• Journal of Animal Science and Technology
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• v.64 no.1
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• pp.155-165
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• 2022

As pork consumption increases, rapid and accurate determination of porcine carcass grades at abattoirs has become important. Non-destructive, automated inspection methods have improved slaughter efficiency in abattoirs. Furthermore, the development of a calibration equation suitable for non-destructive inspection of domestic pig breeds may lead to rapid determination of pig carcass and more objective pork grading judgement. In order to increase the efficiency of pig slaughter, the correct estimation of the automated-method that can accommodate the existing pig carcass judgement should be made. In this study, the previously developed calibration equation was verified to confirm whether the estimated traits accord with the actual measured traits of pig carcass. A total of 1,069,019 pigs, to which the developed calibration equation, was applied were used in the study and the optimal estimated regression equation for actual measured two traits (backfat thickness and hot carcass weight) was proposed using the estimated traits. The accuracy of backfat thickness and hot carcass weight traits in the estimated regression models through stepwise regression analysis was 0.840 (R²) and 0.980 (R²), respectively. By comparing the actually measured traits with the estimated traits, we proposed optimal estimated regression equation for the two measured traits, which we expect will be a cornerstone for the Korean porcine carcass grading system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.430-433
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• 2004

The ophthalmic lens manufacturing processes need to extract the aspherical surface equation from the unknown surface since its real profile can be adjusted by the process variables to make the ideal curve without the optical aberration. This paper presents a procedure to get the aspherical surface equation of an aspherical ophthalmic lens. Aspherical form generally consists of the Schulz formula to describe its profile. Therefore, the base curvature, conic constant, and high-order polynomial coefficient should be set to the original design equation. To find an estimated aspherical profile, firstly lens profile is measured by a contact profiler, which has a sub-micrometer measurement resolution. A mathematical tool is based on the minimization of the error function to get the estimated aspherical surface equation from the scanned aspherical profile. Error minimization step uses the Nelder-Mead simplex (direct search) method. The result of the refractive power measurement is compared with the curvature distribution on the estimated aspherical surface equation

• Korean Journal of Agricultural Science
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• v.38 no.1
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• pp.129-143
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• 2011

In this study, to select the incoming solar radiation equation which is most suitable for the estimation of Penman evaporation, 12 incoming solar radiation equations were selected. The Penman evaporation rates were estimated using 12 selected incoming solar radiation equations, and the estimated Penman evaporation rates were compared with measured pan evaporation rates. The monthly average daily meteorological data measured from 17 meteorological stations (춘천, 강능, 서울, 인천, 수원, 서산, 청주, 대전, 추풍령, 포항, 대구, 전주, 광주, 부산, 목포, 제주, 진주) were used for this study. To evaluate the reliability of estimated evaporation rates, mean absolute bias error(MABE), root mean square error(RMSE), mean percentage error(MPE) and Nash-Sutcliffe equation were applied. The study results indicate that to estimate pan evaporation using Penman evaporation equation, incoming solar radiation equation using meteorological data such as precipitation, minimum air temperature, sunshine duration, possible duration of sunshine, and extraterrestrial radiation are most suitable for 11 study stations out of 17 study stations.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.949-961
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• 2022

The purpose of this study is to build an oyster outlook model. In particular, by limiting oyster items, it was designed as a partial equilibrium model based on a panel analysis of a fixed effect model on aquaculture facilities. The model was built with a dynamic ecological equation (DEEM) system that considers aquaculture and harvesting processes. As a result of the estimation of the initial aquaculture facilities based on the panel analysis, the elasticity of the remaining facility volume in the previous month was estimated to be 0.63. According to Nerlove's model, the adjustment coefficient was interpreted as 0.31 and the adjustment speed was analyzed to be very slow. Also, the relative income coefficient was estimated to be 2.41. In terms of elasticity, it was estimated as 0.08% in Gyeongnam, 0.32% in Jeonnam, and 1.98% in other regions. It was analyzed that the elasticity of relative income was accordingly higher in non-main production area. In case of the estimation of the monthly harvest facility volume, the elasticity of the remaining facility volume in the previous month was estimated as 0.53, and the elasticity of the farm-gate price was estimated as 0.23. Both fresh and chilled and frozen oysters' exports were estimated to be sensitive to fluctuations in domestic prices and exchange rates, while Japanese wholesale prices were estimated to be relatively low in sensitivity, especially to the exchange rate with Japan. In estimating the farm-gate price, the price elasticity coefficient of monthly production was estimated to be inelastic at 0.25.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.11a
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• pp.643-646
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• 2003

This study concerns the new estimated strength equation of concrete by penetration test. There are not only few estimate strength equations of concrete, but also many problems to apply them because of time, cost, easiness, structural damage, reliability and so on. In this study, there performed a series of test for one year and estimated strength equation of concrete as follows; Linear: fck =3.38d - 95.1 ($$r^2$$=88.6%) Quadratic: fck =0.188$$d^2$$- 10.76d + 166.3 ($$r^2$$=96.7%) here, fck : estimated compressive strength of concrete by Mpa d: exposed probe length by mm.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.6
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• pp.25-31
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• 2009

In this study, pollutant loads delivery ratio by flow duration in Hwangryoung A watershed was estimated. The delivery ratio was estimated with measured data by Ministry of Environment(MOE) and the regression equation based on geomorphic parameters. Eight day interval flow data measured by the MOE were converted to daily flow to calculate daily load and flow duration curve by correlating data of neighboring station which has daily flow data. Regression equation developed by previous study was tested to study watershed and found to be satisfactory. The delivery ratios estimated by two methods were compared. For the case of Biochemical oxygen demand(BOD), the delivery ratios of low flow condition were 7.6 and 15.5% by measured and regression equation, respectively. Also, the delivery ratios of Total phosphorus(T-P) for normal flow condition were 13.3 and 6.3% by measured and regression equation, respectively.

• Journal of Soil and Groundwater Environment
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• v.8 no.3
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• pp.8-12
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• 2003

The centrifuge test result on capped sediment was compared to the advection- dispersion equation proposed for one layered to predict contaminant transport parameters. The fitted contaminant transport parameters for the centrifuge test results were one to three orders of magnitude greater than the estimated parameters from the advection-dispersion equation. This indicates that the centrifuge model over estimated the contaminant transport phenomena. Thus, the centrifuge provides a non-conservative approach to modeling contaminant transport. It should be also noted that the advection-dispersion equation used in this study is a one layered model. Two layered modeling approaches are more appropriate for modeling this data since there are two layers with different partitioning coefficients. Further research is required to model the centrifuge test using two-layered advection-dispersion models.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.107-115
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• 2006

In this paper, a new speed sensorless control based on an instantaneous reactive power is proposed for the interior permanent magnet synchronous motor(IPMSM) drives. In proposed algorithm, the current observer estimates the line currents and the estimated speed can be yielded from the voltage equation because the information of speed is included in back EMF. To implement speed sensorless control, the current observer is composed by using the voltage equation of the IPMSM in the stationary reference frame fixed to the stator. The estimated speed of the rotor is composed by using the voltage equation of the IPMSM in the rotating reference frame fixed to the rotor The estimated speeds to minimize the speed error compensated by using the instantaneous reactive power. The instantaneous reactive power is calculated on the rotating reference frame fixed to the rotor. The effectiveness of the preposed algorithm is confirmed by the experiments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.239-245
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• 2005

Through the fatigue test of plastic gears using polyacetal polymer, this research aims at providing basic data for not only specifying operation conditions of plastic gears, but also designing dimensions of plastic gears with giving fatigue life and the estimated equation of fatigue life of plastic gears. That is, from the fatigue life curves, the estimated equation of fatigue life of plastic gears is taken out. For the estimated equation of fatigue life of plastic gears, this research provides two test methods; one is preserving non-limited temperature of tooth flank, the other is preserving limited temperature of tooth flank. As results, how the temperature of tooth flank affects the fatigue life is shown. In addition, based on the endurance limit, the essential factors of the unit load and K-factor are determined, which are needed in the design of gear by bending strength and surface durability.