• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.237-250
• /
• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.

• International Journal of Computer Science & Network Security
• /
• v.22 no.9
• /
• pp.43-50
• /
• 2022

For high-quality education of the modern generation of students, forms of organizing the educational process and the latest methods of obtaining knowledge that differ from traditional ones are necessary. The importance of multimedia teaching tools is shown, which are promising and highly effective tools that allow the teacher not only to present an array of information in a larger volume than traditional sources of information, but also to include text, graphs, diagrams, sound, animation, video, etc. in a visually integrated form. Approaches to the classification of multimedia learning tools are revealed. Special features, advantages of multimedia, expediency of use and their disadvantages are highlighted. A comprehensive analysis of the capabilities of multimedia teaching tools gave grounds for identifying the didactic functions that they perform. Several areas of multimedia application are described. Multimedia technologies make it possible to implement several basic methods of pedagogical activity, which are traditionally divided into active and passive principles of student interaction with the computer, which are revealed in the article. Important conditions for the implementation of multimedia technologies in the educational process are indicated. The feasibility of using multimedia in education is illustrated by examples. Of particular importance in education are game forms of learning, in the implementation of which educational elements based on media material play an important role. The influence of the game on the development of attention by means of works of media culture, which are very diverse in form and character, is shown. The importance of the role of multimedia in student education is indicated. In the educational process of multimedia students, a number of educational functions are implemented, which are presented in the article. Recommendations for using multimedia are given.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.5
• /
• pp.423-429
• /
• 2022

This study is a study on the perceptions of pre-primary early childhood teachers on teaching and learning methods for infants and toddlers in the early childhood teacher training process. This is a mixed study using word cloud analysis and qualitative case analysis on the subject, focusing on literature research and understanding of pre-primary early childhood teachers' 'teaching and learning methods for infants and toddlers'. The purpose of this study was to find out the meaning of a early childhood teacher through thoughts on teaching and learning methods for infants, difficulties, points to be learned, teaching competency to be good as a teacher, and experiences for teaching professionalism. Through the results of this study, it is expected to find a way to increase their sense of efficacy on teaching and learning methods when conducting classes for young children in the future, and to provide basic data for improving the quality of early childhood education.

• Korean Journal of Remote Sensing
• /
• v.38 no.4
• /
• pp.395-409
• /
• 2022

The purpose of this study is to evaluate the classification performance and applicability when land cover datasets constructed for AI training are cross validation to other areas. For study areas, Gyeongsang-do and Jeolla-do in South Korea were selected as cross validation areas, and training datasets were obtained from AI-Hub. The obtained datasets were applied to the U-Net algorithm, a semantic segmentation algorithm, for each region, and the accuracy was evaluated by applying them to the same and other test areas. There was a difference of about 13-15% in overall classification accuracy between the same and other areas. For rice field, fields and buildings, higher accuracy was shown in the Jeolla-do test areas. For roads, higher accuracy was shown in the Gyeongsang-do test areas. In terms of the difference in accuracy by weight, the result of applying the weights of Gyeongsang-do showed high accuracy for forests, while that of applying the weights of Jeolla-do showed high accuracy for dry fields. The result of land cover classification, it was found that there is a difference in classification performance of existing datasets depending on area. When constructing land cover map for AI training, it is expected that higher quality datasets can be constructed by reflecting the characteristics of various areas. This study is highly scalable from two perspectives. First, it is to apply satellite images to AI study and to the field of land cover. Second, it is expanded based on satellite images and it is possible to use a large scale area and difficult to access.

• Journal of The Korean Association of Information Education
• /
• v.26 no.5
• /
• pp.307-315
• /
• 2022

The purpose of this study was to design a training program for pre-service elementary teachers, incorporating the concepts of extended reality technologies. This program contained the basic skills necessary for them to utilize in their future classrooms. To accomplish this, 12 undergraduate students of various majors enrolled in one of Korea's national universities of education were selected as research subjects. For a total of 6 times over 6 weeks, they participated in a training program learning the basic concepts of virtual, augmented, and mixed reality, as well as creating their own education software to use in simulated classes. To improve the quality of future research efforts, this study found it would be beneficial to: 1) expand the relevant support equipment, 2) provide students with preliminary, background knowledge of text-based programming, 3) introduce short-term, more intensive training, and 4) improve the survey methods for this research.

• International Journal of Computer Science & Network Security
• /
• v.23 no.11
• /
• pp.59-66
• /
• 2023

Text mining (TM) is most widely used to find patterns from various text documents. Cyber-bullying is the term that is used to abuse a person online or offline platform. Nowadays cyber-bullying becomes more dangerous to people who are using social networking sites (SNS). Cyber-bullying is of many types such as text messaging, morphed images, morphed videos, etc. It is a very difficult task to prevent this type of abuse of the person in online SNS. Finding accurate text mining patterns gives better results in detecting cyber-bullying on any platform. Cyber-bullying is developed with the online SNS to send defamatory statements or orally bully other persons or by using the online platform to abuse in front of SNS users. Deep Learning (DL) is one of the significant domains which are used to extract and learn the quality features dynamically from the low-level text inclusions. In this scenario, Convolutional neural networks (CNN) are used for training the text data, images, and videos. CNN is a very powerful approach to training on these types of data and achieved better text classification. In this paper, an Ensemble model is introduced with the integration of Term Frequency (TF)-Inverse document frequency (IDF) and Deep Neural Network (DNN) with advanced feature-extracting techniques to classify the bullying text, images, and videos. The proposed approach also focused on reducing the training time and memory usage which helps the classification improvement.

• Journal of Hospice and Palliative Care
• /
• v.27 no.2
• /
• pp.64-76
• /
• 2024

Purpose: End-of-life (EOL) care is a vulnerable period in an individual's life. Healthcare professionals (HPs) strive to balance the preservation of human life with respect for the patient's wishes. The aims of our study were to assess HPs' knowledge and perceptions of EOL care and to propose areas of improvement to improve the quality of care. Methods: We conducted a single-center, cross-sectional study involving HPs from a university hospital who encountered EOL care situations. We used a questionnaire divided into four sections: knowledge, practice, perception, and training. We calculated the rate of correct answers and the collective competence index. Results: Eighty-six questionnaires were analyzed, with 82.5% (71/86) completed by medical respondents and 17.5% (15/86) by paramedical respondents. Most of the respondents, 71.8% (51/71), were interns and residents. The study focused on palliative care, medical assistance in dying, aggressive medical treatment, and euthanasia, finding adequate knowledge in the first three areas. Respondents assigned to the intensive care unit and those with more than 8 years of experience had significantly higher correct answer rates than their counterparts. Seventy-five percent of respondents (65/86) reported feeling that they had little or no mastery of EOL care, primarily attributing this to insufficient training and the unavailability of trainers. Conclusion: Based on the findings of our study, which we believe to be the first of its kind in Tunisia, we can conclude that HPs possess an acceptable level of knowledge regarding EOL care. However, they require more exposure and training to develop expertise in this area.

• Journal of the Korean Institute of Gas
• /
• v.28 no.2
• /
• pp.84-92
• /
• 2024

This study applied the User-Centered Design(UCD) to develop effective VR safety training content for specific users. The UCD-based design was tailored to the VR, facilitating efficient design activities. The UCD process comprises key activities: deriving design concepts from user needs, designing with VR features, developing prototypes, conducting comprehensive evaluations with experts and users, and completing the finals. Unlike traditional UCD, this flexible approach allows iterative cycles, enhancing the quality and user satisfaction of VR safety training contents.

• Journal of Advanced Navigation Technology
• /
• v.28 no.4
• /
• pp.574-581
• /
• 2024

This study explores the usability of extended reality (XR) content tailored for production process training, with a focus on user experience. Participants engaged with extended reality training modules, and qualitative data was subsequently collected through interviews. These interviews evaluated the hardware, user interface, and overall user satisfaction. The analysis utilized python packages for keyword extraction and word cloud visualization, offering insights into user perceptions. The findings revealed that although the hardware was deemed comfortable, concerns were raised regarding its weight and heat emission. The interactive interface, which relies on hand tracking, encountered issues with recognition rates, leading to suggestions for alternative input methods. Users acknowledged extended reality's potential impact on industries like healthcare and education, sharing both positive and negative views on the technology. This research enhances our understanding of user responses and guides the future enhancement of extended reality content for industrial applications, aiming to improve its quality and practical usability

• International Journal of Industrial Entomology and Biomaterials
• /
• v.12 no.2
• /
• pp.95-100
• /
• 2006

Central Sericultural Research and Training Institute, Mysore have evolved several highly productive bivoltine hybrids which can produce international grade raw silk. Among them $CSR2{\times}CSR4,\;CSR2{\times}CSR5,\;CSR3{\times}CSR6,\;CSR17{\times}CSR16,\;CSR18{\times}CSR19$ and $CSR12{\times}CSR6$ are being popularized in the field. There is a minimum difference in their economic characters but they appear to differ in survival. Though they are productive under high input management conditions, they are very susceptible to different diseases under normal rearing practices. No systematic attempts have been made to test their susceptibility status / resistance. Thus the present study is a modest attempt to screen the above six productive bivoltine hybrids to two important pathogens viz., Bombyx mori Nuclear Polyhedrosis Virus (BmNPV) and Bombyx mori Infectious Flacherie Virus (BmIFV) along with existing hybrid, $KA{\times}NB4D2$ to assess their susceptibility / resistance. The results shows that the productive hybrid $CSR2{\times}CSR4$ is the most resistant to BmNPV and it is suggested by its highest $LC_{50}$ value followed by $CSR12{\times}CSR6,\;KA{\times}NB4D2,\;CSR3{\times}CSR6,\;CSR17{\times}CSR16,\;CSR18{\times}CSR19,\;CSR2{\times}CSR5$. Based on the $LC_{50}$ value and $LT_{50}$ values for BmIFV, the hybrid $KA{\times}NB4D2$ was found to be the most resistant (1st position) one followed by $CSR3{\times}CSR6$ (2nd position) $CSR2{\times}CSR$ (3rd position) and $CSR12{\times}CSR6$ (4th position) $CSR17{\times}CSR16$, $CSR18{\times}CSR19$ (5th position) and $CSR2{\times}CSR5$ being the least. The response of 7 bivoltine hybrids to both the pathogens BmNPV and BmIFV indicates that, the hybrids $CSR2{\times}CSR4$, $CSR12{\times}CSR6$ and $KA{\times}NB4D2$ were found to be the most resistant when compared to others. Further, $KA{\times}NB4D2$ being less productive hybrid with a shell ratio of 20.08%, the other two hybrids $CSR2{\times}CSR4$ (Cocoon shell ratio, 21.44%) and $CSR12{\times}CSR6$ (cocoon shell ratio, 23.45%) can be considered to be most productive with superior quality cocoon and resistant to both BmNPV and BmIFV pathogens. The overall study indicated that the hybrid $CSR2{\times}CSR5$ is the most susceptible hybrid to both the pathogens.