Engineering Commons^™

Gen-Acceleration: Pioneering Work For Hardware Accelerator Generation Using Large Language Models, Durga Lakshmi Venkata Deepak Vungarala

Theses

Optimizing computational power is critical in the age of data-intensive applications and Artificial Intelligence (AI)/Machine Learning (ML). While facing challenging bottlenecks, conventional Von-Neumann architecture with implementing such huge tasks looks seemingly impossible. Hardware Accelerators are critical in efficiently deploying these technologies and have been vastly explored in edge devices. This study explores a state-of-the-art hardware accelerator; Gemmini is studied; we leveraged the open-sourced tool. Furthermore, we developed a Hardware Accelerator in the study we compared with the Non-Von-Neumann architecture. Gemmini is renowned for efficient matrix multiplication, but configuring it for specific tasks requires manual effort and expertise. We propose implementing …

Characterization Of Low Power Hfo2 Based Switching Devices For In-Memory Computing, Aseel Zeinati

Theses

Oxide based Resistive Random Access Memory (RRAM) devices are investigated as one of the promising non-volatile memories to be used for in-memory computing that will replace the classical von Neumann architecture and reduce the power consumption. These applications required multilevel cell (MLC) characteristics that can be achieved in RRAM devices. One of the methods to achieve this analog switching behavior is by performing an optimized electrical pulse. The RRAM device structure is basically an insulator between two metals as metal-insulator-metal (MIM) structure. Where one of the primary challenges is to assign an RRAM stack with both low power consumption and …

A Parametric Numerical Analysis Investigation To Optimize The Performance Of The Ranque-Hilsch Vortex Tube, Muneer Ahmad Sungur

Theses

A vortex tube is a device that separates compressed air into two streams: one with a higher temperature (hot stream) and the other with a lower temperature (cold stream). It is a popular cooling option because it is small, safe, and affordable. The main objective of this thesis is to examine the energy separation performance of RHVT by varying the internal tapering angles of convergent angles (2°, 1.75°, 1.5°, 1.25°, 1°, 0.75°, and 0.5°), straight angles (0°), and divergent angles (0.5°, 1°, 2°, 4°, and 6°), While the cold mass fraction is constant (0.317). Length-to-diameter ratio (Lt/Dt), inlet pressure, and …

A Novel Approach For Detection Fault In The Aircraft Exterior Body Using Image Processing, Noura Nayef Almansoori

Theses

The primary objective of this thesis is to develop innovative techniques for the inspection and maintenance of aircraft structures. We aim to streamline the entire process by utilizing images to detect potential defects in the aircraft body and comparing them to properly functioning images of the aircraft. This enables us to determine whether a specific section of the aircraft is faulty or not. We achieve this by employing image processing to train a model capable of identifying faulty images. The image processing methodology we use involves the use of images of both defective and operational parts of the aircraft's exterior. …

Modeling Of Quad-Station Module Cluster Tools Using Petri Nets, Aung Nay

Theses

The semiconductor industry is highly competitive, and with the recent chip shortage, the throughput of wafers has become more important than ever. One of the tools that the industry has deployed is to use of quad-station modules instead of the traditional single-station modules that allow for higher throughput and better wafer consistency by processing multiple wafers at the same time and distributing work. The industry trend is to use multiple transfer chamber robots to stack the quad-station modules in a series, particularly for etch products. In this work, the quad-station cluster tool wafer movement is modeled by using Petri net …

Recycling Of Cured Carbon Fiber/Epoxy Resin Laminated Composites Scraps: Processing And Characterization, Khaled Mohammed Al Harmoodi

Theses

The concept of reinforced composites came decades ago from the need to fabricate high-strength, heat-resistant, wear-resistant, and low-density materials. The polymer matrix composites offer a wide range of applications due to the collaborative nature of the functional fillers and polymers present. Towards the twenty-first century, the aviation industry flourished due to flying being the preferred way of travel across states and countries. With such a massive demand for air transport, there is an equally parallel demand for the production of aircraft components. This study aims to reuse the waste of uncured composite prepreg scraps from the ply-cutting manufacturing process in …

Disturbance-Observer Based Control For Pwm Rectifiers Without Dc Voltage Oscillations Under Unbalanced Grid Conditions, Mohammed Samer Al-Razehi

Theses

A three-phase controlled rectifier is a power electronic converter that employs the grid voltages as an input to produce a constant dc voltage at its output through the use of a capacitor, known as dc-link capacitor. However, the switching devices of power converters can create harmonics in the grid current, which mandates the need for filters to ensure high-quality grid current. This explains why the power converter is normally connected to the grid using passive filters such as L filter or LCL filter. The L filter is normally preferred over LCL filter to reduce harmonic distortions in grid currents as …

The Design Of A Point Of Care Fet Biosensor To Detect And Screen Covid-19, Nisreen Amer Mohammad Alnaji

Theses

This work proposes and demonstrates a biosensor with reduced Graphene Oxide (rGO) based Field Effect Transistor (FET) for rapid and selective detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The main objective of this thesis is to detect the SARS-CoV-2 spike protein antigen on spot selectively and rapidly. The rGO channel is coated with the spike protein antibodies to achieve selectivity. Moreover, the biosensing performance and specificity are governed by decorating the sensor’s channel with Metal Nanoparticles (MNPs) such as, copper, and silver. The designed sensor successfully detects the SARS-CoV-2 spike protein and shows singular electrical behavior for detection. …

Quality-Of-Service Provisioning For Smart City Applications Using Software-Defined Networking, Basima Kurungadan

Theses

In the current world, most cities have WiFi Access Points (AP) in every nook and corner. Hence upraising these cities to the status of a smart city is a more easily achievable task than before. Internet-of-Things (IoT) connections primarily use WiFi standards to form the veins of a smart city. Unfortunately, this vast potential of WiFi technology in the genesis of smart cities is somehow compromised due to its failure in meeting unique Quality-of-Service (QoS) demands of smart city applications. Out of the following QoS factors; transmission link bandwidth, packet transmission delay, jitter, and packet loss rate, not all applications …

Advancing Industrial Participation In Demand Response Within National Electricity Grids Through Systematic Asset Selection, Risk Assessment And Modelling Approaches, Alexander Brem

Theses

Increasing the flexible capacity on national electricity grids will be key to maintain reliable control as the levels of renewables continue to increase annually. The industrial sector has been identified as being capable of contributing and potentially offering flexible capacities, following appropriate investigation. The aim of this thesis is to develop the knowledge, advance the engagement and encourage additional participation in national demand response programmes from the industrial sector to provide this flexibility. The potential within this sector, facilitated by the smart grid and demand response concepts is outlined, specifically detailing their benefits, driving factors and potential barriers as part …

Robust Detection Of Coronary Heart Disease Using Machine Learning Algorithms, Anas Haitham Domyati

Theses

Predicting whether or not someone will get heart or cardiac disease is now one of the most difficult jobs in the area of medicine. Heart disease is responsible for the deaths of about one person per minute in the contemporary age. Processing the vast amounts of data that are generated in the field of healthcare is an important application for data science. Because predicting cardiac disease is a difficult undertaking, there is a pressing need to automate the prediction process to minimize the dangers that are connected with it and provide the patient with timely warning. The chapter one in …

Human Detection From Aerial Imagery For Search And Rescue Operations, Namat Ahmad Bachir

Theses

Mountain recreation is becoming more popular with mountaineering, rock climbing, skiing, mountain biking, hiking, and mushroom picking among the most popular sports. Despite this tendency, there is currently limited research available explaining the rise in search and rescue (SAR), as well as the injuries and illnesses that entail SAR aid in tourist-friendly mountain and desert areas. The objective of a search and rescue operation is to scan the farthest area feasible in the shortest amount of time in order to locate a lost or wounded individual. In the past decade, several new and spectacular uses for drones, including search and …

Quantitative Dynamic Cellular Imaging Based On 3d Unwrapped Optical Coherence Phase Microscopy, Arunkumar Gunasekar

Theses

Phase wrapping artifacts are frequently encountered in phase resolved imaging and sensing techniques based on interferometry. When the value of the actual phase (φ) ranges beyond (-π, π], the extracted phase value (wrapped phase Ψ) is artificially increased or decreased by a multiple of 2π.

In this study, we develop a 3D phase unwrapping method that exploits the correlation of 3D phase data (φ(x,y,t)) over the other dimension (t). We validate our 3D unwrapping method using simulated data, as well as experimental data obtained by optically computed phase microscopy (OCPM) recently developed in our lab. Our results show that the …

Design And Implementation Of Photovoltaic Energy Harvesting Automaton, Iskandar Askarov

Theses

Global domestic electricity consumption has been rapidly increasing in the past three decades. In fact, from 1990 to 2020, consumption has more than doubled from 10,120 TWh to 23,177 TWh [1]. Moreover, consumers have been turning more towards clean, renewable energy sources such as Photovoltaic. According to International Energy Agency, global Solar power generation alone in 2019 has reached almost 3% [4] of the electricity supply. Even though the efficiency of photovoltaic panels has been growing, presently, the highest efficiency solar panels available to an average consumer range only from 20%-22% [14]. Many research papers have been published to increase …

Model-Based Cognitive Communications For Low-Power Wireless Networks, Indika Sanjeewa Abeywickrama Dhanapala

Theses

Our world is increasingly being instrumented with low-power wireless networks that deliver data for diverse application domains such as energy management, health and well-being, security, and other Internet of Things services. As these wireless networks operate in the unlicensed radio spectrum while co-existing with various other communication networks, their communication reliability and energy efficiency are affected by the radio environment. Because of this vulnerability to radio interference, low-power wireless networks may be unable to deliver their application requirements and be inefficiently consuming energy, functioning as a low-dependability network. The situation is exacerbated in indoor environments such as office and residential …

Robust Control Strategies For Optimal Operation Of Distributed Generation In Smart Microgrids, Chi-Thang Phan-Tan

Theses

The high penetration of PV systems and fast communications networks increase the potential for PV inverters to support the stability and performance of smart grids and microgrids. PV inverters in the distribution network can work cooperatively and follow centralized and decentralized control commands to optimize energy production while meeting grid code requirements. However, there are older autonomous inverters that have already been installed and will operate in the same network as smart controllable ones. This research proposes a decentralized optimal control (DOC) that performs multi-objective optimization for a group of PV inverters in a network of existing residential loads and …

Flexible Microfluidic Device With Nonplanar Interdigitated Microelectrodes, Saud Alssaidy

Theses

The lab-on-a-chip concept has improved significantly in recent years to meet global demand for various applications with the advent of new technologies. Much progress has been achieved, but many microfluidic devices still suffer from design limitations in terms of sensitivity and selectivity because they use rigid, fragile substrate materials and conventional electrodes, which do not provide high sensitivity or selectivity and suffer from signal-to-noise ratio issues. This work proposes a novel device architecture that uses flexible, transparent top and bottom layers integrated with (nonplanar interdigitated microelectrodes) to create a sandwich-like flexible substrate base. The top and bottom layers consist of …

Split-Horizon Dual-Stage Dispatch Scheme For A Standalone Microgrid, Aslam Amir

Theses

The advent of microgrids has prompted plenty of studies into its design, control, protection, and implementation, with several operational as well as pilot systems being commissioned worldwide. This necessitates the development of hardware and software for the Energy Management System, the supervisory controller in a microgrid. Hence, this thesis provides a novel dual-stage dispatch scheme for the Energy Management System of a Standalone microgrid by “splitting” the dispatch time horizon into four equal quarters to facilitate better usage of power forecast accuracies. The two stages include Unit Commitment/Scheduling and Economic Dispatch for the dispatchable Distributed Energy Resources based on renewable …

Adaptive Uplink Data Rate Prediction And Networkselection In A Vehicular Mobile Channel, Georgi Nikolov

Theses

The rapid acceleration into the digital age brings a worldwide interconnectedness of an unprecedented level. This interconnectedness transforms the modern transportation network by linking its infrastructure components (e.g., signaling systems, traffic control systems, maintenance systems) together. Intelligent transportation systems (ITS) can utilize this newly emerged network infrastructure, improving traffic safety, traffic control, and reducing transportation-related environmental impacts, changing the way drivers, businesses and governments deal with road transport. It is expected that in the near future self-aware vehicles (e.g., trains, cars or trucks) will constitute the majority of the transportation infrastructure. Vehicles need to be able to reliably communicate critical …

Treated Hfo2 Based Rram Devices With Ru, Tan, Tin As Top Electrode For In-Memory Computing Hardware, Yuvraj Dineshkumar Patel

Theses

The scalability and power efficiency of the conventional CMOS technology is steadily coming to a halt due to increasing problems and challenges in fabrication technology. Many non-volatile memory devices have emerged recently to meet the scaling challenges. Memory devices such as RRAMs or ReRAM (Resistive Random-Access Memory) have proved to be a promising candidate for analog in memory computing applications related to inference and learning in artificial intelligence. A RRAM cell has a MIM (Metal insulator metal) structure that exhibits reversible resistive switching on application of positive or negative voltage. But detailed studies on the power consumption, repeatability and retention …

Spectral 3d Reconstruction Based On Macroscopic Oct Imaging, Xingyu Zhou

Theses

Various optical technologies have been utilized to improve art conservation by art conservators, such as laser triangulation, stereophotogrammetry, structured light, laser scanner and time of flight sensors. These methods have been deployed to capture the 3D or surface topography information of sculptures and architectures. Optical coherence tomography (OCT) has introduced new imaging methods to study the surface features and subsurface structures of delicate cultural heritage objects. However, despite its higher spatial resolution, the field of view (FOV) of OCT severely limits the size of the scanning area and does not allow macroscopic examination. To solve this issue, we develop and …

Deep Learning For Quantitative Motion Tracking Based On Optical Coherence Tomography, Peter Abdelmalak

Theses

Optical coherence tomography (OCT) is a cross-sectional imaging modality based on low coherence light interferometry. OCT has been widely used in diagnostic ophthalmology and has found applications in other biomedical fields such as cancer detection and surgical guidance.

In the Laboratory of Biophotonics Imaging and Sensing at New Jersey Institute of Technology, we developed a unique needle OCT imager based on a single fiber probe for breast cancer imaging. The needle OCT imager with sub-millimeter diameter can be inserted into tissue for minimally invasive in situ breast imaging. OCT imaging provides spatial resolution similar to histology and has the potential …

An Information Theoretic Approach To Assess Perceived Audio Quality Using Eeg With Reduced Number Of Electrodes, Sansit Das

Theses

Electroencephalograph(EEG) is a process mainly used in medical and research fields to study the electrical activities in a brain. In this technique, 128 or 256 electrodes are attached to the scalp and the electrical activities of the human brain is recorded with the help of a software. In the global scenario, the EEG responses are studied and analysed to acknowledge any disorders in the brain, such as epilepsy or head injury.

Recent studies performed by researchers, have focused on analysing these electrical activities to access perceived audio quality from users by using information theoretic approaches, such as mutual information. Experiments …

Smart Inverters For Distributed Pv Network Management, Colin Charles Levis

Theses

Securing a sustainable decarbonised economy involves moving towards a decentralised power system with increasing penetration levels of distributed photovoltaics (PVs) within the low voltage distribution network (LVDN). Increasing penetration levels of PV systems pose challenges for maintaining grid voltage and frequency stability. Thus requires studies and simulations to estimate the needs and technical requirements to overcome the challenges and maximise the opportunities. These simulations require time-domain system models with a high dynamic resolution such as electromagnetic transient (EMT) simulations with small-time steps that capture the required performance with large numbers of network elements. However, the small-time step implies a high …

Study And Modelling Of Lithium Ion Cell With Accurate Soc Measurement Algorithm Using Kalman Filter For Electric Vehicles, Kasthuriramanan Mahendravadi Sivaguru

Theses

Lithium Ion cells are preferred over lead acid cells for electric vehicles due to their energy density, higher discharge current and size. The cost of lithium ion cells is scaling down compared to ten years earlier, but as their performance characteristics increase, the need for safety and accurate modelling also increases.

The absence of a generic cell model is associated to the different makes of cells and different chemistries of Lithium ion cells behave differently under the testing conditions required for every unique application. The focus of this thesis will be on how to provide intelligence to the battery management …

Magnetic Field Effects On Lithium Ion Batteries, Kevin Mahon

Theses

The Nobel Prize in Chemistry 2019 was just recently awarded to John B. Goodenough, M. Stanley Whittingham, and Akira Yoshino for the development of lithium-ion batteries. Lithium-ion batteries have seen use in many different industries and applications such as in portable devices, power grids, and electric vehicles. As lithium-ion batteries become more commonplace they will need to be modeled more extensively. The magnetic field effect on lithium-ion batteries has not been studied significantly since they were first discovered.

Modeling these batteries is still difficult because of the many complexities of the operation of a battery. Lithium-ion batteries are commonly modeled …

Blind Source Separation Using Dictionary Learning Over Time-Varying Channels, Anushreya Ghosh

Theses

Distributed sensors observe radio frequency (RF) sources over flat-fading channels. The activity pattern is sparse and intermittent in the sense that while the number of latent sources may be larger than the number of sensors, only a few of them may be active at any particular time instant. It is further assumed that the source activity is modeled by a Hidden Markov Model. In previous work, the Blind Source Separation (BSS) problem solved for stationary channels using Dictionary Learning (DL). This thesis studies the effect of time-varying channels on the performance of DL algorithms. The performance metric is the probability …

Comparison Study Of Supervised Machine Learning Algorithms For Real Time Prediction Of Uav Behaviors, Brian Baity

Theses

An American scientific writer/critic of the mid-20th century, Joseph Wood Krutch, stated, “Technology made large populations possible: large populations now make technology indispensable.” Unmanned aerial vehicles (UAVs) have become a vital part of society, evolving from solely military use to commercial and even personal day-to-day use. UAV application has grown for mobility on demand, increasing the number of UAVs in the sky. Consequently, more UAVs increases the possibility of aerial collisions, challenging the safety of passengers flying and bystanders on the ground. Understanding the behavior of UAVs and unmanned aerial systems (UAS) in general, therefore, will decrease the possibility of …

Design Of Dual-Band Rf-Dc Rectifier And Dc-Dc Boost Converter For Energy Harvesting Applications, Merghani K. Merghani

Theses

Wireless sensors are used in many industrial and commercial applications. However powering up those sensors is challenging, because batteries have limited lifetime, require periodic maintenance, and their depositions are toxic to the environment. One of the new methods to power up those small sensors is to capture energy from ambient sources and convert it into a steady dc output voltage, which is known as energy harvesting or scavenging. In this thesis, we propose an energy harvesting method by scavenging the electromagnetic (EM), or radio frequency (RF) energy in the ambient and converting it into a steady dc output voltage that …

Reinforcement Learning Reward Design For Low-Level Controllers, Evan J. Olney

Theses

The past few decades have produced many successful applications of machine learning. In the area of automated controls, machine learning controllers have been developed to take advantage of the tendency for computers to stumble upon avenues to solutions people either overlooked, or simply do not have the computational capability to explore. Reinforcement learning is a machine learning technique for learning how to choose actions in an environment to increase its expected reward. The reward is the signal that indicates whether or not proper actions were chosen, therefore a behavioral goal is achieved from implicit rewards rather than explicit direction. The …