• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2000.11a
• /
• pp.313-329
• /
• 2000

Background of Theme Selection ; Safety is the most important value, 공장 KPI의 20%, 협력업체 직원 1,200명/Day 출입, 최근 5년간 년 평균 11건의 사고, 안전교육에 대한 현상파악(협력업체에 대한 적절한 안전교육 부재, 안전교육에 대한 전반적인 개선 요구). 고객의 요구사항 수렴; Digital 시대에 부응하는 해결방안= The Web-based Safety Training System.(중략)

• Hwankyungkyoyuk
• /
• v.23 no.3
• /
• pp.1-16
• /
• 2010

Global climate change becomes one of the most serious environmental problems over the world. There is growing recognition thai climate change education, especially for children is important. However, there have been few programmes, curricula, teachers' training chances, and teaching-learning materials for climate change education so far. Therefore, we analyse the world wide web(web) contents in Korea which are available for climate change education, providing fundamental data in developing educational contents for climate change, as well as helping users to search appropriate contents for climate change education. Subjects for this study are 10 web sites of public institutions related to climate change in Korea. The web contents are evaluated in terms of diversity, accuracy, authenticity and the ease of use. The key finding in this study is that the majority of the contents are focused on how to respond to the problem, especially mitigation and also we find that most of the web sites provide text-types of lesson plan and video-types. Consequently, it would be necessary to develop various web contents for climate change education in both quality and quantity aspects.

• The Journal of the Korea Contents Association
• /
• v.9 no.2
• /
• pp.203-215
• /
• 2009

Many companies in Korea have developed job competency models and are utilizing them for the purpose of training and management of employees. However many of them are unable to be utilized efficiently through their own job competency model because the company failed to reflect what happens in the real work place in the model or the model itself is not concrete enough to be applied practically. Thus, in this study, the current status of Korean companies which had developed their own job competency model were investigated and the subsequent development of training system which is based on the model were developed. By result of the survey, about 43.5% of the company, which has more than 400 employees, have developed job competency models and 31.7% of them haven‘t been able to develop training system based upon the model due to the lack of concreteness of their model. To overcome this contradiction, we developed web 2.0 based job competency modeling method where each individuals in the organization themselves develop job competency as opposed to an expert oriented developing method. The result of this study is that web 2.0 based job competency modeling method is superior to any another modeling in an accuracy of competency, an acceptance of competency, and an usefulness of competency description.

• Journal of Korea Multimedia Society
• /
• v.5 no.5
• /
• pp.538-551
• /
• 2002

Even though the distance education via Web has a great advantage to overcome time and space, its problem that the management of trainees is not efficient compared with classroom and group education. This problem is a great obstacle to the objects and achievement standards of distance education, giving controversial arguments to the advocators of distance education. Distance educators need to monitor the trainees 'participation and responses continuously and offer appropriate feedback to the trainees. However, the existing distance education system only focuses on teaching and teaming activities, and as a result, the efficient management function of distance education is not available. Accordingly, the study attempts to find out the appropriate managing elements of distance teacher training in order to effectively achieve the goals of teacher training and the efficient management of distance education. Also, it proposes distance teacher training system that offers appropriate feedback to trainees, applying the derived elements of distance teacher training to the training processes. To verify the efficiency of the system, hypotheses on related items of distance teacher education and learning types are suggested, and the achievement of learning and its relations are investigated through questionnaire of learning types.

• The Journal of Korean Institute for Practical Engineering Education
• /
• v.3 no.2
• /
• pp.158-165
• /
• 2011

The purpose of this study is to develop competency model in preparation for training programs for CEO of vocational training institutes in terms of needs assessment. This study collected data from 230 public and designated vocational training institutes including commercial learning facilities and life-long training centers using questionnaire by web mail. The frame of assessing training needs of competency applied to this study was based on the model with three components, namely importance, proficiency and learning desires of job skill and task needed to CEO of vocational training institutes. The methodologies of this study used were survey, FGI and case study. The major results proved that the higher priorities of training needs for vocational training institute CEO competency were as followings: (1) Competency for attaining talent of training teachers (2) Needs assessing competency for labor market change and trainee (3) Problem solving competency (4) Leadership skills and so on.

• Journal of Advanced Navigation Technology
• /
• v.21 no.6
• /
• pp.674-679
• /
• 2017

As the importance of the 4th industrial revolution and ICT technology increased, it became a software centered society. Existing software training was limited to the composition of the learning environment, and a lot of costs were incurred early. In order to solve these problems, a learning method using a web compiler was developed. The web compiler supports various software languages and shows compilation results to the user via the web. However, Web compilers that support artificial intelligence technology are missing. In this paper, we designed and implemented a tensor flow based web compiler, Google's artificial intelligence library. We implemented a system for learning artificial intelligence by building a meteorJS based web server, implementing tensor flow and tensor flow serving, Python Jupyter on a nodeJS based server. It is expected that it can be utilized as a tool for learning artificial intelligence in software centered society.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.13 no.2
• /
• pp.115-125
• /
• 2003

As Web services are generally open for external uses and not filtered by Firewall, these result in attacker's target. Web attacks which exploit vulnerable web-applications and malicious users' requests cause economical and social problems. In this paper, we are modelling general web service usages based on user-web-session and detect anomal usages with Bayesian estimation method. Finally we propose SAD(Session Anomaly Detection) for detection unknown web attacks. To evaluate SAD, we made an experiment on attack simulation with web vulnerability scanner, whisker. The results show that the detection rate of SAD is over 90%, which is influenced by several features such as size of window or training set, detection filter method and web topology.

• Journal of the Korean Society for Library and Information Science
• /
• v.35 no.2
• /
• pp.207-225
• /
• 2001

As Web based knowledge and technology is needed for librarians in the digital environments, it should be educated through the Department of Library and Information(DLI) courses. For importing the courses in DLI, we go through several preliminary stages. First, the role and duties of web masters in digital libraries are figured out. Second, it is known that the tendency of MLS courses in American universities is toward to adopt the web related subjects, but still not in Korea. Third, the survey finds out the recognition of web masters in Korean university libraries about the functions and abilities web masters. As the results, we suggest several subjects for the web master's training. They are HTML, XML, Window NT and Web Server Management, Javascript and Java, Networks, Mutimedia Programs, Programming, and LINUX.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.1 s.256
• /
• pp.26-35
• /
• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.12
• /
• pp.165-172
• /
• 2020

Recently, due to exponential growth of access information on the web, the importance of predicting a user's next web page use has been increasing. One of the methods that can be used for predicting user's next web page is deep learning. To predict next web page, web logs are analyzed by data preprocessing and then a user's next web page is predicted on the output of the analyzed web logs using a deep learning algorithm. In this paper, we propose a framework for web page prediction that includes methods for web log preprocessing followed by deep learning techniques for web prediction. To increase the speed of preprocessing of large web log, a Hadoop based MapReduce programming model is used. In addition, we present a web prediction system that uses an efficient deep learning technique on the output of web log preprocessing for training and prediction. Through experiment, we show the performance improvement of our proposed method over traditional methods. We also show the accuracy of our prediction.