• 한국영재학회:학술대회논문집
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• 한국영재학회 2005년도 춘계학술대회
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• pp.173-180
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• 2005

The purpose of this study was to identify common and domain-specific cognitive characteristics of gifted students based on a hierarchical structural model of human abilities. This study is based on the premise that abilities identified by tests can appear as observable characteristics in test or school situations. Abilities proposed by major models of intelligence were reviewed in terms of their power to explain cognitive characteristics of gifted students. However, due to the lack of their explanatory power and disagreement on common and domain-specific cognitive abilities, a new hierarchical structural model was conceptualized in a unique way based on interrelationships between abilities proposed by the models. The newly established model hypothesizes a cognitive mechanism that accounts for how domain-specific knowledge is formed, as well as which abilities are common and domain-specific, how they are related functionally, and how they account for common and domain-specific cognitive characteristics of gifted students. The cognitive mechanism has important implications for our understanding of the chronically controversial concepts, 'intelligence' and 'knowledge.' Clearer definitions of what intelligence is (g or multiple), what knowledge is, and how knowledge develops ('genetic or environmental,' 'rationalistic or empiricist') may result from this model.

• 지식경영연구
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• 제5권1호
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• pp.1-17
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• 2004

Based on the diffusion of innovation paradigm, this study conceptualizes the constituent components (3P) and the growth stages (6C) for knowledge management. It is critical for knowledge management efforts to identify 'where we are' and decide 'where to go' and then to manage 'how to go'. As a framework for the success of knowledge management, the 3P6C model is intended to systematically guide these efforts toward knowledge asset management and implementation, for knowledge productivity. This model is illustratively applied to such success stories as in Skandia, Buchman Lab and Hall Mark Cards. Such applications of this model show that they have been through such prior activities required in the earlier stages, and thattechnological platform is just one of the 3 key components working as an enabler, implying together the existence of growth path in KM success. Provided in the appendix are a set of exemplary scenarios in knowledge management practice for growth stage assessment.

• Journal of Korean Biological Nursing Science
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• 제24권3호
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• pp.150-160
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• 2022

Purpose: The current study investigated how clinical microbiology courses are conducted at the undergraduate nursing level in South Korea to identify the perceptions of clinical nurses regarding their knowledge and the clinical importance of microbiology and further assess their educational needs. Methods: Curricula presented on the websites of 202 undergraduate nursing institutions were reviewed. In addition, a survey assessing the knowledge and importance of clinical microbiology perceived by nurses was conducted online. A total of 150 nurses participated in the survey. Data were analyzed using descriptive statistics, correlation coefficients, t-tests, analysis of variance, Borich Needs Assessment Model, and Locus for Focus Model. Results: The results indicated that 90% of undergraduate nursing institutions offer clinical microbiology courses under various subject names. The perceived knowledge and importance of clinical microbiology were correlated; however, knowledge was consistently lower than the perceived importance of clinical biology among nurses. The structure and proliferation of novel viruses ranked highest in the educational needs of nurses based on both the Borich Needs Assessment Model and Locus for Focus Model. Conclusion: Based on the findings, this study suggests educational opportunities for clinical microbiology in hospital settings to reduce discrepancies between knowledge and the importance of clinical microbiology faced by nurses.

• 한국시스템다이내믹스연구
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• 제6권2호
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• pp.5-23
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• 2005

This paper investigates a dynamic mechanism underlying the process of knowledge creation and evolution with a focus on the SECI model(standing for Socialization, Externalization, Combination, Internalization) as proposed by Nonaka and Takeuchi(1991) and broadly accepted especially among the practitioners in knowledge management field. The SECI model provides with intuitive logic and clear delineation of knowledge types between the tacit and the explicit, and embodies an interaction dynamic. However explanations of the propelling forces for the knowledge transfer over the four quadrants of the model is yet to be made. And the transmission mechanisms are not prescribed though the model mentions knowledge is created and evolved in a spiral process. This paper, therefore attempts first to extend and elaborate it into a dynamic SECI model by identifying those propelling factors and their relationships(linkages) based on the systems thinking.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.146-158
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• 2023

Smart City is gaining attention with the advancement of Information and Communication Technology (ICT). ICT provides the basis for smart city foundation; enables us to interconnect all the actors of a smart city by supporting the provision of seamless ubiquitous services and Internet of Things. On the other hand, Crowdsourcing has the ability to enable citizens to participate in social and economic development of the city and share their contribution and knowledge while increasing their socio-economic welfare. This paper proposed a hybrid model which is a compound of human computation, machine computation and citizen crowds. This proposed hybrid model uses knowledge-based crowdsourcing that captures collaborative and collective intelligence from the citizen crowds to form democratic knowledge space, which provision solutions in areas of civic innovations. This paper also proposed knowledge-based crowdsourcing framework which manages knowledge activities in the form of human computation tasks and eliminates the complexity of human computation task creation, execution, refinement, quality control and manage knowledge space. The knowledge activities in the form of human computation tasks provide support to existing crowdsourcing system to align their task execution order optimally.

• 한국전자거래학회지
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• 제6권3호
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• pp.63-80
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• 2001

The construction of the students knowledge in e-Learning systems, namely the student modeling, is a core component used to develop e-Learning systems. However, existing e-Learning systems have many problems to share the knowledge in a heterogeneous student model and a distributed knowledge base. Because the methods of the knowledge representation are different in each e-Learning systems, the accumulated knowledge cannot be used or shared without a great deal of difficulty. In order to share this knowledge, existing systems must reconstruct the knowledge bases. Consequently, we propose a new a Case Markup Language based on XML in order to overcome these problems. A distributed e-Learning systems fan have the advantage of easily sharing and managing the heterogeneous knowledge base proposed by CaseML. Moreover students can generate and share a case knowledge to use the communication protocol of agents. In this paper, we have designed and developed a CaseML by using a knowledge markup language. Furthermore, in order to construct an intelligent e-Learning systems, we have done our research based on the design and development of the intelligent agent system by using CaseML.

• ETRI Journal
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• 제44권3호
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• pp.438-449
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• 2022

This study proposes a dependency grammar-based self-attention multilayered bidirectional long short-term memory (DG-M-Bi-LSTM) model for subject-predicate-object (SPO) tuple recognition from natural language (NL) sentences. To add recent knowledge to the knowledge base autonomously, it is essential to extract knowledge from numerous NL data. Therefore, this study proposes a high-accuracy SPO tuple recognition model that requires a small amount of learning data to extract knowledge from NL sentences. The accuracy of SPO tuple recognition using DG-M-Bi-LSTM is compared with that using NL-based self-attention multilayered bidirectional LSTM, DG-based bidirectional encoder representations from transformers (BERT), and NL-based BERT to evaluate its effectiveness. The DG-M-Bi-LSTM model achieves the best results in terms of recognition accuracy for extracting SPO tuples from NL sentences even if it has fewer deep neural network (DNN) parameters than BERT. In particular, its accuracy is better than that of BERT when the learning data are limited. Additionally, its pretrained DNN parameters can be applied to other domains because it learns the structural relations in NL sentences.

• 디지털산업정보학회논문지
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• 제10권1호
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• pp.157-167
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• 2014

Increasing productivity of knowledge workers is a significant issue in the 21st century referred as knowledge-based society. The core key word is behavior of knowledge transfer among members of an organization. The objective of this study is to investigate a model based on Triandis theory and Social Capital theory. This explored the antecedent factors of knowledge Transfer in ITO(Information Technology Outsourcing) Organization. Data were derived from 42 respondents working IT Cooperation in Seoul, Korea. In this paper, we introduce the research model for the knowledge transfer. In order to validate the proposed research model, social network analysis tool, UCINET, a structural equation modeling tool, SmartPLS, was utilized. The empirical result showed that, all antecedent factors (intention of knowledge sharing, anticipated reciprocal relationships, subjective norm, closeness network centrality) of knowledge transfer behavior were significant. In conclusion, findings and implications were discussed and limitations of the study and future research directions were suggested.

• 한국BIM학회 논문집
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• 제12권4호
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• pp.52-60
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• 2022

Recently, the demand for connection between various heterogeneous dataset and BIM as a construction data model hub is increasing. In the past, in order to connect model between BIM and heterogeneous dataset, related dataset was stored in the RDBMS, and the service was provided by programming a method to link with the BIM object. This approach causes problems such as the need to modify the database schema and business logic, and the migration of existing data when requirements change. This problem adversely affects the scalability, reusability, and maintainability of model information. This study proposes an ontology BIM-based knowledge service framework considering the connectivity and scalability between BIM and heterogeneous dataset. Through the proposed framework, ontology BIM mapping, semantic information query method for linking between knowledge-expressing dataset and BIM are presented. In addition, to identify the effectiveness of the proposed method, the prototype is developed. Also, the effectiveness and considerations of the ontology BIM-based knowledge service framework are derived.

• 한국문헌정보학회지
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• 제40권2호
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• pp.103-123
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• 2006

금융기관의 지식경영 초기 단계 이후부터는 지속적인 지식 창출과 효율적인 지식 검색이 지식경영의 핵심 요인으로 보고, 지식 창출의 한 방안으로 e-러닝을 제시하고, 효율적인 지식 검색 체제를 구축하기 위해서 리포지토리에 저장된 학습객체, 지식객체, 자료실 정보객체를 유사성에 따라 분류하고 상호 연관관계를 맺음으로써 키워드 검색은 물론 분류 검색과 연관 검색을 가능하게 하는 토픽맵 개념에 기반을 둔 지식맵을 활용한 통합 리포지토리 모형을 제안해 보았다. 모형 구현을 위해서 사용된 연구 방법에는 지식 관리 현황을 파악하기 위해서 세 보험회사들을 대상으로 사례 연구를 실시하였고, 기존의 토픽맵 기반의 실험적인 정보시스템들도 분석, 참조하였다. 디렉토리 형식의 전통적인 지식맵은 관련된 지식을 연계시키기가 어려워 지식관리시스템의 효율적인 브라우징이나 검색에 걸림돌로 작용하고 있는데 본 연구에서 제안된 모형은 이러한 문제점들을 개선할 하나의 안으로 이용될 수 있을 것이다.