Engineering Commons^™

Quantum Computing And Its Applications In Healthcare, Vu Giang

OUR Journal: ODU Undergraduate Research Journal

This paper serves as a review of the state of quantum computing and its application in healthcare. The various avenues for how quantum computing can be applied to healthcare is discussed here along with the conversation about the limitations of the technology. With more and more efforts put into the development of these computers, its future is promising with the endeavors of furthering healthcare and various other industries.

Optimizing Technical And Economic Aspects Of Off-Grid Hybrid Renewable Systems: A Case Study Of Manoka Island, Cameroon, Reagan J. J. Molu, Serge R. D. Naoussi, Patrice Wira, Wulfran F. Mbasso, Saatong T. Kenfack, Barun K. Das, Enas Ali, Muhannad J. Alshareef, Sherif S. M. Ghoneim

Research outputs 2022 to 2026

The lack of accessible and reliable electrical energy in Cameroon has become a pervasive obstacle to the nation's progress, with energy availability, quality, and cost identified as key hindrances to development over the past 15 years. Conventional solutions that rely on combustion engines and electrochemical storage systems have proven to be cost-prohibitive, limited in power output, and constrained in capacity. The dependence on traditional diesel generators has perpetuated maintenance challenges and a continuous demand for fuel supply, while the accompanying noise and pollution have restricted their use in residential areas. Recognizing the imperative of reducing dependence on fossil fuels and …

Multiple Uav-Lidar Placement Optimization Under Road Priority And Resolution Requirements, Zachary Osterwisch, Omar Rinchi, Ahmad Alsharoa, Hakim Ghazzai, Yehia Massoud

Electrical and Computer Engineering Faculty Research & Creative Works

An unmanned aerial vehicle (UAV) integrated with the remote sensing technology of light detection and ranging (LiDAR) can provide accurate and real-time road traffic information. In this paper, we propose to equip UAVs with LiDAR sensors for Intelligent Transportation Systems (ITS) applications. The goal is to find the optimal 3D placement of multiple UAV-LiDAR (ULiDs) for a given road segmentation. We formulate an optimization problem to find the optimal placement such that the road coverage efficiency is maximized. The optimization problem is constrained by notable ULiD specifications such as field-of-view (FoV), point-cloud density, geographic information system (GIS) location, and road …

Initial Procedure For Small-Scale Extraction Of Subsurface Martian Ice, Evan Steers

Electronic Theses and Dissertations

For decades, NASA has been surveying the surface of Mars with plans for human exploration. Due to recent advancements, there is strong evidence to believe that frozen aquifers beneath the Martian surface hold great amounts of usable H2O. Since the discovery of water on Mars, NASA has expressed key interest in harvesting this valuable resource. The presence of usable H2O on Mars could reduce the launching mass of future missions by giving astronauts the capability to harvest water once they have landed on Mars. This research focuses on the optimization of a current design to extract Martian water and the …

Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.

Peer-To-Peer Energy Trading In Smart Residential Environment With User Behavioral Modeling, Ashutosh Timilsina

Theses and Dissertations--Computer Science

Electric power systems are transforming from a centralized unidirectional market to a decentralized open market. With this shift, the end-users have the possibility to actively participate in local energy exchanges, with or without the involvement of the main grid. Rapidly reducing prices for Renewable Energy Technologies (RETs), supported by their ease of installation and operation, with the facilitation of Electric Vehicles (EV) and Smart Grid (SG) technologies to make bidirectional flow of energy possible, has contributed to this changing landscape in the distribution side of the traditional power grid.

Trading energy among users in a decentralized fashion has been referred …

Optimal Design Of Special High Torque Density Electric Machines Based On Electromagnetic Fea, Murat G. Kesgin

Theses and Dissertations--Electrical and Computer Engineering

Electric machines with high torque density are essential for many low-speed direct-drive systems, such as wind turbines, electric vehicles, and industrial automation. Permanent magnet (PM) machines that incorporate a magnetic gearing effect are particularly useful for these applications due to their potential for achieving extremely high torque density. However, when the number of rotor polarities is increased, there is a corresponding need to increase the number of stator slots and coils proportionally. This can result in manufacturing challenges. A new topology of an axial-flux vernier-type machine of MAGNUS type has been presented to address the mentioned limitation. These machines can …

Ai-Driven Security Constrained Unit Commitment Using Predictive Modeling And Eigen Decomposition, Talha Iqbal

Graduate Theses, Dissertations, and Problem Reports (ETD)

Security Constrained Unit Commitment (SC-UC) is a complex large scale mix integer constrained optimization problem solved by Independent System Operators (ISOs) in the daily planning of the electricity markets. After receiving offers and bids, ISOs have only few hours to clear the day-ahead electricity market. It requires a lot of computational effort and a reasonable time to solve a large-scale SC-UC problem. However, exploiting the fact that a UC problem is solved several times a day with only minor changes in the system data, the computational effort can be reduced by learning from the historical data and identifying the patterns …

Improving Safety Service Patrol Performance, Mecit Cetin, Hong Yang, Kun Xie, Sherif Ishak, Guocong Zhai, Junqing Wang, Giridhar Kattepogu

Civil & Environmental Engineering Faculty Publications

Safety Service Patrols (SSPs) provide motorists with assistance free of charge on most freeways and some key primary roads in Virginia. This research project is focused on developing a tool to help the Virginia Department of Transportation (VDOT) optimize SSP routes and schedules (hereafter called SSP-OPT). The computational tool, SSP-OPT, takes readily available data (e.g., corridor and segment lengths, turnaround points, average annual daily traffic) and outputs potential SSP configurations that meet the desired criteria and produce the best possible performance metrics for a given corridor. At a high level, the main components of the developed tool include capabilities to: …

Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Presents a New Optimization Method for Complex Power Distribution Networks (PDNs) with Irregular Shapes and Multilayer Structures using Deep Reinforcement Learning (DRL), Which Has Not Been Considered Before. a Fast Boundary Integration Method is Applied to Compute the Impedance Matrix of a PDN Structure. Subsequently, a New DRL Algorithm based on Proximal Policy Optimization (PPO) is Proposed to Optimize the Decoupling Capacitor (Decap) Placement by Minimizing the Number of Decaps While Satisfying the Desired Target Impedance. in the Proposed Approach, the PDN Structure Information is Encoded into Matrices and Serves as the Input of the DRL Algorithm, Which …

Sparsity For Gradient-Based Optimization Of Wind Farm Layouts, Benjamin T. Varela, Andrew Ning

Faculty Publications

Optimizing wind farm layouts is an important step in designing an efficient wind farm. Optimizing wind farm layouts is also a difficult task due to computation times increasing with the number of turbines present in the farm. The most computationally expensive part of gradient- based optimization is calculating the gradient. In order to reduce the expense of gradient calculation, we performed a study on the use of sparsity in wind farm layout optimization. This paper presents the findings of the sparsity study and provides a method to use sparsity in wind farm layout optimization. We tested this sparsity method by …

Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani

Graduate Theses, Dissertations, and Problem Reports (ETD)

The increasing significance of renewable energy sources is thrusting the load cycling of fossil-fueled power plants (FFPP), designed to operate under nominal-load conditions. Integration of energy storage systems (ESS) with the FFPPs such as hydrogen energy storage (HES) and mechanical energy storage facility such as compressed air energy storage (CAES) shows the potential to minimize the levelized cost of electricity during high demand scenarios and also minimize the negative impacts of off-design FFPP operation. The deployment of energy storage facilities at the FFPP level have considerable potential advantages as they can be exploited within the existing equipment items and facilities …

Hydraulic Fracturing Treatment Optimization Using Machine Learning, Abdullah Johar

Graduate Theses, Dissertations, and Problem Reports (ETD)

Friction reducers are chemicals used in hydraulic fracturing to reduce friction between fracturing fluid and the wellbore walls, helping to overcome tubular drag at high flow rates. High viscosity friction reducers are increasingly used due to operational and economic benefits, but their optimal concentration for each stage of fracturing is not well studied. As a result, oil and gas companies often use more friction reducers than necessary to ensure designed injection rates are achieved and to avoid screening out, resulting in excess use of FR and economic losses. The primary goal of this Thesis is to fully comprehend and quantify …

Optimal Design And Operation Of Integrated Hydrogen Generation And Utilization Plants, Ijiwole Solomon Ijiyinka

Graduate Theses, Dissertations, and Problem Reports (ETD)

There are considerable efforts worldwide for reducing the use of fossil fuel for energy production. While renewable energy sources are being increasingly used, fossil fuel still contribute about 80% of the energy used worldwide. As a result, the level of CO₂ is still increasing fast in the atmosphere currently exceeding about 410 parts per million (ppm). For reducing CO₂ build up in the atmosphere, various approaches are being investigated. For the electric power generation sector, two key approaches are post-combustion CO₂ capture and use of hydrogen as a fuel for power generation. These two solutions can also …

Modular Supply Network Optimization Of Renewable Ammonia And Methanol Co-Production, Benjamin Akoh

Graduate Theses, Dissertations, and Problem Reports (ETD)

To reduce the use of fossil fuels and other carbonaceous fuels, renewable energy sources such as solar, wind, geothermal energy have been suggested to be promising alternative energy that guarantee sustainable and clean environment. However, the availability of renewable energy has been limited due to its dependence on weather and geographical location. This challenge is intended to be solved by the utilization of the renewable energy in the production of chemical energy carriers. Hydrogen has been proposed as a potential renewable energy carrier, however, its chemical instability and high liquefaction energy makes researchers seek for other alternative energy carriers. Ammonia …

Low-Fidelity Design Optimization And Parameter Sensitivity Analysis Of Tilt-Rotor Evtol Electric Propulsion Systems, Tyler Critchfield, Andrew Ning

Faculty Publications

Urban air mobility requires a multidisciplinary approach to tackle the important chal- lenges facing the design of these aircraft. This work uses low-to-mid fidelity tools to model rotor aerodynamics, blade structures, vehicle aerodynamics, and electric propulsion for a tilt-rotor electric vertical takeoff and landing (eVTOL) aircraft. We use gradient-based design optimization and extensive parameter sensitivity analysis to explore the design space and complex tradeoffs of tilt-rotor distributed electric propulsion systems.

Tutorial - Shodhguru Labs: Optimization And Hyperparameter Tuning For Neural Networks, Kaushik Roy

Publications

Neural networks have emerged as a powerful and versatile class of machine learning models, revolutionizing various fields with their ability to learn complex patterns and make accurate predictions. The performance of neural networks depends significantly on the appropriate choice of hyperparameters, which are critical factors governing their architecture, regularization, and optimization techniques. As the demand for high-performance neural networks grows across diverse applications, the need for efficient optimization and hyperparameter tuning methods becomes paramount. This paper presents a comprehensive exploration of optimization strategies and hyperparameter tuning techniques for neural networks. Neural networks have emerged as a powerful and versatile class …

Parametric Structural Optimization Of A Wheel Using The Flex Representation Method, Gregory John Vernon

Theses and Dissertations

The use of the finite element method within an optimization workflow is fraught with challenges that limit the automation of such workflows. These challenges are inherent to the traditional finite element formulations which are heavily dependent on a manual meshing process that introduces variability that is challenging to account for within an automated workflow. The recently developed flex representation method (FRM) provides a salient solution to the manual meshing process without sacrificing solution accuracy. In response to the development of FRM a global automotive company requested a study to explore the applicability of FRM to one of their sizing-optimization problems: …

Applying Hls To Fpga Data Preprocessing In The Advanced Particle-Astrophysics Telescope, Meagan Konst

McKelvey School of Engineering Graduate Student Theses & Dissertations

The Advanced Particle-astrophysics Telescope (APT) and its preliminary iteration the Antarctic Demonstrator for APT (ADAPT) are highly collaborative projects that seek to capture gamma-ray emissions. Along with dark matter and ultra-heavy cosmic ray nuclei measurements, APT will provide sub-degree localization and polarization measurements for gamma-ray transients. This will allow for devices on Earth to point to the direction from which the gamma-ray transients originated in order to collect additional data. The data collection process is as follows. A scintillation occurs and is detected by the wavelength-shifting fibers. This signal is then read by an ASIC and stored in an ADC …

Cooperative Wide Area Search Algorithm Analysis Using Sub-Region Techniques, Shawn Whitney

Theses and Dissertations

Recent advances in small Unmmaned Aerial Vehicle (UAV) technology reinvigorates the need for additional research into Wide Area Search (WAS) algorithms for civilian and military applications. But due to the extremely large variability in UAV environments and design, Digital Engineering (DE) is utilized to reduce the time, cost, and energy required to advance this technology. DE also allows rapid design and evaluation of autonomous systems which utilize and support WAS algorithms. Modern WAS algorithms can be broadly classified into decision-based algorithms, statistical algorithms, and Artificial Intelligence (AI)/Machine Learning (ML) algorithms. This research continues on the work by Hatzinger and Gertsman …

Multiple Objective Function Optimization And Trade Space Analysis, Yifan Xu

All Theses

Optimization can assist in obtaining the best possible solution to a design problem by varying related variables under given constraints. It can be applied in many practical applications, including engineering, during the design process. The design time can be further reduced by the application of automated optimization methods. Since the required resource and desired benefit can be translated to a function of variables, optimization can be viewed as the process of finding the variable values to reach the function maxima or minima. A Multiple Objective Optimization (MOO) problem is when there is more than one desired function that needs to …

Analyzing The Supply Chain Operation Of A Fast-Food Restaurant Using Simulation Modeling And Developing A Cost Estimation Optimization Model In The Disruption Period, Amit Kumar Saha

Open Access Theses & Dissertations

Supply chain operation performance is a much-discussed topic over the last decade which will lead to optimizing the resources required to provide the necessary level of customer service to a specific segment and improve customer service through increased product availability and reduced order cycle time. During disruption in supply chain, performance parameter changes, and the overall supply chain cost at each stage increases. External factors such as labor shortages, delayed and costly supplies, and decreased demand also contribute to this cost. This thesis work presents a research-focused analysis of a small pizza shop, under circumstances that include the loss of …

Hybrid Machine Learning And Physics-Based Modeling Approaches For Process Control And Optimization, Junho Park

Theses and Dissertations

Transformer neural networks have made a significant impact on natural language processing. The Transformer network self-attention mechanism effectively addresses the vanishing gradient problem that limits a network learning capability, especially when the time series gets longer or the size of the network gets deeper. This dissertation examines the usage of the Transformer model for time-series forecasting and customizes it for a simultaneous multistep-ahead prediction model in a surrogate model predictive control (MPC) application. The proposed method demonstrates enhanced control performance and computation efficiency compared to the Long-short term memory (LSTM)-based MPC and one-step-ahead prediction model structures for both LSTM and …

An Application Of Optimized Bistable Laminates As A Low Velocity, Low Impact Mechanical Deterrent, Graham Lancaster

All Theses

This research considers the problem of using bistable laminates as a mechanical deterrent to the impending impact of a particle. The structure will be controlled through an algorithm that will utilize piezoelectric devices to activate them in unison with the bistable laminate to successfully deter. A novel experimental setup will be constructed to ensure that the bistable laminate stays fixed when acting as a mechanical deterrent. Piezoelectricity is the main driving force of the bistable laminate to morph and this study will use a Macro Fiber Composite (MFC) actuator that contains piezoelectric ceramic rods in a patch to transfer electrical …

Mitigating Popularity Bias In Recommendation With Unbalanced Interactions: A Gradient Perspective, Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu

Research Collection School Of Computing and Information Systems

Recommender systems learn from historical user-item interactions to identify preferred items for target users. These observed interactions are usually unbalanced following a long-tailed distribution. Such long-tailed data lead to popularity bias to recommend popular but not personalized items to users. We present a gradient perspective to understand two negative impacts of popularity bias in recommendation model optimization: (i) the gradient direction of popular item embeddings is closer to that of positive interactions, and (ii) the magnitude of positive gradient for popular items are much greater than that of unpopular items. To address these issues, we propose a simple yet efficient …

Essays On Perioperative Services Problems In Healthcare, Amogh S. Bhosekar

All Dissertations

One of the critical challenges in healthcare operations management is to efficiently utilize the expensive resources needed while maintaining the quality of care provided. Simulation and optimization methods can be effectively used to provide better healthcare services. This can be achieved by developing models to minimize patient waiting times, minimize healthcare supply chain and logistics costs, and maximize access. In this proposal, we study some of the important problems in healthcare operations management. More specifically, we focus on perioperative services and study scheduling of operating rooms (ORs) and management of necessary resources such as staff, equipment, and surgical instruments. We …

Advancing Statistical Learning And Decision Modeling Using Irregularly-Sampled Multivariate Data For Managing Respiratory Diseases, Maryam Alimohammadi

Graduate Theses and Dissertations

Complex healthcare systems require efficient and effective data-driven decision making in various aspects. As patient data becomes more available, advanced statistical learning and machine learning techniques are applied to improve data-driven decision making. However, patient health data, including clinical trial data, medical records, and electronic health records, are associated with several challenges. Patient health data includes medical information of a patient that may includedemographics, information relating to their health or illness, medications and treatments, etc. They are a combination of static and time series variables, with many censoring and missingness in the data, and are irregularly sampled in most cases. …

Multi-Fidelity Predictions For Control Allocation On The Nasa Ikhana Research Aircraft To Minimize Drag, Justice T. Schoenfeld

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Optimal control settings (camber scheduling) can be used by aircraft to minimize drag at various operating conditions during flight. In this work, camber schedules for minimum drag on the NASA Ikhana are obtained over a range of lift coefficients. A modern numerical lifting-line algorithm is used to predict the lift and drag of the aircraft as a function of operating condition and wing section shape (airfoil camber). The SLSQP optimization algorithm is used to solve for the camber schedule that minimizes drag for a given operating condition. The process is repeated, varying the number of control sections to evaluate the …

Information Dissemination And Perpetual Network, Harshit Srivastava

USF Tampa Graduate Theses and Dissertations

Social networks have attracted increasing attention from both physical and social scientists. Social networks are essential elements in societies, serving as channels for exchanging various benefits, such as innovation, information, and social support. Moreover, research in social networks helps explain macro-level social phenomena, such as social polarization and social contagion. An understanding of social networks has significant implications, such as improving social welfare and political participation. Modeling social network formation has typically employed game theory or agent-based modeling. These studies typically propose simple and tractable micro-level rules for link formation mechanisms and show that these rules have implications for known …

Aeroacoustic Analyses For Noise Reduction Application, Mahmoud M. Abdalmola

Mechanical Engineering Theses

In this study, we examine the hypothesis that airflow noise can be reduced by adding metamaterials. The introduction of any obstacle will generate more disturbance in the airflow and therefore add noise. Hence an efficient metamaterial design is required, capable of reducing noise even at higher flow disturbance. In order to examine this hypothesis, we developed a platform to perform isogeometric aeroacoustic analyses to solve Navier stokes equations first. We obtained the velocity fields from fluid-structure analyses and utilized the light-hill analogy to calculate the noise generated as a result of airflow. Then the Helmholtz equation was solved to perform …