Digital Commons Network^™

Development Of A Subsurface Water Velocity And Quality Measurement Payload For Suas, Mitchell Bailey

All Graduate Theses and Dissertations, Fall 2023 to Present

Aquaculture farms, like oyster farms, often use outdated techniques to measure the quality of their waters. These techniques are often stationary or are deployed by an operator who may struggle to reach a location depending on conditions like the presence of a storm or low tide. This creates data sets with gaps over time and across the area of the farm, meaning the data cannot be used to model the standard farm conditions. An Uncrewed Aerial System (UAS) payload is developed in this paper that is capable of measuring depth-velocity profiles through the use of a tethered velocity sensor. The …

Modeling, Control And Validation Of A Three-Phase Single-Stage Photovoltaic System, Eubis Pereira Machado, Adeon Cecílio Pinto, Rodrigo Pereira Ramos, Ricardo Menezes Prates, Jadsonlee Da Silva Sá, Joaquim Isídio De Lima, Flavio Bezerra Costa, Damásio Fernandes, Alex Coutinho Pereira

Michigan Tech Publications

The central inverter topology presents some advantages such as simplicity, low cost and high conversion efficiency, being the first option for interfacing photovoltaic mini-generation, whose shading and panel orientation studies are evaluated in the project planning phase. When it uses only one power converter, its control structures must ensure synchronization with the grid, tracking the maximum power generation point, appropriate power quality indices, and control of the active and reactive power injected into the grid. This work develops and contributes to mathematical models, the principles of formation of control structures, the decoupling process of the control loops, the treatment of …

An Improved Conditional Integrator Sliding Mode Controller Based On Swarm Intelligence For A Magnetic Levitation System, Abdelkader Kerraci, Mohamed Fayçal Khelfi, Zoubir Ahmed-Foitih

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes an enhanced Conditional Integrator Sliding Mode Controller using Particle Swarm Optimization (CISMCPSO) for a magnetic levitation system (MLS). The main advantage of this controller is its robustness to uncertainties and disturbances, which also avoids chattering and ensures zero static steady-state error. The main idea of CISMCPSO is to activate its integral action only when the sliding surface reaches the boundary layer while it is reduced to zero or close to zero elsewhere, which avoids destroying the transient response caused by the conventional integral sliding-mode controller. A particle swarm optimization algorithm schedules the conditional integral term parameter of …

Developing Linguistic Patterns To Mitigate Inherent Human Bias In Offensive Language Detection, Toygar Tanyel, Besher Alkurdi, Serkan Ayvaz

Turkish Journal of Electrical Engineering and Computer Sciences

With the proliferation of social media, there has been a sharp increase in offensive content, particularly targeting vulnerable groups, exacerbating social problems such as hatred, racism, and sexism. Detecting offensive language use is crucial to prevent offensive language from being widely shared on social media. However, the accurate detection of irony, implication, and various forms of hate speech on social media remains a challenge. Natural language-based deep learning models require extensive training with large, comprehensive, and labeled datasets. Unfortunately, manually creating such datasets is both costly and error-prone. Additionally, the presence of human-bias in offensive language datasets is a major …

Fault Diagnosis Of Photovoltaic Array Based On Gated Residual Network With Multi-Head Self Attention Mechanism, Ahmed Mesai Belgacem, Mounir Hadef, Abdesslem Djerdir

Turkish Journal of Electrical Engineering and Computer Sciences

Effective fault identification and diagnosis in photovoltaic (PV) arrays is vital for improving the effectiveness, and safety of solar energy systems. While various artificial intelligence methods have successfully established fault detection and diagnosis models, introducing inefficiencies and potentially overlooking useful features. Moreover, these methods often employ neural networks with limited performance capabilities. In response to these challenges, this paper introduces an innovative intelligent model that integrates a combination of a gated residual neural network (GRN) and a multi-head self-attention mechanism (MHSA). To evaluate the proposed fault diagnosis model, the small-scale PV grid system is implemented, and fault simulation experiments, including …

Strategies To Alleviate Flickering: Bayesian And Smoothing Methods For Deep Learning Classification In Video, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce A. Cox, Trevor Bihl

Faculty Publications

Excerpt: Increasing reliance on autonomous systems requires confidence in the accuracies produced from computer vision classification algorithms. Computer vision (CV) for video classification provides phenomenal abilities, but it often suffers from “flickering” of results. Flickering occurs when the CV algorithm switches between declared classes over successive frames. Such behavior causes a loss of trust and confidence in their operations.

Soc-Based Control System Performance Analysis For Trapped-Ion Quantum Computing, Tiamike Dudley

Electrical and Computer Engineering ETDs

Scatter-gather dynamic-memory-access (SG-DMA) is utilized in applications that require high bandwidth and low latency data transfers between memory and peripherals, where data blocks, described using buffer descriptors (BDs), are distributed throughout the memory system. The data transfer organization and requirements of a Trapped-Ion Quantum Computer (TIQC) possess characteristics similar to those targeted by SG-DMA. In particular, the ion qubits in a TIQC are manipulated by applying control sequences consisting primarily of modulated laser pulses. These optical pulses are defined by parameters that are (re)configured by the electrical control system. Variations in the operating environment and equipment make it necessary to …

Modeling W/V-Band Satellite Communications In The Presence Of Noise Jamming, Ryan Michael Eckman

Electrical and Computer Engineering ETDs

Understanding the performance of wideband modulated signals under noise jamming conditions is important for advancing W/V-band military satellite communications. This research developed and validated models to predict performance degradation of a communication channel in the presence of wideband noise jamming. Channel models were developed that included both modulated communication signals and jammer signals. Integrated models included environmental link factors and practical implementation factors. Integrated models were verified and validated using outdoor radio frequency environments utilizing two W/V-band transceivers, a portable W-band jammer, and software defined radios. Experimental results demonstrated excellent agreement with integrated model predictions. Channel degradation due to the …

Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin, Ruairí De Fréin, Alexander Mutiso Mutua Mr

Articles

Electric vehicle (EV) drivers in urban areas face range anxiety due to the fear of running out of charge without timely access to charging points (CPs). The lack of sufficient numbers of CPs has hindered EV adoption and negatively impacted the progress of sustainable mobility. We propose a CP distribution algorithm that is machine learning-based and leverages population density, points of interest (POIs), and the most used roads as input parameters to determine the best locations for deploying CPs. The objects of the following research are as follows: (1) to allocate weights to the three parameters in a $6$ km …

Design, Fabrication, And Characterization Of Electro-Optic Radio-Frequency Probes For High Field Environments, Michael D. Sherburne

Electrical and Computer Engineering ETDs

Design, Fabrication, and Characterization of Electro-Optic Radio-Frequency Probes For High Field Environments

Physical Layer Entropy Analysis For Physical Unclonable Functions, Jenilee Jao

Electrical and Computer Engineering ETDs

Process variations within Field Programmable Gate Arrays (FPGAs) provide a rich source of entropy, making them well-suited for the implementation of Physical Unclonable Functions (PUFs). This dissertation presents three studies on FPGA-based PUFs. First, we explore a ring-oscillator (RO) PUF that leverages localized entropy from individual look-up table (LUT) primitives, analyzing design bias. Next, we investigate delay variations that occur through the routing network and switch matrices of FPGAs using a feature of Xilinx called dynamic partial reconfiguration (DPR). Finally, we evaluate entropy across FPGAs from Xilinx, Altera, and Microsemi using the Shift-Register Reconvergent-Fanout (SiRF) PUF architecture to compare path …

A 3d Memristor Architecture For In-Memory Computing Demonstrated With Sha3, Muayad J. Aljafar, Rasika Joshi, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

Security is a growing problem that needs hardware support. Memristors provide an alternative technology for hardware-supported security implementation. This paper presents a specific technique that utilizes the benefits of hybrid CMOS-memristors technology demonstrated with SHA3 over implementations that use only memristor technology. In the proposed technique, SHA3 is implemented in a set of perpendicular crossbar arrays structured to facilitate logic implementation and circular bit rotation (Rho operation), which is perhaps the most complex operation in SHA3 when carried out in memristor arrays. The Rho operation itself is implemented with CMOS multiplexers (MUXs). The proposed accelerator is standby power-free and circumvents …

Hypoxic Incubator: Improving Robustness/Reliability And Demonstrating Physiological Efficacy, Damon Dennis Tan

Master's Theses

The Microphysiological Systems Laboratory aims to develop colorectal cancer tumor models under a hypoxic environment to assess model response to pharmaceutical compounds in vitro. To perform relevant studies, researchers have attempted to use different hypoxic inducing strategies such as a nitrogen pod and hypoxic incubator to recreate in vivo physiological responses to hypoxia. However, studies would be interrupted due to incubator functionality failure. To ensure successful and physiologically relevant studies, I improved and verified the robustness and reliability of a hypoxic incubator previously designed and manufactured in the lab. Through the testing and iterating design processes, I engineered and implemented …

Measuring Soil Salinity, Department Of Primary Industries And Regional Development, Western Australia

Natural resources factsheets

To make sound decisions on managing saline sites, you need to know the source of salt, how salinisation is occurring, the landscape context, and most importantly, the actual salt concentration of the soil.

The most common 'measures' of salt concentration are actually estimates based on electrical conductivity of a soil and water solution. Soil salt content can be measured in a laboratory by measuring the total dissolved solids in a sample. In the field, salt concentration can also be estimated using electromagnetic induction-based soil sensors.

Smart Systems For Employing Iot Devices For Monitoring And Control Of Electric Vehicle Residential Charging, Grant M. Fischer, Steven B. Poore, Rosemary E. Alden, Donovin D. Lewis, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

As the number of electric vehicles (EVs) on the road continues to increase, the rise in power demand may pose challenges, especially for the localized grid capacity during peak load events. This paper briefly reviews methods of power monitoring and load shedding such as smart charging and load management systems. An internet-of-things (IoT) power monitoring system is proposed for high-resolution power monitoring and control of J1772 standard level 2 EV charging systems to provide detailed data to enable future studies on EV grid integration. Additionally, a hardware test bench (HTB) including a DC battery emulator, oscilloscope, and commercial EV charger …

Autonomous Coalition Formation For Energy Trading In Intelligent Grid Systems, Issiac Baca

Electrical and Computer Engineering ETDs

This paper introduces an interactive model and architectural framework for a smart grid system, emphasizing the prosumers dual roles as energy buyers and sellers within localized energy trading markets, i.e., coalitions. Initially, the utilities of both buyers and sellers are formulated to capture the benefits derived from their energy-related activities. Then, the paper presents the Approximate SMARTFORM (ASMARTFORM) mechanism, based on the principles of matching theory, to enhance the prosumers engagement in coalitions by addressing externalities influencing their decisions. To further improve the coalition formation process, the Accurate SMARTFORM (AccSMARTFORM) mechanism is formulated based on the theory of coalition games, …

Safety-Centric Analysis Of Grounding Systems For Substations In Distribution Grids, Fazel Mohammadi, Mahmood Mirhashemi

Electrical & Computer Engineering and Computer Science Faculty Publications

The safety of grounding systems for substations in distribution grids is paramount to ensuring operational reliability, protecting personnel and equipment, and maintaining the stability of distribution grids while complying with regulatory standards. This paper explores essential safety aspects of grounding systems, including fault current handling strategies, the interdependence between protective devices and grounding systems, and maintenance practices. The integration of grounding systems design with overall substation layout and design considerations by focusing on mitigating Ground Potential Rise (GPR) and optimizing bonding techniques, is examined. Additionally, advanced techniques, such as high-frequency grounding and Transient Ground Potential Rise (TGPR) management, are presented …

Techniques For Modeling Ocean Soundscapes: Detailed Description For Wind Contributionsa, Martin Siderius, Michael A. Ainslie, John Gebbie, Alexandra Schäfke, N Ross Chapman, Bruce Martin, Kay L. Gemba

Electrical and Computer Engineering Faculty Publications and Presentations

Wind over the ocean creates breaking waves that generate air-filled bubbles, which radiate underwater sound. This wind-generated sound is a significant component of the ocean soundscape, and models are essential for understanding and predicting its impact. Models for predicting sound pressure level (SPL) from wind have been studied for many years. However, the terminology and definitions behind modeling approaches have not been unified, and ambiguity has led to differences in predicted SPL. The 2022 Ambient Sound Modeling Workshop was organized to compare ambient sound modeling approaches from different researchers. The main goal of the workshop was to quantify differences in …

Ontology Design Metapattern For Relationtype Role Composition, Utkarshani Jaimini, Ruwan Wickramarachchi, Cory Henson, Amit Sheth

Publications

RelationType is a metapattern that specifies a property in a knowledge graph that directly links the head of a triple with the type of the tail. This metapattern is useful for knowledge graph link prediction tasks, specifically when one wants to predict the type of a linked entity rather than the entity instance itself. The RelationType metapattern serves as a template for future extensions of an ontology with more fine-grained domain information.

An Overview Of Ancillary Services Provided By Vehicle-To-Grid Systems, Fazel Mohammadi, Mahmood Mirhashemi

Electrical & Computer Engineering and Computer Science Faculty Publications

Vehicle-to-Grid (V2G) systems are emerging as a pivotal technology in modern power systems, offering a range of ancillary services that enhance the stability and reliability of power systems. This paper provides an overview of the key ancillary services provided by V2G systems, highlighting their role in grid modernization. Technical challenges, economic implications, and policy considerations associated with the deployment of V2G systems are explored to assess their potential impact on advancing a more resilient and sustainable energy infrastructure.

Stressfit: A Hybrid Wearable Physicochemical Sensor Suite For Simultaneously Measuring Electromyogram And Sweat Cortisol, Nafize Ishtiaque Hossain, Tanzila Noushin, Shawana Tabassum

Electrical Engineering Faculty Publications and Presentations

This study introduces StressFit, a novel hybrid wearable sensor system designed to simultaneously monitor electromyogram (EMG) signals and sweat cortisol levels. Our approach involves the development of a noninvasive skin patch capable of monitoring skin temperature, sweat pH, cortisol levels, and corresponding EMG signals using a combination of physical and electrochemical sensors integrated with EMG electrodes. StressFit was optimized by enhancing sensor output and mechanical resilience for practical application on curved body surfaces, ensuring accurate acquisition of cortisol, pH, body temperature, and EMG data without sensor interference. In addition, we integrated an onboard data processing unit with Internet of Things …

Analysis Of Multivariable Sensor Responses To Multi-Analyte Gas Samples In The Presence Of Interferents And Humidity, Sakin Sarwar Satter, Florian Bender, Nicholas Post, Antonio J. Ricco, Fabien Josse

Electrical and Computer Engineering Faculty Research and Publications

This work presents an adaptive sensor signal-processing approach to enable quantification, using a single gas sensor or a small sensor array, of multianalyte mixtures of aromatic hydrocarbons in the presence of various interferents and humidity for environmental-monitoring applications. Dynamic sensor responses are analyzed by extracting multivariable sensing parameters to provide necessary sensitivity and selectivity. This is achieved by integrating the Levenberg–Marquardt-modified, exponentially weighted, recursive-least-squares-estimation (LM-modified EW-RLSE) algorithm and principal-component analysis (PCA). Achieving measured detection limits as low as 3 μg/L (≤1 ppm by volume) for 6 target analytes, the system exhibits excellent PCA cluster separation for all analytes in the …

Design And Analysis Of Optimal Energy Efficient Routing Protocols For Lifetime Maximization And Qos Enhancement In Wireless Body Area Networks, Karthikeyan S

Theses and Dissertations

In recent times, Wireless Body Area Networks (WBAN) a subsection of Wireless Sensor Networks (WSN) a promising technology for the future healthcare realm with cutting-edge technologies that can assist healthcare professionals like doctors, nurses and biomedical engineers which enables one-to-one care by implementing Tele-Medicine and Tele-Health solutions. Machine Learning (ML) and Internet of Things (IoT) enabled medical big data is the future of the healthcare sector and Medical Technology-based industries leading to applications in other sectors such as fitness tracking for commercial purposes, Sportsperson health monitoring to track their day-to-day activities and wearable devices for critical and emergency care.

Recent …

Cross-Track Seabed Imaging And Buried Object Detection With A Multibeam Sonar, Charles W. Holland, Samuel Pinson, Daniel L. Orange, Cody R. Henderson

Electrical and Computer Engineering Faculty Publications and Presentations

What lies underneath the ocean floor is of interest to a wide variety of disciplines. The focus here is imaging the upper tens of meters of material beneath the seafloor. The sub-bottom profiler is a valuable tool to that end, producing a 2-D image in depth below the seafloor and along the track of the ship. Geoscientists and engineers are frequently interested in not only the subseabed beneath the ship but also either side or cross-track of the ship. We show an approach to cross-track imaging using a low-frequency multibeam sub-bottom profiler. The main result is the detection of a …

A Deep Autoencoder For Electric Double Layer Capacitance Prediction In Electrochemical Sensors, Mason Mcgarrity, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

This study explores the application of a deep autoencoder neural network to accurately predict the electric double layer capacitance from real-world parameters in binary, asymmetric electrolytes under low concentration conditions. By utilizing a modest simulation-based dataset of just 250 samples, the deep autoencoder neural network model developed in this study effectively predicted the capacitance by learning the critical features and relationships of the electric double layer model and encoding this learned representation into a low-dimensional latent space. From the latent variables, the decoder block of the neural network learned to effectively recreate the high-dimensional input. To enhance the model's robustness, …

A Concept Of Controlling Grover Diffusion Operator: A New Approach To Solve Arbitrary Boolean-Based Problems, Ali Al-Bayaty, Marek A. Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

A controlled-diffusion operator for Boolean oracles is designed as a new approach for Grover’s algorithm to search for solutions for arbitrary logical structures of such oracles, since the Grover diffusion operator is not able to find correct solutions for some logical structures of Boolean oracles. We also show that the Phase oracles do not work sometimes correctly using the Grover diffusion operator. Our proposed controlled-diffusion operator relies on the states of output qubit, as the reflection of Boolean decisions from a Boolean oracle without relying on the phase kickback. We prove that on many examples of Boolean and Phase oracles …

Long-Distance Photon-Mediated And Short-Distance Entangling Gates In Three-Qubit Quantum Dot Spin Systems, Nooshin M. Estakhri, Ada Warren, Sophia E. Economou, Edwin Barnes

Engineering Faculty Articles and Research

Superconducting resonator couplers will likely become an essential component in modular semiconductor quantum dot (QD) spin qubit processors, as they help alleviate crosstalk and wiring issues as the number of qubits increases. Here, we focus on a three-qubit system composed of two modules: a two-electron triple QD resonator coupled to a single-electron double QD. Using a combination of analytical techniques and numerical results, we derive an effective Hamiltonian that describes the three-qubit logical subspace and show that it accurately captures the dynamics of the system. We examine the performance of short-range and long-range entangling gates, revealing the effect of a …

Experimentally Validated Dynamic Equivalent Circuit Model Of Perovskite Solar Cells: Utilizing Machine Learning Algorithms For Parameter Extraction Using I-V And C-V Characteristics, Zahraa Ismail, Eman Sawires, Fathy Amer, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

M3t-Lm: A Multi-Modal Multi-Task Learning Model For Jointly Predicting Patient Length Of Stay And Mortality, Junde Chen, Qing Li, Feng Liu, Yuxin Wen

Engineering Faculty Articles and Research

Ensuring accurate predictions of inpatient length of stay (LoS) and mortality rates is essential for enhancing hospital service efficiency, particularly in light of the constraints posed by limited healthcare resources. Integrative analysis of heterogeneous clinic record data from different sources can hold great promise for improving the prognosis and diagnosis level of LoS and mortality. Currently, most existing studies solely focus on single data modality or tend to single-task learning, i.e., training LoS and mortality tasks separately. This limits the utilization of available multi-modal data and prevents the sharing of feature representations that could capture correlations between different tasks, ultimately …

Development Of A Universal Humidity Converter At Ultra High Frequency, Hulkar Asadullayevna Usmonova, Asadulla Turgunbayev

Technical science and innovation

The article proposes the and principle of operation of a universal primary measuring transducer of humidity at an ultra-high frequency with reciprocating motion along the vertical axis of rotation, which allows increasing the information redundancy of the primary measuring transducer (the influence of inhomogeneities, including humidity in the composition of the material, on the measurement result is averaged). The design of the primary measuring transducer under consideration provides for correction of the moisture measurement result by the mass (density) of the material, which will make it possible to carry out measurements without preliminary weighing the sample. The obtained results of …