• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.847-859
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• 2019

Purpose: The companies must be located in the area, scale up, create jobs, and return to the local economy. This paper attempted to analyze empirically the relationship between regional context and entrepreneurial orientation(EO) in the region of Korea. Methods: This paper analyzed survey data and regional statistics. We measured EO by region and then examined which regional context affect EO. Regional contexts were measured by population, economic size, budget size, firm size, innovation capacity, and education level. EO was measured by innovativeness, risk taking, proactiveness, autonomy, competitive aggressiveness, and need for achievement. Results: EO was high in the region where the budget size per thousand population, the number of manufacturers per thousand population, the number of new corporations per thousand population, the number of R&D personnel per thousand population, and the number of students of higher education institutions per thousand population were high. Conclusion: The implications of this paper are that regional context affect EO, and there are differences in budget scale, firm size, innovation capacity, and education level. In regions with many investment resources for innovation and startups and manufacturers, the number of R&D personnel and students of higher education institutions (future R&D personnel), in particular, determines EO.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.2
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• pp.5-25
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• 2011

This study aims to identify the most effective statistical feature selecting method and context window size for word sense disambiguation using supervised methods. In this study, features were selected by four different methods: information gain, document frequency, chi-square, and relevancy. The result of weight comparison showed that identifying the most appropriate features could improve word sense disambiguation performance. Information gain was the highest. SVM classifier was not affected by feature selection and showed better performance in a larger feature set and context size. Naive Bayes classifier was the best performance on 10 percent of feature set size. kNN classifier on under 10 percent of feature set size. When feature selection methods are applied to word sense disambiguation, combinations of a small set of features and larger context window size, or a large set of features and small context windows size can make best performance improvements.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.567-582
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• 2011

The growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.18-27
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• 2020

This study is to corroborate the relationship between organizational size and performance in the Korean government context. Hence, this study aims to advance research on the relationship between organization size and performance by considering mediating variable: organizational goal ambiguity, which helps understand how organizational size affects organizational goal ambiguity in government and the organizational goal ambiguity has an influence on organizational performance. Bases on theoretical review, we assume that there is the inverted U-shaped relationship between the number of employees and budget size and organizational performance. From the results of path analysis, it shows that organizational size in the Korean government has a negative correlation, "a linear relationship", with organizational performance. Budget size has mediating variables, but the number of employees not. We try to suggest implications on the relationship between organizational size and performance in terms of theoretical perspectives in the context of the Korean government.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.139-143
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• 2003

This paper is a report on in-progress investigation on antecedents of IS success in small and medium size enterprises. Previous studies on IS success in SME context largely extends research models derived from a large enterprise context. This research applies the grounded theory approach to 1109 ISP outputs exploring SME specific constructs in successful IS implementation and management. When successful, results of this research will provide insights into theories of IS in SME context that may practically applicable to IS practice in SMEs.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.27-44
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• 2008

Owl-based ontology is useful to realize the context-aware services which are composed of the distributed and self-configuring modules. Many ontology-based inference engines are developed to infer useful information from ontology. Since these engines show the uniqueness in terms of speed and information richness, it's difficult to ensure stable operation in providing dynamic context-aware services, especially when they should deal with the complex and big-size ontology. To provide a best inference service, the purpose of this paper is to propose a novel methodology of context-aware engine selection in a contextually prompt manner Case-based reasoning is applied to identify the causality between context and inference engined to be selected. Finally, a series of experiments is performed with a novel evaluation methodology to what extent the methodology works better than competitive methods on an actual context-aware service.

• Journal of The Korean Association For Science Education
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• v.24 no.4
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• pp.774-784
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• 2004

In the previous study, six factors which could disturb students' problem solving in an everyday context were identified and discussed. In this study, teaching materials to help students overcome those disturbing factors for successful problem solving in an everyday context were developed and applied to twenty-nine grade 10 students, and the effects of teaching materials were analyzed. According to the analysis of the correlation between the performance in everyday context problem solving and the benefit from the teaching materials, it was found that students who received the help from the teaching materials showed better performance with statistical significance. And students noted that teaching materials were helpful for them to solve the physics problems. Analyzing the overall performance of students in solving the everyday context problem, students in the experimental group showed better performance than the control group and this performance difference was larger among low-score students in school science testing. However, these differences were not statistically significant because the sample size was small. And, based on the analysis of interviews with students, it was also found that some students who showed low performance might not receive help from the teaching materials because the materials were too complex to be read easily, or because the basic concepts needed to solve the problem were not understood. Therefore, the results obtained from the interviews will be used to design more effective teaching for problem solving in an everyday context.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.254-263
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• 2006

Ontology-based context models are widely used in ubiquitous computing environment because they have advantages in the acquisition of conceptual context through inferencing, context sharing, and context reusing. Among the benefits, inferencing enables context-aware applications to use conceptual contexts which cannot be acquired by sensors. However, inferencing causes processing delay and thus becomes the major obstacle to the implementation of context-aware applications. The delay becomes longer as the amount of contexts increases. In this paper, we propose a context pre-fetching method to reduce the size of contexts to be processed in a working memory in attempt to speed up inferencing. For this, we extend the query-tree method to identify contexts relevant to the queries of a context-aware application. Maintaining the pre-fetched contexts optimal in a working memory, the processing delay of inference reduces without the loss of the benefits of ontology-based context model. We apply the proposed scheme to our ubiquitous computing middleware, Active Surroundings, and demonstrate the performance enhancement by experiments.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.4
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• pp.36-44
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• 1997

An efficient context-free multiple-object segmentation using attention operator based on modified generalized symmetry transform is proposed and implemented by modifying a radial basis function network. By using the difference of intensity gradient, instead of te intensity gradient itself, in generalized symmetry tranform so as to make the attention operator to preserve the edges of the objects shape, an efficient context-free multiple-object segementation is proposed in which no a priori shape informtion on the objects is requried. The attention operator is implemented by using a modified radial basis function network which can reflect symmetry, and by using te edge pyramid of the input image, both of the local and the global symmetry of the objects are reflected simultaneously to make the multiple-object with different sizes be segmented with a singel fixed-size $n\timesm$ can be done with O(n) complexity. The simulaton results show that the proposed algorithm can efficiently be used in context-free multiple-object segmentation even for the low contrast IR images as well as for the images from the camera.

• Journal of Information Technology Applications and Management
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• v.9 no.3
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• pp.13-30
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• 2002

ebXML (Electronic Business using extensible Markup language), sponsored by UN/CEFACT and OASIS, is a modular suite of specifications that enables enterprises of any size and in any geographical location to conduct business over the Internet. Using ebXML, companies now have a standard method to exchange business messages, conduct trading relationships, communicate data In common terms and define and resistor business processes. It is the mission of ebXML that provides an open XML-based infrastructure enabling the global use of electronic business information in an interoperable, secure and consistent manner by all parties for creating a single e1ectronic electronic market. This paper briefly overviews the concept of core component, context, assembly rule and context rule. Then, It designs by standard specifications of ebXML core component commonly used in an industry and among industries, and assembles business messages by using XML schema. Therefore, it suggests the mechanism which effectively exchanges business messages among the trading partners. This paper designs core component by using only three business messages of retail industry : orders, dispatch report, sales report.