Electrical and Computer Engineering Commons^™

Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes, Peijian Zeng, Guan Wang, Haohao Gu, Xiaoguang Hu, Tiezhu Gao, Zhuowei Wang, Aimin Yang, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

Solving large-scale PDEs on complex three-dimensional geometries remains a central challenge in scientific and engineering computing, often due to expensive pre-processing stages and high computational overhead. We present Low-Rank Query-based PDE Solver (LRQ-Solver), a physics-integrated deep learning framework for efficient CAE simulations of complex three-dimensional geometries in CAD-driven design analysis. Built upon the Parameter-Conditioned Lagrangian Modeling (PCLM) that embeds physical consistency into the learning process and the Low-Rank Query Attention (LR-QA) module that reduces attention complexity from O(N2) to O(NC2+C3) via covariance decomposition, LRQ-Solver supports multi-configuration analysis within iterative design workflows. On two benchmark datasets, it achieves a 28.6% error …

Influence Of Particle Properties And Grain Size On Aggregation In Dry Particle-Laden Volcanic Jets, Md Miraz Hossain, Stephen A. Solovitz, Josef Dufek, Joshua S. Mendez Harper, Alexa R. Van Eaton, Mary C. Benage, Larry G. Mastin, Benjamin J. Andrews

Electrical and Computer Engineering Faculty Publications and Presentations

Explosive volcanic eruptions can inject large amounts of ash into the atmosphere. These suspended particles pose hazards to aircraft, so a better understanding of the ash residence time and transport distance is needed. Fine particles combine to form larger aggregates, altering their settling behavior. Ash aggregation is influenced by liquid bonding, electrostatic forces, and preferential concentration driven by turbulence. We examine particle aggregation through controlled, low-humidity experiments at similar particle-fluid scaling to conditions near a volcanic vent. Particle-laden jets used compressed air containing three types of particles at controlled mass loadings: hollow glass spheres (∼10 μm diameter), solid nickel spheres …

A Graph Attention Network-Based Framework For Reconstructing Missing Lidar Beams, Khalfalla Awedat, Mohamed Abidalrekab, Mohammad El-Yabroudi

Electrical and Computer Engineering Faculty Publications and Presentations

Vertical beam dropout in spinning LiDAR sensors -triggered by hardware aging, dust, snow, fog, or bright reflections - removes entire vertical slices from the point cloud and severely degrades 3D perception in autonomous vehicles. This paper proposes a Graph Attention Network (GAT)-based framework that reconstructs these missing vertical channels using only the current LiDAR frame, with no camera images or temporal information required. Each LiDAR sweep is represented as an unstructured spatial graph: points are nodes and edges connect nearby points while preserving the original beam-index ordering. A multi-layer GAT learns adaptive attention weights over local geometric neighborhoods and directly …

Surrogate-Guided Conditional Generative Adversarial Network For Generative Design Of 3d-Printable Terahertz Holographic Metasurfaces, Manxu Lv, Zhikai Hu, Zhichuan Xie, Huizhen Feng, Dongping Zhang, Manna Gu, Chee Leong Tan, Bo Fang, Yongxing Jin, Ying Tian, Xufeng Jing

Electrical and Computer Engineering Faculty Publications and Presentations

Terahertz metasurface holography requires unit cells with prescribed complex transmission responses and sufficient compatibility with practical fabrication processes. For elementary low-bit phase quantization at 0.1 THz, conventional parameter sweeping of simple geometries remains an effective and reliable approach. However, when the design objective is extended from a single phase state to simultaneous consideration of complex transmission matching, transmission amplitude, structural connectivity, and fabrication-related geometric constraints, the design problem becomes a constrained multi-objective inverse-design task. Here, we propose a generative-model-assisted inverse-design framework for 3D-printable terahertz metasurface unit cells. The framework combines a VGG-based surrogate model with a modified WGAN-GP generator. The …

Superiorgat: Graph Attention Networks For Sparse Lidar Point Cloud Reconstruction In Autonomous Systems, Khalfalla Awedat, Mohamed Abidalrekab, Gurcan Comert, Mustafa Ayad, Negash Begashaw

Electrical and Computer Engineering Faculty Publications and Presentations

LiDAR-based perception in autonomous systems is fundamentally limited by sparse vertical sampling and further degraded by structured beam dropout caused by occlusions, sensor faults, or reduced-cost LiDAR hardware. These degradations disrupt vertical geometric continuity and negatively affect downstream perception tasks such as object detection, localization, and scene understanding. Existing reconstruction approaches often struggle to balance reconstruction accuracy with the computational efficiency required for real-time autonomous operation. This paper presents SuperiorGAT, a graph attention–based framework for reconstructing missing elevation information in sparse LiDAR point clouds under structured beam loss. The proposed method models LiDAR scans as beam-aware graphs and enhances standard …

Multi-Solution Ternary Grover’S Algorithm For Logic-Based Quantum Machine Learning With Pseudo-Kronecker Reed–Muller Form Minimization, Sophia Lee, Ali Al-Bayaty, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Optimization problems in machine-learning (ML) applications can be computationally challenging for classical methods, particularly when they involve large, unstructured search spaces. Quantum computing offers a promising approach to combinatorial optimization by utilizing quantum superposition and amplitude amplification. This paper presents a new methodology using logic-based quantum machine learning (QML) as a complete framework for employing a multi-solution ternary Grover’s algorithm to minimize incomplete binary functions represented by Pseudo-Kronecker Reed–Muller (PKRO) expansions, consistent with Occam’s razor principle. Unlike previous quantum approaches based on Kronecker Reed–Muller (KRO) or fixed-polarity Reed–Muller (FPRM) representations, our work introduces the first Grover-based optimization framework for PKRO …

Fault Recovery For A Class Of Unmanned Autonomous Vehicles Using Gaussian Process Regression, Garrison Greenwood

Electrical and Computer Engineering Faculty Publications and Presentations

Unmanned autonomous vehicles (UAVs) must often operate reliably in remote, hostile environments for extended periods. Fault tolerance is essential, enabling continued operation despite system faults. Fault recovery is challenging due to unknown fault characteristics and no possibility of on-site human intervention. Replacing faulty hardware with operating spares is an effective recovery method, but impractical because UAVs have limited space. Reconfiguration may be the only practical option. This paper discusses correcting faulty behavior in robot arm DC servos, guided by a PID controller, by modifying the controller’s gain values. Although simple in principle, finding new gain values is difficult and time-consuming, …

Seasonal Changes In Sediment Sound Speed Profiles, Charles W. Holland, Chad Smith, Tim Sonnemann

Electrical and Computer Engineering Faculty Publications and Presentations

Marine sediment sound speed profiles in the upper ten meters are generally assumed to be constant with time. Models predict that substantive changes occur because of thermal conduction from seasonally varying bottom water temperature. However, definitive measurements have been lacking. In this work, sediment sound speed profiles obtained during different seasons show significant differences in the upper 9 m of mud at the New England Patch. Gradients in late March 2017 are 6.0 s−1 and in early October 2025, 2.6 s−1. This change is shown to have a significant impact on acoustic propagation.

Seabed Wide-Angle Reflection Coefficient And Source Radiation Pattern Measurements From A Low-Frequency Multibeam Sonar, Charles W. Holland, Cody R. Henderson, Tim Sonnemann, Bjørnar Langli, Daniel L. Orange

Electrical and Computer Engineering Faculty Publications and Presentations

In acoustic remote sensing, the seabed frequency-domain reflection coefficient contains significant geoacoustic information, namely the depth and frequency dependence of sediment sound speed, density, and attenuation. Typical reflection measurements are performed with a towed source and/or receivers to obtain a range of seabed reflected angles. It is shown here that the measurements can be performed using a hull-mounted low-frequency multibeam sonar with an offboard fixed or drifting hydrophone. To obtain the reflection coefficient (as well as scattering strength and other quantities of potential interest), the multibeam sonar radiation pattern must be known. Radiation patterns and absolute levels of the Kongsberg …

Rapid-Prototyping Nanofabrication: Lcd-Based Projection Lithography And Physical Vapor Deposition, Sabeel Saleem Mohammmed

University Honors Theses

The semiconductor industry's continued growth, driven in large part by demand for artificial intelligence hardware, has highlighted the need for greater workforce development in regions adjacent to major fabrication centers like Oregon's Silicon Forest. This capstone project lays the groundwork for a small scale and student led semiconductor fabrication lab at Portland State University by demonstrating two of the core steps in chip manufacturing: photolithography and thin film deposition. Rather than relying on conventional fixed reticles, this work explores a unique, low cost approach to patterning that uses an ultraviolet-compatible liquid crystal display (LCD) as a programmable reticle, allowing arbitrary …

Universal Communications Module: Converting Ieee2030.5 Xml Files To Ansi/Cta-2045, Wyatt Bilodeaux

University Honors Theses

The goal of this thesis is to discuss the method and organization of the Universal Communication module capstone project. This project was part of the Portland State University Electrical engineering degree program. While this thesis is part of the University honors curriculum. This thesis goes into detail about team structure and how a 9 person engineering capstone project was managed and organized. It looks at how we broke down the project into sections to be able to properly distribute our resources. This was one of the earliest and most important challenges that this capstone team had to tackle. This was …

The Impact Of Optimization Approximation Algorithms On The Performance Of The Bht-Qaoa, Ali Al-Bayaty, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

This article investigates the performance impact of five classical optimization approximation algorithms on our previously introduced quantum search algorithm, termed the Boolean–Hamiltonians Transform for Quantum Approximate Optimization Algorithm (BHT-QAOA), to effectively search for all best-approximated solutions for Boolean-based problems. These optimization approximation algorithms are BFGS, L-BFGS-B, SLSQP, COBYLA, and COBYQA. Their performance impact is evaluated and compared using two proposed performance metrics—(i) the final number of function evaluations (the lower numbers denote the best optimization approximation algorithms) and (ii) the final quality of qubit measurements (the higher values indicate all best-approximated solutions were found for a problem). Arbitrary classical Boolean …

Improving The Circuit Realization Of Grover’S Quantum Search Algorithm By Replacing Hadamard With √ × Gates, Ali Al-Bayaty, Ali Al-Shuwaili, Abbas Alzubaidi, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Jozsa, Bernstein-Vazirani, and Grover, utilize Hadamard gates to create uniform superposition states for the input qubits of an oracle. However, Hadamard gates are non-native (non-supported) gates in all real quantum computers. For this reason, Hadamard gates are considered cost-expensive gates when realizing (transpiling) such algorithms into a real quantum computer. This paper introduces a new methodology for cost-effective transpilation of Grover’s algorithm into real quantum computers, by replacing all Hadamard gates with √ X gates. In quantum computing, the Hadamard and √ X gates create uniform superposition states of a qubit on the Xaxis and Y-axis of the Bloch sphere, …

Physiobridge: Physiology-Constrained Self-Supervised Foundation Model For Cross-Device Ecg–Ppg Learning With Conformal Risk Control, Abbas Alzubaidi, Ali Al-Shuwaili, Ali Al-Bayaty

Electrical and Computer Engineering Faculty Publications and Presentations

Wearable and bedside sensors continuously generate electrocardiograms (ECG), photoplethysmograms (PPG), and related physiological waveforms that could enable earlier detection of deterioration and more personalized care. However, current deep learning pipelines in biomedical signal processing often remain taskand device-specific, degrade under domain shift (new hospitals, sensors, skin tones, motion), and provide limited uncertainty information for safety-critical decisions. We propose PhysioBridge, a foundation-model approach that learns a shared representation space for ECG and PPG via self-supervised pretraining and explicit physiology constraints, then supports downstream adaptation with distribution-free risk control. PhysioBridge introduces (i) multi-rate patch tokenization that preserves clinically meaningful morphology across heterogeneous …

Intrusion Detection Latency: The Neglected Metric, Sandhyarani Dash, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

Accuracy remains the dominant evaluation metric in Intrusion Detection System (IDS) research, yet an IDS that detects attacks too late is functionally equivalent to one that fails—particularly in Internet of Things (IoT) environments. In operational settings, the timing of detection shapes both the scope of adversarial activity and the feasibility of effective response. To the best of our knowledge, latency (the speed at which intrusions are identified) has received no systematic attention. Our analysis of published IDS papers reveals that latency is defined inconsistently—often referring to inference, communication, computation time, or combinations of these-leading to incomparable performance claims. To close …

Arid: Agglomerative Regionalization Via Information Divergence, A Novel Clustering Algorithm For Geo-Spatial Data, Joshua David Sills

Dissertations and Theses

Regionalization is a clustering problem that seeks to partition geospatial data into geographically contiguous regions while remaining internally homogeneous in their attributes. It has been successfully applied towards the development of urban planning, natural resource discovery, and ecological analysis. Existing popular approaches optimize homogeneity using Euclidean or variance-based criteria, which ignore distributional differences such as variance shifts, multimodality, and higher-order dependence. This thesis introduces ARID (Agglomerative Regionalization via Information Divergence), a spatially constrained agglomerative clustering framework that replaces distance-based merging with an information-theoretic, Ward-like criterion that utilizes the Kullback-Leibler (KL) divergence. ARID constructs a neighborhood graph from coordinate space and …

Mud Sound Speed Profile Constraints From Sub-Bottom Arrival Times, Charles W. Holland

Electrical and Computer Engineering Faculty Publications and Presentations

Arrival times of sub-bottom reflected paths together with co-located direct measurements of the angle of intromission provide narrow constraints on the sediment sound speed profile. Measurements of these two quantities at the central New England Mud Patch in March 2017 indicate that the average sound speed gradient in the upper 3m and upper 9m of mud is 6 s1. Gradients of 5 s1 and 7 s1 over the upper 9m are too small and large, respectively. Below 9m, the sandmud transition interval has a gradient of 200 s1. VC

The Risc-V Fpga (Rvfpga) Teaching Package, Daniel Chaver, Sarah Harris, Luis Pinuel, Olof Kindgren, Zubair Kakakhel, Chris Owen, Roy Kravitz, Jose I. Gomez-Perez, Fernando Castro, Katzalin Olcoz, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

RISC-V is a free and open-standard ISA based on RISC principles, allowing anyone to design, manufacture, and sell RISC-V chips and software. Its flexibility and growing ecosystem have made it popular in research, education, and industry, increasing the need for educational materials. This paper provides an in-depth description of the RVfpga course, which offers a solid introduction to computer architecture using the RISC-V instruction set and FPGA technology. It focuses on providing hands-on experience with real-world RISC-V cores, the VeeR EH1 and EL2 cores, developed by Western Digital and hosted by ChipsAlliance. The course targets students and educators in computing-related …

Research Progress On Generating Perfect Vortex Beams Based On Metasurfaces, Xiujuan Liu, Manna Gu, Ying Tian, Mingfeng Zheng, Bo Fang, Zhi Hong, Chee Leong Tan, Xufeng Jing

Electrical and Computer Engineering Faculty Publications and Presentations

This article reviews the latest advances in the generation and control of perfect vector beams using metasurfaces. In recent years, metasurfaces have garnered increasing interest due to their simple fabrication and easy integration. Perfect vortex beams (PVBs), as a type of vector beams, exhibit complex polarization states that require the superposition of multiple phases for their generation. The use of metasurfaces provides a compact platform for the generation of perfect vortex beams and enables more complex vortex beam control tasks, which are quite challenging for traditional optics. This paper begins by introducing the principle of perfect vortex beam generation using …

Estimating Sediment Properties Using A New Source Level Function For Wind-Driven Underwater Sound Derived From Long-Term Archival Data, S Bruce Martin, Martin Siderius

Electrical and Computer Engineering Faculty Publications and Presentations

Wind-driven breaking waves generate the background sound throughout the ocean. An accurate source level for wind-driven breaking waves is needed for estimating the ambient sound levels needed for sound exposure modeling, environmental assessments, and assessing the detection performance of sonars. Previous models applied a constant roll-off of sound levels at -16 dB/decade at all wind speeds, and these models' source levels were flat at frequencies below ∼1000 Hz due to a lack of measurements. Here, we analyzed 16 long-term archival datasets with limited anthropogenic sound sources to estimate the wind-driven source level down to 100 Hz. We estimated the site-specific …

Favorability Mapping For Hydrothermal Power Resource Assessments Of The Great Basin, Usa, Stanley P. Mordensky, Erick R. Burns, John Lipor, Jacob Deangelo

Electrical and Computer Engineering Faculty Publications and Presentations

Highlights

• • The new approach to predict hydrothermal resource favorability for the U.S. Great Basin is a synthesis of modern data-driven machine learning improvements from the last several years and predicts 85 % of power-producing systems with operating power plants in the most favorable 10 % of the total area with over half of the power-producing systems (10 of the 19 exposed power-producing systems and 5 of the 9 hidden power-producing systems) in the 99th percentile.
• • The new hydrothermal favorability map predicts both hidden and exposed power-producing hydrothermal systems equally well.
• • The new hydrothermal favorability map preferentially predicts …

Realization Of Deterministic Quantum Circuits For Non-Deterministic Or Incompletely Specified Quantum State Machines, Manjith Kumar, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

In classical logic design, there are machine learning methods based on converting a set of input-output traces to non-deterministic automata that are then converted to deterministic automata and synthesized using logic gates. This approach has not yet been extended to quantum automata. In this paper, we present a method to convert a set of input-output traces to a non-deterministic automaton, which is then converted to an incompletely specified multi-output Boolean function. The existing logic synthesis approaches for designing quantum circuits are insufficient to handle incompletely specified functions. So, we present a novel algorithm to synthesize logic functions with don’t cares …

Field Canals Improvement Projects Duration Prediction: A Comparative Analysis Of Machine Learning Models, Hania Ghouse, Ukaegbu Chinonso Ishmael, Edgar Dario Obando-Paredes, Hashem Shafik Shakir, Ali Al-Bayaty

Electrical and Computer Engineering Faculty Publications and Presentations

There are several essential elements in project construction management to be studied appropriately, and priority to these elements, such as cost and duration, is predominantly interesting to be investigated. In this research, the duration of field canal improvement projects (DFCIP) was predicted using two relatively new machine learning (ML) models - the Multivariate Adaptive Regression Spline (MARS) and Extreme Learning Machine (ELM). The targeted DFCIP was calculated using other dependent parameters, such as the length of the pipe, years of construction, the geographical zone of the network, the supplied area with water, and finally the actual cost of the field …

Model-Based Assessment Of Ocean Monitoring Temporal And Spatial Resolution Requirements For Acoustic Operations, William K. Stevens, Martin Siderius

Electrical and Computer Engineering Faculty Publications and Presentations

Understanding present and future ocean conditions is essential for the effective planning and execution of a wide range of naval and commercial acoustic operations. The four-dimensional structure of temperature and salinity}from the ocean surface to the seabed}is a critical factor influencing acoustic transmission properties. Modern numerical ocean modeling systems consist of three primary components: ocean observations, a numerical forecasting model, and a data assimilation system. Of the tens of millions of global ocean observations assimilated daily, the majority derive from satellite-based surface measurements. In stark contrast, subsurface water column measurements number only in the thousands per day. This disparity highlights …

Development And Validation Of A Composite Digital Balance Score For Spinocerebellar Ataxia: A Prospective Study., James Mcnames, Vrutangkumar V. Shah, Hannah L. Casey, Kristen L. Sowalsky, Mahmoud El-Gohary, Delaram Safarpour, Patricia Carlson-Kuhta, Jeremy D. Schmahmann, Liana S. Rosenthal, Susan Perlman, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Clinical trials in spinocerebellar ataxia are currently limited by the large sample sizes required by available clinical endpoints. We aimed to devise a digital composite measure of standing and walking balance using wearable inertial sensors that would require smaller sample sizes. The new score is called the Score of Integrated Balance in Ataxia (SIBA).

Calving As A Source Of Acute And Persistent Kinetic Energy To Enhance Submarine Melting Of Tidewater Glaciers, M. F. Shaya, J. D. Nash, E. C. Pettit, J. M. Amundson, R. H. Jackson, D. A. Sutherland, Dylan Winters

Electrical and Computer Engineering Faculty Publications and Presentations

Calving icebergs at tidewater glaciers release large amounts of potential energy. This energy—in principle—could be a source for submarine melting, which scales with near‐terminus water temperature and velocity. Because near‐terminus currents are challenging to observe or predict, submarine melt remains a key uncertainty in projecting tidewater glacier retreat and sea level rise. Here, we study one submarine calving event at Xeitl Sít’ (LeConte Glacier), Alaska, to explore the effect of calving on ice melt, using a suite of autonomously deployed instruments beneath, around, and downstream of the calving iceberg. Our measurements captured flows exceeding 5 m/s and demonstrate how potential …

Developing Workflows For Passive Acoustic Detection Of Bedload Transport, Quinn Morgan

Dissertations and Theses

Bedload transport is defined as the amount of sediment, including gravel and rocks, traveling down stream. Monitoring bedload transport is important for river safety, hydrological studies and conservation efforts. Existing methods of directly measuring bedload transport (or bedload flux) involve lowering a collection device into a river and measuring the sediment collected; which can be expensive and time consuming. Hydroacoustic sensors, such as hydrophones, have had success tracking bedload flux remotely. This works by measuring the relatively high frequency of sediment impacts to map onto total bedload transported. No perfected method for detection of sediment generated noise (SGN) currently exists. …

Clinic Vs. Daily Life Gait Characteristics In Patients With Spinocerebellar Ataxia, Vrutangkumar V. Shah, Daniel Muzyka, Adam Jagodinsky, Hannah Casey, James Mcnames, Mahmoud El-Gohary, Kristen Sowalsky, Delaram Safarpour, Patricia Carlson-Kuhta, Fay B. Horak, Christopher M. Gomez

Electrical and Computer Engineering Faculty Publications and Presentations

Background:

Recent findings suggest that a single gait assessment in a clinic may not reflect everyday mobility.ObjectiveWe compared gait measures that best differentiated individuals with spinocerebellar ataxia (SCA) from age-matched healthy controls (HC) during a supervised gait test in the clinic vs. a week of unsupervised gait during daily life.

Methods: Twenty-six individuals with SCA types 1, 2, 3, and 6, and 13 (HC) wore three Opal inertial sensors (on both feet and lower back) during a 2-minute walk in the clinic and for seven days in daily life. Seventeen gait measures were analyzed to investigate the group differences using …

Design And Evaluation Of An Electromagnetic Band Gap Structure For Self-Interference Reduction In Mmwave Full-Duplex Systems, Adewale Kehinde Oladeinde

Dissertations and Theses

Full-duplex (FD) wireless is a new technology that allows a device to transmit and receive at the same time and on the same frequency band. It has the potential to double the capacity and spectral efficiency of a wireless link compared to the family of conventional half-duplex wireless systems. The key challenge in implementing FD wireless communication is self-interference (SI): a node's transmitting signal generates significant interference to its receiver. Several previous studies have demonstrated the potential to reduce SI and develop FD radios; however, these studies are mostly limited to sub-6 GHz systems. Previous and on-going research explored various …

Isolation Enhancement Based On Tm010 And Te30 Mode Characteristics In A Patch Antennas Using Genetic Algorithm Optimization For Ku-Band Applications, Muddineni Raveendra, U. Saravanakumar, P. Padmaloshani, P. Saam Prasanth Dheeraj, Anand Anbalagan, R. Sreelakshmy

Electrical and Computer Engineering Faculty Publications and Presentations

This paper proposes a novel technique to enhance isolation in rectangular patch antennas by leveraging the mode characteristics of TM010 and TE30 to achieve better than −40 dB between the transmitter and receiver with dual‐polarization features. The primary innovation of this work lies in achieving significant isolation enhancement solely by combining two resonant modes with orthogonal polarizations, without incorporating any additional design elements such as parasitic components or decoupling structures. To validate the isolation enhancement based on these mode characteristics, a pair of rectangular transmitter and receiver patch antennas was designed to operate in the frequency range from 14 to …