• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.61-74
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• 2019

In this study, the SPI (Standardized Precipitation Index) of meteorological drought and SDI (Streamflow Drought Index) of hydrological drought for 1, 3, 6, 9, and 12 months duration were estimated to analyse the characteristics of drought using rainfall and dam inflow data for Chungju dam ($6,661.8km^2$) with 31 years (1986-2016) and Boryeong dam ($163.6km^2$) watershed with 19 years (1998-2016) respectively. Using the estimated SPI and SDI, the drought forecasting was conducted using seasonal autoregressive integrated moving average (SARIMA) model for the 5 durations. For 2016 drought, the SARIMA had a good results for 3 and 6 months. For the 3 months SARIMA forecasting of SPI and SDI, the correlation coefficient of SPI3, SPI6, SPI12, SDI1, and SDI6 at Chungju Dam showed 0.960, 0.990, 0.999, 0.868, and 0.846, respectively. Also, for same duration forecasting of SPI and SDI at Boryeong Dam, the correlation coefficient of SPI3, SPI6, SDI3, SDI6, and SDI12 showed 0.999, 0.994, 0.999, 0.880, and 0.992, respectively. The SARIMA model showed the possibility to provide the future short-term SPI meteorological drought and the resulting SDI hydrological drought.

• The Journal of Korean Obstetrics and Gynecology
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• v.34 no.4
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• pp.46-61
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• 2021

Objectives: The purpose of this review is to overview the studies of traditional herbal medicine for chronic pelvic inflammatory disease. Methods: We searched relevant studies using seven databases (The Journal of Korean obstetrics & gynecology, National Digital Science Library (NDSL), Research Information Sharing Service (RISS), Oriental Medicine Advanced Searching Integrated System (OASIS), Pubmed, Cochrane, Chinese National Knowledge Infrastructure (CNKI)). Data retrieval was carried out on April 5, 2021 and the papers published from January 1, 2015 to March 31, 2021 were included. The risk of bias was assessed by using Cochrane's risk of bias tool. Results: 524 studies were searched in domestic and foreign databases, and 7 studies were finally selected. In all studies, the treatment group was treated with oral traditional herbal medicine and the control group was treated with western medicine. Although the evaluation index was slightly different for each study, all studies used total efficacy rate index. In all 7 studies, the treatment group was more effective than the control group. Conclusions: Traditional herbal medicine can be an effective option in treating chronic pelvic inflammatory disease. Further high quality studies which include large number should be carried out to confirm the evidence and safety of traditional herbal medicine treatment.

• Health Policy and Management
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• v.32 no.2
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• pp.125-136
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• 2022

The costliness index (CI) is an index that is used in various ways to improve the quality of medical care and the management of appropriate treatment in medical institutions. However, the current calculation method for CI has a limitation in reflecting the actual medical cost of the patient unit because the outpatient and inpatient costs are evaluated separately. It is desirable to calculate the CI by integrating the medical cost into the episode unit. We developed an episode-based CI method using the episode classification system of the Centers for Medicare and Medicaid Services to the National Inpatient Sample data in Korea, which can integrate the admission and ambulatory care cost to episode unit. Additionally, we compared our new method with the previous method. In some episodes, the correlation between previous and episode-based CI was low, and the proportion of outpatient treatment costs in total cost and readmission rates are high. As a result of regression analysis, it is possible that the level of total medical costs of the patient unit in low volume medical institute and rural area has been underestimated. High proportion of outpatient treatment cost in total medical cost means that some medical institutions may have provided medical services in the ambulatory care that are ancillary to inpatient treatment. In addition, a high readmission rate indicates insufficient treatment service for inpatients, which means that previous CI may not accurately reflect actual patient-based treatment costs. Therefore, an integrated patient-unit classification system which can be used as a more effective CI indicator is needed.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Journal of Korean Biological Nursing Science
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• v.24 no.1
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• pp.17-25
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• 2022

Purpose: To determine the prognostic role of muscle area and muscle radiation attenuation in the erector spinae (ES) and multifidus (MF) muscles in patients undergoing gastrectomy. Methods: Patients with stage I-III gastric cancer undergoing gastrectomy were retrospectively enrolled in this study. Clinicopathologic characteristics were collected and analyzed. Both paraspinal muscle index of ES/MF muscles (PMI_EM) and paraspinal muscle radiation attenuation in the same muscles (PMRA_EM) were analyzed at the 3rd lumbar level using axial computed tomographic images. Cox regression analysis was applied to estimate overall survival (OS) and disease-free survival (DFS). Results: There was only a weak correlation between PMI_EM and PMRA_EM (r= 0.28). Multivariate Cox regression revealed that PMRA_EM, but not PMI_EM, was an important determinant of survival. PMRA_EM along with age, tumor-node-metastasis (TNM) stage, perineural invasion, and serum albumin level were significant determinants of both OS and DFS that constituted Model 1. Harrell's concordance index and integrated area under receiver operating characteristic curve were greater for Model 1 than for Model 2 (consisting of the same covariates as Model 1 except PMRA_EM) or Model 3 (consisting of only TNM stage). Conclusion: PMRA_EM, but not PMIEM, was an important determinant of survival. Because there was only a weak correlation between PMI_EM and PMRA_EM in this study, it was presumed that they were mutually exclusive. Model 1 consisting of age, TNM stage, perineural invasion, serum albumin level, and PMRA_EM was greater than nested models (i.e., Model 2 or Model 3) in predicting survival outcomes.

• Archives of Plastic Surgery
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• v.49 no.2
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• pp.207-214
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• 2022

Background Fellowship training is becoming more popular in plastic surgery, with over half of residents pursuing advanced training. Here, we investigate how clinical and research fellowship training impacts career trajectory and scholastic achievement in academic plastic surgery. Methods Plastic surgery faculty members, from programs recognized by the American Council of Academic Plastic Surgeons, were identified using institutional Web sites. Data extracted included faculty demographics, training history, academic positions, and research productivity. Continuous and categorical variables were compared using t-tests and chi-square, respectively. Results In total, 949 faculty members were included, with 657 (69%) having completed fellowship training. Integrated program residents were more likely to complete a fellowship when compared with independent residents (p < 0.0001). Fellowship trained faculty were more likely to have graduated from a higher ranked residency program, in terms of both overall and research reputation (p = 0.005 and p = 0.016, respectively). When controlling for years in practice, there was no difference found in number of publications, Hirsch index (h-index), or National Institutes of Health funding between faculty between the two cohorts (p > 0.05). In a subanalysis comparing hand, craniofacial, microsurgery, and research fellowships, those who completed a research fellowship had higher h-indices and were more likely to reach full professor status (p < 0.001 and p = 0.001, respectively). Fellowship training had no effect on being promoted to Chief/Chair of departments (p = 0.16). Conclusion Fellowship training is common among academic plastic surgeons. In this study, both clinical and research fellowships were associated with various aspects of academic success. However, fellowship training alone did not affect attainment of leadership positions.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.326-326
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• 2021

장기간에 걸쳐 넓은 지역에 대해 발생하는 가뭄을 예측하기위해 많은 학자들의 기술적, 학술적 시도가 있어왔다. 본 연구에서는 복잡한 시계열을 가진 가뭄을 전망하는 방법 중 시나리오에 기반을 둔 가뭄전망 방법과 실시간으로 가뭄을 예측하는 비시나리오 기반의 방법 등을 이용하여 미래 가뭄전망을 실시했다. 시나리오에 기반을 둔 가뭄전망 방법으로는, 3개월 GCM(General Circulation Model) 예측 결과를 바탕으로 2009년도 PDSI(Palmer Drought Severity Index) 가뭄지수를 산정하여 가뭄심도에 대한 단기예측을 실시하였다. 또, 통계학적 방법과 물리적 모델(Physical model)에 기반을 둔 확정론적 수치해석 방법을 이용하여 비시나리오 기반 가뭄을 예측했다. 기존 가뭄을 통계학적 방법으로 예측하기 위해서 시도된 대표적인 방법으로 ARIMA(Autoregressive Integrated Moving Average) 모델의 예측에 대한 한계를 극복하기위해 서포트 벡터 회귀(support vector regression, SVR)와 웨이블릿(wavelet neural network) 신경망을 이용해 SPI를 측정하였다. 최적모델구조는 RMSE(root mean square error), MAE(mean absolute error) 및 R(correlation Coefficient)를 통해 선정하였고, 1-6개월의 선행예보 시간을 갖고 가뭄을 전망하였다. 그리고 SPI를 이용하여, 마코프 연쇄(Markov chain) 및 대수선형모델(log-linear model)을 적용하여 SPI기반 가뭄예측의 정확도를 검증하였으며, 터키의 아나톨리아(Anatolia) 지역을 대상으로 뉴로퍼지모델(Neuro-Fuzzy)을 적용하여 1964-2006년 기간의 월평균 강수량과 SPI를 바탕으로 가뭄을 예측하였다. 가뭄 빈도와 패턴이 불규칙적으로 변하며 지역별 강수량의 양극화가 심화됨에 따라 가뭄예측의 정확도를 높여야 하는 요구가 커지고 있다. 본 연구에서는 복잡하고 비선형성으로 이루어진 가뭄 패턴을 기상학적 가뭄의 정도를 나타내는 표준강수증발지수(SPEI, Standardized Precipitation Evapotranspiration Index)인 월SPEI와 일SPEI를 기계학습모델에 적용하여 예측개선 모형을 개발하고자 한다.

• The Journal of Internal Korean Medicine
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• v.44 no.4
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• pp.603-620
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• 2023

Objectives: This study reviewed randomized controlled trials (RCTs) investigating the efficacy of herbal medicine on sleep disorders associated with Parkinson's disease and suggests a better research process. Methods: We searched for RCTs for herbal medicine treatments for sleep disorders related to Parkinson's disease on July 31, 2023 using eight databases (PubMed, Embase, the Cochrane library, China National Knowledge Infrastructure [CNKI], the Research Information Service System [RISS], Science ON, the Oriental Medicine Advanced Searching Integrated System [OASIS], and the Korea Citation Index [KCI]). Cochrane's risk of bias tool was used to assess the quality of the RCTs. Results: A total of 16 RCTs met all the inclusion criteria, and in most reports, the treatment group showed a significant improvement in sleep disorders compared to the control group. Total effective rate (TER), Pittsburgh Sleep Quality Index (PSQI), Unified Parkinson's Disease Rating Scale (UPDRS), TCM Symptom Score (TSS), Parkinson's Disease Sleep Scale (PDSS), etc., were used as evaluation indicators. Conclusion: Herbal medicine is a potential treatment for sleep disorders associated with Parkinson's disease. However, the selected RCTs were of poor quality, and it is necessary to perform more systematic studies.

• Journal of Digital Policy
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• v.3 no.2
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• pp.15-22
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• 2024

This study was conducted to identify the cause of turtle neck syndrome that occurs in a pharmacists and the relationship between the height and table height and to suggest a table height appropriate for height. By conducting correlation and regression analysis of the turtle neck index, NDI, and VAS. As a result of calculating, the relationship between the pharmacist's height and table height, which is good for preventing turtle neck, is less than about 65cm, and it was proven that the height of the table is a major factor in causing or worsening turtle neck syndrome. It is believed that further follow-up research is needed to determine whether the calculated through this paper is effective and can be applied to other occupational groups.

• Human Ecology Research
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• v.62 no.3
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• pp.517-530
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• 2024

This study aims to develop and validate a home economics education program focused on the consumer life area to enhance artificial intelligence (AI) literacy. To achieve this objective, a 10-session AI-consumer life integration education program was developed by analyzing literature on AI Literacy, AI curriculum, consumer education, and the home economics curriculum for the middle school consumer life area. The program's validity was assessed by nine teachers using a four-point Likert scale. The average scores for each item and the content validity index (CVI) were calculated. Based on expert feedback, the program was revised and improved accordingly. The expert validity assessment of the lesson plans, teaching materials and learning resources resulted in an average score of 3.78 for all items and an average CVI of 0.96. For the overall program, the expert validity assessment yielded an average score of 3.72 for all items and an average CVI of 0.97. Since the content validity index for all questions was above 0.78, the program demonstrated high validity across achievement standards integration, learning objectives, content and teaching methods, motivation, and volume areas. This confirms its effectiveness as an educational program for enhancing AI literacy. This study is significant in terms of defining and identifying the components of AI literacy, developing an AI-integrated program encompassing the entire consumer life area and confirming the suitability of the home economics curriculum for enhancing digital consumer competencies and promoting sustainable consumption. Additionally, it highlights the potential to integrate AI into the home economics and consumer life area.