Biomedical Applications of Perovskites: The Era of Bio-Piezoelectric Systems focuses on recent developments in the area of piezoelectric systems and their biomedical applications. A compilation of 19 edited chapters covers different piezoelectric materials, device designs, and their use cases. Readers will be familiarized with the many perovskite materials being used in research and development as well as the role they play in designing novel medical devices and biomaterials. Key Features - systematically explains the piezoelectric perovskite materials starting from their introduction, their structure and synthesis techniques - explains the key materials used in devices such as pacemakers and nanogenerators - highlights a range of applications including bone regeneration and growth, bone replacement, tissue engineering, dental science, neurotrauma and neurodegenerative disease treatment and bionic prosthesis - discusses future challenges and the roadmap for piezoelectric perovskite materials - Presents scientific references for advanced reading

Smart Kinematics for Modern Engineering Students is an essential reference on basic kinematics. The book provides detailed knowledge on coordinate transformations for matrix calculations, followed by information about different configurations in component pairs and joints. Readers will learn about the basic mechanical engineering methods used to design components for systems with moving parts along with various practical applications of these concepts. Key Features - Provides-In-depth knowledge of 3D vector calculations in kinematics - Includes descriptions and depictions of major joints commonly used in engineering designs and applications - Discusses common methods of optimization for solving multivariable systems of highly nonlinear equations using displacement models - Presents practical examples of analysis applied to commonly used mechanical system - 6 DOF robotic arm and moving platform - A generic Light Manufacturing Tool (LMT) - Phantom DOF devices - Temporomandibular joint (TMJ) as a biomechanical joint - Include scientific references The material in this book will be helpful to undergraduate and graduate engineers who are required to understand knowledge about modern methods in mechanical engineering, including prerequisite courses in advanced linear algebra, kinematics and complex systems.

This reference provides a comprehensive overview of computational modelling and simulation for theoretical and practical biomedical research. The book explains basic concepts of computational biology and data modelling for learners and early career researchers. Chapters cover these topics: 1. An introduction to computational tools in biomedical research 2. Computational analysis of biological data 3. Algorithm development for computational modelling and simulation 4. The roles and application of protein modelling in biomedical research 5. Dynamics of biomolecular ligand recognition Key features include a simple, easy-to-understand presentation, detailed explanation of important concepts in computational modeling and simulations and references.

Introduction to Advanced Soft Robotics is an introductory textbook on soft body robotics. The content is designed to enable readers to better understand soft body robotics. Starting with an introduction to the subject, contents explain fundamental concepts such as perception and sensing, fabrication techniques and material design. These introductory chapters demonstrate the design concept and related design structures of soft robots from multiple perspectives, which can provide considerable design references for robotics learners and enthusiasts. Next, the book explains modeling and control for soft robotics and the applications. Key features of this book include easy-to-understand language and format, simple illustrations and a balanced overview of the subject (including a section on challenges and future prospects for soft robotics), and scientific references.

This volume explores diverse applications for automated machine learning and predictive analytics. The content provides use cases for machine learning in different industries such as healthcare, agriculture, cybersecurity, computing and transportation. Key highlights of this volume include topics on engineering for underwater navigation, and computer vision for healthcare and biometric applications. Chapters 1-4 delve into innovative signal detection, biometric authentication, underwater AUV localization, and COVID-19 face mask detection. Chapters 5-9 focus on wireless pH sensing, differential pattern identification, economic considerations in off-grid hybrid power, high optimization of image transmission, and ANN-based IoT-bot traffic detection. Chapters 10-12 cover mixed-signal VLSI design, pre-placement 3D floor planning, and bio-mimic robotic fish. Finally, Chapters 13 and 14 explore underwater robotic fish and IoT-based automatic irrigation systems, providing a comprehensive overview of cutting-edge technological advancements. The book is a resource for academics, researchers, educators and professionals in the technology sector who want to learn about current trends in intelligent technologies.

This volume is a review of recent developments, opportunities, and challenges in the conversion of biomass from different sources to biodiesel or related fuel additives. Key features of the book include fully referenced chapters edited by experts, a blend of basic and current information on biodiesel and a summary of sustainable use of biodiesel byproducts like glycerol. The volume presents a comprehensive range of 13 topics related to biodiesel production and fuel additives. It begins with a historical overview of biodiesel and related additives, followed by detailed chapters on biodiesel production from various sources such as soybean oil, palm oil, and Jatropha curcas oil. Recent advancements in catalytic thermochemical conversions of biomass into biofuels are explored, alongside discussions on algal biocrude as a feedstock. The role of homogeneous and heterogeneous catalysis in biodiesel production is examined, along with innovative techniques such as microwave and ultrasound-assisted synthesis. The book also presents information about the utilization of waste cooking oil and waste-derived catalysts, concluding with insights into solketal synthesis and catalytic biodiesel production via simultaneous esterification and transesterification. The book imparts the technical know-how on biodiesel and relevant fuel additives for engineering and sustainability students, professionals and apprentices. It also informs policymakers in the energy sector on the benefits of biodiesel as a renewable energy resource.

This volume covers a wide array of topics related to research, technology and sustainability for technology researchers and educators. Chapter 1 explores the detection of fake news in a distributed environment. Material science is covered in Chapter 2, which explains the influence of MOS2, B4C, and graphite on the mechanical and dry sliding wear behavior of aluminum 7075 hybrid matrix composites. Chapter 3 focuses on sensors and antennas for smart sensor networks. Chapters 4 to 8 delve into various aspects of electrical and computer engineering, including induction motor condition monitoring, automatic conversion of building plans to graphs for robot navigation, and analysis of defects in microscopic and electroluminescent images using AI and image processing algorithms. Chapters 9 to 16 cover topics such as missing data prediction techniques, breast cancer diagnosis on mammography, groundwater contamination, biofertilizers, organic farming, and remediation using organisms. Sustainable development is a key theme in Chapters 17 to 26, addressing issues like sensor-based vehicle fuel theft detection, waste management techniques, bioremediation of soil contaminated with heavy metals, sustainable agriculture practices, and novel approaches in bioplastics and nanoremediation. Finally, Chapters 27 to 29 touch upon renewable energy and Industrial IoT, discussing research challenges in renewable energy sources, recent trends, and the transformation brought about by the Industrial Internet of Things.

Multidimensional Nanomaterials for Supercapacitors: Next Generation Energy Storage explores the cutting-edge advancements in multidimensional nanomaterials for supercapacitor applications, addressing key techniques, challenges, and future prospects in the field. The book offers a comprehensive overview of the fundamentals of supercapacitors, including electrode materials, electrolytes, charge storage mechanisms, and performance metrics. Key Features Comprehensive Coverage: 15 referenced chapters cover a wide range of topics, including graphene derivatives, quantum dots, MOFs, MXenes, and fiber-shaped supercapacitors, providing a holistic view of the field. Cutting-Edge Techniques: Covers the latest advancements in multidimensional nanomaterials for supercapacitors, providing insights into their synthesis, properties, and applications. Future Applications: Chapters explore the potential future applications of nanomaterials in energy storage devices, offering valuable insights for researchers and practitioners. Real-World Case Studies: Practical examples and case studies illustrate the application of nanomaterials in supercapacitors, enhancing understanding and applicability. Challenges and Opportunities: Highlights the challenges and limitations associated with nanomaterial-based supercapacitors, offering information into overcoming barriers and expanding possibilities for future research.

Computational simulation and experimental techniques for nanofluid flow is a collection of studies on nanofluid modelling. It brings together eight detailed research articles that describe the latest developments in nanofluid flow experimentation and simulation. Topics covered include numerical flow simulations and applications on MHD viscous nanofluid, bioconvective nanofluid, oblique nanofluid, Casson nanofluid, hybrid nanofluid, Darcy-Forchheimer hybrid nanofluid, magneto-radiative Ag-water nanofluid, and thixotropic nanofluid. Key Features - Includes eight chapters authored by experts in fluid mechanics and numerical simulation - Showcases significant and novel attempts on computational simulation modelling for developing new mathematical models on nanofluids at the research level - Highlights current research intended to advance mathematics and other areas of science and technology - Includes references for advanced readers This publication is essential for researchers and students, academicians who are learning nanofluid flow models. Readers involved in applied research and development projects involving nanofluids will also benefit from the information (environmentalists, technicians and biomedical engineers).

This volume explores a diverse range of applications for automated machine learning and predictive analytics. The content provides use cases for machine learning in different industries such as healthcare, agriculture, cybersecurity, computing and transportation. Chapter 1 introduces an innovative device for automatically notifying and analyzing the impact of automobile accidents. Chapter 2 focuses on the detection of malaria using systematized image processing techniques. In Chapter 3, an intelligent technique based on LMEPOP and fuzzy logic for the segmentation of defocus blur is discussed. Predictive analytics is introduced in Chapter 4, providing an overview of this emerging field. Chapter 5 delves into discrete event system simulation, offering insights into its applications. The performance analysis of different hypervisors in OS virtualization is explored in Chapter 6. Load balancing in cloud computing is the subject of investigation in Chapter 7. Chapter 8 presents a survey on a facial and fingerprint-based voting system utilizing deep learning techniques. Chapter 9 explores IoT-based automated decision-making with data analytics in agriculture. Biometric recognition through modality fusion is investigated in Chapter 10. Chapter 11 offers a new perspective on evaluating machine learning algorithms for predicting employee performance. Pre-process methods for cardiovascular diseases diagnosis using CT angiography images are discussed in Chapter 12. Chapter 13 presents the implementation of a smart wheelchair using ultrasonic sensors and LabVIEW. Cryptography using the Internet of Things is the focus of Chapter 14. Chapter 15 explores machine learning applications for traffic sign recognition, and the book concludes with Chapter 16, which analyzes machine learning algorithms in healthcare. The book is a resource for academics, researchers, educators and professionals in the technology sector who want to learn about current trends in intelligent technologies.