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Machine Learning for Sustainable Energy
Solutions

Machine Learning for Sustainable Energy Solutions

Analytical chemistry is a cornerstone of modern chemistry and many of the traditional techniques remain in use, albeit now mostly in automated form. The cognitive and practical skills developed in analytical work has ensured its inclusion in all chemistry programs worldwide. While laboratory work by its nature incorporates the cognitive and psychomotor learning domains, it does not always fully include the affective domain. This can be often attributed to repetition of laboratory activities -- 'we've done this before' -- and so it is useful to have access to a range of more diverse activities to engage and challenge students.This book is a laboratory manual which focuses on chemical analysis, providing teachers with a rich source of novel experiments. It features approximately 60 practical activities which have been extensively beta-tested, and do not require access to specialist equipment. There are worked examples for students and well-developed appendices for instructors and technicians. While not aligned with any specific curriculum, the activities are drawn from content across the nations including AP Chemistry, A-level Chemistry, BTEC National Diploma, Irish Leaving Certificate, Scottish Advanced Higher, International Baccalaureate, Abitur, and Matura. It is suitable for high school, community college, and early undergraduate students, and will be especially useful for those preparing for competitions such as the International Chemistry Olympiad and World Skills as it contains more unusual applications of well-known techniques.

Chemical Analysis For Schools & Colleges: A Lab Manual

Exploring Machine and Deep Learning's Impact on Computer Vision

From Pixels to Insights

A Design Oriented Approach using MATLAB

Elements of Mechatronic Systems

An incisive discussion of the applications of digital technology to sustainable supply chain management In Green Innovations in Supply Chain Management, a team of distinguished researchers deliver an up-to-date and authoritative account of contemporary green technology applications in supply chain management. The authors discuss digital technologies that address longstanding development and supply chain challenges associated with sustainability. Split into five sections - green tech logistics, sustainable packaging, sustainable harvesting, e-waste, and green investments - Green Innovations in Supply Chain Management dives into robotics, mobile applications, sustainability packaging initiatives, sustainable seafood sourcing, e-waste, green health initiatives business case studies, and other green investments critical to management of modern supply chains. Readers will also find: <ul> <li>A thorough introduction of green innovations in practice</li> <li>Comprehensive explorations of continental and regional case studies</li> <li>Practical discussions of green investments</li> </ul> Perfect for supply chain management professionals and policymakers with an interest in the field, Green Innovations in Supply Chain Management will also benefit students and researchers of green and sustainable technology, renewable energy, and a wide variety of engineering specialties.

Case Studies and Applications

Green Innovations in Supply Chain Management

A fully updated introduction to cutting-edge Internet of Things (IoT) technology. The Internet of Things (IoT) has revolutionized the way we interact with technology in a highly connected world, bringing a host of new objects and points of entry into global communications networks. Internet of Things A to Z: Technologies and Applications, Second Edition, is a thorough and accessible introduction to IoT for undergraduate and postgraduate students, as well as practitioners and implementers. With a contributor team led by an editor who has decades of experience in information and communication technology (ICT), it covers all foundational subjects for understanding IoT. Now fully updated to reflect the latest developments in the field, it is an indispensable resource for students, researchers, and IT learners looking to keep pace with this rapidly growing technology. Readers of the second edition will also find: <ul> <li>Three additional chapters covering applications of artificial intelligence, machine learning, and deep learning, including information on the Internet of Military Things</li> <li>New information on design and prototyping, including updated hardware boards and instructions</li> <li>Detailed chapters on IoT architecture and ecosystems, security issues such as trust management and IoT authentication methods, big data analytics, and more</li> <li>Expanded treatment of essential technologies not covered in the first edition including edge computing and edge intelligence, with coverage of applications such as TinyML, Digital Twins, AR/VR, and the metaverse</li> </ul> Internet of Things A to Z: Technologies and Applications, Second Edition, is ideal for students interested in the Internet of Things, ICT researchers, industry professionals, and lifetime IT learners.

Technologies and Applications

Internet of Things A to Z

This book will not only deal with the analysis of nutraceuticals, but will also focus on the extraction and purification of the analytes using newer tools/instruments. It will also help the analyst during the actual estimation of these compounds from different matrices.

This book will not only deal with the analysis of nutraceuticals, but will also focus on the extraction and purification of the analytes using newer tools/instruments. It will also help the analyst during the actual estimation of these compounds from different matrices.

Practical Guide to LC Analysis of Nutraceuticals

Using Electromagnetic Signal and Information Theory

Intelligent Metasurfaces for 6G and Beyond

Learn to secure, build, implement, and test future blockchain applications Blockchain was originally introduced in the crypto-currency of Bitcoin in order to keep track of transactions over a peer-to-peer network to prevent the double-spending of bitcoin. This distributed ledger technology, however, has developed a reputation as a disruptive technology for the transfer of values and disintermediation. Despite this reputation, blockchain is, simply, at its core, a data structure-in this case, a cryptographic hash chain of blocks of transactions-continually replicated and maintained in a distributed manner by a peer-to-peer network of hosts. Together they decide through a specific consensus protocol, what transactions can be registered or added to the blockchain. Blockchain Application Security introduces the reader to the architecture and components of blockchain, as well as blockchain and bitcoin protocol, aimed at a basic level of understanding of the technical perspective. The book discusses the benefits, the vulnerabilities, and even the design flaws found in blockchain applications. It also teaches how to manage the risks of blockchain by deciding how digital assets, data confidentiality, and data availability should be protected from unauthorized access. Blockchain Application Security readers will also find: <ul> <li>An exploration of source code and core APIs relevant to blockchain</li> <li>A glossary of common terminology used for blockchain</li> <li>Real cases of blockchain applications to illustrate points</li></ul>Blockchain Application Security is an ideal resource for application architects, software developers, security auditors, and vulnerability testers of enterprise-based blockchain applications.

How to Design Secure and Attack Resilient Blockchain Applications

Blockchain Application Security

iPhone For Seniors For Dummies, 2026 Edition

Practical Analytical Testing and Processing Methods for Cannabis and Hemp-Based Products

Comprehensive overview of the principles, theories, and techniques behind deep learning-enabled semantic communications Deep Learning Enabled Semantic Communications explores the synergy between deep learning and semantic communication, particularly in the context of advancing 6G networks. It provides a focused introduction to the subject, systematically covering deep learning-enabled semantic communication systems and task-oriented semantic transmission paradigms in wireless communication. The book reviews various aspects of semantic communications, including information theory, multimodal technologies, semantic noise, and semantic sensing. It explores cutting-edge semantic communication architectures, highlighting their advantages over traditional approaches and their potential to drive the future of intelligent information industry. The book also details applications of deep learning-based semantic communication systems across various sources, including text, speech, images, and videos, comprehensively addressing system design, performance optimization, and measurement metrics. The book is divided into eight main parts, which cover foundational knowledge, system design, multimodal and multitask-oriented semantic communication systems, joint semantic sensing and sampling, semantic noise suppression, and generative AI enabled systems. Written by a diverse group of experts in academia and research institutions, Deep Learning Enabled Semantic Communications includes information on: <ul> <li>Fundamental knowledge about the deep learning and semantic communications, including the history, neural networks, and semantic information theory</li> <li>Compression of multimodal inputs, extraction of global semantic information, and the design of neural networks to boost the capability of handling lengthy speech</li> <li>Incorporation of different sources to extract semantic features and serve diverse intelligent tasks at the receiver</li> <li>Introduction of semantic impairments in communications to uncover how to design robust systems</li> <li>Joint design of data sampling, compression, and coding schemes under the guidance of semantic information</li> <li>Framework of generative semantic communications to detail the principles of incorporating generative models into semantic communications</li> </ul> Deep Learning Enabled Semantic Communications is an essential learning resource and reference for graduate and undergraduate students pursuing degrees in wireless communications, signal processing, or deep learning as well as engineers in the telecommunications and IT industries focusing on wireless communication techniques.

Deep Learning Enabled Semantic Communications

Machine Learning for Sustainable Energy Solutions

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