• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.40-51
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• 2008

To realize advanced collaboration environments for knowledge workers distributed geographically, there are extensive researches in ubiquitous computing environments. Especially, to cope with several known problems in traditional collaboration tools such as limited display resolution, uncomfortable shared documentation, difficult operation of collaboration environments, various approaches are attempted in the aspect of framework design. In this paper, we design a framework for collaboration environments covering hardware/software/networking architecture to flexibly coordinate a set of collaboration services and devices considering users' expectation and node capabilities. Based on the proposed framework, we develop the collaboration environment supporting the interactive networked tiled display enabling media/data sharing via networking, display interaction using pointing/tracking, and high-resolution tiled display. Finally the demonstration of the developed prototype is introduced to prove the possibility of its realization.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.214-227
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• 2008

As cellular network technologies continue to evolve, various network standards coexist in most CDMA-based cellular networks. This means that mobile device users access mobile services over different network bandwidths according to the users' positions or the mobile devices' network access capabilities. Such differences of network bandwidths cause big differences in service response times. To address this problem, we present a framework called CANS (Context-Aware framework for mobile Navigation Services), which takes into account the user's network profile to adapt the contents for CDRG(Centrally Determined Route Guidance) navigation services for cellular phones. To the best of the authors' knowledge, CANS is the first context-aware framework to make mobile navigation services more feasible. The experimental results under commercial CDMA network show that CANS is able to provide similar service response times regardless of type of wireless network to which users connect by adapting the contents to network bandwidths.

• The Journal of Society for e-Business Studies
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• v.14 no.2
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• pp.23-39
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• 2009

Increasing number of business and technology expansion has sparked a growing interest in IT service business evaluation. However, it is not an easy task to come up with a fair and objective evaluation of IT service business due to the difficulties involved in the definition performance assets (marketing, human resources etc.) and knowledge assets with respect to its industry. Several public organizations in Korea are developing a "standardized evaluation protocol" based on qualitative method. But the standard evaluation protocol does not provide suitable guidelines on how to construct and evaluate the key index of IT service business. The main objective of this study is in the development of a systematic approach for the evaluation of IT service business competitiveness by emphasizing the qualitative and quantitative index to be evaluated in the framework. Application of the developed framework and guideline format showed that the used of the framework in this study provided relatively more efficient evaluation results in IT service industry.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.89-94
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• 2010

This paper proposes an educational robot game framework for novice students in k-12 to learn concepts of programming through interesting experiences. It is designed to be able to enjoy robot games without technical knowledge of robotics and programming. For this, in the proposed robot game framework, educational robots based on line-tracer are used and the programming APls that can be used for various educational programming languages are offered. And the proposed robot game framework also offers a game board to create several games with easy operations. Additionally, through experiments, it shows that novice students are able to create different games that have several game solutions for various programming using this robot game framework.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.69-87
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• 2008

The Web is evolving toward the Semantic Web. Ontologies are considered as a crucial component of the Semantic Web since it is the backbone of knowledge representation for this Web. However, most of these ontologies are still built manually. Manual building of an ontology is time-consuming activity which requires many resources. Consequently, the need for automatic ontology extraction tools has been increased for the last decade, and many tools have been developed for this purpose. Yet, there is no comprehensive framework for evaluating such tools. In this paper, we proposed a set of criteria for evaluating ontology extraction tools and carried out an experiment on four popular ontology extraction tools (i.e., OntoLT, Text-To-Onto, TERMINAE, and OntoBuilder) using our proposed evaluation framework. The proposed framework can be applied as a useful benchmark when developers want to develop ontology extraction tools.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.992-1000
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• 2022

Heritage buildings (HBs) as structures with historical and architectural relevance that form an integral part of contemporary society. HBs deserve to be protected for as long as possible to retain their significance. Therefore, prioritizing HB maintenance management (HBMM) is pertinent. However, the decision-making process of HBMM can be relatively daunting. The decision-making challenge may be attributed to the multiple 'stakeholders' expectation and requirement which needs to be met. To this end, professionals in the built environment have identified the need to apply the strategic concept of facilities management (FM) in decision making. However, studies exploring the application of FM in decision-making seem lacking. To bridge this gap, this study focuses on developing a framework for strategic decision-making HBMM, which helps achieve HBMM sustainability. At the study's inception, relevant works of literature in the domains of HBMM and FM were conducted. This review helped identify contemporary maintenance practices and their applicability to HBMM. Afterward, a conceptual framework to aid decision-making in HBMM was developed. This framework integrated the concept of FM scope (people, place, process, and technology) while ensuring that decisions and plans were made at strategic, tactical, and operational levels. The conceptual framework presents a holistic guide for professionals in HBMM to ensure that decision processes and outcomes are practical and efficient. It also contributes to the existing body of knowledge on the integration of FM in HBMM. Furthermore, it will help achieve HB sustainability through an effective decision-making process.

• Informatization Policy
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• v.21 no.3
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• pp.85-101
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• 2014

This study analyzed the influencing factors for knowledge sharing at GKMC, and then tried to illuminate the policy meanings implied in the results. To build a framework of analysis, reviewing the KM-related studies, the author selected five influencing factors for knowledge sharing, such as CMC quality, community commitment, structural social capital, cognitive social capital, and relational capital, and actors, and identified the fact that all the factors have a positive effect on knowledge sharing. In the case of Kwang-ju metropolitan city, the first factor that affects knowledge sharing is community commitment, the second one is CMC quality, and the third one is structural social capital. This result means that to succeed in knowledge sharing, the local government managers should try to shape the bonding among members, and then to get rid of the causes of complaints. In addition, local government also needs to predict problems claims and take proper actions for GKMC to be used conveniently through monitoring their work continuously. Furthermore, they should make a free and happy working environment, closely examining the change of the relationship among social capitals.

• Korean Journal of Cognitive Science
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• v.10 no.4
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• pp.71-83
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• 1999

Conventional symbolic inference systems lack flexibility because they do not well reflect flexible semantic structure of knowledge and use symbolic logic for their basic inference mechanism. For solving this problem. we have recently proposed the 'Connectionist Semantic Network(CSN)' as a model for flexible knowledge representation and inference based on neural networks. The CSN is capable of carrying out both approximate reasoning and commonsense reasoning based on similarity and association. However. we have difficulties in representing general and structured high-level knowledge and variable binding using the connectionist framework of the CSN. In this paper. we propose a hybrid system called SymCSN(Symbolic CSN) that combines a symbolic module for representing general and structured high-level knowledge and a connectionist module for representing and learning low-level semantic structure Simulation results show that the SymCSN is a plausible model for human-like flexible knowledge representation and inference.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.4
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• pp.1-17
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• 2020

Along with the development of information technology, the digitalization of archives has also been accelerating. However, digital archives have limitations in effectively searching, interlinking, and understanding records. In response to these issues, this study proposes a knowledge graph that represents comprehensive relationships among heterogeneous entities in digital archives. In this case, the knowledge graph organizes resources in the archives on the Korean financial crisis of 1997 by transforming them into named entities that can be discovered by machines. In particular, the study investigates and creates an overview of the characteristics of the archives on the Korean financial crisis as a digital archive. All resources on the archives are described as entities that have relationships with other entities using semantic vocabularies, such as Records in Contexts-Ontology (RiC-O). Moreover, the knowledge graph of the Korean Financial Crisis of 1997 is represented by resource description framework (RDF) vocabularies, a machine-readable format. Compared to conventional digital archives, the knowledge graph enables users to retrieve a specific entity with its semantic information and discover its relationships with other entities. As a result, the knowledge graph can be used for semantic search and various intelligent services.