• Title/Summary/Keyword: Slope prediction model

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Genetic Aspects of Persistency of Milk Yield in Boutsico Dairy Sheep

  • Kominakis, A.P.;Rogdakis, E.;Koutsotolis, K.
    • Asian-Australasian Journal of Animal Sciences
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    • v.15 no.3
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    • pp.315-320
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    • 2002
  • Test-day records (n=13677) sampled from 896 ewes in 5-9 (${\mu}$=7.5) monthly test-days were used to estimate genetic and phenotypic parameters of test-day yields, lactation milk yield (TMY), length of the milking period (DAYS) and three measures of persistency of milk yield in Boutsico dairy sheep. Τhe measures of persistency were the slope of the regression line (${\beta}$), the coefficient of variation (CV) of the test-day milk yields and the maximum to average daily milk yield ratio (MA). The estimates of variance components were obtained under a linear mixed model by restricted maximum likelihood. The heritability of test-day yields ranged from 0.15 to 0.24. DAYS were found to be heritable ($h^2$=0.11). Heritability estimates of ${\beta}$, CV and MA were 0.15, 0.13, 0.10, respectively. Selection for maximum lactation yields is expected to result in prolonged milking periods, high rates of decline of yields after peak production, variable test-day yields and higher litter sizes. Selection for flatter lactation curves would reduce lactation yields, increase slightly the length of the milking period and decrease yield variation as well as litter size. The most accurate prediction of TMY was obtained with a linear regression model with the first five test-day records.

Numerical Prediction on Snowfall Intensity in the Mountainous Coastal Region

  • Choi, Hyo;Lee, Han-Se;Kim, Tae-Kook;Choi, Doo-Sun
    • Proceedings of the Korean Environmental Sciences Society Conference
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    • 2003.11a
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    • pp.89-94
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    • 2003
  • The formation of a severe snow storm occurred in the mountainous coastal region near Mt. Taegualyang and Kangnung city in the eastern part of Korea was investigate from 0900LST, December 7 through 9, 2002, using MM5 model. As synoptic scale easterly wind induced a great amount of moisture from the East Sea into the inland coastal region and sea-breeze further induced more moisture from the basin toward the top of the mountain side. The lifted moisture toward the mountain top was cooled down along the eastern slope of the mountain and near the mid of the mountain the moisture was much cooled down with relative humidity of 100% under the air temperature below $O^{\circ}C$, resulting in the formation of snow. Relative humidity of 100% generally occurred at the 5km away from the coast toward the inland mountain and the band of 100% RH was parallel to the coastal line. The 100% band coincided with minimum air temperature band and line.

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Analysis of Wave Responses in Harbor Using Boundary Damper Techniques (경계 damper를 이용한 항만 파낭응답 해석)

  • 정원무;박우선
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.5 no.1
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    • pp.39-44
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    • 1993
  • This paper is concerned with developing a finite element model incorporating boundary damper techniques which is applicable to the prediction of wave agitations in harbors. Based on the linear wave theory, a mild-slope equation is used. In order to consider the wave energy dissipations on solid boundary. the partial reflecting boundary condition is introduced. Radiating boundary condition is modeled by using tile second-order boundary damper developed by Bando et al. (1984). The near field region in harbor is discretized using 8-noded isoparametric elements, the boundary conditions are presented using 3-noded line elements. The numerical model is applied to a fully open rectangular harbor to prove its validity. Numerical experiments are also performed to investigate the effects of the wave reflection coefficients of solid boundary and the types of the dampers.

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The nose-up effect in twin-box bridge deck flutter: Experimental observations and theoretical model

  • Ronne, Maja;Larsen, Allan;Walther, Jens H.
    • Wind and Structures
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    • v.32 no.4
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    • pp.293-308
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    • 2021
  • For the past three decades a significant amount of research has been conducted on bridge flutter. Wind tunnel tests for a 2000 m class twin-box suspension bridge have revealed that a twin-box deck carrying 4 m tall 50% open area ratio wind screens at the deck edges achieved higher critical wind speeds for onset of flutter than a similar deck without wind screens. A result at odds with the well-known behavior for the mono-box deck. The wind tunnel tests also revealed that the critical flutter wind speed increased if the bridge deck assumed a nose-up twist relative to horizontal when exposed to high wind speeds - a phenomenon termed the "nose-up" effect. Static wind tunnel tests of this twin-box cross section revealed a positive moment coefficient at 0° angle of attack as well as a positive moment slope, ensuring that the elastically supported deck would always meet the mean wind flow at ever increasing mean angles of attack for increasing wind speeds. The aerodynamic action of the wind screens on the twin-box bridge girder is believed to create the observed nose-up aerodynamic moment at 0° angle of attack. The present paper reviews the findings of the wind tunnel tests with a view to gain physical insight into the "nose-up" effect and to establish a theoretical model based on numerical simulations allowing flutter predictions for the twin-box bridge girder.

Sales Pattern and Related Product Attributes of T-shirts (티셔츠 상품의 판매패턴과 연관된 상품속성)

  • Chae, Jin Mie;Kim, Eun Hie
    • Journal of the Korean Society of Clothing and Textiles
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    • v.44 no.6
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    • pp.1053-1069
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    • 2020
  • This study examined the sales pattern relationship with respect to product attributes to propose sales forecasting for fashion products. We analyzed 537 SKU sales data of T-shirts in the domestic sports brand using SAS program. The sales pattern of fashion products fluctuated and were influenced by exogenous factors; therefore, we removed the influence of exogenous factors found to be price discounts and holiday effects as a result of regression analysis. In addition, it was difficult to predict sales using the sales patterns of the same product since fashion products were released as new products every year. Therefore, the forecasting model was proposed using sales patterns of related product attributes when attributes were considered descriptive variables. We classified sales patterns using K-means clustering in order to explain the relationship between sales patterns and product attributes along with creating a decision tree classifier using attributes as input and sales patterns as output. As a result, the sales patterns of T-shirts were clustered into six types that featured the characteristic shape of peak and slope. It was also associated with the combination of product attributes and their values in regards to the proposed sales pattern prediction model.

Numerical study to reproduce a real cable tray fire event in a nuclear power plant

  • Jaiho Lee ;Byeongjun Kim;Yong Hun Jung;Sangkyu Lee;Weon Gyu Shin
    • Nuclear Engineering and Technology
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    • v.55 no.4
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    • pp.1571-1584
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    • 2023
  • In this study, a numerical analysis was performed as part of an international joint research project to reproduce a real cable tray fire that occurred in the heater bay area of the turbine building of a nuclear power plant. A sensitivity analysis was performed on various input parameters to derive results consistent with the sprinkler activation time obtained from the fire event analysis. For all sensitive parameters, the normalized sprinkler activation time correlated well with the power function of the normalized sprinkler height. A correlation equation was developed to identify the sprinkler activation time at any location when determining the slope or fire growth rate under the conditions assuming a linear or t-squared heat release rate (HRR) time curve. Various cable fire growth assumptions were used to determine which assumption was better to provide the prediction coincident with the information given from the fire event analysis in terms of the sprinkler activation time and total energy generated from cables damaged by fire. In the comprehensive analysis of all the sensitive parameters, the standard deviation of the input parameters increased as the sprinkler height decreased. Within the range of the sensitivity parameter values given in this study, when considering all sprinkler heights, the standard deviation of the cable model change was the largest and that of the overhang position change was the smallest.

A Study on Estimate of Sediment Yield Using Tank Model in Oship River Mouth of East Coast (Tank 모형을 이용한 동해안 오십천 하구의 유사량 평가에 관한 연구)

  • Kang, Sank-Hyeok;Ok, Yong-Sik;Kim, Sang-Ryul;Ji, Jeong-Hwan
    • Korean Journal of Environmental Agriculture
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    • v.30 no.3
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    • pp.268-274
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    • 2011
  • BACKGROUND: A large scale of sediment load delivered from watershed causes substantial waterway damages and water quality degradation. Controlling sediment loading requires the knowledge of the soil erosion and sedimentation. The various factors such as watershed size, slope, climate, land use may affect sediment delivery processes. Traditionally sediment delivery ratio prediction equations have been developed by relating watershed characteristics to measured sediment yield divided by predicted gross erosion. However, sediment prediction equations have been developed for only a few regions because of limited sediment data. Besides, little research has been done on the prediction of sediment delivery ratio for asia monsoon period in mountainous watershed. METHODS AND RESULTS: In this study Tank model was expanded and applied for estimating sediment yield to Oship River of east coast. The rainfall-runoff in 2006 was verified using the Tank model and we derived good result between observed and calculated discharge in 2009 at the same conditions. In relation to sediment yield, the sediment delivery rate of 2006 was very high than 2009 regardless of methods for estimating sediment load. It was thought to be affected by heavy rainfall due to the typhoon. CONCLUSION(s): For estimating sediment volume from watershed, long-term monitoring data on discharge and sediment is needed. This model will be able to apply to predict discharge and sediment yield simultaneously in ungauged area. This approach is more effective and less expensive method than the traditional method which needs a lot of data collection.

Analysis and Validation of Geo-environmental Susceptibility for Landslide Occurrences Using Frequency Ratio and Evidential Belief Function - A Case for Landslides in Chuncheon in 2013 - (Frequency Ratio와 Evidential Belief Function을 활용한 산사태 유발에 대한 환경지리적 민감성 분석과 검증 - 2013년 춘천 산사태를 중심으로 -)

  • Lee, Won Young;Sung, Hyo Hyun;Ahn, Sejin;Park, Seon Ki
    • Journal of The Geomorphological Association of Korea
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    • v.27 no.1
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    • pp.61-89
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    • 2020
  • The objective of this study is to characterize landslide susceptibility depending on various geo-environmental variables as well as to compare the Frequency Ratio (FR) and Evidential Belief Function (EBF) methods for landslide susceptibility analysis of rainfall-induced landslides. In 2013, a total of 259 landslides occurred in Chuncheon, Gangwon Province, South Korea, due to heavy rainfall events with a total cumulative rainfall of 296~721mm in 106~231 hours duration. Landslides data were mapped with better accuracy using the geographic information system (ArcGIS 10.6 version) based on the historic landslide records in Chuncheon from the National Disaster Management System (NDMS), the 2013 landslide investigation report, orthographic images, and aerial photographs. Then the landslides were randomly split into a testing dataset (70%; 181 landslides) and validation dataset (30%; 78 landslides). First, geo-environmental variables were analyzed by using FR and EBF functions for the full data. The most significant factors related to landslides were altitude (100~200m), slope (15~25°), concave plan curvature, high SPI, young timber age, loose timber density, small timber diameter, artificial forests, coniferous forests, soil depth (50~100cm), very well-drained area, sandy loam soil and so on. Second, the landslide susceptibility index was calculated by using selected geo-environmental variables. The model fit and prediction performance were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under Curve (AUC) methods. The AUC values of both model fit and prediction performance were 80.5% and 76.3% for FR and 76.6% and 74.9% for EBF respectively. However, the landslide susceptibility index, with classes of 'very high' and 'high', was detected by 73.1% of landslides in the EBF model rather than the FR model (66.7%). Therefore, the EBF can be a promising method for spatial prediction of landslide occurrence, while the FR is still a powerful method for the landslide susceptibility mapping.

Prediction of Future Climate Change Using an Urban Growth Model in the Seoul Metropolitan Area (도시성장모델을 적용한 수도권 미래 기후변화 예측)

  • Kim, Hyun-Su;Jeong, Ju-Hee;Oh, In-Bo;Kim, Yoo-Keun
    • Journal of Korean Society for Atmospheric Environment
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    • v.26 no.4
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    • pp.367-379
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    • 2010
  • Future climate changes over the Seoul metropolitan area (SMA) were predicted by the Weather Research and Forecasting (WRF) model using future land-use data from the urban growth model (SLEUTH) and forecast fields from ECHAM5/MPI-OM1 GCM (IPCC scenario A1B). Simulations from the SLEUTH model with GIS information (slope, urban, hill-shade, etc.) derived from the water management information system (WAMIS) and the intelligent transportation systems-standard nodes link (ITS-SNL) showed that considerable increase by 17.1% in the fraction of urban areas (FUA) was found within the SMA in 2020. To identify the effects of the urban growth on the temperature and wind variations in the future, WRF simulations by considering urban growth were performed for two seasons (summer and winter) in 2020s (2018~2022) and they were compared with those in the present (2003~2007). Comparisons of model results showed that significant changes in surface temperature (2-meter) were found in an area with high urban growth. On average in model domain, positive increases of $0.31^{\circ}C$ and $0.10^{\circ}C$ were predicted during summer and winter, respectively. These were higher than contributions forced by climate changes. The changes in surface temperature, however, were very small expect for some areas. This results suggested that surface temperature in metropolitan areas like the SMA can be significantly increased only by the urban growth during several decades.

Development of Crop Growth Model under Different Soil Moisture Status

  • Goto, Keita;Yabuta, Shin;Sakagami, Jun-Ichi
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2019.09a
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    • pp.19-19
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    • 2019
  • It is necessary to maintain stable crop productions under the unsuitable environments, because the drought and flood may be frequently caused by the global warming. Therefore, it is agent to improve the crop growth model corresponded to soil moisture status. Chili pepper (Capsicum annuum) is one of the useful crop in Asia, and then it is affected by change of precipitation in consequence drought and flood occur however crop model to evaluate water stresses on chili pepper is not enough yet. In this study, development of crop model under different soil moisture status was attempted. The experiment was conducted on the slope fields in the greenhouse. The water level was kept at 20cm above the bottom of the container. Habanero (C. chinense) was used as material for crop model. Sap bleeding rate, SPAD value, chlorophyll content, stomatal conductance, leaf water potential, plant height, leaf area and shoot dry weight were measured at 10 days after treatment (DAT) and 13 DAT. Moreover, temperature and RH in the greenhouse, soil volume water contents (VWC) and soil water potential were measured. As a result, VWC showed 4.0% at the driest plot and 31.4% at the wettest plot at 13 DAT. The growth model was calculated using WVC and the growth analysis parameters. It was considered available, because its coefficient of determination showed 0.84 and there are significant relationship based on plants physiology among the parameters and the changes over time. Furthermore, we analyzed the important factors for higher accuracy prediction using multiple regression analysis.

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