• Korean System Dynamics Review
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• v.17 no.3
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• pp.51-90
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• 2016

Learning is naturally embedded in organizational ongoing-processes and routines. Recent many research models of organizational failure ignore how failing masks breakdowns and recoveries of organization-embedded learning as a naturally occurring process. Organizational learning is the platform in tandem with base-modules of organization in this point. Organizations learn and unlearn while they acquire, discard, and forget organizational experiences or knowledges. These processes in public sector organizations are different from learning behaviors in private sector. This study expects to explore architectural components of learning organization in public sector, focusing on distinct characteristics of public organizations, and to implement learning model based on system thinking(system dynamic) approach.

• Korean Journal of Breeding Science
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• v.43 no.2
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• pp.103-114
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• 2011

In recent years, genomic resources and information have accumulated at an ever increasing pace, in many plant species, through whole genome sequencing, large scale analysis of transcriptomes, DNA markers and functional studies of individual genes. Well-characterized species within key plant taxa, co-called "model systems", have played a pivotal role in nucleating the accumulation of genomic information and databases, thereby providing the basis for comparative genomic studies. In addition, recent advances to "Next Generation" sequencing technologies have propelled a new wave of genomics, enabling rapid, low cost analysis of numerous genomes, and the accumulation of genetic diversity data for large numbers of accessions within individual species. The resulting wealth of genomic information provides an opportunity to discern evolutionary processes that have impacted genome structure and the function of genes, using the tools of comparative analysis. Comparative genomics provides a platform to translate information from model species to crops, and to relate knowledge of genome function among crop species. Ultimately, the resulting knowledge will accelerate the development of more efficient breeding strategies through the identification of trait-associated orthologous genes and next generation functional gene-based markers.

• Educational Technology International
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• v.9 no.1
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• pp.49-77
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• 2008

As clearly suggested in the case of Wikipedia, collective intelligence is predicted to develop into the most important platform of knowledge and information in the future society. But it just remains at the level of activities for group projects in the present frame of education and so it doesn't lead to creating collective intelligence. This study looks into an 'information repository model of collective intelligence' that makes it possible to deliver an education process a priori of Shared Knowledge Reservoir to "Junior Digital Nomad", who is definitely and will be in existence, and that further enables them to be active there in reality. Based on this storage model, it suggests a practicable web system model; Junior Maphistory e-encyclopedia, which is appropriately consistent with the features of Web 2.0 and can grow into a general historical and geographical information service.

• Knowledge Management Research
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• v.23 no.1
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• pp.133-148
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• 2022

In an ever-changing tourism environment, we need to think about how to successfully attract tourists and provide them with memorable experiences. Smart tourism content is considered as a useful tourism resource for converting into an attractive tourist destination by providing new values in various tourist destinations as well as the changed tourism patterns due to COVID-19. However, there are still few successful cases of smart tourism contents that have secured economic sustainability. Accordingly, this study applied the Contingent Valuation Method (CVM) to estimate the economic value perceived by tourists for smart tourism contents based on augmented reality to develop a smart tourism content development plan that can secure economic sustainability. As a results, it was confirmed that the lower the offered amount, the higher the awareness of the new value, the higher the likelihood of willingness to pay. Based on these research results, this study presented academic and practical implications for the development of smart tourism content that secured economic sustainability.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.135-142
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• 2015

As the importance of software to society has grown, more and more schools worldwide teach coding basics in the classroom. Despite the rapid spread of coding instruction in grade schools, experience in the classroom is certainly limited because there is a gap between the curriculum and the existing computing environment such as the mobile and cloud computing. We propose an approach to fill this gap by using a mobile environment and the robot on the cloud-based platform for effective teaching. In this paper, we propose an architecture called Cloudboard that enables knowledge sharing and collaboration among knowledge providers in the cloud-based robot platforms. We also describe five representative architectural patterns that are referenced and analyzed to design the Cloudboard architecture. Our early experimental results show that the Cloudboard can be effective in the development of collective robotic systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.43-50
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• 2021

Recently, researches and projects of companies based on artificial intelligence have been actively carried out. Various services and systems are being grafted with artificial intelligence technology. They become more intelligent. Accordingly, interest in deep learning, one of the techniques of artificial intelligence, and people who want to learn it have increased. In order to learn deep learning, deep learning theory with a lot of knowledge such as computer programming and mathematics is required. That is a high barrier to entry to beginners. Therefore, in this study, we designed and implemented a web-based deep learning platform called DeepBlock, which enables beginners to implement basic models of deep learning such as DNN and CNN without considering programming and mathematics. The proposed DeepBlock can be used for the education of students or beginners interested in deep learning.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.1
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• pp.113-119
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• 2013

Despite rapid changes in the structure of industry, manufacturing remains a key industry for economic progress, promotion of trade, increased employment, and the creation of new industries. Production technologies are essential for strengthening the competitiveness of small- and medium-sized manufacturing industries. However, it is very difficult to standardize and systematically propagate production technology from an experienced worker to an inexperienced worker because these technologies are generally improved by the skilled people in a workshop. In this study, we introduce a Web-based platform system consisting of a knowledge authoring tool, technology database, semantic database, and Web portal service for sharing production technologies for the exterior housing parts of mobile products. By investigating various cellular phone designs, reference form factors for three types of mobile phone housings were designed based on the standard features. In addition, several manufacturing technologies and considerable information such as reference mold designs and molding conditions optimized using CAE and recent R&D outputs are stored in this system.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.688-710
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• 2016

Our approach permits to capitalize the expert's knowledge as business rules by using an agent-based platform. The objective of our approach is to allow experts to manage the daily evolutions of business domains without having to use a technician, and to allow them to be implied, and to participate in the development of the application to accomplish the daily tasks of their work. Therefore, the manipulation of an expert's knowledge generates the need for information security and other associated technologies. The notion of cryptography has emerged as a basic concept in business rules modeling. The purpose of this paper is to present a cryptographic algorithm based approach to integrate the security aspect in business rules modeling. We propose integrating an agent-based approach in the framework. This solution utilizes a security agent with domain ontology. This agent applies an encryption/decryption algorithm to allow for the confidentiality, authenticity, and integrity of the most important rules. To increase the security of these rules, we used hybrid cryptography in order to take advantage of symmetric and asymmetric algorithms. We performed some experiments to find the best encryption algorithm, which provides improvement in terms of response time, space memory, and security.

• Nuclear Engineering and Technology
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• v.45 no.4
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• pp.477-488
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• 2013

The PLC (Programmable Logic Controller) has been widely used to implement real-time controllers in nuclear RPSs (Reactor Protection Systems). Increasing complexity and maintenance cost, however, are now demanding more powerful and cost-effective implementation such as FPGA (Field-Programmable Gate Array). Abandoning all experience and knowledge accumulated over the decades and starting an all-new development approach is too risky for such safety-critical systems. This paper proposes an RPS software development process with a platform change from PLC to FPGA, while retaining all outputs from the established development. This paper transforms FBD designs of the PLC-based software development into a behaviorally-equivalent Verilog program, which is a starting point of a typical FPGA-based hardware development. We expect that the proposed software development process can bridge the gap between two software developing approaches with different platforms, such as PLC and FPGA. This paper also demonstrates its effectiveness using an example of a prototype version of a real-world RPS in Korea.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.193-202
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• 2017

Development of Intelligent Systems involves effective integration of large-scaled knowledge processing and understanding, human-machine interaction, and intelligent services. Especially, in our project for development of a self-growing knowledge-based system with inference methodologies utilizing the big data technology, we are building a platform called WiseKB as the central knowledge base for storing massive amount of knowledge and enabling question-answering by inferences. WiseKB thus requires an effective methodology to analyze diverse requirements convoluted with the integration of various components of knowledge representation, resource management, knowledge storing, complex hybrid inference, and knowledge learning, In this paper, we propose an integrated requirement analysis method that blends the traditional sequential method and the iterative-incremental method to achieve an efficient requirement analysis for large-scale systems.