• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.39-48
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• 2022

The main purpose of the work is to analyze modern innovative educational practices in the field of culture and art and their effectiveness in the context of the spread of digitalization trends. The study used general scientific theoretical methods of analysis, synthesis, analogy, comparative, induction, deduction, reductionism, and a number of others, allowing you to fully understand the pattern of modern modernization processes in a long historical development and demonstrate how the rejection of the negativity of progress allows talented artists to realize their own potential. The study established the advantages and disadvantages of involving innovative technologies in the educational process on the example of European experience and outlined possible ways of implementing digitalization processes in Ukrainian institutions of higher education, formulated the main difficulties encountered by teachers and students in the use of technological innovation in the pandemic. The rapid development of digital technologies has had a great impact on the sphere of culture and art, both visual, scenic, and musical in all processes: creation, reproduction, perception, learning, etc. In the field of art education, there is a synthesis of creative practices with digital technologies. In terms of music education, these processes at the present stage are provided with digital tools of specially developed software (music programs for composition and typing of musical text, recording, and correction of sound, for quality listening to the whole work or its fragments) for training programs used in institutional education and non-institutional learning as a means of independent mastering of the theory and practice of music-making, as well as other programs and technical tools without which contemporary art cannot be imagined. In modern stage education, the involvement of video technologies, means of remote communication, allowing realtime adjustment of the educational process, is actualized. In the sphere of fine arts, there is a transformation of communicative forms of interaction between the teacher and students, which in the conditions of the pandemic are of two-way communication with the help of information and communication technologies. At this stage, there is an intensification of transformation processes in the educational industry in the areas of culture and art.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.87-95
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• 2022

Recently, with the development of smart technology, in medical information platform, patient's biometric data is measured in real time and accumulated into database, and it is possible to determine the patient's emergency situations. Medical staff can easily access patient information after simple authentication using a mobile terminal. However, in accessing medical information using the mobile terminal, it is necessary to study authentication in consideration of the patient situations and mobile terminal. In this paper, we studied on medical information platforms based on big data processing and edge computing for supporting automatic authentication in emergency situations. The automatic authentication system that we had studied is an authentication system that simultaneously performs user authentication and mobile terminal authentication in emergency situations, and grants upper-level access rights to certified medical staff and mobile terminal. Big data processing and analysis techniques were applied to the proposed platform in order to determine emergency situations in consideration of patient conditions such as high blood pressure and diabetes. To quickly determine the patient's emergency situations, edge computing was placed in front of the medical information server so that the edge computing determine patient's situations instead of the medical information server. The medical information server derived emergency situation decision values using the input patient's information and accumulated biometric data, and transmit them to the edge computing to determine patient-customized emergency situation. In conclusion, the proposed medical information platform considers the patient's conditions and determine quick emergency situations through big data processing and edge computing, and enables rapid authentication in emergency situations through automatic authentication, and protects patient's information by granting access rights according to the patient situations and the role of the medical staff.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.101-106
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• 2023

In this busy world actually stress is continuously grow up in research and monitoring social websites. The social interaction is a process by which people act and react in relation with each other like play, fight, dance we can find social interactions. In this we find social structure means maintain the relationships among peoples and group of peoples. Its a limit and depends on its behavior. Because relationships established on expectations of every one involve depending on social network. There is lot of difference between emotional pain and physical pain. When you feel stress on physical body we all feel with tensions, stress on physical consequences, physical effects on our health. When we work on social network websites, developments or any research related information retrieving etc. our brain is going into stress. Actually by social network interactions like watching movies, online shopping, online marketing, online business here we observe sentiment analysis of movie reviews and feedback of customers either positive/negative. In movies there we can observe peoples reaction with each other it depends on actions in film like fights, dances, dialogues, content. Here we can analysis of stress on brain different actions of movie reviews. All these movie review analysis and stress on brain can calculated by machine learning techniques. Actually in target oriented business, the persons who are working in marketing always their brain in stress condition their emotional conditions are different at different times. In this paper how does brain deal with stress management. In software industries when developers are work at home, connected with clients in online work they gone under stress. And their emotional levels and stress levels always changes regarding work communication. In this paper we represent emotional intelligence with stress based analysis using machine learning techniques in social networks. It is ability of the person to be aware on your own emotions or feeling as well as feelings or emotions of the others use this awareness to manage self and your relationships. social interactions is not only about you its about every one can interacting and their expectations too. It about maintaining performance. Performance is sociological understanding how people can interact and a key to know analysis of social interactions. It is always to maintain successful interactions and inline expectations. That is to satisfy the audience. So people careful to control all of these and maintain impression management.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.145-151
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• 2023

3D-CNN is one of the deep learning techniques for learning time series data. Such three-dimensional learning can generate many parameters, so that high-performance machine learning is required or can have a large impact on the learning rate. When learning dynamic hand-gestures in spatiotemporal domain, it is necessary for the improvement of the efficiency of dynamic hand-gesture learning with 3D-CNN to find the optimal conditions of input video data by analyzing the learning accuracy according to the spatiotemporal change of input video data without structural change of the 3D-CNN model. First, the time ratio between dynamic hand-gesture actions is adjusted by setting the learning interval of image frames in the dynamic hand-gesture video data. Second, through 2D cross-correlation analysis between classes, similarity between image frames of input video data is measured and normalized to obtain an average value between frames and analyze learning accuracy. Based on this analysis, this work proposed two methods to effectively select input video data for 3D-CNN deep learning of dynamic hand-gestures. Experimental results showed that the learning interval of image data frames and the similarity of image frames between classes can affect the accuracy of the learning model.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.39-44
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• 2023

The creativity of thesis is that the significance of cyber security challenges in blockchain. The variety of enterprises, including those in the medical market, are the targets of cyberattacks. Hospitals and clinics are only two examples of medical facilities that are easy targets for cybercriminals, along with IoT-based medical devices like pacemakers. Cyberattacks in the medical field not only put patients' lives in danger but also have the potential to expose private and sensitive information. Reviewing and looking at the present and historical flaws and vulnerabilities in the blockchain-based IoT and medical institutions' equipment is crucial as they are sensitive, relevant, and of a medical character. This study aims to investigate recent and current weaknesses in medical equipment, of blockchain-based IoT, and institutions. Medical security systems are becoming increasingly crucial in blockchain-based IoT medical devices and digital adoption more broadly. It is gaining importance as a standalone medical device. Currently the use of software in medical market is growing exponentially and many countries have already set guidelines for quality control. The achievements of the thesis are medical equipment of blockchain-based IoT no longer exist in a vacuum, thanks to technical improvements and the emergence of electronic health records (EHRs). Increased EHR use among providers, as well as the demand for integration and connection technologies to improve clinical workflow, patient care solutions, and overall hospital operations, will fuel significant growth in the blockchain-based IoT market for linked medical devices. The need for blockchain technology and IoT-based medical device to enhance their health IT infrastructure and design and development techniques will only get louder in the future. Blockchain technology will be essential in the future of cybersecurity, because blockchain technology can be significantly improved with the cybersecurity adoption of IoT devices, i.e., via remote monitoring, reducing waiting time for emergency rooms, track assets, etc. This paper sheds the light on the benefits of the blockchain-based IoT market.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.3
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• pp.215-226
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• 2023

Severe wear of the anterior teeth facilitates the loss of anterior guidance, which protects the posterior teeth from wear during excursive movement. Additionally, when treating patients with collapsed occlusion due to multiple tooth loss and tooth wear, it is important to determine the presence of vertical dimension loss through accurate clinical and radiographic examinations and diagnostic wax-up. The patient of this case is a 44-year-old female patient who complained of overall tooth wear and loss of posterior teeth due to bruxism and clenching habits, visited the hospital with the address of restoring masticatory function and improving aesthetic appearance through prosthetic treatment. Through model analysis and diagnostic wax-up, an increase in vertical dimension was determined, and full mouth restoration with fixed prostheses was planned. The degree of adaptation to the vertical dimension was confirmed step by step using an occlusal splint designed with CAD (Computer aided design) software and 3-D (3-Dimensional) printed, and then restored with provisional restoration and after a 4-month adaptation period, the entire dentition was restored with metal ceramic crowns and implants. Through this procedure, satisfactory treatment results were obtained in terms of function and aesthetics.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.23-29
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• 2023

For given the importance of elementary school students developing the ability to solve problems using artificial intelligence (AI), problem-solving abilities should be developed using AI along with education to develop problem-solving abilities. Such students need a form that allows them to understand the concepts and principles of AI and to be easily educated in a fun way to understand basic understanding of how AI works. To this end, this study planned an 8-hour AI convergence program and operated based on self-driving cars, demonstrating that it was effective in improving elementary school students' problem-solving abilities, creativity, and AI understanding. As a result of operating the camp, students' understanding of AI was 3.56 (standard deviation 0.85), 4.00 (standard deviation 0.71), and t-value was -5.412 (p<0.001), indicating statistically improved understanding of AI, and high satisfaction and interest of students. In the future, it will be necessary to develop an educational program that allows elementary school students to devise their own ideas and create products to which AI models can be applied.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.57-68
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• 2023

With the technological development in the era of the 4th Industrial Revolution, technologies using HMD are being applied in various fields. HMD is especially useful in virtual reality fields such as AR/VR, and is very effective in receiving vivid impressions from users located in remote locations. According to these characteristics, the frequency of using HMD is increasing in the field related to collaboration. However, when HMD is applied to collaboration, communication between experts located in remote locations and workers located in the field is not smooth, causing various problems in terms of usability. In this paper, remote experts and workers in the field use HMD to solve various problems arising from collaboration, design/propose new types of HMD structures and functions that enable more efficient collaboration, and verify their usability using SUS evaluation techniques. As a result of the SUS evaluation, the new type of HMD structure and function proposed in this paper was 86.75points, which is believed to have greatly resolved the restrictions on collaboration and inconvenience in use of the existing HMD structure. In the future, when the HMD structure and design proposed in this paper are actually applied, it is expected that the application technology using HMD will expand rapidly.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.11-21
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• 2023

There have been many studies to improve the efficiency of the CG production process, but it was not easy to overcome the problem that it was difficult to check the result in the middle of work and it took a lot of time for rendering. However, as the possibility of using Unreal Live Link, which can check the result in real-time, is increasing, expectations for improving the efficiency of the production process are rising. This study analyzed the efficiency of the 3D animation production process using Unreal Live Link. To this end, modeling, rigging, animation, and layout work were done in Maya, and the final output image sequence was rendered in Unreal Engine through Unreal Live Link. And the difference between this production process and the existing production process in which the final output image sequence is rendered in the 3D software itself was compared and analyzed. As a result of the analysis, unlike the traditional 3D animation production process, it was possible to check the final work result in real-time by proceeding with the work through a high-quality viewport screen, and it was found that the efficiency of work was maximized by deriving the final result through real-time screen capture. Recently, the use of game engines in the 3D animation and film industry is gradually increasing, and the efficiency of work is expected to be maximized if Unreal Live Link is used.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.