• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.321-324
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• 2005

기존의 LMS(Learning Management System)는 웹 기반의 e-Learning 교육의 장점에도 불구하고 학습자의 요구와 수준에 무관하게 학습과 관련한 컨텐츠들이 획일적으로 구성됨으로써, 학습자의 요구를 만족시키지 못하고 있다. 본 논문에서는 LCMS(Learning Content Management System) 와 LMS를 연계한 학습 통계 모듈을 제시하고, LMS에 학습자와 운영자에게 학습정보 데이터를 제공함으로써 학습하는 과정을 추적하고 학습이력을 관리 할 수 있는 학습통계모듈을 설계하고 구현한다. 제시된 모듈에서는 효과적인 학습통계을 위한 검색 방안으로 LCMS의 메타데이터와 다양한 학습관리 정보(CMI)값을 LMS를 호출하는 기능인 API(Application Program Interface) 어댑터를 이용하여 연계된 값과 LMS시스템에 학습지원과 운영지원 기능을 추가하여 나온 결과값을 바탕으로 하였다. 이 학습통계모듈을 통해서 LMS운영자는 학습자의 컨텐츠의 활용을 더욱 확장할 수가 있으며 학습자의 학습정보관리를 하는 LMS의 성능을 향상 시키고자 하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.197-198
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• 2017

최근 IT기술의 발전, 대학 교육의 글로벌화 등의 추세는 대학의 이러닝(e-learning) 형태의 교육을 촉진하고 있다. 국내향후 연구에서는 17개의 사이버대학은 이러닝 형태의 교육을 제공하고 있는데, 최근 재학생 수가 크게 증가하고 있다. 이에 사이버대학들은 우수한 강의 제공을 위해 학생-교수간의 다양한 상호작용에 대해서 연구하고 있다. 본 연구는 사이버대학의 LMS(Learning Management System)에 온라인 채팅 서비스를 최초로 도입하여, 시스템을 구축하였다. 본 연구에서는 온라인 채팅과 학습만족과의 관계에 대해서 검증하고, 강의질 개선을 위한 전략을 도출하고자 한다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.19-28
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• 2020

Vehicle license plate recognition system is not generalized in Malaysia due to the loose character layout rule and the varying number of characters as well as the mixed capital English characters and italic English words. Because the italic English word is hard to segmentation, a separate method is required to recognize in Malaysian license plate. In this paper, we propose a mixed character level and word level English license plate recognition algorithm using deep learning neural networks. The difference of Gaussian method is used to segment character and word by generating a black and white image with emphasized character strokes and separated touching characters. The proposed deep learning neural networks are implemented on the LPR system at the gate of a building in Kuala-Lumpur for the collection of database and the evaluation of algorithm performance. The evaluation results show that the proposed Malaysian English LPR can be used in commercial market with 98.01% accuracy.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.3
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• pp.93-114
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• 2002

This paper suggests a dynamic balanced scorecard (DBSC) model employing the concept of system dynamics (SD), which could overcome the limitations inherent in the conventional balanced scorecard (BSC) and facilitate strategic learning process in organizations. The BSC has been a successful framework for measuring an organization＇s performance in various Perspectives through translating an organization＇s vision and strategy into an interrelated set of key performance indicators and specific actions. The BSC, while having significant strengths over traditional performance measurement methods, however, has its own limitations, due to its static nature, such as overlooking two-way causation between performance Indicators and neglecting the impact of delayed feedback flowing from the adoption of new strategies or policy changes. To overcome these limitations, we employs SD, a methodology for understanding complex systems where dynamic feedback among the interrelated system components significantly impact on the system outcomes. The SD simulation model in the form of DBSC we suggest in this paper would serve as a useful strategic learning tool for facilitating an organization＇s communication process through various scenario analyses as well as predicting the dynamic behavior pattern of their key performance measures over a future time frame. For the demonstration purpose, we apply the DBSC model to Korea Coal Corporation (KoCoal ) BSC case.

• Journal of information and communication convergence engineering
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• v.2 no.2
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• pp.80-83
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• 2004

The core purpose of the system proposed in this paper is to help learners pursue proactive and self-oriented education by allowing learners to proactively configure their own content, that is, learners no longer have to be restricted by prescribed sequence of lectures. Although a variety of standardization and Learning Management System (LMS) were produced to develop and effectively manage web contents in response to active diffusion of internet application, practical changes to assist online learners are not yet to be found. In this paper, I would like to introduce a LMS that can support self-leading education by providing various types of learners at Virtual University with delicately organized educational contents for maximum efficiency. The system allows a learner to select a lecture or a chapter which has been presorted to meet his educational needs and intellectual ability. In general, most LMSs cannot meet every individual's educational needs because they structure their programs by letting learners simply choose from a list of available lectures at prescribed level or difficulty. However the Self-Leading LMS eliminates such boundaries by allowing learners to choose contents and difficulty within the limit set by their own educational competence.

• Knowledge Management Research
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• v.13 no.2
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• pp.73-93
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• 2012

Although a wide range of theoretical researches have emphasized on the importance of knowledge management in cooperative R&D network, the empirical researches to synthetically examine the role of organizational learning and open innovation which influence on the performance of technological innovation are not enough to meet academic and practical demands. This study is to investigate the effect of open innovation and organizational learning in venture business on technological competitive advantage and establish the mediating role of organizational learning. For the purpose, the questionnaires, made based on the reviewing previous researches, were collected from 274 Korean venture businesses whose managerial focus is on developing technological innovation. As a result of analysis, the relational dimensions of open innovation - network, intensity and trust shared by a firm with external R&D partners - as well as the internal organizational learning system and competence have positive influence on building technological competitive advantage whose sub-variables are technological excellence, market growth potential and business feasibility. In addition, it is identified that organizational learning has the mediating and moderating effect in the relationship between open innovation and technological competitive advantage. These results imply that open innovation complements and expend the range of limited resources and the scope of innovation in technology-intensive small and medium-sized enterprises. Besides, organizational learning activity reinforces the use of knowledge and resources, obtained from external R&D partners. On the basis of these results, detailed issues and discussion were made in the conclusion.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Asia pacific journal of information systems
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• v.12 no.3
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• pp.45-70
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• 2002

This paper examines the role of distance learning self-efficacy, belief in one's capabilities of using a system in the accomplishment of web-based distance learning, in predicting user intention to use and performance of distance learning system. It used self-efficacy theory and technology acceptance model(TAM) to build a model that predicts relationships between antecedents to students' distance learning self-efficacy assessments and their behavioral and attitudinal consequences. The model was tested using LISREL analysis on the sample of 250 students who have worked with the Distance Learning System. The results indicated partial support for the conceptual model. In accordance with TAM, perceived usefulness had strong direct effects on intention to use and performance, while perceived ease of use had both direct and indirect effects on intention to use, but not performance. Distance learning self-efficacy had only direct effect on perceived ease of use to use. Computer experience was found to have a strong positive effect on distance learning self-efficacy, and computer anxiety had a negative effect on distance learning self-efficacy. Implications of these findings are discussed for researchers and practitioners.

• Journal of the Korea Safety Management & Science
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• v.24 no.3
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• pp.61-74
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• 2022

In a rapidly changing environment, it is essential for companies to develop their capabilities for sustainable growth. To this end, informal learning at work plays an important role for small and medium-sized enterprises that are having difficulties in human resource development. If the GRIT of workers and the spiritual leadership of leaders are maintained at an appropriate level, the effect of informal learning will increase. This study derived the following results through a survey of workers participating in the Work-learning Dual System in Korea. First, experience and feedback among informal learning activities have a significant positive effect on competency development. Second, the higher the level of the GRIT of workers, the greater the magnitude of the positive effect of experience and feedback on competency development, showing a positive moderating effect. Third, in the case of workers with high GRIT, capacity development is strengthened as experience or feedback increases, and the higher the level of spiritual leadership, the greater the scope of reinforcement. On the other hand, it can be seen that in the case of workers with low GRIT, competency development weakens as experience or feedback increases, and the higher the level of spiritual leadership, the greater the extent of the weakening.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.476-483
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• 2022

The novel coronavirus pandemic has had a significant impact on society and everyday life. The pandemic imposed a global shutdown leading to many challenges such as the suspension of academic programs at universities. The result of this suspension contributed to the rapid overnight migration of educational activities from traditional face-to-face learning to a virtual environment which until then was unfamiliar to both instructors and students. This study identified the experiences faced by built environment higher education instructors in KwaZulu-Natal, South Africa during this sudden switch to online teaching and learning. This pilot study employed a quantitative research approach to survey instructor experiences on online teaching and learning during a global pandemic. The data was computed and analyzed using IBM Statistical Package for Social Sciences (SPSS) version 27. Descriptive statistics were used to analyze the data collected. The study sample comprised of 20 higher education instructors in the region of the KwaZulu Natal province in South Africa. Findings from the study revealed that instructors faced adaptive challenges with rapidly having to redesign and remodel the mode of academic course delivery and assessments to suit an online platform. Additionally, instructors observed that students faced technological challenges such as connectivity and navigating the online learning management system platforms. The challenges identified by instructors and students can be effectively transformed to opportunities for future learning under the 'new normal'.