S Karthikeyan – författare

Convergence of Blockchain, AI and IoT: A Digital Platform discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy.Discusses innovative technological upgradation and significant challenges in the current eraGives an overview of clinical scientific research that enables smart diagnosis through artificial intelligence Provides an insight into how disruptive technology enabled with the self-running devices and protection mechanism is involved in an augmented reality with blockchain mechanismTalks about neural science being capable of enhancing deep brain waves to predict an overall improvement in human thoughts and behavioursCovers the digital currency mechanism in detailEnhances the knowledge of readers about smart contract and ledger mechanism with artificial intelligence and blockchain mechanismTargeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

Convergence of Blockchain, AI and IoT: A Digital Platform discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy.Discusses innovative technological upgradation and significant challenges in the current eraGives an overview of clinical scientific research that enables smart diagnosis through artificial intelligence Provides an insight into how disruptive technology enabled with the self-running devices and protection mechanism is involved in an augmented reality with blockchain mechanismTalks about neural science being capable of enhancing deep brain waves to predict an overall improvement in human thoughts and behavioursCovers the digital currency mechanism in detailEnhances the knowledge of readers about smart contract and ledger mechanism with artificial intelligence and blockchain mechanismTargeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

Convergence of Blockchain, AI and IoT: A Digital Platform discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy.

Discusses innovative technological upgradation and significant challenges in the current era Gives an overview of clinical scientific research that enables smart diagnosis through artificial intelligence Provides an insight into how disruptive technology enabled with the self-running devices and protection mechanism is involved in an augmented reality with blockchain mechanism Talks about neural science being capable of enhancing deep brain waves to predict an overall improvement in human thoughts and behaviours Covers the digital currency mechanism in detail Enhances the knowledge of readers about smart contract and ledger mechanism with artificial intelligence and blockchain mechanism

Targeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

Convergence of Blockchain, AI and IoT: A Digital Platform discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy.

Discusses innovative technological upgradation and significant challenges in the current era Gives an overview of clinical scientific research that enables smart diagnosis through artificial intelligence Provides an insight into how disruptive technology enabled with the self-running devices and protection mechanism is involved in an augmented reality with blockchain mechanism Talks about neural science being capable of enhancing deep brain waves to predict an overall improvement in human thoughts and behaviours Covers the digital currency mechanism in detail Enhances the knowledge of readers about smart contract and ledger mechanism with artificial intelligence and blockchain mechanism

Targeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies.In summary, the book: Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects.This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.

This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies.In summary, the book: Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects.This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.

This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies.

In summary, the book:

Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines.

Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks.

Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting.

Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost.

Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects.

This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.

This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies.

In summary, the book:

Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines.

Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks.

Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting.

Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost.

Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects.

This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.

This book offers an overview of the latest work in environmental remediation and waste management coming out of developing nations. It is split into two sections: one on state-of-the-art sustainable remediation approaches, and the other covering waste management for a cleaner environment The ten chapters in this book are structured as reviews that assimilate recent works in these areas; they provide a centralized resource for scholars in developing nations who are working in environmental remediation and waste management. The volume will be of interest to sustainability researchers, environmental engineers, industry managers and agricultural scientists.

This book offers an overview of the latest work in environmental remediation and waste management coming out of developing nations. It is split into two sections: one on state-of-the-art sustainable remediation approaches, and the other covering waste management for a cleaner environment The ten chapters in this book are structured as reviews that assimilate recent works in these areas; they provide a centralized resource for scholars in developing nations who are working in environmental remediation and waste management. The volume will be of interest to sustainability researchers, environmental engineers, industry managers and agricultural scientists.

This book offers an overview of the latest work in environmental remediation and waste management coming out of developing nations. It is split into two sections: one on state-of-the-art sustainable remediation approaches, and the other covering waste management for a cleaner environment The ten chapters in this book are structured as reviews that assimilate recent works in these areas; they provide a centralized resource for scholars in developing nations who are working in environmental remediation and waste management. The volume will be of interest to sustainability researchers, environmental engineers, industry managers and agricultural scientists.