• Journal of the Korean School Mathematics Society
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• v.22 no.3
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• pp.241-256
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• 2019

In this paper, we analyzed the types of tasks presented in the 'Probability and Statistics' textbooks and how the cognitive competences required to perform the tasks provide students with opportunity-to-learn. To this end, the analysis of the 9 books of the 'Probability and Statistics' test textbooks according to the 2015 revised mathematics curriculum showed that the context-based tasks(CF type, RE type) ranged from 67.5% to 78.0% of the total number of tasks in each textbook, but the ratio of relevant and essential tasks related to real life is from 0.4% to 2.0%, it was found that most of the context-based tasks presented in the textbooks were disguised as real life materials. The cognitive competences of context-based tasks ranged from 29.6% to 50.0% in reproduction category, from 33.8% to 54.3% in connection category, and from 8.8% to 20.0% in reflection category. As a result, there was not enough opportunity-to-learn for students to experience reflective cognitive processes.

• ETRI Journal
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• v.29 no.2
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• pp.169-178
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• 2007

With the advent of ubiquitous computing environments, it has become increasingly important for applications to take full advantage of contextual information, such as the user's location, to offer greater services to the user without any explicit requests. In this paper, we propose context-aware active services based on context-aware middleware for URC systems (CAMUS). The CAMUS is a middleware that provides context-aware applications with a development and execution methodology. Accordingly, the applications based on CAMUS respond in a timely fashion to contextual information. This paper presents the system architecture of CAMUS and illustrates the content recommendation and control service agents with the properties, operations, and tasks for context-aware active services. To evaluate CAMUS, we apply the proposed active services to a TV application domain. We implement and experiment with a TV content recommendation service agent, a control service agent, and TV tasks based on CAMUS. The implemented content recommendation service agent divides the user's preferences into common and specific models to apply other recommendations and applications easily, including the TV content recommendations.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.434-443
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• 2016

Users can set manually Android phone to do particular tasks on some situations. This type of setting is inconvenient, and also provide with unnecessary services, which don't consider users' situation. In this research, we design and implement a context-aware automatic task setting application. Users can get context-aware service by setting desired tasks based on contexts using this system. We design a language for describing context-action rules, and statically check validity of context-action rules by performing syntax and semantic check.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.617-628
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• 2005

The services for ubiquitous computing environments have to provide automatically user-specific adaptive services in dynamically changed environments with many informations provided by both a user and his/her environment. Workflows used in business and distributed computing environments support service automation by connecting many tasks with rules or orderings of tasks. Therefore we must specify context information on transition condition to support context-aware services by adapting a workflow to ubiquitous computing environments. In this paper, we present a structural context model to specify context information on transition constraints of the workflow. And we propose an uWDL Ubiquitous Workflow Description Language) based on web services, which provides web service interfaces which are standardized and independent on heterogeneous and various platforms, protocols, and languages. The uWDL tan be interpreted and executed by a workflow engine, and provide users autonomic services based on context-awareness.

• Communications of Mathematical Education
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• v.33 no.2
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• pp.123-139
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• 2019

This study analyzed how problem-posing tasks included in Korean middle school mathematics textbooks were distributed in terms of content area, task type, and context of task to investigate that the mathematics textbooks are giving students ample opportunities for problem-posing activities. The analysis of 10 mathematics textbooks for first grade in middle school according to the revised mathematics curriculum in 2015 found that the problem-posing tasks contained in the textbooks are insufficient in quantity and not evenly distributed in terms of content areas. There were also more problem-posing tasks with relatively moderate constraints than those with strong or weak constraints in terms of mathematical constraints. In addition, there were more problem-posing tasks that were not requiring students to make a new context, and more often camouflage contexts were used. Based on this, implications for improving mathematics problem-posing tasks in mathematics textbook were suggested.

• School Mathematics
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• v.17 no.3
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• pp.493-513
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• 2015

This study is based on the perspective that tasks in local and global contexts are important to raise students' ability to mathematically analyze and solve diverse phenomena and social issues as members of future civil society. Therefore, this study analyzes 880 real world tasks from 13 types of 7th grade textbook based on 2009 revised Curriculum. As a result of analyzing tasks by using 3 types of context category and 9 types of ways as analysis framework and allowing repetitive coding, personal context was most frequent in the context of Younbokhap. In level of Integrated ways of Yungbokhap, sequential model in which other subjects' topics were not directly related to mathematics problem or presented in simple description is most frequent. The result shows that the textbooks are too limited to develop learner's competencies. Through such analysis result, we discuss about the necessity and methods of developing tasks which allow learners to study further in future society and global context and which connect other subjects' knowledge and social issue with mathematics in deeper level.

• Journal of Information Technology Applications and Management
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• v.14 no.2
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• pp.11-26
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• 2007

In this paper we suggest a context-driven configuration model of virtual businesses to form a business network model consisting of role-based, interaction-centered business partners. The model makes use of the subcontext concept which explicitly represents actors and interactions in virtual business (VB) context. We separate actors who have capacities on tasks in a specific kind of role and actor subcontext which models requirements in specific interaction subcontext. Three kinds of actors are defined in virtual service chains, service user, service provider, and external service supporter. Interaction subcontext models a service exchange process between two actor subcontexts with consideration of context dependencies like task and quality dependencies. Each subcontext may be modeled in the form of a situation network which consists of a finite set of situation nodes and transitions. A specific situation is given in a corresponding context network of actors and interactions. It is illustrated with a simple example.

• Journal of Information Science Theory and Practice
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• v.2 no.3
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• pp.6-17
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• 2014

The purpose of this study is to examine to what extent the context in which people interact with online information affects people's credibility perceptions. In this study, credibility assessment is defined as perceptions of credibility relying on individuals' expertise and knowledge. Context has been characterized with respect to three aspects: Context as user goals and intentions, context as topicality of information, and context as information activities. The data were collected from two empirical studies. Study 1 was a diary study in which 333 residents in Michigan, U.S.A. submitted 2,471 diary entries to report their trust perceptions associated with ten different user goals and nine different intentions. Study 2 was a lab-based study in which 64 subjects participated in performing four search tasks in two different information activity conditions - information search or content creation. There are three major findings of this study: (1) Score-based trust perceptions provided limited views of people's credibility perceptions because respondents tended to score trust ratings consistently high across various user goals and intentions; (2) The topicality of information mattered more when study subjects assessed the credibility of user generated content (UGC) than with traditional media content (TMC); (3) Subjects of this study exerted more effort into making credibility judgments when they engaged in searching activities than in content creation. These findings indicate that credibility assessment can or should be seen as a process-oriented notion incorporating various information use contexts beyond simple rating-based evaluation. The theoretical contributions for information scientists and practical implications for web designers are also discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2881-2894
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• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.2
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• pp.68-77
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• 2003

The Least-Laxity First(or LLF) scheduling algorithm assigns the highest priority to a task with the least laxity, and has been proved to be optimal for a uni-processor and sub-optimal for a multi-processor. However, this algorithm Is Impractical to implement because laxity tie results in the frequent context switches among tasks. In this paper, a Modified Least-Laxity First on Multiprocessor(or MLLF/MP) scheduling algorithm is proposed to solve this problem, i.e., laxity tie results in the excessive scheduling overheads. The MLLF/MP is based on the LLF, but allows the laxity inversion. MLLF/MP continues executing the current running task as far as other tasks do not miss their deadlines. Consequently, it avoids the frequent context switches. We prove that the MLLF/MP is also sub-optimal in multiprocessor systems. By simulation results, we show that the MLLF/MP has less scheduling overheads than LLF.