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• pp.423-446
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• 2015

This study aims to look into the characteristics of argumentation in the task context of 'Monty Hall problem' at a high school probability class. As a result of an analysis of classroom discourses on the argumentation between teachers and second-year students in one upper level class in high school using Toulmin's argument pattern, it was found that it would be important to create a task context and a safe classroom culture in which the students could ask questions and refute them in order to make it an argument-centered discourse community. In addition, through the argumentation of solving complex problems together, the students could be further engaged in the class, and the actual empirical context enriched the understanding of concepts. However, reasoning in argumentation was mostly not a statistical one, but a mathematical one centered around probability problem-solving. Through these results of the study, it was noted that the teachers should help the students actively participate in argumentation through the task context and question, and an understanding of a statistical reasoning of interpreting the context would be necessary in order to induce their thinking and reasoning about probability and statistics.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.3
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• pp.139-147
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• 2009

This paper proposed the context awareness reasoning system to provide the personalized services dynamically in a ubiquitous mobile environments. The proposed system is designed to provide the personalized services to mobile users and consists of the context aggregator and the knowledge manager. The context aggregator can collect information from networks through Open API Gateway as well as sensors in a various ubiquitous environment. And it can also extract the place types through the geocoding and the social address domain ontology. The knowledge manager is the core component to provide the personalized services, and consists of activity reasoner, user pattern learner and service recommender to provide the services predict by extracting the optimized service from user situations. Activity reasoner uses the ontology reasoning and user pattern learner learns with previous service usage history and contexts. And to design service recommender easy to flexibly apply in dynamic environments, service recommender recommends service in the only use of current accessible contexts. Finally, we evaluate the learner and recommender of proposed system by simulation.