• Korean System Dynamics Review
• /
• v.10 no.1
• /
• pp.5-32
• /
• 2009

This paper revisited the key advances on System Dynamics modeling about traditional macro-economic models and economic growth structures, and then tries to elaborate a new model based on the endogenous growth theory that incorporates new growth factors, relevant to knowledge/technology as well as the Environment, into traditional growth models. Accordingly, the new model augments the acceleration and multiplier loops and the balancing ones representing market clearing mechanism with a simple numerical example. The authors thus provides macroeconomic System Dynamics analysts with a milestone to model macro-economic structures reflecting on traditional and cutting-edge theories on sustainable economic growth and general equilibrium modeling.

• Journal of Information Technology Services
• /
• v.8 no.1
• /
• pp.143-163
• /
• 2009

The study investigates the challenge of knowledge maintenance in the KMSs. Knowledge pieces are the embodiment of structures in an organization and need to be modified tuned to environmental change over time. Since the change of knowledge in the KMS is not made automatically, it requires user's active participation which is called maintenance action. This study shows that users are not voluntary in taking maintenance action with empirical data based upon knowledge pieces that are already established in the KMS. This article shows that the intention of maintaining KMS is negatively influenced by KM-related culture, organizational culture and the authority of knowledge piece rather than the organizational demography. An organizational culture has an influence directly upon the intention of maintaining knowledge but influence upon KM-related culture or the authority of knowledge piece, the influence indirectly related to the intention of maintaining knowledge. It can be argued that the organizational demography have only meager influence upon the intention of maintaining knowledge only by KM-related culture. This research has the implication that what factors are to be considered in maintaining knowledge pieces over time for the organization managers.

• 한국경영정보학회:학술대회논문집
• /
• 2007.11a
• /
• pp.284-293
• /
• 2007

In the present competitive organizational environment more organizations are implementing knowledge management initiatives to gain strategic advantage. One such initiative is that of implementing electronic knowledge repositories (EKR) which often leads to a rapid increase in the quantity of information employees have to process daily; raising concerns of employees being overloaded. This is especially true for current EKRs using distributive technology, enabling customizable individual workspaces which can result in loose knowledge structures. This paper identifies a new type of information overload (IO), extending the concept as occurring in both knowledge seekers and contributors and uses cognitive dissonance theory to provide evidence that IO can change employees' perception of EKR usage. This research paper provides the first empirical evidence that overload has no sufficient affect on EKR continuance intention directly, but has significant negative affect on the two main success measures; perceived usefulness and satisfaction of the system.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.43 no.6
• /
• pp.187-196
• /
• 2001

In this study, by using the natural language processing of the field of artificial intelligence, automated index was performed. And then, the Natural Language Processing Interface for knowledge representation(NALPI) has been developed. Furthermore, the DEsign KnOwledge DataBase(DEKODB) has been also developed, which is designed to interlock the knowledge base. The DEKODB processes both the documented design-data, like a concrete standard specification, and the design knowledge from an expert. The DEKODB is also simulates the design space of structures accordance with the production rule, and thus it is determined that DEKODB can be used as a engine to retrieve new knowledge and to implement knowledge base that is necessary to the development of automatic design system. The application field of the system, which has been developed in this study, can be expanded by supplement of the design knowledge at DEKODB and developing dictionaries for foreign languages. Furthermore, the perfect automation at the data accumulation and development of the automatic rule generator should benefit the unified design automation.

• Asia pacific journal of information systems
• /
• v.8 no.1
• /
• pp.43-64
• /
• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention to the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy(KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance, On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.

• Knowledge Management Research
• /
• v.18 no.4
• /
• pp.287-306
• /
• 2017

This research focus on the effect of developers' participation structure in knowledge creation and knowledge sharing activities in open source software development projects. Based on preferential selection theory, hypotheses of relationship between a developers' concentration of knowledge creation/sharing activities and collaboration performance was derived. To verify the hypotheses, we use the Gini coefficient in the commit contribution of the developers (knowledge creation) and the centralization index in the repository issue network (knowledge sharing network). Using social network analysis, this paper calculates centralization index from developers in the issue boards in each repository based on data from 837 repositories in GitHub, a leading open source software development platform. As a result, instead of all developers creating and sharing knowledge equally, only a few of developers creating and sharing knowledge intensively further improve the performance of the open collaboration. In other words, a few developers predominantly providing commit and actively responding to issues raised from other developers enhance the project performance. The results of this study are expected to be used by developers who manage open source software project as a governance strategy, which could improve the performance of open collaboration.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.18
• /
• pp.8351-8358
• /
• 2016

Electronic cleansing is an image post processing technique in which the tagged colonic content is subtracted from colon using CTC images. There are post processing artefacts, like: 1) soft tissue degradation; 2) incomplete cleansing; 3) misclassification of polyp due to pseudo enhanced voxels; and 4) pseudo soft tissue structures. The objective of the study was to subtract the tagged colonic content without losing the soft tissue structures. This paper proposes a novel adaptive method to solve the first three problems using a multi-step algorithm. It uses a new edge model-based method which involves colon segmentation, priori information of Hounsfield units (HU) of different colonic contents at specific tube voltages, subtracting the tagging materials, restoring the soft tissue structures based on selective HU, removing boundary between air-contrast, and applying a filter to clean minute particles due to improperly tagged endoluminal fluids which appear as noise. The main finding of the study was submerged soft tissue structures were absolutely preserved and the pseudo enhanced intensities were corrected without any artifact. The method was implemented with multithreading for parallel processing in a high performance computer. The technique was applied on a fecal tagged dataset (30 patients) where the tagging agent was not completely removed from colon. The results were then qualitatively validated by radiologists for any image processing artifacts.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.11 no.2
• /
• pp.5-23
• /
• 2000

This study explores the relationships between knowledge and classification. Classification schemes have properties that show the representation of entities and relationships in structures that reflect knowledge being classified. Four representative classifying methods. i. e. hierarchies, trees, paradigms, and faceted analysis those brings new knowledge are analyzed and those strengths and weaknesses are described. Based upon the analysis, the links between knowledge and classification are verified. Finally a better way of representing knowledge structure through classification schemes in the future is suggested.

• ETRI Journal
• /
• v.38 no.6
• /
• pp.1229-1239
• /
• 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.

• 한국항공운항학회:학술대회논문집
• /
• 2006.05a
• /
• pp.32-37
• /
• 2006