• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1265-1265
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• 2001

The organic materials included in excreta of livestock are important resources for organic manure and for improving soil quality, although there is still far from effective using. One reason for this is still unclearly standard of quality for evaluation of manure made from excreta of livestock. Therefore, the objective of this study is to develop rapid and accurate analytical method for analyzing organic compositions of manure made from excreta of livestock, and to establish quality evaluation method based on the compositions predicted by near infrared reflectance spectroscopy (NIRS). Sixteen samples of manure, each eight samples prepared from two treatments, were used in this study. The manure samples were prepared by mixing 560 kg feces of swine,60 kg sawdust with moisture content was adjusted to be 65%. The mixture was then keep under two kinds of shelter, black and clear sheets, as a treatment on the effect of sunlight. Samples were taken in every week (form week-0 to 7) during the process of manure making. Samples were analyzed to determine neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) by detergent methods, and organic cell wall (OCW) and fibrous content of low digestibility in OCW (Ob) by enzymatic methods. Biological oxygen demand (BOD) was analyzed by coulometric respirometer method. These compositions were carbohydrateds and lignin that were hardly digested. Spectra of samples were scanned by NIR instrument model 6500 (Pacific Scientific) and read over the range of wavelength between 400 and 2500nm. Calibration equations were developed using eight manure samples collected from black sheet shelter, while prediction was conducted to the other eight samples from clear sheet shelter. Accuracy of NTRS prediction was evaluated by correlation coefficients (r), standard error of prediction (SEP) and ration of standard deviation of reference data in prediction sample set to SEP (RPD). The r, SEP and RPD value of forage were 0.99, 0.69 and 7.6 for ADL, 0.96, 1.03 and 4.1 for NDF, 0.98, 0.60 and 4.9 for ADF, 0.92, 1.24 and 2.6 for Ob, and 0.91, 1.02 and 7.3 for BOD, respectively. The results indicated that NIRS could be used to measure the organic composition of forage used in manure samples.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4101-4101
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• 2001

Information of body composition (fat and protein) in living animal is important to determine the nutrients requirement. Deuterium oxide (D2O) dilution techniques, as one of isotope dilution techniques have been useful for the prediction of body composition. However, the determination of D2O concentration is time consuming and complicated. Therefore this study was conducted to develop a new method to predict D2O concentration in plasma using near infrared spectroscopy technique (NIRS). Four dairy cows in early lactation were used. They were fed total mixed ration containing conr silage, timothy hay, and concentrates to make 17.0%CP and 14.0 MJDE/kgDM. Dosing D2O was at week 1,3 and 5 after parturition. After dosing D2O, the blood was collected from hour 0 to 72. Blood samples were then centrifuge at 3,000 rpm for 10 minutes to obtain plasma. D2O concentration was analyzed by gas chromatograph (deuterium oxide analyzable system, HK102, Shokotsusyou) after extracted from plasma by liophilization. Plasma sample was scanned by NIRS using Pacific Scientific (Neotec) model 6500 (Perstorp Analytical, Silver Spring, MD) in the range of wavelength from 1100 to 2500 nm. Calibration equation was developed using multiple linear regression. Sample from one animal (cow #550; n: 74) was used for developing the calibration while the rest three animals were used for validating the equation. The range, R and SEC of the calibration set samples were 135-925 ppm, 0.93 and 48.1 ppm, respectively. Validation of the calibration equation for three individual cows was done and the average of NIR predicted value of D2O at each collection time from three weeks injection showed a high correlation. The range, r and 53 of plasma from cow #474 were 322-840 ppm,0.93 and 53.1; cow #478 were 146-951 ppm,0.95 and 39.8; cow #942 were 313-885 ppm,0.95 and 37.2, respectively. Judgement of accuracy based on ratio of standard deviation and standard error in validation set samples (RPD) for cow #474, #478 and #942 were 2.2,4.3 and 3.4, respectively. The error in application due to the variation between individual was considered smaller than the bias from collection period, however, this prediction can be overcome with correction of standard zero-minute concentration of blood. The results of this preliminary study on the use of NIRS for determination of D2O in plasma showed very promising as shown by a convenient and satisfy accuracy. Further study on various physiological stage of animal should be done.

• Steel and Composite Structures
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• v.34 no.5
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.346-352
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• 2017

In this study, we analyzed environmental factors including annual fruit growth and meteorological conditions in Suwon area from 2000 to 2014 to develop and verify a fruit width prediction model in 'Fuji' apple. The 15-year average of full bloom data was April 28 and that of fruit development period was 181 days. The fruit growth until 36 days after full bloom followed single sigmoid curve. The environmental factors affecting fruit width were BIO2, precipitation in September, the average of daily maximum and minimum temperature in April, minimum temperature in August, and growing degree days (GDD) in April. Among them, the model was constructed by combining BIO2 and precipitation in September, which are not cross-correlated with each other or, with other factors. And then, the final model was selected as 19.33095 + (5.76242 ${\times}$ BIO2) - (0.01891 ${\times}$ September precipitation) + (2.63046 ${\times}$ minimum temperature in April) which was the most suitable model with AICc of 92.61 and the adjusted $R^2$ value of 0.53. The model was compared with the observed values f rom 2000 to 2014. As a result, the mean difference between the measured and predicted values of 'Fuji' apple fruit width was ${\pm}2.9mm$ and the standard deviation was 3.54.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.12
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• pp.1705-1710
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• 2003

A small body size of Brown Tsaiya laying duck is desirable to reduce maintenance requirements, so the body weight at 40 weeks of age (BW40) has to be maintained at its current level. Egg weight has to be maintained at around 65 g to meet market requirements. Eggshell strength at 40 weeks of age (ES40) must to be increased in order to maintain a low incidence of broken eggs. Thus, number of eggs laid up to 52 weeks of age (EN52) has to be increased without negative correlated response on ES40. A new linear genetic selection index was used: $I_g=a_0{\times}GEW40\;(g)+a_1{\times}GBW40\;(g)+a_2{\times}GES40\;(kg/cm^2)+a_3{\times}GEN52\;(eggs)$ where GEW40, GBW40, GES40 and GEN52 were the multitrait best linear unbiased prediction (MT-BLUP) animal model predictors of the breeding values respectively of egg weight and body weight at 40 weeks of age (EW40, BW40), ES40 and EN52. The coefficients $a_0$, $a_1$, $a_2$ and $a_3$ were calculated with constraints of 0.0 g, 0.0 g and $0.013kg/cm^2$ for expected genetic gains in EW40, BW40 and ES40 respectively and maximum gain in EN52. Since 1997, the drakes and the ducks were selected according to their own indexes, with this new genetic selection index. From G0 to G4, the average per generation predicted genetic responses in female duck were +0.05 g for EW40, +0.92 g for BW40, $+0.035kg/cm^2$ for ES40 and +2.13 eggs for EN52. Which represented respectively 0.07%, 0.06%, 0.67% and 1.0% of the means of the EW40, BW40, ES40 and EN52. For ES40 and EN52, it represented also respectively 16.1% and 21.6% of the additive genetic standard deviation of these traits. Thevse results indicated that selection of laying Brown Tsaiya by a restricted genetic selection index and with MT-BLUP animal model could be an efficient tool for improving the efficiency of egg production, increasing egg shell strength and egg number while holding egg weight and body weight constants.

• Journal of the Korean Ceramic Society
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• v.50 no.3
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• pp.231-237
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• 2013

Thermodynamic modeling of the $Ni_{0.5}Zn_{0.4}Cu_{0.1}Fe_2O_4$ complex ferrite system has been adopted as a rational approach to establish routes to better synthesis conditions for pure phase $Ni_{0.5}Zn_{0.4}Cu_{0.1}Fe_2O_4$ complex ferrite. Quantitative analysis of the different reaction equilibria involved in the precipitation of $Ni_{0.5}Zn_{0.4}Cu_{0.1}Fe_2O_4$ from aqueous solutions has been used to determine the optimum synthesis conditions. The spinel ferrites, such as magnetite and substitutes for magnetite, with the general formula $MFe_2O_4$, where M= $Fe^{2+}$, $Co^{2+}$, and $Ni^{2+}$ are prepared by coprecipitation of $Fe^{3+}$ and $M^{2+}$ ions with a stoichiometry of $M^{2+}/Fe^{3+}$= 0.5. The average particle size of the as synthesized $Ni_{0.5}Zn_{0.4}Cu_{0.1}Fe_2O_4$, measured by transmission electron microscopy (TEM), is 14.2 nm, with a standard deviation of 3.5 nm the size when calculated using X-ray diffraction (XRD) is 16 nm. When $Ni_{0.5}Zn_{0.4}Cu_{0.1}Fe_2O_4$ ferrite is annealed at elevated temperature, larger grains are formed by the necking and mass transport between the $Ni_{0.5}Zn_{0.4}Cu_{0.1}Fe_2O_4$ ferrite nanoparticles. Thus, the grain sizes of the $Ni_{0.5}Zn_{0.4}Cu_{0.1}Fe_2O_4$ gradually increase as heat treatment temperature increases. Based on the results of Thermogravimetric Analysis (TGA) and Differential Scanning Calorimeter (DSC) analysis, it is found that the hydroxyl groups on the surface of the as synthesized ferrite nanoparticles finally decompose to $Ni_{0.5}Zn_{0.4}Cu_{0.1}Fe_2O_4$ crystal with heat treatment. The results of XRD and TEM confirmed the nanoscale dimensions and spinel structure of the samples.

• Journal of Korean Home Economics Education Association
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• v.31 no.2
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• pp.67-77
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• 2019

The purpose of this study was to identify significant differences in dietary guidelines, emotional intelligence, resilience and violence according to the frequency of family meals for middle school students in Daegu. To achieve the purpose of this study, 241 data collected through self-administered questionnaires were analyzed. The collected data were analyzed using the SPSS (v25.0) program for frequency, percentage, standard deviation, reliability, one-way ANOVA and Duncan comparison. The results of this study were as follows. There was a significant difference in the level of the dietary guidelines practice, emotional intelligence and resilience according to the frequency of family meals of middle school students. Implications and suggestions based on the results of this study were as follows. First, family meal frequency is significantly related to middle school students' dietary guidelines practice, emotional intelligence, and resilience (p<0.05). Accordingly, personal efforts and social and institutional arrangements are required to increase the family meal frequency. Second, some of the core competences required in the 2015 revised curriculum were consistent with sub-areas of emotional intelligence and resilience, which can be predicted by the results that family meal experience of middle school students is also related to the development of core competences. In conclusion, increasing family meal frequency is important considering the trend of education, and is required for personality education.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.6
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• pp.871-879
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• 2014

Two experiments were conducted to determine the digestible energy (DE) and metabolizable energy (ME) contents of corn gluten feed (CGF) for finishing pigs and to develop equations predicting the DE and ME content from the chemical composition of the CGF samples, as well as validate the accuracy of the prediction equations. In Exp. 1, ten CGF samples from seven provinces of China were collected and fed to 66 finishing barrows (Duroc${\times}$Landrace${\times}$Yorkshire) with an initial body weight (BW) of $51.9{\pm}5.5$ kg. The pigs were assigned to 11 diets comprising one basal diet and 10 CGF test diets with six pigs fed each diet. The basal diet contained corn (76%), dehulled soybean meal (21%) and premix (3%). The ten test diets were formulated by substituting 25% of the corn and dehulled soybean meal with CGF and contained corn (57%), dehulled soybean meal (15.75%), CGF (24.25%) and premix (3%). In Exp. 2, two additional CGF sources were collected as validation samples to test the accuracy of the prediction equations. In this experiment, 18 barrows (Duroc${\times}$Landrace${\times}$Yorkshire) with an initial BW of $61.1{\pm}4.0$ kg were randomly allotted to be fed either the basal diet or two CGF containing diets which had a similar composition as used in Exp. 1. The DE and ME of CGF ranged from 10.37 to 12.85 MJ/kg of dry matter (DM) and 9.53 to 12.49 MJ/kg of DM, respectively. Through stepwise regression analysis, several prediction equations of DE and ME were generated. The best fit equations were: DE, MJ/kg of DM = 18.30-0.13 neutral detergent fiber-0.22 ether extract, with $R^2$ = 0.95, residual standard deviation (RSD) = 0.21 and p<0.01; and ME, MJ/kg of DM = 12.82+0.11 Starch-0.26 acid detergent fiber, with $R^2$ = 0.94, RSD = 0.20 and p<0.01. These results indicate that the DE and ME content of CGF varied substantially but the DE and ME for finishing pigs can be accurately predicted from equations based on nutritional analysis.

• Food Science of Animal Resources
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• v.31 no.1
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• pp.115-121
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• 2011

The objective of this study was to develop models to predict freshness factors (total viable counts (TVC), pH, volatile basic nitrogen (VBN), trimethylamine (TMA), and thiobarbituric acid (TBA) values) and the storage period in beef using a visible and near-infrared (NIR) spectroscopic technique. A total of 216 beef spectra were collected during the storage period from 0 to 14 d at a $10^{\circ}C$ storage. A spectrophotometer was used to measure reflectance spectra from beef samples, and beef freshness spectra were divided into a calibration set and a validation set. Multi-linear regression (MLR) models using the stepwise method were developed to predict the factors. The MLR results showed that beef freshness had a good correlation between the predicted and measured factors using the selected wavelength. The correlation of determination ($r^2$), standard error of prediction (SEP), and ratio of standard deviation to SEP (RPD) of the prediction set for TVC was 0.74, 0.64, and 2.75 Log CFU/$cm^2$, respectively. The $r^2$, SEP, and RPD values for pH were 0.43, 0.10, and 1.10; those for VBN were 0.73, 1.45, and 2.00 mg%; those for TMA were 0.70, 0.19, and 2.58 mg%; those for TBA values were 0.73, 0.13, and 2.77 mg MA/kg; and those for storage period were 0.77, 1.94, and 2.53 d, respectively. The results indicate that visible and NIR spectroscopy can predict beef freshness during storage.

• Journal of the Korean Society of Radiology
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• v.10 no.7
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• pp.551-557
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• 2016

National competency standards, which are the contents of the knowledge, skills and attitudes required to perform a job in industry, is organized by the country. the job performance was evaluated based on the National competency standards from the third-year grade of radiology students by using field-based training courses. according to the evaluation results, students showed over 93% satisfactory ratio of job performance in all radiography projection methods. Therefore, it can be predicted that field-based training courses for students made a positive effect on improving their job performance. Exposure methods with CR equipment were evaluated the best rating, yet it has various problems. The standard deviation between students was very high, and the CR operation skill of students was insufficient. Film methods was evaluated also showed problems, due to the exposure condition setting and developing operation. although DR method was rated good to the students, it was evaluated that the operation skill of DR and the ancillary equipment operation skill was shortage. By supplementing the evaluation factors below proficiency levels to a course management in each exposure method, it could help students course achievement. Also, it could help students to improve job performance of clinical areas after graduation.