Vishal Chaudhary – författare

Pattern Recognition Techniques in Gas Sensing overviews the methods and technologies used to detect and analyze gases through advanced pattern recognition approaches. The book begins by introducing the fundamentals of gas sensors and their unique data characteristics, laying the groundwork for understanding the complexities involved in gas detection. It then explores the basics of pattern recognition, detailing various statistical methods that have been traditionally employed to interpret sensor data. The text looks into Bayesian and probabilistic methods, offering insights into their applications for improving gas sensing accuracy.Cluster analysis techniques are examined as tools for grouping sensor responses to identify specific gas patterns. The integration of machine learning in gas sensing is thoroughly discussed, highlighting how these algorithms enhance detection capabilities by learning from complex datasets. Further, the book presents deep learning techniques, showcasing their power in handling large volumes of sensor data and extracting meaningful features for precise gas identification. Data processing techniques essential for preparing and refining sensor outputs are also covered, providing readers with practical knowledge for real-world applications and future directions.Incorporates practical examples, codes, and exercises designed to help readers implement the techniques and algorithms using basic programming skillsAnalyzes a variety of case studies to demonstrate the use of pattern recognition techniques in a variety of fields, including environmental monitoring, industrial safety, and medical diagnosticsExamines emerging technologies and trends preparing readers for the future of the field

This book proposes the most effective approach to avert AMR through the utilization of biosensors as a wastewater surveillance tool at the community level. It seeks to bridge the gap between two cutting-edge domains: the burgeoning field of biosensor technology and the escalating threat of antimicrobial resistance.Antimicrobial resistance (AMR) is one of the most pressing challenges to global One Health in the 21st century. The pervasive misuse, overuse and abuse of antibiotics have augmented the emergence of resistant microbes, rendering once-effective therapeutics ineffectual. To address this crisis, novel strategies integrated with advanced technologies are urgently required to monitor antibiotic usage at the community level and mitigate the spread of resistance. Biosensors, characterized by their ability to detect specific molecules with high sensitivity and specificity, are crucial vectors for real-time/point-of-care monitoring of antibiotic consumption in various sectors, ranging from healthcare facilities and industrial utilizations to agricultural operations. By critically examining the principles of biosensors and revealing their prospective applications in antibiotic surveillance from wastewater, this book aims to postulate a comprehensive understanding of how radical technology can be harnessed to address a multifaceted One Health challenge.Throughout the book, readers will probe into the intricate mechanisms underpinning AMR through antibiotic abuse, gaining an understanding of the evolutionary dynamics of resistant bacteria and the selective pressures driving their proliferation. By further examining the broader societal implications of antibiotic abuse, this book aspires to catalyze interdisciplinary collaboration and foster dialogue among stakeholders invested in the fight against antimicrobial resistance using biosensors. It is an invaluable resource for graduate students in environment sciences, public health academics and policymakers.

This book comprehensively reviews the theranostic applications of nanomaterials against various neurological disorders. Additionally, the book provides information on the commonly used molecular imaging tools and biosensors, using different nanomaterials for the early detection of neurological disorders.