• Asia pacific journal of information systems
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• 제32권1호
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• pp.151-167
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• 2022

This paper is motivated by social influence theory implying the multilevel nature of knowledge management (KM) in an organization. Organizational knowledge is generated and distributed by individuals from different groups across organizational boundaries. Its transfers are supported by IS/IT practice, i.e., the individual and collective use of the technology available in the organization. I propose a multilevel perspective to explain how IS/IT practice supports multilevel KM capabilities to manage organizational knowledge successfully and how the effectiveness of multilevel KM capabilities expands into the improvement of multilevel task-related organizational performance. The multilevel KM theory extends the knowledge-based view of the firm by describing the dynamic process through which strategic values of knowledge are generated by IS/IT practice across the organizational levels. This paper also discusses multilevel insights on the strategic value of organizational learning based on the social context of organizations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1071-1076
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• 2003

In this work, we propose a new framework of robot control for a variety of applications to our unstructured everyday environments. Programming robots can be a very time-consuming process and seems almost impossible for ordinary end users. To cope with this, this work is to provide a software framework for building robot application programs automatically, where we have robots learn how to accomplish a commanded task from the object. An integrated sensing and computing tag is embedded into every single object in the environment. In the robot controller, only the basic software libraries for low-level robot motion control are provided from the robot manufacturer. The main contributions of this work is to develop a server platform that we call Omniscient Server that generates the application programs and send them to the robot controller through the network. The object-related information from the object server merges into robot control software to generate a detailed application program based on the task commands from the human. We have built a test bed and demonstrated that a robot can perform a common household task within the proposed framework.

• The Journal of Asian Finance, Economics and Business
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• 제5권2호
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• pp.81-94
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• 2018

The purpose of this study is to substantiate the affecting factors of informal learning outcomes for professions in various dimensions of an individual and organization. In specific, the study analyzed the effects of learning motivation, job characteristics, and a supportive learning environment which have on task-related knowledge acquisition, adapting to organization and understanding contexts, relationship formation, and improving self-development-ability. The participants of the study were 261 professionals working at four major accounting firms in South Korea. Multiple regression models were applied step by step for analysis. In this study, the informal learning of professionals working at four major accounting firms is influenced by various factors of learning motivation, job characteristics, and a supportive learning environment. The detailed analysis results were as follows. Firstly, peer-support showed the most positive effect on task-related knowledge acquisition. Secondly, for adapting to organization and understanding contexts, task autonomy showed the greatest effect. Thirdly, peer-support was found to be the most important factor for relationship formation. Fourthly, for improving self-development ability, learning goal orientation showed to be the most important factor. The various factors facilitated the professional learning by empirical identification. The study presented practical implications for creating an effective informal learning support environment.

• 지식경영연구
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• 제14권5호
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• pp.81-100
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• 2013

In this era of cut-throat competition, innovation is a source of competitive advantage, and securing core competency through innovation plays a pivotal role in ensuring the survival and growth of an organization. In an organization, R&D team is a core division driving innovation, and creative tension and conflict among researchers fuels innovative performance. Despite heated debate over the positive and negative effects of conflict, insufficiently-identified process factors have left sophisticated mechanisms between conflicts and effects unaddressed. This study assumes that team learning behaviors can bean important process factor given that conflict propels learning, and that learning is a decisive factor in creating competitive advantage. This study conducted an empirical analysis of the relationship between relationship/task conflict and team innovative performance, and the mediating role of team learning behaviors using data collected from a questionnaire sent out to the heads of 262 R&D teams and second highest-ranking officials thereof. The analysis conducted based on structural equation model indicates that relationship conflict has negatively affected team learning behaviors, whereas task conflict has positively influenced team learning behaviors(full mediation effect), team learning behaviors has positively influenced team innovative performance. Based on these results, the study has suggested implications of intra-team conflict and team learning behaviors for team innovative performance.

• Journal of Information Processing Systems
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• 제13권6호
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• 영어영문학
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• 제57권6호
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• pp.1017-1041
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• 2011

This study investigates Korean EFL learners' awareness and use of the English existential there-construction by examining data collected from 54 Korean EFL learners of English by means of a pragmalinguistic judgment task and a controlled discourse completion task. The results of the judgment task reveal that lower proficiency learners rated canonical sentences and existentials with a preposed locative best in the communicative situations where the use of existentials would have been most appropriate. A comparison of the ratings by more proficient learners and native speakers shows that existentials received highest ratings by both groups where they are the most natural option, while canonical sentences received significantly higher ratings by the learners. With regard to the production data, learners tended to avoid existentials, but rather relied on canonical sentences. Existentials were rarely used by lower proficiency learners and not used productively even by more proficient learners in the situations where existentials would have been the most natural option. These results suggest that Korean learners' difficulty with the use of existentials is not merely a product of performance limitations, but attributable to limited knowledge about existentials and their syntactic alternatives in terms of contextual appropriateness. Lower proficiency learners lack such knowledge, and more proficient learners, while showing better awareness of the use of existentials, have problems as to the placement of new information when engaging in writing tasks that place lower level of demands on attention to the information status of noun phrases compared to communicative, oral tasks.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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• pp.193-195
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• 2003

The analysis of EEG data is an important task in the domain of Brain Computer Interface (BCI). In general, this task is extremely difficult because EEG data is very noisy and contains many artifacts and consists of mixtures of several brain waves. The P300 component of the evoked potential is a relatively evident signal which has a large positive wave that occurs around 300 msec after a task-relevant stimulus. Thus automatic detection of P300 is useful in BCI. To this end, in this paper we employ a method of reference-based independent component analysis (ICA) which overcomes the ordering ambiguity in the conventional ICA. We show here. that ICA incorporating with prior knowledge is useful in the task of automatic P300 detection.

• 한국어교육
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• 제25권1호
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• pp.29-52
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• 2014

The purpose of this paper is to suggest a discourse analysis activity that can be used in the stage after performing tasks in task-based Korean speaking class and show its pedagogical advantages. A discourse analysis activity is an metadiscourse activity in which learners speak what they have spoken. By analyzing discourse and performing tasks again, learners can enhance their fluency and accuracy, make their knowledges in target language more stable and extend them, and develop problem solving skills. Consequently, this facilitates learners' acquisition of Korean language. This paper reviewed theoretical background of proposing discourse analysis activity, suggested the pedagogical advantages of the analysis, and examined discourse analysis activity in Korean speaking class. And it included the discourse sample of learners in actual class.

• 농촌지도와개발
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• 제26권2호
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• pp.57-68
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• 2019

This paper was done as an exploratory study aiming to identify the relationship between small group characteristic factors and perceived performance in the Village Development Committee (VDC) in Saemaul Undong project in Laos. The data were gathered from 166 members in 17 VDCs in Vientian province, however 135 questionnaires were used in analysis. Structure Equation Model was applied in the analysis with Amos 21. The major finding of this study were as follows; firstly decision making was more influenced by task cohesion than social cohesion, secondly organizational citizen behavior was influenced by both task cohesion and social cohesion. However, social cohesion had more influence than task cohesion, thirdly the VDC members learned their technical knowledge from decision-making process, and influenced to their perceived performance level and to VDC sustainablity, and fourthly in overall, committee members implemented their jobs based on task-oriented.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.