• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.387-393
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• 2022

The article reflects short-term perspectives on the use of information and communication technologies in the training of teachers for higher education. Education is characterized by conservatism, so aspects of systematic development of the industry are relevant to this cluster of social activity. Therefore, forecasting the introduction of innovative elements of ICT training is in demand for the educational environment. Forecasting educational trends are most relevant exactly in the issues of training future teachers of higher education because these specialists are actually the first to implement the acquired professional skills in pedagogical activities. The article aims to consider the existing potential of ICT-based learning, its implementation in the coming years, and promising innovative educational elements that may become relevant for the educational space in the future. The tasks of scientific exploration are to show the optimal formats of synergy between traditional and innovative models of learning. Based on already existing experience, extrapolation of conditions of educational process organization with modeling realities of using information and communication technologies in various learning dimensions should be carried out. Educational trends for the next 3 years are a rather tentative forecast because, as demonstrated by the events associated with the COVID-19 pandemic, the socio-cultural space is very changeable. Consequently, the dynamism of the educational environment dictates the need for a value-based awareness of the information society and the practical use of technological advances. Thus, information and communication technologies are a manifestation of innovative educational strategies of today and become an important component along with traditional aspects of educational process organization. Future higher education teachers should develop a training strategy taking into account the expediency of the ICT component.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.165-171
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• 2024

The processes of society's informatization and digitalization necessitate the widespread use of new pedagogical technologies. Through these technologies, comprehensive disclosure of didactic functions of new methods of educational activity and the realization of the potential and creative potential. The use of information and computer multimedia technologies in teaching music art is especially relevant in the intensification of the development of interactive technologies, the transition to mixed forms of learning, and a period of socio-economic and sociopolitical upheavals. The study aims to substantiate the theoretical and applied principles of the analysis of multimedia technology learning musical art in modern conditions and assess the status and trends in their use in conducting educational activities. The study uses general scientific and unique methods of economic analysis, in particular, analysis and synthesis, analogy and comparison, generalization and systematization, and graphic ways. Regarding the results of the study of multimedia technologies for teaching musical art in current conditions, it was found that they contribute to the development of the seeker's creative, creative, and cognitive activity, have a positive impact on learning material, and diversify the educational process. Multimedia technologies such as presentations, programs for watching a video, listening to audio, music and singing karaoke, electronic encyclopedias, and Internet resources are proven to be the most used in music education. They have several qualitative and quantitative advantages, manifested in the possibilities of audio-visual presentation of educational material and significantly higher information density. It is suggested to strengthen the use of such computer programs as Microsoft Word, Ahead Nero, Finale, Adobe Audition, Sound Forge, and Microsoft PowerPoint for musical art classes.

• Journal of Information Processing Systems
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• v.4 no.4
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• pp.159-168
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• 2008

Human-Robot Interaction (HRI), based on already well-researched Human-Computer Interaction (HCI), has been under vigorous scrutiny since recent developments in robot technology. Robots may be more successful in establishing common ground in project-based education or foreign language learning for children than in traditional media. Backed by its strong IT environment and advances in robot technology, Korea has developed the world's first available e-Learning home robot. This has demonstrated the potential for robots to be used as a new educational media - robot-learning, referred to as 'r-Learning'. Robot technology is expected to become more interactive and user-friendly than computers. Also, robots can exhibit various forms of communication such as gestures, motions and facial expressions. This study compared the effects of non-computer based (NCB) media (using a book with audiotape) and Web-Based Instruction (WBI), with the effects of Home Robot-Assisted Learning (HRL) for children. The robot gestured and spoke in English, and children could touch its monitor if it did not recognize their voice command. Compared to other learning programs, the HRL was superior in promoting and improving children's concentration, interest, and academic achievement. In addition, the children felt that a home robot was friendlier than other types of instructional media. The HRL group had longer concentration spans than the other groups, and the p-value demonstrated a significant difference in concentration among the groups. In regard to the children's interest in learning, the HRL group showed the highest level of interest, the NCB group and the WBI group came next in order. Also, academic achievement was the highest in the HRL group, followed by the WBI group and the NCB group respectively. However, a significant difference was also found in the children's academic achievement among the groups. These results suggest that home robots are more effective as regards children's learning concentration, learning interest and academic achievement than other types of instructional media (such as: books with audiotape and WBI) for English as a foreign language.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.845-850
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• 2023

In this paper, we propose a method for diagnosing ball bearing vibration using transfer learning. STFT, which can analyze vibration signals in time-frequency, was used as input to CNN to diagnose failures. In order to rapidly learn CNN-based deep artificial neural networks and improve diagnostic performance, we proposed a transfer learning-based deep learning learning technique. For transfer learning, the feature extractor and classifier were selectively learned using a VGG-based image classification model, the data set for learning was publicly available ball bearing vibration data provided by Case Western Reserve University, and performance was evaluated by comparing the proposed method with the existing CNN model. Experimental results not only prove that transfer learning is useful for condition diagnosis in ball bearing vibration data, but also allow other industries to use transfer learning to improve condition diagnosis.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.1-10
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• 2020

The image analysis is an important and predominant task for classifying the different parts of the image. The analysis of complex image analysis like histopathological define a crucial factor in oncology due to its ability to help pathologists for interpretation of images and therefore various feature extraction techniques have been evolved from time to time for such analysis. Although deep reinforcement learning is a new and emerging technique but very less effort has been made to compare the deep learning and deep reinforcement learning for image analysis. The paper highlights how both techniques differ in feature extraction from complex images and discusses the potential pros and cons. The use of Convolution Neural Network (CNN) in image segmentation, detection and diagnosis of tumour, feature extraction is important but there are several challenges that need to be overcome before Deep Learning can be applied to digital pathology. The one being is the availability of sufficient training examples for medical image datasets, feature extraction from whole area of the image, ground truth localized annotations, adversarial effects of input representations and extremely large size of the digital pathological slides (in gigabytes).Even though formulating Histopathological Image Analysis (HIA) as Multi Instance Learning (MIL) problem is a remarkable step where histopathological image is divided into high resolution patches to make predictions for the patch and then combining them for overall slide predictions but it suffers from loss of contextual and spatial information. In such cases the deep reinforcement learning techniques can be used to learn feature from the limited data without losing contextual and spatial information.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.344-355
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• 2002

Having a variety of good characteristics against other pattern recognition techniques, Multilayer Perceptron (MLP) has been used in wide applications. But, it is known that Error Backpropagation (EBP) algorithm which MLP uses in learning has a defect that requires relatively long leaning time. Because learning data in pattern recognition contain abundant redundancies, in order to increase learning speed it is very effective to use online-based teaming methods, which update parameters of MLP pattern by pattern. Typical online EBP algorithm applies fixed learning rate for each update of parameters. Though a large amount of speedup with online EBP can be obtained by choosing an appropriate fixed rate, fixing the rate leads to the problem that the algorithm cannot respond effectively to different leaning phases as the phases change and the learning pattern areas vary. To solve this problem, this paper defines learning as three phases and proposes a Instant Learning by Varying Rate and Skipping (ILVRS) method to reflect only necessary patterns when learning phases change. The basic concept of ILVRS is as follows. To discriminate and use necessary patterns which change as learning proceeds, (1) ILVRS uses a variable learning rate which is an error calculated from each pattern and is suppressed within a proper range, and (2) ILVRS bypasses unnecessary patterns in loaming phases. In this paper, an experimentation is conducted for speaker verification as an application of pattern recognition, and the results are presented to verify the performance of ILVRS.

• Journal of The Korean Association For Science Education
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• v.31 no.4
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• pp.641-662
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• 2011

In this study, explicit Teaching and Learning strategy for middle school students were developed to improve basic science process skills. After applying these strategy in an actual class, the effects of Teaching and Learning strategy and change of students were analyzed. Explicit Teaching and Learning strategy to improve basic science process skills are developed based on analyzing preceding research. The use of application criteria for class of basic science process skills combined with explicit Teaching and Learning strategy, it is sought for the explicit instructional procedures of said skills. After analyzing the class in which explicit Teaching and Learning strategy were demonstrated, students reported that they were able to comprehend basic science process skills more effectively through the stages of explicit explaining and independent practice. The showing demonstration stage was heavily emphasized by the teacher in this class. Analysis of students' understanding degree about basic science process skills, most of them show positive outcome. Another analysis of ripple effect on daily life and other subjects, it is found that students could have the attitude to make use of science process skills for themselves. Through the result of study, it is found that explicit Teaching and Learning strategy that are developed from this study are an effective way to comprehension students' basic science process skills. Thus, continued study is needed to develop and spread explicit Teaching and Learning strategy of science process skills to be applicable in actual classes in secondary schools.

• Journal of The Korean Association of Information Education
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• v.14 no.3
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• pp.427-435
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• 2010

As the e-Learning plays an increasingly larger important part in education and has been increased as an alternative to offline education, academic organizations are moving ahead to set guidelines for quality assurance in e-Learning. And various quality assurance techniques in e-Learning have been developed because the e-Learning does not always match well traditional models of teaching and learning, much care needs to be taken in the design, creation and implementation of service. But the present quality assurances in e-Learning which are focused in learning objects have much problems because they use partial and static management. In this thesis we suggested dynamic quality assurance using CLD(Causal Loop Diagram) in e-Learning. The suggested method has more efficiency than existing methods and it can provide important strategies with regard to administrative issues in e-Learning.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.2
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• pp.75-96
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• 2011

Recently, Dennis et al.(2008) proposed media synchronicity theory. In this theory, for conveyance communication processes, use of media supporting lower synchronicity should result in better communication performance. But for convergence processes, use of media supporting higher synchronicity should result in better communication performance. This paper proved a part of the propositions of media synchronicity theory, because media synchronicity theory was proposed theoretically, not empirically. We used a data set generated from the survey. The respondents of survey were 163 students who had experienced the communication media in the classes that should summit result of team projects or team reports. According to the results of data analysis, higher use of communication media led to better learning performance. The familiarity of task moderated the effect of communication media on learning performance. And use of media supporting higher synchronicity led to better learning performance.

• Journal of Engineering Education Research
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• v.22 no.2
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• pp.55-60
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• 2019

Colleges of technology in Japan are characterized by specialized education starting from the first grades aged fifteen, making it particularly important to provide motivation for specialized subjects. The most difficult thing for teachers in the technical college is giving the motivation to a professional education to the lower grades who don't know the technology and engineering. Teachers tried to use and make a suitable example or an education material for their lecture. The generation gap with students makes it difficult for teachers to use examples of objects that students are actually familiar with in their daily life. To compensate for the generation gap with students, we asserted that education for lower grades should adopt the perspectives of students in higher grades. The relative closeness in age of lower and higher grades helps reduce the generation gap with students, which is advantageous in that teachers can share the perspectives of students.