{"title":"Books by Ajit Khosla","description":null,"products":[{"product_id":"pattern-recognition-techniques-in-gas-sensing","title":"Pattern Recognition Techniques in Gas Sensing","description":"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.","brand":"Gardners","offers":[{"title":"Default Title","offer_id":57499330937205,"sku":"9780443442797","price":137.99,"currency_code":"GBP","in_stock":true}]},{"product_id":"3d-printed-devices-sensors-and-actuators","title":"3D Printed Devices: Sensors and Actuators","description":"3D Printed Devices: Sensors and Actuators 3D printing or additive manufacturing has been one of the most revolutionary developments in rapid prototyping. This type of manufacturing has now developed to the degree that it can be used to manufacture complex devices, particularly sensors and actuators, without the need of traditional molds. The engineering potential that emerge from the creation of moldless devices are boundless, and engineers and materials scientists are urgently in need of increased familiarity with these possibilities 3D Printed Devices meets this need with a timely, comprehensive overview to 3D printing techniques in the field of sensors and actuators. Students, researchers, and scientists in industry can all benefit from this volume's robust knowledge of both the current and future state of this growing field. Thoroughly engaged with both the possibilities and limitations of 3D printed devices, the book is a must-own for anyone looking to stand on the cutting edge of our technological future. 3D Printed Devices readers will also find: Analysis of both physical and chemical sensors, as well as different types of actuators including electrically or thermally actuatedDetailed discussion of sensor and actuator materials including gels, polymers, composites, and moreDetailed know-how required to design, fabricate, and innovate 3D printed devices 3D Printed Devices is an indispensable resource for academic researchers and industrial scientists in engineering and the physical sciences. It caters to those working in the cutting-edge fields of sensors, robotics, 3D printing, electronic materials, and electrochemistry. This book is also perfect for advanced undergraduate and graduate students eager to delve into these dynamic and rapidly evolving areas.","brand":"Gardners","offers":[{"title":"Default Title","offer_id":57503579505013,"sku":"9781119837367","price":145.95,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0612\/7193\/3106\/files\/9781119837367.jpg?v=1786867285"},{"product_id":"sensor-system-hardware-design-implementation-an-d-applications","title":"Sensor System Hardware: Design, Implementation, an d Applications","description":null,"brand":"Gardners","offers":[{"title":"Default Title","offer_id":57503588745589,"sku":"9781394322886","price":175.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"data-augmentation-for-chemical-gas-sensing","title":"Data Augmentation for Chemical Gas Sensing","description":"\u003cp\u003eBy providing a comprehensive yet accessible guide to both the theory and practical implementation of data augmentation, this book will equip researchers, engineers, and practitioners to enhance their sensor systems, ensuring more accurate, robust, and scalable predictive models that can handle complex real-world scenarios.\u003c\/p\u003e \u003cp\u003eIn recent years, chemical gas sensors have become crucial to diverse real-world applications, from monitoring air quality in urban areas to ensuring safety in industrial environments. However, one of the most critical limitations of these sensors is the challenge of obtaining sufficient, high-quality data to train predictive models. Sensor data collection is often labor intensive, costly, and limited in scope, particularly when attempting to capture the dynamic behavior of multiple gases in varying environmental conditions. These challenges make it difficult to build predictive models that are widely effective in real-world scenarios, where gas concentrations fluctuate unpredictably.\u003c\/p\u003e \u003cp\u003eThis book aims to tackle this issue by providing a comprehensive introduction to data augmentation techniques in the context of chemical gas sensing. The objective is to show how artificial data generation can overcome the limitations of real-world sensor data, thus enhancing the accuracy and generalization of machine learning models. The book will cover traditional data augmentation methods, such as geometric transformations as well as more advanced techniques like recurrent neural networks (RNNs), Long Short-Term Memory (LSTM) networks, Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs).\u003c\/p\u003e \u003cp\u003eWhat makes this book unique is its blend of theory and hands-on application. It will provide a solid foundation for readers who may not have advanced knowledge in machine learning, making it accessible to those with basic programming skills. Each chapter will not only explain the theoretical concepts behind various data augmentation methods but also provide practical and ready-to-use code snippets in Python. These code examples will allow readers to quickly implement and test the techniques described, enabling them to apply the methods directly to real-world sensor data.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":57573164253557,"sku":"9783119143653","price":82.0,"currency_code":"GBP","in_stock":false}]}],"url":"https:\/\/backstory.london\/collections\/author-ajit-khosla.oembed","provider":"Backstory","version":"1.0","type":"link"}