Variances and Covariance Assessment of Liquid Water Content in Precipitating Warm Cloud | Chapter 8 | Research Updates in Mathematics and Computer Science Vol. 9

 

A shallow cloud of warm microphysics is used to analyze the subgrid variability of liquid water content. These turbulent flows are diagnosed by means of second-order moment transport equations for liquid water quantities. These equations show that liquid water variabilities are controlled by the production of the gradient of mean liquid water quantities and microphysical processes. The contributions (source or sink) of these different productions reflect the effects of the gradient of average quantities of liquid water content and microphysical processes on the evolution of liquid water variability. It emerges that cloud water variance is mainly produced by the cloud water gradient term and constantly destroyed by the effects of auto conversion and accretion processes. Inversely, the processes of rain droplet formation and growth contribute as the main source for the variance of precipitating water and the cloud water-precipitating water covariance. Microphysical depletion processes, notably cloud droplet evaporation and precipitable droplet sedimentation, act as sinks for liquid water variances and covariance. Finally, for rainwater variability, the gradient term may be less important, but it provides real support for the source or sink terms of microphysics. This work particularly highlights the subgrid variabilities associated with precipitating droplets. In particular, this work focuses on the subgrid variabilities associated with liquid water content. Incorporating a good parameterization of liquid water variances and cloud water-rainwater correlation in statistical schemes could improve rainwater formation, growth and loss processes in large-scale models.

 

 

Author(s) Details

Bakary Coulibaly

Laboratory of Computer Science and Mechanics, Université Félix Houphouét-Boigny, 22 BP 582, Abidjan 22, Cote d'Ivoire.

Emile Danho

Laboratory of Computer Science and Mechanics, Université Félix Houphouét-Boigny, 22 BP 582, Abidjan 22, Cote d'Ivoire.

N’dri Roger Djue

Laboratory of Computer Science and Mechanics, Université Félix Houphouét-Boigny, 22 BP 582, Abidjan 22, Cote d'Ivoire.

 

Please see the link:- https://doi.org/10.9734/bpi/rumcs/v9/12465F

Variances and Covariance Assessment of Liquid Water Content in Precipitating Warm Cloud | Chapter 8 | Research Updates in Mathematics and Computer Science Vol. 9

A shallow cloud of warm microphysics is used to analyze the subgrid variability of liquid water content. These turbulent flows are diagnosed by means of second-order moment transport equations for liquid water quantities. These equations show that liquid water variabilities are controlled by the production of the gradient of mean liquid water quantities and microphysical processes. The contributions (source or sink) of these different productions reflect the effects of the gradient of average quantities of liquid water content and microphysical processes on the evolution of liquid water variability. It emerges that cloud water variance is mainly produced by the cloud water gradient term and constantly destroyed by the effects of auto conversion and accretion processes. Inversely, the processes of rain droplet formation and growth contribute as the main source for the variance of precipitating water and the cloud water-precipitating water covariance. Microphysical depletion processes, notably cloud droplet evaporation and precipitable droplet sedimentation, act as sinks for liquid water variances and covariance. Finally, for rainwater variability, the gradient term may be less important, but it provides real support for the source or sink terms of microphysics. This work particularly highlights the subgrid variabilities associated with precipitating droplets. In particular, this work focuses on the subgrid variabilities associated with liquid water content. Incorporating a good parameterization of liquid water variances and cloud water-rainwater correlation in statistical schemes could improve rainwater formation, growth and loss processes in large-scale models.

 

Author (s) Details

 

Bakary Coulibaly
Laboratory of Computer Science and Mechanics, Université Félix Houphouét-Boigny, 22 BP 582, Abidjan 22, Cote d'Ivoire.

Bakary Coulibaly
Laboratory of Computer Science and Mechanics, Université Félix Houphouét-Boigny, 22 BP 582, Abidjan 22, Cote d'Ivoire.

N’dri Roger Djue
Laboratory of Computer Science and Mechanics, Université Félix Houphouét-Boigny, 22 BP 582, Abidjan 22, Cote d'Ivoire.

 

Please see the book here:- https://doi.org/10.9734/bpi/rumcs/v9/12465F.

Quantifying Uncertainty: Potential Medical Applications of the Heston Model of Financial Stochastic Volatility | Chapter 8 | Contemporary Perspective on Science, Technology and Research Vol. 3

The Heston Model, usual in financial markets to typify stochastic volatility, manage potentially suffice in accounting for the impact of volatility in the broad field of cure. This theoretical item highlights the potential uses of the Heston Model to quantify evaporation in healthcare, focusing on community health and pharmacology. Conceptually, the ability of the model to quantify instability could determine insight into complex medical processes accompanying variable instability. Rigorous testing hopeful required to decide the feasibility and validity of requesting a financial model to organic processes. Nonetheless, the hypothetical relations between commercial market volatility and evaporation in medicine merit further investigation. This theoretical article investigate a broad overview of likely applications of the Heston Model to the medical field.

Author(s) Details:

Thomas F. Heston,
Department of Medical Education and Clinical Sciences, Washington State University, Spokane, USA and Department of Family Medicine, University of Washington, Seattle, USA.

Please see the link here: https://stm.bookpi.org/CPSTR-V3/article/view/12920

Study on Zoomorphic Variation with Copulation Duration in Centrobolus | Chapter 14 | New Visions in Biological Science Vol. 8

 As a kind of syn-copula mate-guarding, Centrobolus usually has protracted copulation. In four species of the millipede genus Centrobolus, variations in copulation duration were calculated and examined. All four species had distinct mean copulation durations, however only two of them differed intra-specifically. Copulation duration coefficient of variation (CV) was different between C. inscriptus and C. anulatus (F=0.41490, d.f.=114, 7, p=0.04892), and copulation duration CV was different between C. fulgidus and C. anulatus (F=0.38912, d.f.=50, 7, p=0.04836). Copulation duration was vary within species, although it tended to be moderate and evolutionarily decisive (interspecifically). Male and female volumes were substantially linked (Spearman's Rho Calculator) with copulation duration (r=1, p=0, n=4, 4; 4, 4). Copulation length was shown to be strongly linked with size (volumes) when sex was accounted for (r=0.6655, r2=0.4429, p=0.004897, n=8, 8). Larger male and female physical sizes are linked to codependency.

Author(S) Details

Mark Cooper
School of Animal, Plant & Environmental Sciences, University of the Witwatersrand, Johannesburg 2050, South Africa

View Book:- https://stm.bookpi.org/NVBS-V8/article/view/5389

Study on Seizure Detection from the Features of EEG Signals | Chapter 8 | New Approaches in Engineering Research Vol. 16

 A seizure must be identified in order to support an epileptic patient's diagnosis and treatment. The goal of this study is to use an EEG signal to automatically detect epileptic episodes in a patient. The EEG signal is proven to be more favourable than other biological signals such as PET, MEG, MRI, and fMRI. The EEG signal that was recorded was first preprocessed. The EEG signal's features were then determined, and the signal was then classed as seizure or normal based on the calculated features. The highest performing characteristics were chosen from a comparison of features such as Mean, PSE (Power Spectral Entropy), variance, and energy. To confirm a robust feature vector, weighted combinations of these characteristics were obtained. We suggest a weighted mixture of variance and energy (in two specific frequency bands) as a composite characteristic in this research. We established a threshold for this composite feature, using which an EEG signal may be categorised as normal or seizure-like. The recommended feature composition provides up to 96.5 percent accuracy.

Author(S) Details

Anita Patil
Department of Electronics and Tele-Communication, Cummins College of Engineering for Women, Pune, India.

View Book:- https://stm.bookpi.org/NAER-V16/article/view/4061

Mathematical Statistics for Beginners | Book Publisher International

 A significant number of discrete and continuous probability distributions are already accessible. A probability distribution's mean, variance, skewness, and kurtosis are a collection of constants that can be used to describe its attributes and, in certain cases, to specify it. These constants are determined by the random variable's distribution. To find the mean, variance, skewness, and kurtosis of any probability distribution, extensive understanding of integration, differentiation, and summation is necessary. It's difficult to explain things to students who don't know much about math. Instead than using integration, differentiation, or summation procedures, this book developed and utilised universal equations to directly find mean, variance, skewness, and kurtosis. We derive and apply universal formulae for determining the characteristic function, Laplace transform, and moments of various distributions from the converted Chi-square family, generalised gamma family, generalised family of discrete distributions, and log type distributions. This book also includes generic equations for determining point and interval estimators of function of parameters, as well as identification of the best population in the converted Chi-square family, as well as the likelihood of correct identification. This book teaches you how to choose null and alternative hypotheses, calculate p-values, and make conclusions using a simple procedure.

Author(S) Details

M. Shafiqur Rahman
Department of Operations Management and Business Statistics College of Economics and Political Science Sultan Qaboos University Muscat, Sultanate of Oman.

View Book:- https://stm.bookpi.org/MSB/article/view/3779

Econometrics Panel Data and Dea in Practice Guide | Book Publisher International

 This text book is designed to address the basic econometrics demands of master's and graduate students in economics, finance, and other social sciences, as well as other advanced scholars in the field of social science and science. Non-statistical research professionals will find the statistical and mathematical applications used to be relatively difficult to understand. The author elucidates local study areas, with specific examples drawn from earlier studies in the areas of auditing, savings and credit cooperative societies, and Tropics County Government activities. The use of empirical approaches such as non-parametric and parametric analysis, as well as data envelopment analysis in Stata software, is heavily emphasised in making sense of the data obtained. The Gauss Markov theorem, functional forms, vector error correction models, time series analysis, unit root tests, panel data models, data envelopment analysis (DEA), and structural equation modelling are among the specific subjects discussed. The book also contains a wealth of inefficiency and efficiency measurement routines in Stata utilising the DEA technique. The cited illustrations in the text book primarily involve author research in the areas of auditing services and front-office banking services in savings and credit cooperative societies (Saccos), as well as efficiency measurement targeting County Governments departments' operations with a specific sample drawn from the Tropics of Kenya. The use of DEA to measure efficiency in departments like as schools, hospitals, corporations, and universities, among others, is a serious replacement for the time-honored and subjective balanced score card approach often used in enterprises. When it comes to structural equation modelling (SEM), a modern topic of study in the field of econometrics, researchers and students can rely on this book. The application of panel data is briefly explored in this guide book.

Author(s) Details

Leonard R. Lari
KCA University, Kenya. and Moi University, Kenya.

View Book:- https://stm.bookpi.org/EPDDPG/article/view/2130