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Advances in Wireless Sensors and Sensor Networks
In recent times wireless sensors and sensor networks have become a great interest to research, scientific and technological community. Though the sensor networks have been in place for more than a few decades now, the wireless domain has opened up a whole new application spaces of sensors. Wireless sensors and sensor networks are different from traditional wireless networks as well computer networks and therefore pose more challenges to solve such as limited energy, restricted life time, etc. This book intends to illustrate and to collect recent advances in wireless sensors and sensor networks, not as an encyclopedia but as clever support for scientists, students and researchers in order to stimulate exchange and discussions for further developments.
Ad Hoc Networks
This book constitutes the refereed proceedings of the 9th International Conference on Ad Hoc Networks, AdHocNets 2017, held in Niagara Falls, Ontario, USA, in September 2017. The 19 full papers were selected from 30 submissions and cover a variety of network paradigms including mobile ad hoc networks (MANETs), sensor networks, vehicular networks, underwater networks, airborne networks, underground networks, personal area networks, device-to-device (D2D) communications in 5G cellular networks, and home networks. The papers present a wide range of applications in civilian, commercial, and military areas.
Handbook of Research on Machine and Deep Learning Applications for Cyber Security
As the advancement of technology continues, cyber security continues to play a significant role in todays world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Cognitive Radio Mobile Ad Hoc Networks
Cognitive radios (CR) technology is capable of sensing its surrounding environment and adapting its internal states by making corresponding changes in certain operating parameters. CR is envisaged to solve the problems of the limited available spectrum and the inefficiency in the spectrum usage. CR has been considered in mobile ad hoc networks (MANETs), which enable wireless devices to dynamically establish networks without necessarily using a fixed infrastructure. The changing spectrum environment and the importance of protecting the transmission of the licensed users of the spectrum mainly differentiate classical MANETs from CR-MANETs. The cognitive capability and re-configurability of CR-...
Ad Hoc Networks
This volume constitutes the refereed proceedings of the Third International ICST Conference, ADHOCNETS 2011, held in Paris, France, in September 2011. The 15 revised full papers - selected from 42 submissions - and the 2 invited papers cover several fundamental aspects of ad hoc networking, including security, quality of service, radio and spectrum analysis, mobility, energy efficiency, and deployment. They are organized in topical sections on security and QoS, WSN development and evaluation, radio and spectrum analysis, mobile WSNs, mobile ad hoc networks, and energy.
Multisensor Fusion
The fusion of information from sensors with different physical characteristics, such as sight, touch, sound, etc., enhances the understanding of our surroundings and provides the basis for planning, decision-making, and control of autonomous and intelligent machines. The minimal representation approach to multisensor fusion is based on the use of an information measure as a universal yardstick for fusion. Using models of sensor uncertainty, the representation size guides the integration of widely varying types of data and maximizes the information contributed to a consistent interpretation. In this book, the general theory of minimal representation multisensor fusion is developed and applied in a series of experimental studies of sensor-based robot manipulation. A novel application of differential evolutionary computation is introduced to achieve practical and effective solutions to this difficult computational problem.
MXene-Based Hybrid Nano-Architectures for Environmental Remediation and Sensor Applications
Approx.630 pages Covers fundamentals of MXene-based hybrid nanostructures, including synthesis and characterization methods Explores innovative and emerging applications, with a focus on environmental remediation and sensors Addresses challenges, such as environmental impact and lifecycle, as well as future possibilities
