• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.371-385
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• 1995

The yield of semiconductor chips is dependent not only on the average defect density but also on the distribution of defects over a wafer. The distribution of defects leads to consider a cluster index. This paper briefly reviews the existing yield prediction models ad proposes a new cluster index, which utilizes the information about the defect location on a wafer in terms of the coefficient of variation. An extensive simulation is performed under a variety of defect distributions and a yield prediction model is derived through the regression analysis to relate the yield with the proposed cluster index and the average number of defects per chip. The performance of the proposed simulation-based yield prediction model is compared with that of the well-known negative binomial model.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.2
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• pp.186-191
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• 2001

A crack with electrically impermeable surfaces in an electrostrictive material subjected to uniform electric loading is analysed. The effect of electric yielding on stress intensity factor is investigated by using a small scale yielding model and a strip yield zone model. Complete forms of electric fields and elastic fields are derived by using complex function theory. The electrical yield zone shapes for two models are different each other. The two models, however, predict similar yield zone sizes under the small scale yielding conditions. It is found that the influence of electric yielding on the stress intensity factor is insensitive to the modeling of the electrical yield zone shape.

• IE interfaces
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• v.20 no.1
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• pp.87-93
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• 2007

Burn-in is an engineering method for screening out products containing reliability defects which would cause early failures in field operation. Previously, various burn-in models have been proposed mainly focused on the trade-off of shop repair cost and warranty cost ignoring manufacturing yield. From the view point of a manufacturer, however, burn-in decreases warranty cost at the expense of yield reduction. In this paper, we provide a general model quantifying a trade-off between product yield and reliability, in which any defect distribution from previous yield models can be used. A profit function is expressed in burn-in environments for determining an optimal burn-in time. Finally, the method is illustrated with gate oxide failures which is an important reliability concerns for VLSI CMOS circuits.

• Journal of Forest and Environmental Science
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• v.28 no.4
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• pp.205-211
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• 2012

Yield tables are a frequently used data base for regional timber resource forecasting. A normal yield table is based on two independent variables, age and site (species constant), and applies to fully stocked (or normal) stands while empirical yield tables are based on average rather than fully stocked stands. Normal and empirical yield tables essentially have many limitations. The limitations of normal and empirical yield tables led to the development of variable density yield tables. Mathematical models for estimating timber yields are usually developed by fitting a suitable equation to observed data. The model is then used to predict yields for conditions resembling those of the original data set. It may be accurate for the specific conditions, but of unproven accuracy or even entirely useless in other circumstances. Thus, these models tend to be specific rather than general and require validation before applying to other areas. Dalbergia sissoo forms a major portion of irrigated plantations in the hot desert of India and is an important timber tree species where stem wood is primarily used as timber. Variable density yield model is not available for this species which is very crucial in long-term planning for managing the plantations on a sustained basis. Thus, the objective of this study was to develop variable density yield model based on the data collected from 30 sample plots of D. sissoo laid out in IGNP area of Rajasthan State (India) and measured annually for 5 years. The best approximating model was selected based on the fit statistics among the models tested in the study. The model develop was evaluated based on quantitative and qualitative statistical criteria which showed that the model is statistically sound in prediction. The model can be safely applied on D. sissooo plantations in the study area or areas having similar conditions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.5
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• pp.394-406
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• 2004

A split-plot designed experiment including four rice varieties and 10 nitrogen levels was conducted in 2003 at the Experimental Farm of Seoul National University, Suwon, Korea. Before heading, hyperspectral canopy reflectance (300-1100nm with 1.55nm step) and nine crop variables such as shoot fresh weight (SFW), leaf area index, leaf dry weight, shoot dry weight, leaf N concentration, shoot N concentration, leaf N density, shoot N density and N nutrition index were measured at 54 and 72 days after transplanting. Grain yield, total number of spikelets, number of filled spikelets and 1000-grain weight were measured at harvest. 14,635 narrow-band NDVIs as combinations of reflectances at wavelength ${\lambda}l\;and\;{\lambda}2$ were correlated to the nine crop variables. One NDVI with the highest correlation coefficient with a given crop variable was selected as the NDVI of the best fit for this crop variable. As expected, models to predict crop variables before heading using the NDVI of the best fit had higher $r^2$ (>10\%)$ than those using common broad- band NDVI red or NDVI green. The models with the narrow-band NDVI of the best fit overcame broad- band NDVI saturation at high LAI values as frequently reported. Models using NDVIs of the best fit at booting showed higher predictive capacity for yield and yield component than models using crop variables.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.741-744
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• 1996

Artifical Neural Network(ANN) models were used for forecasting interest rate as a new methodology, which has proven itself successful in financial domain. This research intended to construct ANN models which can maximize the performance of prediction, regarding Corporate Bond Yield (CBY) as interest rate. Synergistic Market Analysis (SMA) was applied to the construction of models [Freedman et al.]. In this aspect, while the models which consist of only time series data for corporate bond yield were devloped, the other models generated through conjunction and reorganization of fundamental variables and market variables were developed. Every model was constructed to predict 1,6, and 12 months after and we obtained 9 ANN models for interest rate forecasting. Multi-layer perceptron networks using backpropagation algorithm showed good performance in the prediction for 1 and 6 months after.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.5
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• pp.575-579
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• 2000

First lactation records of 683 Murrah buffaloes maintained at NDRI, Karnal which were progeny of 84 sires used for comparing the heritability estimates of age at first calving, first lactation milk yield and first service period under single and multiple trait models using restricted maximum likelihood (REML) method of estimation under an individual animal model. The results indicated that the heritability estimates may vary under single and multiple trait models depending upon the magnitude of genetic and environmental correlation among the traits being considered. Therefore, a single or multiple trait model is recommended for estimation of variance components depending upon the goal of breeding programme. However, there may not be any advantage of considering a trait with zero or near zero heritability and having no or very low genetic correlation with other traits in the model. Lower heritability estimates of part lactation yield (120-day milk yield) implied that there may not be any advantage of considering this trait in place of actual 305-day milk yield, whereas, comparable heritability estimates of predicted 305-day milk yield suggested that it could be used for sire evaluation to reduce the cost of milk recording under field conditions.

• Journal of Pharmaceutical Investigation
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• v.37 no.3
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• pp.137-148
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• 2007

Using a strain-controlled rheometer [Rheometrics Dynamic Analyzer (RDA II)], the steady shear flow properties of a semi-solid ointment base (vaseline) have been measured over a wide range of shear rates at temperature range of $25{\sim}60^{\circ}C$. In this article, the steady shear flow properties (shear stress, steady shear viscosity and yield stress) were reported from the experimentally obtained data and the effects of shear rate as well as temperature on these properties were discussed in detail. In addition, several inelastic-viscoplastic flow models including a yield stress parameter were employed to make a quantitative evaluation of the steady shear flow behavior, and then the applicability of these models was examined by calculating the various material parameters (yield stress, consistency index and flow behavior index). Main findings obtained from this study can be summarized as follows : (1) At temperature range lower than $40^{\circ}C$, vaseline is regarded as a viscoplastic material having a finite magnitude of yield stress and its flow behavior beyond a yield stress shows a shear-thinning (or pseudo-plastic) feature, indicating a decrease in steady shear viscosity as an increase in shear rate. At this temperature range, the flow curve of vaseline has two inflection points and the first inflection point occurring at relatively lower shear rate corresponds to a static yield stress. The static yield stress of vaseline is decreased with increasing temperature and takes place at a lower shear rate, due to a progressive breakdown of three dimensional network structure. (2) At temperature range higher than $45^{\circ}C$, vaseline becomes a viscous liquid with no yield stress and its flow character exhibits a Newtonian behavior, demonstrating a constant steady shear viscosity regardless of an increase in shear rate. With increasing temperature, vaseline begins to show a Newtonian behavior at a lower shear rate range, indicating that the microcrystalline structure is completely destroyed due to a synergic effect of high temperature and shear deformation. (3) Over a whole range of temperatures tested, the Herschel-Bulkley, Mizrahi-Berk, and Heinz-Casson models are all applicable and have an almostly equivalent ability to quantitatively describe the steady shear flow behavior of vaseline, whereas the Bingham, Casson,and Vocadlo models do not give a good ability.

• Animal Bioscience
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• v.35 no.10
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• pp.1499-1511
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• 2022

Objective: This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms. Methods: The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations. Results: The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period. Conclusion: Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.

• Economic and Environmental Geology
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• v.40 no.1 s.182
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• pp.103-113
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• 2007

The empirical USLE and the physically-based GeoWEPP which were distributed model linked with GIS (Geographical Information System) were applied to small natural catchment located in Icheon-si, Gyeonggi-do, South Korea. The results using by two models were total sediment yield from study catchment between January, 2004 and January, 2005. During the study period, the observed total sediment yield was 270.54 ton and the total sediment yield computed by USLE and GeoWEPP model were 358.1 ton and 283.30 ton, respectively. Each of results computed by USLE and GeoWEPP overestimated more than the observed total sediment yield, but, based on the results, the total sediment yield computed by GeoWEPP approximated to the observed result. We suggest that the reason why the total sediment yield using by models overestimated was that computed amounts by two models did not contain the amount of suspended sediment flowed over the weir.