Engineering Commons^™

Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel

Turkish Journal of Electrical Engineering and Computer Sciences

The number of people who die due to cardiovascular diseases is quite high. In our study, ECG (electrocar-diogram) signals were divided into segments and waves based on temporal boundaries. Signal similarity methods such as convolution, correlation, covariance, signal peak to noise ratio (PNRS), structural similarity index (SSIM), one of the basic statistical parameters, arithmetic mean and entropy were applied to each of these sections. In addition, a square error-based new approach was applied and the difference of the signs from the mean sign was taken and used as a feature vector. The obtained feature vectors are used in the artificial …

Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel

Theses and Dissertations

Infrastructure is a key component in the well-being of our society that leads to its growth, development, and productive operations. A well-built infrastructure allows the community to be more competitive and promotes economic advancement. In 2021, the ASCE (American Society of Civil Engineers) ranked the American infrastructure as substandard, with an overall grade of C-. The overall ranking suffers when key infrastructure categories are not maintained according to the needs of the population. Therefore, there is a need to consider alternative methods to improve our infrastructure and make it more sustainable to enhance the overall grade. One of the challenges …

Training Set Optimization In An Artificial Neural Network Constructed For High Bandwidth Interconnects Design, Bo Pu, Heegon Kim, Xiao Ding Cai, Bidyut Sen, Chunchun Sui, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

In this article, a novel training set optimization method in an artificial neural network (ANN) constructed for high bandwidth interconnects design is proposed based on rigorous probability analysis. In general, the accuracy of an ANN is enhanced by increasing training set size. However, generating large training sets is inevitably time-consuming and resource-demanding, and sometimes even impossible due to limited prototypes or measurement scenarios. Especially, when the number of channels in required design are huge such as graphics double data rate (GDDR) memory and high bandwidth memory (HBM). Therefore, optimizing the training set selection process is crucial to minimizing the training …

Grey-Taguchi Approach To Optimize Fused Deposition Modeling Process In Terms Of Mechanical Properties And Dimensional Accuracy, Md Asif Bin Syed, Qausar Rhaman, Hasan Md Shahriar, Mohammad Muhshin Aziz Khan

Graduate Student Scholarship

Fused Deposition Modeling (FDM) is a process that allows for the rapid production of functional parts through the deposition of fused material layers in a sequential manner. FDM has flexibility and the potential to create complicated parts. This study aims to optimize the FDM process parameters in terms of tensile strength, flexural strength, and longitudinal shrinkage using the Grey-Taguchi approach. The input parameters chosen to study the effects on dimension and mechanical properties are layer thickness, the raster angle, fill density, the number of contours, printing temperature, and printing speed. The Taguchi L27 orthogonal array is used as the statistical …

Optimizing Heavy Civil Internships Based On Student Interest, Nicole Nguyen

Construction Management

Many Cal Poly Construction Management students are expected to have at least one internship prior to graduating. With that being said, the construction industry has many sectors of work that one may enter. Internships are a good way for students to determine what kind of work they would like to go into whether it is commercial, heavy civil, residential, etc. The purpose of this research paper is to analyze what can be done to optimize a heavy civil internship based off student interest and experiences. Research was conducted via survey that was sent out to all Cal Poly Construction Management …

Design And Control Of Next-Generation Uavs For Effectively Interacting With Environments, Caiwu Ding

Dissertations

In this dissertation, the design and control of a novel multirotor for aerial manipulation is studied, with the aim of endowing the aerial vehicle with more degrees of freedom of motion and stability when interacting with the environments. Firstly, it presents an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. The effectiveness of this method is demonstrated through simulation. Secondly, a humanoid robot arm is adopted to serve as …

An Optimization Modeling Framework To Evaluate Civilians Response Under Active Shooter Violence Situations, Joseph G. Kerlin

Theses and Dissertations

Workplace safety is under serious threat due to the increasing trend of active shooter violence in recent years. Therefore, it becomes essential that the safety of a workplace is rigorously and, most importantly, methodologically assessed against active shooter violence. To serve this purpose, this study proposes a machine learning-optimization framework to assess the safety of a building against possible active shooter violence. First, several state-of-the-art machine learning models are employed to predict an agent’s movement decisions (with directions) under different violence scenarios. The predictions are then utilized in a mixed-integer linear programming model to maximize the agent’s utility under a …

Optimization And Analysis Of A Styrene Production Process, Alexis Kimpel

Honors Theses

The production of styrene from ethylbenzene in Unit 500 is designed to start up in 2024 and operate for 12 years after startup. The engineering team was tasked with designing the process, creating an economic model, and optimizing the net present value (NPV). The process was simulated in AVEVA PRO/II Simulation for the design process and to estimate the size of equipment. Parametric and topological optimization was performed subsequently on the unit operations in the process. The NPV was improved by $423M from a base case of -$919M to an optimized case of -$496M. The project is recommended to continue …

An Adaptive Search Equation-Based Artificial Bee Colony Algorithm For Transportation Energy Demand Forecasting, Durmuş Özdemi̇r, Safa Dörterler

Turkish Journal of Electrical Engineering and Computer Sciences

This study aimed to develop a new adaptive artificial bee colony (A-ABC) algorithm that can adaptively select an appropriate search equation to more accurately estimate transport energy demand (TED). Also, A-ABC and canonical artificial bee colony (C-ABC) algorithms were compared in terms of efficiency and performance. The input parameters used in the proposed TED model were the official economic indicators of Turkey, including gross domestic product (GDP), population, and total vehicle kilometer per year (TKM). Three mathematical models, linear (A-ABCL), exponential (A-ABCE), and quadratic (A-ABCQ) were developed and tested. Also, economic variables were generated using the "curve fitting" technique to …

Interdiction Models To Disrupt The Operations Of Sex Trafficking And Other Forced Illicit Labor Networks, Michael T. Clark

All Theses

Sex traffickers often force their victims to work in both commercial sex markets and perform other illicit activities (e.g., drug dealing, theft, and fraud). Current literature has failed to address interdiction models that aim to disrupt all components of a sex traffickers’ operation, including these other illicit activities. In this thesis, we present a interdiction problem, and its single-level linear optimization reformulation, to reduce the profit of a human trafficking network concurrently operating in the commercial sex market and other illicit activity markets. Our novel formulation aims to investigate the practical implications of interdiction decisions made to disrupt a human …

Optimal Relative Path Planning For Constrained Stochastic Space Systems, Nathan Bohus Stastny

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Rendezvous and proximity operations for automated spacecraft systems requires advanced path planning techniques that are capable of generating optimal paths. Real-world constraints, such as sensor noise and actuator errors, complicate the planning process. Operations also require flight safety considerations in order to prevent the spacecraft from potentially colliding with the associated companion spacecraft. This work proposes a new, ground-based trajectory planning approach that seeks an optimal trajectory while meeting all mission constraints and accounting for vehicle performance and safety requirements. This approach uses a closed-loop linear covariance simulation of the relative trajectory coupled with a genetic algorithm to determine fuel …

Investigations Of External Resources And The Impact Of Imaging On Patient Flow In The Emergency Department, Marisa Shehan

All Theses

The problems associated with Emergency Department (ED) crowding are numerous, varied, and complex. Though overcrowded Emergency Departments are frequently attributed to overcrowded hospitals, crowding is also impacted by bottlenecks in patient flow. While discrete-event simulation (DES) is commonly used to model ED flow, external resources are typically excluded from these models due to their complexity and the limited amount of known information for these processes. Instead, external resources such as consults, labs, and imaging are modeled using estimation and/or educated guesswork. In this study, the impact of imaging on patient flow was assessed through data analysis of specific imaging factors, …

A Numerical Optimization Study Of A Novel Electrospray Emitter Design, Joshua H. Howell

Masters Theses

The low thrust and high specific impulse of electric propulsion has been brought to the forefront for CubeSat and small spacecraft applications. Electrospray thrusters, which operate via electrostatic principles, have seen much research, development, and application in recent years. The small sizes of the spacecraft that utilize electrospray thrusters has focused development into the miniaturization of this technology to the micro-scale. Miniaturization introduces design challenges that must be addressed, including power supply mass and footprint requirements. This consequence requires investigation into the effects of design choices on the thruster onset voltage, defined as the voltage at which ion emission begins. …

Machine Learning Based Aerodynamic Shape Optimization, Noe Martinez Jr.

Theses and Dissertations

The coefficient of pressure distribution for various 2D airfoil geometries were found using source – vortex panel methods. The data obtained in these simulations was used in multiple machine learning models which would predict the airfoil geometry from a given coefficient of pressure distribution. The neural networks employed were fully connected feedforward networks with Levenberg – Marquardt backpropagation and one model employed Bayesian Regularization. A novel tool for optimizing airfoil shape for a given coefficient of pressure distribution was created which performed well during testing. These models serve as the first step in minimizing the conflict between aerodynamic and stealth …

Multi-Device Data Analysis For Fault Localization In Electrical Distribution Grids, Jacob D L Hunte

Electronic Thesis and Dissertation Repository

The work presented in this dissertation represents work which addresses some of the main challenges of fault localization methods in electrical distribution grids. The methods developed largely assume access to sophisticated data sources that may not be available and that any data sets recorded by devices are synchronized. These issues have created a barrier to the adoption of many solutions by industry. The goal of the research presented in this dissertation is to address these challenges through the development of three elements. These elements are a synchronization protocol, a fault localization technique, and a sensor placement algorithm.

The synchronization protocol …

Optimal Kanban Number: An Integrated Lean And Simulation Modelling Approach, Angassu Girma Mullisa, Walid Abdul-Kader

Mechanical, Automotive & Materials Engineering Publications

Kanban is credited as a major means to controlling the inventory within a manufacturing system. Determining the optimum number of Kanban is of great interest for manufacturing industries. To fulfill this aim, an integrated modelling approach using discrete-event simulation technique and Kanban Lean tool is developed for a pull system ensuring an optimum Kanban number. This research has developed a base-case simulation model which was statistically validated using ANOVA. Initial Kanban number obtained from the mathematical model of Toyota motor company is used to obtain initial results. A Kanban integrated simulation model is developed that employed the idea of pull …

Using Project Production Methodology To Compare Onsite Prefabrication Steel Erection To Traditional Stick-Built, Corinne R. Nalder

Construction Management

Project production management provides continuity, predictability, and optimization of a process in comparison to the traditional approach of project management. Prefabrication is an example of project production management in which there is continuity of the product, reduced variability, and where the assembly process can be altered for best results. This paper will examine the benefits of project production management and compare two methods of steel erection in which one method performs an onsite prefabrication process while the other method employs the traditional stick-built process. The two methods will be modeled by a tool that replicates a repetitive process similar to …

A New Approach To Career Field Matching For Commissioning Air Force Cadets, Daniel Griffen Laird

Theses and Dissertations

The current method of assigning graduating cadets from the United States Air Force Academy and Reserve Officers' Training Corps (ROTC) detachments to their career fields uses an integer programming model to maximize \global" Air Force utility, subject to several Air Force-defined constraints. This utility evaluates the positive benefit of assigning a certain cadet to a certain career field. This paper discusses the issues with such a model, as well as presents a new, more refined approach to the problem. Rather than provide a one-size-fits-all formulation of this particular assignment problem, a Value-Focused Thinking (VFT) framework is applied, in conjunction with …

Recent Advances Of Wind-Solar Hybrid Renewable Energy Systems For Power Generation: A Review, Pranoy Roy, Jiangbiao He, Tiefu Zhao, Yash Veer Singh

Electrical and Computer Engineering Faculty Publications

A hybrid renewable energy source (HRES) consists of two or more renewable energy sources, such as wind turbines and photovoltaic systems, utilized together to provide increased system efficiency and improved stability in energy supply to a certain degree. The objective of this study is to present a comprehensive review of wind-solar HRES from the perspectives of power architectures, mathematical modeling, power electronic converter topologies, and design optimization algorithms. Since the uncertainty of HRES can be reduced further by including an energy storage system, this paper presents several hybrid energy storage system coupling technologies, highlighting their major advantages and disadvantages. Various …

A Surrogate Assisted Quantum-Behaved Algorithm For Well Placement Optimization, Jahedul Islam, Amril Nazir, Moinul Hossain, Hitmi Khalifa Alhitmi, Muhammad Ashad Kabir, Abdul-Halim Jallad

All Works

The oil and gas industry faces difficulties in optimizing well placement problems. These problems are multimodal, non-convex, and discontinuous in nature. Various traditional and non-traditional optimization algorithms have been developed to resolve these difficulties. Nevertheless, these techniques remain trapped in local optima and provide inconsistent performance for different reservoirs. This study thereby presents a Surrogate Assisted Quantum-behaved Algorithm to obtain a better solution for the well placement optimization problem. The proposed approach utilizes different metaheuristic optimization techniques such as the Quantum-inspired Particle Swarm Optimization and the Quantum-behaved Bat Algorithm in different implementation phases. Two complex reservoirs are used to investigate …

Data-Driven Decarbonization Of Residential Heating Systems: An Equity Perspective., John Wamburu, Emma Grazier, David Irwin, Christine Crago, Prashant Shenoy

Publications

Since heating buildings using natural gas, propane and oil makes up a significant proportion of the aggregate carbon emissions every year, there is a strong interest in decarbonizing residential heating systems using new technologies such as electric heat pumps. In this poster, we conduct a data-driven optimization study to analyze the potential of replacing gas heating with electric heat pumps to reduce carbon emissions in a city-wide distribution grid. We seek to not only reduce the carbon footprint of residential heating, but also show how to do so equitably. Our results show that lower income homes have an energy usage …

Optimal Design Of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank Units And Electrolyzer Hybrid System For A Remote Area In Egypt, Hoda Abd El-Sattar, Salah Kamel, Hamdy M. Sultan, Hossam Zawbaa, Francisco Jurado

Articles

In this paper, a new isolated hybrid system is simulated and analyzed to obtain the optimal sizing and meet the electricity demand with cost improvement for servicing a small remote area with a peak load of 420 kW. The major configuration of this hybrid system is Photovoltaic (PV) modules, Biomass gasifier (BG), Electrolyzer units, Hydrogen Tank units (HT), and Fuel Cell (FC) system. A recent optimization algorithm, namely Mayfly Optimization Algorithm (MOA) is utilized to ensure that all load demand is met at the lowest energy cost (EC) and minimize the greenhouse gas (GHG) emissions of the proposed system. The …

Optimal Design Of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank Units And Electrolyzer Hybrid System For A Remote Area In Egypt, Abd El-Sattar Abd El-Sattar, Salah Kamel, Hamdy M. Sultan, Hossam Zawbaa, Francisco Jurado

Articles

In this paper, a new isolated hybrid system is simulated and analyzed to obtain the optimal sizing and meet the electricity demand with cost improvement for servicing a small remote area with a peak load of 420 kW. The major configuration of this hybrid system is Photovoltaic (PV) modules, Biomass gasifier (BG), Electrolyzer units, Hydrogen Tank units (HT), and Fuel Cell (FC) system. A recent optimization algorithm, namely Mayfly Optimization Algorithm (MOA) is utilized to ensure that all load demand is met at the lowest energy cost (EC) and minimize the greenhouse gas (GHG) emissions of the proposed system. The …

Hamiltonian-Driven Adaptive Dynamic Programming With Efficient Experience Replay, Yongliang Yang, Yongping Pan, Cheng Zhong Xu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a novel efficient experience-replay-based adaptive dynamic programming (ADP) for the optimal control problem of a class of nonlinear dynamical systems within the Hamiltonian-driven framework. The quasi-Hamiltonian is presented for the policy evaluation problem with an admissible policy. With the quasi-Hamiltonian, a novel composite critic learning mechanism is developed to combine the instantaneous data with the historical data. In addition, the pseudo-Hamiltonian is defined to deal with the performance optimization problem. Based on the pseudo-Hamiltonian, the conventional Hamilton–Jacobi–Bellman (HJB) equation can be represented in a filtered form, which can be implemented online. Theoretical analysis is investigated in terms …

Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk

VMASC Publications

Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about …

Distributed Wireless Sensor Node Localization Based On Penguin Searchoptimization, Md Al Shayokh, Soo Young Shin

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor networks (WSNs) have become popular for sensing areas-of-interest and performing assigned tasks based on information on the location of sensor devices. Localization in WSNs is aimed at designating distinct geographical information to the inordinate nodes within a search area. Biologically inspired algorithms are being applied extensively in WSN localization to determine inordinate nodes more precisely while consuming minimal computation time. An optimization algorithm belonging to the metaheuristic class and named penguin search optimization (PeSOA) is presented in this paper. It utilizes the hunting approaches in a collaborative manner to determine the inordinate nodes within an area of interest. …

Evaluating The Performance Impact Of Fine-Tuning Optimization Strategies On Pre-Trained Distilbert Models Towards Hate Speech Detection In Social Media, Aidan Mcgovern

Dissertations

Hate speech can be defined as forms of expression that incite hatred or encourage violence towards a person or group based on race, religion, gender, or sexual orientation. Hate speech has gravitated towards social media as its primary platform, and its propagation represents profound risks to both the mental well-being and physical safety of targeted groups. Countermeasures to moderate hate speech face challenges due to the volumes of data generated in social media, leading companies, and the research community to evaluate methods to automate its detection. The emergence of BERT and other pre-trained transformer-based models for transfer learning in the …

Particle Swarm Optimization For Critical Experiment Design, Cole Michael Kostelac

Masters Theses

“Critical experiments are used by nuclear data evaluators and criticality safety engineers to validate nuclear data and computational methods. Many of these experiments are designed to maximize the sensitivity to a certain nuclide-reaction pair in an energy range of interest. Traditionally, a parameter sweep is conducted over a set of experimental variables to find a configuration that is critical and maximally sensitive. As additional variables are added, the total number of configurations increases exponentially and quickly becomes prohibitively computationally expensive to calculate, especially using Monte Carlo methods.

This work presents the development of a particle swarm optimization algorithm to design …

Using Computational Methods To Optimize High Heat Flux Component Thermal Performance In Magnetic Confinement Fusion Reactor Research, Monica Gehrig

Doctoral Dissertations

"Heat transfer enhancement by means of internally modified geometries in tubes and channels is an important mechanism to improve the survivability of components in extreme high-heat flux environments. Various features such as ribs and fins are studied using computational fluid dynamics in both uniform and one-sided heating in tubes and rectangular channels respectively to determine the most effective geometries across a variety of different flow and heating conditions. This work examines heat transfer enhancement and rib geometry optimization to support experimental research for nuclear fusion applications. The project begins by designing and analyzing test sections supporting a helium flow loop …

Extraction Of Melanin From Black Knot Fungus: Optimization And Applications, Amara Davis

Williams Honors College, Honors Research Projects

The goal of this research project was to optimize the extraction of melanin from black knot fungus and to analyze possible applications of the extracted melanin. An extraction method that was previously created was examined for possible improvements. Improvements that were studied include the elimination of steps in the extraction process while obtaining the same quality of product, examining options for machinery that could be used to increase production rate when moved to a production plant setting, and optimize the concentrations of the raw materials that are used in the extraction for possible reduction of cost without compromising yield or …