• Journal of Korean Library and Information Science Society
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• v.40 no.4
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• pp.243-259
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• 2009

This study introduces strengths theory, a core subject of career development and job-getting, and discusses about the factors of strengths(namely talents, knowledge and skills), the processes of strengths personalization, and generating employability. It searches for opportunities to apply the concept of employability to the field of Library and Information Science now thrown under hard pressure from information and communication technology. Employability is defined here as competence to make oneself employable as needed by discovering or creating work opportunities using one's own tested personalized strengths. Employability is a package of systematically organized information about the essential abilities and productive personalities of a person, and it is essential to be duly cognitive of one's employability if one seriously intends to succeed in jobs and career. Since generation of employability heavily involves complex processes of information and knowledge-making, expertise from LIS, particularly from areas of personal information management(PIM) and personal knowledge management(PKM), is expected to help for process facilitation.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.167-171
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• 2007

Application areas of Knowledge Discovery in Database (KDD) have been expanded into many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has recently fully utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not cheap, korean language process not available, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information (KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. Knowledge Matrix main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Journal of Korean Academy of Nursing
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• v.37 no.4
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• pp.540-548
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• 2007

Purpose: The purpose of this study was to develop online aging and health management education for undergraduate students and to evaluate its effects analyzing the differences in knowledge and attitude toward aging and the elderly. Method: An Online aging and health management education program was established through analysis, planning, content framing and production, program application, and evaluation stages. The study sample consisted of 98 undergraduate students in one university in D city. The instruments used were FAQ I for knowledge of aging and a 20 item semantic differential scale for attitude toward aging and the elderly Results: The results of this study were as follows. First, undergraduate students' knowledge level was low and attitudes were negative at the baseline. Second, after the class, knowledge scores improved significantly from 14.44 to 20.12. In addition, the attitudes toward elderly and aging changed from negative to a more positive way showing a 23.57 point difference. Conclusion: This study shows that the online aging and health management education program was an effective educational method to improve knowledge and attitude of aging for the young generation such as college students.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.454-457
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• 2005

Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns. And calendar based on temporal association rules proposes the discovery of association rules along with their temporal patterns in terms of calendar schemas, but this approach is also adopt an Apriori-like candidate set generation. In this paper, we propose an efficient temporal frequent pattern mining using TFP-tree (Temporal Frequent Pattern tree). This approach has three advantages: (1) this method separates many partitions by according to maximum size domain and only scans the transaction once for reducing the I/O cost. (2) This method maintains all of transactions using FP-trees. (3) We only have the FP-trees of I-star pattern and other star pattern nodes only link them step by step for efficient mining and the saving memory. Our performance study shows that the TFP-tree is efficient and scalable for mining, and is about an order of magnitude faster than the Apriori algorithm and also faster than calendar based on temporal frequent pattern mining methods.

• Corrosion Science and Technology
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• v.15 no.3
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• pp.113-119
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• 2016

Corrosion science faces new challenges in various nuclear environments. Three main areas may be identified where increases of knowledge and understanding have been done and are still needed to face the technical needs: (i) the extension of the service time of nuclear power plants from 40 years, as initially planned, to 60 years and probably more as expected now, (ii) the prediction of long term behaviour of metallic materials in nuclear waste disposal where the corrosion processes have to be predicted over large periods of time, some thousands years and more, (iii) the choice of materials for use at very high temperatures as expected in Generation IV power plants in environments like gas (helium), supercritical water, liquid metals or salts. Service time extension, deep geological waste repositories and high temperature reactors sustain researches and developments to model corrosion phenomena at various scales, from atoms to components.

• The Korean Journal of Zoology
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• v.26 no.4
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• pp.295-296
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• 1983

Further research needs in environmental carcinogenesis are much to be desired. Currently, the methodology for identification, quantitation, and assay of some environmental carcinogens is available, but there remains a pressing need for additional fundamental knowledge of the carcinogenic process at the molecular level. The best hope for the control of cancer lies in prevention and chemotherapy, and this in turn depends upon the generation of basic information not yet available. The history of medical science reveals that quantum advances in control and prevention of disease have been direct consequences of research applications derived from pools of existing knowledge. It is hoped that the major efforts on specific problems of eivironmental carcinogenesis and substantial support of research to obtain new knowledge will prove to be equally rewarding.

• Journal of The Korean Association For Science Education
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• v.34 no.3
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• pp.207-212
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• 2014

The national reform document, Science for All Americans (AAAS, 1990), and the Next Generation Science Standards (NRC, 2012) emphasize the importance of the nature of science in guiding science educators in accurately portraying science to students. Therefore, it is important that textbook materials convey an accurate conception of the nature of science. This study employs content analysis to examine the content of textbooks in US and Korea elementary science textbooks with regard to the four aspects of the nature of science: (a) nature of scientific knowledge; (b) nature of scientific inquiry; (c) nature of scientific thinking; and (d) nature of interactions among science, technology, and society (Chiappetta, Fillman, & Sethna, 2004). Intercoder reliability was determined by calculating Cohen's kappa (Cohen, 1960). Findings show that while US elementary science textbooks are not balanced in presenting the four aspects of the nature of science regardless of the publishing companies, the presentation of the nature of science in Korean elementary science textbooks have better balanced treatment of the four themes across the grade levels. On the other hand, both US and Korean elementary science textbooks are attempting to convey an idea of what science is by emphasizing scientific knowledge and investigation.

• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.61-74
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• 2010

The knowledge sharing in a knowledge management process is much affecting generation and distribution of knowledge. Especially, the knowledge distribution is being revitalized with the center of social media service like twitter and library service 2.0 in the knowledge-based IT (Information Technology) environment. The present research analyzed the structure and characteristics of a social network inside an organization that is growing like an organism through self-organization through tools for SNA (Social Network Analysis) and multiple regression analysis of independent variables such as 1) a relationship between social network's structure and knowledge sharing, 2) a relationship between structural holes and knowledge sharing influence of centrality, 3) a relationship between individual ability and knowledge sharing of information technology and work recognition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.214-221
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• 2015

A new classification system with 9 main categories and 56 subcategories for the Open Korean Knowledge Dictionary is proposed. The classification system setup is to prepare for the standard classification system to be used to manage effectively vast of terminologies which were published in the Open Korean Knowledge Dictionary and is meant to enhance the fifteen-year old classification system for the standard korean great dictionary to match up to the trend of the modern terminology. The new terminology classification system covering all the academic areas such as humanity, sociology, politics, science, medicine, agriculture, engineering, etc, is designed and proposed after investigating several classification systems. The classification system setup procedures follow as ${\circ}$ The classification system is designed and planed by both the classification system and the academic expert. ${\circ}$ Classification system design covers all the academic areas following National Science and Technology standard classification system after investigating several classification systems such as the National Research Foundation, National Science and Technology Standard Act, Ministry of Knowledge Economy. ${\circ}$ Poll and survey is made to collect comments from total 93 members of several academic areas. ${\circ}$ The poll result is reviewed among working group members and utilized to update the new terminology classification system. Reclassifications are made for the around 200,000 terms in electricity, computer, medicine, pharmacy, biology, and economics according to the new terminology classification system.