• Research in Community and Public Health Nursing
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• v.33 no.2
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• pp.259-268
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• 2022

Purpose: In Cambodia, noncommunicable diseases (NCDs) account for 64% of all deaths. A lack of risk perception of NCDs leads to poor measures of their prevention and management. This study aimed to investigate Cambodians' risk perceptions of NCDs based on the health belief model. Methods: A cross-sectional design was used, and using convenience sampling, participants included 200 Cambodians aged 40 years or older. A face-to-face administered structured questionnaire was used to assess demographic characteristics, health behaviors, and risk perceptions of NCDs. Results: Of the constructs of NCD risk perception, perceived severity (88.2%) and benefits (86.3%) were high, but relative to these, perceived cues to action (64.1%), barriers (63.5%), and self-efficacy (58.1%) were low. Conclusion: It is important to improve perceived self-efficacy in government health promotion, outreach, and improvement programs and to reduce perceived barriers through medical tests either by facility-based delivery or via outreach health services in Cambodia.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.443-454
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• 2020

The purpose of this study is to propose a structural theoretical model that can explain the learning flow of online distance education participants and to clarify the structural causal relationship among related variables that affect the learning flow of cyber university learners. Study results found a modified final model with a statistically significant fit based on the structural research model proposed in this study explained the learning flow of cyber university learners. Second, as a result of verifying the relationship between learning motivation and learning flow of cyber university learners, it was found that intrinsic motivation had a significant positive effect on learning flow. Third, as a result of the empirical verification on the relationship between academic self-efficacy and learning flow of cyber university learners, it was found that academic self-efficacy had a significant effect on learning flow. Fourth, as a result of empirical verification on the relationship between self-directed learning and the learning flow of cyber university learners, it was found that the learner's self-directed learning ability had a significant effect on learning flow. Such research results can be used to suggest a strategic direction for successful settlement and diffusion of a new paradigm of online non-face-to-face distance education, which has recently attracted attention.

• Knowledge Management Research
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• v.25 no.1
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• pp.89-109
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• 2024

The development of digital technology has given rise to a new service model: self-service. This model introduces the concept of "digital shadow work", in which consumers conduct unpaid behind-the-scenes digital tasks instead of employees. While consumers are engaging in increasingly more digital shadow work in self-service environments, they are unaware of their unpaid labor. This raises concerns about consumer rights and businesses' long-term sustainability and health. This study aims to reveal the psychological awareness factors that influence consumers' decisions to engage in digital shadow work in self-service environments. This exploratory qualitative study utilizes a grounded theory approach and semi-structured interviews to reveal the psychological awareness factors that contribute to consumers' decision to engage in digital shadow work. By revealing the psychological awareness of decision-making factors, this study enhances consumer's understanding and awareness of digital shadow work, which helps increase their awareness of self-protection in the context of self-service technologies. Additionally, understanding consumers' decision-making psychology is crucial for non-face-to-face self-service technology companies and provides a theoretical basis for sustainable and healthy business development.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.103-110
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• 2011

A widely used 3D face reconstruction method, structure from motion(SfM), shows robust performance when frontal, left, and right face images are used. However, this method cannot reconstruct a self-occluded facial part correctly when only one side view face images are used because only partial facial feature points can be used in this case. In order to solve the problem, the proposed method exploit a constrain that is bilateral symmetry of human faces in order to generate bilateral facial feature points and use both input facial feature points and generated facial feature points to reconstruct a 3D face. For quantitative evaluation of the proposed method, 3D faces were obtained from a 3D face scanner and compared with the reconstructed 3D faces. The experimental results show that the proposed 3D face reconstruction method based on both facial feature points outperforms the previous 3D face reconstruction method based on only partial facial feature points.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.1
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• pp.103-116
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• 2022

The purpose of this study is to investigate the perception on video material making and the effect on science teaching ability after conducting non-face-to-face teaching material making activity for elementary pre-service teachers. This activity consisted two processes. One is that elementary pre-service teachers conduct inquiry, understand related science concepts, analyze science textbooks and then make video material. The other is that they watch video materials produced by colleagues. This study was conducted on 89 elementary pre-service teachers for 8 weeks. After this activity was completed, the perception on video material making and the effect on science teaching ability of elementary pre-service teachers were investigated, and the results were analyzed. In the process of making and watching non-face-to-face teaching materials, elementary pre-service teachers showed positive results in teaching-learning, video production, and emotion and attitude toward video material making. In addition, it was found that they improved their science teaching ability through this activity and were very satisfied with this activity. However, they also mentioned several disappointments such as exclusion of learners' right to self-determination, lack of various communication channels, and errors in content of materials. This suggests that if these problems are solved, non-face-to-face classes can also be a good form of class.

• Korean Journal of Adult Nursing
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• v.23 no.2
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• pp.111-122
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• 2011

Purpose: The aim on this study was to establish the validity, reliability and efficiency of a Pain Self-Report Scale for elderly with dementia and compare these results with an observational pain rating scale. Methods: Study subjects were 136 elderly with dementia who were residents in a nursing home, geriatric hospital, or day care center. The subject's pain was measured by five self-report scales and observational scale. DS-DAT (discomfort scale-dementia of the Alzheimer's type) was used for pain behavior observational measure. Cognitive state was assessed using the MMSE (Mini-Mental State Examination). Results: Observational rating correlated moderately with self-report (r=.225~.585, p<.05) and tended to underestimate pain intensity. Test-retest reliability was high for all five self-report scales, and the correlation between these scales was very strong (r=.735~.856, p<.05). Comprehension rate of VDS (verbal descriptor scale) was 88.3%, and NRS (numeric rating scale) 69.9%, FPS (face pain scale) 66.9%, HVAS (horizontal visual analog scale) and VVAS (vertical visual analog scale) 65.4%. Conclusion: Nurses should not apply observational scales routinely in demented patients as many of these are capable of reporting their own pain. Self-report, the highest standard of pain measurement can be reliably performed in a large proportion of demented elderly.

• The Research Journal of the Costume Culture
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• v.7 no.5
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• pp.68-79
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• 1999

The purposes of the study, based on the social comparison theory, were 1) to examine the body image and the body distortion of the late adolescent through the attitudinal and perceptual measurement of the body image and to examine the self-esteem, 2) to examine the difference of the clothing behaviors depending on the level of the body image, the body distortion and the self-esteem, 3) to examine the difference in the clothing behavior, the body image and the self-esteem according to sex. The sampling method was a convenient sampling and the subjects were 137 undergraduate students in Chungnam national University. The results of this study were as follows : The results of analysing the factors to the response of attitudinal body image emerged three factors (appearance interest, weight concern, and body satisfaction). The results of analysing the response of the clothing behavior showed four factors (fashion interest, psychological dependence of clothing, conformity to clothing, and exhibitionism of clothing). The positive group to the body image showed more interest in the fashion and had the tendency of depending on the clothing psychologically, and also showed that the group revealed much exhibitive attitude by using the clothing. The group of perceiving the face rather correctly tends to do the conformity behaviors, but the group distorting the shoulder width wider than tends to reveal more conformity behaviors. The group with the higher self-esteem had little interested in the fashion and also did the conformity behaviors slightly.

• Journal of Arbitration Studies
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• v.31 no.4
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• pp.119-136
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• 2021

Due to the restriction of movement caused by the Corona epidemic and the expansion of the "big face" through human distance, the "unmanned system" based on artificial intelligence and the Internet of Things has been widely used in modern life. "Self-driving," one of the transportation systems based on artificial technology, has taken the initiative in the transportation system as the spread of Corona has begun. Self-driving technology eliminates unnecessary contact and saves time and manpower, which can significantly impact current and future transportation. Accidents may occur, however, due to the performance of self-driving technology during transportation albeit the U.S. allows ordinary people to drive automatically through experimental operations, and the product liability law will resolve the dispute. Self-driving has become popular in the U.S. after the experimental stage, and in the event of a self-driving accident, product liability should be applied to protect drivers from complicated self-driving disputes. The purpose of this paper is to investigate whether disputes caused by defects in ordinary cars can be resolved through arbitration through U.S. precedents and to investigate whether disputes caused by defects in autonomous cars can be arbitrated.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.65-79
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• 2022

Non-face-to-face classes continue due to Covid-19. There have been e-learning classes since the past, but the difference is that the current non-face-to-face classes are blended classes that combine real-time and recording classes or combine face-to-face and non-face classes. It is also characterized by being able to self-filmed or choose various lecture platforms in a place other than a dedicated studio. The advantages of non-face-to-face classes can be learned beyond time and space, and repetitive viewing and learning speed can be adjusted. Greening classes have no time and place constraints, and real-time classes have the advantage of high communication effects with learners. Evaluating whether non-face-to-face classes provide sufficient quality compared to face-to-face classes or e-learning will be necessary if branded classes are considered for post Covid. In this paper, for the evaluation of the service quality of non-face-to-face classes, the essential attributes desired by the instructors were derived from the viewpoint of Kano quality attributes and a quality improvement plan was proposed. After expressing the degree of functions that non-face-to-face classes should have on the X-axis and the satisfaction of learners on the Y-axis, 23 quality attributes were classified into 6 quality dimensions. In addition, satisfaction coefficient, dissatisfaction coefficient, and customer satisfaction improvement index were derived. As a result, 50% of learners were satisfied with non-face-to-face classes, but the preference was slightly higher than satisfaction, suggesting the sustainability of non-face-to-face classes. In terms of the customer satisfaction improvement index, the ranking of attributes with the largest increase in satisfaction when improving class quality was as follows. Professors' quick answers to learners' questions, content that can fully explain the subject, what the professor explains easily, develop high-quality content that can be learned on mobile phones, fairness of attendance checks, and real-time classes should start on time.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.