• Journal of vocational education research
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• v.37 no.5
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• pp.25-53
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• 2018

The purpose of this study is to find out the improvement plan through the satisfaction survey of the trainees involved in vocational training fraud preventive education. In order to do this, we conducted a satisfaction survey(4,263 persons) of 5,939 people who participated in the prevention education conducted by group education or e-learning in 2017. Finally we collected 4,237 effective responses data. Descriptive statistics and the regression analysis were conducted. The finding of the study were as follows. First, the education service quality(4.42), satisfaction level(4.44), understanding level(4.44) and help level(4.45) were significantly higher than those of participants in the preventive education 4 and above. Second, e-learning participants' perceived level of education service quality, satisfaction, comprehension, and help was higher in all variables than collective education's. Third, all of the sub-factors of preventive education service quality influenced satisfaction, understanding, and help in collective education and e-learning, respectively. In the collective education, the contents of education had the greatest influence, and in e-learning, the data composition had the greatest influence. Fourth, desirable education contents were cases of fraud training(70.7%), disposition regulations(47.9%), NCS course operation instructions(32.8%) and training management best practices(32.4%). Additional requirements also included the establishment of an in-depth course, the provision of anti-fraud education content for trainees, and screen switching and system stability that can be focused on e-learning. Therefore, this study suggests that first, it is necessary to activate e-learning for prevention education more, reflecting satisfaction of e-learning is higher than that of collective education. Second, it is necessary to diversify the content of preventive education and to provide it more abundantly, because it has the biggest influence in common with the satisfaction, understanding and help level of the preventive education. Third, education content next, the factors that have a relatively big influence on satisfaction are shown as delivery method and education place in the collective education. Therefore, it is necessary to prepare education place considering the assignment of instructor and convenience. Fourth, constructing data next, the factor that have a relatively great influence on understanding and help are found to be operator support, and more active operator support activities are required in e-learning. Fifth, it is required to delivery prevention activity for trainees participating in vocational training. Sixth, it is necessary to analyze the educational need to construct the contents of preventive education more systematically.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.97-106
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• 2020

Due to the rapid development and dissemination of 5G communication and IoT technologies, there are increasing demands for big data analysis techniques and service systems. In particular, explosively growing demands on AI technology adoption are also causing high competitions to take advantages of machine/deep-learning models to extract novel values from enormously collected data. In order to adopt AI technology to various research and application domains, it is necessary to prepare high-performance GPU-equipped systems and perform complicated settings to utilze deep learning models. To relieve the efforts and lower the barrier to utilize AI techniques, AIaaS(AI as a service) platform is attracting a great deal of attention as a promising on-line service, where the complexity of preparation and operation can be hidden behind the cloud side and service developers only need to utilize the high-level AI services easily. In this paper, we propose an AIaaS system which can support the creation of AI services based on Docker and OpenFaaS from the registration of models to the on-line operation. We also describe a case study to show how AI services can be easily generated by the proposed system.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.71-80
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• 2022

In the past, fish diseases were bacterial in aqua farms, but in recent years, the frequency of fish diseases has increased as they have become viral and mixed. Viral diseases in an enclosed space called a aqua farm have a high spread rate, so it is very likely to lead to mass death. Fast identification of fish diseases is important to prevent group death. However, diagnosis of fish diseases requires a high level of expertise and it is difficult to visually check the condition of fish every time. In order to prevent the spread of the disease, an automatic identification system of diseases or fish is needed. In this paper, in order to improve the performance of the disease identification system of Paralichthys olivaceus based on deep learning, the existing pre-processing method is compared and tested. Target diseases were selected from three most frequent diseases such as Scutica, Vibrio, and Lymphocystis in Paralichthys olivaceus. The RGB, HLS, HSV, LAB, LUV, XYZ, and YCRCV were used as image pre-processing methods. As a result of the experiment, HLS was able to get the best results than using general RGB. It is expected that the fish disease identification system can be advanced by improving the recognition rate of diseases in a simple way.

• International Journal of Contents
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• v.10 no.4
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• pp.11-17
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• 2014

The influence of acquisition environment on music score images captured by a camera has not yet been seriously examined. All existing Optical Music Recognition (OMR) systems attempt to recognize music score images captured by a scanner under ideal conditions. Therefore, when such systems process images under the influence of distortion, different viewpoints or suboptimal illumination effects, the performance, in terms of recognition accuracy and processing time, is unacceptable for deployment in practice. In this paper, a novel, lightweight but effective approach for dealing with the issues caused by camera based music scores is proposed. Based on the staff line information, musical rules, run length code, and projection, all regions of interest are determined. Templates created from inverse filter are then used to recognize the music symbols. Therefore, all fragmentation and deformation problems, as well as missed recognition, can be overcome using the developed method. The system was evaluated on a dataset consisting of real images captured by a smartphone. The achieved recognition rate and processing time were relatively competitive with state of the art works. In addition, the system was designed to be lightweight compared with the other approaches, which mostly adopted machine learning algorithms, to allow further deployment on portable devices with limited computing resources.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.1087-1091
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• 2009

The concept for algorithm needs to be established in various fields such as architecture, medicine and life science but understanding only theoretically has its limits. It is therefore educated using many multimedia factors but still is difficult to bring interests and carry out the higher level courses. For algorithm and programming, due to the subject's peculiarity it is very important to actually execute the program to understand the realization theory. In this paper, it aims to design a basic concept of algorithm using a flow chart of visualizing program and an algorithm education system to learn the basic programming C language, which is the fundamental element in algorithm learning.

• The Journal of Korean Institute for Practical Engineering Education
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• v.5 no.1
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• pp.34-39
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• 2013

This paper suggests an input device that allows a user not only to naturally interact with education contents in virtual environment but also to sense haptic feedback according to his/her interaction. The proposed system measures a user's motion and then creates haptic feedback based on the measured position. To create haptic information in response to a user's interaction with educational contents in virtual environment, we develop a motion input device which consists of a motion controller, a haptic actuator, a wireless communication module, and a motion sensor. To measure a user's motion input, an accelerometer is used as the motion sensor. The experiment shows that the proposed system creates continuous haptic sensation without any jerky motion or vibration.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.85-92
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• 2009

As World Wide Web is more popularized nowadays, the environment is flooded with the information through the web pages. However, despite such convenience of web, it is also creating many problems due to uncontrolled flood of information. The pornographic, violent and other harmful information freely available to the youth, who must be protected by the society, or other users who lack the power of judgment or self-control is creating serious social problems. To resolve those harmful words, various methods proposed and studied. This paper proposes and implements the protecting system that it protects internet youth user from harmful contents. To classify effective harmful/harmless contents, this system uses two step classification systems that is harmful word filtering and SVM learning based filtering. We achieved result that the average precision of 92.1%.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.122-130
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• 2021

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

• Journal of Digital Contents Society
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• v.11 no.1
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• pp.1-8
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• 2010

Computers can intensify the students' motivation and understanding about the solution to the problems in class, therefore, computers can be the most appropriate educational tools for the study of problem solving and have been also recognized as a representable study method in the information age, which can pass on various educational experience to the right place at the right time. Mutimedia producing tool helps us develop and maintain the educational courseware by way of using general technology of multimedia system. In this thesis, it presents the efficient development process of educational software by using mutimedia producing tool, its educational advantages and problems, and its future progress direction as well.

• Korean Medical Education Review
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• v.23 no.2
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• pp.90-103
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• 2021

This study examined the current status of the medical professionalism curriculum in Korea to suggest a plan to move towards the formation of a professional identity. Professionalism education data from 28 Korean medical schools were analyzed, including the number of courses, required or elective status, corresponding credits, major course contents, and teaching and evaluation methods. Considerable variation was found in the number of courses and credits in the professionalism curriculum between medical schools. The course contents were structured to expand learners' experiences, including the essence and knowledge of professionalism, understanding of oneself, social interaction with others, and the role of doctors in society and the healthcare system. The most common teaching methods were lectures and discussions, while reflective writing, coaching, feedback, and role models were used by fewer than 50% of medical schools. Written tests, assignments and reports, discussions, and presentations were frequently used as evaluation methods, but portfolio and self-evaluation rates were relatively low. White coat ceremonies were conducted in 96.2% of medical schools, and 22.2% had no code of conduct. Based on the above results, the author suggests that professional identity formation should be explicitly included in learning outcomes and educational contents, and that professional identity formation courses need to be added to each year of the program. The author also proposes the need to expand teaching methods such as reflective writing, feedback, dilemma discussion, and positive role models, to incorporate various evaluation methods such as portfolios, self-assessment, and moral reasoning, and to strengthen faculty development.