• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.157-169
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• 2024

The article presents an analysis of innovative teaching technologies as a way to increase students' competitiveness. The author found that innovative technologies in education are information and communication technologies relying on computer-based learning. The structure, content of educational software, organization of Web-space are important when using innovative teaching technologies in English classes. We conducted the study in several stages: comparative analysis, synthesis, classification and systematization of the results of psychological and pedagogical, educational and methodological research; study of legislative acts, periodicals in order to identify the state of the research issue, and determining the directions of its solution, as well as subject, goal and objectives of the study. We used modelling to create situations of foreign language professional communication of future IT specialists. Empirical methods involved questionnaires used for identifying the motives of professional development and determining the features of the educational activities of future IT specialists in the process of training. The methods of mathematical statistics allowed to scientifically describe and systematize the obtained data, to identify the quantitative relationship between the studied phenomena, to analyse and summarize the results. We conducted a socio-psychological study during 2016 - 2019. It involved 255 first- and fourth-year students of National Technical University of Ukraine "Igor Sikorsky Kyiv Poly-technic Institute." Innovative information and communication technologies that improve the educational and cognitive activity of students, as well as increase the level of their knowledge have become important in teaching a foreign language in higher educational institutions. These technologies include MOODLE - Modular Object-Oriented Dynamic Learning Environment, business game, integrated pedagogical technology, case study technology. Thus, the information-rich learning process in combination with the use of innovative technologies, well-organized e-learning, interactive training courses, multimedia tools improves the program of teaching and learning foreign languages in general, and English in particular, improves the level of knowledge of future IT specialists and motivation to study and learn foreign languages, allows students to use a variety of authentic materials. We state that all these factors influence the process of individualization of learning and contribute to the successful mastery of a foreign language.

• Journal of Platform Technology
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• v.6 no.3
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• pp.23-30
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• 2018

A motion pattern generation is a process of calculating a certain stable motion trajectory for stably operating a certain motion. A motion control is to make a posture of a robot stable by eliminating occurring disturbances while a robot is in operation using a pre-generated motion pattern. In this paper, a general method of motion pattern generation for a biped walking robot using universal approximator, learning neural networks, is proposed. Existing techniques are numerical methods using recursive computation and approximating methods which generate an approximation of a motion pattern by simplifying a robot's upper body structure. In near future other approaches for the motion pattern generations will be applied and compared as to be done.

• Journal of electromagnetic engineering and science
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• v.17 no.4
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• pp.186-190
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• 2017

Visible-near-infrared (VIS-NIR) spectroscopy is a fast and non-destructive method for analyzing materials. However, most commercial VIS-NIR spectrometers are inappropriate for use in various locations such as in homes or offices because of their size and cost. In this paper, we classified eight food powders using a portable VIS-NIR spectrometer with a wavelength range of 450-1,000 nm. We developed three machine learning models using the spectral data for the eight food powders. The proposed three machine learning models (random forest, k-nearest neighbors, and support vector machine) achieved an accuracy of 87%, 98%, and 100%, respectively. Our experimental results showed that the support vector machine model is the most suitable for classifying non-linear spectral data. We demonstrated the potential of material analysis using a portable VIS-NIR spectrometer.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.170-177
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• 2010

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.

• Proceedings of the KSPS conference
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• 2000.07a
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• pp.96-104
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• 2000

The Bodysonic system was invented on the basis of 'Bone Conduction Theory,' which states that people feel sounds with their whole body. The Bodysonic system is used for L2 (English) learning at Aichi Women's Junior College. In recent years we have developed some unique methodology related to use of the Bodysonic system. In Japan it is difficult for adult L2 learners to acquire the prosody of a foreign language. A language laboratory using the Bodysonic system has been suggested as one way to eradicate such adult L2 problems. The Bodysonic system changes sounds into vibrations. It makes it easy for learners to acquire the prosody of a foreign language because humans can convey information, through their tactile organs. In addition, this system was originally designed to make people relax, so it can also help minimize learner anxiety. The effect of Bodysonic vibrations on language learning has already been proven by some experiments. The Bodysonic system appears to be an ideal teaching method for adult to learn a foreign language.

• Annual Conference of KIPS
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• 2018.05a
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• pp.352-353
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• 2018

Many deep learning approaches are studied for face detection in these days. However, there is still a performance problem to run efficiently on devices with limited resources. Our method can enhance the detection speed by decreasing the number of scaling for detection methods that use many different scaling per image to detect the different size of faces. Also, we keep our deep learning model easy to implement and small as possible. Moreover, it can be used for other special object detection problems but not only for face detection.

• Journal of Engineering Education Research
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• v.24 no.6
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• pp.79-85
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• 2021

In a future society where cutting-edge science technology such as artificial intelligence becomes commonplace, the demand for talented people with basic knowledge of mathematics and science is expected to increase continuously, and the educational infrastructure suitable for the characteristics of future generations is still insufficient. In particular, in the case of students taking convergence courses including practical training, there was a problem in communication with the instructor. In this study, we looked at the current status of distance learning at domestic universities that came suddenly due to the global pandemic of COVID-19. In addition, a case study of the use of technology was conducted to facilitate the interaction between instructors and learners through case analysis of distance classes in convergence subjects. Therefore, this study aims to introduce the case of developing lecture contents for smooth convergence education in a non-face-to-face educational environment targeting the developed AI convergence courses and applying them to the education of enrolled students.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.275-279
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• 2022

The growth of technology nowadays has made many things easy for humans. These things are from everyday small task to more complex tasks. Such growth also comes with the illegal activities that are perform by using technology. These illegal activities can simple as displaying annoying message to big frauds. The easiest way for the attacker to perform such activities is to convenience user to click on the malicious link. It has been a great concern since a decay to classify URLs as malicious or benign. The blacklist has been used initially for that purpose and is it being used nowadays. It is efficient but has a drawback to update blacklist automatically. So, this method is replace by classification of URLs based on machine learning algorithms. In this paper we have use four machine learning classification algorithms to classify URLs as malicious or benign. These algorithms are support vector machine, random forest, n-nearest neighbor, and decision tree. The dataset that is used in this research has 36694 instances. A comparison of precision accuracy and recall values are shown for dataset with and without preprocessing.

• ETRI Journal
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• v.44 no.6
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• pp.915-924
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• 2022

In this paper, we present a two-stage scalable channel estimator (TSCE), a deep learning (DL)-based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting-edge neural network architecture, as a backbone for accurate estimation. For computation-efficient global feature extractions, we propose using window and window averaging-based self-attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL-based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL-based estimators.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.18-26
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• 2023

The use of holographic standardized patient (HSP) with mixed reality can provide students with the opportunity to enhance clinical reasoning skills. This is still relatively new, so there is a lack of guidelines for educators. Thus, we aimed to develop the instructional model of HSP-based education, for enhancing clinical reasoning skills in undergraduate healthcare education, which could systematically guide educators in designing and implementing HSP-based teaching and learning activities appropriately. Using a design and development research, a theoretically constructed initial mode in this study was iteratively improved and underwent validation through expert review and model usability test. Features of the model were discussed, along with theoretical and practical implications and suggestions for further research.