• 한국터널공학회:학술대회논문집
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• 한국터널공학회 2005년도 학술발표회 논문집
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• pp.251-258
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• 2005

In this study, a new concept for simulating a long-term mechanical degradation mechanism of shotcrete in tunnels has been proposed. In fact, it is known that the degradation takes place mainly by internal cracks and reduced stiffness, which results mainly from volume expansion of shotcrete and corrosion of cement materials, respectively. This degradation mechanism of shotcrete in tunnels appears similar to those of the most kinds of chemical reactions in tunnels. Therefore, the mechanical degradation induced by a kinds of chemical reaction was generalized and mathematically formulated in the framework of thermodynamics. The numerical model was implemented to a 3D finite element code, which can be used to simulate behaviour of shotcrete structures undergoing external forces as well as chemical degradation in time. A number of illustrative examples were given to show the feasibility of the model in tunnel designs with consideration of long-term degradation effect of shotcrete quantitatively for increase of long-term safety of tunnels.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1508-1520
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• 2018

In this paper, we propose an improved model to provide users with a better long-term prediction of waterworks operation data. The existing prediction models have been studied in various types of models such as multiple linear regression model while considering time, days and seasonal characteristics. But the existing model shows the rate of prediction for demand fluctuation and long-term prediction is insufficient. Particularly in the deep running model, the long-short-term memory (LSTM) model has been applied to predict data of water purification plant because its time series prediction is highly reliable. However, it is necessary to reflect the correlation among various related factors, and a supplementary model is needed to improve the long-term predictability. In this paper, convolutional neural network (CNN) model is introduced to select various input variables that have a necessary correlation and to improve long term prediction rate, thus increasing the prediction rate through the LSTM predictive value and the combined structure. In addition, a multiple linear regression model is applied to compile the predicted data of CNN and LSTM, which then confirms the data as the final predicted outcome.

• 보건의료산업학회지
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• 제12권4호
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• pp.155-172
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• 2018

Objectives: The purpose of this study was to investigate the influence of fall-related knowledge and fall prevention self-efficacy of care-givers working in long-term care hospitals on fall prevention behaviors and fall management behaviors for older adults with dementia. Methods: Participants were 125 care-givers working in long-term care hospitals. Data were collected with structured questionnaires from August 7 to 14, 2018. Data were analyzed by t-test, ANOVA, $Scheff{\dot{e}}$ test, Pearson's correlation coefficients, and multiple regression analysis using SPSS 18.0. Results: Fall prevention self-efficacy influence fall prevention behaviors(${\beta}=.55$, p<.001), while fall-related knowledge impacted fall management behaviors(${\beta}=.43$, p<.001). Conclusions: The results suggest that an education program for fall prevention of older adults with dementia in long-term care hospitals should focus on improving the fall-related knowledge and fall prevention self-efficacy of care-givers to increase both the fall prevention behaviors and fall management behaviors of care-givers.

• 한국노년학
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• 제36권4호
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• pp.1025-1036
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• 2016

본 연구는 노인요양시설의 사례관리자가 인지하는 조직 내 의사소통 만족과 서비스 질과의 관련성을 규명함으로써 사례관리에 있어 다양한 전문가로 구성된 팀원들간의 원활한 의사소통이 양질의 서비스의 전제조건임을 살펴보고자 하였다. 이를 위해 서울시와 경기도의 30인 이상 규모의 48개 법인시설에 종사하는 사례관리자 104명을 대상으로 설문조사를 진행하였으며, 기술분석 및 다중회귀분석을 통해 두 변인간의 관련성을 규명하고자 하였다. 연구결과 사례관리자가 인지하는 조직 내 의사소통의 만족도가 높을수록 제공하는 서비스의 질이 높은 것으로 평가하는 것으로 나타났다. 이러한 연구결과를 바탕으로 사례관리팀내의 의사소통을 원활히 하기 위한 방안과 다양한 사례관리모델 중 노인요양기관에서는'팀접근'모델이 보다 적합할 수 있음을 제언하였다.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.771-781
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• 2021

The purpose of this study is to identify major drivers of Myanmar's long-term economic growth and draw implications to implement development policies. This study investigated Myanmar, as the country is the most recently opened economy in Southeast Asia. This study conducted simulation analysis based on scenarios by applying World Bank's Long-Term Growth Model, Penn World Table 9.1, and World Development Indicator data. This study makes extensive use of LTGM and the LTGM-TFP extension to improve the validity of models for data calibration. This study confirms the validity of the model with data calibration and specifies scenarios for simulation analyses by setting the growth trajectory of Vietnam due to common geographical, political, and economic conditions. Main findings include that Myanmar's economic growth rate will continue to fall below 3% in 2040 without proper improvement of growth drivers. The results of this study also provide that total factor productivity growth and female labor participation are key factors for Myanmar's long-term economic growth. This study advises policymakers in Myanmar to strengthen human capital, which is crucial for total factor productivity growth in Myanmar's context and directly affects economic growth. Further, labor market policies to promote female labor participation is important to sustain economic growth.

• 가정∙방문간호학회지
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• 제29권1호
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• pp.70-81
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• 2022

Purpose: This study was performed to explore the trend of nursing research in the Korean long-term care system. Methods: Articles published between 2008 and 2021 were searched using the terms "long-term care system" and "nursing." Ninety-one articles were analyzed and classified into five categories according to research methods. Data were extracted through a systematic review process and underwent descriptive statistics and content analyses. Results: The most analyzed variable in the survey studies was job satisfaction. Many variables were classified into input and output factors using Donabedian's model. The content analysis showed that most suggestions were about improving the political regulation system. Conclusion: It is necessary to establish a research foundation to provide research funding and support to cultivate future nursing research in long-term care. Systematic improvement of research in nursing should be continuously pursued to revitalize nursing services, expand nursing service interventions, and improve management competency programs in nursing institutions.

• 보건행정학회지
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• 제32권3호
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• pp.258-271
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• 2022

The rapidly aging trend of Korea is a major factor that threatens the sustainability of the long-term care insurance system. Therefore, looking at how Japan and Germany mitigated the financial burden when they managed similar long-term care insurance systems will provide important implications for improving the Korean system in the future. The study was conducted using the literature review method, and the "country" was set as a unit for the case analysis. The three countries selected are Korea, Japan, and Germany. Recently in Korea, the insurance premium rates of all subjects have been rapidly rising, which can exacerbate the issue of intergenerational equity. On the other hand, Japan has responded to the aggravating finances for long-term care insurance due to aging by raising coinsurance for selected groups like the wealthy elderly. Germany is selectively raising the insurance premium rates by additionally increasing the premium rate for childless recipients. A more preventive and quality-oriented care service plan can be promoted by referring to the recent changes in Japan and Germany. In addition, a more effective and selective increase in payment burden in Japan and Germany could be considered in response to a recent equity issue in Korea.

• Smart Structures and Systems
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• 제29권3호
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• pp.433-444
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• 2022

Concrete is a most utilized material in the construction industry that have main components. The strength of concrete can be improved by adding some admixtures. Evaluating the impact of fly ash (FA) and silica fume (SF) on the long-term compressive strength (CS) of concrete provokes to find the significant parameters in predicting the CS, which could be useful in the practical works and would be extensible in the future analysis. In this study, to evaluate the effective parameters in predicting the CS of concrete containing admixtures in the long-term and present a fitted equation, the multivariate adaptive regression splines (MARS) method has been used, which could find a relationship between independent and dependent variables. Next, for optimizing the output equation, biogeography-based optimization (BBO), particle swarm optimization (PSO), and hybrid PSOBBO methods have been utilized to find the most optimal conclusions. It could be concluded that for CS predictions in the long-term, all proposed models have the coefficient of determination (R²) larger than 0.9243. Furthermore, MARS-PSOBBO could be offered as the best model to predict CS between three hybrid algorithms accurately.

• 한국해양공학회지
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• 제25권4호
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• pp.59-65
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• 2011

In structural health monitoring (SHM) using electro-mechanical impedance signatures, it is a critical issue for extremely large structures to extract the best damage diagnosis results, while minimizing unknown environmental effects, including temperature, humidity, and acoustic vibration. If the impedance signatures fluctuate because of these factors, these fluctuations should be eliminated because they might hide the characteristics of the host structural damages. This paper presents a long-term SHM technique under an unknown noisy environment for tidal current power plant structures. The obtained impedance signatures contained significant variations during the measurements, especially in the audio frequency range. To eliminate these variations, a continuous principal component analysis was applied, and the results were compared with the conventional approach using the RMSD (Root Mean Square Deviation) and CC (Cross-correlation Coefficient) damage indices. Finally, it was found that this approach could be effectively used for long-term SHM in noisy environments.

• 가정과삶의질연구
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• 제25권1호
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• pp.29-43
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• 2007

Effectiveness of Long-term Group-counseling in Improving Emotional Intelligence and Prosocial Behavior in Preschooler The purpose of this study was to assess the effectiveness of long-term group-counseling in preventing children's maladjustment at school. for this study, six children were selected for an experimental group and another six for a control group. They were tested using the Emotional Intelligence Rating System and the Prosocial Behavior Skill Situations Measure for Preschool Level. In addition to quantitative analysis, a qualitative analysis was conducted to examine group processes and changes in each child. The experimental group participated insocio-drama, group art therapy, and game play therapy whereas the control group did not receive any treatment. In order to examine the impact of the intervention, pre-program tests and post-program tests were conducted. The results were as follows. First, the children's emotional intelligence was improved with group counseling. There was a significant difference in emotional intelligence between the experimental and the control groups. Second, children's prosocial behavior ability alsoimproved. There was a significant difference in social ability between the experimental and the control groups.