• Knowledge Management Research
• /
• v.15 no.1
• /
• pp.1-19
• /
• 2014

Absorptive capacity is an ability to acquire, assimilate, transform, and apply external knowledge. Since the objectives of communities of practice(CoPs) are to share task-related knowledge and to apply it to operations, individual absorptive capacities of CoP members are one of the most important success factors of CoPs. The study examined the structural relationship among three groups; antecedents of absorptive capacity, absorptive capacity, and the performance of CoPs. The findings are as follows; Goal interdependence, reciprocal altruism, coordination mechanism and socialization mechanism had significant and positive effects on absorptive capacity. In addition absorptive capacity had significant and positive effects on goal attainment and knowledge application of CoP.

• Journal of Intelligence and Information Systems
• /
• v.1 no.1
• /
• pp.61-72
• /
• 1995

Dynamic and explicit ordering of strategies is a key process in modeling knowledge-level problem-solving behavior. This paper addressed the important problem of howl to make the scheduler more knowledge-intensive in a way that facilitates the acquisition, integration, and maintenance of the scheduler control knowledge. The solution a, pp.oach described in this paper involved formulating the scheduler task as a heuristic classification problem, and then implementing it as a classification expert system. By doing this, the wide spectrum of known methods of acquiring, refining, and maintaining the knowledge of a classification expert system are a, pp.icable to the scheduler control knowledge. One important innovation of this research is that of recursive heuristic classification : this paper demonstrates that it is possible to formulate and solve a key subcomponent of heuristic classification as heuristic classification problem. Another key innovation is the creation of a method of dynamic heuristic classification : the classification alternatives that are selected among are dynamically generated in real-time and then evidence is gathered for and aginst these alternatives. In contrast, the normal model of heuristic classification is that of structured selection between a set of preenumerated fixed alternatives.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.06a
• /
• pp.215-222
• /
• 2001

The task for chromosome analysis and diagnosis by experienced cytogenetists are being concerned as repetitive, time consuming job and expensive. FOr that reason, chromosome analysis system based on knowledge base for CAI had been established to be able to analyze chromosomes and obtain necessary advises from the knowledge base instead of human experts. That s to say, knowledge base by IF THEN production rule was implemented to a knowledge domain with normal and abnormal chromosomes, and then the inference results by knowledge base could enter the inference data into the database. Experimental data were composed of normal chromosome of 2,736 patients'cases and abnormal chromosomes of 259 patients'cases that have been obtained from GTG-banding metaphase peripheral blood and amniotic fluid samples. The complete system provides variously morphological information by analysis of normal or abnormal chromosomes and it also has the advantage of being able to consult with user on chromosome analysis and diagnosis.

• IE interfaces
• /
• v.11 no.3
• /
• pp.227-240
• /
• 1998

This article presents a model for Intelligent Groupware Systems(IGS). The model is concerned not just with a future framework, but attempts to integrate many technologies into the framework. In order to do so, first of all it identifies essential technologies to improve the performance of the components in the model in terms of task-independent technologies(TIT) and task-dependent technologies(TDT). The former mainly consists of current technologies, which is under progress, being able to affect the groupware performance greatly. On the other hand, the latter is closely related to the knowledge depending on application systems. Fianlly, it presents these potential technologies which will be required for the IGS.

• Journal of Environmental Impact Assessment
• /
• v.17 no.1
• /
• pp.81-95
• /
• 2008

The study is intended to develop the measures to introduce the Environmental Impact Assessment (EIA) project manager (Environmental Assessor), who will be responsible for leading the EIA task. This role requires a quality standard of expertise in the area of natural science, social science, knowledge and technology on environment design mechanism, and the integrated approaches that combine the relevant policies and systems. To facilitate the system, the certificate will be given to the person who is well acquainted with the knowledge on EIA with relevant experiences, thereby authorizing them to coordinate the assessment task for reliable outcome. Hence, the need for introducing the system is very crucial. The EIA project manager, as a guide for an EIA project team, shall be the person who has a comprehensive understanding of the project, the knowledge about the principal for implementation of EIA and the expertise in structuring the management system, with a skill to maintain the good relationship with the people engaged in the project. To that end, it is highly recommended to set up such a certificate system to be incorporated in the college curriculum.

• Annual Conference on Human and Language Technology
• /
• 2018.10a
• /
• pp.652-657
• /
• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• International Journal of Contents
• /
• v.15 no.2
• /
• pp.20-28
• /
• 2019

This study was conducted with a non-equivalent control group experimental design to investigate the effects of a video-based infection control program through the application of the social cognitive theory on caregivers. Forty-six caregivers were recruited, with 23 pairs being randomly assigned to the control and experimental groups each. While the experimental group took part in the video-based education, the control group was involved in typical lectures. For two weeks, both groups were educated on the principles of infection control, medical and external handwashing, standard precautions, and quarantine. Their knowledge, performance, and self-efficacy were evaluated before and after the program. There was a significant increase in knowledge (p<.001 and p=.005) and infection control performance (p<.001) in the experimental and control groups. Similarly, self-efficacy, self-regulatory efficacy, task-difficulty preference and confidence significantly increased in the experimental group (p<.001). In the control group, only task-difficulty preference significantly increased (p=.005). Consequently, the online video-based infection control education program applying the social cognitive theory proved effective in improving the caregivers' knowledge and performance in infection control, and their self-efficacy. We suggest the use of this program in effective infection control education for caregivers in the future.

• Journal of Multimedia Information System
• /
• v.6 no.2
• /
• pp.49-60
• /
• 2019

Plants are very crucial for life on Earth. There is a wide variety of plant species available, and the number is increasing every year. Species knowledge is a necessity of various groups of society like foresters, farmers, environmentalists, educators for different work areas. This makes species identification an interdisciplinary interest. This, however, requires expert knowledge and becomes a tedious and challenging task for the non-experts who have very little or no knowledge of the typical botanical terms. However, the advancements in the fields of machine learning and computer vision can help make this task comparatively easier. There is still not a system so developed that can identify all the plant species, but some efforts have been made. In this study, we also have made such an attempt. Plant identification usually involves four steps, i.e. image acquisition, pre-processing, feature extraction, and classification. In this study, images from Swedish leaf dataset have been used, which contains 1,125 images of 15 different species. This is followed by pre-processing using Gaussian filtering mechanism and then texture and color features have been extracted. Finally, classification has been done using Multiclass-support vector machine, which achieved accuracy of nearly 93.26%, which we aim to enhance further.

• International Journal of Advanced Culture Technology
• /
• v.9 no.4
• /
• pp.169-179
• /
• 2021

This study was conducted to develop and apply clinical nursing practice training simulation program using Standardized Patient for Nursing Students focused on infectious respiratory disease. This study is descriptive methodological study. Through prior consideration of documents and educational task of infectious respiratory disease was conducted with interview of clinical specialists of infection control managers. Development of educational task for infectious respiratory disease for Nursing Students went through the content validity. Finally, 10 educational tasks are developed 'knowledge of respiratory infections disease', 'hand washing', 'put on mask', 'lead to put on mask to patients and caregiver', 'intravenous injection via 3way', 'surgical aseptic technique', 'sterilization medical instrument', 'management of contaminated linen', 'infected personnel management manual'. The infectious respiratory disease simulation program was developed based on the ADDIE model and proceeded to 4 steps of analysis, design, development, implementation. The infection control education program included lectures (20 min), skill training (20 min), simulation using standardized patient (20 min), and debriefing (40 min), The collected data were analyzed by descriptive statistics with SPSS program for version 23.0. The results of this study confirmed that the clinical nursing practice training simulation program using standardized patients was effective in infectious respiratory disease of the nursing college students in knowledge of infectious respiratory disease and clinical nursing performance. we found this practical training program for nursing college students to improve knowledge and clinical competency of infection control. we expected that this developed program could be applied to practical training for various infectious control.

• Asia pacific journal of information systems
• /
• v.10 no.4
• /
• pp.57-75
• /
• 2000

Most current literature on knowledge and technology transfer(Appropriability Model, Dissemination Model, and Knowledge Utilization Model), describe the process of transfer in details, but has limitation in terms of their application in contemporary high-tech industries since most studies have not provided plausible explanation on levels and factors affecting transfer of knowledge and/or technology. To overcome these limitations, the four levels of knowledge and technology transfer are suggested: Knowledge and Technology Creation(Level I), Sharing(Level II), Implementation(Level III), and Commercialization(Level IV). Comprehensive literature identifies sixteen variables affecting the process and results of knowledge and technology transfer. The survey results show four key factors in knowledge and technology transfer: Communication, Distance, Equivocality, and Motivation, Communication refers to the degree to which a medium is able to efficiently and accurately conveys task-relevant information and media while distance involves both physical and cultural proximity. Equivocality refers to the degree of concreteness of knowledge and technology to be transferred while motivation involves incentives for and the recognition of the importance of knowledge and technology transfer activities. Further analysis shows that there are four distinctive clusters and they show very contrasting characteristics in terms of four key factors. The careful mapping of the four clusters on the four key factors show very informative knowledge and technology transfer patterns, the Knowledge and Technology Transfer Grid. Finally, actions to increase communication interactivity and motivation, and to reduce cultural distance and equivocality are suggested.