• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.41-50
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• 2020

The consequences of wearing high heels can be different according to the heel height, gait speed, shoe design, heel base area, and shoe size. This study aimed to focus on the knee extension and flexion range of motion (ROM) during gait, which were challenged by wearing five different shoe heel types and two different self-selected gait speeds (comfortable and fast) as experimental conditions. Measurement standards of knee extension and flexion ROM were individually calibrated at the time of heel strike, mid-stance, toe-off, and stance phase based on the 2-minute video recordings of each gait condition. Seven healthy young women (20.7 ± 0.8 years) participated and they were asked to walk on a treadmill wearing the five given shoes at a self-selected comfortable speed (average of 2.4 ± 0.3 km/h) and a fast speed (average of 5.1 ± 0.2 km/h) in a random order. All of the shoes were in size 23.5 cm. Three of the given shoes were 9.0 cm in height, the other two were flat shoes and sneakers. A motion capture software (Kinovea 0.8.27) was used to measure the kinematic data; changes in the knee angles during each gait. During fast speed gait, the knee extension angles at heel strike and mid-stance were significantly decreased in all of the 3 high heels (p<0.05). The results revealed that fast gait speed causes knee flexion angle to significantly increase at toe-off in all five types of shoes. However, there was a significant difference in both the knee flexion and extension angles when the gait in stiletto heels and flat shoes were compared in fast gait condition (p<0.05). This showed that walking fast in high heels leads to abnormal knee ROM and thus can cause damages to the knee joints. The findings in this preliminary study can be a basis for future studies on the kinematic changes in the lower extremity during gait and for the analysis of causes and preventive methods for musculoskeletal injuries related to wearing high heels.

• Smart Media Journal
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• v.9 no.4
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• pp.81-90
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• 2020

Due to the recent economic development and the improvement of income level in China, the desire for quality medical services is increasing compared to the past. As an alternative to satisfy these needs, various applications using smart phones and the like are being developed. The new corona that occurred in December 2019 began to show great interest in non-face-to-face telemedicine services using smart phones due to the worldwide spread of the coronavirus. Therefore, in this study, a total of 200 people were surveyed on the top three mobile medical applications in China, and the data of 120 people who actually used medical applications were analyzed based on Venkatesh's UTAUT2 theory. A study was conducted on the intent to use and the factors affecting the in-law behavior. First, it has become clear that the interactive characteristics, expectations for effort, price value, interest in privacy, habits, and promotional conditions have a positive impact on the user's use. Second, it was investigated that the user's intention to use influences the behavior of use, and among the intentions of use, it was found that the mobilization characteristic expectation, hedonistic motivation, price value, habits, and promotion conditions affect the use behavior. Third, a study result was derived that the controlling variables such as gender, age, school age, and annual income do not affect the user's intention to use mobile medical applications as a controlling variable. Finally, due to the nature of mobile devices that use the Internet, various security vulnerabilities exist, and this can cause great damage or personal and social impact. Therefore, for the development of mobile medical services in China, it is necessary to re-establish a research model through comprehensive and in-depth considerations to supplement these problems in the future.

• Journal of Korean society of Dental Hygiene
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• v.22 no.1
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• pp.11-19
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• 2022

Objectives: The purpose of this study was to identify new variables that can enhance adult oral health behaviors by confirming the degree of adult e-health literacy, oral health knowledge, and oral health behaviors and examining their relevance. Methods: A self-reported questionnaire was filled out by 350 adults from June 22 to August 1, 2021. Data were analyzed using SPSS 23.0. independent t-test, one way ANOVA, the scheffé post-hoc test and the pearson correlation coefficients were reviewed, A hierarchical regression analysis was conducted. Results: Oral health behaviors according to general characteristics showed significant differences in gender, educational background, dental visit within 1 year, subjective oral health status, oral health interest, frequency of oral internet use, and reliability of internet oral health information. Also it was found that e-health literacy affects oral health behavior. Conclusions: In this study, e-health literacy, oral health knowledge, and oral health behavior were correlated and it was confirmed that e-health literacy had an effect on oral health behavior. In the future, it is necessary to develop a tool that can measure e-oral health literacy and to find a way to improve the oral health behavior of adults by using e-oral health literacy.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.13-24
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• 2022

In order to explore the context of fraudulent claims and the measures for preventing them targeting the long-term care institutions for the elderly, which is increasing every year in Korea, this study conducted the text mining analysis using the media report articles. The media report articles were collected from the news big data analysis system called 'BIG KINDS' for about 15 years from July 2008 when the Long-Term Care Insurance for the Elderly took effect, to February 28^th 2022. During this period of time, total 2,627 articles were collected under keywords like 'elderly care+fraudulent claims' and 'long-term care+fraudulent claims', and among them, total 946 articles were selected after excluding overlapped articles. In the results of the text mining analysis in this study, first, the top 10 keywords mentioned in the highest frequency in every section(July 1^st 2008-February 28^th 2022) were shown in the order of long-term care institution for the elderly, fraudulent claims, National Health Insurance Service, Long-Term Care Insurance for the Elderly, long-term care benefits(expenses), elderly care facilities, The Ministry of Health & Welfare, the elderly, report, and reward(payment). Second, in the results of the N-gram analysis, they were shown in the order of long-term care benefits(expenses) and fraudulent claims, fraudulent claims and long-care institution for the elderly, falsehood and fraudulent claims, report and reward(payment), and long-term care institution for the elderly and report. Third, the analysis of TF-IDF was similar to the results of the frequency analysis while the rankings of report, reward(payment), and increase moved up. Based on such results of the analysis above, this study presented the future direction for the prevention of fraudulent claims of long-term care institutions for the elderly.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.83-88
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• 2022

The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.155-163
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• 2022

In order to avoid the spread of Covid-19, outdoor activities are decreasing worldwide and the time spent at home is increasing. As physical activity declines, the number of people who feel bored, restless and immune deficient is increasing. As indoor life becomes more permanent, multiple approaches to home workout are becoming active. This paper examines how the Covid blue (boredom and social anxiety) produced in the no-touch era affects quality of life through the use of home training applications. Questionnaires were collected from Chinese people using a website dedicated to Chinese questionnaires, and finally 383 appropriate data were analyzed using SPSS24.0 and AMOS24.0. The research results showed that the actual experience of using home workout had a positive impact on quality of life. The higher the user's sense of social unease about being late in the untact, It was found that the higher the social anxiety perceived by users about the untact era, the higher the interactivity and exercise satisfaction with the home workout app. Home workout application can improve exercise satisfaction and quality of life, which are more positive effects beyond the result of resolving consumers' boredom. Therefore, it can be used as a channel for digital services.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.59-68
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• 2021

The purpose of this study is to develop a personality education tea culture therapy program to effectively improve juvenile delinquency prevention and social adaptation. In order to verify the effectiveness of the tea culture therapy program through social intervention, we analyzed whether there were significant differences in the scores of social characteristics such as self-efficacy, self-control, and interpersonal relationships of juvenile detention students before and after participating in the program. Ten juvenile detention students between the ages of 14 and 17 who were accommodated to a juvenile detention center in B city were selected as the experimental group for the study. The tea culture therapy program was conducted 10 times as a social intervention personality education for juvenile delinquents, and as a result, self-efficacy was found to have a pre-mean of 2.37 (SD 0.33) and a post-mean of 2.49 (SD 0.31), showing a significant difference (Z=-5.874. P=.000), self-control showed a significant difference with the pre-mean 2.06 (SD 0.20) and the post-mean of 2.16 (SD 0.19) (Z=-4.743, P=.001). The interpersonal relationship was found to have a significant difference, with a pre-mean of 1.90 (SD 0.32) and a post-mean of 2.15 (SD 0.21) (Z=-5.892, P=.000). The above results show that this program has a significant effect on improving social characteristics such as self-efficacy, self-control, and interpersonal relationships among juvenile detention students. Therefore, the tea culture therapy program developed in this study for personality education for juveniles can be used as a personality education program for various types of adolescents as well as in the field of correctional welfare in the future.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.63-70
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• 2022

This study is a study that collects and analyzes data through An autoethnographyon as one of method of qualitative research, through which researcher have experienced firsthand in the process of developmenting and counseling there a new concept professional mental health mobile service platform as a mental health social welfare expert. The results of this study are as follows.First, there are people in Korea who are directly exposed to mental health issues and need to receive professional medical services, but there are also quite a few members of the public who have a desire for general mental health services, although the level of therapeutic intervention is not required. Second, considering the characteristics of modern society and especially in the pandemic situation of infectious diseases such as COVID-19, more and more people are preferring various mental health service platforms using mobile devices. Third, all generations complain of mental health issues such as family problems, stress, interpersonal relationships, and occupations, and other mental health problems such as self-harm and suicide accidents are frequently mentioned in connection with mental disorders such as depression, anxiety disorder, addiction, and post-traumatic stress disorder. Fourth, youngth s were exposed to various mental health-related issues, and above all, they were complaining of serious mental health problems such as self-harm and suicide accidents. Fifth, in delivering professional mental health services, mental health experts with the ability also to provide professional services online through mobile devices are needed as well offline. Finally, based on the results of this study, policy and practical suggestions related to the provision of mental health services in the future, and directions for follow-up studies were suggested.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.35-43
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• 2022

Makeup is the most common way to improve a person's appearance. However, since makeup styles are very diverse, there are many time and cost problems for an individual to apply makeup directly to himself/herself.. Accordingly, the need for makeup automation is increasing. Makeup transfer is being studied for makeup automation. Makeup transfer is a field of applying makeup style to a face image without makeup. Makeup transfer can be divided into a traditional image processing-based method and a deep learning-based method. In particular, in deep learning-based methods, many studies based on Generative Adversarial Networks have been performed. However, both methods have disadvantages in that the resulting image is unnatural, the result of makeup conversion is not clear, and it is smeared or heavily influenced by the makeup style face image. In order to express the clear boundary of makeup and to alleviate the influence of makeup style facial images, this study divides the makeup area and calculates the loss function using HoG (Histogram of Gradient). HoG is a method of extracting image features through the size and directionality of edges present in the image. Through this, we propose a makeup transfer network that performs robust learning on edges.By comparing the image generated through the proposed model with the image generated through BeautyGAN used as the base model, it was confirmed that the performance of the model proposed in this study was superior, and the method of using facial information that can be additionally presented as a future study.