• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1153-1153
• /
• 2001

Directive 79/373/EEC on the marketing of compound feeding stuffs, provided far a flexible declaration arrangement confined to the indication of the feed materials without stating their quantity and the possibility was retained to declare categories of feed materials instead of declaring the feed materials themselves. However, the BSE (Bovine Spongiform Encephalopathy) and the dioxin crisis have demonstrated the inadequacy of the current provisions and the need of detailed qualitative and quantitative information. On 10 January 2000 the Commission submitted to the Council a proposal for a Directive related to the marketing of compound feeding stuffs and the Council adopted a Common Position (EC N$^{\circ}$/2001) published at the Official Journal of the European Communities of 2. 2. 2001. According to the EC (EC N$^{\circ}$ 6/2001) the feeds material contained in compound feeding stufs intended for animals other than pets must be declared according to their percentage by weight, by descending order of weight and within the following brackets (I :< 30%; II :> 15 to 30%; III :> 5 to 15%; IV : 2% to 5%; V: < 2%). For practical reasons, it shall be allowed that the declarations of feed materials included in the compound feeding stuffs are provided on an ad hoc label or accompanying document. However, documents alone will not be sufficient to restore public confidence on the animal feed industry. The objective of the present work is to obtain calibration equations fur the instanteneous and simultaneous prediction of the chemical composition and the percentage of ingredients of unground compound feeding stuffs. A total of 287 samples of unground compound feeds marketed in Spain were scanned in a FOSS-NIR Systems 6500 monochromator using a rectangular cup with a quartz window (16 $\times$ 3.5 cm). Calibration equations were obtained for the prediction of moisture ($R^2$= 0.84, SECV = 0.54), crude protein ($R^2$= 0.96, SECV = 0.75), fat ($R^2$= 0.86, SECV = 0.54), crude fiber ($R^2$= 0.97, SECV = 0.63) and ashes ($R^2$= 0.86, SECV = 0.83). The sane set of spectroscopic data was used to predict the ingredient composition of the compound feeds. The preliminary results show that NIRS has an excellent ability ($r^2$$\geq$ 0, 9; RPD $\geq$ 3) for the prediction of the percentage of inclusion of alfalfa, sunflower meal, gluten meal, sugar beet pulp, palm meal, poultry meal, total meat meal (meat and bone meal and poultry meal) and whey. Other equations with a good predictive performance ($R^2$$\geq$0, 7; 2$\leq$RPD$\leq$3) were the obtained for the prediction of soya bean meal, corn, molasses, animal fat and lupin meal. The equations obtained for the prediction of other constituents (barley, bran, rice, manioc, meat and bone meal, fish meal, calcium carbonate, ammonium clorure and salt have an accuracy enough to fulfill the requirements layed down by the Common Position (EC Nº 6/2001). NIRS technology should be considered as an essential tool in food Safety Programs.

• Asia Marketing Journal
• /
• v.13 no.4
• /
• pp.159-189
• /
• 2012

What attracts consumers to bloggers' reviews? Consumers would be attracted both by the Bloggers' expertise (i.e., knowledge and experience) and by his/her unbiased manner of delivering information. Expertise and trustworthiness are both virtues of information sources, particularly when there is uncertainty in decision-making. Noting this point, we postulate that consumers' motives determine the relative weights they place on expertise and trustworthiness. In addition, our hypotheses assume that tie strength moderates consumers' expectation on bloggers' expertise and trustworthiness: with expectation on expertise enhanced for power-blog user-group (weak-ties), and an expectation on trustworthiness elevated for personal-blog user-group (strong-ties). Finally, we theorize that the effect of credibility on willingness to accept a review is moderated by tie strength; the predictive power of credibility is more prominent for the personal-blog user-groups than for the power-blog user groups. To support these assumptions, we conducted a field survey with blog users, collecting retrospective self-report data. The "gourmet shop" was chosen as a target product category, and obtained data analyzed by structural equations modeling. Findings from these data provide empirical support for our theoretical predictions. First, we found that the purposive motive aimed at satisfying instrumental information needs increases reliance on bloggers' expertise, but interpersonal connectivity value for alleviating loneliness elevates reliance on bloggers' trustworthiness. Second, expertise-based credibility is more prominent for power-blog user-groups than for personal-blog user-groups. While strong ties attract consumers with trustworthiness based on close emotional bonds, weak ties gain consumers' attention with new, non-redundant information (Levin & Cross, 2004). Thus, when the existing knowledge system, used in strong ties, does not work as smoothly for addressing an impending problem, the weak-tie source can be utilized as a handy reference. Thus, we can anticipate that power bloggers secure credibility by virtue of their expertise while personal bloggers trade off on their trustworthiness. Our analysis demonstrates that power bloggers appeal more strongly to consumers than do personal bloggers in the area of expertise-based credibility. Finally, the effect of review credibility on willingness to accept a review is higher for the personal-blog user-group than for the power-blog user-group. Actually, the inference that review credibility is a potent predictor of assessing willingness to accept a review is grounded on the analogy that attitude is an effective indicator of purchase intention. However, if memory about established attitudes is blocked, the predictive power of attitude on purchase intention is considerably diminished. Likewise, the effect of credibility on willingness to accept a review can be affected by certain moderators. Inspired by this analogy, we introduced tie strength as a possible moderator and demonstrated that tie strength moderated the effect of credibility on willingness to accept a review. Previously, Levin and Cross (2004) showed that credibility mediates strong-ties through receipt of knowledge, but this credibility mediation is not observed for weak-ties, where a direct path to it is activated. Thus, the predictive power of credibility on behavioral intention - that is, willingness to accept a review - is expected to be higher for strong-ties.

• Journal of the Korean Geotechnical Society
• /
• v.36 no.11
• /
• pp.149-156
• /
• 2020

Permeation grouting effectively enhances soil strength and decreases permeability of soil; however, the flow of grout is heavily affected by anisotropy of hydraulic conductivity in layers. Therefore, this study investigates the effect of permeability anisotropy on the effective radius of horizontal permeation grout using computational fluid dynamics (CFD). We modeled the horizontal permeation grout flow as a two-phase viscous fluid flow in porous media, and the model incorporated the chemical diffusion and the viscosity variation due to hardening. The numerical simulation reveals that the permeability anisotropy shapes the grout bulb to be elliptic and the dissolution-driven diffusion causes a gradual change in grout pore saturation at the edge of the grout bulb. For the grout pore saturations of 10%, 50% and 90%, the horizontal and vertical radii of grout bulb are estimated when the horizontal-to-vertical permeability ratio varies from 0.01 to 100, and the predictive model equations are suggested. This result contributes to more efficient design of injection strategy in formation layers with permeability anisotropy.

• Journal of Korea Water Resources Association
• /
• v.37 no.12
• /
• pp.979-991
• /
• 2004

In this study, RMA2 and RMA4, the 2-D depth-averaged models, were employed to simulate the two-dimensional mixing characteristics of the pollutants in the natural streams. The velocity and depth were first calculated using RMA2, 2-D hydrodynamic model, and then the resulting flow field was inputted to RMA4, 2-D water quality model, to compute the concentration field. RMA models were verified using the velocity and concentration data measured in S-curved meandering channel. The results showed that the RMA2 model simulated well the phenomenon that the maximum velocity line is located at the Inner bank of meandering channel, and the RMA4 model was well adapted to reproduce the general mixing behavior and the separation of tracer clouds. Comparing model simulations with measured data in the field experiments, RMA2 model simulated well general flow field and tendency that the maximum velocity line skewed toward the outer bank which were found in field experiments. The simulations of RMA4 model showed that the center of the tracer cloud tends to follow the path in which the maximum velocity occurs. In this study, the dispersion coefficients are fine-tuned based on the measured coefficients calculated using field concentration data, and the results show reasonable agreement with predictive equations.

• Journal of Crop Science and Biotechnology
• /
• v.11 no.2
• /
• pp.141-150
• /
• 2008

The response of grain yield(GY) and milled-rice protein content(PC) to crop growth status and nitrogen(N) rates at panicle initiation stage(PIS) is critical information for prescribing topdress N rate at PIS(Npi) for target GY and PC. Three split-split-plot experiments including various N treatments and rice cultivars were conducted in Experimental Farm, Seoul National University, Korea in 2003-2005. Shoot N density(SND, g N in shoot $m^{-2}$) and canopy reflectance were measured before N application at PIS, and GY, PC, and SND were measured at harvest. Data from the first two years(2003-2004) were used for calibrating the predictive models for GY, PC, and SND accumulated from PIS to harvest using SND at PIS and Npi by multiple stepwise regression. After that the calibrated models were used for calculating N requirement at PIS for each of nine plots based on the target PC of 6.8% and the values of SND at PIS that was estimated by canopy reflectance method in the 2005 experiment. The result showed that SND at PIS in combination with Npi were successful to predict GY, PC, and SND from PIS to harvest in the calibration dataset with the coefficients of determination ($R^2$) of 0.87, 0.73, and 0.82 and the relative errors in prediction(REP, %) of 5.5, 4.3, and 21.1%, respectively. In general, the calibrated model equations showed a little lower performance in calculating GY, PC, and SND in the validation dataset(data from 2005) but REP ranging from 3.3% for PC and 13.9% for SND accumulated from PIS to harvest was acceptable. Nitrogen rate prescription treatment(PRT) for the target PC of 6.8% reduced the coefficient of variation in PC from 4.6% in the fixed rate treatment(FRT, 3.6g N $m^{-2}$) to 2.4% in PRT and the average PC of PRT was 6.78%, being very close to the target PC of 6.8%. In addition, PRT increased GY by 42.1 $gm^{-2}$ while Npi increased by 0.63 $gm^{-2}$ compared to the FRT, resulting in high agronomic N-use efficiency of 68.8 kg grain from additional kg N. The high agronomic N-use efficiency might have resulted from the higher response of grain yield to the applied N in the prescribed N rate treatment because N rate was prescribed based on the crop growth and N status of each plot.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1620-1620
• /
• 2001

Forages, both grazed and conserved, provide the basis of ruminant production systems throughout the world. More than 90 per cent of the feed energy consumed by herbivorous animals world - wide were provided by forages. With such world - wide dependence on forages, the economic and nutritional necessity of been able to characterize them in a meaningful way is vital. The characterization of forages for productive animals is becoming important for several reasons. Relative to conventional laboratory procedures, Near Infrared Reflectance Spectroscopy (NIRS) offers advantages of simplicity, speed, reduced chemical waste, and more cost-effective prediction of product functionality. NIR spectroscopy represents a radical departure from conventional analytical methods, in that entire sample of forage is characterized in terms of its absorption properties in the near infrared region, rather than separate subsamples being treated with various chemicals to isolate specific components. This forces the analyst to abandon his/her traditional narrow focus on the sample (one analyte at a time) and to take a broader view of the relationship between components within the sample and between the sample and the population from which it comes. forage is usually analysed by NIRS in dry and ground presentation. Initial success of NIRS analysis of coarse forages suggest a need to better understand the potential for analysis of minimally processed samples. Preparation costs and possible compositional alterations could be reduced by samples presented to the instrument in undried and unground conditions. NIRS has gained widespread acceptance for the analysis of forage quality constituents on dry material, however little attention has been given to the use of NIRS for chemical determinations on undried and unground forages. Relatively few works reported the use of NIRS to determine quality parameters on undried materials, most of them on both grass and corn silage. Only two works have been found on the determination of quality parameters on fresh forages. The objectives of this paper were (1) to evaluate the use of NIRS for determination of nitrogen and moisture on undried and unground forage samples and (2) to explore two mathematical treatments and two NIR regions to predict chemical parameters on fresh forage. Four hundred forage samples (n: 400) were analysed in a NIRS 6500 instrument (NIR Systems, PA, USA) in reflectance mode. Two mathematical treatments were applied: 1,4,4,1 and 2,5,5,2. Predictive equations were developed using modified partial least squares (MPLS) with internal cross - validation. Coefficient of determination in calibration (${R^2}_{CAL}$) and standard error in cross-validation (SECV) for moisture were 0.92 (12.4) and 0.92 (12.4) for 1,4,4,1 and 2,5,5,2 respectively, on g $kg^{-1}$ dry weight. For crude protein NIRS calibration statistics yield a (${R^2}_{CAL}$) and (SECV) of 0.85 (19.8) and 0.85 (19.6) for 1,4,4,1 and 2,5,5,2 respectively, on a dry weight. It was concluded that NIRS is a suitable method to predict moisture and nitrogen on fresh forage without samples preparation.

• Journal of Korean Society of Environmental Engineers
• /
• v.39 no.10
• /
• pp.568-574
• /
• 2017

The purpose of this study was to optimize experimental conditions (time ($X_1$) (ranging of 26.36 - 93.64 min), concentration of sulfuric acid ($X_2$) (ranging of 0-2.5%) and temperature ($X_3$) (ranging of $136.4-203.6^{\circ}C$) for an organosolv pretreatment process to extract lignin from waste wood. The resulting quadratic model equation using RSM (response surface methodology) represented y (lignin yield) = $-79.89+0.91X_1+9.8X_2-2.54{\times}10^{-3}X_1{^2}-2.11X_2{^2}$. The $R^2$ (coefficient of determination) value of 0.8531 for a model indicates this model has statistically significant predictors at the 10% levels. The predictive results optimized by quadratic model produced a lignin yield of 12.46 g/100 g of dry wood under conditions of $178.2^{\circ}C$ and 2.32% $H_2SO_4$. The lignin yield was more affected by the acid catalyst concentrations than the reaction temperature, but the reaction time was not an influential factor for improving lignin extraction from waste wood in this organosolv pretreatment. According to ANOVA (analysis of variance), the significance probability (p-value) of model was smaller than 0.001 and simulation of obtained model equations showed a good reproducibility based on actual organosolv tests under optimal conditions.

• Korean Journal of Applied Biomechanics
• /
• v.18 no.4
• /
• pp.109-114
• /
• 2008

The purpose of this study was to estimate the energy expenditure simply and practically during physical activities. The physical activity is quantified by the integration of the accelerometer signals obtained from the triaxial accelerometer attached at the waist level of the human body. To find a relationship between energy expenditure and accelerometer data, 6 male and 5 female subjects walked and ran on the treadmill with speeds of 1.5, 3.0, 4.5, 6.0, 6.5, 7.0, and 8.5 km/hr. Each subject performed walking at the speed lower than 6.0 km/hr and running at the speed higher than 6.5 km/hr. Actual energy expenditure was determined by a continuous direct gas analyzer. Two predictive equations of walking and running mode for energy expenditure which includes gender, body mass index(BMI) and data from accelerometer were developed using multiple regression analysis. The correlation coefficients and coefficients of determination between the estimated and measured energy expenditure were R=0.936, R2=0.876 and R=0.881, R2=0.776 in walking and running mode, respectively. For further study, experiments on a larger scale of test subjects are essential for acquiring more reliable results.

• Journal of Korea Soil Environment Society
• /
• v.1 no.2
• /
• pp.91-101
• /
• 1996

In recent years, phytoremediation, the use of plants to detoxify hydrocarbons, has been a promising new area of research, particularly in situ cleanup of large volumes of slightly contaminated soils. There is increasing need for a mathematical model that can be used as a predictive tool prior to actual field implementation of such a relatively new technique. Although a number of models exist for solute-plant interaction in the vegetated zone of soil, most of them have focused on ionic nutrients and some metals. In this study, we developed a mathematical model for simulation of bioremediation of hydrocarbons in soil, associated with plant root systems. The proposed model includes root interactions with soil-water and hydrocarbons in time and space, as well as advective and dispersive transport in unsaturated soil. The developed model considers gas phase diffusion and liquid-gas mass exchanges. For simulation of temporal and spatial changes in root behavior on soil-water and with hydrocarbons, time-specific distribution of root quantity through soil was incorporated into the simulation model. Hydrocarbon absorption and subsequent uptake into roots with water were simulated with empirical equations. In addition, microbial activity in the rhizosphere, a zone of unique interaction between roots and soil microorganisms, was modeled using a biofilm theory. This mathematical model for understanding and predicting fate and transport of compound in plant-aided remediation will assist effective application of plant-aided remediation to field contamination.

• Asian-Australasian Journal of Animal Sciences
• /
• v.31 no.8
• /
• pp.1238-1243
• /
• 2018

Objective: Two experiments were conducted to determine the effects of feeding level on nutrient digestibility and enteric methane ($CH_4$) emissions in growing goats and Sika deer. Methods: Three growing male goats (initial body weight [BW] of $22.4{\pm}0.9kg$) and three growing male deer (initial BW of $20.2{\pm}4.8kg$) were each allotted to a respiration-metabolism chamber for an adaptation period of 7 d and a data collection period of 3 d. An experimental diet was offered to each animal at one of three feeding levels (1.5%, 2.0%, and 2.5% of BW) in a $3{\times}3$ Latin square design. The chambers were used for measuring enteric $CH_4$ emission. Results: Nutrient digestibility decreased linearly in goats as feeding level increased, whereas Sika deer digestibility was not affected by feeding level. The enteric production of $CH_4$ expressed as g/kg dry matter intake (DMI), g/kg organic matter intake, and % of gross energy intake decreased linearly with increased feeding level in goats; however, that of Sika deer was not affected by feeding level. Six equations were estimated for predicting the enteric $CH_4$ emission from goats and Sika deer. For goat, equation 1 was found to be of the highest accuracy: $CH_4(g/d)=6.2({\pm}14.1)+10.2({\pm}7.01){\times}DMI(kg/d)+0.0048({\pm}0.0275){\times}dry$ matter digestibility (DMD, g/kg)-0.0070 (${\pm}0.0187$)${\times}$neutral detergent fiber digestibility (NDFD; g/kg). For Sika deer, equation 4 was found to be of the highest accuracy: $CH_4(g/d)=-13.0({\pm}30.8)+29.4({\pm}3.93){\times}DMI(kg/d)+0.046(0.094){\times}DMD(g/kg)-0.0363({\pm}0.0636){\times}NDFD(g/kg)$. Conclusion: Increasing the feeding level increased $CH_4$ production in both goats and Sika deer, and predictive models of enteric $CH_4$ production by goats and Sika deer were estimated.