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Books on the topic 'Coefficient of variation'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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1

United States. Environmental Protection Agency. Office of Radiation and Indoor Air, United States. Dept. of Energy. Office of Environmental Restoration, and United States. Environmental Protection Agency. Office of Air and Radiation, eds. Understanding variation in partition coefficient, Kd, values: A cooperative effort. [Washington, D.C.?]: U.S. Environmental Protection Agency, Office of Air and Radiation, 1999.

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2

George C. Marshall Space Flight Center., ed. The temperature variation of hydrogen diffusion coefficients in metal alloys. [Marshall Space Flight Center, Ala.]: National Aeronautics and Space Administration, George C. Marshall Space Flight Center, 1990.

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3

United States. Environmental Protection Agency. Office of Air Quality Planning and Standards, ed. Understanding Variation In Partition Coefficient, KD, Values... Volume II: Review Of Geochemistry And Available KD Values For Cadmium Chromium..., U.S. Environmental Protection Agency... Aug. 1998. [S.l: s.n., 1999.

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4

Forest Products Laboratory (U.S.), ed. Confidence bounds for normal and lognormal distribution coefficients of variation. [Madison, Wis.]: U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 2003.

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5

Verrill, S. P. Confidence bounds and hypothesis tests for normal distribution coefficients of variation. Madison, WI: USDA, Forest Service, Forest Products Laboratory, 2007.

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6

Manichev, Vladimir, Valentina Glazkova, and Кузьмина Анастасия. Numerical methods. The authentic and exact solution of the differential and algebraic equations in SAE systems of SAPR. ru: INFRA-M Academic Publishing LLC., 2016. http://dx.doi.org/10.12737/13138.

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In the manual classical numerical methods are considered and algorithms for the decision of systems of the ordinary differential equations (ODE), nonlinear and linear algebraic equations (NAU and LAU), and also ways of ensuring reliability and demanded accuracy of results of the decision. Ideas, which still not are stated are reflected in textbooks on calculus mathematics, namely: decision systems the ODE without reduction to a normal form of Cauchy resolved rather derivative, and refusal from any numerical an equivalent - nykh of transformations of the initial equations of mathematical models and is- the hodnykh of data because such transformations can change properties of models at a variation of coefficients in corresponding urav- neniyakh. It is intended for students, graduate students and teachers of higher education institutions in the direction of preparation "Informatics and computer facilities". The grant will also be useful for engineers and scientists on the corresponding specialties.

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7

Coefficient of Variation and Machine Learning Applications. Taylor & Francis Group, 2019.

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8

Bindu, K. Hima, M. Raghava, Nilanjan Dey, and C. Raghavendra Rao. Coefficient of Variation and Machine Learning Applications. CRC Press, 2019. http://dx.doi.org/10.1201/9780429296185.

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9

Coefficient of Variation and Machine Learning Applications. Taylor & Francis Group, 2019.

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10

Dey, Nilanjan, K. Hima Bindu, Raghava Morusupalli, and C. Raghavendra Rao. Coefficient of Variation and Machine Learning Applications. Taylor & Francis Group, 2019.

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11

Dey, Nilanjan, K. Hima Bindu, Raghava Morusupalli, and C. Raghavendra Rao. Coefficient of Variation and Machine Learning Applications. Taylor & Francis Group, 2019.

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12

Dey, Nilanjan, K. Hima Bindu, Raghava Morusupalli, and C. Raghavendra Rao. Coefficient of Variation and Machine Learning Applications. Taylor & Francis Group, 2019.

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13

Dey, Nilanjan, K. Hima Bindu, Raghava Morusupalli, and C. Raghavendra Rao. Coefficient of Variation and Machine Learning Applications. Taylor & Francis Group, 2021.

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14

Byars, Beverly J. Variation of the drag coefficient with wind and wave state. 1985.

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15

National Aeronautics and Space Administration (NASA) Staff. Temperature Variation of Hydrogen Diffusion Coefficients in Metal Alloys. Independently Published, 2018.

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16

Atlas of Fourier Coefficients of Diurnal Variation of FoF2; NBS Technical Note 142. Hassell Street Press, 2021.

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17

Kacorzyk, Piotr. Wartość gospodarcza okrywy roślinnej gleby w aspekcie nawożenia oraz zdolności retencyjnej płytki gleby górskiej. Publishing House of the University of Agriculture in Krakow, 2018. http://dx.doi.org/10.15576/978-83-66602-33-5.

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The aim of the study was to assess the impact of method management of mountain soil on the quantity and quality of waste water, and the amount of mineral nutrients it contains. I have analyzed the water, that was moved through the soil profiles of 0-20 cm and 0-40 cm depth. I have also evaluated the floristic composition, the productivity of grassland and arable land, and the use of fertilizers by vegetation and soil chemical properties. I have found that the type of plant cover of the soil had a significant effect on the amount and chemical composition of water moving through the soil profile. Arable land was characterized by an average of 5 percentage point higher drainage rates compared to meadows. The smallest outflow of water from the soil was found in the first research period (intensive vegetation), and the largest in the third period (non-vegetation). The largest amount of the mineral content carried out annually with a soaking water, was observed on the arable land and was on average more than 2 times larger than on other fertilizers. This evidenced by the greater variation in the composition of floristic vegetation and its productivity. Between 0-20 cm and 0-40 cm of soil profiles, significant differences in the amount of waste water and mineral components were observed. The water drainage coefficient from the shallow profile was on average 9 percentage points higher than from the deeper profile. The amount of the sum of mineral loads, excluding calcium from the shallow soil profile was 94,5% higher than the sum of loads taken from the deeper soil profile. In the unused meadow the improvement of soil chemical properties was observed. There was an increase in pH, and the accumulation of minerals resulted from the positive balance of most of the ingredients.

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18

Henriksen, Niels Engholm, and Flemming Yssing Hansen. Rate Constants, Reactive Flux. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805014.003.0005.

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This chapter discusses a direct approach to the calculation of the rate constant k(T) that bypasses the detailed state-to-state reaction cross-sections. The method is based on the calculation of the reactive flux across a dividing surface on the potential energy surface. Versions based on classical as well as quantum mechanics are described. The classical version and its relation to Wigner’s variational theorem and recrossings of the dividing surface is discussed. Neglecting recrossings, an approximate result based on the calculation of the classical one-way flux from reactants to products is considered. Recrossings can subsequently be included via a transmission coefficient. An alternative exact expression is formulated based on a canonical average of the flux time-correlation function. It concludes with the quantum mechanical definition of the flux operator and the derivation of a relation between the rate constant and a flux correlation function.

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19

Sullivan's New Hydraulics: Consisting of New Hydraulic Formulas and the Rational Law of Variation of Coefficients. Flow and Resistance to Flow in All ... Fire Hose, Hydraulic Giants, Power Mains, No. Nabu Press, 2010.

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20

Dussaule, Jean-Claude, Martin Flamant, and Christos Chatziantoniou. Function of the normal glomerulus. Edited by Neil Turner. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0044_update_001.

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Glomerular filtration, the first step leading to the formation of primitive urine, is a passive phenomenon. The composition of this primitive urine is the consequence of the ultrafiltration of plasma depending on renal blood flow, on hydrostatic pressure of glomerular capillary, and on glomerular coefficient of ultrafiltration. Glomerular filtration rate (GFR) can be precisely measured by the calculation of the clearance of freely filtrated exogenous substances that are neither metabolized nor reabsorbed nor secreted by tubules: its mean value is 125 mL/min/1.73 m² in men and 110 mL/min/1.73 m² in women, which represents 20% of renal blood flow. In clinical practice, estimates of GFR are obtained by the measurement of creatininaemia followed by the application of various equations (MDRD or CKD-EPI) and more recently by the measurement of plasmatic C-cystatin. Under physiological conditions, GFR is a stable parameter that is regulated by the intrinsic vascular and tubular autoregulation, by the balance between paracrine and endocrine agents acting as vasoconstrictors and vasodilators, and by the effects of renal sympathetic nerves. The mechanisms controlling GFR regulation are complex. This is due to the variety of vasoactive agents and their targets, and multiple interactions between them. Nevertheless, the relative stability of GFR during important variations of systemic haemodynamics and volaemia is due to three major operating mechanisms: autoregulation of the afferent arteriolar resistance, local synthesis and action of angiotensin II, and the sensitivity of renal resistance vessels to respond to NO release.

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