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Applied Statistical Methods
by Finch, W. Holmes;
English | 2025 | ISBN: 1032459344 | 374 pages | True EPUB | 6.46 MB

This book is designed to provide students, teachers, and researchers with a text that includes a full range of statistical methods available to address commonly encountered research problems. Many textbooks for introductory, intermediate, and advanced statistics courses focus heavily on parametric methods. However, in practice, the assumptions underlying these methods are frequently not met, therefore calling into question their use. This book addresses this issue by presenting parametric, nonparametric, robust, and Bayesian techniques that are appropriate for research scenarios often encountered in practice and typically found in statistics courses. For each of these major topics, the standard parametric approach is presented, along with the assumptions underlying it and the methods used to assess the viability of these assumptions. Next, a set of alternative techniques for the research scenario is presented and applied to the motivating example that begins each chapter. Each chapter concludes with a summary focused on how researchers should select which method to use when and a summary of the material covered in the chapter. The chapters have motivating examples that serve as an anchor for discussion of the featured methods. The focus of the chapters is intended to be conceptual (as opposed to highly technical) to make the text useful to individuals with a wide array of statistical backgrounds. More technical material is included in each chapter for interested readers and instructors who would like to focus more attention on it. Instructors will be able to use this book as a main text in introductory, intermediate, and some specialized statistics courses such as nonparametric and robust methods. In addition, researchers and data analysts from a wide array of disciplines will be able to use this book as a primary resource in their work.
Key features of this book are as follows:
It presents a full range of statistical options available to researchers for major problems faced in the social and life sciences, health care, and business.
It explains how to evaluate a dataset to determine which statistical approach (e.g., standard parametric, nonparametric, robust, Bayesian) may be optimal.
It features a website containing datasets and computer code.

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Artificial Intelligence and Biological Sciences
by P.V. Mohanan
English | 2025 | ISBN: 1032781203 | 468 pages | True PDF | 65.61 MB

Advancements of AI in medical and biological sciences have opened new ways for drug development. Novel therapeutic molecules and their target action can be easily predicted and can be modified. AI helps in disease detection and diagnosis faster. The breakthrough of AI is made especially in the area of personalized precision medicine, host-pathogen interaction and predictive epidemiology. These approaches could help in faster decision-making with minimal errors that can improve risk analysis, especially disease diagnosis and selecting treatment strategy. In agricultural practices, an exact combination of fertilizers, pesticides, herbicides, soil management, water requirement analysis, yield prediction and overall crop management can be modified by implementing AI interventions. AI could provide a better improvement in agriculture, medical research, pharmaceuticals and bio-based industries for a sustainable life.
The key features of this book are: AI in medical Sciences, biotechnology and drug discovery; Application of AI in Digital Pathology, cytology and bioinformatics; Overview of AI, Machine Learning and Deep Learning; Impact of Artificial Intelligence in Society; Artificial Intelligence in Pharmacovigilance; and Ethics in Artificial Intelligence. The volume aims to comprehensively cover the application of AI in biological sciences. It is a collection of contributions from different authors who have several years of experience in their specific areas. The book will be useful for pharma companies, CROs, product developers, students, researchers, academicians, policymakers and practitioners.

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Artificial Intelligence and Law in the Communication Professions
by Myers, Cayce
English | 2025 | ISBN: 1032730730 | 193 pages | True PDF EPUB | 11.8 MB

This book analyzes the current attempts to regulate artificial intelligence (AI) and its impact on the communication field. Examining existing and proposed laws, policies, and regulations of AI in the U.S. and the European Union, this book analyzes how the technological development of AI will be governed in the next decade and how this will impact the communication industry. Chapters explore the influence of laws on key communication issues including free speech, disinformation, intellectual property, privacy, and discrimination, as well as the AI industry's approach to self-regulation. It shows how communication professionals such as public relations practitioners, advertisers, and journalists will be affected by generative AI content production and how communication will ultimately be shaped by the regulations and laws placed on AI. Providing readers with a working knowledge of the contemporary legal issues surrounding AI and communication, this book will be of interest to scholars and students in the fields of Media and Communication Law, Public Relations, Advertising, and Journalism.

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Artificial Intelligence
by Alan Dix with Janet Finlay
English | 2025 | ISBN: 0367515989 | 429 pages | True PDF EPUB | 78.97 MB

An authoritative and accessible one-stop resource, the first edition of An Introduction to Artificial Intelligence presented one of the first comprehensive examinations of AI. Designed to provide an understanding of the foundations of artificial intelligence, it examined the central computational techniques employed by AI, including knowledge representation, search, reasoning and learning, as well as the principal application domains of expert systems, natural language, vision, robotics, software agents and cognitive modelling. Many of the major philosophical and ethical issues of AI were also introduced. This new edition expands and revises the book throughout, with new material to augment existing chapters, including short case studies, as well as adding new chapters on explainable AI, big data and deep learning, temporal and web-scale data, statistical methods and data wrangling. It expands the book's focus on human-centred AI, covering gender, ethnic and social bias, the need for transparency, intelligent user interfaces, and designing interactions to aid machine learning. With detailed, well-illustrated examples and exercises throughout, this book provides a substantial and robust introduction to artificial intelligence in a clear and concise coursebook form. It stands as a core text for all students and computer scientists approaching AI.

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Artificial Intelligence in Action, Real-World Applications and Innovations
by Ahmed Banafa
English | 2025 | ISBN: 8770046204 | 362 pages | True PDF | 22.73 MB

This comprehensive book dives deep into the current landscape of AI, exploring its fundamental principles, development challenges, potential risks, and the cutting-edge breakthroughs that are propelling it forward. Artificial intelligence (AI) is rapidly transforming industries and societies worldwide through groundbreaking innovations and real-world applications. Starting with the core concepts, the book examines the various types of AI systems, generative AI models, and the complexities of machine learning. It delves into the programming languages driving AI development, data pipelines, model creation and deployment processes, while shedding light on issues like AI hallucinations and the intricate path of machine unlearning.
The book then showcases the remarkable real-world applications of AI across diverse domains. From preventing job displacement and promoting environmental sustainability, to enhancing disaster response, drone technology, and even nuclear energy innovation, it highlights how AI is tackling complex challenges and driving positive change.
The book also explores the double-edged nature of AI, recognizing its tremendous potential while cautioning about the risks of misuse, unintended consequences, and the urgent need for responsible development practices. It examines the intersection of AI and fields like operating system design, warfare, and semiconductor technology, underscoring the wide-ranging implications of this transformative force.
As the quest for artificial general intelligence (AGI) and superintelligent AI systems intensifies, the book delves into cutting-edge research, emerging trends, and the pursuit of multimodal, explainable, and causally aware AI systems. It explores the symbiotic relationship between AI and human creativity, the rise of user-friendly "casual AI," and the potential of AI to tackle open-ended tasks.
This is an essential guide for understanding the profound impact of AI on our world today and its potential to shape our future. From the frontiers of innovation to the challenges of responsible development, this book offers a comprehensive and insightful exploration of the remarkable real-world applications and innovations driving the AI revolution.

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Artificial Intelligence in Remote Sensing for Disaster Management
by Dahiya, Neelam;Singh, Gurwinder;Singh, Sartajvir;Sharma, Apoorva;, Gurwinder Singh, Sartajvir Singh, Apoorva Sharma
English | 2025 | ISBN: 1394287194 | 384 pages | True EPUB | 17.91 MB

Invest inArtificial Intelligence in Remote Sensing for Disaster Managementto gain invaluable insights into cutting-edge AI technologies and their transformative role in effectively monitoring and managing natural disasters.
Artificial Intelligence in Remote Sensing for Disaster Managementexamines the involvement of advanced tools and technologies such as Artificial Intelligence in disaster management with remote sensing. Remote sensing offers cost-effective, quick assessments and responses to natural disasters. In the past few years, many advances have been made in the monitoring and mapping of natural disasters with the integration of AI in remote sensing. This volume focuses on AI-driven observations of various natural disasters including landslides, snow avalanches, flash floods, glacial lake outburst floods, and earthquakes. There is currently a need for sustainable development, near real-time monitoring, forecasting, prediction, and management of natural resources, flash floods, sea-ice melt, cyclones, forestry, and climate changes. This book will provide essential guidance regarding AI-driven algorithms specifically developed for disaster management to meet the requirements of emerging applications.

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Asphalt Core Embankment Dams
by Høeg, Kaare, Wang, Weibiao
English | 2025 | ISBN: 113803763X | 198 pages | True PDF EPUB | 133.89 MB

Dams are built for several purposes, e.g., water supply, irrigation, hydropower production, or flood control. The main categories are concrete dams and embankment dams, but inside each of these two main general categories, there are several different types. Asphalt Core Embankment Dams focusses on the design and construction of these types of dams. Asphalt core embankment dams are gaining in popularity, as their recorded field performance is excellent, they are economically very competitive, and the construction period may be shortened compared to other types of embankment dams. This book presents several case studies of dams that have been successfully built and been in service for many years, and:
introduces the concept of using asphalt concrete core rather than earth core or upstream facing;
points out there is no concern about internal erosion when using hydraulic asphalt concrete in the core;
discusses material selection and mix design for hydraulic asphalt concrete to achieve flexibility and ductility;
discusses suitability testing and asphalt concrete mix improvements and optimization by using additives;
presents the use of triaxial tests, tension tests, and bending tests to study cracking resistance and potential self-healing;
discusses the use of modern construction equipment and field quality control;
shows that asphalt core dams may reduce the construction period compared to other options; and
treats earthquake resistance of this type of dams.
The authors have built on decades of experience with the design and construction, construction control, and research and development for asphalt core embankment dams. Asphalt Core Embankment Dams is aimed at engineering students, practising engineers, civil engineering contractors, equipment suppliers, and asphalt producers.

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Assassinations That Shaped the Ancient World
by Phil Carradice;
English | 2025 | ISBN: 139905399X | 226 pages | True PDF EPUB | 27.41 MB

Explores the history of political assassinations from ancient Egypt to the Dark Ages, examining notable figures and motivations.
Assassination! Just mentioning the word is enough to send a shiver up the spine. And yet, for many years, the deliberate act of 'taking out' notable public figures has been the mainstay of political factions and individuals when faced with problems and dilemmas that discussion and debate cannot solve.
Most monarchs, statesmen and military commanders of the ancient world, whether they were successful or failures, had to deal with threats. At one stage or another in their careers, they would all have been vulnerable to unexpected attacks. They would all have been potential targets for assassin's blades or poison. And they knew it.
So common was the assassination of notable individuals that it became almost an occupational hazard in the ancient world. From Pharaoh Teti, the first recorded victim of assassination, to Julius Caesar, despatched on the Ides of March, from Pompey the Great to Commodious, the Gladiator Emperor of Rome, so many rulers perished before their allotted period of time.
In this new book, Phil Carradice takes a broad sweep at assassinations in the ancient world. Beginning with the Egyptian Empire, it traces the assassin's art through Greek, Roman, Biblical, Chinese, Byzantine and other periods or empires, up to and including the Kings and Emperors of the Dark Ages. The book does not stop there. It examines individual assassinations, motivation and practice and looks at assassination groups such as the thugee of India and the Sacred Band of Thebes.

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Assessment of Tensegrity Structures: Static, Dynamic, and Dynamic Stability Analysis
by Paulina Obara
English | 2025 | ISBN: 1032874686 | 209 pages | True PDF | 69.19 MB

This book enables a proper understanding of tensegrity structures. It contains both theoretical background and examples. First, a geometrically non-linear model and the methods used to evaluate the behavior of tensegrity structures are explained. Next, a broad spectrum of different planar and spatial design solutions is considered.
Assessment of Tensegrity Structures is very logically organized, in line with its down-to-earth subject, beginning with the simplest two-dimensional structure, for which solutions can be presented in explicit form, and ending with more complex tensegrity structures used in civil engineering such as domes, towers, and plates.
This book is designed for everyone who is interested in tensegrity systems, from beginners to those who want to deepen their knowledge of them.

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At the Emperor's Pleasure
by Richard Graham;
English | 2025 | ISBN: 1036109216 | 298 pages | True PDF EPUB | 9.2 MB

At the Emperors Pleasure follows the young couple Christopher and Topsy Man through the savage battle for Hong Kong and the years of enforced separation, she interned in Stanley Camp, Hong Kong, he as a prisoner of war and forced labourer in Kobe, Japan.
The book is not about Christopher and Topsy Man alone but also of friends and colleagues close to them forced to endure the cruel torture and execution by the Kempeitai.
Amongst those close to them some of Topsy's friends and colleagues were raped and murdered, one was imprisoned within shouting distance of her husband being tortured then executed by the Kempeitai, while another died when their camp was mistakenly bombed by the Allies. Topsy was herself the reluctant witness to ritual executions.
Christopher lost brother officers and many of the Cockney soldiers under his command in the battle for Hong Kong. Others drowned in the East China Sea, victims of a barbaric but little-known mass war crime, the sinking of the Lisbon Maru. Still others survived the sinking only to succumb to the harsh regime of the POW camp in Japan. Perhaps most tragic of all, four of Christopher's men came through the battle, the Lisbon Maru sinking and cruel imprisonment only to die when the aircraft carrying them to freedom crashed into the sea during a typhoon.
Like many of their generation who suffered at the hands of the Japanese during the second world war, Christopher and Topsy Man rarely spoke of their experience, and when they did, they were guarded in what they chose to share of it, even with those closest to them in their post-war lives.
With privileged access to personal letters, diaries and records from the wartime years, from memories exchanged with Christopher's and Topsy's contemporaries and from knowledge shared by other historians, the author has written a compelling and moving account of the young couple's lives being torn apart by world events in late 1941.

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ATD's Handbook for Measuring and Evaluating Training
by Patricia Pulliam Phillips
English | 2025 | ISBN: 1960231243 | 536 pages | True EPUB | 25.74 MB

Get the A-to-Z Resource on Training Evaluation
Fully revised and updated, ATD's Handbook for Measuring and Evaluating Training is the comprehensive go-to reference for talent development professionals in need of immediate measurement and evaluation (M&E) guidance. Edited by M&E powerhouse Patti Phillips, with contributions from 30 expert practitioners, this handbook provides an essential roadmap to developing effective processes to prove the value and impact of your learning and development programs.
Training measurement and evaluation is one of the top frustrations of a talent development professional's job. At first glance, it appears to be a drain on precious time and resources, yet it is a critical function for understanding the results and proving the value of L&D programs. If not conducted properly, it can yield questionable results, lack of accountability, and stakeholder skepticism. All to say, TD professionals must...

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Bayesian Econometric Modelling for Big Data
by Qian, Hang;
English | 2025 | ISBN: 1032915250 | 486 pages | True EPUB | 7 MB

This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques, seamlessly integrating these scalable methods into a broad spectrum of econometric models. In addition to its focus on big data, the book introduces novel concepts within traditional statistics, such as the summation, subtraction, and multiplication of conjugate distributions. These arithmetic operators conceptualize pseudo data in the conjugate prior, sufficient statistics that determine the likelihood, and the posterior as a balance between data and prior information, adding an intriguing dimension to Bayesian analysis. This book also offers a deep dive into Bayesian computation. Given the intricacies of the floating-point representation of real numbers, computer programs can sometimes yield unexpected or theoretically impossible results. Drawing from his experience as a senior statistical software developer, the author shares valuable strategies for designing numerically stable algorithms. The book is an essential resource for a diverse audience: graduate students seeking foundational knowledge in Bayesian econometric models, early-career statisticians eager to explore cutting-edge advancements in scalable Bayesian methods, data analysts struggling with out-of-memory challenges in large datasets, and statistical software users and developers striving to program with efficiency and numerical stability.

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Bayesian Econometric Modelling for Big Data
by Hang Qian
English | 2025 | ISBN: 1032915250 | 487 pages | True PDF | 7.89 MB

This book delves into scalable Bayesian statistical methods designed to tackle the challenges posed by big data. It explores a variety of divide-and-conquer and subsampling techniques, seamlessly integrating these scalable methods into a broad spectrum of econometric models.
In addition to its focus on big data, the book introduces novel concepts within traditional statistics, such as the summation, subtraction, and multiplication of conjugate distributions. These arithmetic operators conceptualize pseudo data in the conjugate prior, sufficient statistics that determine the likelihood, and the posterior as a balance between data and prior information, adding an intriguing dimension to Bayesian analysis. This book also offers a deep dive into Bayesian computation. Given the intricacies of floating-point representation of real numbers, computer programs can sometimes yield unexpected or theoretically impossible results. Drawing from his experience as a senior statistical software developer, the author shares valuable strategies for designing numerically stable algorithms.
The book is an essential resource for a diverse audience: graduate students seeking foundational knowledge in Bayesian econometric models, early-career statisticians eager to explore cutting-edge advancements in scalable Bayesian methods, data analysts struggling with out-of-memory challenges in large datasets, and statistical software users and developers striving to program with efficiency and numerical stability.

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Bayesian Meta-Analysis
by Grant, Robert;Di Tanna, Gian Luca;, Di Tanna, Gian Luca
English | 2025 | ISBN: 1032451890 | 328 pages | True EPUB | 9.59 MB

"...this book is extremely timely...not just a technical exposition, but provides practical guidance about using different software platforms, as well as valuable advice about extracting summary statistics, eliciting prior information, communicating results, visualisation, and many other issues...reflects years of thoughtful experience, and should be of huge value to anyone faced with pooling studies into a coherent whole." ~From the Foreword by Professor Sir David Spiegelhalter Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data. It is widespread in life sciences and is gaining popularity in economics and beyond. In many real-life meta-analyses, challenges in the source information, such as unreported statistics or biases, can be incorporated using Bayesian methods. Bayesian Meta-Analysis: A Practical Introduction provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both. There is an emphasis on hands-on learning using a variety of software packages. Key Features Introductory chapters assume no prior experience or mathematical training and are aimed at non-statistical researchers. Examples of basic meta-analyses in seven different software alternatives: BUGS, JAGS, Stan, bayesmeta, brms, Stata, and JASP. Practical advice on extracting information from studies, eliciting expert opinions, managing project decisions, and writing up findings. Discussion of specific problems, including publication bias, unreported statistics, and a mixture of study designs, with code examples. Accompanying online blog and forum, with all code and data from the book, plus more translations to different software. This book aims to bridge the gap between the researcher who wants to carry out tailored meta-analysis and the techniques they need, which have previously been available only in mathematically or computationally demanding publications.

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Bayesian Models
by N. Thompson Hobbs, Mevin B. Hooten
English | 2025 | ISBN: 069125012X | 360 pages | True EPUB | 9.46 MB

A fully updated and expanded edition of the essential primer on Bayesian modeling for ecologists
Uniquely suited to deal with complexity in a statistically coherent way, Bayesian modeling has become an indispensable tool for ecological research. This book teaches the basic principles of mathematics and statistics needed to apply Bayesian models to the analysis of ecological data, using language non-statisticians can understand. Deemphasizing computer coding in favor of a clear treatment of model building, it starts with a definition of probability and proceeds step-by-step through distribution theory, likelihood, simple Bayesian models, and hierarchical Bayesian models. Now revised and expanded, Bayesian Models enables students and practitioners to gain new insights from ecological models and data properly tempered by uncertainty.
Covers the basic rules of probability needed to model diverse types of ecological data in the Bayesian framework
Shows how to write proper mathematical expressions for posterior distributions using directed acyclic graphs as templates
Explains how to use the powerful Markov chain Monte Carlo algorithm to find posterior distributions of model parameters, latent states, and missing data
Teaches how to check models to assure they meet the assumptions of model-based inference
Demonstrates how to make inferences from single and multiple Bayesian models
Provides worked problems for practicing and strengthening modeling skills
Features new chapters on spatial models and modeling missing data

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