Academic literature on the topic 'Ratio type estimator'

In this article, we have proposed a generalized estimator for mean estimation by combining the ratio and regression methods of estimation in the presence of auxiliary information using systematic sampling. We incorporated some robust parameters of the auxiliary variable to obtain precise estimates of the proposed estimator. The mathematical expressions for bias and mean square error of proposed the estimator are derived under large sample approximation. Many other generalized ratio and product-type estimators are obtained from the proposed estimator using different choices of scalar constants. Some special cases are also discussed in which the proposed generalized estimator reduces to the usual mean, classical ratio, product, and regression type estimators. Mathematical conditions are obtained for which the proposed estimator will perform more precisely than the challenging estimators mentioned in this article. The efficiency of the proposed estimator is evaluated using four populations. Results showed that the proposed estimator is efficient and useful for survey sampling in comparison to the other existing estimators.

In this article, a new robust ratio type estimator using the Uk’s redescending M-estimator is proposed for the estimation of the finite population mean in the simple random sampling (SRS) when there are outliers in the dataset. The mean square error (MSE) equation of the proposed estimator is obtained using the first order of approximation and it has been compared with the traditional ratio-type estimators in the literature, robust regression estimators, and other existing redescending M-estimators. A real-life data and simulation study are used to justify the efficiency of the proposed estimators. It has been shown that the proposed estimator is more efficient than other estimators in the literature on both simulation and real data studies.

A chain ratio-type estimator is proposed for the estimation of finite population mean under systematic sampling scheme using two auxiliary variables. The mean square error of the proposed estimator is derived up to the first order of approximation and is compared with other relevant existing estimators. To illustrate the performances of the different estimators in comparison with the usual simple estimator, we have taken a real data set from the literature of survey sampling.

Auxiliary variable is commonly used in survey sampling to improve the precision of estimates. Whenever there is auxiliary information available, we want to utilize it in the method of estimation to obtain the most efficient estimator. In this paper using multiauxiliary information we have proposed estimators based on geometric and harmonic mean. It was also shown that estimators based on harmonic mean and geometric mean are less biased than Olkin (1958) and Singh (1967) estimators under certain conditions. However, the MSE of Olkin (1958) estimator and geometric and harmonic estimators are same up to the first order of approximations.

Abstract In this paper we have proposed a class of modified ratio type variance estimators for estimation of population variance of the study variable using the known parameters of the auxiliary variable. The bias and mean squared error of the proposed estimators are obtained and also derived the conditions for which the proposed estimators perform better than the traditional ratio type variance estimator and existing modified ratio type variance estimators. Further we have compared the proposed estimators with that of the traditional ratio type variance estimator and existing modified ratio type variance estimators for certain natural populations.

We suggest an estimator using two auxiliary variables for the estimation of the unknown population variance. The bias and the mean square error of the proposed estimator are obtained to the first order of approximations. In addition, the problem is extended to two-phase sampling scheme. After theoretical comparisons, as an illustration, a numerical comparison is carried out to examine the performance of the suggested estimator with several estimators.

This paper deals with the assessment of finite population mean. An estimator is suggested for estimation of finite population mean of study variable. The purpose of this study is to evolve a ratio-type estimator to enhance the proficiency of the existing estimators considered in the study in sample random sampling without replacement using information of auxiliary variable. Expressions of the bias and mean square error (MSE) of the proposed estimator was derived by Taylor series method. The efficiency conditions under which the proposed ratio-type estimator is better than sample mean, ratio estimator, and other estimators considered in this study have been established. Theoretical and empirical findings are incentive and brace the robustness of the proposed estimator for mean estimation. The empirical results shown that the suggested estimator is more efficient than the sample mean, ratio estimator and other estimators.

This article examines the issue of population mean estimation utilizing past and present data in the form of an exponentially weighted moving average (EWMA) statistic under simple random sampling (SRS). We suggest memory-type logarithmic estimators and derive their properties, such as mean-square error (MSE) and bias up to a first-order approximation. Using the EWMA statistic, the conventional and novel memory-type estimators are compared. Real and artificial populations are used as examples to illustrate the theoretical findings. According to the empirical findings, memory-type logarithmic estimators are superior to the conventional mean estimator, ratio estimator, product estimator, logarithmic-type estimator, and memory-type ratio and product estimators.

In this manuscript, we study the problem of separate type exponential ratio estimator for estimation of population mean with their properties. The MSE and Bias up to the first degree of approximation for the suggested estimator are computed. The suggested estimator is proven to be more efficient than estimators mentioned in the literature under stratified random technique. An empirical investigation was done to assess the suggested estimator. Also, the percent relative efficiency is to be remarkable for the proposed estimator.

Estimation of population parameters have been a challenging aspect in sample survey for sometimes and many efforts have been made to enhance the exactness of the parameters of these estimators. We suggested the logarithmic-product-cum-ratio type estimator. Expression of the MSE of the intended estimator originated using the Taylor series technique. A numerical illustration was conducted and the results revealed that the modified work is ameliorated than sample means with other estimators observed.

碩士
國立成功大學
統計學系碩博士班
92
The inference of ratio-typed random variables occurred often in different application situations,for example calibration, critical dosage,relative potency, etc. Estimation of failure time distribution in linear degradation model with random intercept and slope also involves ratio of two random variables. Bernstein model has been established in degradation analysis in estimating a time-to-failure distribution. In this work, we study the approaches of Wald and maximum likelihood, compared with Bernstein distribution, in estimation and making inference of ratio-typed quantity of interest. Profile likelihood is used to construct confidence interval in likelihood approach.The distribution of the ratio of bivariate normally distributed random variables is discussed by Hinkley (1969),it provides an exact and correct distribution of Bernstein model when the assumption of positive slope is not hold.

The microstructure of polyolefins determines their macroscopic properties. Consequently, it is essential to predict how polymerization conditions will affect polyolefin microstructure. The most important microstructural distributions of ethylene/alfa-olefin copolymers made with coordination catalysts are their molecular weight (MWD), chemical composition (CCD), and comonomer sequence length (CSLD). Several mathematical models have been developed to predict these microstructural distributions; reliable techniques to estimate parameters for these models, however, are still poorly developed, especially for catalysts that have multiple site types, such as heterogeneous Ziegler-Natta complexes. Most commercial polyolefins are made with heterogeneous Ziegler-Natta catalysts, which make polyolefins with broad MWD, CCD, and CSLD. This behavior is attributed to the presence of several active site types, leading to a final product that can be seen as a blend of polymers made on the different catalyst site types. The main objective of this project is to develop a methodology to estimate the most important parameters needed to describe the microstructure of ethylene/alfa-olefin copolymers made with these multiple site-type catalysts. To accomplish this objective, we developed the Integrated Deconvolution Estimation Model (IDEM). IDEM estimates ethylene/alf-olefin reactivity ratios for each site type in two-steps. In the first step, the copolymer MWD, measured by high-temperature gel permeation chromatography, is deconvoluted into several Flory’s most probable distributions to determine the number of site types and the weight fractions of copolymer made on each of them. In the second estimation step, the model uses the MWD deconvolution information to fit the copolymer triad distributions measured by 13C NMR and estimate the reactivity ratios per site type. This is the first time that MWD and triad distribution information is integrated to estimate the reactivity ratio per site type of multiple site-type catalysts used to make ethylene/alfa-olefin copolymers. IDEM was applied to two sets of ethylene-co-1-butene copolymers made with a commercial Ziegler-Natta catalyst, covering a wide range of 1-butene fractions. In the first set of samples (EBH), hydrogen was used as a chain transfer agent, whereas it was absent in the second set (EB). Comparison of the reactivity ratio estimates for the sets of samples permitted the quantification of the hydrogen effect on the reactivity ratios of the different site types present in the Ziegler-Natta catalyst used in this thesis. Since 13C NMR it is an essential analytical step in IDEM, triad distributions for the EB and EBH copolymers were measured in two different laboratories (Department of Chemistry at the University of Waterloo, and Dow Chemical Research Center at Freeport, Texas). IDEM was applied to both set of triad measurements to find out the effect of interlaboratory 13C NMR analysis on reactivity ratio estimation.

This chapter examines the search for a pattern of repetitive adaptive substitutions over evolutionary time. In contrast with the previous chapter, only a modest number of tests toward this aim have been proposed. The HKA and McDonald-Kreitman tests contrast the polymorphism to divergence ratio between different genomic classes (such as different genes or silent versus replacement sites within the same gene). These approaches can detect an excess of substitutions, which allows one to estimate the fraction of adaptive sites. This chapter reviews the empirical data on estimates of this fraction and discusses some of the sources of bias it its estimation. Over an even longer time scale, one can contrast the rate of change of sites in a sequence over a phylogeny. These tests require a rather special type of selection, wherein the same specific site (usually a codon) experiences multiple adaptive substitutions over a phylogeny, such as might occur in arms-race genes.

Bones are multifunctional passive organs of movement that supports soft tissue and directly attached muscles. They also protect internal organs and are a reserve of calcium, phosphorus and magnesium. Each bone is covered with periosteum, and the adjacent bone surfaces are covered by articular cartilage. Histologically, the bone is an organ composed of many different tissues. The main component is bone tissue (cortical and spongy) composed of a set of bone cells and intercellular substance (mineral and organic), it also contains fat, hematopoietic (bone marrow) and cartilaginous tissue. Bones are a tissue that even in adult life retains the ability to change shape and structure depending on changes in their mechanical and hormonal environment, as well as self-renewal and repair capabilities. This process is called bone turnover. The basic processes of bone turnover are: • bone modeling (incessantly changes in bone shape during individual growth) following resorption and tissue formation at various locations (e.g. bone marrow formation) to increase mass and skeletal morphology. This process occurs in the bones of growing individuals and stops after reaching puberty • bone remodeling (processes involve in maintaining bone tissue by resorbing and replacing old bone tissue with new tissue in the same place, e.g. repairing micro fractures). It is a process involving the removal and internal remodeling of existing bone and is responsible for maintaining tissue mass and architecture of mature bones. Bone turnover is regulated by two types of transformation: • osteoclastogenesis, i.e. formation of cells responsible for bone resorption • osteoblastogenesis, i.e. formation of cells responsible for bone formation (bone matrix synthesis and mineralization) Bone maturity can be defined as the completion of basic structural development and mineralization leading to maximum mass and optimal mechanical strength. The highest rate of increase in pig bone mass is observed in the first twelve weeks after birth. This period of growth is considered crucial for optimizing the growth of the skeleton of pigs, because the degree of bone mineralization in later life stages (adulthood) depends largely on the amount of bone minerals accumulated in the early stages of their growth. The development of the technique allows to determine the condition of the skeletal system (or individual bones) in living animals by methods used in human medicine, or after their slaughter. For in vivo determination of bone properties, Abstract 10 double energy X-ray absorptiometry or computed tomography scanning techniques are used. Both methods allow the quantification of mineral content and bone mineral density. The most important property from a practical point of view is the bone’s bending strength, which is directly determined by the maximum bending force. The most important factors affecting bone strength are: • age (growth period), • gender and the associated hormonal balance, • genotype and modification of genes responsible for bone growth • chemical composition of the body (protein and fat content, and the proportion between these components), • physical activity and related bone load, • nutritional factors: – protein intake influencing synthesis of organic matrix of bone, – content of minerals in the feed (CA, P, Zn, Ca/P, Mg, Mn, Na, Cl, K, Cu ratio) influencing synthesis of the inorganic matrix of bone, – mineral/protein ratio in the diet (Ca/protein, P/protein, Zn/protein) – feed energy concentration, – energy source (content of saturated fatty acids - SFA, content of polyun saturated fatty acids - PUFA, in particular ALA, EPA, DPA, DHA), – feed additives, in particular: enzymes (e.g. phytase releasing of minerals bounded in phytin complexes), probiotics and prebiotics (e.g. inulin improving the function of the digestive tract by increasing absorption of nutrients), – vitamin content that regulate metabolism and biochemical changes occurring in bone tissue (e.g. vitamin D3, B6, C and K). This study was based on the results of research experiments from available literature, and studies on growing pigs carried out at the Kielanowski Institute of Animal Physiology and Nutrition, Polish Academy of Sciences. The tests were performed in total on 300 pigs of Duroc, Pietrain, Puławska breeds, line 990 and hybrids (Great White × Duroc, Great White × Landrace), PIC pigs, slaughtered at different body weight during the growth period from 15 to 130 kg. Bones for biomechanical tests were collected after slaughter from each pig. Their length, mass and volume were determined. Based on these measurements, the specific weight (density, g/cm3) was calculated. Then each bone was cut in the middle of the shaft and the outer and inner diameters were measured both horizontally and vertically. Based on these measurements, the following indicators were calculated: • cortical thickness, • cortical surface, • cortical index. Abstract 11 Bone strength was tested by a three-point bending test. The obtained data enabled the determination of: • bending force (the magnitude of the maximum force at which disintegration and disruption of bone structure occurs), • strength (the amount of maximum force needed to break/crack of bone), • stiffness (quotient of the force acting on the bone and the amount of displacement occurring under the influence of this force). Investigation of changes in physical and biomechanical features of bones during growth was performed on pigs of the synthetic 990 line growing from 15 to 130 kg body weight. The animals were slaughtered successively at a body weight of 15, 30, 40, 50, 70, 90, 110 and 130 kg. After slaughter, the following bones were separated from the right half-carcass: humerus, 3rd and 4th metatarsal bone, femur, tibia and fibula as well as 3rd and 4th metatarsal bone. The features of bones were determined using methods described in the methodology. Describing bone growth with the Gompertz equation, it was found that the earliest slowdown of bone growth curve was observed for metacarpal and metatarsal bones. This means that these bones matured the most quickly. The established data also indicate that the rib is the slowest maturing bone. The femur, humerus, tibia and fibula were between the values of these features for the metatarsal, metacarpal and rib bones. The rate of increase in bone mass and length differed significantly between the examined bones, but in all cases it was lower (coefficient b <1) than the growth rate of the whole body of the animal. The fastest growth rate was estimated for the rib mass (coefficient b = 0.93). Among the long bones, the humerus (coefficient b = 0.81) was characterized by the fastest rate of weight gain, however femur the smallest (coefficient b = 0.71). The lowest rate of bone mass increase was observed in the foot bones, with the metacarpal bones having a slightly higher value of coefficient b than the metatarsal bones (0.67 vs 0.62). The third bone had a lower growth rate than the fourth bone, regardless of whether they were metatarsal or metacarpal. The value of the bending force increased as the animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. The rate of change in the value of this indicator increased at a similar rate as the body weight changes of the animals in the case of the fibula and the fourth metacarpal bone (b value = 0.98), and more slowly in the case of the metatarsal bone, the third metacarpal bone, and the tibia bone (values of the b ratio 0.81–0.85), and the slowest femur, humerus and rib (value of b = 0.60–0.66). Bone stiffness increased as animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. Abstract 12 The rate of change in the value of this indicator changed at a faster rate than the increase in weight of pigs in the case of metacarpal and metatarsal bones (coefficient b = 1.01–1.22), slightly slower in the case of fibula (coefficient b = 0.92), definitely slower in the case of the tibia (b = 0.73), ribs (b = 0.66), femur (b = 0.59) and humerus (b = 0.50). Bone strength increased as animals grew. Regardless of the growth point tested, bone strength was as follows femur > tibia > humerus > 4 metacarpal> 3 metacarpal> 3 metatarsal > 4 metatarsal > rib> fibula. The rate of increase in strength of all examined bones was greater than the rate of weight gain of pigs (value of the coefficient b = 2.04–3.26). As the animals grew, the bone density increased. However, the growth rate of this indicator for the majority of bones was slower than the rate of weight gain (the value of the coefficient b ranged from 0.37 – humerus to 0.84 – fibula). The exception was the rib, whose density increased at a similar pace increasing the body weight of animals (value of the coefficient b = 0.97). The study on the influence of the breed and the feeding intensity on bone characteristics (physical and biomechanical) was performed on pigs of the breeds Duroc, Pietrain, and synthetic 990 during a growth period of 15 to 70 kg body weight. Animals were fed ad libitum or dosed system. After slaughter at a body weight of 70 kg, three bones were taken from the right half-carcass: femur, three metatarsal, and three metacarpal and subjected to the determinations described in the methodology. The weight of bones of animals fed aa libitum was significantly lower than in pigs fed restrictively All bones of Duroc breed were significantly heavier and longer than Pietrain and 990 pig bones. The average values of bending force for the examined bones took the following order: III metatarsal bone (63.5 kg) <III metacarpal bone (77.9 kg) <femur (271.5 kg). The feeding system and breed of pigs had no significant effect on the value of this indicator. The average values of the bones strength took the following order: III metatarsal bone (92.6 kg) <III metacarpal (107.2 kg) <femur (353.1 kg). Feeding intensity and breed of animals had no significant effect on the value of this feature of the bones tested. The average bone density took the following order: femur (1.23 g/cm3) <III metatarsal bone (1.26 g/cm3) <III metacarpal bone (1.34 g / cm3). The density of bones of animals fed aa libitum was higher (P<0.01) than in animals fed with a dosing system. The density of examined bones within the breeds took the following order: Pietrain race> line 990> Duroc race. The differences between the “extreme” breeds were: 7.2% (III metatarsal bone), 8.3% (III metacarpal bone), 8.4% (femur). Abstract 13 The average bone stiffness took the following order: III metatarsal bone (35.1 kg/mm) <III metacarpus (41.5 kg/mm) <femur (60.5 kg/mm). This indicator did not differ between the groups of pigs fed at different intensity, except for the metacarpal bone, which was more stiffer in pigs fed aa libitum (P<0.05). The femur of animals fed ad libitum showed a tendency (P<0.09) to be more stiffer and a force of 4.5 kg required for its displacement by 1 mm. Breed differences in stiffness were found for the femur (P <0.05) and III metacarpal bone (P <0.05). For femur, the highest value of this indicator was found in Pietrain pigs (64.5 kg/mm), lower in pigs of 990 line (61.6 kg/mm) and the lowest in Duroc pigs (55.3 kg/mm). In turn, the 3rd metacarpal bone of Duroc and Pietrain pigs had similar stiffness (39.0 and 40.0 kg/mm respectively) and was smaller than that of line 990 pigs (45.4 kg/mm). The thickness of the cortical bone layer took the following order: III metatarsal bone (2.25 mm) <III metacarpal bone (2.41 mm) <femur (5.12 mm). The feeding system did not affect this indicator. Breed differences (P <0.05) for this trait were found only for the femur bone: Duroc (5.42 mm)> line 990 (5.13 mm)> Pietrain (4.81 mm). The cross sectional area of the examined bones was arranged in the following order: III metatarsal bone (84 mm2) <III metacarpal bone (90 mm2) <femur (286 mm2). The feeding system had no effect on the value of this bone trait, with the exception of the femur, which in animals fed the dosing system was 4.7% higher (P<0.05) than in pigs fed ad libitum. Breed differences (P<0.01) in the coross sectional area were found only in femur and III metatarsal bone. The value of this indicator was the highest in Duroc pigs, lower in 990 animals and the lowest in Pietrain pigs. The cortical index of individual bones was in the following order: III metatarsal bone (31.86) <III metacarpal bone (33.86) <femur (44.75). However, its value did not significantly depend on the intensity of feeding or the breed of pigs.

SummaryThis chapter discusses dataset characteristics that play a crucial role in many metalearning systems. Typically, they help to restrict the search in a given configuration space. The basic characteristic of the target variable, for instance, determines the choice of the right approach. If it is numeric, it suggests that a suitable regression algorithm should be used, while if it is categorical, a classification algorithm should be used instead. This chapter provides an overview of different types of dataset characteristics, which are sometimes also referred to as metafeatures. These are of different types, and include so-called simple, statistical, information-theoretic, model-based, complexitybased, and performance-based metafeatures. The last group of characteristics has the advantage that it can be easily defined in any domain. These characteristics include, for instance, sampling landmarkers representing the performance of particular algorithms on samples of data, relative landmarkers capturing differences or ratios of performance values and providing estimates of performance gains. The final part of this chapter discusses the specific dataset characteristics used in different machine learning tasks, including classification, regression, time series, and clustering.

Abstract Coffee is one of the most valuable commodity tree crops worldwide. However, it suffers from several devastating diseases and pests, for example coffee leaf rust and coffee berry borer, whose impact is being amplified by changing climatic conditions. Development of new adapted varieties remains a laborious effort by conventional breeding due to the long juvenile period in tree crops. Plant cell/tissue culture represents the ultimate method to produce large amounts of true-to-type healthy plants and of explants for mutation breeding. In fact, mutation induction combined with in vitro cell/tissue culture techniques has proved to be effective for developing improved cultivars of perennial crops. Prior to mutation breeding, cell and tissue radiosensitivity tests to various mutagens need to be performed, so that optimal treatments can be applied for large population development. Thus, different in vitro explants (plantlet, leaf, callus, embryogenic callus, globular and torpedo stage embryos) of Coffea arabica and Coffea canephora were exposed to different gamma-ray doses (0, 10, 15, 20, 40, 60 and 80 Gy). After 9-21 weeks incubation, a radiosensitivity test was conducted on the different explants and LD50 doses corresponding to 50% of viability or survival of callus, embryogenic callus, globular and torpedo stage embryos and 50% growth reduction (GR50) of shoot were also determined. Callus explants showed a relatively high radio-resistance (LD30-LD50 50-100 Gy) in comparison with entire plantlets or embryos (LD30-GR50 8-46 Gy). Globular embryo development into plantlets and also leaf area of irradiated plantlets were more severely affected by irradiation than other explants. It was possible to confirm the relative radio-resistance of unicellular explants compared with multicellular explants. Estimation of optimal mutation induction dosage range for various in vitro explants is important for tree crops, especially for coffee improvement.

Abstract To analyze the ripple effects of CO2 emissions from the introduction of renewable energy power plants, this study developed input–output tables for analysis of next-generation energy systems (IONGES). The results revealed that the environmental benefits obtained from investing in power plants of the same capacity vary significantly depending on the type of renewable energy. Using the IONGES, under assumptions of three carbon taxation methods (upstream, midstream, and downstream), we calculated the taxable CO2 emissions induced when producing each good or service and estimated the carbon tax burden associated with the final demand. We found that, in the upstream method, the taxation effects of one unit of carbon tax is concentrated in energy goods such as coal products and petroleum basic, while the effects are relatively dispersed in the downstream taxation method. If renewable energy is added to the government target level in 2030, taxable CO2 emissions will decrease by 12–13.3%. Compared with the upstream taxation method, in the midstream and downstream methods, the CO2 emissions induced by each final demand are distributed more evenly across various goods and services. Compared to the downstream taxation method, upstream taxation leads to higher CO2 emissions from exports, but lower CO2 emissions from household consumption. This is because energy-intensive industries such as machinery have high export ratios. We analyzed which expenditure categories contribute to the carbon tax burden associated with household consumption. In the case of upstream taxation, households mainly focus on reducing electricity consumption; in the case of downstream taxation, households reduce consumption of various energy-intensive goods and services.

AbstractOriginally, the concept of resilience refers to one’s capacity to cope with unexpected shocks and unpredictable situations. Originating from ecological theories, the approach has gained ground in social sciences. In the context of education, the concept has been applied to explain how disadvantaged students can overcome structural constraints and become educationally successful and socially mobile (Werner, E. E., Vulnerable but invincible: a longitudinal study of resilient children and youth. McGraw-Hill, New York, 1982; Masten A. S., American Psychologist 56: 227–238, 2001; Reid, R., Botterrill L. C., Australian Journal of Public Administration 72:31–40, 2013; Máté, D., Erdélyi Társadalom 13:43–55, 2015).This paper is based on the analysis of the Hungarian National Assessment of Basic Competences (NABC) database which has been conducted annually since 2001. We created a typology of school resilience based on the schools’ social and ethnic profile as well as their performance indicators. We defined those schools resilient which over perform others with similar social intake, and we also identified irresilient schools which underperform others with similar social intake. The school types were created by correlating the socio-economic status index (SES) and school performance.Since the NABC database provides us with data on the estimated rate of Roma students in each school, it is possible to take into account the schools’ ethnic intake in the analysis of resilience. We conducted statistical analyses to compare the performance of resilient and irresilient schools in the light of the ratio of Roma students. Finally, we seek answers to the question whether ethnic segregation correlates with school achievement in Hungary. We could identify some crucial institutional factors contributing to resilience (or school success) in the case of schools with relatively high proportion of Roma students.

Many existing aircraft engine diagnostic methods are based on linearized engine models. However, the dynamics of aircraft engines are highly nonlinear and rapidly changing. Future engine health management designs will benefit from new methods that are directly based on intrinsic nonlinearities of the engine dynamics. In this paper, a fault detection and isolation (FDI) method is developed for aircraft engines by utilizing nonlinear adaptive estimation and nonlinear observer techniques. Engine sensor faults, actuator faults and component faults are considered under one unified nonlinear framework. The fault diagnosis architecture consists of a fault detection estimator and a bank of nonlinear fault isolation estimators. The fault detection estimator is used for detecting the occurrence of a fault, while the bank of fault isolation estimators is employed to determine the particular fault type or location after fault detection. Each isolation estimator is designed based on the functional structure of a particular fault type under consideration. Specifically, adaptive estimation techniques are used for designing the isolation estimators for engine component faults and actuator faults, while nonlinear observer techniques are used for designing the isolation estimators for sensor faults. The FDI architecture has been integrated with the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) engine model developed by NASA researchers in recent years. The engine model is a realistic representation of the nonlinear aero thermal dynamics of a 90,000-pound thrust class turbofan engine with high-bypass ratio and a two-spool configuration. Representative simulation results and comparative studies are shown to verify the effectiveness of the nonlinear FDI method.

This paper addresses the methodology to estimate the effective thermal conductivity of the wiring board, where the metal wiring network is very complicated and then the thermal conductivity of the metal wiring is more than 1000 times higher than that of the resign board. Based on the concept of analogy between the electric and the thermal resistance network, two types of estimation equations are derived by dividing the composite system parallel or perpendicular to the heated/cooled surface. When the ratio of higher to lower thermal conductivities is less than 10, the estimated values by these equations agree with each other. However, the difference is clearly found between them when the ratio is larger than 100. The estimated values are moreover compared with the exact solutions, which are obtained by numerical simulation of heat transfer using Microsoft Excel, and then the applicability of the present estimation methodology is discussed. It is found that the thermal resistance network obtained by dividing the composite system perpendicular to the heated/cooled surface is effective to estimate the effective thermal conductivity of the composite system.

This paper provides two types of engineering J estimation equations for welded piping branch junctions with poor penetration crack under internal pressure. The first type is the so-called GE/EPRI type J estimation equation based on Ramberg-Osgood (R-O) materials. Based on detailed 3-D FE results using deformation plasticity, plastic influence functions for fully plastic J components are tabulated for practical ranges of the inner radius of brace to the inner radius of chord ratio, the thickness of brace to the thickness of chord, the thickness of chord to the inner radius of chord ratio, the crack depth to the thickness of chord ratio, the strain hardening index for the R-O material, and the location along the poor penetration crack front. Based on tabulated plastic influence functions, the GE/EPRI-type J estimation equation along the crack front is proposed. For more general application, the effective remote stress method based on GE/EPRI-type solutions is provided. This method provides a simpler equation for J, which could be used for any stress-strain relationship material, including Ramborg-Osgood (R-O) material and non-R-O materials under monotonic increasing loading. The proposed effective remote stress based J estimation equation is compared with elastic-plastic 3-D FE results using actual stress–strain data for a Type 304 strainless steel. Good agreement between the FE results and the proposed reference stress based J estimation provides confidence in the use of the proposed method for elastic-plastic fracture mechanics of pressurized welded piping branch junction.

Settlement of subsea structures is an important design consideration, yet it is typically estimated using empirical correlations. A total of 74 consolidation test results from deepwater projects are collected and analyzed to develop an empirical correlation for shallow depth (less than 20 m) deepwater clays in the Gulf of Mexico. Compression indexes with and without clay structural effects are separately considered. Most of the published empirical correlations are irrelevant to offshore clays and the commonly used empirical correlation that uses liquid limit could significantly underestimate the peak compression index of deepwater offshore clays. Initial void ratio is selected as an independent variable for peak compression index estimation. A power function type correlation is proposed between the peak compression index and initial void ratio. With the lower and upper bounds (±30 %), the proposed empirical correlation encompasses the majority of the peak compression index data considering the structural effects. The proposed correlation is applicable for deepwater clays in the Gulf of Mexico having initial void ratios between 1 and 4.

Compaction and sand migration are some of the main problems for the loosely consolidated and unconsolidated high rate gas reservoirs. A reliable estimation of the well productivity depends on accurate modeling of permeability and inertial effects. Therefore, the key objective of this paper is to quantify the flow parameters change in the case of compaction and sand migration, and the development of permeability and the non-Darcy coefficient correlations that can be used in reservoir simulations. The compaction effects are simulated by increasing grains diameters with the same ratio. Permeability and the non-Darcy coefficients are calculated from lattice Boltzmann method (LBM). Results indicate that permeability decrease is not directional and the change in permeability can be estimated from porosity change with a Kozeny-Carman type relation with an exponent of 3.2. A Kozeny-Carman type relation between the non-Darcy coefficient and permeability is also found with an exponent −1.303. For high compressibility reservoirs, estimation of the inertial effects from the correlations developed as a function of permeability and porosity may also lead to underestimation of the inertial effects. Sand migration causes pore-throat plugging that leads to significant reduction in permeability. Permeability impairment due to sand or fines migration is usually estimated from Kozeny-Carman type relation based on porosity. There is no study in the literature on how the inertial effects are changed with permeability impairment due to sand or fines migration. Sand particle plugging locations are found from the network simulations for different pore volume reduction, and corresponding permeability and the non-Darcy coefficient are calculated from LBM. It is found that permeability change with sand plugging is direction dependent: permeability reduction in the flow direction is twice compared to other directions. Porosity reduction does not depend on only pore-throat plugging, porosity can be decrease due to compaction and pore-surface deposition. Therefore, a correlation is developed to estimate permeability from pore-throat sand concentration. Even though permeability change is directional, the trend between permeability and the non-Darcy coefficient is similar and the magnitude of exponent in Kozeny-Carman type relation is larger, −1.803, compared to that of compaction.

Fault monitoring of the upstream universal exhaust gas oxygen (UEGO) sensor, as mandated by the California air resources board (CARB), is a necessary action to maintain the performance of the operation of the air-fuel ratio (AFR) control system and indicate the need for maintenance when a fault is present which could potentially lead to exceeding the emissions limits. When the UEGO sensor fault is accurately diagnosed, i.e. fault is detected, direction is identified and magnitude is estimated, tuning of the controller gains can be performed accurately with minimal calibration efforts. Presented in this paper is a control strategy that utilizes the type, direction and magnitude of fault detected to adapt the gains of the controller and update the parameters of the Smith predictor (SP) in order to maintain the stability of AFR control loop. The proposed approach has been validated on a vehicle (Mustang V6 3.7L) equipped with ATI No-Hooks rapid prototyping system. Different fault types and magnitudes were tested and the tailpipe emissions were assessed on federal test procedure (FTP) cycles.

The Solar Load Ratio (SLR) method is a performance prediction algorithm for passive solar space heating systems developed at Los Alamos National Laboratory. Based on curve fits of detailed thermal simulations of buildings, the algorithm provides fast estimation of monthly solar savings fraction for direct gain, indirect gain (water wall and concrete wall) and sunspace systems of a range of designs. Parameters are not available for passive solar heat pipe systems, which are of the isolated gain type. While modern computers have increased the speed with which detailed simulations can be performed, the quick estimates generated by the SLR method are still useful for early building design comparisons and for educational purposes. With this in mind, the objective of this project was to develop SLR predictions for heat pipe systems, which use heat pipes for one-way transport of heat into the building. A previous thermal network was used to simulate the heat pipe system with Typical Meteorological Year (TMY3) weather data for 13 locations across the US, representing ranges of winter temperature and available sunshine. A range of (nonsolar) load-to-collector ratio LCR = 1–15 W/m2K was tested for each location. The thermal network, along with TMY3 data, provided monthly-average-daily absorbed solar radiation and building load to calculate SLR. Losses from the solar aperture in a heat pipe system are very low compared to conventional passive solar systems, thus the load-to-collector ratio of the solar aperture was neglected in these preliminary calculations. Likewise, nighttime insulation is unnecessary for a heat pipe system, and was not considered. An optimization routine was used to determine an exponential fit (the heart of the SLR method) to simulated monthly solar savings fraction (SSF) across all locations and LCR values. Accuracy of SSF predicted by SLR compared to the thermal network results was evaluated. The largest errors (up to 50%) occurred for months with small heating loads (< 80 K days), which inflated SSF. Limiting the optimization to the heating season (October to March), reduced the error in SSF to an average of 4.24% and a standard deviation of 5.87%. These results expand the applications of the SLR method to heat pipe systems, and allow building designers to use this method to estimate the thermal benefits of heat pipe systems along with conventional direct gain, indirect gain and sunspace systems.

Abstract Bonding to casing material characterization is a topic of interest in the context of well barrier evaluation. There is a consolidated need directed to log data interpreters to answer questions related to the type of material present in the casing annuli of a given well. The objective of this work is to explore the possibility to provide a complementary answer to current general acoustic impedance and attenuation practice. We reiterate that knowledge about the density of the annuli material can reduce the well barrier evaluation uncertainty. We are describing and exemplifying a rapid method to estimate the "pseudo – density" of the material in the annuli at the time of data acquisition. We define "pseudo-density" as the ratio between estimated impedance (from ultrasonic pulse-echo) and annuli apparent velocities (from ultrasonic oblique incidence techniques). Resulting "pseudo-density" maps are constrained with prior information from geology, logging, and drilling data. This allows the interpreter to judge the uncertainty in the current interpretation practice and contextualization of the annuli material into the borehole reality. The examples provided show that when the underlying physics principles are met, the results are clear and a robust interpretation at scale along the entire logged path is possible. The estimated complementary results are affected by inherent errors and uncertainty associated with acoustic impedance and velocity estimation. However, using prior knowledge information, intervals with high uncertainty (such as unusually high impedances or large errors in the velocity estimation) are flagged providing the interpreter with information background easy to be used for final delivery. Along with standard applications, the proposed method includes the basic mandatory tool for evaluating, validating, and incorporating the forecasted growth based on nuclear integrity logging behind the casing evaluation techniques.

Testing normality against discrete normal mixtures is complex because some parameters turn increasingly underidentified along alternative ways of approaching the null, others are inequality constrained, and several higher-order derivatives become identically 0. These problems make the maximum of the alternative model log-likelihood function numerically unreliable. We propose score-type tests asymptotically equivalent to the likelihood ratio as the largest of two simple intuitive statistics that only require estimation under the null. One novelty of our approach is that we treat symmetrically both ways of writing the null hypothesis without excluding any region of the parameter space. We derive the asymptotic distribution of our tests under the null and sequences of local alternatives. We also show that their asymptotic distribution is the same whether applied to observations or standardized residuals from heteroskedastic regression models. Finally, we study their power in simulations and apply them to the residuals of Mincer earnings functions.

Review question / Objective: This study aimed to evaluate the relationship between NLR and in-hospital or long-term prognosis of patients with heart failure by meta-analysis. Eligibility criteria: Inclusion criteria: (1) Patients with heart failure who underwent NLR measurement ;the study types were prospective cohort study or retrospective cohort study; and (3) risk estimates of association between NLR levels and heart failure related events occurring during hospital or follow-up were studied experimentally. Case reports, reviews, animal studies, conference proceedings, letters to editors, abstract only and duplicated studies were excluded.

Review question / Objective: The present study aimed to comprehensively explore the relationship between CD155 expression and clinical characteristics and prognosis of cancer patients. The study was based on comprehensive search of relevant literature. In particular, the study attempted to define the role of CD155 in various cancer types. Eligibility criteria: The pre-established inclusion criteria were as follows: (1) all subjects were cancer patients who received standard treatment; (2) The expression of CD155 in the cancer patients was well-examined, and all patients were assigned into two groups based on the expression; (3) survival analysis was performed based on these two groups, and provided sufficient data to estimate the risk ratio (HR) and 95% confidence interval (CI) for overall survival (OS); and (4) scientific and reasonable research. Case reports, reviews, abstracts, letters, bioinformatic analysis, TCGA analysis, and articles that did not meet the inclusion criteria were excluded from analyses.

Computers have become a vital part of the control of pipeline compressors and compressor stations. For many tasks, computers have helped to improve accuracy, reliability, and safety, and have reduced operating costs. Computers excel at repetitive, precise tasks that humans perform poorly - calculation, measurement, statistical analysis, control, etc. Computers are used to perform these type of precise tasks at compressor stations: engine / turbine speed control, ignition control, horsepower estimation, or control of complicated sequences of events during startup and/or shutdown. For other tasks, however, computers perform very poorly at tasks that humans find to be trivial. A discussion of the differences in the way humans and computer process information is crucial to an understanding of the field of artificial intelligence. In this project, several artificial intelligence/ intelligent control systems were examined: heuristic search techniques, adaptive control, expert systems, fuzzy logic, neural networks, and genetic algorithms. Of these, neural networks showed the most potential for use on large bore engines because of their ability to recognize patterns in incomplete, noisy data. Two sets of experimental tests were conducted to test the predictive capabilities of neural networks. The first involved predicting the ignition timing from combustion pressure histories; the best networks responded within a specified tolerance level 90% to 98.8% of the time. In the second experiment, neural networks were used to predict NOx, A/F ratio, and fuel consumption. NOx prediction accuracy was 91.4%, A/F ratio accuracy was 82.9%, and fuel consumption accuracy was 52.9%. This report documents the assessment of the state of the art of artificial intelligence for application to the monitoring and control of large-bore natural gas engines.

The objectives of this project were to predict the performance of naturally and fan-ventilated greenhouses as a function of climate, type of crop, evaporative cooling and greenhouse size, and to estimate the effects of the two cooling systems on yield, quality and disease development in the different crops under study. Background In the competitive field of greenhouse cultivation, growers and designers in both the US and Israel are repeatedly forced to choose between naturally ventilated (NV) and fan ventilated (FV) cooling systems as they expand their ranges in an effort to remain profitable. The known advantages and disadvantages of each system do not presently allow a clear decision. Whether essentially zero operating costs can offset the less dependable cooling of natural ventilation systems is question this report hopes to answer. Major Conclusions US It was concluded very early on that FV greenhouses without evaporative pad cooling are not competitive with NV greenhouses during hot weather. During the first year, the US team found that average air temperatures were always higher in the FV houses, compared to the NV houses, when evaporative pad cooling was not used, regardless of ventilation rate in the FV houses or the vent configuration in the NV houses. Canopy temperatures were also higher in the FV ventilated houses when three vents were used in the NV houses. A second major conclusion was that the US team found that low pressure fogging (4 atm) in NV houses does not completely offset the advantage of evaporative pad cooling in FV houses. High pressure fog (65 atm) is more effective, but considerably more expensive. Israel Experiments were done with roses in the years 2003-2005 and with tomatoes in 2005. Three modes of natural ventilation (roof, side and side + roof openings) were compared with a fan-ventilated (with evaporative cooling) house. It was shown that under common practice of fan ventilation, during summer, the ventilation rate is usually lower with NV than with FV. The microclimate under both NV and FV was not homogeneous. In both treatments there were strong gradients in temperature and humidity in the vertical direction. In addition, there were gradients that developed in horizontal planes in a direction parallel to the direction of the prevailing air velocity within the greenhouse. The gradients in the horizontal direction appear to be larger with FV than with NV. The ratio between sensible and latent heat fluxes (Bowen ratio) was found to be dependent considerably on whether NV or FV is applied. This ratio was generally negative in the naturally ventilated house (about -0.14) and positive in the fan ventilated one (about 0.19). Theoretical models based on Penman-Monteith equation were used to predict the interior air and crop temperatures and the transpiration rate with NV. Good agreement between the model and experimental results was obtained with regard to the air temperature and transpiration with side and side + roof ventilation. However, the agreement was poor with only roof ventilation. The yield (number of rose stems longer than 40 cm) was higher with FV

Original objectives and revisions The original objectives as stated in the approved proposal were: (1) To establish guidelines for the use of micrometeorological techniques as accurate, reliable and low-cost tools for continuous monitoring of whole canopy ET of common crops grown in large agricultural structures. (2) To adapt existing methods for protected cultivation environments. (3) To combine previously derived theoretical models of air flow and scalar fluxes in large agricultural structures (an outcome of our previous BARD project) with ET data derived from application of turbulent transport techniques for different crops and structure types. All the objectives have been successfully addressed. The study was focused on both screenhouses and naturally ventilated greenhouses, and all proposed methods were examined. Background to the topic Our previous BARD project established that the eddy covariance (EC) technique is suitable for whole canopy evapotranspiration measurements in large agricultural screenhouses. Nevertheless, the eddy covariance technique remains difficult to apply in the farm due to costs, operational complexity, and post-processing of data – thereby inviting alternative techniques to be developed. The subject of this project was: 1) the evaluation of four turbulent transport (TT) techniques, namely, Surface Renewal (SR), Flux-Variance (FV), Half-order Time Derivative (HTD) and Bowen Ratio (BR), whose instrumentation needs and operational demands are not as elaborate as the EC, to estimate evapotranspiration within large agricultural structures; and 2) the development of mathematical models able to predict water savings and account for the external environmental conditions, physiological properties of the plant, and structure properties as well as to evaluate the necessary micrometeorological conditions for utilizing the above turbulent transfer methods in such protected environments. Major conclusions and achievements The major conclusions are: (i) the SR and FV techniques were suitable for reliable estimates of ET in shading and insect-proof screenhouses; (ii) The BR technique was reliable in shading screenhouses; (iii) HTD provided reasonable results in the shading and insect proof screenhouses; (iv) Quality control analysis of the EC method showed that conditions in the shading and insect proof screenhouses were reasonable for flux measurements. However, in the plastic covered greenhouse energy balance closure was poor. Therefore, the alternative methods could not be analyzed in the greenhouse; (v) A multi-layered flux footprint model was developed for a ‘generic’ crop canopy situated within a protected environment such as a large screenhouse. The new model accounts for the vertically distributed sources and sinks within the canopy volume as well as for modifications introduced by the screen on the flow field and microenvironment. The effect of the screen on fetch as a function of its relative height above the canopy is then studied for the first time and compared to the case where the screen is absent. The model calculations agreed with field experiments based on EC measurements from two screenhouse experiments. Implications, both scientific and agricultural The study established for the first time, both experimentally and theoretically, the use of four simple TT techniques for ET estimates within large agricultural screenhouses. Such measurements, along with reliable theoretical models, will enable the future development of lowcost ET monitoring system which will be attainable for day-to-day use by growers in improving irrigation management.

Considering the importance of the transportation network and bridge structures, the associated seismic design philosophy is shifting from the basic collapse prevention objective to maintaining functionality on the community scale in the aftermath of moderate to strong earthquakes (i.e., resiliency). In addition to performance, the associated construction philosophy is also being modernized, with the utilization of accelerated bridge construction (ABC) techniques to reduce impacts of construction work on traffic, society, economy, and on-site safety during construction. Recent years have seen several developments towards the design of low-damage bridges and ABC. According to the results of conducted tests, these systems have significant potential to achieve the intended community resiliency objectives. Taking advantage of such potential in the standard design and analysis processes requires proper modeling that adequately characterizes the behavior and response of these bridge systems. To evaluate the current practices and abilities of the structural engineering community to model this type of resiliency-oriented bridges, the Pacific Earthquake Engineering Research Center (PEER) organized a blind prediction contest of a two-column bridge bent consisting of columns with enhanced response characteristics achieved by a well-balanced contribution of self-centering, rocking, and energy dissipation. The parameters of this blind prediction competition are described in this report, and the predictions submitted by different teams are analyzed. In general, forces are predicted better than displacements. The post-tension bar forces and residual displacements are predicted with the best and least accuracy, respectively. Some of the predicted quantities are observed to have coefficient of variation (COV) values larger than 50%; however, in general, the scatter in the predictions amongst different teams is not significantly large. Applied ground motions (GM) in shaking table tests consisted of a series of naturally recorded earthquake acceleration signals, where GM1 is found to be the largest contributor to the displacement error for most of the teams, and GM7 is the largest contributor to the force (hence, the acceleration) error. The large contribution of GM1 to the displacement error is due to the elastic response in GM1 and the errors stemming from the incorrect estimation of the period and damping ratio. The contribution of GM7 to the force error is due to the errors in the estimation of the base-shear capacity. Several teams were able to predict forces and accelerations with only moderate bias. Displacements, however, were systematically underestimated by almost every team. This suggests that there is a general problem either in the assumptions made or the models used to simulate the response of this type of bridge bent with enhanced response characteristics. Predictions of the best-performing teams were consistently and substantially better than average in all response quantities. The engineering community would benefit from learning details of the approach of the best teams and the factors that caused the models of other teams to fail to produce similarly good results. Blind prediction contests provide: (1) very useful information regarding areas where current numerical models might be improved; and (2) quantitative data regarding the uncertainty of analytical models for use in performance-based earthquake engineering evaluations. Such blind prediction contests should be encouraged for other experimental research activities and are planned to be conducted annually by PEER.

The geology of the Montney Formation and the geochemistry of its produced fluids, including nonhydrocarbon gases such as hydrogen sulfide were investigated for both Alberta and BC play areas. Key parameters for understanding a complex petroleum system like the Montney play include changes in thickness, depth of burial, mass balance calculations, timing and magnitudes of paleotemperature exposure, as well as kerogen concentration and types to determine the distribution of hydrocarbon composition, H2S concentrations and CO2 concentrations. Results show that there is first-, second- and third- order variations in the maturation patterns that impact the hydrocarbon composition. Isomer ratio calculations for butane and propane, in combination with excess methane estimation from produced fluids, are powerful tools to highlight effects of migration in the hydrocarbon distribution. The present-day distribution of hydrocarbons is a result of fluid mixing between hydrocarbons generated in-situ with shorter-chained hydrocarbons (i.e., methane) migrated from deeper, more mature areas proximal to the deformation front, along structural elements like the Fort St. John Graben, as well as through areas of lithology with higher permeability. The BC Montney play appears to have hydrocarbon composition that reflects a larger contribution from in-situ generation, while the Montney play in Alberta has a higher proportion of its hydrocarbon volumes from migrated hydrocarbons. Hydrogen sulphide is observed to be laterally discontinuous and found in discrete zones or pockets. The locations of higher concentrations of hydrogen sulphide do not align with the sulphate-rich facies of the Charlie Lake Formation but can be seen to underlie areas of higher sulphate ion concentrations in the formation water. There is some alignment between CO2 and H2S, particularly south of Dawson Creek; however, the cross-plot of CO2 and H2S illustrates some deviation away from any correlation and there must be other processes at play (i.e., decomposition of kerogen or carbonate dissolution). The sources of sulphur in the produced H2S were investigated through isotopic analyses coupled with scanning electron microscopy, energy dispersive spectroscopy, and mineralogy by X-ray diffraction. The Montney Formation in BC can contain small discrete amounts of sulphur in the form of anhydrite as shown by XRD and SEM-EDX results. Sulphur isotopic analyses indicate that the most likely source of sulphur is from Triassic rocks, in particular, the Charlie Lake Formation, due to its close proximity, its high concentration of anhydrite (18-42%), and the evidence that dissolved sulphate ions migrated within the groundwater in fractures and transported anhydrite into the Halfway Formation and into the Montney Formation. The isotopic signature shows the sulphur isotopic ratio of the anhydrite in the Montney Formation is in the same range as the sulphur within the H2S gas and is a lighter ratio than what is found in Devonian anhydrite and H2S gas. This integrated study contributes to a better understanding of the hydrocarbon system for enhancing the efficiency of and optimizing the planning of drilling and production operations. Operators in BC should include mapping of the Charlie Lake evaporites and structural elements, three-dimensional seismic and sulphate ion concentrations in the connate water, when planning wells, in order to reduce the risk of encountering unexpected souring.

In this work multispectral reflectance images are used in conjunction with a neural network classifier for the purpose of detecting and classifying weeds under real field conditions. Multispectral reflectance images which contained different combinations of weeds and crops were taken under actual field conditions. This multispectral reflectance information was used to develop algorithms that could segment the plants from the background as well as classify them into weeds or crops. In order to segment the plants from the background the multispectrial reflectance of plants and background were studied and a relationship was derived. It was found that using a ratio of two wavelenght reflectance images (750nm and 670nm) it was possible to segment the plants from the background. Once ths was accomplished it was then possible to classify the segmented images into weed or crop by use of the neural network. The neural network developed for this work is a modification of the standard learning vector quantization algorithm. This neural network was modified by replacing the time-varying adaptation gain with a constant adaptation gain and a binary reinforcement function. This improved accuracy and training time as well as introducing several new properties such as hill climbing and momentum addition. The network was trained and tested with different wavelength combinations in order to find the best results. Finally, the results of the classifier were evaluated using a pixel based method and a block based method. In the pixel based method every single pixel is evaluated to test whether it was classified correctly or not and the best weed classification results were 81% and its associated crop classification accuracy is 57%. In the block based classification method, the image was divided into blocks and each block was evaluated to determine whether they contained weeds or not. Different block sizes and thesholds were tested. The best results for this method were 97% for a block size of 8 inches and a pixel threshold of 60. A simulation model was developed to 1) quantify the effectiveness of a site-specific sprayer, 2) evaluate influence of diffeent design parameters on efficiency of the site-specific sprayer. In each iteration of this model, infected areas (weed patches) in the field were randomly generated and the amount of required herbicides for spraying these areas were calculated. The effectiveness of the sprayer was estimated for different stain sizes, nozzle types (conic and flat), nozzle sizes and stain detection levels of the identification system. Simulation results indicated that the flat nozzle is much more effective as compared to the conic nozzle and its relative efficiency is greater for small nozzle sizes. By using a site-specific sprayer, the average ratio between the spraying areas and the stain areas is about 1.1 to 1.8 which can save up to 92% of herbicides, especially when the proportion of the stain areas is small.