• PNF and Movement
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• v.19 no.2
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• pp.225-231
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• 2021

Purpose: This study was conducted to investigate the type of physical therapist response work and its intensity, along with the prolonged prevalence of COVID-19, to determine the impact on physical therapists' occupational stress and occupational burnout. Methods: An online survey was conducted with 118 physiotherapists and collected the participants' gender, final educational background, clinical work experience, workplace type, additional workload, and fatigue associated with COVID-19. After excluding one participant who submitted an incomplete questionnaire, 117 respondents were included in the final data. Results: Additional COVID-19-related workloads and response reliability for fatigue, occupational burnout, and occupational stress were shown to have Cronbach's alpha measures of 0.76, 0.89, and 0.87, respectively. Groups who had experienced a new epidemic in the past showed higher fatigue levels (3.06±0.94) than those groups who had no such experience (2.49±0.84; p < 0.05). Correlation analysis of COVID-19 work fatigue and occupational burnout scales showed a positive correlation (r = 0.19; p < 0.05). The regression of occupational burnout and occupational stress showed a regression model of Y = 20.00+0.43X₁ (X₁: job stress; p< 0.05) and an explanatory power of 24.8% with an adj.R² = 0.25. Conclusion: Based on the results, it is suggested that various institutions, such as medical institutions, educational institutions, and physiotherapists' associations, should seek ways to manage and alleviate physiotherapists' stress.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.301-307
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• 2022

Excessive work intensity and stress from customers visiting nail salons due to the increase in the frequency of visits and treatments to nail salons of modern people are negatively affecting the job psychology of nail salons. Accordingly, according to the need to prepare realistic and specific measures to increase job efficacy and job satisfaction through nail treatment techniques of nail salons, the perceived job efficacy and job This study was conducted based on the research model and hypothesis for satisfaction. As a result of the study, it was found that the nail gradation technique induces the highest job efficacy of nail polishers, and it was found that the more gel manicure techniques were applied, the higher the job satisfaction of nail polishers was. Through this study, it is expected that the complex application between various nail techniques will be possible and the coordinates of the job psychology of nail beauticians will be presented, and at the same time, it will serve as basic data for improving the work environment and developing new nail treatment techniques.

• Physical Therapy Rehabilitation Science
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• v.11 no.1
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• pp.8-15
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• 2022

Objective: Post stroke motor recovery is facilitated by the brain reorganization or the neuroplastic changes. The therapeutic approach mentioned in the current case is one of the approaches for enhancing motor recovery by stimulating the damaged neural networks directing the motor behaviour of a person. The aim of the present study was to establish the changes in the balance and gait pattern of an individual through multi target stimulation of areas of cerebral cortex by utilising multichannel trans cranial direct current stimulation (M-tDCS) in a sub-acute stroke survivor. Design: A Case Report Methods: The present patient was the participant of the trial (CTRI/2021/02/031044).The patient was intervened with M-tDCS (anodes over left primary motor cortex that is C3 point and left dorsolateral prefrontal cortex i.e., F3 point and cathodes over supraorbital areas, Intensity - 1.2mA) for the duration of 20 minutes along with turbo med extern - an AFO to facilitate ankle dorsi flexion and conventional physiotherapy rehabilitation. The Fugl-Meyer assessment lower extremity (FMA-LE), Berg Balance Scale (BBS), Wisconsin Gait Scale (WGS) and the Stroke Specific Quality of Life (SSQOL) measures were used for outcome assessment. Baseline assessment was done on day 0 followed by assessment on 10 and 20 post intervention. Results: Improvement was seen in all the tools i.e. (FMA -LE), BBS, SSQOL and WGS over the time period of 20 days. Conclusions: M-tDCS resulted in improvement in gait parameters, balance and motor functions of lower extremity of the patient.

• Journal of Preventive Medicine and Public Health
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• v.55 no.4
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• pp.360-370
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• 2022

Objectives: This study evaluated the response in Daegu, Korea to the first wave of the coronavirus disease 2019 (COVID-19) pandemic according to a public health emergency response model. Methods: After an examination of the official data reported by the city of Daegu and the Korea Centers for Disease Control and Prevention, as well as a literature review and advisory meetings, we chose a response model. Daegu's responses were organized into 4 phases and evaluated by applying the response model. Results: In phase 1, efforts were made to block further transmission of the virus through preemptive testing of a religious group. In phase 2, efforts were concentrated on responding to mass infections in high-risk facilities. Phase 3 involved a transition from a high-intensity social distancing campaign to a citizen participation-based quarantine system. The evaluation using the response model revealed insufficient systematic preparation for a medical surge. In addition, an incorporated health-related management system and protection measures for responders were absent. Nevertheless, the city encouraged the participation of private hospitals and developed a severity classification system. Citizens also played active roles in the pandemic response by practicing social distancing. Conclusions: This study employed the response model to evaluate the early response in Daegu to the COVID-19 pandemic and revealed areas in need of improvement or maintenance. Based on the study results, creation of a systematic model is necessary to prepare for and respond to future public health emergencies like the COVID-19 pandemic.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1242-1242
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• 2022

Annually, several construction workers fall ill, are injured, or die due to heat-related exposure. The prevalence of work-related heat illness may rise and become an issue for workers operating in temperate climates, given the increase in frequency and intensity of heatwaves in the US. An increase in temperature negatively impacts physical exertion levels and mental state, thereby increasing the potential of accidents on the job site. To reduce the impact of heat stress on workers, it is critical to develop and implement measures for monitoring physical exertion levels and mental state in hot conditions. For this, limited studies have evaluated the utility of wearable biosensors in measuring physical exertion and mental workload in hot conditions. In addition, most studies focus solely on male participants, with little to no reference to female workers who may be exposed to greater heat stress risk. Therefore, this study aims to develop a process for objective and continuous assessment of worker physical exertion and mental workload using wearable biosensors. Physiological data were collected from eight (four male and four female) participants performing a simulated drilling task at 92oF and about 50% humidity level. After removing signal artifacts from the data using multiple filtering processes, the data was compared to a perceived muscle exertion scale and mental workload scale. Results indicate that biosensors' features can effectively detect the change in worker physical and mental state in hot conditions. Therefore, wearable biosensors provide a feasible and effective opportunity to continuously assess worker physical exertion and mental workload.

• Journal of Animal Science and Technology
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• v.65 no.2
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• pp.365-376
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• 2023

Pig breeding management directly contributes to the profitability of pig farms, and pregnancy diagnosis is an important factor in breeding management. Therefore, the need to diagnose pregnancy in sows is emphasized, and various studies have been conducted in this area. We propose a computer-aided diagnosis system to assist livestock farmers to diagnose sow pregnancy through ultrasound. Methods for diagnosing pregnancy in sows through ultrasound include the Doppler method, which measures the heart rate and pulse status, and the echo method, which diagnoses by amplitude depth technique. We propose a method that uses deep learning algorithms on ultrasonography, which is part of the echo method. As deep learning-based classification algorithms, Inception-v4, Xception, and EfficientNetV2 were used and compared to find the optimal algorithm for pregnancy diagnosis in sows. Gaussian and speckle noises were added to the ultrasound images according to the characteristics of the ultrasonography, which is easily affected by noise from the surrounding environments. Both the original and noise added ultrasound images of sows were tested together to determine the suitability of the proposed method on farms. The pregnancy diagnosis performance on the original ultrasound images achieved 0.99 in accuracy in the highest case and on the ultrasound images with noises, the performance achieved 0.98 in accuracy. The diagnosis performance achieved 0.96 in accuracy even when the intensity of noise was strong, proving its robustness against noise.

• The Korean Journal of Pain
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• v.36 no.1
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• pp.84-97
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• 2023

Background: The concept of high-impact chronic pain (HICP) has been proposed for patients with chronic pain who have significant limitations in work, social life, and personal care. Recognition of HICP and being able to distinguish patients with HICP from other chronic pain patients who do not have life interference allows the necessary measures to be taken in order to restore the physical and emotional functioning of the affected persons. The aim was to reveal the risk factors and predictors associated with HICP. Methods: Patients with chronic pain without life interference (grade 1 and 2) and patients with HICP were compared. Significant data were evaluated with regression analysis to reveal the associated risk factors. Receiving operating characteristic (ROC) analysis was used to evaluate predictors and present cutoff scores. Results: One thousand and six patients completed the study. From pain related cognitive processes, fear of pain (odds ratio [OR], 0.92; 95% confidence interval [CI], 0.87-0.98; P = 0.007) and helplessness (OR, 1.06; 95% CI, 1.01-1.12; P = 0.018) were found to be risk factors associated with HICP. Predictors of HICP were evaluated by ROC analysis. The highest discrimination value was found for pain intensity (cut-off score > 6.5; 83.8% sensitive; 68.7% specific; area under the curve = 0.823; P < 0.001). Conclusions: This is the first study in our geography to evaluate HICP with measurement tools that evaluate all dimensions of pain. Moreover, it is the first study in the literature to evaluate predictors and cut-off scores using ROC analysis for HICP.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.65-78
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• 2023

In recent times, the frequency and intensity of natural disasters, such as heavy rains and typhoons, have been increasing due to the impacts of climate change. This has led to a rise in social and economic damages. Rural areas, in particular, possess limited disaster response capabilities due to their underdeveloped infrastructure and are highly vulnerable to flooding. Therefore, it is crucial to establish preventative and responsive measures. In this study, an Inventory-Based Flood Loss Estimation (IB-FLE) method utilizing high-resolution spatial information was developed for estimating flood-related losses in rural areas. Additionally, the developed approach was applied to a study area and compared with the Multidimensional Flood Damage Analysis (MD-FDA) method. Compared to the MD-FDA, the IB-FLE enables faster and more accurate estimation of flood damages and allows for the assessment of individual building and agricultural land losses using up-to-date information. The findings of this study are expected to contribute to the rational allocation of budgets for rural flood damage prevention and recovery, as well as enhancing disaster response capabilities.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.151-161
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• 2024

In this paper, we develop 'the Danger Map' of a workplace to identify risk and harmful factors by analyzing images of each process within the manufacturing plant site using artificial intelligence (AI). We proposed a system that automatically derives 'the risk and safety levels' based on the frequency and intensity derived from this Danger Map in accordance with actual field conditions and applies them to similar manufacturing industries. In particular, in the traditional evaluation method of manually evaluating the risk of a workplace using Excel, the risk level for each risk and harmful factor acquired from the video is automatically calculated and evaluated to ensure safety through the system and calculate the safety level, so that the company can take appropriate actions accordingly. and measures were prepared. To automate safety calculation and evaluation, 'Heinrich's law' was used as a model, and a 5X4 point evaluation scale was calculated for risky behavior patterns. To demonstrate this system, we applied it to a casting factory and were able to save 2 people the time and labor required to calculate safety each month.

• Journal of Wind Energy
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• v.14 no.4
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• pp.50-56
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• 2023

With the abnormal weather phenomena caused by global warming, the frequency and intensity of lightning strikes are increasing, and lightning accidents are becoming one of the biggest causes of failures and accidents in offshore wind turbines. In order to secure generator operation reliability, effective and practical measures are needed to reduce lightning damage. Because offshore wind turbines are tall structures installed at sea, the possibility of direct lightning strikes is very high compared to other structures, and the role of surge protection devices to minimize damage to the electrical and electronic circuits inside the wind turbine is very important. In this study, a varistor, which is a key element for a class 1 surge protection device for direct lightning protection, was developed. The current density was improved by changing the varistor composition, and the distance between the electrode located on the varistor surface and the edge of the varistor was optimized through a simulation program to improve the fabrication process. Considering the combined effects of heat distribution, electric field distribution, and current density on the optimized varistor surface, silver electrodes were formed with a gap of 0.5 mm. The varistor developed in this study was confirmed to have an energy tolerance of 10/350 ㎲, 50kA, which is a representative direct lightning current waveform, and good protection characteristics with a limiting voltage of 2 kV or less.