• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.125-138
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• 2023

The development of AI systems for radiation therapy is important to improve the accuracy, effectiveness, and safety of cancer treatment. The current system has the disadvantage of monitoring patients using CCTV, which can cause errors and mistakes in the treatment process, which can lead to misalignment of radiation. Developed the PMRP system, an AI automation system that uses depth cameras to measure patient's fine movements, segment patient's body into parts, align Z values of depth cameras with Z values, and transmit measured feedback to positioning devices in real time, monitoring errors and treatments. The need for such a system began because the CCTV visual monitoring system could not detect fine movements, Z-direction movements, and body part movements, hindering improvement of radiation therapy performance and increasing the risk of side effects in normal tissues. This study could provide the development of a field of radiotherapy that lags in many parts of the world, along with the economic and social importance of developing an independent platform for radiotherapy devices. This study verified its effectiveness and efficiency with data through phantom experiments, and future studies aim to help improve treatment performance by improving the posture correction mechanism and correcting left and right up and down movements in real time.

• Journal of the Korean Geosynthetics Society
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• v.22 no.3
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• pp.27-35
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• 2023

Ensuring the stability of visible structures during excavation works are extremely crucial. While the stability of the ground is analyzed through numerical calculations the during design phase, the conditions during construction often differ. Therefore, it is imperative to analyze the stability of the wall through measurements. The cost of measurements on the construction site is set at a very low unit price, which increases the risk of accidents involving retaining walls. In this study, we argue for the importance of automated or wireless system measurements of retaining walls, by estimating construction duration and accident costs through the analysis of hypothetical accident cases, and comparing these with measurement costs. In case of a major destruction during excavation work, the accident handling cost could be less than 5% of the total measurement budget. Therefore, increasing the measurement budget to prevent accidents in advance can be economically beneficial.

• Journal of Medicine and Life Science
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• v.18 no.3
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• pp.61-65
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• 2021

Although re-expansion pulmonary edema (RPE) is rare (incidence rate <1%), it is associated with a mortality rate of >20%; therefore, early diagnosis and treatment are important. We report a case of RPE following chest tube insertion in a patient with spontaneous pneumothorax. We have specifically focused on the mechanism underlying RPE and the possible etiology. An 82-year-old man with a history of chronic anemia, chronic obstructive pulmonary disease, diabetes mellitus, and hypertension was referred to the emergency department for management of recurrent right-sided pneumothorax. We performed emergency closed thoracostomy for suspected tension pneumothorax, which led to stabilization of the patient's vital signs; however, he coughed up frothy pink sputum accompanied by severe right-sided chest pain 30 min postoperatively. The patient showed new-onset right pulmonary consolidation on chest radiography, as well as desaturation, tachycardia, and tachypnea and was diagnosed with RPE. He was transferred to the intensive care unit for mechanical ventilation and supportive treatment using diuretics, ionotropic agents, and prophylactic antibiotics. RPE gradually resolved, and the patient was extubated 3 days after admission. He has not experienced recurrent pneumothorax or pulmonary disease for 4 months. We emphasize the importance of RPE prevention and that aggressive ventilator care and supportive treatment can effectively treat RPE following an accurate understanding of the underlying pathogenetic mechanisms and risk factors.

• The Journal of the Society of Stroke on Korean Medicine
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• v.7 no.1
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• pp.59-64
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• 2006

Objective : This study was aimed to investigated the warning signs and its relationship with the other characteristics in acute stroke patients. Methods : Three-hundred sixty three acute stroke patients were recuited in the oriental medical hospitals of 3 universities located in metropolitan region from October in 2005 to October in 2006. We evaluated their stroke type with brain MRI, their waring signs, and general characteristics such as age, sex, past history, risk factor, etc. Result : Of the 363 patient, 138(38%) patients were experience of warning signs. The frequency of Stress were found more in experience of warning signs than none of them. Warning signs were more common in Large Artery Atherosclerosis than in the other etiology. Conclusion : Although a concrete conclusion can hardly be drawn from this study, it reminds physicians of the importance of warning signs which their patients appeal. For the further investigation, it seems to be necessary to construct fundamental databases for stroke by increasing the number of patients and by examination into the etiology and location.

• Korean Journal of Veterinary Research
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• v.63 no.2
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• pp.17.1-17.12
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• 2023

Antimicrobial (AM) resistance is a growing threat in human and veterinary medicine, spreading across species and perceived as One-Health issue. Prudent use of AM products is essential in mitigating this risk in both human and veterinary medicine. Farm veterinarians, responsible for prescribing appropriate AM and offering advice to farmers on their proper usage, are regarded as key players in the livestock industry. An online survey of farm veterinarians (n = 1,531) was conducted to assess their educational experience, beliefs, current status of prescription, practical behavior, and self-efficacy regarding the prudent use of antimicrobials (PUA). The data from 170 respondents were analyzed using descriptive statistics, regression and mediation analysis. Participants chose AM based on their experiences, academic resources, and peer veterinarians. Approximately 77% did not routinely conduct antibiotic-susceptibility-test. Most participants believed in the importance of PUA and the role of veterinarians to reduce AM resistance, but they reported a lack of awareness among farmers and insufficient national support interfere with their practical behavior with regard to PUA. Half of the participants had PUA-education, and 78.6% reported that education had a positive impact on their behavior with PUA. Self-efficacy partly mediates the relationship between belief and behavior for PUA, which accounted for 23.77% of the total effect that beliefs have on behavior for PUA. The findings of the study show that enhancing veterinarians' abilities to practice and their self-efficacy through education tailored to the current status of farms can contribute to the reduction of AMs in the livestock sector.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.285-292
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• 2023

As various accidents have occurred in underground spaces, we aim to improve the quality validation standards and methods as specified in the Regulations on Producing Integrated Map of Underground Spaces devised by the Ministry of Land, Infrastructure and Transport of the Republic of Korea for a high-quality integrated map of underground spaces. Specifically, we propose measures to improve the quality assurance of pipeline-type underground facilities, the so-called life lines given their importance for citizens' daily activities and their highest risk of accident among the 16 types of underground facilities. After implementing quality validation software based on the developed quality validation standards, the adequacy of the validation standards was demonstrated by testing using data from two-dimensional water supply facilities in some areas of Busan, Korea. This paper has great significance in that it has laid the foundation for reducing the time and manpower required for data quality inspection and improving data quality reliability by improving current quality validation standards and developing technologies that can automatically extract errors through software.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.53-63
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• 2023

This study developed a cognitive impairment predictive model as one of the screening tests for preventing dementia in the elderly by using Automated Machine Learning(AutoML). We used 'Wearable lifelog data for high-risk dementia patients' of National Information Society Agency, then conducted using PyCaret 3.0.0 in the Google Colaboratory environment. This study analysis steps are as follows; first, selecting five models demonstrating excellent classification performance for the model development and lifelog data analysis. Next, using ensemble learning to integrate these models and assess their performance. It was found that Voting Classifier, Gradient Boosting Classifier, Extreme Gradient Boosting, Light Gradient Boosting Machine, Extra Trees Classifier, and Random Forest Classifier model showed high predictive performance in that order. This study findings, furthermore, emphasized on the the crucial importance of 'Average respiration per minute during sleep' and 'Average heart rate per minute during sleep' as the most critical feature variables for accurate predictions. Finally, these study results suggest that consideration of the possibility of using machine learning and lifelog as a means to more effectively manage and prevent cognitive impairment in the elderly.

• Korea Trade Review
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• v.48 no.2
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• pp.27-43
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• 2023

The maritime industry is playing an increasingly vital part in global economic expansion. Specifically, the Baltic Dry Index is highly correlated with global commodity prices. Hence, the importance of BDI prediction research increases. But, since the global situation has become more volatile, it has become methodologically more difficult to predict the BDI accurately. This paper proposes an integrated machine-learning strategy for accurately forecasting BDI trends. This study combines the benefits of a convolutional neural network (CNN) and long short-term memory neural network (LSTM) for research on prediction. We collected daily BDI data for over 27 years for model fitting. The research findings indicate that CNN successfully extracts BDI data features. On this basis, LSTM predicts BDI accurately. Model R2 attains 94.7 percent. Our research offers a novel, machine-learning-integrated approach to the field of shipping economic indicators research. In addition, this study provides a foundation for risk management decision-making in the fields of shipping institutions and financial investment.

• Journal of Environmental Health Sciences
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• v.49 no.6
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• pp.353-361
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• 2023

Background: Noise has been linked to an increased risk of various health issues, including stress, anxiety, insomnia, and cardiovascular disorders. However, research on the relationship between residential traffic noise and mental health in South Korea is limited. Objectives: This study aims to examine the correlation between regional traffic noise levels and mental health using an ecological study design. Methods: In this ecological study, all data were collected from the Korean Statistical Information Service. Traffic noise data in residential areas and the prevalence of mental health indices in 44 cities with noise monitoring stations were obtained. Pearson correlation coefficients were calculated to assess the relationship between regional traffic noise levels and mental health indices. Results: Daytime traffic noise levels were found to have a positive correlation with stress perception (r=0.428, p=0.004) and showed a borderline positive correlation with depressive symptom prevalence (r=0.273, p=0.073). In cities with airports, significant correlations was observed between 24-hour average noise levels and depressive symptoms (r=0.604, p=0.010), whereas this relationship was not observed in cities without airports (r=0.048, p=0.813). Multiple regression analysis, which adjusted for factors such as age, gender ratio, smoking, obesity, unemployment, urban size, and the presence of an airport, confirmed the relationship between 24-hour average noise levels and stress perception (beta=0.287, p=0.024). Conclusions: This study identified correlations between regional traffic noise levels and depressive symptoms or stress perception in adults, with a more pronounced effect in areas with airports. These findings suggest a potential impact of residential traffic noise on mental health, highlighting the importance of preventive measures like noise management in urban planning to promote mental well-being.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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• pp.428-442
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• 2023

In this study, we have a goal to develop usability evaluation guidelines for heuristic-based artificial intelligence-based Software as a Medical Device (SaMD) in the medical field. We conducted a gap analysis between medical hardware (H/W) and non-medical software (S/W) based on ten heuristic principles. Through severity assessments, we identified 69 evaluation domains and 112 evaluation criteria aligned with the ten heuristic principles. Subsequently, we categorized each evaluation domain into five types, including user safety, data integrity, regulatory compliance, patient therapeutic effectiveness, and user convenience. We proposed usability evaluation guidelines that apply the newly derived heuristic-based Software as a Medical Device (SaMD) evaluation factors to the risk management process. In the discussion, we also have proposed the potential applications of the research findings and directions for future research. We have emphasized the importance of the judicious application of AI technology in the medical field and the evaluation of usability evaluation and offered valuable guidelines for various stakeholders, including medical device manufacturers, healthcare professionals, and regulatory authorities.