Dong-Hyun Kim;Jun-Hee Cho;Jung-Hwa Lim;Bo-Kyung Kim
Journal of Oriental Neuropsychiatry
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v.34
no.3
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pp.163-179
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2023
Objectives: The purpose of this study was to provide evidence for the clinical effects of foot bath therapy for insomnia disorder through a systematic review and meta-analysis. Methods: Studies were selected from seven domestic and international literature databases. Data on diagnostic tools, pattern identification, sample size, intervention methods, outcome measurements, results, and adverse events were extracted. The quality of the selected literature was assessed using Cochrane's risk of bias (RoB) assessment tool. Results: A total of 11 studies were included in this study. The primary diagnostic tool for insomnia dis- order was the criteria for the diagnosis and therapeutic effect of diseases and syndromes in traditional Chinese medicine (CDTDSTCM), along with the Chinese classification of mental disorders-3 (CCMD-3). Treatment effects were mainly evaluated by the effective rate and the Pittsburgh Sleep Quality Index (PSQI). The meta-analysis results showed statistically higher effectiveness rates for treating insomnia disorder in the experimental groups receiving herbal medicine foot bath therapy with sleeping or herbal medication compared to the control group. The PSQI was lower in the treatment group receiving herbal medicine foot bath therapy with sleeping medication. The herbal materials used in herbal medicine foot bath therapy mainly included Radix Angelicae Sinensis, Polygonum Multiflorum, Ziziphi Spinosae Semen, Rhizoma Coptidis, Radix Salviae Miltiorrhizae, and Cortex Albizziae. The quality of the included studies was generally poor. Conclusions: This study found that foot bath therapy had clinical efficacy for treating insomnia disorder. The research findings could provide foundational evidence for establishing the clinical basis of foot bath therapy in the treatment of insomnia.
Yong Jig Lee;Dong Gil Han;Se Hun Kim;Jeong Su Shim;Sung-Eun Kim
Archives of Craniofacial Surgery
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v.24
no.1
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pp.18-23
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2023
Background: When performing reduction of zygomatic arch fractures, locating the inward portion of the fracture can be difficult. Therefore, this study investigated the discrepancy between the locations of the depression on the soft tissue and bone and sought to identify how to determine the inward portion of the fracture on the patient's face. Methods: We conducted a retrospective review of chart with isolated zygomatic arch fractures of type V in the Nam and Jung classification from March 2013 to February 2022. For consistent measurements, a reference point (RP), at the intersection between a vertical line passing through the end point of the root of the ear helix in the patient's side-view photograph and a transverse line passing through the longest horizontal axis of the external meatus opening, was established. We then measured the distance between the RP and the soft tissue depression in a portrait and the bone depression on a computed tomography (CT) scan. The discrepancy between these distances was quantified. Results: Among the patients with isolated zygomatic arch fractures, only those with a fully visible ear on a side-view photograph were included. Twenty-four patients met the inclusion criteria. There were four types of discrepancies in the location of the soft tissue depression compared to the bone depression: type I, forward and upward discrepancy (7.45 and 3.28 mm), type II, backward and upward (4.29 and 4.21 mm), type III, forward and downward (10.06 and 5.15 mm), and type IV, backward and downward (2.61 and 3.27 mm). Conclusion: This study showed that discrepancy between the locations of the depressions on the soft tissue and bone exists in various directions. Therefore, applying the transverse and vertical distances measured from a bone image of the CT scan onto the patient's face at the indicated RP will be helpful for predicting the reduction location.
Byungyoung Moon;Hyeonjin Hong;Dae-Hyeon Kim;Wonmin Lee;Sangmok Lee
Journal of the Society of Naval Architects of Korea
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v.60
no.1
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pp.38-47
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2023
According to the government policy of environmental regulations, interest of ship, which made with High-Density Polyethylene (HDPE) as a low-carbon and eco-friendly material, is growing as a substitute for the existing fishery boat hull materials such as FRP, aluminum, steel etc. However, regulations related to the production of HDPE ship are still quite incomplete. Even there are no regulations related to structural analysis. Therefore, in this study, structural analysis is carried out by applying different design loads for each international classification for 38ft class HDPE power boats, and the results are compared and analyzed. According to this study, although there is a correlation between the based pressure value and the analysis result value of each class regulation, it is not necessarily proportional. Also, This analysis result shows a difference not only depending on the size of design load, but also application range of the load, the pressure adjustment factor and section shape. However, the occurrence point and trend of the maximum stress values were quite consistent. It is hoped that the results of this study will be used when establishing HDPE ship structure analysis procedures and standards in the future.
Gi-Lim Kim;Hyein Kim;Hyung-Woo Seo;Ji-Hwan Yu;Jin-Won Son
Nuclear Engineering and Technology
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v.54
no.12
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pp.4809-4818
/
2022
The decommissioning project of a nuclear facility is a large-scale process that is expected to take about 15 years or longer. The range of risks to be considered is large and complex, then, it is expected that various risks will arise in decision-making by area during the project. Therefore, in this study, the risk family derived from the Decommissioning Risk Management (DRiMa) project was reconstructed into a decommissioning project risk profile suitable for the Kori Unit 1. Two criteria of uncertainty and importance are considered in order to prioritize the selected 26 risks of decommissioning project. The uncertainty is scored according to the relevant laws and decommissioning plan preparation guidelines, and the project importance is scored according to the degree to which it primarily affects the triple constraints of the project. The results of risks are divided into high, medium, and low. Among them, 10 risks are identified as medium level and 16 risks are identified as low level. 10 risks, which are medium levels, are classified in five categories: End state of decommissioning project, Management of waste and materials, Decommissioning strategy and technology, Legal and regulatory framework, and Safety. This study is a preliminary assessment of the risk of the decommissioning project that could be considered in the preparation stage. Therefore, we expect that the project risks considered in this study can be used as an initial data for reevaluation by reflecting the detail project progress in future studies.
Purpose: This study aimed to understand the general characteristics and biomarkers of inflammation in adult patients who visited the emergency department with fever and to determine whether the severity of clinical symptoms varies according to cancer diagnosis. Methods: Data were collected retrospectively from 4,002 adult patients with fever who visited the emergency department at a tertiary hospital from January 2018 to December 2018 using medical records. Results: On average, cancer patients were older than non-cancer patients (p < .001), and differences were observed between cancer and non-cancer patients in the origin of fever and biomarkers associated with inflammation. A higher proportion of cancer patients than non-cancer patients had a Korean Triage and Acuity Scale level of 1 to 3 (p < .001), and more cancer patients than non-cancer patients met two or more criteria for systemic inflammatory response syndrome (p = .001). More life-saving interventions in the emergency department were required in cancer patients than in non-cancer patients (p < .001), and cancer patients spent more time in the emergency department than non-cancer patients (p < .001). Conclusion: This study showed that the general characteristics and biomarkers of inflammation differed among adult patients with fever depending on cancer diagnosis. Furthermore, among adult patients with fever, cancer patients had more severe clinical symptoms than non-cancer patients. The results of this study are hoped to be helpful as a basis of nursing knowledge for adult patients with fever in the emergency department and as evidence for the classification of severity in patients with fever according to cancer diagnosis.
The purpose of this study is to identify trends in the application of artificial intelligence by analyzing upper extremity movement assessment and artificial intelligence convergence research using a systematic literature review method. The research was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Among the 380 articles searched in three databases, 8 articles were finally selected according to the selection and exclusion criteria. For the evaluation of upper extremity movement, motion performance evaluation, FMA, and ARAT were used. For quantification, data were extracted using various tools, and upper extremity movement classification, recovery prognosis prediction, and evaluation tool score were predicted using artificial intelligence. This study is meaningful in that it systematically reviewed studies that objectively evaluated upper extremity movement using artificial intelligence and identified the direction in which artificial intelligence is being applied. Based on this, the introduction of artificial intelligence technology in the assessment of upper extremity movements is expected to help objectively identify the intervention effect and the patient's recovery.
Purpose: The purpose of this study is to provide information for other journals as well as the continuous development of distribution science research by confirming the globalization performance of the Journal of Distribution Science (JDS), the main journal of KODISA. Research Design, Data, and Methodology: A total of 863 papers published in JDS from 2011 to 2021 searched by scienceON were divided into 4 periods and analyzed under the headings of submission system, standardity, collaboration, and degree of achievement of publication goals. SPSS 24.0 and R 4.1.1 package were used to perform the publication frequency analysis, crosstab-analysis, keyword frequency analysis, and LDA topic modeling were performed. In addition, trend analysis with weight applied to each word was performed. Results: It was found that the ratio of English-written papers, which is the indicator of a journal's starndardity, is continuously increasing, and the ratio of overseas authors, which is the indicator of collaboration, is also continuously increasing. It was confirmed through keyword trend analysis by period and LDA topic modeling results - which were weighted to confirm the degree of achievement of the journal's publication goal - that the articles published by the journal has been in agreement with monthly research topic proposed by JDS. Conclusion: By examining the five criteria for globalization, it can be concluded that JDS's efforts for globalization are achieving significant results and providing effective directions for other academic journals. However, in order for JDS to become a top academic journal, it was suggested that efforts should be made to establish a system for collaborative research by domestic and foreign authors, as well as to provide a clear definition for the monthly research topics and classification of sub-topics.
Journal of Korean Society of Industrial and Systems Engineering
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v.46
no.2
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pp.72-81
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2023
This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.
Journal of Korean Society of Disaster and Security
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v.16
no.2
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pp.33-47
/
2023
Under the "Act on Safety Control of Small Public Facilities (enacted in 2015)", each local government selects and conducts annual safety inspections for small public facilities. Among small public facilities, small bridges pose high risks and are heavily utilized by local residents, making them challenging to manage due to their large numbers and limited resources. Therefore, there is a need for a rational selection method that considers the management capacity of local governments, as well as the establishment of objective risk evaluation and maintenance planning for small hazardous facilities. In this study, we propose a selection method based on structural and functional classification of small bridges, considering the management capacity of local governments. Additionally, we present quantitative evaluation indicators for ten risk evaluation criteria, aiming to facilitate objective risk evaluation.
According to the World Health Organization, for medical schools to fulfill their obligation of social accountability, it is necessary for medical education, research, and service areas to ref lect the healthcare system's relevance, quality, cost-effectiveness, and equity. This study utilized Boelen and Heck's (1995) social accountability grid model to analyze the degree to which the Accreditation Standards of Korean Institute of Medical Education and Evaluation 2019 (ASK2019) standards apply the World Federation for Medical Education's (WFME) standards. The social accountability characteristics of the former were compared to those of the WFME, the Liaison Committee on Medical Education, and the Australian Medical Council. Experts with experience and certification in medical education and evaluation classified the ASK2019 standards according to the grid model, evaluated social accountability perspectives, and categorized them according to the process, content, and outcome. Of the 92 standards, 61 (66.30%) were selected as social accountability standards; these encompassed all areas. There was a particular focus on outcome-related areas, such as "mission and outcomes," "student assessment," "educational evaluation," and "continuous improvement." Education and quality were the most common (33, 54.11%), followed by 18 standards related to education and relevance. However, the standards on cost effectiveness and equity corresponding to education, research, and service were significantly insufficient. As a result of classification using a logic model, many criteria were incorporated into the process, producing results similar to those of international accreditation institutions. Therefore, to fulfill medical schools' social accountability, it is necessary to develop cost effectiveness and equity standards with reference to grid models and expand them beyond education to include research and service areas. Developing content and outcome standards is also required.
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