• Title/Summary/Keyword: Learning resources

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Deep Learning Based Security Model for Cloud based Task Scheduling

  • Devi, Karuppiah;Paulraj, D.;Muthusenthil, Balasubramanian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.9
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    • pp.3663-3679
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    • 2020
  • Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

Educational-Resources Recommending System for Web Based Learning

  • Ochi, Youji;Yano, Yoneo;Wakita, Riko
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.310-315
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    • 2001
  • We are focusing on an approach which handle a general Web as a resource in order to support self-directed learning for a student. Then, we are developing a Web based learning environment "Web-Retracer"for utilizing Web as teaching materials by a user′s Annotation. Although the learner can share the Web resource that the others utilized in this environment, Web resources unsuitable for a student′s needs becomes hindrance about her/his self-directed learning. In this paper, we propose a recommending method of the resource united with a student′s needs on the basis of a student′s learning and Web browsing history. This method analyzed the feature peculiar to a resource, and extracts the resource with which the needs of the feature and a student agreed.

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A Design of Human Cloud Platform Framework for Human Resources Distribution of e-Learning Instructional Designer (이러닝 교수 설계자 인적 자원 유통을 위한 휴먼 클라우드 플랫폼 프레임워크 설계)

  • Kim, Yong
    • Journal of Distribution Science
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    • v.16 no.7
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    • pp.67-75
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    • 2018
  • Purpose - In the 21st century, as information technology advances alongside the emergence of the 4th generation, industrial age, industrial environment has become individualized and customized. It is important to hire good quality employees for good service in the industry. The e-learning market is growing every year. Although e-learning companies are finding better quality employees in e-learning, it is not easy to find it. Companies also spend a lot of time and cost to find employee. On the employees side, they want to get a job freely when they want, but they cannot find their job easily. Furthermore, the labor market environment is changing fast. In the 4th generation, industrial age, employers require to find manpower whenever they need and want at little cost. So of their own accord, we have considered the necessity of management of human resources for employees and employers in e-learning. The purpose of this study is to propose a human cloud platform framework for enabling an efficient management of human resources in e-learning industry. Research design, data, and methodology - To pinpoint the items of a human cloud platform framework, the study was initiated according to the following process. First, items of competency relating to e-learning instructional designer was analyzed. Second, based on the items of information from this analysis, selection and validity verification took place with 5 e-learning specialists group. Third, the opinion of experts who were in charge of hiring in e-learning companies were collated with the questionnaire. Lastly, the human cloud platform framework was proposed based on opinion results. Results - The framework was comprised of 7 domains and 27 items in order to develop the human cloud platform for e-learning instructional designer. The analysis results showed that the most highly considered item were 'skill (4.60)' that employee already have the capability. Following this (in order) were 'project type (4.56)', 'work competency (4.56)', and 'strength area of instructional design (4.52)'. Conclusions - The 27 items in the human cloud platform framework were suggested in this study. Following this, we can consider to develop the human cloud platform for finding a job and hiring e-learning instructional designer easily. For successful platform operation, we need to consider reliability between employer and employee. In addition, we need quality assurance system based on operation has public confidence.

Guide to Learning Systems Biology for Korean Medicine Researchers (한의학 연구자를 위한 시스템 생물학 학습 가이드)

  • Kim, Chang-Eop
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.30 no.6
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    • pp.412-418
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    • 2016
  • The emergence of systems biology in the 21st century is changing the paradigm of biomedical research. Whereas the reductionist approaches focus on components rather than time or contexts, systems biology focus more on interrelationships, dynamics, and contexts. The key ideas of the systems biology shares much with the philosophy of Korean Medicine(KM) and therefore, the paradigm shift is shedding light on understanding the mechanism of action of KM at system level. In this article, I provide a guide to learning systems biology for KM researchers using online learning resources. Thanks to the recent development of MOOC(massive open online courses) and other online learning platforms, learners can access to plenty of high-quality resources from top-tier universities in the world. I expect this guide help researchers to employ systems biology methods into their KM researches, and will lead to the development of future curricula for training "bi-lingual" experts, KM and computational approaches.

The Effect of Open Innovation and Organizational Learning on Technological Competitive Advantage in Venture Business (개방형 혁신과 조직학습 특성이 벤처기업의 기술경쟁우위에 미치는 영향)

  • Seo, Ribin;Yoon, Heon Deok
    • 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.

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Fault Detection for Seismic Data Interpretation Based on Machine Learning: Research Trends and Technological Introduction (기계 학습 기반 탄성파 자료 단층 해석: 연구동향 및 기술소개)

  • Choi, Woochang;Lee, Ganghoon;Cho, Sangin;Choi, Byunghoon;Pyun, Sukjoon
    • Geophysics and Geophysical Exploration
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    • v.23 no.2
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    • pp.97-114
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    • 2020
  • Recently, many studies have been actively conducted on the application of machine learning in all branches of science and engineering. Studies applying machine learning are also rapidly increasing in all sectors of seismic exploration, including interpretation, processing, and acquisition. Among them, fault detection is a critical technology in seismic interpretation and also the most suitable area for applying machine learning. In this study, we introduced various machine learning techniques, described techniques suitable for fault detection, and discussed the reasons for their suitability. We collected papers published in renowned international journals and abstracts presented at international conferences, summarized the current status of the research by year and field, and intensively analyzed studies on fault detection using machine learning. Based on the type of input data and machine learning model, fault detection techniques were divided into seismic attribute-, image-, and raw data-based technologies; their pros and cons were also discussed.

English Learning Application by Animation and Multimedia Software (애니메이션과 멀티미디어 소프트웨어의 영어 학습 연구)

  • Lee, Il Seok
    • Journal of Digital Contents Society
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    • v.16 no.5
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    • pp.707-715
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    • 2015
  • With the development of computer technology, the multimedia mediums that allow for animated videos, conversational illustrations are increasingly receiving attention for materials for educational purposes. Accordingly, there is a need to research whether multimedia resources and material is more effective compared to traditional educational material and resources. This study aims to compare traditional English reading and writing learning methods with learning methods using educational multimedia mediums such as illustrations or animation. Students were divided into a experimental group and a control group, and during 6 months the groups were exposed to different educational resources and on the basis of student evaluation feedback and grades, a new approach to English education is offered.

The Successful Factors of e-Learning for Human Resources Development (효과적 인적자원 개발을 위한 e-Learning의 성공요인)

  • Lee, Sung
    • Journal of Agricultural Extension & Community Development
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    • v.8 no.1
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    • pp.1-14
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    • 2001
  • e-Learning has brought dramatic changes in education system for many companies in Korea. Many researchers and practitioners believe that e-Learning will be the main educational system for every companies in the world. e-Learning is an alternative education system, which includes computer based learning, web based learning, virtual classroom, and distance learning. e-learning has been expected to impact every educational sectors including Extension services. This study intends to identify and suggest some implications for successful e-Learning implementation of Extension education by investigating the successful factors of enterprises' e-Learning system, where outstanding results have be shown.

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The Case Study on Informal Learning in the Workplace for Social Workers -Based on Social Welfare Centers in Jeju- (사회복지사의 일터에서 나타난 무형식학습 사례연구 -제주지역 종합사회복지관을 중심으로-)

  • Kim, Junghee;Ko, Suhee
    • Korean Journal of Social Welfare
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    • v.66 no.1
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    • pp.87-111
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    • 2014
  • The purpose of this study is to analyze informal learning cases including learning work and being skillful of social workers in the workplace. In addition, it is to examine the promotion plan of informal learning to reinforce competences of social workers in the development of human resources and managemental way. This is a qualitative case study that was involved 20 social workers working in social welfare centers in Jeju. Face to face in-depth interviews were used for collected data. Nvivo10, qualitative data analysis program, was used for analyzing data. According to the findings, the most normal informal learning method in their workplace was to get feedback from the boss including adapting the system of a workplace senior, participating in the meetings, reviewing various media and etc. In addition, feedback from the boss and contacting with acquaintances were used the most as the informal learning method in the learning work and being skillful process of social workers and focused on communication with human resources. Therefore, social welfare centers need to create working environments to promote informal activities such as supporting individual learning, informal meetings, mentoring, supervision, interacting with colleagues and etc as well as supporting institutional formal learning including refresher training to reinforce the capabilities for social workers.

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