• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.4
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• pp.41-50
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• 2023

Purpose: As life expectancy increases and interest in oral health increases, the opportunity to visit the dentist increases. To provide safe dental care for elderly patients and accurately identify their needs. We aim to understand the impact of knowledge, image, and empathy for the elderly on communication skills. Research design, data, and methodology: This study conducted an online survey using a convenience sample of 201 dental hygienists working in dental hospitals and clinics from October 4 to October 6, 2023. The purpose of the survey was explained and consent was obtained in the research consent form before being conducted. Results: Differences in knowledge, image, empathy, and communication skills among the elderly include age, clinical experience, need for elderly-related education, and confidence in oral care in elderly patients with systemic diseases (p<0.05, p<0.01, p<0.001). The factor affecting communication skills toward the elderly was empathy (t=15.416(0.000^***)). Conclusions: Through this study, the communication skills with the elderly is a basic quality and attitude that dental hygienists must have. Therefore, it is essential to develop and implement empathy and communication skills training programs for dental hygienists, which can significantly contribute to fostering a positive trust-based relationship between elderly patients and dental professionals. This proactive measure is crucial in preparing for the upcoming era of an increasingly aged society.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.32-42
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• 2023

The paper describes the new approaches to the automated analysis of curricula according to the higher education standard. The analysis process is proposed to carry out in two ways: (a) the analysis of completeness and sufficiency of curricula according to the standard of higher education; (b) the comparison of curricula of the same qualification and specialty. The problem of improving the quality of university students' training launches the process of monitoring and analyzing educational curricula and their correspondence to the higher education standard. We developed the rules and methods to compare curricula. In addition, we implemented the automated system of curricula comparison. The paper reveals the use of these methods based on the analysis of the curriculum bachelor level of higher education "Informatics", specialty "Computer science", at the Faculty of Computer Science and Cybernetics of the Taras Shevchenko National University of Kyiv. The findings put towards the idea that the implementation of developed methods as well as the automated system of curricula analysis will improve the educational services by higher education institutions.

• Journal of Hospice and Palliative Care
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• v.26 no.4
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• pp.149-159
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• 2023

The Spiritual Care Guide in HospiceㆍPalliative Care is evidence-based and focuses on the universal and integral aspects of human spirituality-such as meaning and purpose, interconnectedness, and transcendence-which go beyond any specific religion. This guide was crafted to improve the spiritual well-being of adult patients aged 19 and older, as well as their families, who are receiving end-of-life care. The provision of spiritual care in hospice and palliative settings aims to assist patients and their families in finding life's meaning and purpose, restoring love and relationships, and helping them come to terms with death while maintaining hope. It is recommended that spiritual needs and the interventions provided are periodically reassessed and evaluated, with the findings recorded. Additionally, hospice and palliative care teams are encouraged to pursue ongoing education and training in spiritual care. Although challenges exist in universally applying this guide across all hospice and palliative care organizations in Korea-due to varying resources and the specific environments of medical institutions-it is significant that the Korean Society for Hospice and Palliative Care has introduced a spiritual care guide poised to enhance the spiritual well-being and quality of care for hospice and palliative care patients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3330-3344
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• 2023

This paper proposes an antenna performance prediction model in the autonomous driving radar manufacturing process. Our research work is based upon a challenge dataset, Driving Radar Manufacturing Process Dataset, and a typical AutoML machine learning workflow engine, Pycaret open-source Python library. Note that the dataset contains the total 70 data-items, out of which 54 used as input features and 16 used as output features, and the dataset is properly built into resolving the multi-output regression problem. During the data regression analysis and preprocessing phase, we identified several input features having similar correlations and so detached some of those input features, which may become a serious cause of the multicollinearity problem that affect the overall model performance. In the training phase, we train each of output-feature regression models by using the AutoML approach. Next, we selected the top 5 models showing the higher performances in the AutoML result reports and applied the ensemble method so as for the selected models' performances to be improved. In performing the experimental performance evaluation of the regression prediction model, we particularly used two metrics, MAE and RMSE, and the results of which were 0.6928 and 1.2065, respectively. Additionally, we carried out a series of experiments to verify the proposed model's performance by comparing with other existing models' performances. In conclusion, we enhance accuracy for safer autonomous vehicles, reduces manufacturing costs through AutoML-Pycaret and machine learning ensembled model, and prevents the production of faulty radar systems, conserving resources. Ultimately, the proposed model holds significant promise not only for antenna performance but also for improving manufacturing quality and advancing radar systems in autonomous vehicles.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.31-38
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• 2024

This study proposes a novel approach to enhancing the social inclusion and participation of individuals with developmental disabilities. Utilizing cutting-edge virtual reality (VR) technology, we designed and developed a metaverse simulator that enables individuals with developmental disabilities to safely and conveniently experience indoor handicapped handball sports. This simulator provides an environment where individuals with disabilities can experience and practice handball matches. For the modeling and animation of handball players, we employed advanced modeling and motion capture technologies to accurately replicate the movements required in handball matches. Additionally, we ported various training programs, including basic drills, penalty throws, and target games, onto XR (Extended Reality) devices. Through this research, we have explored the development of immersive assistive tools that enable individuals with developmental disabilities to more easily participate in activities that may be challenging in real-life scenarios. This is anticipated to broaden the scope of social participation for individuals with developmental disabilities and enhance their overall quality of life.

• Convergence Security Journal
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• v.23 no.5
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• pp.117-123
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• 2023

Recently, as the demand for Generative Artificial Intelligence (AI) and artificial intelligence has increased, the seriousness of misuse and abuse has emerged. However, intelligent CCTV, which maximizes detection of abnormal behavior, is of great help to prevent crime in the military and police. AI performs learning as taught by humans and then proceeds with self-learning. Since AI makes judgments according to the learned results, it is necessary to clearly understand the characteristics of learning. However, it is often difficult to visually judge strange and abnormal behaviors that are ambiguous even for humans to judge. It is very difficult to learn this with the eyes of artificial intelligence, and the result of learning is very many False Positive, False Negative, and True Negative. In response, this paper presented standards and methods for clarifying the learning of AI's strange and abnormal behaviors, and presented learning measures to maximize the judgment ability of intelligent CCTV's False Positive, False Negative, and True Negative. Through this paper, it is expected that the artificial intelligence engine performance of intelligent CCTV currently in use can be maximized, and the ratio of False Positive and False Negative can be minimized..

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.167-177
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• 2024

In nursing education, there has been efforts for enhancing the quality, with a growing interest in the utilization of digital technologies. In clinical training of nursing curriculum, the emphasis on digital technology is pronounced, as it has the potential to offer learners effective and accessible educational experience while enabling the integrated management of individualized learning outcomes. This study developed a digital nursing education platform, allowing educators and learners to select functionalities based on the educational content and characteristics of the learning tools. Additionally, the user interface was designed to facilitate learners' accurate understanding and execution of assigned tasks and objectives. The detailed design and implementation process of the platform are elaborated and then the validation of its usefulness was provided based on feedback from ten educators who are responsible for diverse subjects. The high usability of the digital nursing practicum education platform was confirmed, with potential implications for significant improvements in learner performance. The potential of this digital platform is to lead to innovative shifts in educational methodologies within the field of integrative nursing education.

• Anatomy and Cell Biology
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• v.56 no.1
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• pp.86-93
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• 2023

Age at death estimation has always been a crucial yet challenging part of identification process in forensic field. The use of human skeletons have long been explored using the principle of macro and micro-architecture change in correlation with increasing age. The clavicle is recommended as the best candidate for accurate age estimation because of its accessibility, time to maturation and minimal effect from weight. Our study applies pre-trained convolutional neural network in order to achieve the most accurate and cost effective age estimation model using clavicular bone. The total of 988 clavicles of Thai population with known age and sex were radiographed using Kodak 9000 Extra-oral Imaging System. The radiographs then went through preprocessing protocol which include region of interest selection and quality assessment. Additional samples were generated using generative adversarial network. The total clavicular images used in this study were 3,999 which were then separated into training and test set, and the test set were subsequently categorized into 7 age groups. GoogLeNet was modified at two layers and fine tuned the parameters. The highest validation accuracy was 89.02% but the test set achieved only 30% accuracy. Our results show that the use of medial clavicular radiographs has a potential in the field of age at death estimation, thus, further study is recommended.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.226-234
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• 2024

The frequent handover problem and playing ping-pong effects in 5G (5th Generation) ultra-dense networking cannot be effectively resolved by the conventional handover decision methods, which rely on the handover thresholds and measurement reports. For instance, millimetre-wave LANs, broadband remote association techniques, and 5G/6G organizations are instances of group of people yet to come frameworks that request greater security, lower idleness, and dependable principles and correspondence limit. One of the critical parts of 5G and 6G innovation is believed to be successful blockage the board. With further developed help quality, it empowers administrator to run many systems administration recreations on a solitary association. To guarantee load adjusting, forestall network cut disappointment, and give substitute cuts in case of blockage or cut frustration, a modern pursuing choices framework to deal with showing up network information is require. Our goal is to balance the strain on BSs while optimizing the value of the information that is transferred from satellites to BSs. Nevertheless, due to their irregular flight characteristic, some satellites frequently cannot establish a connection with Base Stations (BSs), which further complicates the joint satellite-BS connection and channel allocation. SF redistribution techniques based on Deep Reinforcement Learning (DRL) have been devised, taking into account the randomness of the data received by the terminal. In order to predict the best capacity improvements in the wireless instruments of 5G and 6G IoT networks, a hybrid algorithm for deep learning is being used in this study. To control the level of congestion within a 5G/6G network, the suggested approach is put into effect to a training set. With 0.933 accuracy and 0.067 miss rate, the suggested method produced encouraging results.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.101-110
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• 2024

Purpose : The purpose of this study provided an overview of the general status and recent intervention approaches in overseas research related to feeding problems in children with autism spectrum disorder (ASD). This review aims to explore interventions for feeding problems in order to provide higher quality follow-up research directions and implications, particularly focusing on providing recommendations for future research in the context of domestic studies. Methods : Analyzing studies published in international journals from 2017 to 2023. This review involved six selected articles, through Embase, Pubmed, RISS, KISS database search engine. A literature analysis that includes inclusion and exclusion criteria, six selected articles were examined. The literature analysis categorized the general status of the research and intervention approaches and treatment components into intervention, treatment settings and therapists, and dependent variables, respectively. Results : Among feeding intervention approaches, parent education interventions based on behavioral therapy had the highest proportion, followed by multidisciplinary interventions. To maintain the effectiveness of interventions over the long term and to generalize them to the home environment, parent education that utilizes parents as mediators is considered a crucial factor. The most commonly observed effects as dependent variables were changes in the consumption of disliked foods, health foods and alterations in feeding behavior. Conclusion : This study introduces various intervention approaches for addressing feeding problems in children with autism spectrum disorder (ASD), focusing on the positive effects demonstrated by active intervention research in abroad. Furthermore, it underscores the need for additional research in Korea to validate the efficacy of these feeding intervention methods. Lastly, the study outlines future research directions aimed at developing feeding programs to support children with ASD and their families coping with feeding issues.