The passive charge compensation (PCC) technique was introduced for switched capacitor (SC) circuit to increase the slew rate and enhance the linearity performance, as PCC techniques are used on the Delta-Sigma modulator (DSM) in ADC circuitry. The PCC technique of the project was applied to the design of a SC...
The sensors in real time data processing IoT devices require high resolution and sub-MHz data converters, usually implemented as Incremental ADCs due to the advantages of oversampling technique and low latency. In discrete time incremental (IDT) ADCs, the sampling switch non-linearity, charge injection degrade the resolution, and power hungry OPAMPs...
It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
Given the abundance of images related to operations that are being captured and stored, it behooves firms to innovate systems using image processing to improve operational performance that refers to any activity that can save labor cost. In this paper, we use deep learning techniques, combined with classic image/signal processing...
Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
Continuous Improvement (CI) of academic computing programs is a main requirement of accreditation. Academic computing programs must have a well-documented CI plan in order to be granted accreditation. Based on the existing literature, we developed a comprehensive CI (or 360-CI) model consisting of 8 components: course, curriculum, administration, faculty, research,...
Smart home devices are becoming increasingly popular and by 2021, it is estimated to have 80 million devices in the households of the U.S. The privacy and security threats involved with devices, as a result, are also scaling up in recent years. Smart home cameras have been hacked, private conversations...
The electrical grid is a key component of the Nation's critical infrastructure. Its continuous and reliable operation is of vital importance; any system-wide disruption would have a debilitating impact on crucial services, public health and safety, the economy, and the national security of the United States.
High-impact low-frequency events pose...
Is it possible to determine whether a signal violates a formula in Signal Temporal Logic (STL), if the monitor only has access to a low-resolution version of the signal? We answer this question affirmatively by demonstrating that temporal logic has a multiresolution structure, which parallels the multiresolution structure of signals....
The uncontrolled growth in domains such as surveillance systems, health care services, and finance produce a large amount of data and contain potentially sensitive data that can become public if they are not appropriately sanitized.
Motivated by this issue, we introduce a privacy filter (PF), a novel non-negative matrix factorization...
This work presents a novel CCRW receiver that utilizes a window of variable width, for e˙ectively mitigating multipath and ambiguity in both civil and military positioning applica-tions using Global Navigation Satellite Systems (GNSS). This CCRW receiver incorporates a single stroboscopic window, whose width is iteratively reduced until the e˙ect of...
There is a significant amount of research analyzing the effect of race, gender, and other common demographical data on student interest and performance in computer science. However, there is relatively little research concerning less common demographic populations, such as introverts, artistic students, and visual learners. This study investigates if these...
The need for sustainably powering unobtrusive internet-of-things applications has led to an interest in energy harvesting. Particularly, the proliferation of wireless communication and devices in the 2.4 GHz Industrial Scientificc Medical (ISM) band creates an opportunity to leverage commonly used devices for RF powering. This dissertation presents a low-quiescent-power...
This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
In this dissertation, we address action segmentation in videos under limited supervision. The goal of action segmentation is to predict an action class for each frame of a video. The limited supervision means ground truth labels of video frames are not available in training. We focus on three types of...
Significance: Movement intent decoding algorithms can interpret human bioelectrical signals to control prosthetic limbs with many degrees of freedom (DOFs). This work involves decoding volitional movement intent from surface electromyogram (sEMG) signals to control prosthetic arms. To train these algorithms, patients flex their muscles to “follow” a movement prompt, and...
Movement intent decoders, which interpret volitional movement intent from human bioelectric signals, can be incorporated into modern neuroprostheses to offer people living with limb loss or paralysis the potential to regain their lost motor control. Machine learning methods have become the research standard for continuous decoders with high degrees of...
This dissertation proposes the use of advanced time-varying approaches for modeling the dynamics of the multipath channel in wireless communication networks. These advanced time-varying approaches include linear Kalman innovation models in observable block companion form, and neural network-based models. The e˙ectiveness of these type of models is evaluated through three...
Simultaneous translation, which translates concurrently with the source language speech, is widely used in many scenarios including multilateral organizations. However, it is well known to be one of the most challenging tasks for humans due to the simultaneous perception and production in two languages. On the other hand, simultaneous translation...
Global Positioning Systems have allowed for precise timing of power system measurements over wide areas. This newly found capability has the potential to provide much greater insight into the operation of the power system and its response to contingencies, but few analytical techniques currently exist that provide enough robustness and...
Question Answering in natural language processing has achieved significant progress in recent years. Yet, training and testing set methodology to evaluate the language models has proved inadequate. Adversarial examples aid us in finding loopholes inside these models and provide insights into their inner workings. In this work, an evaluation based...
The tools and infrastructure used in tech, including Open Source Software (OSS), can embed “inclusivity bugs”—features that disproportionately disadvantage particular groups of contributors. To see whether OSS developers have existing practices to ward off such bugs, we surveyed 266 OSS developers. Our results show that a majority (77%) of developers...
Students’ success is one of the foremost objectives in higher education, and their self-efficacy plays a prominent role in students’ achieving their full potentials. It is especially important in STEM fields, which often suffer from higher attrition rates. Therefore, it is important to understand students’ self-efficacy levels at an early...
The Internet of Things (IoT) paradigm brought an ever-increasing dependence on low-power devices to collect sensor data and transmit that information to the cloud, placing greater demand on connectivity and lifespan. In response, rapid worldwide innovation demonstrates the trade-offs in processing, communication, and energy consumption with diverse approaches to low-power...
Smart home devices, such as voice assistants, smart lights, and smart video doorbells have become a part of end users' daily lives. Many of these devices combine their features with other services and smart devices to create a simple and efficient user experience. This is partly because of the contribution...
Merge conflicts have long plagued software development. With larger and more dispersed teams comes greater risk of developers working on the same code at the same time. While merge conflicts are known to be painful, their exact impact on software is still largely unknown. Are merge conflicts an isolated problem,...
Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
This work addresses the application of Nonlinear Model Predictive Control (NMPC) to a class of ocean wave energy conversion systems in which the cost functional is not in a standard quadratic form, and the WEC model includes the nonlinear effects, such as the hydrodynamic viscous drag. The NMPC implementation is...
Magnetic materials can be used in modern soft robotics as a method for external stimulus actuation and motion control. By combining aspects of biology and mechanics, devices are fabricated to create a structure capable of complex movement. Applications that these devices are subject to can be broken down into four...
In the ever-evolving field of computer science (CS) education, the significance of teachers and their backgrounds have often been overshadowed by the predominant focus on students. Teachers in the K-12 often lack the necessary expertise and have limited support provided by existing CS-based curricula. While research on CS education effectiveness...
Modern datacenters are constructed with multirooted tree topologies and support multiple service queues per switch port. They support a wide variety of applications and services with stringent performance needs and conflicting requirements. To meet these requirements, recent works focus on load balancing or ECN marking approaches. Though existing load-balancing approaches...
Throughput-oriented processors, such as graphics processing units (GPUs), have been increasingly used to accelerate general purpose computing, including machine learning models that are being utilized in numerous disciplines. Thousands of concurrently running threads in a GPU demand a highly efficient memory subsystem for data supply in GPUs. In this dissertation,...
With the advent of Artificial Intelligence (AI) in every sphere of life in today's day and age, it has become increasingly important for non-AI experts to be able to comprehend the underlying logic of how AI systems work, assess them and find faults in these systems, particularly when they are...
Tensor field topology is of importance to research areas of medicine, science, and engineering. Degenerate curves are one of the crucial topological features that provide valuable insights for tensor field visualization. In this thesis, we study the atomic bifurcations of degenerate curves in 3D linear second-order symmetric tensor fields, and...
Atomic layer deposition (ALD) is an enabling technique for many new micro- and nanoscale technologies. The self-limiting surface chemical reactions by which ALD fundamentally operates give rise to uniquely high precision (atomic) control over deposited film thickness, uniformity over large areas, and conformality over complex and extreme topographies. One such...
This study compares three approaches in the design of an autonomous machine listening agent that predicts harbor porpoise ultrasonic echolocation clicks in diverse noise environments. Considering the temporal variations of noisy coastal ocean soundscapes which the harbor porpoises inhabit, we propose a leave-one-day-out (LODO) cross-validation strategy in the training of...
In an increasingly computation-driven world, algorithms and mathematical models significantly impact decision making across various fields. To foster trust and understanding, it is crucial to provide users with clear and concise explanations of the reasoning behind the results produced by computational tools, especially when recommendations appear counterintuitive. Legal frameworks in...
Wind turbines serve an increasing proportion of total energy generation, with expanded onshore and offshore installations proceeding worldwide. Continued construction, expansion, and operation of wind energy installations must be managed in conjunction with effects on local and migratory wildlife, specifically bird and bat species that may be affected by wind...
Top-performing approaches to embodied AI tasks like point-goal navigation often rely on training agents via reinforcement learning over tens of millions (or even billions) of experiential steps – learning neural agents that map directly from visual observations to actions. In this work, we question whether these extreme training durations are...
Voltage fault injection is a technique to disrupt power supply, such that the data or instruction flow in a microcontroller can be modified. Recently, a new class of voltage glitches was introduced termed arbitrary wave voltage glitches. Despite its demonstrated success in practical studies it comes with additional challenges, such...
This work – in which three peer-reviewed academic papers are presented – addresses the ap-plication of Bayesian Reinforcement Learning to the control of a class of ocean wave energy conversion systems. The first paper presents a comparison of a Reinforcement-Learning (RL) based wave energy converter controller against standard Reactive Damping...
Due to the limitation of the radio frequency (RF) spectrum, it is increasingly more difficult to support billions of wireless devices in the age of Internet-of-Things. Consequently, many recent wireless indoor communication systems have been developed using free space optical (FSO) communication technologies that exploit the extremely large light spectrum...
This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
One of the pervasive problems arising in our modern, digital world surrounds data breaches where an adversary, through zero-day exploitations, phishing, or old-fashioned social engineering attacks, gains access to a service’s data stores. Our society increasingly relies on these cloud-based services for everything from our taxes to personal communication. As...
Materials with a strong spin Hall effect and Rashba-Edelstein effect have the potential to improve the efficiency of solid-state magnetic memory technologies and other magnetic logic devices. Heavy metals have been identified as having these properties, including the beta crystal phase of tungsten. In this work, we determine the strength...
Modern sensors are complex systems comprising multiple sub-systems such as transducers, analog and mixed-signal interface circuits, digital processing circuits, and packaging. Over the last few decades, innovations in these sub-systems combined with their increased integration in complementary metal-oxide semiconductor (CMOS) processes have led to the rapid growth in sensors for...
Relational binary operators, such as join, are arguably the most costly and frequently used operations in relational data systems. In many join algorithms, the majority of the process time is spent on scanning and attempting to join the parts of the relations that do not satisfy the join condition and...