• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2001년도 학술대회지
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• pp.525-530
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• 2001

기업의 경쟁력이 지식중심으로 전환되고 있는 현대 사회의 실정과 더불어 IMF 이후 건설업계는 경영 패러다임 변화의 필요성을 인식하고 지식경영을 통해 기업의 경쟁력을 향상하고 있다. 지식경영 실천의 도구인 지식관리시스템은 기업의 지식을 관리하여 조직지식자원의 가치를 향상시키는 도구로 관리대상 지식의 형태와 특성에 따라 각기 다른 형태와 관리방법을 갖는다. 따라서 산업별 지식의 특성에 적합한 지식관리 시스템에 대한 연구가 필요하다. 본 연구에서는 건설산업 지식의 특성을 적합한 지식관리시스템의 지식관리 방안을 도출하였고, 이를 토대로 현재 구축된 건설업 KMS 지식관리의 문제점을 진단하였다.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.1017-1030
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• 2021

Constructed upon Knowledge Management (KM) processes, the current study aims to investigate the interrelationship between Knowledge Sharing (KS) attitude among the faculty members and KM processes in higher education institutes (HEIs) in Pakistan along with the intervening role of subjective norms between KM processes and KS attitude. This research incorporated the theory of Planned Behavior (TPB) and the theory of Reasoned Action (TRA) to conceptualize the KS behavior by using a sample frame of 302 academic and administrative staff from research-based HEIs in Quetta, Pakistan. A questionnaire-based survey was conducted on permanent faculty members from different universities of Quetta, Pakistan. The finding of the study shows a positive attitude among the researchers. The study empirically examined the interface between KM processes and KS attitude and higher education performance while providing valuable insights into the prevailing literature by investigating the mediating role of subject norms. The impact of subjective norms on KS attitude and KM process indicates the importance and basic determinant in organizational premises and improvement of skills of faculty management in HEIs. The partial mediation also reveals the importance of subjective norms in the development of faculty members' KM and KS attitude process.

• Journal of Contemporary Eastern Asia
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• 제12권1호
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• pp.49-63
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• 2013

This work identifies the key factors influencing the success of multidisciplinary, interdisciplinary, and trans-disciplinary R&D projects in transition economies by integrating knowledge management, organizational, inter/intra-collaboration (open-innovation), and leadership perspectives, while also addressing the perspective of the science of team science, which is an integrative approach to R&D. This is followed by providing the major sub-constructs of team science and policy implications to better facilitate multidisciplinary, interdisciplinary, and transdisciplinary R&D projects in knowledge-based transition economies.

• 한국컴퓨터정보학회논문지
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• 제21권10호
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• pp.135-142
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• 2016

In this paper, we propose a plan for the introduction of a knowledge-based system proposed by the traditional computing sciences, in order to operate the computer system computerized hospital workers effectively. Hospital computational features of the operating system for this purpose, were made about the working conditions, computational difficulties of the hospital administrator. It is necessary for a knowledge management system for results-effective IT system operational review findings apply to the hospital, where a hospital computer system having features and hospitals computational workers must be resolved on the technical and environmental constraints with It became aware of the need. This study further shows that an effective hospital computer system to derive additional operating a variety of issues to consider for the base and the introduction of a knowledge management system can gradually solve the problem.

• 국제초고층학회논문집
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• 제4권1호
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• pp.85-90
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• 2015

Advances in the technology of computational design are giving architects and engineers the opportunity to analyze buildings with complex geometries. This study explores the optimization and automation process using the parametric design method, and uses digital tools to achieve surface representation and panelization for curved shaped office buildings. In this paper, we propose parametric algorithms of dimensional and geometric constraints using the Knowledge-ware scripts embedded in Gehry Technologies' Digital Project. The knowledge-based design methods proposed in this study can be used to systemize the knowledge possessed by experts in the form of data. Such knowledge is required to promote collaboration between designers and engineers in the process of CAD/CAE/CAM. The aim of this study is to integrate the process into design, which establishes an integrated process. This integration enables two-way feedback between design and construction data by combining the methods used in designing, engineering, and construction.

• 한국전자거래학회지
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• 제5권1호
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• pp.1-18
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• 2000

As the networks (i.e., intranet and internet) proliferate all over the world, it is inevitable to move some (or all) of the enterprise activities into virtual spaces. Differently from business data, product data have complex semantics and thus are not properly exchanged among different application programs. Even though some neutral formats of product data have been developed by standard organizations, translating them among various application programs still needs the comprehensive understanding of the complex semantics. Recently, it is widely recognized that capturing more knowledge is the next step In overcome the current difficulties on sharing product data. In this paper, we present Web-based knowledge management that facilitates seamless sharing of product data among various application programs in virtual enterprises. Three types of knowledge are managed by the knowledge management system - metadata, ontology, and mapping. In this environment, we consider both business applications (e.g., ERP, SCM, and EDI System) and engineering applications (e.g., CAD and CAM system).

• ETRI Journal
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• 제38권6호
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• pp.1229-1239
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• 2016

For efficient interaction between humans and robots, robots should be able to understand the meaning and intention of human behaviors as well as recognize them. This paper proposes an interactive human intention reading method in which a robot develops its own knowledge about the human intention for an object. A robot needs to understand different human behavior structures for different objects. To this end, this paper proposes a hierarchical behavior knowledge network that consists of behavior nodes and directional edges between them. In addition, a human intention reading algorithm that incorporates reinforcement learning is proposed to interactively learn the hierarchical behavior knowledge networks based on context information and human feedback through human behaviors. The effectiveness of the proposed method is demonstrated through play-based experiments between a human and a virtual teddy bear robot with two virtual objects. Experiments with multiple participants are also conducted.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.360-363
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• 1995

In this paper, we describe the composition of frequency response bands based on experimental data of plants (controlled systems) with uncertainty and nonlinearity, and the robust stability evaluation of feedback control systems. Analysis and design of control systems using the upper and lower bounds of such experimental data would be effective as a practicable method which is not heavily dependent upon mathematical models such as the transfer function. First, we present a method to composite gain characteristic bands of frequency response of cascade connected plants with uncertainty and a recurrent inequality for the composition. Next, evaluation methods of the robust stability of multi-loop control systems obtained through feedback from the output terminals and multi-loop control systems obtained through feedback into the input terminals are described. In actual control systems, experimental data of frequency responses often depends on the amplitude of input. Therefore, we present the evaluation method of the nominal value and the width of the frequency response band in such a case, and finally give numerical examples based on virtual experimental data.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.245-252
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• 2022

Risk identification for bridge projects is a knowledge-based and labor-intensive task involving several procedures and stakeholders. Presently, risk information of bridge projects is unstructured and stored in different sources and formats, hindering knowledge sharing, reuse, and automation of the risk identification process. Consequently, there is a need to develop structured and formalized risk information for bridge projects to aid effective risk identification and automation of the risk management processes to ensure project success. This study proposes a semantic risk breakdown structure (SRBS) to support risk identification for bridge projects. SRBS is a searchable hierarchical risk breakdown structure (RBS) developed with python programming language based on a semantic modeling approach. The proposed SRBS for risk identification of bridge projects consists of a 4-level tree structure with 11 categories of risks and 116 potential risks associated with bridge projects. The contributions of this paper are threefold. Firstly, this study fills the gap in knowledge by presenting a formalized risk breakdown structure that could enhance the risk identification of bridge projects. Secondly, the proposed SRBS can assist in the creation of a risk database to support the automation of the risk identification process for bridge projects to reduce manual efforts. Lastly, the proposed SRBS can be used as a risk ontology that could aid the development of an artificial intelligence-based integrated risk management system for construction projects.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.505-509
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• 2020

Twitter is a useful medium to grasp various damage situations that have occurred in society. However, it is a laborious task to spot damage-related topics according to time in the environment where information is constantly produced. This paper proposes a methodology of constructing a knowledge structure by combining the BERT-based classifier and the community detection techniques to discover the topics underlain in the damage information. The methodology consists of two steps. In the first step, the tweets are classified into the classes that are related to human damage, infrastructure damage, and industrial activity damage by a BERT-based transfer learning approach. In the second step, networks of the words that appear in the damage-related tweets are constructed based on the co-occurrence matrix. The derived networks are partitioned by maximizing the modularity to reveal the hidden topics. Five keywords with high values of degree centrality are selected to interpret the topics. The proposed methodology is validated with the Hurricane Harvey test data.