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Computational Intelligence in Healthcare Law: AI for Ethical Governance and Regulatory Challenges
by Bhupinder Singh, Christian Kaunert, Balamurugan Balusamy, and Rajesh Kumar Dhanaraj
English | 2025 | ISBN: 1032885661 | 185 pages | True PDF | 8.6 MB

This book explores the intersection of legal frameworks, healthcare innovation, and computational intelligence, shedding light on how emerging technologies like artificial intelligence (AI) and machine learning (ML) are reshaping the medical landscape. It presents real- life challenges such as patient privacy, data security, and compliance issues in smart healthcare by delving into the associated ethical and regulatory implications. Comprising the concepts of predictive analytics, regulatory compliance algorithms, and legal decision- making processes, this book offers a roadmap for stakeholders to navigate the evolving landscape of healthcare innovation responsibly and ethically.
Features:
Investigates how artificial intelligence supports legal decision- making processes in smart healthcare, addressing ethical and accountability concernsDemonstrates the use of smart contracts and automation tools powered by computational intelligence to streamline legal processes and ensure compliance in smart healthcare initiativesFocuses on managing healthcare data within legal frameworks, emphasizing the role of computational intelligence's in ensuring privacy and securityExamines how computational intelligence enables predictive analytics models to anticipate legal challenges and compliance issues in smart healthcareHighlights the development and implementation of computational algorithms for navigating evolving legal frameworks in healthcare
This reference book is a useful resource for scholars and researchers working on smart healthcare.

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Computational Techniques for Biological Sequence Analysis
by Umer, Saiyed, Rout, Ranjeet Kumar, Khandelwal, Monika, Pati, Smitarani
English | 2025 | ISBN: 1032630264 | 211 pages | True PDF EPUB | 26.76 MB

This book provides an overview of basic and advanced computational techniques for analyzing and understanding protein, RNA, and DNA sequences. It covers effective computing techniques for DNA and protein classifications, evolutionary and sequence information analysis, evolutionary algorithms, and ensemble algorithms. Furthermore, the book reviews the role of machine learning techniques, artificial intelligence, ensemble learning, and sequence-based features in predicting post-translational modifications in proteins, DNA methylation, and mRNA methylation, along with their functional implications. The book also discusses the prediction of protein-protein and protein-DNA interactions, protein structure, and function using computational methods. It also presents techniques for quantitative analysis of protein-DNA interactions and protein methylation and their involvement in gene regulation. Additionally, the use of nature-inspired algorithms to gain insights into gene regulatory mechanisms and metabolic pathways in human diseases is explored. This book acts as a useful reference for bioinformaticians and computational biologists working in the fields of molecular biology, genomics, and bioinformatics. Key Features: Reviews machine learning techniques for DNA sequence classification and protein structure prediction Discusses genetic algorithms for analyzing multiple sequence alignments and predicting protein-protein interaction sites Explores computational methods for quantitative analysis of DNA-protein interactions Examine the role of nature-inspired algorithms in understanding the gene regulation and metabolic pathways Covers evolutionary algorithms and sequence-based features in predicting post-translational modifications

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Concentration Camps
by Kramer, Alan;
English | 2025 | ISBN: 0198800622 | 640 pages | True EPUB | 18.28 MB

Terror was central to the Nazi regime, and the Nazi concentration camps were places of horror where prisoners were dehumanized and robbed of their dignity and where millions were murdered. How did prisoners cope with the brutal and degrading conditions of life within the camps?
In this highly original book Maja Suderland takes the reader inside the concentration camps and examines the everyday social life of prisoners - their daily activities and routines, the social relationships and networks they created and the strategies they developed to cope with the harsh conditions and the brutality of the guards. Without overlooking the violence of the camps, the contradictions of camp life or the elusive complexity of the multicultural prisoner society, Suderland explores the hidden social practices that enabled prisoners to preserve their human dignity and create a sense of individuality and community despite the appalling circumstances.
This remarkable account of social life in extreme conditions will be of great interest to students and scholars in history, sociology and the social sciences generally, as well as to a wider readership interested in the Holocaust and the concentration camps.

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Math Anxiety - How to Beat It!
by Brian Cafarella
English | 2025 | ISBN: 1032973110 | 245 pages | True PDF | 16.14 MB

Copula additive distributional regression enables the joint modeling of multiple outcomes, an essential aspect of many real-world research problems. This book provides an accessible overview of this modeling approach, with a particular focus on its implementation in the GJRM R package, developed by the authors. The emphasis is on bivariate responses with empirical illustrations drawn from diverse fields such as health and medicine, epidemiology, economics and social sciences.
Key Features:
Provides a comprehensive overview of joint regression modeling for multiple outcomes, with a focus on bivariate responses
Offers a practical approach with real-world examples from various fields
Demonstrates the implementation of all the discussed models using the GJRM package in R
Includes supplementary resources such as data accessible through the GJRM.data package in R and additional code available on the authors' webpages
This book is designed for graduate students, researchers, practitioners and analysts who are interested in using copula additive distributional regression for the joint modeling of bivariate outcomes. The methodology is accessible to readers with a basic understanding of core statistics and probability, regression, copula modeling and R.

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Creating Loyalty in Youth Travel
by Lowy, Stephen;
English | 2025 | ISBN: 1398620645 | 256 pages | True EPUB | 1.38 MB

By attracting young people, travel brands and destinations can create a lifetime of value, with young people often staying longer, spreading their spend across a destination, contributing to the local economy and returning again and again.
Creating Loyalty in Youth Travelexplores the varying and unique needs of young tourists - from backpackers to youth mobility workers - and the challenges brands and destinations face in attracting and retaining them. While travel professionals often target certain sectors such as business or luxury travellers, this can be a short-sighted strategy. Youth travellers can be a more sustainable market as they frequently form an emotional tie to a destination or travel brand, driving them to return throughout their lives, sharing with family and friends and increasing their spend as they age.
This book looks at how successful brands and destinations prioritize developing long-term relationships with travellers early on, so that they can continue to cater to loyal customers throughout their lives with different offerings from within the same brand. Some countries and travel brands excel at this, building it into the heart of their strategy, while others have ignored this key market to their own detriment.
Through extended interviews from leaders in the sector such as Marriott and Tourism Australia, this book helps tourism and hospitality professionals to understand the needs of the youth traveler market and harness the potential of it to build a long-term strategy for the tourism industry.

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Crime‑Related Events Identification Based on Text Analytics Approach
by Orken Mamyrbayev
English | 2025 | ISBN: 1032957891 | 141 pages | True PDF | 10.59 MB

As modern society is extremely dependent on the Internet, social networks, and developing technologies, a threat to the security of both the individual and society as a whole has emerged. The openness and global nature of the Internet create opportunities both for criminals, who can use the available information for criminal purposes, and for law enforcement officials. Police officers, in turn, can deal with the preventive processing of data from the Internet in order to prevent crimes. This type of data analysis can detect illegal or criminal actions even at the stage of their formation. Crime-Related Events Identification Based on Text Analytics Approach describes the possibilities of extracting crime-related facts from semi-structured information from various Internet sources so that crime can be combatted. This book is aimed at police officers and IT professionals working in online investigations.

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Crochet Squares
by Gullberg, Maria;
English | 2025 | ISBN: 1849949573 | 178 pages | True EPUB | 145.85 MB

30 magical crochet square designs for clothes, accessories and the home. A square is a small, repeatable crochet project that is versatile and easy to take with you wherever you go. You can use them individually or you can join endless amounts of squares together to build up patterns which can give you everything from mug coasters to duvet covers. In this book, Maria Gullberg has designed different types of squares including classic and easy granny squares, new and interesting designs of squares and hexagons, as well as mosaic crochet squares. They can be used for all kinds of projects, from jumpers, shawls and waistcoats to rugs, cushion covers and bags: the possibilities really are endless. Each square can be joined together in as many ways as you can think of. There are pattern examples with clear instructions if you're looking for inspiration or specific designs, or you can make it up as you go along mixing patterns and choosing your own colour ways. In this book you'll discover squares to crochet that you'll never have seen before. With projects suitable for all abilities, from beginner through to intermediate and advanced, there's plenty to ignite your imagination.

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Cyber Insecurity; Examining the Past, Defining the Future
by Vladas Leonas With Contribution from Sorin Toma
English | 2025 | ISBN: 1032672579 | 368 pages | True PDF | 14.17 MB

Cyber Insecurity: Examining the Past, Defining the Futuredeals with the multifaceted world of cybersecurity, starting with the premise that while perfection in cybersecurity may be unattainable, significant improvements can be made through understanding history and fostering innovation. Vladas Leonas shares his journey from Moscow to Australia, highlighting his academic and professional milestones.
This book covers the evolution of cybersecurity from the late 1960s to the present, detailing significant events and technological advancements. The author emphasises the importance of simplicity in technology projects, citing complexity as a major hindrance to success. The book also discusses the impact of the digital revolution, using the example of a global IT outage caused by a faulty software update.
Project management methodologies are explored, tracing their origins from ancient civilisations to modern techniques such as CPM and PERT. The concept of cloud computing is examined, highlighting its benefits and potential security issues. The evolution and advantages of SaaS solutions are also discussed, noting their increased adoption during the COVID-19 pandemic.
The author then addresses supply chain challenges, using real-world examples to illustrate vulnerabilities. He traces the history of communication methods leading up to TCP/IP and discusses the development and importance of DNS. The differences between compliance and conformance in cybersecurity are clarified, emphasising that compliance does not equate to security.
Key cybersecurity standards such as the NIST CSF and ISO/IEC 27000 series are examined. The book also covers the Essential 8, a set of cybersecurity controls developed by the Australian Signals Directorate. The convergence of OT and IoT is discussed, highlighting the cybersecurity risks associated with this integration.
Emerging threats from AI and quantum computing are explored, noting their potential to both advance and threaten cybersecurity. The evolving legal landscape of cybersecurity is also covered, emphasising the need for international cooperation and innovative legal solutions.
In conclusion, the book stresses the importance of critical thinking and a holistic approach to cybersecurity, advocating for simplicity and foundational practices to enhance security.

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Cyprus and the First World War (Hardcover)
by Kazamias, Georgios
English | 2025 | ISBN: 1350446971 | 236 pages | True EPUB | 5.93 MB

Shedding light on a forgotten aspect of Cypriot history, this book explores the involvement of Cyprus during the Great War and the impact it left on British colonial rule.It examines the political, economic, social and military aspects of the war effort.
Cyprus and the First World Warreflects on how Cyprus, as a British colony not in control of its own affairs, had a very specific and uncommon experience of the First World War; decisions were made elsewhere, communities were forced into a struggle that was not their own and their future status and ownership of the island was likely to be affected by the outcome. Bringing together contributors from various disciplines, this volume considers numerous facets of Cyprus' part in and contribution to the First World War and the war's effects on the island. It also highlights the fact that, while the island saw hardly any military action, it played an important role as a rear area for recovery and training purposes, as well as a provider of supplies, while Cypriots from all communities participated in the war, in particular at the Macedonian Front, a key theatre where conflict raged for much of the war.

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Data Science and Analytics with Python: Second Edition
by Jesús Rogel-Salazar
English | 2025 | ISBN: 1032772492 | 514 pages | True PDF | 25.74 MB

Since the first edition of "Data Science and Analytics with Python" we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI).
This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucial issues of explainability, transparency, and fairness in AI. These topics have rightly gained significant attention in recent years. As AI integrates more deeply into various aspects of our lives, understanding and mitigating biases, ensuring fairness, and maintaining transparency become paramount. This book provides comprehensive coverage of these topics, offering practical insights and guidance for data scientists and analysts.
Designed as a practical companion for data analysts and budding data scientists, this book assumes a working knowledge of programming and statistical modelling but aims to guide readers deeper into the wonders of data analytics and machine learning. Maintaining the book's structure, each chapter stands alone as much as possible, allowing readers to use it as a reference as well as a textbook. Whether revisiting fundamental concepts or diving into new, advanced topics, this book offers something valuable for every reader.

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Data Without Labels
by Vaibhav Verdhan
English | 2025 | ISBN: 1617298727 | 352 pages | True/Retail EPUB | 23.66 MB

Discover all-practical implementations of the key algorithms and models for handling unlabeled data. Full of case studies demonstrating how to apply each technique to real-world problems.
In Data Without Labels you'll learn:
* Fundamental building blocks and concepts of machine learning and unsupervised learning
* Data cleaning for structured and unstructured data like text and images
* Clustering algorithms like K-means, hierarchical clustering, DBSCAN, Gaussian Mixture Models, and Spectral clustering
* Dimensionality reduction methods like Principal Component Analysis (PCA), SVD, Multidimensional scaling, and t-SNE
* Association rule algorithms like aPriori, ECLAT, SPADE
* Unsupervised time series clustering, Gaussian Mixture models, and statistical methods
* Building neural networks such as GANs and autoencoders
* Dimensionality reduction methods like Principal Component Analysis and multidimensional scaling
* Association rule algorithms like aPriori, ECLAT, and SPADE
* Working with Python tools and libraries like sci-kit learn, numpy, Pandas, matDescriptionlib, Seaborn, Keras, TensorFlow, and Flask
* How to interpret the results of unsupervised learning
* Choosing the right algorithm for your problem
* Deploying unsupervised learning to production
* Maintenance and refresh of an ML solution
Data Without Labels introduces mathematical techniques, key algorithms, and Python implementations that will help you build machine learning models for unannotated data. You'll discover hands-off and unsupervised machine learning approaches that can still untangle raw, real-world datasets and support sound strategic decisions for your business.
Don't get bogged down in theory-the book bridges the gap between complex math and practical Python implementations, covering end-to-end model development all the way through to production deployment. You'll discover the business use cases for machine learning and unsupervised learning, and access insightful research papers to complete your knowledge.
Foreword by Ravi Gopalakrishnan.
About the technology
Generative AI, predictive algorithms, fraud detection, and many other analysis tasks rely on cheap and plentiful unlabeled data. Machine learning on data without labels-or unsupervised learning-turns raw text, images, and numbers into insights about your customers, accurate computer vision, and high-quality datasets for training AI models. This book will show you how.
About the book
Data Without Labels is a comprehensive guide to unsupervised learning, offering a deep dive into its mathematical foundations, algorithms, and practical applications. It presents practical examples from retail, aviation, and banking using fully annotated Python code. You'll explore core techniques like clustering and dimensionality reduction along with advanced topics like autoencoders and GANs. As you go, you'll learn where to apply unsupervised learning in business applications and discover how to develop your own machine learning models end-to-end.

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Data-Driven Global Optimization Methods and Applications
by Dong, Huachao;Wang, Peng;Li, Jinglu;, Wang, Peng, Li, Jinglu
English | 2026 | ISBN: 1041065752 | 384 pages | True EPUB | 21.39 MB

This book presents recent advances in data-driven global optimization methods, combining theoretical foundations with real-world applications to address complex engineering optimization challenges.
The book begins with an overview of the state of the art, key technologies and standard benchmark problems in the field. It then delves into several innovative approaches: space reduction-based, hybrid surrogate model-based and multi-surrogate model-based global optimization, followed by surrogate-assisted constrained global optimization, discrete global optimization and high-dimensional global optimization. These methods represent a variety of optimization techniques that excel in both optimization capability and efficiency, making them ideal choices for complex engineering optimization problems. Through benchmark test problems and real-world engineering applications, the book illustrates the practical implementation of these methods, linking established theories with cutting-edge research in industrial and engineering optimization.
Both a professional book and an academic reference, this title will provide valuable insights for researchers, students, engineers and practitioners in a variety of fields, including optimization methods and algorithms, engineering design and manufacturing and artificial intelligence and machine learning.

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