• Journal of Multimedia Information System
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• v.8 no.3
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• pp.159-166
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• 2021

COVID-19 has dramatically changed people's daily life. Wearing masks is considered as a simple but effective way to defend the spread of the epidemic. Hence, a real-time and accurate mask wearing detection system is important. In this paper, a deep learning-based mask wearing detection system is developed to help people defend against the terrible epidemic. The system consists of three important functions, which are image detection, video detection and real-time detection. To keep a high detection rate, a deep learning-based method is adopted to detect masks. Unfortunately, according to the suddenness of the epidemic, the mask wearing dataset is scarce, so a mask wearing dataset is collected in this paper. Besides, to reduce the computational cost and runtime, a simple online and real-time tracking method is adopted to achieve video detection and monitoring. Furthermore, a function is implemented to call the camera to real-time achieve mask wearing detection. The sufficient results have shown that the developed system can perform well in the mask wearing detection task. The precision, recall, mAP and F1 can achieve 86.6%, 96.7%, 96.2% and 91.4%, respectively.

• ETRI Journal
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• v.41 no.4
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• pp.494-505
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• 2019

In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.5
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• pp.804-824
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• 2021

This study qualitatively explored the case of users utilizing multiple accounts on one social network service to create their own multiple spaces and different personas. The purpose of the study was to understand the behavior of people who use multiple accounts to express their identity online using Carl Jung's personality theory. We used in-depth interviews and the Zaltman metaphor elicitation technique (ZMET), targeting 19 people in their 20s and 30s who use more than one personal account on Instagram. Creating a shared consensus map using the configuration concept of ZMET derived six personas in relation to Instagram accounts. The motivations for the respondents' self-presentation associated with their personas and self-presentation types shown on Instagram were analyzed in terms of persona and fashion and subdivided into five dimensions: relationship management strategic presentation, self-monitoring presentation, competence demonstration presentation, anonymous presentation, and persona-centered presentation. Each respondent's persona and self-presentation formed by the Instagram account was analyzed.

• Journal of Korean Public Health Nursing
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• v.36 no.2
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• pp.265-281
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• 2022

Purpose: Adolescence is a developmental period characterized by the rapid growth of the musculoskeletal system, which is important for maintaining correct posture. Incorrect posture, lack of exercise, and reduced physical activity can cause spine deformities and affect lifelong health. This study was designed to evaluate the application and effect of a program for improving adolescents' musculoskeletal health. Methods: A quasi-experimental pilot study was conducted with 13 male and 20 female middle and high school students, with an average age of 15.39 years. Their general characteristics and physical measurements were obtained. The program consisted of group exercises (60 minutes, once per week), gait pattern monitoring, and online communication. A paired t-test and Wilcoxon signed-rank test were used to examine the program's effect. Results: Overall posture habits improved, and the total musculoskeletal index decreased; however, these results were not statistically significant. Conclusions: The devised program was effective in improving musculoskeletal imbalance. Therefore, effective programs and health devices should be developed to help adolescents maintain correct posture and encourage and support continuous participation in such programs.

• Korean Journal of Occupational Health Nursing
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• v.30 no.4
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• pp.167-174
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• 2021

Purpose: This study aimed to identify how job stress and teaching efficacy impacted organizational commitment. Methods: Data were collected from 158 nursing professors via an online survey, from Jan to June 2019. Results: The study found that four factors affected the organizational commitment of nursing professors: i) type of nursing institution in which they are currently employed (β=-.16, p=.030), ii) position as an assistant professor (β=-.37, p=.012) and an associate professor (β=-.44, p=.002), iii) salary in the 50-59 million won range (β=.20, p=.024), and above 60 million won (β=.41, p<.001), and iv) professor's teaching efficacy (β=-.18, p<.016). Conclusion: To increase the organizational commitment of four-year university professors, job characteristics should be considered. In the case of lower positions and salaries, additional compensation and programs that increase school affiliation should be introduced. Teaching methods training, lecture evaluation monitoring programs, and clinical training may also improve teaching efficacy.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1277-1283
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• 2021

It is important for operators of poly-pipelines in petroleum industry to continuously monitor characteristics of transferred fluid such as its type and amount. To achieve this aim, in this study a dual energy gamma attenuation technique in combination with artificial neural network (ANN) is proposed to simultaneously determine type and amount of four different petroleum by-products. The detection system is composed of a dual energy gamma source, including americium-241 and barium-133 radioisotopes, and one 2.54 cm × 2.54 cm sodium iodide detector for recording the transmitted photons. Two signals recorded in transmission detector, namely the counts under photo peak of Americium-241 with energy of 59.5 keV and the counts under photo peak of Barium-133 with energy of 356 keV, were applied to the ANN as the two inputs and volume percentages of petroleum by-products were assigned as the outputs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4385-4399
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• 2021

The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput.

• Journal of Korean society of Dental Hygiene
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• v.23 no.4
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• pp.295-302
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• 2023

Objectives: In this study, existing knowledge and needs of childcare teachers for developing oral health education plans for infants and young children were investigated. Methods: From March to April 2023, an online questionnaire survey led to the collection of data from 150 childcare teachers. Data were analyzed using the SPSS 22.0 program. Results: Importance-Performance Analysis (IPA) revealed that importance and knowledge of oral health education, importance of oral health, and prevention of oral diseases were priority areas, and treatment, symptoms, and causes were priority areas that needed improvement . According to the IPA on the importance of and demand for oral health education support, the importance and demand for an educational plan were both high. Expert education based on educational goals, information sharing, educational environment support, evaluation system, and monitoring was low in importance but high in demand. Conclusions: Oral care habits during infancy are important for maintaining oral health throughout life. Oral care practice should be improved by developing an oral health education plan for childcare teachers to implement.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.249-256
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• 2020

Historical construction health and safety (H&S) challenges, in terms of a range of resources and issues, continue to be experienced, namely design process-related hazards are encountered on site, workers are unaware of the hazards and risks related to the construction process and its activities, activities are commenced on site without adequate hazard identification and risk assessments (HIRAs), difficulty is experienced in terms of real time monitoring of construction-related activities, workers handle heavy materials, plant, and equipment, and ultimately the experience of injuries. Given the abovementioned, and the advent of Industry 4.0, a quantitative study, which entailed the completion of a self-administered questionnaire online, was conducted among registered professional (Pr) and candidate Construction H&S Agents, to determine the potential of Industry 4.0 to contribute to resolving the challenges cited. The findings indicate that Industry 4.0 technologies such as augmented reality (AR), drone technology, virtual reality (VR), VR based H&S training, and wearable technology /sensors have the potential to resolve the cited H&S challenges as experienced in construction. Conclusions include that Industry 4.0 technologies can finally address the persistent H&S challenges experienced in construction. Recommendations include: employer associations, professional associations, and statutory councils should raise the level of awareness relative to the potential implementation of Industry 4.0 relative to H&S in construction; case studies should be documented and shared; tertiary construction management education programmes should integrate Industry 4.0 into all possible modules, especially H&S-related modules, and continuing professional development (CPD) H&S should address Industry 4.0.

• Steel and Composite Structures
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• v.49 no.4
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• pp.407-417
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• 2023

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.