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Mathematics and Statistics (R0)

Egon Balas

Disjunctive Programming

1 Disjunctive programming and its relation to integer programming.-&amp;nbsp;2 The convex hull of a disjunctive set.-&amp;nbsp;3 Sequential convexification of disjunctive sets.-&amp;nbsp;4 Moving between conjunctive and disjunctive normal forms.-&amp;nbsp;5 Disjunctive programming and extended formulations.-&amp;nbsp;6 Lift-and-project cuts for mixed 0-1 programs.-&amp;nbsp;7 Nonlinear higher-dimensional representations.-&amp;nbsp;8 The correspondence between lift-and-project cuts and simple disjunctive&amp;nbsp;cuts.-&amp;nbsp;9 Solving (CGLP)k on the LP simplex tableau.-&amp;nbsp;10 Implementation and testing of variants.-&amp;nbsp;11 Cuts from general disjunctions.-&amp;nbsp;12 Disjunctive cuts from the V -polyhedral representation.-&amp;nbsp;13 Unions of polytopes in different spaces.- References.

How AI is shaped by Western religious culture and universal existential aspirations—and why we think we need it in the first place. Artificial Religion argues that to fully understand our puzzling relation to AI, we must first look at the religious and existential background of our thinking about machines. Mapping some surprising connections between our history of thought about machines and Western religious narratives to political issues and existential human needs and aspirations, Mark Coeckelbergh offers a better understanding of our relationship to machines and why we think we need them at all. The book is unique in not just discussing the myth of AI in terms of its technical limitations and the power of Big Tech but also revealing the deeper cultural “grammar” of AI—that is, the religious patterns of thinking and existential aspirations that are often not visible but still haunt Western thinking and shape its technological culture. Moreover, this is done in a way that sheds critical light on the power of AI.

How AI is shaped by Western religious culture and universal existential aspirations—and why we think we need it in the first place. Artificial Religion argues that to fully understand our puzzling relation to AI, we must first look at the religious and existential background of our thinking about machines. Mapping some surprising connections between our history of thought about machines and Western religious narratives to political issues and existential human needs and aspirations, Mark Coeckelbergh offers a better understanding of our relationship to machines and why we think we need them at all. The book is unique in not just discussing the myth of AI in terms of its technical limitations and the power of Big Tech but also revealing the deeper cultural “grammar” of AI—that is, the religious patterns of thinking and existential aspirations that are often not visible but still haunt Western thinking and shape its technological culture. Moreover, this is done in a way that sheds critical light on the power of AI.

On AI, Myth, and Power

Artificial Religion

Dance with the Dragon “A must-read for any reverse engineer.” ­—Max “Libra” Kersten Developed through more than a decade of research within the NSA, Ghidra was created to address some of the most challenging reverse engineering problems faced by the US government. With its open source release, this formerly restricted tool suite is now freely available to cybersecurity practitioners, researchers, and students worldwide. The Ghidra Book provides a clear, practical guide to understanding and using this powerful platform. In addition to introducing core reverse engineering techniques for software and malware analysis, the book explains Ghidra’s key components, features, and support for extensibility and collaborative analysis. Beginning with the fundamentals and progressing to more advanced workflows, you’ll learn how to use Ghidra effectively and adapt it to new challenges. You’ll learn how to: <ul><li>Navigate and interpret a disassembly</li><li>Use Ghidra’s built-in decompiler to expedite analysis</li><li>Analyze unfamiliar and obfuscated binaries</li><li>Extend Ghidra to recognize new data types</li><li>Build custom analyzers, loaders, and processor support modules</li><li>Script Ghidra tasks to automate analysis tasks</li><li>Set up a collaborative reverse engineering environment</li></ul> This fully revised second edition reflects the modern Ghidra platform as it is used in practice, with updated tooling, improved workflows, and hands-on real-world examples. Designed for beginners and experienced users alike, The Ghidra Book prepares you to tackle real reverse engineering problems with confidence. New to this edition: <ul><li>Behavioral analysis with BSim</li><li>Full Python 3 support via PyGhidra</li><li>Enhanced debugging and graphing tools</li><li>Modern container-based deployment</li></ul>

Dance with the Dragon “A must-read for any reverse engineer.” ­—Max “Libra” Kersten Developed through more than a decade of research within the NSA, Ghidra was created to address some of the most challenging reverse engineering problems faced by the US government. With its open source release, this formerly restricted tool suite is now freely available to cybersecurity practitioners, researchers, and students worldwide. The Ghidra Book provides a clear, practical guide to understanding and using this powerful platform. In addition to introducing core reverse engineering techniques for software and malware analysis, the book explains Ghidra’s key components, features, and support for extensibility and collaborative analysis. Beginning with the fundamentals and progressing to more advanced workflows, you’ll learn how to use Ghidra effectively and adapt it to new challenges. You’ll learn how to: <ul><li>Navigate and interpret a disassembly</li><li>Use Ghidra’s built-in decompiler to expedite analysis</li><li>Analyze unfamiliar and obfuscated binaries</li><li>Extend Ghidra to recognize new data types</li><li>Build custom analyzers, loaders, and processor support modules</li><li>Script Ghidra tasks to automate analysis tasks</li><li>Set up a collaborative reverse engineering environment</li></ul> This fully revised second edition reflects the modern Ghidra platform as it is used in practice, with updated tooling, improved workflows, and hands-on real-world examples. Designed for beginners and experienced users alike, The Ghidra Book prepares you to tackle real reverse engineering problems with confidence. New to this edition: <ul><li>Behavioral analysis with BSim</li><li>Full Python 3 support via PyGhidra</li><li>Enhanced debugging and graphing tools</li><li>Modern container-based deployment</li></ul>

The Definitive Guide

The Ghidra Book, 2nd Edition

Build intelligent applications—no data science degree required. Your boss is pitching new AI features. Your team is buzzing about MCP servers. Job postings are asking for AI experience with RAG, vector databases, fine-tuning, and agents. You can feel the excitement. You see the potential. You may be wondering how to get started in AI without a data science degree. You’re in the right place. The Developer’s Guide to AI gives working developers a practical path through the terminology, tools, and implementation patterns that matter. It shows you how to build with AI using the tools you already know: JavaScript, Python, APIs, SDKs, and databases. By the end of this book, you’ll know how to: <ul><li>Call LLM APIs and stream intelligent responses directly to your UI.</li><li>Engineer prompts that produce reliable, production-ready results.</li><li>Build RAG pipelines using vector databases to give AI access to your private data.</li><li>Fine-tune models with LoRA for specialized tasks like classification.</li><li>Deploy AI agents using tool-calling and the Model Context Protocol (MCP) to reason and act inside real workflows.</li></ul> LLMs, RAG, LoRA, MCP, embeddings, and agents are not just intimidating buzzwords. They are the building blocks for the next generation of software. Grab your code editor, bring your engineering instincts, and let’s build what’s next!

Build intelligent applications—no data science degree required. Your boss is pitching new AI features. Your team is buzzing about MCP servers. Job postings are asking for AI experience with RAG, vector databases, fine-tuning, and agents. You can feel the excitement. You see the potential. You may be wondering how to get started in AI without a data science degree. You’re in the right place. The Developer’s Guide to AI gives working developers a practical path through the terminology, tools, and implementation patterns that matter. It shows you how to build with AI using the tools you already know: JavaScript, Python, APIs, SDKs, and databases. By the end of this book, you’ll know how to: <ul><li>Call LLM APIs and stream intelligent responses directly to your UI.</li><li>Engineer prompts that produce reliable, production-ready results.</li><li>Build RAG pipelines using vector databases to give AI access to your private data.</li><li>Fine-tune models with LoRA for specialized tasks like classification.</li><li>Deploy AI agents using tool-calling and the Model Context Protocol (MCP) to reason and act inside real workflows.</li></ul> LLMs, RAG, LoRA, MCP, embeddings, and agents are not just intimidating buzzwords. They are the building blocks for the next generation of software. Grab your code editor, bring your engineering instincts, and let’s build what’s next!

The Developer's Guide to AI

AN INSTANT NATIONAL BESTSELLER “Evenhanded and insightful.”&nbsp; —Publisher’s Weekly (starred review) “An accessible, often fascinating primer.... Essential, illuminating reading.” —Kirkus From the author of the New York Times bestseller The Digital Doctor comes an engaging, clear-eyed, and ultimately hopeful examination of healthcare’s efforts to embrace generative artificial intelligence. In A Giant Leap, physician and thought leader Robert Wachter navigates between hype and skepticism to make a compelling case for AI’s power to transform healthcare. He argues that, in a system buckling under the weight of bureaucratic pressures, soaring costs, and clinician burnout, AI doesn’t need to be perfect—it only needs to be better. Drawing on extensive research and more than 100 interviews with pioneers across medicine, technology, policy, and business, Wachter shows how AI is already entering hospitals and clinics to draft notes, field patient questions, recommend treatments, interpret images, and guide surgeries. He unflinchingly confronts risks like hallucinations, biases, and misinformation, while revealing how AI can now match, and sometimes surpass, physicians in areas ranging from diagnosis to empathy. But this isn’t simply a technology story. It’s about the human choices that will determine whether AI becomes healthcare’s salvation or another source of harm and frustration.&nbsp; Blending clinical insight, vivid storytelling, and journalistic precision, A Giant Leap offers an indispensable roadmap for healthcare leaders, clinicians, and patients. It&nbsp;is a vibrant and timely account of how AI is changing what it means to care—and be cared for—in this age of astonishing technology.

AN INSTANT NATIONAL BESTSELLER “Evenhanded and insightful.”&nbsp; —Publisher’s Weekly (starred review) “An accessible, often fascinating primer.... Essential, illuminating reading.” —Kirkus From the author of the New York Times bestseller The Digital Doctor comes an engaging, clear-eyed, and ultimately hopeful examination of healthcare’s efforts to embrace generative artificial intelligence. In A Giant Leap, physician and thought leader Robert Wachter navigates between hype and skepticism to make a compelling case for AI’s power to transform healthcare. He argues that, in a system buckling under the weight of bureaucratic pressures, soaring costs, and clinician burnout, AI doesn’t need to be perfect—it only needs to be better. Drawing on extensive research and more than 100 interviews with pioneers across medicine, technology, policy, and business, Wachter shows how AI is already entering hospitals and clinics to draft notes, field patient questions, recommend treatments, interpret images, and guide surgeries. He unflinchingly confronts risks like hallucinations, biases, and misinformation, while revealing how AI can now match, and sometimes surpass, physicians in areas ranging from diagnosis to empathy. But this isn’t simply a technology story. It’s about the human choices that will determine whether AI becomes healthcare’s salvation or another source of harm and frustration.&nbsp; Blending clinical insight, vivid storytelling, and journalistic precision, A Giant Leap offers an indispensable roadmap for healthcare leaders, clinicians, and patients. It&nbsp;is a vibrant and timely account of how AI is changing what it means to care—and be cared for—in this age of astonishing technology.

How AI Is Transforming Healthcare and What That Means for Our Future

A Giant Leap

Frontiers of Artificial Intelligence, Ethics and Multidisciplinary Applications

This book introduces cutting-edge computational optimization techniques designed especially for AI enabled systems. These techniques inculcate advanced algorithms with real world applications to enhance efficiency and accuracy. Its focus on the hybrid and ensemble models makes it stand out, presenting novel and creative solutions for the complex problems. Through case studies and real-world applications the book not only highlights the theoretical aspects of the optimization techniques but also provides a link between theory and practice. With the help of clear explanations and practical examples the book empowers the readers to delve into the complex problems and providing optimized solutions leading to enhancing the performance of AI enabled systems.&nbsp;The book explores the advanced computational optimization techniques covering wide range of topics like nature-inspired algorithms, metaheuristics and hybrid optimization methods. This book caters the need of AI researchers, data scientists and machine learning engineers who aim to optimize their models and algorithms. It will be a valuable resource for the academicians and students studying AI and its related subfield. Professionals in the field of finance, healthcare, agriculture, education where AI applications are prevalent, will benefit from the practical insights provided. Overall, it caters to anyone interested in enhancing AI systems through sophisticated optimization strategies.

Computational Optimization Techniques for Artificial Intelligence Enabled Environments

How tech companies, journalists, and policymakers can prevent AI decision-making from going wrong. Our lives are increasingly governed by automated systems influencing everything from medical care to policing to employment opportunities, but researchers and investigative journalists have proven that AI systems regularly get things wrong. Auditing AI is a first-of-its-kind exploration of why and how to audit artificial intelligence systems. It offers a simple roadmap for using AI audits to make product and policy changes that benefit companies and the public alike. The book aims to convince readers that AI systems should be subject to robust audits to protect all of us from the dangers of these systems. Readers will come away with an understanding of what an AI audit is, why AI audits are important, key components of an audit that follows best practices, how to interpret an audit, and the available choices to act on an audit’s results. The book is organized around canonical examples: from AI-powered drones mistakenly targeting civilians in conflict areas to false arrests triggered by facial recognition systems that misidentified people with dark skin tones to HR hiring software that prefers men. It explains these definitive cases of AI decision-making gone wrong and then highlights specific audits that have led to concrete changes in government policy and corporate practice. The Marquand House Collective: Marc Aidinoff, Lena Armstrong, Esha Bhandari, Ellery Roberts Biddle, Motahhare Eslami, Karrie Karahalios, Nate Matias, Danaé Metaxa, Alondra Nelson, Christian Sandvig, and Kristen Vaccaro.

How tech companies, journalists, and policymakers can prevent AI decision-making from going wrong.

Auditing AI

A timely, practical guide to AI—its strengths, weaknesses, and real-world applications—for business professionals and policymakers. Artificial intelligence, or AI, can recognize a pattern from any set of data it is given, which is what makes it such an extraordinarily powerful tool. But because not all patterns are authentic or reliable, AI's pattern-finding superpower can lead to spurious patterns—and to disastrous results for business and government entities that rely on them. Hence the conundrum at the heart of AI: its greatest strength can also be its greatest weakness. Targeting the businessperson who needs to know how to use AI profitably and responsibly, Caleb Briggs and Rex Briggs offer in this book a foundational understanding of AI that is easy to grasp yet thorough enough to be used effectively.

A timely, practical guide to AI its strengths, weaknesses, and real-world applications for business professionals and policymakers.

Harnessing the Power of AI for Your Organization—Profitably and Safely

The AI Conundrum

International Series in Operations Research & Management Science

Recent Applications and Cases with the FITradeoff Method

Multi-Criteria Decision Making with Partial Preference Information

This book presents advanced mathematical programming models for contemporary supply chain risk optimization problems. It focuses on cutting‑edge issues such as supply chain viability under long‑term disruption risks, including reshoring decisions; optimization of digital supply chain cybersecurity and physical resilience in cyber‑physical supply chains; and supply chain fairness with respect to cost–service trade‑offs, profit distribution, and the allocation of cybersecurity investments. It also introduces computationally efficient decision‑making frameworks for emerging challenges in global supply chain management, including the reduction of cyber and physical risks and the enhancement of resilience and fairness. Each chapter ends with a table summarizing major managerial insights and the end-of-chapter problems to help the reader a self-check of material comprehension and to encourage for a further self-study.The book is intended for practitioners, researchers, and master’s and PhD‑level students in supply chain management, industrial engineering, operations research, applied mathematics, and related fields. Only an introductory background in operations research and supply chain management is assumed.

This book presents advanced mathematical programming models for contemporary supply chain risk optimization problems. It focuses on cutting‑edge issues such as supply chain viability under long‑term disruption risks, including reshoring decisions; optimization of digital supply chain cybersecurity and physical resilience in cyber‑physical supply chains; and supply chain fairness with respect to cost–service trade‑offs, profit distribution, and the allocation of cybersecurity investments. It also introduces computationally efficient decision‑making frameworks for emerging challenges in global supply chain management, including the reduction of cyber and physical risks and the enhancement of resilience and fairness. Each chapter ends with a table summarizing major managerial insights and the end-of-chapter problems to help the reader a self-check of material comprehension and to encourage for a further self-study. The book is intended for practitioners, researchers, and master’s and PhD‑level students in supply chain management, industrial engineering, operations research, applied mathematics, and related fields. Only an introductory background in operations research and supply chain management is assumed.

Viability, Cybersecurity, and Fairness

Optimization Models for Supply Chains

Das Werk bietet eine Einführung in die lineare Algebra und die analytische Geometrie und enthält Material für eine zweisemestrige Vorlesung. Es beginnt mit einem Kapitel, das allgemein in die mathematische Denkweise und Beweistechniken einführt, um dann über lineare Gleichungssysteme zur linearen Algebra überzuleiten. Der Text spannt den Bogen bis hin zu Tensorprodukten und ihren Anwendungen im Quantencomputing. Besonderer Wert wird auf eine enge Verzahnung von algebraischen und geometrischen Konzepten gelegt, zum einen um eine gute geometrische Intuition für algebraische Begriffe zu entwickeln, zum anderen um elegante algebraische Beweismethoden für geometrische Sätze einsetzen zu können.
 Der Text ist klar und verständlich geschrieben und in einem erfrischenden Stil verfasst. Interaktive Online-Übungsseiten und Illustrationen regen zu einem aktiven Studium an. Sie können auf internetfähigen Geräten mittels der angegebenen URL oder des QR-Codes aufgerufen werden. Die Aufgaben am Ende jedes Kapitels sind integraler Bestandteil des Textes. Einige von ihnen behandeln interessante Anwendungen des Stoffs.
 Der AutorProf. Dr. Christian Bär 
 hatte Professuren in Freiburg und Hamburg inne und ist heute Professor für Geometrie an der Universität Potsdam. Er war Präsident der Deutschen Mathematiker-Vereinigung und ist neben seiner Tätigkeit in Forschung und Lehre Chefredakteur von zbMATH Open.

Das Werk bietet eine Einführung in die lineare Algebra und die analytische Geometrie und enthält Material für eine zweisemestrige Vorlesung. Es beginnt mit einem Kapitel, das allgemein in die mathematische Denkweise und Beweistechniken einführt, um dann über lineare Gleichungssysteme zur linearen Algebra überzuleiten. Der Text spannt den Bogen bis hin zu Tensorprodukten und ihren Anwendungen im Quantencomputing. Besonderer Wert wird auf eine enge Verzahnung von algebraischen und geometrischen Konzepten gelegt, zum einen um eine gute geometrische Intuition für algebraische Begriffe zu entwickeln, zum anderen um elegante algebraische Beweismethoden für geometrische Sätze einsetzen zu können.Der Text ist klar und verständlich geschrieben und in einem erfrischenden Stil verfasst. Interaktive Online-Übungsseiten und Illustrationen regen zu einem aktiven Studium an. Sie können auf internetfähigen Geräten mittels der angegebenen URL oder des QR-Codes aufgerufen werden. Die Aufgaben am Ende jedes Kapitels sind integraler Bestandteil des Textes.&nbsp;Einige von ihnen behandeln interessante Anwendungen des Stoffs.&nbsp;&nbsp;

Lineare Algebra und analytische Geometrie

Build Bayesian Networks and Causal Inference Models with R and Python

Causal Inference with Bayesian Networks

Banish Your Mouse. The Linux Command Line isn’t just a reference manual. It’s a complete education on how Linux really works. From your first tentative keystrokes to writing powerful shell scripts, you’ll build the confidence and understanding to make your system work for you. Now in its third edition, this best-selling guide has been fully updated with modern examples, nearly 40 pages of new content, and downloadable scripts from LinuxCommand. Used in more than a thousand classrooms and libraries worldwide, it has helped over 150,000 readers gain fluency and confidence in Linux. Author and command line guru William Shotts delivers not just commands, but genuine insight, guided by his philosophy: Make everything as simple as possible, but no simpler. Through short, digestible chapters, you’ll learn to: <ul><li>Navigate the filesystem, manage files, and configure your environment</li><li>Chain commands, redirect input/output, and use regular expressions</li><li>Control processes, manage packages, and work with networking tools</li><li>Edit text with Vim</li><li>Write shell scripts to automate tasks and build custom tools</li><li>Use core utilities like grep, cut, sed, and tar to process data</li><li>Manage filesystems and compile programs from source</li></ul> Whether you’re managing servers, studying cybersecurity, or just curious about your computer, The Linux Command Line gives you the knowledge to command your system with confidence.

Banish Your Mouse. The Linux Command Line isn’t just a reference manual. It’s a complete education on how Linux really works. From your first tentative keystrokes to writing powerful shell scripts, you’ll build the confidence and understanding to make your system work for you. Now in its third edition, this best-selling guide has been fully updated with modern examples, nearly 40 pages of new content, and downloadable scripts from LinuxCommand. Used in more than a thousand classrooms and libraries worldwide, it has helped over 150,000 readers gain fluency and confidence in Linux. Author and command line guru William Shotts delivers not just commands, but genuine insight, guided by his philosophy: Make everything as simple as possible, but no simpler. Through short, digestible chapters, you’ll learn to: <ul><li>Navigate the filesystem, manage files, and configure your environment</li><li>Chain commands, redirect input/output, and use regular expressions</li><li>Control processes, manage packages, and work with networking tools</li><li>Edit text with Vim</li><li>Write shell scripts to automate tasks and build custom tools</li><li>Use core utilities like grep, cut, sed, and tar to process data</li><li>Manage filesystems and compile programs from source</li></ul> Whether you’re managing servers, studying cybersecurity, or just curious about your computer, The Linux Command Line gives you the knowledge to command your system with confidence.

A Complete Introduction

The Linux Command Line, 3rd Edition

Disjunctive Programming

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