• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.256-266
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• 2023

The purpose of this study is to investigate the relationship between stress and school life adaptation according to the degree of participation in physical education class and perception of middle school students. In order to achieve this research objective, the subjects of this study were sampled using cluster random sampling from male and female students attending middle schools in Gwangju Metropolitan City and Jeollanam-do in 2020. 150 males and 150 females, a total of 300 people were sampled. The statistical analysis used for data analysis was frequency analysis, exploratory factor analysis, reliability analysis, and multiple regression analysis using SPSS Windows 21.0 Version. The conclusions obtained in this study through data analysis by such methods and procedures are as follows. First, it was found that middle school students' participation in physical education classes and perceptions had a partial effect on stress. Second, it was found that the degree of participation and awareness of middle school students' physical education class had a partial effect on their adaptation to school life. Third, middle school students' stress was found to have a partial effect on school life adaptation.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.267-275
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• 2023

The purpose of this study is to investigate the influence of sports center members' lifestyles on participation promotion and choice behavior. To this end, more specifically, we intend to establish and clarify a hypothetical model based on the preceding studies of facilitating factors and factors that continue to participate according to the lifestyle of sports center members. In order to achieve this research purpose, the study subjects were set as the population of male and female adults over 20 who are using sports centers in Gwangju Metropolitan City and Jeollanam-do in 2021. As for the sampling method, the sample was extracted using cluster random sampling, and 300 people were used for the actual analysis, excluding 60 copies of double-entry and insincere or unreliable questionnaires. The survey tool was modified and supplemented according to this study based on the questionnaire that had been verified for reliability and validity in previous studies, and all questionnaire items were composed of a 5-point scale. The statistical analysis used for data analysis was frequency analysis, exploratory factor analysis, reliability analysis, and multiple regression analysis using SPSS Windows 21.0 Version. The conclusions obtained in this study through data analysis by such methods and procedures are as follows. First, according to the lifestyle of sports center members, participation promotion factors were found to have a partial influence. Second, according to the lifestyle of sports center members, the selection behavior was found to have a partial influence. Third, it was found that the participation promotion factors of sports center members partially affected the choice behavior.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1657-1673
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• 2023

With the advancement of information technology, criminals employ multiple cyberspaces to promote cybercrime. To combat cybercrime and cyber dangers, banks and financial institutions use artificial intelligence (AI). AI technologies assist the banking sector to develop and grow in many ways. Transparency and explanation of AI's ability are required to preserve trust. Deep learning protects client behavior and interest data. Deep learning techniques may anticipate cyber-attack behavior, allowing for secure banking transactions. This proposed approach is based on a user-centric design that safeguards people's private data over banking. Here, initially, the attack data can be generated over banking transactions. Routing is done for the configuration of the nodes. Then, the obtained data can be preprocessed for removing the errors. Followed by hierarchical network feature extraction can be used to identify the abnormal features related to the attack. Finally, the user data can be protected and the malicious attack in the transmission route can be identified by using the Wrapper stepwise ResNet classifier. The proposed work outperforms other techniques in terms of attack detection and accuracy, and the findings are depicted in the graphical format by employing the Python tool.

• Journal of Hospice and Palliative Care
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• v.25 no.4
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• pp.178-192
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• 2022

Purpose: This scoping review identified scientific evidence on basic human needs (BHNs) in the elderly receiving palliative care. Methods: Systematic searches were conducted using six electronic databases (PubMed, CINAHL, Scopus, Lilacs, IBECS, and Web of Science). The initial search resulted in 1,227 articles, of which 104 were identified as potentially relevant. Fifty-three articles that met the inclusion criteria were identified and included in the final analysis. Results: Using the three hierarchical dimensions of the BHN model, 17 needs were organised, with five in the psychobiological dimension, 10 in the psychosocial dimension, and two in the psychospiritual dimension. These needs reflect the importance of care with dignity and relief from suffering for the elderly in palliative care. Conclusion: Recognising impaired BHNs in elderly people receiving palliative care will contribute to better care plans for the elderly, considering the multiple bio-psycho-social-spiritual dimensions of BHNs. This review points to a predominance of psychosocial needs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1671-1686
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• 2022

Face manipulation tools represented by Deepfake have threatened the security of people's biological identity information. Particularly, manipulation tools with deep learning technology have brought great challenges to Deepfake detection. There are many solutions for Deepfake detection based on traditional machine learning and advanced deep learning. However, those solutions of detectors almost have problems of poor performance when evaluated on different quality datasets. In this paper, for the sake of making high-quality Deepfake datasets, we provide a preprocessing method based on the image pixel matrix feature to eliminate similar images and the residual channel attention network (RCAN) to resize the scale of images. Significantly, we also describe a Deepfake detector named Cascaded-Hop which is based on the PixelHop++ system and the successive subspace learning (SSL) model. By feeding the preprocessed datasets, Cascaded-Hop achieves a good classification result on different manipulation types and multiple quality datasets. According to the experiment on FaceForensics++ and Celeb-DF, the AUC (area under curve) results of our proposed methods are comparable to the state-of-the-art models.

• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.247-261
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• 2023

Purpose: This study investigates the relationship between service compensation, consumer sentiment and revisit intention for service recovery in the Chinese foodservice industry, and the moderating effect of employee authenticity. Methods: Data were collected from people who experienced eating out in a city located in central China, and the hypothesis was verified through multiple regression analysis and hierarchical regression analysis. Results: The results indicate that the specificity of compensation affects both positive and negative emotions of customers, and the activeness of compensation also influences positive emotions of customers. Also, employee autheticity moderates the effect of specificity of compensation on customers' positive emotions. Both positive and negative emotions of customers influences revisit intention. Conclusion: These results show that the role of service compensation is important in service recovery in the rapidly expanding Chinese foodservice industry. In addition, since the sincerity of employees plays an important role in maximizing the recovery effect in the process of service recovery, it suggests that it is important not only to improve services in the quantitative aspect but also in the qualitative aspect through employee training.

• Journal of the Korean Dietetic Association
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• v.29 no.4
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• pp.248-260
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• 2023

This study provides basic data when planning nutrition support for healthy aging by revealing the relationship between various symptoms in the elderly and nutrient intake. From the 8th National Health and Nutrition Examination Survey, data from senior citizens aged 65 years or older in 2021 were used, and answers on the depression prevalence, activity restrictions, complaints of discomfort when chewing, and nutrient intake were analyzed through SPSS multiple logistic regression analysis. In the case of depression, there was a significant effect on the intake of four of the 20 nutrients (water, protein, cholesterol, and vitamin E). When experiencing activity restrictions, the intake of eight of the 20 nutrients (phosphorus, magnesium, vitamin A, vitamin D, beta-carotene, retinol, thiamine, and niacin) was affected. When experiencing chewing discomfort, the intake of three of the 20 nutrients (fat, magnesium, and vitamin E) was affected. Elderly people who suffer from depression, activity restrictions, and discomfort with chewing are at risk of various nutrient deficiencies, and related studies need to be conducted.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.244-254
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• 2023

The purpose of the study is to determine the relationship between leisure sports activities among the elderly, wellness awareness, perceived freedom, and subjective well-being. In order to achieve the purpose of this study, the study subjects were selected as the population aged 65 or older who lived in the Gwangju Metropolitan City area in 2022 and engaged in leisure sports activities. As for the sampling method, samples were extracted using cluster random sampling. A total of 300 people, 150 male and 150 female, were sampled. The survey tool was modified and supplemented according to this study based on the questionnaire that had been verified for reliability and validity in previous studies, and all questionnaire items were composed of a 5-point scale. The statistical analysis used for data analysis was frequency analysis, exploratory factor analysis, reliability analysis, and multiple regression analysis using SPSS Windows 21.0 Version. First, it was found that the wellness perception of the elderly partially affects the perceived sense of freedom. Second, it was found that the wellness perception of the elderly partially affects psychological happiness. Third, the elderly's perceived sense of freedom was found to affect their subjective well-being. Considering these research results, in order to effectively improve the quality of life in old age, it is important to promote physical, mental, emotional, and social relationships through nature-friendly sports activities to improve subjective life motivation, satisfaction, and happiness. It can be said that it increases the sense of well-being.

• ETRI Journal
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• v.45 no.6
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• pp.1079-1089
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• 2023

Stroke is one of the leading causes of long-term disability worldwide, placing huge burdens on individuals and society. Further, automatic human activity recognition is a challenging task that is vital to the future of healthcare and physical therapy. Using a baseline long short-term memory recurrent neural network, this study provides a novel dataset of stretching, upward stretching, flinging motions, hand-to-mouth movements, swiping gestures, and pouring motions for improved model training and testing of stroke-affected patients. A MATLAB application is used to output textual and audible prediction results. A wearable sensor with a triaxial accelerometer is used to collect preprocessed real-time data. The model is trained with features extracted from the actual patient to recognize new actions, and the recognition accuracy provided by multiple datasets is compared based on the same baseline model. When training and testing using the new dataset, the baseline model shows recognition accuracy that is 11% higher than the Activity Daily Living dataset, 22% higher than the Activity Recognition Single Chest-Mounted Accelerometer dataset, and 10% higher than another real-world dataset.

• Asia pacific journal of information systems
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• v.32 no.3
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• pp.601-629
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• 2022

Social networking sites (SNSs) have become an essential part of people's lives. It is thus crucial to understand how individuals use these platforms. Previous literature has divided usage into numerous activities and then grouped them into dimensions to avoid excessive granularity. However, these categories have not been derived from a uniform theoretical background; consequently, these dimensions are dispersed, overlapping, and disconnected from each other. This study argues that "SNS usage" is a complex phenomenon consisting of multiple activities that can be grouped into dimensions under the umbrella of communication theories and these dimensions are related to each other in a particular multi-dimensional architecture. "SNS usage" is conceptualized as a third-order construct formed by "producing," "consuming," and "communicating." "Producing," in turn, is proposed as a second-order construct manifested by "commenting," "general information sharing," and "self-disclosure." The proposed model was assessed with data collected from 414 USA adult users and PLS-SEM technique. The results show empirical support for the theorized model. SNS providers now have this architecture that clarifies the role of each dimension of use, which will allow them to design effective strategies to encourage the use of these networks.