Objective: The objective of this study was to obtain (co) variance components and genetic parameter estimates for post-weaning body measurements such as body length (BL), height at withers (HW), and chest girth (HG) recorded at six (SBL, SHW, and SHG), nine (NBL, NHW, and NHG) and twelve (YBL, YHW, and YHG) months of age along with yearling weight (YW) in Nellore sheep maintained at livestock research station, Palamaner, Andhra Pradesh, India and also the association among body measurements with YW was studied. Methods: Data on 2,076 Nellore sheep (descended from 75 sires and 522 dams) recorded between 2007 and 2016 (10 years) were utilized in the study. Lambing year, sex of lamb, season of lambing and parity of dam were included in the model as fixed effects and ewe weight was kept as a covariate. Analyses were conducted with six animal models with different combinations of direct and maternal genetic effects using restricted maximum likelihood procedure. Best model for each trait was determined based on Akaike's information criterion. Results: Moderate estimates of direct heritability were obtained for the studied traits viz., BL (0.02 to 0.24), HW (0.31 to 0.49), and CG (0.08 to 0.35) and their corresponding maternal heritability estimates were in the range of 0.00 to 0.07 (BL), 0.13 to 0.17 (HW), and 0.07 to 0.13 (CG), respectively. Positive direct genetic and phenotypic correlations among the traits and they ranged from 0.07 (YBL-YW) to 0.99 (SBL-SHG, SHG-YW, and NBL-YBL) and 0.01 (SBL-YBL) to 0.99 (NBL-NHG), respectively. Further, the genetic correlations among all the body measurements and YW were positive and ranged from 0.07 (YW and YBL) to 0.99 (YW and SHG). Conclusion: There was a strong association of chest girth at six months with YW. Further, it is indicated that moderate improvement of post-weaning body measurements in Nellore sheep would be possible through selection.
Journal of the Korea institute for structural maintenance and inspection
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v.11
no.6
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pp.169-180
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2007
Among several splicing system of reinforcing bar, the grout-filled splice sleeve system has been applied widely. However, as the splice sleeve for high strength rebar as SD500 is not yet made in korea, the development of splice sleeve for high strength reinforcing bar are required as soon as possible. It is the purpose of this study to develop the steel pipe sleeve for high strength rebar as SD500 and estimate its structural performance by monotonic loading test. The experimental variables adopted in this study are the development length of rebars, types of sleeve etc. The results of this study showed that the developed steel pipe splice sleeve system for high strength reinforcing bar as SD500 retained the structural performance required in domestic, ACI and AIJ criteria. And it is considered that the study result presented in this paper can be helpful in developing reasonable design method of steel pipe splice sleeve system for high strength reinforcing bar as SD500.
Ibrahim Albaijan;Hanan Samadi;Arsalan Mahmoodzadeh;Hawkar Hashim Ibrahim;Nejib Ghazouani
Computers and Concrete
/
v.34
no.2
/
pp.247-265
/
2024
Measuring the fracture toughness of concrete in laboratory settings is challenging due to various factors, such as complex sample preparation procedures, the requirement for precise instruments, potential sample failure, and the brittleness of the samples. Therefore, there is an urgent need to develop innovative and more effective tools to overcome these limitations. Supervised learning methods offer promising solutions. This study introduces seven machine learning algorithms for predicting concrete's effective fracture toughness (K-eff). The models were trained using 560 datasets obtained from the central straight notched Brazilian disc (CSNBD) test. The concrete samples used in the experiments contained micro silica and powdered stone, which are commonly used additives in the construction industry. The study considered six input parameters that affect concrete's K-eff, including concrete type, sample diameter, sample thickness, crack length, force, and angle of initial crack. All the algorithms demonstrated high accuracy on both the training and testing datasets, with R2 values ranging from 0.9456 to 0.9999 and root mean squared error (RMSE) values ranging from 0.000004 to 0.009287. After evaluating their performance, the gated recurrent unit (GRU) algorithm showed the highest predictive accuracy. The ranking of the applied models, from highest to lowest performance in predicting the K-eff of concrete, was as follows: GRU, LSTM, RNN, SFL, ELM, LSSVM, and GEP. In conclusion, it is recommended to use supervised learning models, specifically GRU, for precise estimation of concrete's K-eff. This approach allows engineers to save significant time and costs associated with the CSNBD test. This research contributes to the field by introducing a reliable tool for accurately predicting the K-eff of concrete, enabling efficient decision-making in various engineering applications.
This study aims to developing a method for estimating pharmaceutical compounds within a monolith column using high-performance liquid chromatography (HPLC). The monolithic column was prepared using copolymerization of glycidyl methacrylate, co-ethylene dimethacrylate, and co-acrylic acid inside a borosilicate tube of specific dimensions a 60 mm borosilicate tube length with 1.5 mm and 3.5 mm inner and outer diameters, respectively. A UV Ultra violet source with a wavelength of 365 nm was used, and the polymerization process involved mixing glycidyl methacrylate, acrylic acid, ethylene dimethacrylate as a binder, and 2,2-dimethoxy-2-phenyl acetate phenone as an initiator in suitable solvents consisting of ethanol and 1-hexanol. The polymerization process formed the monolith column after 4 minutes, and subsequently, the epoxy groups were altered to diol groups using 0.2 M hydrochloric acid HCl, which were pumped through the column for 3 hours at a flow rate of 10 µL·min-1. Various techniques, such as Scanning Electron Microscope SEM, Brunauer-Emmett-Teller BET, Fourier-transform infrared spectroscopy FT-IR and HNMR, were utilized to characterize and confirm the structure of the monolith. The prepared monolith was employed to estimate and identify the pharmaceutical compound of warfarin using high-performance liquid chromatography HPLC. The analytical curve of warfarin was linear in the range of 3 to 100 ㎍·mL-1 with an r2 value of 0.999. The detection and quantification limits were 0.932 and 2.788 ㎍·mL-1, respectively. The molar absorptivity and Sandells sensitivity were 2.99138 × 106 L·mol-1·cm-1 and 103.1 × 10-3 ㎍·cm-2, respectively.
Objective: To evaluate the discrepancies between initial STO and final STO in Class III malocclusions and to find which factors are related to the discrepancies. Methods: Twenty patients were selected for the extraction group and 20 patients for the non-extraction group. They were diagnosed as skeletal Class III and received presurgical orthodontic treatment and mandibular set-back surgery at Pusan National University Hospital. The lateral cephalograms were analyzed for initial STO (T1s) at pretreatment and final STO (T2s) after presurgical orthodontic treatment, and specified the landmarks 3s coordinates of the X and V axes. Results: Differences in hard tissue points (T1s-T2s) in the X coordinates of upper central incisor edge, upper first molar mesial end surface, lower central incisor apex, lower first molar mesial end surface and mesio-buccal cusp and Y coordinates of upper central incisor edge, upper central incisor apex, upper first molar mesio-buccal cusp were statistically significant in the extraction group. Differences in hard tissue points (T1s-T2s) in the X coordinates of upper central incisor edge, lower central incisor apex, lower first molar mesial end surface and Y coordinates of lower central incisor apex were statistically significant in the non-extraction group. In the extraction group, the upper arch length discrepancy (UALD) had a statistically significant effect on maxillary incisor and first molar estimation. Lower arch length discrepancy and IMPA had statistically significant effects on mandibular incisor estimation in both groups. Conclusions: Discrepancies between initial STO and final STO and factors contributing to the accuracy of initial STO must be considered in treatment planning of Class III surgical patients to increase the accuracy of prediction.
There is systematic spatial variations in environmental properties due to sensitive reaction to external conditions at plastic greenhouse occupied 99.2% of domestic agricultural facilities. In order to construct 3 dimensional distribution of temperature, relative humidity, CO2 and illuminance, measurement matrix as 3 by 3 by 5 in direction of width, height and length, respectively, dividing indoor space of greenhouse was designed and tested at experimental site. Linear regression analysis was conducted to evaluate optimal estimation method in terms with horizontal and vertical variations. Even though sole measurement point for temperature and relative humidity could be feasible to assess indoor condition, multiple measurement matrix is inevitably required to improve spatial precision at certain time domain such as period of sunrise and sunset. In case with CO2, multiple measurement matrix could not successfully improve the spatial predictability during a whole experimental period. In case with illuminance, prediction performance was getting smaller after a time period of sunrise due to systematic interference such as indoor structure. Thus, multiple sensing methodology was proposed in direction of length at higher height than growing bed, which could compensate estimation error in spatial domain. Appropriate measurement matrix could be constructed considering the transition of stability in indoor environmental properties due to external variations. As a result, optimal measurement matrix should be carefully designed considering flexibility of construction relevant with the type of property, indoor structure, the purpose of crop and the period of growth. For an instance, partial cooling and heating system to save a consumption of energy supplement could be successfully accomplished by the deployment of multiple measurement matrix.
Accident prediction models have been utilized to predict accident possibilities in existing or projected freeways and to evaluate programs or policies for improving safety. In this study, a traffic accident prediction model for freeways was developed for the above purposes. When selecting variables for the model, the highest priority was on the ease of both collecting data and applying them into the model. The dependent variable was set as the number of total accidents and the number of accidents including casualties in the unit of IC(or JCT). As a result, two models were developed; the overall accident model and the casualty-related accident model. The error structure adjusted to each model was the negative binomial distribution and the Poisson distribution, respectively. Among the two models, a more appropriate model was selected by statistical estimation. Major nine national freeways were selected and five-year dada of 2003~2007 were utilized. Explanatory variables should take on either a predictable value such as traffic volumes or a fixed value with respect to geometric conditions. As a result of the Maximum Likelihood estimation, significant variables of the overall accident model were found to be the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volume to the number of curved segments between ICs(or JCTs). For the casualty-related accident model, the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volumes had a significant impact on the accident. The likelihood ratio test was conducted to verify the spatial and temporal transferability for estimated parameters of each model. It was found that the overall accident model could be transferred only to the road with four or more than six lanes. On the other hand, the casualty-related accident model was transferrable to every road and every time period. In conclusion, the model developed in this study was able to be extended to various applications to establish future plans and evaluate policies.
Kim, Ki-Deog;Suh, Jong-Taek;Lee, Jong-Nam;Yoo, Dong-Lim;Kwon, Min;Hong, Soon-Choon
Horticultural Science & Technology
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v.33
no.6
/
pp.911-922
/
2015
This study was carried out to evaluate growth characteristics of Kimchi cabbage cultivated in various highland areas, and to create a predicting model for the production of highland Kimchi cabbage based on the growth parameters and climatic elements. Regression model for the estimation of head weight was designed with non-destructive measured growth variables (NDGV) such as leaf length (LL), leaf width (LW), head height (HH), head width (HW), and growing degree days (GDD), which was $y=6897.5-3.57{\times}GDD-136{\times}LW+116{\times}PH+155{\times}HH-423{\times}HW+0.28{\times}HH{\times}HW{\times}HW$, ($r^2=0.989$), and was improved by using compensation terms such as the ratio (LW estimated with GDD/measured LW ), leaf growth rate by soil moisture, and relative growth rate of leaf during drought period. In addition, we proposed Excel spreadsheet model for simulation of yield prediction of highland Kimchi cabbage. This Excel spreadsheet was composed four different sheets; growth data sheet measured at famer's field, daily average temperature data sheet for calculating GDD, soil moisture content data sheet for evaluating the soil water effect on leaf growth, and equation sheet for simulating the estimation of production. This Excel spreadsheet model can be practically used for predicting the production of highland Kimchi cabbage, which was calculated by (acreage of cultivation) ${\times}$ (number of plants) ${\times}$ (head weight estimated with growth variables and GDD) ${\times}$ (compensation terms derived relationship of GDD and growth by soil moisture) ${\times}$ (marketable head rate).
Park, Mi-Young;Kim, Sang-Sik;Lee, Seung-Bae;Kim, Chang-Hyuk;Kim, Kang-Su
Journal of the Korea Concrete Institute
/
v.21
no.1
/
pp.93-103
/
2009
The concept of the effective moment of inertia has been generally used for the deflection estimation of reinforced concrete flexural members. The KCI design code adopted Branson's equation for simple calculation of deflection, in which a representative value of the effective moment of inertia is used for the whole length of a member. However, the code equation for the effective moment of inertia was formulated based on the results of beam tests subjected to uniformly distributed loads, which may not effectively account for those of members under different loading conditions. Therefore, this study aimed to verify the influences of moment shapes resulting from different loading patterns by experiments. Six beams were fabricated and tested in this study, where primary variables were concrete compressive strengths and loading distances from supports, and test results were compared to the code equation and other existing approaches. A method utilizing variational analysis for the deflection estimation has been also proposed, which accounts for the influences of moment shapes to the effective moment of inertia. The test results indicated that the effective moment of inertia was somewhat influenced by the moment shape, and that this influence of moment shape to the effective moment of inertia was not captured by the code equation. Compared to the code equation, the proposed method had smaller variation in the ratios of the test results to the estimated values of beam deflections. Therefore, the proposed method is considered to be a good approach to take into account the influence of moment shape for the estimation of beam deflection, however, the differences between test results and estimated deflections show that more researches are still required to improve its accuracy by modifying the shape function of deflection.
KSCE Journal of Civil and Environmental Engineering Research
/
v.32
no.6D
/
pp.679-686
/
2012
KTX step 1 April 2004, after the opening, the second phase of the project was opened in November 2010. High-speed rail after the opening and continue to increase the demand of high-speed rail, Have the speed of competitive advantage compared too the means of transportation. The opening of these high-speed rail has led to changes of the move, the company's position, and the spatial structure of the population of reorganization, such as the social, economic, transportation. In this study, survey data using the High Speed Rail Station EMME/2 of the program to take advantage of the 2-Dimentional Blancing trip distribution to investigate the passage through the trip distribution by the estimation of the parameters of the model to estimate the distribution of the means of access and high-speed rail station to reproduce and Analysis of the results by means of access parameters (${\theta}$) autos 0.0395, buses 0.0390, subway 0.0650, taxi 0.0415, the frequency distribution (Trip Length Frequency Distribution: TLFD) were analyzed survey data value model with the results of comparing $R^2$ cars analysis and model values similar survey data 0.909 bus 0.923, subway 0.745 to 0.922, taxi, F test P value analysis is smaller than 0.05 at the 95% confidence level as a note that was judged to have been. Trip frequency distribution analysis, but in the future, set the unit to 5km-trip frequency distribution middle zone Units from small zone units (administrative district) segmentation research is needed, and can reflect the trip distance 0~5 km interval combined function to take advantage of the gravity model and the 3-Dimentional Blancing applied research is needed to be considered.
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