• Journal of Information Technology Services
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• v.9 no.1
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• pp.113-125
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• 2010

Recently, a smart space with Ubiquitous Environment is expanding rapidly due to the development of Ubiquitous Sensor Network. Therefore, more appropriate and intelligent services of the context awareness system is being required. The previous context awareness system can provide a service to the user through the inference only on the current situation. But, it does not handle certain situation properly when the system provides abnormal result. Also it does not have any proper method of generating reliable semantic data from sensed raw data. In this paper, we are trying to solve the problems as the following approaches. First, the system recognizes abnormal result and corrects it by learning feedback from the user. Second, we suggest a method of converting sensed data into more reliable semantic data. Third, we build the system based on an Ontological context model that is capable of interoperability and reusability. Therefore, the context awareness system of our study can enhance the previous system that can generate more reliable context data, can provide more effective inference method, and can provide more intelligent system structure.

• Knowledge Management Research
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• v.4 no.2
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• pp.55-77
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• 2003

In this study, some issues that are related to embody the original conception and ideal of action learning are explored in terms of misunderstanding and misuse of action learning in Korean corporate context. The conception of action learning is deconstructed through the lens of 'action' and 'learning' concept, followed by conceptual analysis to the nature of 'action' and 'learning'. Based upon this conceptual deconstruction of 'action' and 'learning', this study is conducted to categorize the concept of 'action' and 'learning' into several representative attributes. Categorization of 'action' and 'learning' leads to draw some adjectives, for examples, reflective, dynamic, complex, nonlinear, that are critical for characterizing action learning. That is, the nature and ideal of action learning are critically reviewed with the reconceptualization of 'action' and learning, which are deconstructed. The Discussion of final thoughts is on what kinds of knowledge perspectives action learning holds in comparison with those of knowledge management and on how to facilitate knowledge construction and sharing with action learning.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.529-536
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• 2004

Smart homes integrated with sensors, actuators, wireless networks and context-aware middleware will soon become part of our daily life. This paper describes a context-aware middleware providing an automatic home service based on a user's preference. The context-aware middle-ware utilizes 6 basic data for learning and predicting the user's preference on the multimedia content : the pulse, the body temperature, the facial expression, the room temperature, the time, and the location. The six data sets construct the context model and are used by the context manager module. The log manager module maintains history information for multimedia content chosen by the user. The user-pattern learning and pre-dicting module based on a neural network predicts the proper home service for the user. The testing results show that the pattern of an in-dividual's preferences can be effectively evaluated and predicted by adopting the proposed context model.

• Journal of Korea Game Society
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• v.14 no.1
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• pp.93-102
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• 2014

The non-player character(NPC) either cooperates with the player character to proceed the game or fight against the game player. This paper proposes the context awareness method for the natural action control of the same NPC. The context awareness method analyzes the context information of the NPC that can be utilized in the current status and creates the actions which suit the current context automatically. The context awareness method analyzes the information value of the context elements of the NPC which occur in the current context and creates natural actions of the character by utilizing the analyzed context element information. In this experiment, average performance improved by 39% and by 8% in the context awareness method as compared to the rule-based method and information gain method, respectively.

• Korea Information Processing Society Review
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• v.11 no.6
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• pp.56-75
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• 2004

In this article we address some system characteristics and challenging issues in developing Context-aware Middleware for Ubiquitous Computing. The functionalities of a Context-aware Middleware includes gathering context data from hardware/software sensors, reasoning and inferring high-level context data, and disseminating/delivering appropriate context data to interested applications/services. The Middleware should facilitate the query, aggregation, and discovery for the contexts, as well as facilities to specify their privacy policy. Following a formal context model using ontology would enable syntactic and semantic interoperability, and knowledge sharing between different domains. Moddleware should also provide different kinds of context classification mechanical as pluggable modules, including rules written in different types of logic (first order logic, description logic, temporal/spatial logic, fuzzy logic, etc.) as well as machine-learning mechanical (supervised and unsupervised classifiers). Different mechanisms have different power, expressiveness and decidability properties, and system developers can choose the appropriate mechanism that best meets the reasoning requirements of each context. And finally, to promote the context-trigger actions in application level, it is important to provide a uniform and platform-independent interface for applications to express their need for different context data without knowing how that data is acquired. The action could involve adapting to the new environment, notifying the user, communicating with another device to exchange information, or performing any other task.

• Cross-Cultural Studies
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• v.19
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• pp.313-338
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• 2010

Attitudes toward target language culture and motivation have been known as important factors in second or foreign language learning. In this study, cadets' attitudes toward the target language community and culture were investigated to find out any relationships with English achievement. Integrative or instrumental motivation in foreign military context was investigated to determine which motivation was more positively related to English proficiency. Cadets' responses were shown highly positive and internally consistent in most cases. Military cadets' attitudes toward American culture were statistically significant and could predict their English achievement. Even though integrative motivation was statistically significant, correlation with English achievement was low. However, instrumental motivation was not significant. This result implies that attitudes toward culture is an important factor in foreign language learning and integrative-instrumental motivation dichotomy might not be enough to explain specific context like cadets' English learning situation at Korea Army Academy at Youngcheon.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.198-201
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• 2022

Recently, new cyber threats targeting new technologies are increasing, and hackers' attack targets are becoming broader and more intelligent. To counter these attacks, major security companies are using traditional EDR (Endpoint Detection and Response) solutions. However, the conventional method does not consider the context, so there is a limit to the accuracy and efficiency of responding to an advanced attack. In order to improve this problem, the need for a security solution centered on XDR (Extended Detection and Response) has recently emerged. In this study, we present effective threat detection and countermeasures in a changing environment through XDR trends and development roadmaps using machine learning-based context analysis.

• Asia Marketing Journal
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• v.21 no.4
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• pp.77-89
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• 2020

Population-level learning has traditionally been used to provide an explanation for the underlying mechanism of industry change. But it has yet to examine the impact on strategic decisions such as market entry. This conceptual paper aims to provide an insight into how population-level learning affects entry likelihood by acting as a tool for interpreting population-level changes. We study this in the context of the fast-paced mobile gaming industry where population-level information is salient and develop a set of propositions with regard to the likelihood of entry.

• Korean Medical Education Review
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• v.17 no.1
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• pp.5-9
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• 2015

A teaching hospital is a place where both patient care and learning occur together. To identify the role of the teaching hospital in an effective clerkship, we first determined the features of workplace learning and the factors that affect learning in the workplace, and then we proposed a role for the teaching hospital in the clinical clerkship. Features of learning in a clerkship include learning in context, and learning from patients, supervising doctors, others in the team, and colleagues. During the clerkship, medical students learn in three-way learner-patient-teacher relationships, and students' participation in the tasks of patient care is crucial for learning. Factors that influence learning in the workplace are associated with tasks, context, and learner. Tying the three factors together, we proposed a role for the teaching hospital in the three categories: involvement in the tasks of patient care, engagement in the medical team, and engagement in the learning environment and system. Supervising doctors and team members in a teaching hospital support students' deep participation in patient care, while improving the learning environment through organizational guidelines and systems. Gathering both qualitative and quantitative data for the evaluation of a teaching hospital is important.

• Educational Technology International
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• v.13 no.1
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• pp.145-173
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• 2012

The purpose of this study is to develop collaboration scripts as an instructional means to facilitate argumentation in computer-supported collaborative learning, and to analyze their effects. To develop collaboration scripts for argumentation, researchers used activity theory as a conceptual framework and refined the design principles by design-based research. Using LAMS, collaboration scripts for argumentation were developed based on the ArgueGraph. To examine their effects, 72 participants were divided into two groups by internal scripts and randomly allocated to one of three external scripts. Applying mixed methods, researchers analyzed argumentation competence related to the cognitive aspect, examined self-efficacy related to the motivational aspect, and identified the factors influencing collaborative learning processes and outcomes. Researchers found that the internal script is a critical factor to determine the dimensions, degrees, and duration of improvement in argumentation competence. That is, learners with higher internal scripts improved highly in the quality of single arguments, while learners with lower internal scripts improved continuously in the quality of argumentation sequences. The effects of the external scripts varied with the internal script levels and supporting periods. Besides, collaboration scripts for argumentation had positive effects on learners' self-efficacy, and learners with higher internal scripts had better self-efficacy. The factors influencing collaborative learning processes and outcomes showed different results depending on the learning context. Therefore, when scripting learner's interaction in CSCL, researchers should design the scripts adaptable to a natural context of activities.