Mufti Mahmud – författare

This volume contains the papers presented at International Conference on Emerging Trends in Engineering and Technology-Industry 4.0 (ETETI-2023) being organized by the prestigious Indira Gandhi Institute of Technology, Sarang (An Autonomous institute of Govt of Odisha), India, during 6th and 7th May 2023.

This volume contains the papers presented at International Conference on Emerging Trends in Engineering and Technology-Industry 4.0 (ETETI-2023) being organized by the prestigious Indira Gandhi Institute of Technology, Sarang (An Autonomous institute of Govt of Odisha), India, during 6th and 7th May 2023.

The International Conference on Sustainable Materials, Structures and IoT (SMSI-2024) was organized by Department of Civil Engineering, Indira Gandhi Institute of Technology Sarang, India. The practical problems associated with various engineering in many developing countries including India and developed countries are different and complex. Therefore, researchers and agencies have been working to tackle these challenges and to identify implementable solutions for various transportation engineering related problems as per prevailing conditions. As a recurring event with nationwide participation, SMSI-2024 converged experts, researchers, practitioners, industry professionals around the world to share and deliberate on their work, offering profound insights into emerging technological trends. This conference invited papers related to various themes under the umbrella of engineering.

The International Conference on Sustainable Materials, Structures and IoT (SMSI-2024) was organized by Department of Civil Engineering, Indira Gandhi Institute of Technology Sarang, India. The practical problems associated with various engineering in many developing countries including India and developed countries are different and complex. Therefore, researchers and agencies have been working to tackle these challenges and to identify implementable solutions for various transportation engineering related problems as per prevailing conditions. As a recurring event with nationwide participation, SMSI-2024 converged experts, researchers, practitioners, industry professionals around the world to share and deliberate on their work, offering profound insights into emerging technological trends. This conference invited papers related to various themes under the umbrella of engineering.

This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications.

Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption.

This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications.

Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption.

This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

This book provides an in-depth exploration of the potential impact of 6G networks on various industries, including healthcare, agriculture, transport, and national security, making it an essential resource for researchers, scholars, and students working in the field of wireless networks and high-speed data processing systems.

Development of 6G Networks and Technology explores the benefits and challenges of 5G and beyond that play a key role in the development of the next generation of internet. 6G is targeted to improve download speeds, eliminate latency, reduce congestion on mobile networks, and support advancements in technology. 6G has the potential to transform how the human, physical, and digital worlds interact with each other and the capability to support advancements in technology, such as virtual reality (VR), augmented reality (AR), the metaverse, and artificial intelligence (AI). Machine learning and deep learning modules are also an integral part of almost all automated systems where signal processing is performed at different levels. Signal processing in the form text, image, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of IC area with embedded bulk memories that lead to power consumption. Trade-offs between power consumption, delay, and IC area are always a concern of designers and researchers. Energy-efficient, high-speed data processing is required in major areas like biomedicine and healthcare, agriculture, transport, climate change, and national security and defense. This book will provide a foundation and initial inputs for researchers, scholars, and students working in the areas of wireless networks and high-speed data processing systems. It also provides techniques, tools, and methodologies to develop next-generation internet and 6G.

This book provides an in-depth exploration of the potential impact of 6G networks on various industries, including healthcare, agriculture, transport, and national security, making it an essential resource for researchers, scholars, and students working in the field of wireless networks and high-speed data processing systems.

Development of 6G Networks and Technology explores the benefits and challenges of 5G and beyond that play a key role in the development of the next generation of internet. 6G is targeted to improve download speeds, eliminate latency, reduce congestion on mobile networks, and support advancements in technology. 6G has the potential to transform how the human, physical, and digital worlds interact with each other and the capability to support advancements in technology, such as virtual reality (VR), augmented reality (AR), the metaverse, and artificial intelligence (AI). Machine learning and deep learning modules are also an integral part of almost all automated systems where signal processing is performed at different levels. Signal processing in the form text, image, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of IC area with embedded bulk memories that lead to power consumption. Trade-offs between power consumption, delay, and IC area are always a concern of designers and researchers. Energy-efficient, high-speed data processing is required in major areas like biomedicine and healthcare, agriculture, transport, climate change, and national security and defense. This book will provide a foundation and initial inputs for researchers, scholars, and students working in the areas of wireless networks and high-speed data processing systems. It also provides techniques, tools, and methodologies to develop next-generation internet and 6G.

This book constitutes the refereed proceedings of the 13th International Conference on Brain Informatics, BI 2020, held in Padua, Italy, in September 2020. The conference was held virtually due to the COVID-19 pandemic.

The 33 full papers were carefully reviewed and selected from 57 submissions. The papers are organized in the following topical sections: cognitive and computational foundations of brain science; investigations of human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain-inspired computing.

The 29 papers were selected from 65 submissions and the main theme of BI 2022 is Brain Science meets Artificial Intelligence with respect to the five tracks: Cognitive and computational foundations of brain science; human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain inspired computing.