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Articles 1 - 11 of 11
Full-Text Articles in Other Electrical and Computer Engineering
Energy Efficient Spintronic Devices For Non-Volatile Memory And Hardware Ai, Walid Al Misba
Energy Efficient Spintronic Devices For Non-Volatile Memory And Hardware Ai, Walid Al Misba
Theses and Dissertations
Nanomagnetic devices have emerged as a promising alternative to conventional complementary metal-oxide-semiconductor (CMOS) devices due to their low energy dissipation and inherent non-volatility. However, the widespread adoption of these devices requires high-density, high-speed, reliable, scalable, and energy-efficient technologies. This thesis investigates the use of nanomagnetic memory devices as both conventional Boolean memory and multistate memory for hardware AI applications.
Magnetic tunnel junctions (MTJs) are nanomagnetic memory devices that can be switched reliably and energy-efficiently using stress-mediated switching. However, realistic material inhomogeneity and scalability pose challenges for stress-mediated switching of MTJs scaled to lateral dimensions below 50 nm. We demonstrate that …
Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber
Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber
Theses and Dissertations
As cyber-physical systems (CPS) become more integrated into everyday life, the security of these systems must also be considered during their development due to their ever-increasing importance. With the growth of physical components in the system, more autonomous control requirements, and increased dependence on proper functionality, verifying system safety and correct operation becomes increasingly difficult. CPS have become more complex through the combination of additional hardware and the resulting interconnected software in many layers, each requiring unique security solutions. One example of such a safety-critical CPS embedded system is the Flight Control System (FCS) of an Unmanned Aerial System (UAS). …
Low Insertion-Loss Nanophotonic Modulators Through Epsilon-Near-Zero Material-Based Plasmon-Assisted Approach For Integrated Photonics, Mohammad Ariful Hoque Sojib
Low Insertion-Loss Nanophotonic Modulators Through Epsilon-Near-Zero Material-Based Plasmon-Assisted Approach For Integrated Photonics, Mohammad Ariful Hoque Sojib
Theses and Dissertations
Electro-optic/absorption Modulators (EOM/EAMs) encode high-frequency electrical signals into optical signals. With the requirement of large packing density, device miniaturization is possible by confining light in a sub-wavelength dimension by utilizing the plasmonic phenomenon. In plasmon, energy gets transferred from light to the form of oscillation of free electrons on a surface of a metal at an interface between the metal and a dielectric. Plasmonic provides increased light-matter interaction (LMI) and thus making the light more sensitive to local refractive index change. Plasmonic-based integrated nanophotonic modulators, despite their promising features, have one key limiting factor of large Insertion Loss (IL) which …
Smart City Management Using Machine Learning Techniques, Mostafa Zaman
Smart City Management Using Machine Learning Techniques, Mostafa Zaman
Theses and Dissertations
In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …
Reliable Navigation For Suas In Complex Indoor Environments, Andrew J. Fabian
Reliable Navigation For Suas In Complex Indoor Environments, Andrew J. Fabian
Theses and Dissertations
Indoor environments are a particular challenge for Unmanned Aerial Vehicles (UAVs). Effective navigation through these GPS-denied environments require alternative localization systems, as well as methods of sensing and avoiding obstacles while remaining on-task. Additionally, the relatively small clearances and human presence characteristic of indoor spaces necessitates a higher level of precision and adaptability than is common in traditional UAV flight planning and execution. This research blends the optimization of individual technologies, such as state estimation and environmental sensing, with system integration and high-level operational planning.
The combination of AprilTag visual markers, multi-camera Visual Odometry, and IMU data can be used …
On-Demand Electrically Induced Decomposition Of Thin-Film Nitrocellulose Membranes For Wearable Or Implantable Biosensor Systems, Benjamin M. Horstmann
On-Demand Electrically Induced Decomposition Of Thin-Film Nitrocellulose Membranes For Wearable Or Implantable Biosensor Systems, Benjamin M. Horstmann
Theses and Dissertations
Implantable or subcutaneous biosensors used for continuous health monitoring have a limited functional lifetime requiring frequent replacement and therefore may be highly discomforting to the patient and become costly. One possible solution to this problem is use of biosensor arrays where each individual reserve sensor can be activated on-demand when the previous one becomes inoperative due to biofouling or enzyme degradation. Each reserve biosensor in the array is housed in an individual Polydimethylsiloxane (PDMS) well and is protected from exposure to bodily fluids such as interstitial fluid ( ISF) by a thin-film nitrocellulose membrane. Controlled activation is achieved by decomposing …
Multi-Column Neural Networks And Sparse Coding Novel Techniques In Machine Learning, Ammar O. Hoori
Multi-Column Neural Networks And Sparse Coding Novel Techniques In Machine Learning, Ammar O. Hoori
Theses and Dissertations
Accurate and fast machine learning (ML) algorithms are highly vital in artificial intelligence (AI) applications. In complex dataset problems, traditional ML methods such as radial basis function neural network (RBFN), sparse coding (SC) using dictionary learning, and particle swarm optimization (PSO) provide trivial results, large structure, slow training, and/or slow testing. This dissertation introduces four novel ML techniques: the multi-column RBFN network (MCRN), the projected dictionary learning algorithm (PDL) and the multi-column adaptive and non-adaptive particle swarm optimization techniques (MC-APSO and MC-PSO). These novel techniques provide efficient alternatives for traditional ML techniques. Compared to traditional ML techniques, the novel ML …
Omni-Directional Infrared 3d Reconstruction And Tracking Of Human Targets, Emrah Benli
Omni-Directional Infrared 3d Reconstruction And Tracking Of Human Targets, Emrah Benli
Theses and Dissertations
Omni-directional (O-D) infrared (IR) vision is an effective capability for mobile systems in robotics, due to its advantages: illumination invariance, wide field-of-view, ease of identifying heat-emitting objects, and long term tracking without interruption. Unfortunately, O-D IR sensors have low resolution, low frame rates, high cost, sensor noise, and an increase in tracking time. In order to overcome these disadvantages, we propose an autonomous system application in indoor scenarios including 1) Dynamic 3D Reconstruction (D3DR) of the target view in real time images, 2) Human Behavior-based Target Tracking from O-D thermal images, 3) Thermal Multisensor Fusion (TMF), and 4) Visual Perception …
Respiratory Prediction And Image Quality Improvement Of 4d Cone Beam Ct And Mri For Lung Tumor Treatments, Seonyeong Park
Respiratory Prediction And Image Quality Improvement Of 4d Cone Beam Ct And Mri For Lung Tumor Treatments, Seonyeong Park
Theses and Dissertations
Identification of accurate tumor location and shape is highly important in lung cancer radiotherapy, to improve the treatment quality by reducing dose delivery errors. Because a lung tumor moves with the patient's respiration, breathing motion should be correctly analyzed and predicted during the treatment for prevention of tumor miss or undesirable treatment toxicity. Besides, in Image-Guided Radiation Therapy (IGRT), the tumor motion causes difficulties not only in delivering accurate dose, but also in assuring superior quality of imaging techniques such as four-dimensional (4D) Cone Beam Computed Tomography (CBCT) and 4D Magnetic Resonance Imaging (MRI). Specifically, 4D CBCT used in CBCT …
Coherent/Incoherent Magnetization Dynamics Of Nanomagnetic Devices For Ultra-Low Energy Computing, Md Mamun Al-Rashid
Coherent/Incoherent Magnetization Dynamics Of Nanomagnetic Devices For Ultra-Low Energy Computing, Md Mamun Al-Rashid
Theses and Dissertations
Nanomagnetic computing devices are inherently nonvolatile and show unique transfer characteristics while their switching energy requirements are on par, if not better than state of the art CMOS based devices. These characteristics make them very attractive for both Boolean and non-Boolean computing applications. Among different strategies employed to switch nanomagnetic computing devices e.g. magnetic field, spin transfer torque, spin orbit torque etc., strain induced switching has been shown to be among the most energy efficient. Strain switched nanomagnetic devices are also amenable for non-Boolean computing applications. Such strain mediated magnetization switching, termed here as “Straintronics”, is implemented by switching the …
Autonomous Navigation With Obstacle Avoidance For Unmanned Aircraft Systems Using Milp, James A. Devens
Autonomous Navigation With Obstacle Avoidance For Unmanned Aircraft Systems Using Milp, James A. Devens
Theses and Dissertations
Autonomous coordination among multiple aerial vehicles to ensure a collision free airspace is a critical aspect of today’s airspace. With the rise of Unmanned Aerial Vehicles (UAVs) in the military and commercial sectors, obstacle avoidance in a densely populated airspace is necessary. This thesis investigates finding optimal or near-optimal trajectories in real-time for aircraft in complex airspaces containing a large number of obstacles. The solution for the trajectories is described as a linear program subject to mixed integer constraints, known as a Mixed Integer Linear Program (MILP). The resulting MILP problem is solved in real time using a well-known, public …