• Journal of Agricultural Extension & Community Development
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• v.1 no.1
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• pp.67-74
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• 1994

The objectives of this study were to review the present situations of computer use, computer education and training, and attitude to computer of agricultural extension agents. The research subjects were 279 agricultural extension agents in 15 City and Gun Rural Extension Offices Which were sampled by random sampling method among 182 City and Gun Rural Extension Offices. The major findings of the study were as follows; 1. Only 28% of the agricultural extension agents had personal computer in their home. 2. Agricultural extension agents mainly used word processor program, but hardly used data base, spreadsheet, and computer language. 3. About 40% of the respondents had not chance to be participated in computer education/training program yet. 4. Generally, rural change agents agreed that computer is very valuable for their job and that they should learn high computer technology. 5. Concludly, various contents of computer education/training program should be prepared for rural change agents and they should take full advantage of computer facilities.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.153-159
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• 2022

The article discusses the use of smart technologies in the training of future specialists. Today, learning using smart technologies is becoming a new educational standard, where information is presented in a logical sequence, computer training systems have powerful functions for the educational process. The functions of smart technologies are highlighted. It is noted that smart technologies are successfully used in the field of education and professional training. The concept of "smart education" is characterized. Smart education is an educational paradigm that underlies a new type of education system. The implementation of the smart education paradigm is aimed at the process of obtaining competencies and competencies for flexible and adapted interaction with the social, economic and technological environment. Smart education should ensure that the benefits of the global information society can be used to meet educational needs and interests. A special place is occupied by computer-based educational multimedia systems that allow you to deepen your knowledge, reduce the duration of training, and increase the number of students per teacher. The main principles of smart education are highlighted. Improving the efficiency of training in a modern higher education institution is impossible without the introduction of smart technologies in the organization of the educational process.

• Journal of The Korean Association of Information Education
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• v.3 no.1
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• pp.116-124
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• 1999

Cyber education and teacher training is the distance training program which is operating in the Korea National University of Education for teachers and citizen. In this paper, we suggest a model for establishing legal basis of cyber teacher training, by analyzing laws and processing-laws in the parliament and cyber teacher training institutes. The model contain 'The Rule for Operating CTTI(Cyber Teacher Training Institute)', 'The Rule for Using CIT Systems', 'The Rule for Operation CIT'.

• Journal of Multimedia Information System
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• v.7 no.4
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• pp.277-280
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• 2020

Extended reality-assisted training offers repeatable learning opportunities at a low cost. This paper proposes a smart glass application for training core nursing skills to nursing students, who often need to memorize and practice training sequences. The proposed smart glass application interactively presents a series of instructions to help students remember and perform two core nursing skills in the correct order. We conducted a usability test on 30 undergraduate nursing students in their third year using the smart glass application. Our initial findings show that many students have positively evaluated the possibility of using smart glasses for training, but have also encountered several challenges with the smart glass application's user interface, which takes time to adapt.

• ETRI Journal
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• v.44 no.2
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• pp.327-338
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• 2022

Classification models for human action recognition require robust features and large training sets for good generalization. However, data augmentation methods are employed for imbalanced training sets to achieve higher accuracy. These samples generated using data augmentation only reflect existing samples within the training set, their feature representations are less diverse and hence, contribute to less precise classification. This paper presents new data augmentation and action representation approaches to grow training sets. The proposed approach is based on two fundamental concepts: virtual video generation for augmentation and representation of the action videos through robust features. Virtual videos are generated from the motion history templates of action videos, which are convolved using a convolutional neural network, to generate deep features. Furthermore, by observing an objective function of the genetic algorithm, the spatiotemporal features of different samples are combined, to generate the representations of the virtual videos and then classified through an extreme learning machine classifier on MuHAVi-Uncut, iXMAS, and IAVID-1 datasets.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.47-53
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• 2019

In general, dizziness is caused by various situations, but among them, symptoms due to dysfunction of the motor system belonging to the nervous system are the most severe, accompanied by nausea and vomiting. Treatment of these dizziness includes drug therapy, surgical therapy, and rehabilitation. Drug therapy and surgery are generally performed in vest rehabilitation training, which is a rehabilitation therapy because of the risk of aftereffects. The vestibular rehabilitation training includes eye training, posture stabilization training, and walking training. Among them, walking training is performed in a certain space under the supervision of a doctor or a professional therapist, so that the time and space burden is increased. In order to solve this problem, we implemented gait training contents which can be used for rehabilitation training by using the augmented reality technology. It is expected that it can be utilized as dizziness rehabilitative contents which can be used in medical environment through clinical tests for patients with dizziness.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.7
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• pp.759-768
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• 2018

As the number of exchange in various fields between countries increases, the number of international conference increases. Many students study simultaneous interpretation due to the increased demand of simultaneous interpretation. Since simultaneous interpretation requires a lot of learning time, students majoring in translation perform the self learning. The paper based sight translation training system is a representative self learning method, but backtracking decreases the efficiency of self learning and it requires the help of the partner. To improve the learning efficiency, computer based sight translation training system has been proposed. However, since students uses the computer based sight translation training system only in a fixed area due to low mobility of computer, the utilization of the system decreases. In this paper, smart device based sight translation training system has been proposed to increase the utilization of the proposed system. Since smart device has lower computing capabilities than the computer, we have proposed algorithms to deal with the low performance. We implement and evaluate the functionalities of the proposed training system.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.3
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• pp.747-756
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• 2019

Students studying interpretation perform additional study and training in addition to regular class. In simultaneous interpreting and consecutive interpreting, interpreter should memorize speaker's announcement because of different language structure. To improve short-term memory, students perform memory training that requires a pair of students. Therefore, they can not perform self-learning, and therefore, efficiency of studying decreases. To resolve this problem, computer based short-term memory training system has been proposed. Student can perform self-learning by changing words in text to special character in the training system. However, efficiency of studying decreases because computer has low portability. Since the number of words is larger than the number of words to be switched into special character, learning difficulty decreases. To resolve this problem, smart device based short-term memory training system has been proposed. Student can perform smart device based training system without space constraints. Since the proposed training system increases the number of words to be changed into special character, learning difficulty increases. We implemented and evaluated the functionalities of the proposed training system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.89.3-89
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• 2001

Recently computer graphic technology has achieved remarkable development. Applications of this technology to various fields are expected. In this study, one application of computer graphics to the medical field is shown. We developed a rehabilitation system of hand manipulation using virtual reality aiming to offer enjoyable rehabilitation training to physically handicapped people with upper limb disabilities. This rehabilitation system generates training environments for upper limbs, such as moving balls in virtual space of computer. And by using data glove as a sophisticated input device, a user can manipulate objects in virtual space by his hand. By using this rehabilitation system, a user can have rehabilitation training under various conditions without feeling tedious.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.335-354
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• 2014

The accuracy of training-based activity recognition depends on the training procedure and the extent to which the training dataset comprehensively represents the activity and its varieties. Additionally, training incurs substantial cost and effort in the process of collecting training data. To address these limitations, we have developed a training-free activity recognition approach based on a fuzzy logic algorithm that utilizes a generic activity model and an associated activity semantic knowledge. The approach is validated through experimentation with real activity datasets. Results show that the fuzzy logic based algorithms exhibit comparable or better accuracy than other training-based approaches.