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Free Download Designing with Alternative Building Materials and Review of Building Materials by Kalyan Kumar Ganguly
English | June 1, 2025 | ISBN: 1032333189 | 668 pages | PDF | 69 Mb
This book explores alternative building materials and their test results. It includes a review of common building materials, earth engineering and construction, suitable soil types, soil mechanics and production, masonry construction, rammed earth construction, the use of ferro-cement units in projects, and the application of fibre-reinforced concrete. Other topics such as project management, computer-aided design, education and training for engineers, construction work, quality control, safety aspects, communication, applications and case studies, accompanied by construction photographs, are covered in this book.

Free Download Designing for Older Adults: Principles and Creative Human Factors Approaches By Arthur D. Fisk, Wendy A. Rogers, Neil Charness, Sara J. Czaja, Joseph Sharit
2004 | 176 Pages | ISBN: 0415286115 | PDF | 1 MB
As life expectancy increases, older workers and the retired form a large and growing proportion of the world's population. Professionals working to develop systems and environments need to better accommodate the user needs of the older adult. This new guide provides a practical introduction to human factors and the older adult. It considers the subject primarily from an engineering psychology perspective, heavily grounded in today's scientific knowledge. The authors show how current understanding of age-related issues of perception, cognition, and movement control can be applied in practice. They also provide a reference source with guidelines and advice for design issues ranging from lighting, computer input device selection, and web site design, to training program development and work task design. The text draws on research-oriented work and presents this in a form that can be used by the broad audience of product designers, health care practitioners, managers, and others who need answers to problems and require sound recommendations for design.

Free Download Designing for AI Internal Control and Compliance: The Ledger-Cache Drift and Mutability Control Framework
English | December 13, 2025 | ASIN: B0G6VPCZG1 | 198 pages | Epub | 776.42 KB
AI systems have an architectural vulnerability that mainstream discourse completely ignores. Enterprise AI increasingly relies on dual-state architectures: authoritative baselines paired with fast working copies. This pattern appears everywhere-data systems, ML platforms, IT operations, emerging hardware. It's elegant and efficient, but creates serious control problems. When both states can change independently, auditors cannot prove which state drove a decision. Traditional frameworks don't address this drift dynamic. EU regulations demand explanations of algorithmic decisions. SOX violations carry severe consequences. Legal challenges are mounting. This book delivers the Ledger-Cache Drift & Mutability Control (LCDMC) framework-ten design controls addressing internal controls and compliance exposure across all dual-architecture systems. Written by a veteran IT, Internal and Big Four auditor and multinational technology consultant with decades implementing IT systems and solutions, this book is relvant for: Auditors: testable criteria for AI system verification. Organizations: a blueprint for designing compliance in from the start. Technical teams: governance patterns that address drift and mutability before they become legal exposure. Don't retrofit controls after deployment. Design compliance in from the start. This book shows you how with audit tests, schema and code examples, cross reference to audit assertions, internal control objectives and specific regulations plus how LCDMC extends existing control frameworks like COSO and SOX and more. Here is the book structure: Introduction Chapter 1 - The Compliance Challenge Chapter 2 - Compliance Risks Explained Chapter 3 - The LCDMC Playbook Chapter 4 - Mapping to Regulatory Frameworks Chapter 5 - Audit Approach Chapter 6 - Practical Applications Chapter 7 - Conclusion Appendix A - Event Log Requirements and Schemas Appendix B - Cross-Domain Risk Comparison Appendix C - Calibration and Verification Protocols Appendix D - Hardware Systems Technical Detail Appendix E - Quick Reference Card for Auditors Appendix F - LCDMC Integration with Domain Objectives Appendix G - Glossary of Terms Bibliorapyy

Free Download Designing Smart Autonomous Systems: Integrating AI, Robotics, and Edge Intelligence for Smarter Automation
English | December 18, 2025 | ASIN: B0G8D4D5NC | 51 pages | Epub | 1.93 MB
Designing Smart Autonomous Systems is a practical guide to building intelligent, adaptive systems that can operate independently in complex, dynamic environments. As industries increasingly adopt AI, robotics, and IoT, understanding how to design autonomous systems is essential for engineers, developers, and technology leaders. This book explores the principles, tools, and frameworks needed to integrate machine learning, sensor networks, and real-time decision-making into autonomous systems. Through real-world examples and case studies, readers will learn how to design systems that can perceive their environment, make decisions, and act effectively without human intervention. From robotics and smart vehicles to industrial automation and AI-driven processes, Designing Smart Autonomous Systems provides a roadmap for translating theory into practical, deployable solutions. The book emphasizes modular design, reliability, and scalability, helping readers build systems that are not only intelligent but also safe, efficient, and adaptable.

Free Download Designing Modern Data Systems: Decision-Focused Software Architecture for Data Engineering, System Design, and Large Language Model Platforms
English | December 25, 2025 | ASIN: B0GCKSWRQW | 422 pages | EPUB (True) | 3.16 MB
Data systems outlive applications, frameworks, and infrastructure. They encode decisions that shape what a system can become-and what it can never safely change. Designing Modern Data Systems is a deep, decision-driven guide to building data systems that are reliable, scalable, and adaptable over time. Rather than focusing on tools or trends, this book teaches how to reason about architecture itself: how guarantees are chosen, where authority lives, how failures manifest, and how systems evolve under real-world pressure. Written for experienced engineers and architects, the book treats data systems as long-lived sociotechnical systems-not just databases or pipelines. It focuses on clarity of responsibility, explicit trade-offs, and preserving meaning as data moves, changes, and ages. What This Book Covers This book takes a structured journey through modern data system design: How to define data systems as distinct from applications and infrastructure How non-functional requirements like reliability, availability, latency, and cost shape architecture long before technology choices How to design data models, storage engines, and indexing strategies that survive product evolution How to reason about replication, partitioning, coordination, and distributed transactions without accidental complexity How batch and stream processing fit into a unified view of data over time How logs, history, and derived data enable recovery, reprocessing, and safe change How to operate systems in production with observability, backpressure, and failure isolation How to design data systems that support machine learning and large language model platforms , including feature pipelines and embeddings How to migrate, evolve, and decommission systems without outages or loss of trust Throughout the book, ideas are grounded in a single evolving reference system, allowing readers to see how architectural decisions accumulate and interact as requirements change. What Makes This Book Different Decision-focused, not tool-driven The book avoids product comparisons and instead teaches how to evaluate any technology within clear architectural constraints. Explicit trade-offs, not recipes Every design choice is examined in terms of what it enables, what it forbids, and what it costs. Modern, without being trendy AI and LLM systems are addressed where they introduce real architectural pressure-without hype or speculation. Written for longevity The principles in this book are designed to remain relevant as tools, platforms, and organizational structures change. This book is written for: Software engineers designing backend and platform systems Data engineers responsible for storage, processing, and pipelines Staff, principal, and senior engineers shaping architectural direction Architects and technical leaders responsible for long-term system evolution Practitioners preparing for system design interviews who want judgment, not templates It assumes familiarity with software systems and databases, but does not require expertise in any specific language, framework, or vendor. What This Book Is Not A beginner's introduction to databases A step-by-step tutorial for specific tools A catalog of technologies or patterns If you are responsible for making architectural decisions-and living with their consequences- Designing Modern Data Systems is written for you. Order Now

Destroyer Weapons of World War 2

Destination Dissertation, 3rd Edition

Designing with ChatGPT A Modern Creative's Evolution

Designing with Alternative Building Materials and Review of Building Materials

Designing for Situation Awareness An Approach to User-Centered Design, Third Edition

Designing for Older Adults Principles and Creative Human Factors Approaches

Designing for AI Internal Control and Compliance The Ledger-Cache Drift and Mutability Control Framework

Designing TTRPGs For Dummies

Designing Smart Autonomous Systems Integrating AI, Robotics, and Edge Intelligence for Smarter Automation

Designing Modern Data Systems Decision-Focused Software Architecture for Data Engineering, System Design, and Large Language