• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.443-450
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• 2022

The method of studying 3D-technologies abroad and in Ukraine is considered. The analysis of educational resources and experience of use of the equipment in branch is carried out. The didactic principles of the educational process for 3D-printing specialists are determined. The use of FDM technology and the ability to minimize the occurrence of defects in the future have been studied. An analysis of the international experience of the educational process of relevant specialists in the field. The content of training for 3D printing specialists has been developed. The experience of using 3D-technologies is described and the list of recommendations for elimination of defects during production of products by means of additive technologies is made. The recommendations will be useful not only for beginners, but also for experienced professionals in additive technologies. The need to study such experience is the main condition for the development of enterprises in Ukraine that plan to automate their own production. A 3D printing engineer must know the basics of economics and marketing, because his responsibilities include optimizing workflows to reduce the cost and speed up printing. Therefore, the knowledge gained from practical experience presented and in building for learning 3D printing engineers by the authors will be important.

• ETRI Journal
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• v.39 no.5
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• pp.643-651
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• 2017

Human age estimation is one of the key factors in the field of Human-Robot Interaction/Human-Computer Interaction (HRI/HCI). Owing to the development of deep-learning technologies, age recognition has recently been attempted. In general, however, deep learning techniques require a large-scale database, and for age learning with variations, a conventional database is insufficient. For this reason, we propose an age estimation method using artificially generated data. Image data are artificially generated through 3D information, thus solving the problem of shortage of training data, and helping with the training of the deep-learning technique. Augmentation using 3D has advantages over 2D because it creates new images with more information. We use a deep architecture as a pre-trained model, and improve the estimation capacity using artificially augmented training images. The deep architecture can outperform traditional estimation methods, and the improved method showed increased reliability. We have achieved state-of-the-art performance using the proposed method in the Morph-II dataset and have proven that the proposed method can be used effectively using the Adience dataset.

• Journal of the Korean Institute of Gas
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• v.21 no.5
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• pp.89-94
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• 2017

The VR(Virtuality Reality) technology provides very close experience to reality by stimulating humans' external recognition with artificial technologies. In order to overcome the limitation of real-environment training, VR is being applied in industry field as a key technology to prevent safety accident and its control procedure training. However, it is difficult to build VR-based training system because 3D modeling and software coding are necessary for materialization of VR environment demands of many development resource. In this research referring to VR based training content implementation, a method to utilizing VRDC(VR-based Dynamic visualization Component) is suggested and by applying it to plant safety training system, it was confirmed its practicality.

• Journal of radiological science and technology
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• v.44 no.2
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• pp.123-131
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• 2021

In this study, safety education contents for medical radiation workers were produced based on Mixed Reality(MR). Currently, safety training for radiation workers is based on theory. This is insufficient in terms of worker satisfaction and efficiency. To address this, we created ICT(Information and Communication Technologies)-based MR radiation worker safety education content. The expected effect of Mixed Reality worker safety education content is that education is possible without space and time constraints, realistic education is possible without on-site training, and interaction between images is possible through reality-based 3D images, enabling self-directed learning Is that. In addition, learning in a virtual space expressed through HMD(Head Mounted Display) is expected to make education more enjoyable and increase concentration, thereby increasing the efficiency of education. A quantitative evaluation was conducted by an accredited institution and a qualitative evaluation was performed on users, which received excellent evaluation. The MR safety education conducted in this study is expected to be of great help to the education of medical radiation workers, and is expected to develop into a new educational paradigm as online education in accordance with Corona 19 progresses.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.15-24
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• 2022

The article clarifies the conditions for information, digital and educational accessibility for higher education seekers with disabilities in terms of distance learning caused by quarantine restrictions. It is established that such conditions are regulated by international and Ukrainian legal documents (The Standard Rules on the Equalization of Opportunities for Persons with Disabilities, Convention on the Rights of Persons with Disabilities, Sustainable Development Goals, Law of Ukraine "On Education", Law of Ukraine "On Higher Education", Strategy for the Development of Higher Education in Ukraine 2021-2031, Development Strategy areas of innovation for the period up to 2030, Development strategy of the sphere of innovation activity for the period up to 2030). As a part of information barrierlessness, Higher Education Institutions (HEI) should provide access to information in various formats and using technologies, in particular Braille script, large-type printing, audio description (audio descriptive commenting), sign language interpretation, subtitling, a format suitable for reading by screen access programs, formats of simple speech, easy-to-read formats, means of alternative communication. The experience of Pavlo Tychyna Uman State Pedagogical University is described. In particular, special attention is paid to the study of sign language: in view of this, the initiative group implemented the project "Learning to hear and overcome social isolation together" with the financial support of the British Council in Ukraine. Within the framework of digital accessibility, the official website of the Faculty of Social and Psychological Education has been adapted for the visually impaired in accordance with WCAG 2.0 World Standards. In 2021, Pavlo Tychyna Uman State Pedagogical University implemented the project "Cultural, Recreational and Tourist Cherkasy Region: Inclusive Social 3D Map" funded by the Ukrainian Cultural Foundation; a site with available content for online travel in the region to provide barrier-free access to the historical and cultural heritage of Cherkasy region was created. Educational accessibility is achieved by increasing the number of people with special educational needs, receiving education in inclusive groups; activities of the Center for Social and Educational Integration and Inclusive Rehabilitation Social Tourism "Bez barieriv" ("Without barriers"); implementation of a research topic for financing the Ministry of Education and Science of Ukraine: "Social and psychological rehabilitation of children and youth with special educational needs by means of inclusive tourism"; implementation of the project "Social inclusion of distance educational process"; development of information campaigns to popularize the ideas of accessibility, the need for its implementation, ongoing training programs and competitions, etc.