• Title/Summary/Keyword: Parameter Studies

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A Study on the Improvement of 3D Slope Modeling for BIM Designing Site Construction (택지조성공사 BIM을 위한 비탈면 3차원 모델링 효율화 방안에 관한 연구)

  • Kwon, Yongkyu;Ha, Dahyun;Kim, Jeonghwan;Seo, Joonwon;Shim, Ho
    • Korean Journal of Construction Engineering and Management
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    • v.22 no.4
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    • pp.29-40
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    • 2021
  • Recently, interest in Building Information Modeling (BIM) has increased globally, and 3D modeling is a start for the application of BIM at construction sites. However, while many studies have been conducted on the efficiency of 3D modeling focused on civil facilities, there is a lack of research on the earthwork BIM. In particular, since 3D slope often has complex shapes depending on the ground models, the efficiency method for 3D slope are needed. This study analyzed the interfaces and procedures of other software to find out what functions users need. Then the functions to enter intervals between 3D faces, select multiple ground models, and improve the interface are reflected on the developed system and is able to efficiently perform modeling with only five steps, and reduce the number of clicks and inputs. As a result of conducting the test to verify the efficiency, using the developed system made skilled users complete modeling at least 1.8 times faster and unskilled people at least 2.4 times faster than using other software. This is expected to perform 3D slope modeling more efficiently, as well as to contribute to the activation of future BIM adoption for housing construction projects.

The Effect of Perception of Transaction Fairness and Transaction Integrity on Reputation, Trust, and Transaction Cost Reduction in Business-to-Business Transactions (기업 간 거래에서 거래공정성과 거래진정성 지각이 평판, 신뢰, 거래비용감소에 미치는 영향)

  • Seo, Yeong-Bok;Park, Chan-Kwon
    • Korean small business review
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    • v.42 no.3
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    • pp.145-172
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    • 2020
  • This study shows that it is favorable for Korean companies to maintain fairness and authenticity trading relationship with trading companies. It suggests that a positive reputation can be secured, trust relationships can be built, and transaction costs can be reduced. For this purpose, research hypothesis was established, questionnaires were collected for domestic companies, and a hypothesis test was conducted. As a result of the research hypothesis test, the perception of transaction fairness and the perception of transaction authenticity have a positive effect on reputation, and the reputation has a positive effect on trust. Trust has a positive effect on the reduction of transaction costs, and reputation and trust play a role in the perception of transaction fairness and transaction authenticity and the reduction of transaction cost, and trust is a parameter between reputation and reduction in transaction cost. Do it. In order for sustainable management activities to be carried out for Korean companies, it is necessary to improve fairness and authenticity in business relations. It is important to have a positive reputation. It has been demonstrated that securing a positive reputation can develop into a trust relationship and ultimately lead to a decrease in transaction costs.

Calculation of optimal design flood using cost-benefit analysis with uncertainty (불확실성이 고려된 비용-편익분석 기법을 도입한 최적설계홍수량 산정)

  • Kim, Sang Ug;Choi, Kwang Bae
    • Journal of Korea Water Resources Association
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    • v.55 no.6
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    • pp.405-419
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    • 2022
  • Flood frequency analysis commonly used to design the hydraulic structures to minimize flood damage includes uncertainty. Therefore, the most appropriate design flood within a uncertainty should be selected in the final stage of a hydraulic structure, but related studies were rarely carried out. The total expected cost function introduced into the flood frequency analysis is a new approach for determining the optimal design flood. This procedure has been used as UNCODE (UNcertainty COmpliant DEsign), but the application has not yet been introduced in South Korea. This study introduced the mathematical procedure of UNCODE and calculated the optimal design flood using the annual maximum inflow of hydroelectric dams located in the Bukhan River system and results were compared with that of the existing flood frequency. The parameter uncertainty was considered in the total expected cost function using the Gumbel and the GEV distribution, and the Metropolis-Hastings algorithm was used to sample the parameters. In this study, cost function and damage function were assumed to be a first-order linear function. It was found that the medians of the optimal design flood for 4 Hydroelectric dams, 2 probability distributions, and 2 return periods were calculated to be somewhat larger than the design flood by the existing flood frequency analysis. In the future, it is needed to develop the practical approximated procedure to UNCODE.

Review of Remote Sensing Technology for Forest Canopy Height Estimation and Suggestions for the Advancement of Korea's Nationwide Canopy Height Map (원격탐사기반 임분고 추정 모델 개발 국내외 현황 고찰 및 제언)

  • Lee, Boknam;Jung, Geonhwi;Ryu, Jiyeon;Kwon, Gyeongwon;Yim, Jong Su;Park, Joowon
    • Journal of Korean Society of Forest Science
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    • v.111 no.3
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    • pp.435-449
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    • 2022
  • Forest canopy height is an indispensable vertical structure parameter that can be used for understanding forest biomass and carbon storage as well as for managing a sustainable forest ecosystem. Plot-based field surveys, such as the national forest inventory, have been conducted to provide estimates of the forest canopy height. However, the comprehensive nationwide field monitoring of forest canopy height has been limited by its cost, lack of spatial coverage, and the inaccessibility of some forested areas. These issues can be addressed by remote sensing technology, which has gained popularity as a means to obtain detailed 2- and 3-dimensional measurements of the structure of the canopy at multiple scales. Here, we reviewed both international and domestic studies that have used remote sensing technology approaches to estimate the forest canopy height. We categorized and examined previous approaches as: 1) LiDAR approach, 2) Stereo or SAR image-based point clouds approach, and 3) combination approach of remote sensing data. We also reviewed upscaling approaches of utilizing remote sensing data to generate a continuous map of canopy height across large areas. Finally, we provided suggestions for further advancement of the Korean forest canopy height estimation system through the use of various remote sensing technologies.

A comparative study of conceptual model and machine learning model for rainfall-runoff simulation (강우-유출 모의를 위한 개념적 모형과 기계학습 모형의 성능 비교)

  • Lee, Seung Cheol;Kim, Daeha
    • Journal of Korea Water Resources Association
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    • v.56 no.9
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    • pp.563-574
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    • 2023
  • Recently, climate change has affected functional responses of river basins to meteorological variables, emphasizing the importance of rainfall-runoff simulation research. Simultaneously, the growing interest in machine learning has led to its increased application in hydrological studies. However, it is not yet clear whether machine learning models are more advantageous than the conventional conceptual models. In this study, we compared the performance of the conventional GR6J model with the machine learning-based Random Forest model across 38 basins in Korea using both gauged and ungauged basin prediction methods. For gauged basin predictions, each model was calibrated or trained using observed daily runoff data, and their performance was evaluted over a separate validation period. Subsequently, ungauged basin simulations were evaluated using proximity-based parameter regionalization with Leave-One-Out Cross-Validation (LOOCV). In gauged basins, the Random Forest consistently outperformed the GR6J, exhibiting superiority across basins regardless of whether they had strong or weak rainfall-runoff correlations. This suggest that the inherent data-driven training structures of machine learning models, in contrast to the conceptual models, offer distinct advantages in data-rich scenarios. However, the advantages of the machine-learning algorithm were not replicated in ungauged basin predictions, resulting in a lower performance than that of the GR6J. In conclusion, this study suggests that while the Random Forest model showed enhanced performance in trained locations, the existing GR6J model may be a better choice for prediction in ungagued basins.

The Effects of Job Stress on Depression by Burnout in The Hospital Employees (의료기관 종사자의 직무스트레스가 정서적 소진, 우울에 미치는 영향)

  • Kyoungjin Song;Jeongwon Lee
    • Journal of Service Research and Studies
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    • v.12 no.3
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    • pp.26-44
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    • 2022
  • Job stress experienced during work has a positive effect on the organization, such as performance improvement, but if not properly managed, it can cause physical diseases such as digestive diseases and mental diseases such as depression and neurological diseases. If job stress persists for a long time, it causes emotional exhaustion and depression, which has a significant adverse effect on individuals and organizations, so proper management is essential. Therefore, in this study, a descriptive survey study was conducted using a self-report questionnaire method to find out the relationship between job stress, emotional exhaustion and depression of medical institution workers. As a result of the analysis, it was found that job stress of medical institution workers had a significant (+) effect on emotional exhaustion and depression, and emotional exhaustion of medical institution workers had a significant (+) effect on depression. Through this study, it was found that there was a significant relationship between job stress, emotional exhaustion, and depression of hospital employees, and that emotional exhaustion acts as a parameter in the relationship between job stress and depression. Considering that job stress of hospital employees causes adverse organizational effects, such as threatening workers' mental and physical health and causing deterioration in the quality of medical services, organizational efforts will be needed to relieve and properly manage job stress of hospital employees.

The Research Features Analysis of Leisure and Recreation based on Co-authors Network and Topic Model (공저자 네트워크 및 토픽 모델링 기반 여가레크리에이션 학술 연구 특징 분석)

  • Park, SungGeon;Park, Kwang-Won;Kang, Hyun-Wook
    • 한국체육학회지인문사회과학편
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    • v.57 no.2
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    • pp.279-289
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    • 2018
  • The purpose of this study is to investigate features of leisure and recreation scholarship study in The Korean Journal of physical education based on co-authors network and topic modeling through using Word Cloud and LDA Topic Modeling(Latent Dirichlet Allocation). The data collected for this study are 2,697 papers published online from January 2008 to March 2017 on the Korean journal of physical education. Respectively ordered analysis targets are the major author, author of correspondence, co-author 1, co-author 2, co-author n in related document to explore studies' trends using the 369 documents. As a result, the co-author network analysis result found that 451 were linked to the research network, on average researchers had 1.52 relationships and the average distance between researchers was 2.33. The Representative author's concentration of connection was ranked high in the order of the following, Lee. K. M., Hwang. S. H., H., Lee. C. S., and proximity centers were shown in Seo K. B., Han. J. H., Kim. K. J. Finally, parameter-centric features appeared in order of Lee. C. W. and Seo. K. B. was most actively connected between the researchers of the leisure-related academic papers. Future research needs discussions among scholars regarding the trend and direction of future leisure research.

Effect of Dance Sports Participation in Obesity Middle-Women on Body Composition and Blood Lipids: Meta-Analysis (비만 중년여성의 댄스스포츠 참여가 신체조성과 혈중지질에 미치는 효과: 메타분석)

  • NARUSE, MASAYO;An, Ki-Yong;Jeon, Justin Y
    • 한국체육학회지인문사회과학편
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    • v.55 no.3
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    • pp.613-626
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    • 2016
  • The purpose of this study was to identify the effect of dance sport participation on body composition and cardiometabolic parameters in obese middle aged women, by analyzing the current literature(2005-2015). The data from 9 studies were included in this systematic review and meta-analysis, and Comprehensive Meta Analysis(CMA) Version 2.0 was used for statistical analysis. A total of 197 middle aged women(intervention group: n=98, control group: n=99) were included in this analysis. An average duration of the dance sports intervention was 12.2 weeks, 3.13 session per week and 75 minutes per session. Significant reduction in body weight, body fat percent, triglyceride, low density lipoprotein LDL-Cholesterol and leptin were observed while significant increase in high density lipoprotein HDL-cholesterol was observed after the intervention. There were large effect size in percent body fat, total cholesterol, HDL-cholesterol and LDL-cholesterol while medium and small effect size were observed for triglyceride and body weight, leptin, insulin and glucose, respectively. In conclusion, dance sport participation resulted in positive changes in body composition and cardiometabolic parameter in middle aged women.

Numerical Simulations of Cellular Secondary Currents in Open-Channel Flows using Non-linear k-ε Model (비선형 k-ε 모형을 이용한 개수로 흐름에서의 격자형 이차흐름 구조 수치모의)

  • Kang, Hyeongsik;Choi, Sung-Uk;Park, Moonhyeong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6B
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    • pp.643-651
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    • 2008
  • In the present paper, turbulent open-channel flows over longitudinal bedforms are numerically simulated. The Reynolds- averaged Navier-Stokes equations in curvilinear coordinates are solved with the non-linear $k-{\varepsilon}$ model by Speziale( 1987). First, the developed model is applied to rectangular open channel flows for purposes of model validation and parameter sensitivity studies. It is found that the parameters $C_D$ and $C_E$ are important to the intensity of secondary currents and the level of turbulent anisotropy, respectively. It is found that the non-linear $k-{\varepsilon}$ model can hardly reproduce the turbulence anisotropy near the free surface. However, the overall pattern of the secondary currents by the present model is seen to coincide with measured data. Then, numerical simulations of turbulent flows over longitudinal bedforms are performed, and the simulated results are compared with the experimental data in the literature. The simulated secondary currents clearly show upflows and downflows over the ridges and troughs, respectively. The numerical results of secondary currents, streamwise mean velocity, and turbulence structures compare favorably with the measured data. However, it is observed that the secondary currents towards the troughs were significantly weak compared with the measured data.

Parameter Calibration of Storage Function Model and Flood Forecasting (2) Comparative Study on the Flood Forecasting Methods (저류함수모형의 매개변수 보정과 홍수예측 (2) 홍수예측방법의 비교 연구)

  • Kim, Bum Jun;Song, Jae Hyun;Kim, Hung Soo;Hong, Il Pyo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1B
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    • pp.39-50
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    • 2006
  • The flood control offices of main rivers have used a storage function model to forecast flood stage in Korea and studies of flood forecasting actively have been done even now. On this account, the storage function model, which is used in flood control office, regression models and artificial neural network model are applied into flood forecasting of study watershed in this paper. The result obtained by each method are analyzed for the comparative study. In case of storage function model, this paper uses the representative parameters of the flood control offices and the optimized parameters. Regression coefficients are obtained by regression analysis and neural network is trained by backpropagation algorithm after selecting four events between 1995 to 2001. As a result of this study, it is shown that the optimized parameters are superior to the representative parameters for flood forecasting. The results obtained by multiple, robust, stepwise regression analysis, one of the regression methods, show very good forecasts. Although the artificial neural network model shows less exact results than the regression model, it can be efficient way to produce a good forecasts.