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Kinder- und Jugendgewalt aus der Perspektive von Gesundheitsexperten

Kinder- und Jugendgewalt aus der Perspektive von Gesundheitsexperten

Carlus Alberto Oliveira Dos Santos; Aparecida Tharlla Leite de Caldas; Fernanda de Araújo T Campos

Verlag Unser Wissen
2024
pokkari
In Anbetracht der Rolle der Angeh rigen der Gesundheitsberufe bei der Diagnose von Kindesmissbrauch besteht das Ziel dieses Buches darin, die Angeh rigen der Gesundheitsberufe und verwandter Bereiche ber Gewalt gegen Kinder und Jugendliche aufzukl ren sowie die Kenntnisse von Medizin- und Zahnmedizinstudenten zu diesem Thema zu berpr fen, da sie kurz vor dem Eintritt in den Arbeitsmarkt stehen und eine grundlegende Rolle bei der Erkennung fr her klinischer Anzeichen von Missbrauch spielen.
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Child and youth violence from the perspective of health academics

Child and youth violence from the perspective of health academics

Carlus Alberto Oliveira Dos Santos; Aparecida Tharlla Leite de Caldas; Fernanda de Araújo T Campos

Our Knowledge Publishing
2024
pokkari
Given the role of health professionals in diagnosing child abuse, the aim of this book is to enlighten health professionals and related areas about violence against children and adolescents, as well as to check the knowledge of medical and dental students on the subject, since they are about to enter the job market and play a key role in recognizing the early clinical signs of abuse.
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La violenza infantile e giovanile dal punto di vista degli studiosi della salute

La violenza infantile e giovanile dal punto di vista degli studiosi della salute

Carlus Alberto Oliveira Dos Santos; Aparecida Tharlla Leite de Caldas; Fernanda de Araújo T Campos

Edizioni Sapienza
2024
pokkari
Considerato il ruolo degli operatori sanitari nella diagnosi di abuso sui minori, l'obiettivo di questo libro quello di illuminare gli operatori sanitari e i settori correlati sulla violenza contro i bambini e i giovani, nonch di verificare le conoscenze degli studenti di medicina e odontoiatria sull'argomento, dal momento che stanno per entrare nel mercato del lavoro e svolgono un ruolo fondamentale nel riconoscere i primi segni clinici di abuso.
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Distributions for Modeling Location, Scale, and Shape

Distributions for Modeling Location, Scale, and Shape

Robert A. Rigby; Mikis D. Stasinopoulos; Gillian Z. Heller; Fernanda De Bastiani

CRC Press
2019
sidottu
This is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book ‘Flexible Regression and Smoothing: Using GAMLSS in R’, [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and all the distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application.Key features: Describes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions. Comprehensive summary tables of the properties of the distributions. Discusses properties of distributions, including skewness, kurtosis, robustness and an important classification of tail heaviness. Includes mixed distributions which are continuous distributions with additional specific values with point probabilities. Includes many real data examples, with R code integrated in the text for ease of understanding and replication. Supplemented by the gamlss website.This book will be useful for applied statisticians and data scientists in selecting a distribution for a univariate response variable and modelling its dependence on explanatory variables, and to those interested in the properties of distributions.
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Flexible Regression and Smoothing

Flexible Regression and Smoothing

Mikis D. Stasinopoulos; Robert A. Rigby; Gillian Z. Heller; Vlasios Voudouris; Fernanda De Bastiani

CRC Press
2020
nidottu
This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent.In particular, the GAMLSS statistical framework enables flexible regression and smoothing models to be fitted to the data. The GAMLSS model assumes that the response variable has any parametric (continuous, discrete or mixed) distribution which might be heavy- or light-tailed, and positively or negatively skewed. In addition, all the parameters of the distribution (location, scale, shape) can be modelled as linear or smooth functions of explanatory variables. Key Features: Provides a broad overview of flexible regression and smoothing techniques to learn from data whilst also focusing on the practical application of methodology using GAMLSS software in R. Includes a comprehensive collection of real data examples, which reflect the range of problems addressed by GAMLSS models and provide a practical illustration of the process of using flexible GAMLSS models for statistical learning. R code integrated into the text for ease of understanding and replication. Supplemented by a website with code, data and extra materials. This book aims to help readers understand how to learn from data encountered in many fields. It will be useful for practitioners and researchers who wish to understand and use the GAMLSS models to learn from data and also for students who wish to learn GAMLSS through practical examples.
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Distributions for Modeling Location, Scale, and Shape

Distributions for Modeling Location, Scale, and Shape

Robert A. Rigby; Mikis D. Stasinopoulos; Gillian Z. Heller; Fernanda De Bastiani

Taylor Francis Ltd
2021
nidottu
This is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book ‘Flexible Regression and Smoothing: Using GAMLSS in R’, [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and all the distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application.Key features: Describes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions. Comprehensive summary tables of the properties of the distributions. Discusses properties of distributions, including skewness, kurtosis, robustness and an important classification of tail heaviness. Includes mixed distributions which are continuous distributions with additional specific values with point probabilities. Includes many real data examples, with R code integrated in the text for ease of understanding and replication. Supplemented by the gamlss website. This book will be useful for applied statisticians and data scientists in selecting a distribution for a univariate response variable and modelling its dependence on explanatory variables, and to those interested in the properties of distributions.
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Flexible Regression and Smoothing

Flexible Regression and Smoothing

Mikis D. Stasinopoulos; Robert A. Rigby; Gillian Z. Heller; Vlasios Voudouris; Fernanda De Bastiani

CRC Press
2017
sidottu
This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent.In particular, the GAMLSS statistical framework enables flexible regression and smoothing models to be fitted to the data. The GAMLSS model assumes that the response variable has any parametric (continuous, discrete or mixed) distribution which might be heavy- or light-tailed, and positively or negatively skewed. In addition, all the parameters of the distribution (location, scale, shape) can be modelled as linear or smooth functions of explanatory variables. Key Features: Provides a broad overview of flexible regression and smoothing techniques to learn from data whilst also focusing on the practical application of methodology using GAMLSS software in R. Includes a comprehensive collection of real data examples, which reflect the range of problems addressed by GAMLSS models and provide a practical illustration of the process of using flexible GAMLSS models for statistical learning. R code integrated into the text for ease of understanding and replication. Supplemented by a website with code, data and extra materials.This book aims to help readers understand how to learn from data encountered in many fields. It will be useful for practitioners and researchers who wish to understand and use the GAMLSS models to learn from data and also for students who wish to learn GAMLSS through practical examples.
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Partial Discharges in Hydroelectric Generators

Partial Discharges in Hydroelectric Generators

Victor Dmitriev; Rodrigo M. S. Oliveira; Ronaldo F. Zampolo; Paulo R. Moutinho de Vilhena; Fernando de Souza Brasil; Martim Felipe Fernandes

Springer International Publishing AG
2023
sidottu
Effective implementation of predictive maintenance programs in power plants requires the online condition monitoring of electrical generators. This book offers a comprehensive guide on the measurement, detection, and interpretation of partial discharges in hydroelectric generators. It covers a range of essential topics such as the physics of partial discharge phenomenon, various types of defects and partial discharge patterns, sensors and acquisition procedures, signal processing techniques, automatic classification of discharge types, and correlation between partial discharge occurrence and ozone generation. Numerical modelling of partial discharges and calculation of the associated radiating electromagnetic fields are also discussed. To aid understanding, the book provides theoretical explanations, practical examples, and functional Python code on Google’s Colaboratory platform. This book is a valuable resource for anyone seeking a deep understanding of partial discharges in hydroelectric generators.Presents in-depth theory with examples;Provides experimental data illustrating effects of PD in machine components;Includes functional Python and C code examples.
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Partial Discharges in Hydroelectric Generators

Partial Discharges in Hydroelectric Generators

Victor Dmitriev; Rodrigo M. S. Oliveira; Ronaldo F. Zampolo; Paulo R. Moutinho de Vilhena; Fernando de Souza Brasil; Martim Felipe Fernandes

Springer International Publishing AG
2024
nidottu
It covers a range of essential topics such as the physics of partial discharge phenomenon, various types of defects and partial discharge patterns, sensors and acquisition procedures, signal processing techniques, automatic classification of discharge types, and correlation between partial discharge occurrence and ozone generation.
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