• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.131-140
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• 2018

The KAIE computing system curriculum consists of information equipment, operating systems, and information and communication fields, and covers basic understanding and principles of computer science. The role of the teacher is important to achieve the curriculum achievement standards. Therefore, we examined the factors affecting the teaching capacity of the KAIE computing system curriculum. The results of this study show that the teaching methods of teachers through the literacy of information and communication technology have a statistically significant effect on the teaching competency of the computing system curriculum. Also, male teachers perceived higher perceived factors than female teachers. The differences in teaching competency between teacher groups of less than 5 years and less than 5~10 years were significant. Based on these results, it is necessary to develop collaborate SW teaching strategies and mentor - centered training programs that can strengthen ICT and SW professors' competence and encourage participation of low - career teachers and female teachers.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.599-606
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• 2019

Telepresence robot-assisted learning can provide opportunities of education for students who are in vulnerable physical, intellectual, cultural or environmental conditions. It is to be applied in international virtual education for global citizenship education. To date, the study of acceptance model has been conducted only for preservice teachers, and post-intention for use is not considered. This paper identified whether there are significant differences by gender or years of experience from elementary school teachers on it and the basic factors that affect the acceptance intentions for it. Factors related to intention to use for a telepresence robot were investigated, and a questionnaire about post-intention for use was made after participants operated. The results showed that elementary school teachers did not have a significant difference in each factor by gender. The experienced teachers showed no difficulty in using it. It was shown that PU, ATT, PENJ, SI and Ttrust were all extremely significant factors to affect acceptance intentions. It will be possible to establish educational information policies based on the acceptance intentions of elementary school teachers on telepresence robot-assisted learning.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.367-372
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• 2013

In Speech recognition system, there is a problem with phoneme in the model training and it cause a stored mode regeneration process which come into being appear time and more costs. In this paper, we propose the methode of likely phoneme model schema using decision tree clustering. Proposed system has a robust and correct sound model which system apply the decision tree clustering methode form generate model, therefore this system reduce the regeneration process and provide a retrieve the phoneme unit in probability model. Also, this proposed system provide a additional likely phoneme model and configured robust correct sound model. System performance as a result of represent vocabulary dependence recognition rate of 98.3%, vocabulary independence recognition rate of 98.4%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.15-24
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• 2008

For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in linear discriminant analysis-based methods for dimension reduction is what is known as the small sample size (SSS) problem. Recently, to solve the SSS problem, a way of employing a dissimilarity-based classification(DBC) has been investigated. In DBC, an object is represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. In this paper, we propose a new method of optimizing DBCs using multi-level fusion strategies(MFS), in which fusion strategies are employed to represent features as well as to design classifiers. Our experimental results for benchmark face databases demonstrate that the proposed scheme achieves further improved classification accuracies.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.157-164
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• 2020

In 2020, due to COVID-19, all universities in Korea were conducting non-face-to-face classes. The purpose of this study is to study what factors affect academic achievement under such non-face-to-face instruction, especially for engineering students where practical training is important. Validity of the statistical hypothesis defined in this study by applying a structural equation model using questionnaires about academic achievement for engineering students at University D for this study. In addition, I would like to suggest what factors should be considered in non-face-to-face classes, especially in engineering colleges. As a result of the study, it was found that students' Q&A, feedback and e-learning system had a direct influence on academic achievement. In addition, it was confirmed that they had an indirect influence on academic achievement through the parameters of theory class and practical class.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.671-680
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• 2015

The Joint Bayesian[1] method was published in 2012. Since then, it has been used for binary classification in almost all state-of-the-art face recognition methods. However, no improved methods have been published so far except 2D-JB[2]. In this paper we propose an improved version of the JB method that considers the features of both the given face image and its mirror image. In pattern classification, it is very likely to make a mistake when the value of the decision function is close to the decision boundary or the threshold. By making the value of the decision function far from the decision boundary, the proposed method reduces the errors. The experimental results show that the proposed method outperforms the JB and 2D-JB methods by more than 1% in the challenging LFW DB. Many state-of-the-art methods required tons of training data to improve 1% in the LFW DB, but the proposed method can make it in an easy way.

• Journal of Fisheries and Marine Sciences Education
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• v.4 no.1
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• pp.1-15
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• 1992

Fishery and shipping industry are ones of the important industries for the Republic of Korea, and the education of competent technicians is a essential-important factor for the further development in these fields. To this end, curriculum for the fisheries and/or merchant marine high schools are rearranged to meet the industrial needs and social change. In this study, the existing goal of education is rearranged inclusively to meet the further development and the curriculum to realize the goal. The departments are reorganized into nine ones by establishing new two. They are Department of Refrigeration Mechanical Engineering and of Automated-ship Operation. Four departments of existing seven-Department of Fish Aquaculture, of Fish Processing, of Marine Engine and of Marine Communication-are renamed into Department of Aquaculture, of Food Processing, of Power Mechanical Engineering and of Electronic Communication respectively. The remaining three departments- Department of Fishing Technology, of Self-managing Fisheries and of Navigation-are unchanged. The specialized subjects are revised as follows; (1) The existing seven subjects especially prepared for the fisheries and/or merchant marine high schools are changed into the common subjects for all the vocational high schools. They are Food Science, Food Hygiene, Food Processing Machinery, Air-conditioning Facilities, Welding and Piping, Communication Law and Introduction to Computer. (2) Two subjects are newly established: Refrigeration Mechanical Engineering and Automated-ship Operation. (3) Four subjects are disused : Sea Training, Fisheries Law, Canned Food and Practice in Communication. (4) Introduction to ship, to Marine Engine and to Marine Communication are merged into Introduction to ship. (5) The compulsory major subject is fixed as Introduction to Fisheries for the fisheries high schools and Introduction to shipping Industry for the merchant marine high schools.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.12
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• pp.502-508
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• 2016

An optimized PI controller design method is presented to promote the control performance of an oil cooler system for high precision machine tools. First, a transfer function model of the oil cooler system with a variable rotating speed compressor was obtained by the perturbation method as the first order system with a negligible dead time. Then, the closed-loop control system was described as the second order system with a zero. Its dynamic behaviors are mostly governed by characteristic parameters, the damping ratio, and the natural frequency which is incorporated in PI gains. Next, an optimum integral of the time-weighted absolute error (ITAE) criterion was applied to the second order system. The characteristic parameters can be determined by the given design specifications, percent overshoots and settling times and comparisons with the ITAE criterion. Hence, the PI gains were plainly identified in a deterministic way. Finally, the PI gains were fine-tuned to obtain desirable dynamics in real systems, considering the zero effect and parameter variations. The validity of the proposed method was proven by computer simulations and real experiments for selected cases.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.57-61
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• 1999

In the field of image compression, Classified Vector Quantization(CVQ) reveals attractive characteristics for preserving perceptual features, such as edges. However, the classification scheme is not generalized to effectively reconstruct different kinds of edge patterns in the original CVQ that predefines several linear-type edge classes: vortical edge horizontal edge diagonal edge classes. In this paper, we propose a new classification scheme, especially for edge blocks based on the similarity measure for edge patterns. An edge block is transformed to a feature vector that describes the detailed shape of the edge pattern The classes for edges are formulated automatically from the training images to result in the generalization of various shapes of edge patterns. The experimental results show the generated linear/nonlinear types of edge classes. The integrity of all the edges is faithfully preserved in the reconstructed image based on the various type of edge codebooks generated at 0.6875bpp.

• Journal of radiological science and technology
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• v.43 no.2
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• pp.65-70
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• 2020

PA(postero-anterior) and AP(antero-posterior) chest projections are the most sought-after types of all kinds of projections. But if a radiological technologist puts wrong information about the position in the computer, the orientation of left and right side of an image would be reversed. In order to solve this problem, we utilized CNN(convolutional neural network) which has recently utilized a lot for studies of medical imaging technology and rule-based system. 70% of 111,622 chest images were used for training, 20% of them were used for testing and 10% of them were used for validation set in the CNN experiment. The same amount of images which were used for testing in the CNN experiment were used in rule-based system. Python 3.7 version and Tensorflow r1.14 were utilized for data environment. As a result, rule-based system had 66% accuracy on evaluating whether the orientation reversal on chest x-ray image. But the CNN had 97.9% accuracy on that. Being overcome limitations by CNN which had been shown on rule-based system and shown the high accuracy can be considered as a meaningful result. If some problems which can occur for tasks of the radiological technologist can be separated by utilizing CNN, It can contribute a lot to optimize workflow.