Electronic Nose Technologies and Advances in Machine Olfaction
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Electronic Nose Technologies and Advances in Machine Olfaction

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Release Date: April, 2018|Copyright: © 2018 |Pages: 318
DOI: 10.4018/978-1-5225-3862-2
ISBN13: 9781522538622|ISBN10: 1522538623|EISBN13: 9781522538639
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Description & Coverage
Description:

The design and study of materials is a pivotal component to new discoveries in the various fields of science and technology. By better understanding the components and structures of materials, researchers can increase its applications across different industries.

Electronic Nose Technologies and Advances in Machine Olfaction is an academic scholarly resource that examines the emerging applications of odor-sensing devices as well as a better understanding of the designing process with the aid of neural networks and various other technologies. Featuring coverage on a broad range of topics including food spoilage detection, chemical sensing, and olfactometer, this book is a vital resource for engineers, academicians, researchers, students, and practitioners seeking current research on the advancements in applications of odor-sensing devices.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Odor Classification System
  • Chemical Sensing
  • Drift Compensation Methods
  • Explosive Detection
  • Food Spoilage Detection
  • Odor Sensing
  • Olfactometer
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Editor/Author Biographies
Yousif Al-Bastaki received a BSc. degree from University of Bahrain, Msc from University of Leeds, UK and a PhD degree from University of Nottingham, UK. Recently he has been appointed as an IT advisor at the Deputy Prime Minster at the Kingdom of Bahrain and previously worked as the Dean of College of IT at the University of Bahrain. Currently he is an Associate Professor and the Dean of Admission and Registration at the University of Bahrain. His research interests are Neural Networks, genetic algorithms E-Learning, Distance Education and e-government strategies and implementation.
Fatema A. Albalooshi is an Assistant Professor at the Computer Engineering Department, College of IT, University of Bahrain. She graduated from the Electrical and Computer Engineering (ECE) department, University of Dayton (USA). As a graduate research assistant, Dr. Albalooshi contributed an active member of the Computer Vision and Wide Area Surveillance Laboratory (UD Vision Lab) at the University of Dayton. Dr. Albalooshi had completed her Master of Science degree at the University of Nottingham (United Kingdom) in Electronic communications and computer engineering. Specializing in computer vision research, her primary research focus is in the field of image processing and object segmentation where she has completed several publications in the related areas. Dr. Albalooshi’s other research interests include cybersecurity and authentication, object recognition and tracking, image enhancement, neural networks, medical imagery segmentation, e-noses, and 3D reconstruction.
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