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Machine Learning (ML) algorithms have shown a high level of accuracy, and applications are widely used in many systems and platforms. However, developing efficient ML-based systems requires addressing three problems: energy-efficiency, robustness, and techniques that typically focus on optimizing for a single objective/have a limited set of goals.This book tackles these challenges by exploiting the unique features of advanced ML models and investigates cross-layer concepts and techniques to engage both hardware and software-level methods to build robust and energy-efficient architectures for these advanced ML networks. More specifically, this book improves the energy efficiency of complex models like CapsNets, through a specialized flow of hardware-level designs and software-level optimizations exploiting the application-driven knowledge of these systems and the error tolerance through approximations and quantization. This book also improves the robustness of ML models, in particular for SNNs executed on neuromorphic hardware, due to their inherent cost-effective features. This book integrates multiple optimization objectives into specialized frameworks for jointly optimizing the robustness and energy efficiency of these systems.This is an important resource for students and researchers of computer and electrical engineering who are interested in developing energy efficient and robust ML.

With the advent of advanced technologies in AI, driverless vehicles have elevated curiosity among various sectors of society. The automotive industry is in a technological boom with autonomous vehicle concepts. Autonomous driving is one of the crucial application areas of Artificial Intelligence (AI). Autonomous vehicles are armed with sensors, radars, and cameras. This made driverless technology possible in many parts of the world. In short, our traditional vehicle driving may swing to driverless technology. Many researchers are trying to come out with novel AI algorithms that are capable of handling driverless technology. The current existing algorithms are not able to support and elevate the concept of autonomous vehicles. This addresses the necessity of novel methods and tools focused to design and develop frameworks for autonomous vehicles. There is a great demand for energy-efficient solutions for managing the data collected with the help of sensors. These operations are exclusively focused on non-traditional programming approaches and depend on machine learning techniques, which are part of AI. There are multiple issues that AI needs to resolve for us to achieve a reliable and safe driverless technology. The purpose of this book is to find effective solutions to make autonomous vehicles a reality, presenting their challenges and endeavors. The major contribution of this book is to provide a bundle of AI solutions for driverless technology that can offer a safe, clean, and more convenient riskless mode of transportation.

The new age space value chain is a complex interconnected system with diverse actors, which involves cross-sector and cross-border collaborations. This book helps to enrich the knowledge of Artificial Intelligence (AI) across the value chain in the space-related domains. Advancements of AI and Machine Learning have impactfully supported the space sector transformation as it is shown in the book.'This book embarks on a journey through the fascinating realm of AI in space, exploring its profound implications, emerging trends, and transformative potential.'Prof. Dr. Oliver Ullrich - Director Innovation Cluster Space and Aviaton (UZH Space Hub), University of Zurich, SwitzerlandAimed at space engineers, risk analysts, policy makers, technical experts and non-specialists, this book demonstrates insights into the implementation of AI in the space sector, alongside its limitations and use-case examples. It covers diverse AI-related topics applicable to space technologies or space big data such as AI-based technologies for improving Earth Observation big data, AI for space robotics exploration, AI for astrophysics, AI for emerging in-orbit servicing market, and AI for space tourism safety improvement. Key Features: Provides an interdisciplinary approach, with chapter contributions from expert teams working in the governmental or private space sectors, with valuable contributions from computer scientists and legal experts Presents insights into AI implementation and how to unlock AI technologies in the field Up-to-date with the latest developments and cutting-edge applications

This book reviews present state-of-the-art research related to the security of cloud computing including developments in conversational AI applications. It is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in advanced security solutions for conversational AI in the cloud platform domain by reviewing present and evolving security solutions, their limitations, and future research directions. Conversational AI combines natural language processing (NLP) with traditional software like chatbots, voice assistants, or an interactive voice recognition system to help customers through either a spoken or typed interface. Conversational chatbots that respond to questions promptly and accurately to help customers are a fascinating development since they make the customer service industry somewhat self-sufficient. A well-automated chatbot can decimate staffing needs, but creating one is a time-consuming process. Voice recognition technologies are becoming more critical as AI assistants like Alexa become more popular. Chatbots in the corporate world have advanced technical connections with clients thanks to improvements in artificial intelligence. However, these chatbots'increased access to sensitive information has raised serious security concerns. Threats are one-time events such as malware and DDOS (Distributed Denial of Service) assaults. Targeted strikes on companies are familiar and frequently lock workers out. User privacy violations are becoming more common, emphasizing the dangers of employing chatbots. Vulnerabilities are systemic problems that enable thieves to break in. Vulnerabilities allow threats to enter the system, hence they are inextricably linked. Malicious chatbots are widely used to spam and advertise in chat rooms by imitating human behavior and discussions, or to trick individuals into disclosing personal information like bank account details.

SUSTAINABLE MANAGEMENT OF ELECTRONIC WASTE Written and edited by a group of industry professionals, this new volume provides cutting-edge insights into how the sustainability of managing electronic waste can be achieved, for engineers, scientists, and students. As a result of the rapid advancement of technology and the globalization of the economy, waste electrical and electronic equipment (WEEE) management has become increasingly important. Manufacturers are especially concerned about the proper disposal of their waste, and researchers need to identify the obstacles and enablers that stand in the way of implementing a long-term WEEE management system in order to develop a long-term WEEE management system. Further, the literature did not adequately capture the perspectives of multiple stakeholders while also identifying the enablers required for the development of sustainable WEEE management policies, which was particularly important in developing countries. This volume fills a gap in the literature by considering the perspectives of multiple stakeholders to identify enablers of sustainable WEEE management in emerging economies which was previously unexplored. This book focuses on the most recent technological advancements for the twenty-first century, emphasizing the synergies that exist between computer science, bioinformatics, and other sciences. The research and development of artificial intelligence, machine learning, blockchain technologies, quantum computing with cryptography, nanotechnology, sensors based on biotechnology, Internet of Things devices, nature-inspired algorithms, computer vision techniques, computational biology, and other topics are covered in this book, along with their applications in the fields of science, engineering, physical science, and economics. Modern environmental techniques are among the most innovative innovations emerging as a result of the insatiable demand for health standards in the modern world.

This book presents a vital method for companies to connect with potential clients andconsumers in the digital era of Online Social Networks (OSNs), utilizing the strengthof well-known social networks and AI to achieve success through fostering brandsupporters, generating leads, and enhancing customer interactions. There are currently 4.8 billion Online Social Network (OSN) users worldwide. Online Social Networks in Business Frameworks presents marketing through online social networks (OSNs), which is a potent method for companies of all sizes to connect with potential clients and consumers. If visitors are not on OSN sites like Facebook, Twitter, and LinkedIn, they are missing out on the fact that people discover, learn about, follow, and purchase from companies on OSNs. Excellent OSN advertising may help a company achieve amazing success by fostering committed brand supporters and even generating leads and revenue. A type of digital advertising known as social media marketing (SMM) makes use of the strength of well-known social networks to further advertise and establish branding objectives. Nevertheless, it goes beyond simply setting up company accounts and tweeting whenever visitors feel like it. Preserving and improving profiles means posting content that represents the company and draws in the right audience, such as images, videos, articles, and live videos, addressing comments, shares, and likes while keeping an eye on the reputation to create a brand network, and following and interacting with followers, clients, and influencers.

This book provides information on interdependencies of medicine and telecommunications engineering and how the two must rely on each other to effectively function in this era. The book discusses new techniques for medical service improvisation such as clear-cut views on medical technologies. The authors provide chapters on communication essentiality in healthcare, processing of medical amenities using medical images, the importance of data and information technology in medicine, and machine learning and artificial intelligence in healthcare. Authors include researchers, academics, and professionals in the field.

ROBOTIC PROCESS AUTOMATION Presenting the latest technologies and practices in this ever-changing field, this groundbreaking new volume covers the theoretical challenges and practical solutions for using robotics across a variety of industries, encompassing many disciplines, including mathematics, computer science, electrical engineering, information technology, mechatronics, electronics, bioengineering, and command and software engineering. Robotics is the study of creating devices that can take the place of people and mimic their behaviors. Mechanical engineering, electrical engineering, information engineering, mechatronics, electronics, bioengineering, computer engineering, control engineering, software engineering, mathematics, and other subjects are all included in robotics. Robots can be employed in a variety of scenarios and for a variety of objectives, but many are now being used in hazardous areas (such as radioactive material inspection, bomb detection, and deactivation), manufacturing operations, or in conditions where humans are unable to live (e.g. in space, underwater, in high heat, and clean up and containment of hazardous materials and radiation). Walking, lifting, speaking, cognition, and any other human activity are all attempted by robots. Many of today's robots are influenced by nature, making bio-inspired robotics a growing area. Defusing explosives, seeking survivors in unstable ruins, and investigating mines and shipwrecks are just a few of the activities that robots are designed to undertake. This groundbreaking new volume presents a Robotic Process Automation (RPA) software technique that makes it simple to create, deploy, and manage software robots that mimic human movements while dealing with digital systems and software. Software robots can interpret what's on a screen, type the correct keystrokes, traverse systems, locate and extract data, and do a wide variety of predetermined operations, much like people. Software robots can do it quicker and more reliably than humans, without having to stand up and stretch or take a coffee break.

Machine learning, deep learning, probabilistic neural networks, blockchain, and other new technologies all demand extremely high processing speeds. A quantum computer is an example of such a system. Quantum computers may be accessed over the internet. This technology poses a significant risk, since quantum terrorists, or cyber criminals, coul be able to cause many problems, including bringing down the internet. The principles of quantum mechanics might be used by evil doers to destroy quantum information on a global scale, and an entire class of suspicious codes could destroy data or eavesdrop on communication. Quantum physics, however, safeguards against data eavesdropping. A significant amount of money is being invested in developing and testing a quantum version of the internet that will eliminate eavesdropping and make communication nearly impenetrable to cyber-attacks. The simultaneous activation of quantum terrorists (organized crime) can lead to significant danger by attackers introducing quantum information into the network, breaking the global quantum state, and preventing the system from returning to its starting state. Without signs of identifying information and real-time communication data, such vulnerabilities are very hard to discover. Terrorists'synchronized and coordinated acts have an impact on security by sparking a cyber assault in a fraction of a second. The encryption is used by cyber-criminal groups with the genuine, nefarious, and terrible motives of killing innocent people or stealing money. In the hands of criminals and codes, cryptography is a dangerous and formidable weapon. Small amounts of digital information are hidden in a code string that translates into an image on the screen, making it impossible for the human eye to identify a coded picture from its uncoded equivalents. To steal the cryptographic key necessary to read people's credit card data or banking information, cyber thieves employ installed encryption techniques, human mistakes, keyboard loggers, and computer malware. This new volume delves into the latest cutting-edge trends and the most up-to-date processes and applications for quantum computing to bolster cybersecurity. Whether for the veteran computer engineer working in the field, other computer scientists and professionals, or for the student, this is a one-stop-shop for quantum computing in cyber security and a must have for any library.

We have seen a sharp increase in the development of data transfer techniques in the networking industry over the past few years. We can see that the photos are assisting clinicians in detecting infection in patients even in the current COVID-19 pandemic condition. With the aid of ML/AI, medical imaging, such as lung X-rays for COVID-19 infection, is crucial in the early detection of many diseases. We also learned that in the COVID-19 scenario, both wired and wireless networking are improved for data transfer but have network congestion. An intriguing concept that has the ability to reduce spectrum congestion and continuously offer new network services is providing wireless network virtualization. The degree of virtualization and resource sharing varies between the paradigms. Each paradigm has both technical and non-technical issues that need to be handled before wireless virtualization becomes a common technology. For wireless network virtualization to be successful, these issues need careful design and evaluation. Future wireless network architecture must adhere to a number of Quality of Service (QoS) requirements. Virtualization has been extended to wireless networks as well as conventional ones. By enabling multi-tenancy and tailored services with a wider range of carrier frequencies, it improves efficiency and utilization. In the IoT environment, wireless users are heterogeneous, and the network state is dynamic, making network control problems extremely difficult to solve as dimensionality and computational complexity keep rising quickly. Deep Reinforcement Learning (DRL) has been developed by the use of Deep Neural Networks (DNNs) as a potential approach to solve high-dimensional and continuous control issues effectively. Deep Reinforcement Learning techniques provide great potential in IoT, edge and SDN scenarios and are used in heterogeneous networks for IoT-based management on the QoS required by each Software Defined Network (SDN) service. While DRL has shown great potential to solve emerging problems in complex wireless network virtualization, there are still domain-specific challenges that require further study, including the design of adequate DNN architectures with 5G network optimization issues, resource discovery and allocation, developing intelligent mechanisms that allow the automated and dynamic management of the virtual communications established in the SDNs which is considered as research perspective.

This book presents original, peer-reviewed select articles from the International Conference on Cognitive & Intelligent Computing (ICCIC – 2021), held on December 11–12, 2021, at Hyderabad, India. The proceedings has cutting edge Research outcome related to Machine learning in control applications, Soft computing, Pattern Recognition, Decision Support Systems, Text analytics and NLP, Statistical Learning, Neural Network Learning, Learning Through Fuzzy Logic, Learning Through Evolution (Evolutionary Algorithms), Reinforcement Learning, Multi-Strategy Learning, Cooperative Learning, Planning And Learning, Multi-Agent Learning, Online And Incremental Learning, Scalability Of Learning Algorithms, Inductive Learning, Inductive Logic Programming, Bayesian Networks, Support Vector Machines, Case-Based Reasoning, Multi-Agent Systems, Human–Computer Interaction, Data Mining and Knowledge Discovery, Knowledge Management and Networks, Data Intensive Computing Architecture, Medicine, Health, Bioinformatics, and Systems Biology, Industrial and Engineering Applications, Security Applications, Smart Cities, Game Playing and Problem Solving, Intelligent Virtual Environments, Economics, Business, And Forecasting Applications. Articles in the book are carefully selected on the basis of their application orientation. The content is expected to be especially useful for Professionals, Researchers, Research students working in the area of cognitive and intelligent computing.

Nanotechnology is gaining importance in every field of science and technology. Green synthesis of nanomaterials involves the use of microorganisms such as bacteria, fungi, viruses; and different lower and higher plants. Green synthesis of nanomaterials from plant extracts becoming popular in comparison to synthesis using microorganisms. Plant based-nanomaterials synthesis is easy, have no need to bring back from the culture medium, and is safe. Additionally, plant-based nanomaterials are eco-friendly, in comparison to physical and chemical modes of synthesis. Several lower and higher plants are rich in terms of secondary metabolites. These metabolites have been used as medicine in crude extract form or with some other formulations. They have been also used to isolate the bioactive compounds in modern medicine as well as in herbal medicine systems. Thus, phytochemicals present in the plant and their parts play an important role in nanomaterials synthesis, mainly due to the presence of a significant number of secondary metabolites, for instance, alkaloids, flavonoids, saponins, steroids, tannins, etc. Further, essential and aromatic oils have been also explored for nanomaterials synthesis, and they are also equally useful in terms of their various biological applications. These organic ingredients come from a wide range of plant components, such as leaves, stems, roots, shoots, flowers, bark, and seeds. Globally, the presence of different plants has shown a capability to produce huge and diverse groups of secondary metabolites. The functional groups present in the plant extract acts as capping and stabilizing agent. Most of the time, pure isolated bioactive compounds are more biologically active; hence scholars are focusing their research on the synthesis of nanomaterials using some particular class of secondary metabolites. Investigations have shown that the green synthesized nanomaterials were found to be more biologically active in comparison to chemicallysynthesized nanomaterials. These nanomaterials and or nanocomposites found different applications especially in drug delivery, detection and cure of cancer cells, diagnosis of a genetic disorder, photoimaging, and angiogenesis detection. They have also shown several applications in agricultural, horticultural as well as forestry sectors. The book in hand covers a wide range of topics as mentioned above. It incorporates chapters that the authors have skilfully crafted with clarity and precision, reviewing up-to-date literature with lucid illustrations. The book would cater to the need of graduate students as a textbook and simultaneously be useful for both novices and experienced scientists and or researchers working in the discipline of nanotechnology, nanomedicine, medicinal plants, plant science, economic botany, chemistry, biotechnology, pharmacognosy, pharmaceuticals, industrial chemistry, and many other interdisciplinary subjects. It should also inspire industrialists and policy makers associated with plant-based nano products.