scholarly journals Effect of average diurnal barn airspace temperatures on prediction of their development during the day

2011 ◽  
Vol 59 (6) ◽  
pp. 161-166
Author(s):  
Gustav Chládek ◽  
Oto Hanuš ◽  
Daniel Falta
Keyword(s):  
Statistical Analysis ◽  
Polynomial Regression ◽  
Regression Equations ◽  
Degree Polynomial ◽  
Reliable Prediction ◽  
The Third ◽  
University Training ◽  
Diurnal Temperatures ◽  
The Relationship ◽  
Very High

A year-round (i.e. 365 days) experiment was performed at the Mendel University Training Farm in Žabčice, Czech Republic (GPS 49°0’51.967”N and 16°36’14.614”E, the altitude 179 m) with the aim to quantify the effect of the variation of average diurnal barn airspace temperatures on prediction of their changes during the day. Barn airspace temperatures were monitored daily in one-hour intervals and the recorded values were used for calculations of average diurnal temperatures. These were classified into 7 categories (i.e. below 0 °C; 0.1 to 5 °C; 5.1 to 10 °C; 10.1 to 15 °C; 15.1 to 20 °C; 20.1 to 25 °C and above 25 °C). Regarding this classification system, all differences between temperatures measured at identical hours but within various limits were statistically highly significant. The statistical analysis involved also the calculation of the third degree polynomial regression equations, which enabled to characterise the relationship between the temperature and the hour of measurement within the aforementioned categories of diurnal temperatures. Individual equations were markedly different and ranged from y = − 0.0019x3 + 0.0596x2 − 0.3797x − 1.2169 (for temperatures below 0 °C) to y = − 0.0108x3 + 0.3297x2 − 1.9367x + 24.3931 (for temperatures above 25 °C). Correlation coefficients (r) and coefficients of determination (R2) of these regression equations were generally very high and ranged from 0.872 to 0.976 and from 0.760 to 0.953, respectively. Regarding high values of both coefficients it can be concluded that the calculated equations enable a good and reliable prediction of the diurnal development of barn airspace temperatures.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals THE USE OF THE STOKES-STRUIK APPROXIMATION FOR WAVES OF FINITE HEIGHT

2011 ◽  
Vol 1 (6) ◽  
pp. 16
Author(s):  
L. E. Borgman ◽  
J. E. Chappelear
Keyword(s):  
Wave Profile ◽  
Third Order ◽  
The Third ◽  
Finite Height ◽  
Particle Velocities ◽  
Relationship Of ◽  
The Relationship ◽  
Permanent Form ◽  
Very High ◽  
Water Depths

A formal approximate solution is derived for the profile and velocity components of a wave with permanent form of finite height m moderate water depths. The approximation is carried to the third order, sufficiently far to represent all except the very high "design" waves. The relationship of the formulas to others found in the literature is discussed. The wavelengths and the coefficients in the third-order series for the wave profile, and the water particle velocities and local accelerations are tabulated for approximately 2000 waves. The depths, heights, and periods for the listed wave conditions vary respectively from 10 to 500 feet, 5 to 40 feet, and 4 to 20 seconds. The range of applicability of the theory is discussed and approximate limits estimated. As an aid in calculations, tables of the trigonometric and hyperbolic sines and cosines for integral multiples of the argument are included.

The relationship between the digestibility of a sward and the herbage consumption of grazing calves

1968 ◽  
Vol 70 (1) ◽  
pp. 47-51 ◽  
Author(s):  
J. Hodgson
Keyword(s):  
Food Intake ◽  
Linear Relationship ◽  
Full Range ◽  
Chromic Oxide ◽  
Regression Equations ◽  
Faecal Output ◽  
Herbage Intake ◽  
The Relationship ◽  
Very High

SUMMARYNitro-chalk was applied to S.23 ryegrass swards, at approximately monthly intervals, at two contrasting levels in 1961 and three levels in 1962. Steer calves, 3–6 months old, grazed in rotation round a series of four paddocks on each treatment. Paddocks were trimmed and fertilizer applied after each grazing. The herbage intakes of the calves were determined on three occasions in 1961 and four occasions in 1962. Faecal output was estimated by chromic oxide dilution. In vitro digestibility determinations were carried out on samples of herbage clipped from the swards.There was a close linear relationship between the digestibility of the herbage and the amount eaten, over the full range of digestibility encountered (68–82%). Regression equations calculated within seasons and fertilizer levels, and within years, did not differ significantly. The regressions of faecal output on herbage digestibility were not significantly different from zero.The observed relationship between herbage digestibility and herbage intake may reflect (a) the greater sensitivity of young ruminants than adult stock to changes in the digestibility of the diet, and (b) the reduced importance of the chemostatic control of food intake, except at very high levels of digestibility, in young rapidly growing animals.

scholarly journals Use of Modern Regression Analysis in the Dielectric Properties of Foods

Foods ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1472
Author(s):  
Yu-Kai Weng ◽  
Jiunyuan Chen ◽  
Ching-Wei Cheng ◽  
Chiachung Chen
Keyword(s):  
Regression Analysis ◽  
Dielectric Properties ◽  
Influencing Factors ◽  
Polynomial Regression ◽  
Treatment Method ◽  
Regression Equations ◽  
Constant Variance ◽  
Dependent Variables ◽  
Qualitative Variables ◽  
The Relationship

The dielectric properties of food materials is used to describe the interaction of foods with electromagnetic energy for food technology and engineering. To quantify the relationship between dielectric properties and influencing factors, regression analysis is used in our study. Many linear or polynomial regression equations are proposed. However, the basic assumption of the regression analysis is that data with a normal distribution and constant variance are not checked. This study uses sixteen datasets from the literature to derive the equations for dielectric properties. The dependent variables are the dielectric constant and the loss factor. The independent variables are the frequency, temperature, and moisture content. The dependent variables and frequency terms are transformed for regression analysis. The effect of other qualitative factors, such as treatment method and the position of subjects on dielectric properties, are determined using categorical testing. Then, the regression equations can be used to determine which influencing factors are important and which are not. The method can be used for other datasets of dielectric properties to classify influencing factors, including quantitative and qualitative variables.

Online Trajectory Generation of a 2 Link Robot in Presence of Obstacle

2012 ◽  
Vol 488-489 ◽  
pp. 1772-1776 ◽  
Author(s):  
Mahdi Esmaeilzadeh Abardeh ◽  
Alireza Akbarzadeh
Keyword(s):  
Pso Algorithm ◽  
Regression Equations ◽  
Robot Arm ◽  
Degree Polynomial ◽  
Fourth Degree ◽  
Sinusoidal Functions ◽  
Rectangular Obstacle ◽  
Full Factorial ◽  
The Relationship ◽  
Sinusoidal Function

Online coordination of multiple robots working on a single workstation requires special attention. In these applications it is generally necessary that the robot arm follow a desired path in workspace so that it does not crash with any obstacle or the other robots. In this paper a two link planar robot crossing a rectangular obstacle is considered. The proposed idea is to define the relationship between obstacle's dimensions and the required joints trajectories parameters which allow the robot to reach its destination in the presence of an obstacle. First, the desired path for robot avoiding the obstacle is defined using a fourth degree polynomial. Corresponding robot joints trajectories are defined using a sinusoidal function with four parameters. Next, Design of Experiments (DOE) technique is utilized. Three levels for width and length of the obstacle are used as input and a full factorial DOE with nine experiments is defined. Instead of using the inverse kinematics, Particle Swarm Optimization (PSO) algorithm is used to obtain parameters of the robot joint sinusoidal functions. A second degree regression is used to obtain the relationship between each of the four sinusoidal function parameters and the obstacle dimensions. The obtained regression equations allow online changes to the trajectory as obstacle dimensions change. Four case studies, different obstacle dimensions, are simulated using the two link robot. The results show that using the obtained relationships the robot reaches its desired destination, with high accuracy, while avoiding the obstacles.

scholarly journals How the Infestation Level of Varroa destructor Affects the Distribution Pattern of Multi-Infested Cells in Worker Brood of Apis mellifera

2020 ◽  
Vol 7 (3) ◽  
pp. 136 ◽  
Author(s):  
Ignazio Floris ◽  
Michelina Pusceddu ◽  
Alberto Satta
Keyword(s):  
Varroa Destructor ◽  
Prediction Models ◽  
Polynomial Regression ◽  
Management Strategies ◽  
Reproduction Rate ◽  
Regression Equations ◽  
Infestation Level ◽  
Mite Reproduction ◽  
Worker Brood ◽  
The Relationship

The mite Varroa destructor, the main ectoparasite of honey bees, is a threat to apiculture worldwide. Understanding the ecological interactions between Varroa and honeybees is fundamental for reducing mite impact in apiaries. This work assesses bee colonies with various Varroa infestation levels in apiaries to determine: (1) the relationship between multi-infested brood cells and brood infestation level, (2) the damage caused by Varroa to parasitized honey bee pupae, and (3) mite reproduction rate at various infestation levels. Data were collected from 19 worker brood combs, each from a different colony, ranging from 160 to 1725 (mean = 706) sealed cells per comb. Mite distribution was aggregated, ranging from about 2% to 74% infested cells per comb. The percentage of cells invaded by one, two, three, four, or more than four foundress mites, as a function of infestation level, was estimated by five highly significant (p < 0.0001) second-degree polynomial regression equations. The correction factors found could increase the precision of prediction models. Varroa fertility and adult bee longevity decreased as multi-infestation levels increased, and the implications of this relationship are discussed. Finally, these findings could improve sampling methods and the timing of mite treatments in apiaries, thus favoring sustainable management strategies.

DO SEED MOTHER’S SITES AFFECT THE QUALITY OF THE SEEDLINGS PRODUCED

2020 ◽  
Vol 8 (10) ◽  
pp. 15-20
Author(s):  
Mohamed M. Younis ◽  
Younis Saeed Al Bugg ◽  
Siham Thannon Hussein
Keyword(s):  
Statistical Analysis ◽  
Morphological Characteristics ◽  
Dry Weight ◽  
Stem Length ◽  
Root Weight ◽  
The Third ◽  
Wet Weight ◽  
Total Dry Weight ◽  
The Relationship

This experiment was conducted in (Zawita) area in Dohuk governorate / Iraq, and the morphological characteristics were studied by selecting four sites, four trees from each site, four sectors and, choosing twenty trees in each sector. Statistical analysis (RCBD) was done using the SPSS system. Through this study, it was found that Pinus brutia Ten. In Zawita, there is a clear effect on some morphological characteristics of the seedlings resulting from it. The first site was one of the best sites followed by the second site where he gave seedlings of good quality in terms of stem length with an average of 39.25 cm and the total weight of wet and dry seedlings with averages of 13.97 and 35.34 g respectively, and the third site was the lowest studied sites and gave seedlings of less quality than the rest of the sites where he scored Stem length averaged 23.06 cm while wet and dry weight was 7.68 and 22.17 g, respectively. As for the correlation between the variables, the relationship was positive and strong among all the variables except those between the length of the root and the rest of the variables except with the characteristic of the wet root weight. The highest correlation values were between total dry weight and total wet weight recording 0.960 and the lowest between the length of the root and the dry vegetative weight where the value was 0.070.

scholarly journals Research on dependence of fuel consumption on cargo weight in long-distance transport

2021 ◽  
Vol 18 (3) ◽  
pp. 264-273
Author(s):  
Kh. Kh. Khabibullozoda ◽  
N. K. Goriaev
Keyword(s):  
Statistical Analysis ◽  
Fuel Consumption ◽  
Operating Conditions ◽  
Regression Equations ◽  
Long Distance ◽  
Long Distance Transport ◽  
Long Time ◽  
The Relationship ◽  
Monitoring Devices ◽  
Distance Transport

Introduction. The current methodology for fuel consumption accounting in road vehicles has not been changed in terms of its quality for a long time. In the majority of transport enterprises of the Cheliabinsk Region, official methods for the regulation of fuel consumption are not used, which indicates the need to improve the fuel consumption accounting standards. The most significant differences between standardized and real consumption are related to transport work.Purpose of the experiment. The article aims to carry out a statistical analysis of the influence of cargo weight on fuel consumption in long-distance transport.Results of the experiment. In order to identify the dependence of cargo weight on fuel consumption in longdistance transport, a study is conducted on the statistical data on the operation of truck tractors at OOO Alliance Auto, one of the largest long-distance road carriers in the Cheliabinsk Region. The study is conducted on MercedesBenz Actros-1840 truck tractors equipped with fuel consumption monitoring devices and devices for determining axle loads. The cargo weigh is determined by subtracting the curb weight from the actual one according to the axle load data. Data on the values of the actual cargo weight and fuel consumption for each trip are recorded using the Fleet Board software and hardware complex; Excel and STATISTICA programs are used to calculate and construct the necessary graphs and regression equations. The statistical analysis performed makes it possible to establish the nature and indicators of the dependence of fuel consumption on cargo weight in long-distance transport. As a result, the relationship between the flow rate and the cargo weight is established; a confidence test is performed; and a regression equation is obtained.Conclusion. Analysis of the collected data shows that the dependence of fuel consumption for transport work by road trains with truck tractors Mercedes-Benz Actros-1840 on the cargo weight for the Russian operating conditions in long-distance transport is linear and amounts to 0.39 liters per 100 km for each ton of transported cargo.

scholarly journals Modeling of temporal development of population taking into account the situation of municipalities in the resettlement system (according to the example of the Tyumen Region)

2020 ◽  
Vol 26 (1) ◽  
pp. 215-227
Author(s):  
V. Dobryakova ◽  
A. Dobryakov
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Spatial Statistics ◽  
Network Data ◽  
Regression Equations ◽  
Temporal Development ◽  
Data Set ◽  
Regional Center ◽  
Definition Of ◽  
The Relationship

The work is devoted to application of spatial statistics and regression analysis tools in the ArcGIS Pro program. In this report we try to confirm two theories in the relationship between positional characteristics of municipalities and the temporal development of population: The farther the locality is from the main settlement of the territory, the faster it loses its own population. The farther the locality is from the main highways of the territory, the faster it loses its own population. The main aim of this article is to find the strictest definition of the type of correlation between such specific distances as the distance to the regional center, the distance to the nearest highway and the relative changes in the municipalities’ population, according to the example of the Tyumen region. A network data set was created to calculate the distances, it contains several elements: main roads, calculated centers of municipalities (CM), lines — distances from centers to the nearest road (“stops”). For the study we used information on changes of population for 4 periods: 1981–1990, 1990–2002, 2002–2010 and 2010–2018. The dependence was done by enumerating the degrees of distances. We considered that the dependence was selected in case the relevant correlation coefficient was the largest. For each chosen relationship, ArcGIS Pro performed a complete statistical analysis, based on the results, the significance of the model was identified, residual maps constructed, and regression equations calculated. All the models except the first period turned out to be significant, but they were displaced, which indicates the existence of some unexplored factors. In the context of the constructed models, it was assumed that the distance to the regional center is closely connected with an expansion of the population in the surrounding municipalities, but the expansion gets more the closer the municipal district is to Tyumen. The distance to the nearest highway is associated with a decrease of population, and the farther the municipality is from the highway, the more it loses population.

Monte Carlo Algorithms for Moments of Transition Arrays

1988 ◽  
Vol 102 ◽  
pp. 79-81
Author(s):  
A. Goldberg ◽  
S.D. Bloom
Keyword(s):  
Monte Carlo ◽  
State Vector ◽  
Basis Vector ◽  
Collective State ◽  
Dispersion Characteristics ◽  
Dipole Strength ◽  
The Third ◽  
Monte Carlo Algorithms ◽  
Third Moment ◽  
Very High

AbstractClosed expressions for the first, second, and (in some cases) the third moment of atomic transition arrays now exist. Recently a method has been developed for getting to very high moments (up to the 12th and beyond) in cases where a “collective” state-vector (i.e. a state-vector containing the entire electric dipole strength) can be created from each eigenstate in the parent configuration. Both of these approaches give exact results. Herein we describe astatistical(or Monte Carlo) approach which requires onlyonerepresentative state-vector |RV&gt; for the entire parent manifold to get estimates of transition moments of high order. The representation is achieved through the random amplitudes associated with each basis vector making up |RV&gt;. This also gives rise to the dispersion characterizing the method, which has been applied to a system (in the M shell) with≈250,000 lines where we have calculated up to the 5th moment. It turns out that the dispersion in the moments decreases with the size of the manifold, making its application to very big systems statistically advantageous. A discussion of the method and these dispersion characteristics will be presented.

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