This new two-volume addresses a number of state-of-the-art developments and unsolved open issues in the field of computational intelligence. Volume 1 focuses on data science and artificial intelligence. It highlights the use of predictive analytics of data from various application domains to find timely solutions to various problems. The book focuses on the research developments, limitations, and management of real-time problems using computational intelligence by identifying applicable approaches in order to enhance, automate, and develop effective solutions. The volume introduces empirical research, prospects of theoretical research, and applications in data science and artificial intelligence. The chapters present diverse application of computer intelligence and machine learning in security, healthcare and medicine, agriculture, traffic science/smart cities, and language and text conversion. Volume 2 demonstrates empirical, theoretical, and application perspectives on smart technologies, computational intelligence in network technologies, and computational intelligence in software engineering, identifying the advantages and limitations of each. The chapters on smart technologies address their application in such areas as communication services, healthcare and assistive technology, urban waste management, vehicle pollution and accident detection, and more. The technologies encompass the use of machine learning, blockchain, fog computing, satellite communication technology, ant colony optimization algorithms, etc. Together, these two volumes offer new research on presented by young and dynamic researchers and experts from industry and academia, sharing a plethora of new and emerging technologies that support their effective operations in computational intelligence in information systems. These peer-review chapters were selected from the International Conference on Computational Intelligence in Analytics and Information Systems’ (CIAIS- 2021), held in April 2021 at Manav Rachna University, India.

This new volume introduces various VLSI (very-large-scale integration) architecture for DSP filters, speech filters, and image filters, detailing their key applications and discussing different aspects and technologies used in VLSI design, models and architectures, and more. The volume explores the major challenges with the aim to develop real-time hardware architecture designs that are compact and accurate. Knowledge of VLSI is necessary for understanding today’s contemporary hardware prospects of engineering. It is the process of creating an integrated circuit by combining millions of MOS transistors onto a single chip that is needed for handheld portable battery-operated devices that require efficient, errorless, and low-power arithmetic operation. VLSI plays a most important role in the performance of digital systems, digital signal processing (DSP), image processing applications, hardware security, quantum computing, etc. Especially in DSP systems, the algorithms of VLSI have a number of interesting characteristics that can be exploited in the design of the arithmetic circuits so that they can be implemented more efï¬ciently in terms of computation time, chip area, and power consumption. This volume, VLSI Architecture for Signal, Speech, and Image Processing, provides useful research in the field of computer arithmetic and can be applied for various arithmetic circuits, for their digital implementation schemes, and for performance considerations. It covers how computer arithmetic contributes to the era of quantum computing, hardware security, image processing, biomedical engineering, artificial intelligence, neural networks, and stochastic computing. Prepared by leading researchers in the field of computer arithmetic architecture, the state-of-the-art information presented here helps to provide a comprehensive understanding of VLSI for students, faculty, and researchers in computer science, computer engineering, and electrical and electronics engineering. It may be used as a textbook for courses on VLSI as well as a reference book.

This new volume presents a selection of state-of-the-art technological advancements in various application areas of IoT, network technologies, and software engineering that address unsolved open issues in the field of computational intelligence. The volume focuses on empirical, theoretical, and application perspectives on smart technologies, computational intelligence in network technologies, and computational intelligence in software engineering, identifying the advantages and limitations of each. The chapters on smart technologies address their application in such areas as communication services, healthcare and assistive technology, urban waste management, vehicle pollution and accident detection, and more. The technologies encompass the use of machine learning, blockchain, fog computing, etc. The volume goes on to discuss computational intelligence in network technologies. These include comparisons of cryptography mechanisms, internet privacy protection, satellite communication technology, ant colony optimization algorithms, etc. The topics on computational intelligence in software engineering include security optimization via software-defined networking (SDN), education-based interactive automated agent, data warehouse requirement engineering, and more. The research contributions presented here by young and dynamic researchers and experts from industry and academia share a host of emerging technologies that support their effective operations in computational intelligence in information systems. These peer-review chapters were selected from the International Conference on Computational Intelligence in Analytics and Information Systems (CIAIS- 2021), held in April 2021 at Manav Rachna University, India.

The new book presents a valuable selection of new and state-of-the-art technological advancements in various application areas using the concepts of AI and machine learning, highlighting the use of predictive analytics of data from various application domains to find timely solutions to various problems. The book focuses on the research developments, limitations, and management of real-time problems using computational intelligence by identifying applicable approaches in order to enhance, automate, and develop effective solutions. The volume introduces empirical research, prospects of theoretical research, and applications in data science and artificial intelligence. The various novel approaches include applications in healthcare, natural language processing, and smart cities. As such, the book is divided into sections that address: Computational Intelligence in Image Processing Computational Intelligence in Healthcare Techniques for Natural Language Processing Computational Intelligence in Smart Cities The very diverse range of topics include AI and machine learning applications for In security: For using digital image processing for image fusion (face recognition, feature extraction, object detection as well tracking, moving object identification), for person re-identification for security purposes. In healthcare and medicine: For diagnosis and prediction of breast cancer, other cancers, diabetes, heart disease; for predicting susceptibility to COVID-19; for prediction of mood and anxiety disorders. In agriculture: For prediction of crop profit; for prediction of cropping patterns and recommendation for crop cultivation. In traffic science/smart cities: For understanding road scene images, for detection of traffic signs, for devising a fog-based intelligent traffic phase timing regulation system In language/speech/text: For automatic text summarization, for document indexing for unstructured data, for speech/accent recognition, for sound separation, for American Sign Language interpretation for nonsigners, for emotional recognition and analysis through speech, body postures with facial expressions, and other body movements (to improve the performance of virtual personal assistants / emotion recognition using speech, body postures with facial expressions and other body movements. This volume offers valuable information for researchers working in interdisciplinary or multidisciplinary areas of healthcare, image analysis, natural language processing, and smart cities. This includes academicians, people in industry, and students with engineering background with research interest in these areas. These peer-review chapters were selected from the International Conference on Computational Intelligence in Analytics and Information Systems (CIAIS- 2021), held in April 2021 at Manav Rachna University, India.