• Smart Structures and Systems
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• v.31 no.5
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• pp.469-483
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• 2023

The dynamic characteristics of wind turbine blades are usually monitored by contact sensors with the disadvantages of high cost, difficult installation, easy damage to the structure, and difficult signal transmission. In view of the above problems, based on computer vision technology and the improved YOLOv5 (You Only Look Once v5) deep learning model, a non-contact dynamic characteristic monitoring method for wind turbine blade is proposed. First, the original YOLOv5l model of the CSP (Cross Stage Partial) structure is improved by introducing the CSP2_2 structure, which reduce the number of residual components to better the network training speed. On this basis, combined with the Deep sort algorithm, the accuracy of structural displacement monitoring is mended. Secondly, for the disadvantage that the deep learning sample dataset is difficult to collect, the blender software is used to model the wind turbine structure with conditions, illuminations and other practical engineering similar environments changed. In addition, incorporated with the image expansion technology, a modeling-based dataset augmentation method is proposed. Finally, the feasibility of the proposed algorithm is verified by experiments followed by the analytical procedure about the influence of YOLOv5 models, lighting conditions and angles on the recognition results. The results show that the improved YOLOv5 deep learning model not only perform well compared with many other YOLOv5 models, but also has high accuracy in vibration monitoring in different environments. The method can accurately identify the dynamic characteristics of wind turbine blades, and therefore can provide a reference for evaluating the condition of wind turbine blades.

• Smart Structures and Systems
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• v.31 no.5
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• The korean journal of orthodontics
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• v.53 no.3
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• pp.194-204
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• 2023

Objective: To investigate sex-specific correlations between the dimensions of permanent canines and the anterior Bolton ratio and to construct a statistical model capable of identifying the sex of an unknown subject. Methods: Odontometric data were collected from 121 plaster study models derived from Caucasian orthodontic patients aged 12-17 years at the pretreatment stage by measuring the dimensions of the permanent canines and Bolton's anterior ratio. Sixteen variables were collected for each subject: 12 dimensions of the permanent canines, sex, age, anterior Bolton ratio, and Angle's classification. Data were analyzed using inferential statistics, principal component analysis, and artificial neural network modeling. Results: Sex-specific differences were identified in all odontometric variables, and an artificial neural network model was prepared that used odontometric variables for predicting the sex of the participants with an accuracy of > 80%. This model can be applied for forensic purposes, and its accuracy can be further improved by adding data collected from new subjects or adding new variables for existing subjects. The improvement in the accuracy of the model was demonstrated by an increase in the percentage of accurate predictions from 72.0-78.1% to 77.8-85.7% after the anterior Bolton ratio and age were added. Conclusions: The described artificial neural network model combines forensic dentistry and orthodontics to improve subject recognition by expanding the initial space of odontometric variables and adding orthodontic parameters.

• Physical Therapy Korea
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• v.30 no.2
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• pp.87-91
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• 2023

Most advanced countries that are members of the World Physiotherapy have established a 4-year education system or specialized graduate school system for physical therapists based on national standards. They have also expanded their laws and systems to provide physical therapists with the autonomy and independence to offer services in their clinics. However, compared with developed countries in North America and Europe, there are issues with the autonomy and independence of physical therapists in Korea related to national regulations. Social status and recognition of the profession are also lagging. Korea is expected to become a super-aged society by 2025. To reduce the financial burden of healthcare and welfare on the government, it is necessary to extend the time spent by older adults on independent activities and minimize their time spent using medical services. To achieve this goal and maximize the active life of older adults, a plan to efficiently use licensed physical therapists in the country should be prepared. Korea should increase the license utilization rate of physical therapists to reduce waste at the national level and increase the professional hope of the younger generations of physical therapists. To create a healthcare policy focusing on the use of physical therapy personnel, similar to that in advanced countries, it is necessary to unify educational systems and produce excellent physical therapists. Providing professional autonomy can help physical therapists develop a sense of job satisfaction. Outstanding talent will choose physical therapy as a profession if they can see hope for their future careers, and if physical therapy services in Korea are similar to those delivered in advanced countries, physical therapy in Korea can develop into a healthcare service that people desire.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.6
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• pp.103-110
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• 2016

The recent frequent cases of damage due to leakage of medical data and the privacy of medical patients is increasing day by day. The government says the Privacy Rule regulations established for these victims, such as prevention. Medical data guidelines can be seen 'national medical privacy guidelines' is only released. When replacing the image data between the institutions it has been included in the image file (JPG, JPEG, TIFF) there is exchange of data in common formats such as being made when the file is leaked to an external file there is a risk that the exposure key identification information of the patient. This medial image file has no protection such as encryption, This this paper, introduces a masking technique using a mosaic technique encrypting the image file contains the application to optical character recognition techniques. We propose pseudonymization technique of personal information in the image data.

• Journal of Ginseng Research
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• v.47 no.4
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• pp.583-592
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• 2023

Background: Alcohol is one of the most commonly used psychoactive drugs. Due to its addictive characteristics, many people struggle with the side effects of alcohol. Korean Red Ginseng (KRG) is a traditional herbal medicine that is widely used to treat various health problems. However, the effects and mechanisms of KRG in alcohol-induced responses remain unclear. Therefore, the purpose of this study was to investigate the effects of KRG in alcohol-induced responses. Methods: We investigated two aspects: alcohol-induced addictive responses and spatial working memory impairments. To determine the effects of KRG in alcohol-induced addictive responses, we performed conditioned place preference tests and withdrawal symptom observations. To assess the effects of KRG in alcohol-induced spatial working memory impairment, Y-maze, Barnes maze, and novel object recognition tests were performed using mice after repeated alcohol and KRG exposure. To investigate the potential mechanism of KRG activity, gas chromatography-mass spectrometry and western blot analysis were performed. Results: KRG-treated mice showed dose-dependent restoration of impaired spatial working memory following repeated alcohol exposure. Furthermore, withdrawal symptoms to alcohol were reduced in mice treated with KRG and alcohol. The PKA-CREB signaling pathway was activated after alcohol administration, which was reduced by KRG. However, the levels of inflammatory cytokines were increased by alcohol and decreased by KRG. Conclusion: Taken together, KRG may alleviate alcohol-induced spatial working memory impairments and addictive responses through anti-neuroinflammatory activity rather than through the PKA-CREB signaling pathway.

• Korea Journal of Hospital Management
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• v.28 no.2
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• pp.1-8
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• 2023

Purpose: This study was conducted to identify the impact of human rights sensitivity and patient rights awareness of first-year students in clinical practice on clinical practice adaptation and to prepare practical and systematic personality development program education alternatives to foster high-quality medical personnel. Method: As for the research method, an online survey of 155 medical and nursing students from two universities in G-do (76 medical students and 79 nursing students) was conducted, and the collected data were T-test, ANOVA, Scheffe test, Pearson's correlation coefficient and step-by-step multiple regression analysis using SPSS WIN/25.0. Findings: The results of the study are as follows. First, as a result of analyzing the differences in each variable according to general characteristics, human rights sensitivity had a significant impact on gender, patient rights recognition on personality type, and clinical practice adaptation had a significant impact on major selection motivation. Second, the factors affecting the adaptation of first-year college students to clinical practice had a significant impact on extroverted personality and patient rights perception among personality types (regression model results F=6.38 (p<).001), 24.2% explanatory power). Conclusion: This study suggests that education and policy efforts are needed to foster accurate awareness of human rights issues by developing flexible and flexible extracurricular activity programs in the operation of the curriculum to strengthen medical and nursing students' ability to adapt to clinical practice and improve awareness of human rights issues.

• Journal of Korean Society of Rural Planning
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• v.29 no.1
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• pp.29-35
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• 2023

Although Due to industrial development and urbanization, the number of schools closing due to a decrease in the school-age population is increasing due to the phenomenon of relocation from farming and fishing villages. Closing schools are used as social and cultural facilities, or they are used to generate income by providing education and experiences. Agro-healing is an activity that promotes psychological, social, and physical health by using rural resources. By reflecting the Agro-healing in the services operated by the closed school, the perception of the provision of the Agro-healing service was investigated as a way to provide a therapeutic service to visitors and to increase the utilization of the closed school. The questionnaire consisted of 10 questions, a total of 5 questions related to demographic information, a total of 5 questions related to the perception of agro-healing activities in closed school facilities. As a result, 347 people participated in the survey. The higher the awareness of agro-healing, the need for a agro-healing expert, the satisfaction with the use of rural closed school facilities, and the willingness to participate in agro-healing activities, the higher the awareness that the provision of agro-healing services was necessary by the state. Theses results are expected to be useful as basic to data to solve the diverse limitation in rural closed school and agro-healing activities.

• Journal of the Korean Society of Food Culture
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• v.21 no.2
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• pp.187-192
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• 2006

This study is to investigate the recognition and preference of tofu food among general consumers and housewives in order to develope new tofu menu. The questionnaires are consisted of general questions, style of dining out, frequency of dining, health status, preference of tofu, reason for prefer tofu. A total of 262 questionnaires were analyzed for statistical analysis. The statistical analysis was completed using SAS program (Version 8.2) for descriptive analysis and ${\chi}^2\;-test$. Main results of this study were as follows: Most of the respondents prefer Korean food, 70% of the respondents are general consumers while 73.5% of the respondents are housewives. The frequency of dining out was 1-2 times per week. The two groups bought pre-cooked food one to two times per week. Fourity seven percent of the general consumers and 50% of housewives did not like the taste of tofu due to plain flavor. The respondents overall preferred many different ways to prepare tofu dishes. The results also indicated that tofu dishes are used as side-dishes. Thirty three percent of house wives had tofu with miso soup and pan-fried tofu, while 29.6% of the general consumers had soft tofu stew. 34% of the general consumers preferred stuffed tofu with shrimp, while 35.5% of the housewives liked it. 17% of the general consumers liked grilled tofu with crab meat sauce while only 14.5% of the housewives preferred the menu. Tofu teriyaki was preferred among 8.2% of the general consumers while 13.2% of the housewives liked tofu teriyaki.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.191-199
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• 2023

In this paper, we propose a method to extract the features of five sensor-only facilities built as infrastructure for autonomous cooperative driving, which are from point cloud data acquired by LiDAR. In the case of image acquisition sensors installed in autonomous vehicles, the acquisition data is inconsistent due to the climatic environment and camera characteristics, so LiDAR sensor was applied to replace them. In addition, high-intensity reflectors were designed and attached to each facility to make it easier to distinguish it from other existing facilities with LiDAR. From the five sensor-only facilities developed and the point cloud data acquired by the data acquisition system, feature points were extracted based on the average reflective intensity of the high-intensity reflective paper attached to the facility, clustered by the DBSCAN method, and changed to two-dimensional coordinates by a projection method. The features of the facility at each distance consist of three-dimensional point coordinates, two-dimensional projected coordinates, and reflection intensity, and will be used as training data for a model for facility recognition to be developed in the future.