Multi-agent learning (MAL) has emerged as a promising artificial intelligence (AI) and machine learning (ML) paradigm for creating agent-based technologies to develop, secure, and operate cyber-physical-human networks (CPHNs).

 Multi-agent learning (MAL) has emerged as a promising artificial intelligence (AI) and machine learning (ML) paradigm for creating agent-based technologies to develop, secure, and operate cyber-physical-human networks (CPHNs).

In the array signal processing research, estimation of the direction-of-arrival (DOA) of the transmitted source signal has long been of great interest and plays an important role in both civilian and military applications such as radar, sonar, geophysics, acoustics, bioengineering, seismology, multimedia, radio astronomy and wireless communication. 

In the array signal processing research, estimation of the direction-of-arrival (DOA) of the transmitted source signal has long been of great interest and plays an important role in both civilian and military applications such as radar, sonar, geophysics, acoustics, bioengineering, seismology, multimedia, radio astronomy and wireless communication. 

Global navigation satellite systems (GNSS) have been the main technology used in aerial and ground vehicle navigation systems. As vehicles approach full autonomy, the requirements on the accuracy, reliability, and availability of their navigation systems become very stringent. Due to the limitations of GNSS, namely severe attenuation in deep urban canyons and susceptibility to interference, jamming, and spoofing, alternative sensors and signals are sought. 

This thesis addresses security and privacy problems for digital devices and biometrics, where a secret key is generated for authentication, identification, or secure computa- tions. A physical unclonable function (PUF) is a promising solution for local security in digital devices.

The blood vessels of the brain and the retina share common embryological origins and have comparable anatomy and physiology. In this thesis, patients with Schizophrenia (SCZ) and Bipolar disorder (BD) were recruited and compared with healthy volunteers (HV). We examined the diameters of the retinal venules and arterioles for abnormalities in patients and HV. 

The human visual system has a unique ability to conceptualizing the dynamics of objects' interactions in a scene. We are not only able to detect objects' motion (including articulated and deformable ones, such as humans and animals) in a given scene but also distinguish different types of motion patterns in their bodies during various interactive actions.

The use of machine-learning for multimedia forensics is gaining more and more consensus, especially due to the amazing possibilities offered by modern machine learning techniques. By exploiting deep learning tools, new approaches have been proposed whose performance remarkably exceed those achieved by state-of-the-art methods based on standard machine-learning and model-based techniques. 

In this era of stress-filled life styles and cut-throat competitions, cardiovascular diseases and heart abnormalities are becoming common in the people of early age groups.