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Paperback. Condición: new. Paperback. The development of lightweight, durable, and high-performance gear materials is an important area of modern mechanical and materials engineering. Development and Performance Evaluation of Silicon Carbide Coated Aluminum Hybrid Composite Gears provides a focused introduction to the design, material characteristics, surface engineering, processing considerations, and performance evaluation of aluminum-based hybrid composite gears incorporating silicon carbide coatings. The book brings together concepts from mechanical engineering, materials science, tribology, manufacturing, composite materials, and surface engineering within a structured technical framework.The book introduces the fundamental principles of gear systems and the engineering requirements associated with gear materials. Readers are introduced to concepts such as gear geometry, mechanical loading, contact stresses, friction, wear, hardness, surface durability, and dimensional stability. These foundations provide the necessary context for understanding why material selection and surface modification are important when developing gears for demanding mechanical applications.A central focus is placed on aluminum-based hybrid composite materials and the role of silicon carbide as a reinforcing and surface-engineering material. The text examines the characteristics of aluminum matrices, hybrid reinforcement, silicon carbide, and coated surfaces, with attention to material structure, hardness, wear resistance, thermal behavior, and mechanical response. The discussion considers how material composition and surface characteristics can influence the functional performance of gears.The book further explores the development and evaluation of silicon carbide coated aluminum hybrid composite gears. Topics such as coating formation, surface characteristics, adhesion, hardness, friction, wear, load-bearing behavior, and surface integrity are considered within the broader context of gear engineering. Readers gain an understanding of how surface modification and composite material design can be evaluated through measurable engineering parameters.Tribological performance is an important component of gear reliability, and the book considers the relationship between friction, wear, contact conditions, lubrication, and surface properties. The discussion introduces general approaches for evaluating wear behavior and frictional response while examining how silicon carbide-based surface protection can influence the interaction between contacting surfaces. These concepts are presented as general engineering principles rather than unsupported claims about specific industrial performance.The book also addresses mechanical and structural evaluation of composite gears. Considerations such as tensile and compressive behavior of constituent materials, hardness, dimensional characteristics, surface morphology, gear tooth integrity, and resistance to mechanical degradation are discussed in relation to material and processing variables. Characterization methods provide a basis for connecting material structure and surface condition with measurable gear performance.Manufacturing and materials-processing considerations are also introduced. The relationship between composite formulation, reinforcement, coating characteristics, processing conditions, and final component performance is examined from a general engineering perspective. Attention is given to the importance of controlling surface quality, coating integrity, material uniformity, and dimensional characteristics when developing advanced gear components. Development and Performance Evaluation of Silicon Carbide Coated Aluminum Hybrid Composite Gears explores aluminum-based hybrid composite gears and silicon carbide surface coatings, with emphasis on material development. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Condición: new. Paperback. The rapid growth of online social networks has transformed the way individuals communicate, share information, and participate in digital communities. At the same time, the enormous volume of user-generated data has created significant opportunities for data mining while raising important concerns regarding privacy, security, and responsible data management. Privacy-Preserving Data Mining for Online Social Networks provides a comprehensive introduction to the principles, techniques, and challenges involved in extracting meaningful knowledge from social network data while protecting individual privacy and maintaining data confidentiality.The book examines the intersection of data mining, privacy preservation, social network analysis, and information security, presenting the engineering and computational concepts that support responsible data analysis in large-scale online environments. Readers are introduced to the fundamentals of knowledge discovery, data preprocessing, pattern recognition, classification, clustering, association analysis, anomaly detection, and predictive analytics as they relate to online social platforms. The discussion emphasizes the importance of balancing analytical utility with privacy protection to enable ethical and compliant data-driven decision-making.A central focus is placed on privacy-preserving methodologies that reduce the risk of exposing sensitive information during data collection, storage, sharing, and analysis. The text explores widely recognized approaches including data anonymization, data masking, pseudonymization, secure data publishing, differential privacy, privacy-aware data transformation, cryptographic techniques, and secure multi-party computation. These concepts are presented within the broader framework of privacy engineering, helping readers understand how technical safeguards contribute to secure and trustworthy data mining processes.The book further discusses the structure and dynamics of online social networks, highlighting how graph-based data models, user interactions, community detection, influence analysis, recommendation systems, sentiment analysis, and network evolution contribute to understanding social behavior. It also examines the ethical, legal, and security considerations associated with processing social network data, including data governance, access control, identity protection, risk management, and regulatory compliance. These discussions provide readers with a balanced understanding of both the opportunities and responsibilities associated with mining large-scale social datasets.Designed for undergraduate and graduate students, researchers, data scientists, computer engineers, cybersecurity professionals, educators, and information technology practitioners, this volume serves as both an academic reference and a practical introduction to privacy-aware data mining. The material emphasizes broadly applicable computational principles and established methodologies rather than proprietary software platforms or vendor-specific technologies, making it suitable for university coursework, research, and professional development.As organizations increasingly rely on social data to support business intelligence, public policy, cybersecurity, healthcare, marketing, and scientific research, preserving user privacy has become a critical requirement. Privacy-Preserving Data Mining for Online Social Networks provides readers with a structured understanding of the technologies, analytical methods, and privacy-enhancing techniques that enable responsible knowledge discovery from social network data. Optimized for engineering students, academic libraries, universities, researchers, and data professionals, this book serves as a valuable resource for exploring privacy-preserving analytics, social network mining, data Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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paperback. Condición: New.

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