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Neuromorphic Computing Systems for Industry 4.0
As artificial intelligence (AI) processing moves from the cloud to the edge of the network, battery-powered and deeply embedded devices are challenged to perform AI functions such as computer vision and voice recognition. Microchip Technology Inc., via its Silicon Storage Technology (SST) subsidiary, is addressing this challenge by significantly reducing power with its analog memory technology, the memBrain Memory Solution. The memBrain solution is being adopted by today’s companies looking to advance machine learning capacities in edge devices. Due to its ability to significantly reduce power, this analog in-memory computer solution is ideal for an AI application. Neuromorphic Computing Systems for Industry 4.0 covers the available literature in the field of neural computing-based microchip technology. It provides further research opportunities in this dynamic field. Covering topics such as emotion recognition, biometric authentication, and neural network protection, this premier reference source is an essential resource for technology developers, computer scientists, engineers, students and educators of higher education, librarians, researchers, and academicians.
Proceedings of International Conference on Recent Innovations in Computing
This book features selected papers presented at the 5th International Conference on Recent Innovations in Computing (ICRIC 2022), held on May 13–14, 2022, at the Central University of Jammu, India, and organized by the university’s Department of Computer Science and Information Technology. The conference was hosted in association with ELTE, Hungary; Knowledge University, Erbil; Cyber Security Research Lab and many other national & international partners. The book is divided into two volumes, and it includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India.
Congress on Intelligent Systems
This book is a collection of selected papers presented at the Second Congress on Intelligent Systems (CIS 2021), organized by Soft Computing Research Society and CHRIST (Deemed to be University), Bengaluru, India during September 4 – 5, 2021. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It covers topics such as Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber physical systems, data analytics, data/web mining, data science, intelligence for security, intell...
Data Visualization and Knowledge Engineering
This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge. Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns...
Hybrid Intelligent Systems
This book includes recent research on Hybrid Intelligent Systems. It presents 35 selected papers from the 17th edition of the International Conference on Hybrid Intelligent Systems (HIS), which was held in Delhi, India from December 14 to 16, 2017. Reflecting the awareness in the respective academic communities that combined approaches are essential to solving the remaining tough problems in computational intelligence, the HIS is a premier conference focused on the hybridization of intelligent systems. The book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Principles Of Data Analytics
Principles of Data Analytics refer to the process of using methods from the field of data science to derive useful information. Data collection is the first phase, followed by data preparation, and finally the use of different data analytics tools to get useful insights. The information gained through analysing, modelling, or visually representing data may be put to use in audit preparation and execution, and includes but is not limited to spotting trends, patterns, deviations, discrepancies, and relationships among data pieces. Competitive advantage may be gained by the use of data analytics, which allows for more informed decisionmaking. The public and commercial sectors are still experimenting with and exploring the potential benefits of data analytics since the field is continually developing. This book covers the fundamentals of data analytics, including how to get started with the area, what "big data" is, how to use Apache Hadoop, and how to visualise your data for better business decisions. In addition to its usefulness in ensuring data security, this book also discusses the foundation, ethics, and cutting-edge developments in the field of data analytics.
Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
Neural Information Processing
The four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22–26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Intelligent Fractal-Based Image Analysis
Fractals are infinite, complex patterns used in modeling physical and dynamic systems. Fractal theory research has increased across different fields of applications including engineering science, health science, and social science. Recent literature shows the vital role fractals play in digital image analysis, specifically in biomedical image processing. Fractal graphics is an interdisciplinary field that deals with how computers can be used to gain high-level understanding from digital images. Integrating artificial intelligence with fractal characteristics has resulted in new interdisciplinary research in the fields of pattern recognition and image processing analysis. Intelligent Fractal-...
Cyber-Physical Systems and Supporting Technologies for Industrial Automation
The exchange of data is the most significant feature of cyber-physical systems (CPS). There are definite advantages and limitations of CPS that must be considered in order to be utilized appropriately across various fields and disciplines. Cyber-Physical Systems and Supporting Technologies for Industrial Automation discusses the latest trends of cyber-physical systems in healthcare, manufacturing processes, energy, and the mobility industry. The book also focuses on advanced subsystems required for the communication of real-time data. Covering key topics such as supporting technologies, Industry 4.0, and manufacturing, this premier reference source is ideal for computer scientists, engineers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
