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Engineering (R0)

Nishu Gupta

Jose David Diaz Roman

Decision Support Systems for Industrial and Scientific Applications

&lt;p&gt;Introduction.- Anomaly Detection in Smart Manufacturing Using an Intelligent Decision Support System with Applications in Supply Chain Management.- Lung and colon cancer detection system in histopathological images based on deep transfer Learning.- Design of an application to support the diagnosis of skin cancer using deep learning.- Enhancing Vascular Structure from Computed Tomography Angiography Images using Score-based Generative Models.- Remote medical assistance y wearable devices in health applications.- Product Demand Forecasting in the Industry 4.0 through machine learning and Intelligent Decision Support Systems.- Application of the Sugeno-Takagi-Kang considering fuzzy logic for demand forecasting in the supply chain: a Fuzzy temporary series forecast model (FTS) proposal.- Optimizing a Smart City’s Urban Park Lighting using Monkey Algorithm.- Intelligent System for Multimedia Data Analysis in Industry 4.0 using a Smart color management approach.- Technologies for Vehicle Classification in Intelligent Traffic Systems: Advances, Challenges, and Perspectives.- Conclusion.&lt;/p&gt;


Wiley Finance

The handbook to unleash the power of AI in Finance with guidance to pragmatically managing AI Risk Are you ready to harness the transformative potential of artificial intelligence and machine learning in finance while effectively managing the associated risks? "AI and Risk Management in Finance: A Practitioner's Handbook" by Sri Krishnamurthy, CFA, is your indispensable guide. Tailored for financial professionals, this comprehensive handbook delivers practical insights, case studies, and frameworks to navigate the complex landscape of AI and ML in the financial sector. This pragmatic handbook, developed primarily for professionals involved in designing, developing, and deploying AI models in the financial industry explores cutting-edge technologies, regulatory landscapes, and pragmatic frameworks. From generative AI to robust risk management strategies, this handbook equips you with the tools you need to validate models, ensure compliance, and operationalize AI risk management effectively. Leveraging lessons from QuantUniversity's AI and Machine Learning Risk Management program offered in 18 countries, this book focuses on enabling practitioners apply the state-of-the-art AI and machine learning techniques factoring unique risks specific to the financial services domain. Whether you're a seasoned professional or a newcomer, this book offers invaluable insights for harnessing the power of AI responsibly in the financial industry. Highlights of the Book: <ul> <li>Machine Learning and AI in Financial Services: Dive into the fundamentals of ML and AI, exploring various applications within the financial industry through real-world case studies.</li> <li>Generative AI and LLMs in Finance: Understand the emerging landscape, key players, and advanced concepts like prompt engineering and fine-tuning with practical examples.</li> <li>Risk Management for AI/ML Applications: Learn about current and emerging regulatory landscapes, AI risk management frameworks, and legislative efforts shaping the field.</li> <li>Data Governance Issues: Address critical aspects of data quality, privacy, security, and governance, with actionable frameworks and illustrative case studies.</li> <li>Model and System Governance: Gain insights into validating machine learning models, quantifying model risk, and ensuring robust system governance with MLOps and model monitoring.</li> <li>Key Risk Assessment Facets: Focus on documentation, explainability, fairness, security, and reliability with detailed case studies.</li> <li>Verification and Validation: Distinguish between verification and validation and learn frameworks for effective AI application validation.</li> <li>Algorithmic Auditing: Conduct comprehensive algorithmic audits with detailed processes and real-world examples.</li> <li>Operationalizing AI Risk Management: Discover ten essential strategies for implementing AI risk management practices effectively in your organization.</li> </ul> Prepare for the future of finance with expert advice and actionable strategies. Don't miss out on this comprehensive guide-your roadmap to navigating AI and risk management in the financial sector.

A Practitioner�s Guide to Machine Learning, Generative AI, Agentic Systems, and Responsible Deployment

AI and Risk Management in Finance

Integrated Mega-Models and Systems Science

This open access book offers a systematic introduction to operational thinking as a distinctive Chinese cognitive framework for understanding and governing complex systems. Drawing on five millennia of Chinese civilization, it traces how strategic wisdom evolved from Yu the Great’s flood control, Dujiangyan and the Three Gorges Project to today’s South–North Water Transfer, “Dual Carbon” strategy, smart cities and AI-enabled decision-making. This book provides an original “trinity” framework of systems thinking, coordinated planning thinking, and balancing thinking, explaining how structural cognition, process integration, and conflict coordination work together to solve multi-objective, multi-constraint problems. Through rich historical and contemporary cases—from classical texts such as The Art of War, Qimin Yaoshu and Discourses on Salt and Iron to modern mega-projects, digital platforms and resilient supply chains—it shows how Chinese governance wisdom has been continuously transformed into modern methodologies for optimization, risk control and strategic planning. Methodologically, this book develops a complete toolkit of “structural cognition–process integration–conflict coordination,” supported by cognitive models, case analysis, and digital-intelligent teaching tools. It demonstrates how operational thinking can guide national governance modernization, regional coordinated development, industrial upgrading, and personal time- and life-management (for example, via the “Four Quadrants Rule”). By integrating traditional culture, systems science, management science and AI, this book builds an independent knowledge system of operational thinking with Chinese characteristics, contemporary value and global relevance. It helps readers move from “cognitive mapping” to “practical navigation,” and from intuitive judgment to data- and model-driven decision-making.

The Mind of Operations

The Art Law Library

This open access book investigates the role played by copyright on the digitisation of cultural heritage from three angles: the theoretical differences between cultural property law and copyright; a comparative analysis of the EU, UK, and US; and analysis of current practices and concerns, based on empirical research. As heritage digitisation projects become increasingly common for purposes such as preservation and access, the impact of copyright is also becoming more problematic. In order to provide a full and current picture of the copyright problem, the book first introduces the reader to the debates on the scope and ownership of cultural heritage and provides an overview of the copyright implications of the digitisation process and newer uses, including 2D and 3D scanning; virtual and augmented reality; text and data mining; and artificial intelligence. The author then divides the main critical analysis into three parts, referred to as the 'clashes with copyright'. The first, clash in theory, lies between cultural property law and copyright justification theories. The second clash is in the different legal approaches to digitising in-copyright, public domain, orphan, out-of-commerce and unpublished works in the chosen jurisdictions, focusing on the relevant rights and defences. The third clash is in the interests of stakeholders, based on public reactions to existing projects and cases, supported by interviews with heritage professionals engaging in digitisation. By placing itself in this particular intersection of law, heritage, and technology, the book will be of interest to both intellectual property academics and cultural heritage professionals. The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com.

Clashes with Copyright Law

Digitising Cultural Heritage

Research in Creative Writing

Writing Human in the Age of AI

This book is the first investigation of the relationship between EU digital sovereignty and sustainability strategies. It maps the ambitions and limitations of EU digital strategic autonomy and explores the structural challenges underlying its relationship with its green transition objectives in the context of the ongoing wars in neighbouring European countries and the consequent tensions in the EU energy sector. The EU is racing to achieve technological independence from third countries and foreign multinational companies to protect its digital sovereignty and preserve its fundamental rights. In the EU, digitalisation and the green transformation are seen as twin transitions. Yet, EU digital sovereignty strategies have a significant environmental cost. Reaching a status of strategic autonomy of the EU at the level of digital infrastructures, products, services and data implies higher energy consumption and exploitation of natural resources. Moreover, the geopolitical tensions following the Russian invasion of Ukraine have provoked an unprecedented energy crisis, which is affecting EU economies and impacting objectives of the twin transitions. The book offers an interdisciplinary analysis of the major EU regulatory and policy instruments in this field, providing an invaluable guide for academics, practitioners, and policymakers navigating the complex issues of preserving digital sovereignty and addressing climate change in times of war and energy crisis.

EU Challenges in Times of War and Energy Crisis

Digital Sovereignty and the Green Transition

An acclaimed New York Times Magazine writer brings us into the world of the controversial technology firm Palantir and its very colorful and outspoken CEO, Alex Karp, tracing the ascent of Big Data, the rise of surveillance technology, and the shifting global balance of power in the 21st century. Palantir builds data integration software: its technology ingests vast quantities of information and quickly identifies patterns, trends, and connections that might elude the human eye. Founded in 2003 to help the US government in the war on terrorism—an early investor was the CIA—Palantir is now a $400 billion global colossus whose software is used by major intelligence services (including the Mossad), the US military, dozens of federal agencies, and corporate giants like Airbus and BP. From AI to counterterrorism to climate change to immigration to financial fraud to the future of warfare, the company is at the nexus of the most critical issues of the 21st century. Its CEO, Alex Karp, is a distinctive figure on the global business scene. A biracial Jew who is also severely dyslexic, Karp has built Palantir into a tech giant despite having no background in either business or computer science. Instead, he’s a trained philosopher who has become known for his strongly held views on a range of issues and for his willingness to grapple with the moral and ethical implications of Palantir’s work. Those questions have taken on added urgency during the Trump era, which has also brought attention to the political activism of Karp’s close friend and Palantir cofounder Peter Thiel. In The Philosopher in the Valley, journalist Michael Steinberger explores the world of Alex Karp, Palantir, and the future that they are leading us toward. It is an urgent and illuminating work about one of Silicon Valley’s most secretive and powerful companies, whose technology is at the leading edge of the surveillance state.

Alex Karp, Palantir, and the Rise of the Surveillance State

The Philosopher in the Valley

Humanity's most spectacular era yet is increasingly within reach.So why are we doing everything we can to hold it back?The bestselling author of The Rational Optimist delivers a daring vision of the future - one that is potentially dazzling, but only if we stop sleepwalking into self-inflicted decline.We're on the brink of a truly spectacular explosion of productivity and prosperity, argues Matt Ridley, thanks to a combination of artificial intelligence, material science and genomic knowledge that is unprecedented in its scope and implications. With characteristic wit and ferocity, he confronts the irrational pessimism that dominates public discourse and examines the bureaucratic bloat, regulatory overreach, ideological superstition and crony capitalism that stand in the way.Optimistic in conclusion but unsparing in its analysis, The Flourishing is a rousing call to achieve and innovate by refusing to settle for a merely adequate future when a magnificent one is within reach.

The Rational Pessimist

The Promise and Peril of Navigating Our Agentic AI Future

When Machines Act

Emerging Trends in Science, Innovation and Business

"Federated Learning Applications in Healthcare: Empowering Wellness" is an ambitious and timely endeavor aimed at providing a comprehensive exploration of the intersection between federated learning and healthcare.Federated learning, a decentralized machine learning approach that enables model training across multiple devices or institutions without centralized data sharing, holds immense promise for revolutionizing healthcare by facilitating collaboration, preserving patient privacy, and improving healthcare outcomes. This book aims to unravel the complexities of federated learning and demonstrate its transformative potential in various healthcare applications. Through a combination of theoretical insights, practical guidelines, case studies, and real-world examples, the book aims to empower readers to harness the potential of federated learning to address pressing healthcare challenges effectively.Whether readers are healthcare professionals seeking to leverage data-driven approaches to improve patient care, researchers exploring innovative solutions at the intersection of machine learning and healthcare, policymakers grappling with regulatory and ethical considerations, or technologists developing cutting-edge healthcare solutions, this book serves as a valuable resource for understanding, implementing, and advancing federated learning in healthcare.

Empowering Wellness

Federated Learning Applications in Healthcare

Turn AI investment into scalable business impact by enabling your workforce to build the solutions they actually need. From AI Users to Solution Builders is a strategic guide for senior AI, technology, and transformation leaders who want to move beyond underperforming, centralized AI initiatives, and unlock real enterprise value. As organizations struggle to translate AI into measurable results, this book shows how shifting from top-down deployment to workforce-led solution building creates faster adoption, stronger ROI, and sustained innovation. Written by experienced AI leader Wei Manfredi, this book combines strategic insight with practical execution. It draws clear parallels between failed digital transformation efforts and current AI adoption challenges, while demonstrating how natural language interfaces are reshaping access to AI. By enabling non-technical professionals to design their own tools, organizations can embed AI directly into workflows, decision-making, and daily operations. You'll learn how to: - Shift from centralized AI models to workforce-driven innovation - Enable employees to build AI solutions for real workflows - Design scalable infrastructure for AI solution development - Apply change management to overcome resistance and drive adoption &gt;Featuring real-world examples from organizations including Lululemon, Google, Oracle, and JPMorgan Chase, this book provides a proven framework for embedding AI into everyday collaboration, accelerating innovation, and future-proofing your organization's competitive advantage. Themes include: AI strategy, AI adoption, workforce transformation, AI governance, enterprise AI, change management

Scaling AI Across Your Organization

From AI Users to Solution Builders

Build a resilient, high-performing organization by integrating agentic AI into strategy, operations, and decision-making. Building an Agentic Organization is a strategic guide for senior technology, AI and business leaders responsible for delivering value from agentic AI while managing its risks. As organizations move toward human and AI collaboration at scale, leaders must balance innovation with governance, adoption, and long-term economic impact. Written by experienced AI executive Geoffrey Schaefer, this book provides a comprehensive framework for designing an agentic organization by examining strategy, governance, and economics. It explores how to define the purpose of agentic AI, align it with business objectives, and create the structures needed to support safe, scalable adoption. Addressing both opportunity and risk, it equips leaders to navigate workforce concerns, reputational exposure, and the evolving role of AI agents in enterprise environments. You'll learn how to: - Define a clear strategy for integrating agentic AI - Establish governance frameworks to manage risk and accountability - Drive workforce adoption and address resistance to AI collaboration - Assess economic value and impact of agentic AI systems - Manage reputational and operational risks from AI agent behavior Featuring real-world examples from Leidos, JPMorgan Chase, SY Partners, and OMA, this book provides a practical roadmap for embedding agentic AI into the fabric of your organization while protecting value, trust, and long-term performance. Themes include: agentic AI, AI strategy, AI governance, AI transformation, enterprise AI, risk management

The Strategy, Governance, and Economics of Agentic AI

Building an Agentic Organization

Decision Support Systems for Industrial and Scientific Applications

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