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Full-Text Articles in Entire DC Network
White Light Specular Reflection Data Augmentation For Polyp Detection, Jose Angel Nunez
White Light Specular Reflection Data Augmentation For Polyp Detection, Jose Angel Nunez
Theses and Dissertations
Colorectal cancer is among the deadliest cancers, but fortunately, this type of cancer can be prevented. The best current method of prevention is via detecting the bad polyps in the colon in time. Furthermore, the best method we have available to detect these bad polyps is through colonoscopies. Even though a lot of lives have been saved via these methods, it is still not perfect because of human error. Integrating artificial intelligence into colonoscopy procedures is our next evolution in increasing our prevention of colorectal cancer. Polyp detectors are one of the tools brought by advancements in technology that may …
Comparative Analysis Of Transfer Learning Strategies For Polyp Detection In Colonoscopy Images Using Yolov8, Fabian Vazquez Jr.
Comparative Analysis Of Transfer Learning Strategies For Polyp Detection In Colonoscopy Images Using Yolov8, Fabian Vazquez Jr.
Theses and Dissertations
The early detection of polyps during colonoscopy procedures is crucial for preventing colorectal cancer, a leading cause of cancer-related deaths globally. Traditional methods for polyp detection are often time-consuming and prone to human error. This thesis investigates the effectiveness of transfer learning, the process of taking a pre-trained model that was trained on a large dataset and adapting it to a new, but related task, requiring less data and time for training. This research compares whether the YOLOv8 model trained from scratch on a specific polyp dataset is outperformed by transfer learning methods such as utilizing a pretrained model on …
Unveiling Eureka Math: A Critical Peek Behind The Curricular Curtain, Jennifer L. Goldin-Weeks
Unveiling Eureka Math: A Critical Peek Behind The Curricular Curtain, Jennifer L. Goldin-Weeks
Theses and Dissertations
While contemporary mathematics education literature argues that curricular resources, such as textbooks, play a significant role guiding mathematics teachers in what and how they teach, it also shows that these resources often do not do what they say they will do, nor adhere to the standards they claim to further. When it comes to the most utilized mathematics curricular resource in the United States, Eureka Math, there is a lack of scholarly literature investigating these types of claims made by the publisher. This study aimed to explore how the Eureka Math curricular resources are positioned within the context of the …
The Development And Analysis Of Practical Decision Support Tool Implementations: Case Studies From Small Business To Large Government Enterprise, Alexis Andaverde
The Development And Analysis Of Practical Decision Support Tool Implementations: Case Studies From Small Business To Large Government Enterprise, Alexis Andaverde
Theses and Dissertations
This thesis demonstrates the critical role of decision support tools (DSTs) in both small business and large government operations, enhancing decision-making, operational efficiency, and economic benefits. By implementing Excel-based systems for small businesses and discrete event modelling for large enterprises, this research highlights the importance of adaptable and scalable solutions across various sectors. According to the U.S. Small Business Association, small businesses with 500 or fewer employees make up 99.9% of all U.S. businesses. However, 65% of new businesses fail within the first ten years, according to the Bureau of Labor Statistics. This case study focuses on the used vehicle …
Missing Data Imputation With Longitudinal Data, Joseph Omar Alanis
Missing Data Imputation With Longitudinal Data, Joseph Omar Alanis
Theses and Dissertations
In the repeated measures longitudinal datasets where missing data is a relatively common issue, we explored different imputation methods, including machine learning (ML) methods in order to examine potential efficiencies for using traditional versus newer computational methods. In order to accomplish said comparison, we used a Monte Carlo simulation experiment of a population of size N=70000 to mimic a clinical trial, with different scenarios of missing at random (MAR) data in the response variable. To compare the behavior of each method resulting from the difference between population and sample dataset, a real dataset was used from the Boston College on …
Recognizing Triangles Using Weighted Ehrhart Polynomials, Rafael Sarabia
Recognizing Triangles Using Weighted Ehrhart Polynomials, Rafael Sarabia
Theses and Dissertations
Ehrhart theory is a classical topic for polygons or polytopes with vertices with integer coordinates. One of the main results of the theory claims that for every convex polygon P with integer vertices, the number of integer points in its nth dilation is a polynomial in n, the Ehrhart polynomial of P. This property can be extended if for a polynomial weight w(x, y), we sum values of w(x, y) over all points with integer coordinates in the nth dilation of P. The resulted polynomial is called the weighted Ehrhart polynomial of P associated with the weight w. In this …
Development Of The Structure And Control System Of A Stewart Platform Robot For Human Balance Recovery Interventions, Rhobenn R. Alvarez Zambrano
Development Of The Structure And Control System Of A Stewart Platform Robot For Human Balance Recovery Interventions, Rhobenn R. Alvarez Zambrano
Theses and Dissertations
In this thesis, the process to design a Stewart platform parallel robot for balance recovery with given assembly constraints and mobility requirements is described. A Model Based Design (MBD) approach in MATLAB was used as a tool to model and optimize the design of the platform through quick and repeatable workspace and movements simulations. An algorithm based on Inverse Kinematics was used to find the most adequate Stewart platform configuration which yields a workspace that fulfills the design goals best. Solidworks was used as a 3D CAD Modeling tool to elaborate machining blueprints while ensuring that each piece fits accurately …
Evaluating Feature Selection Methods In Machine Learning With Class Imbalance, Martha Asare
Evaluating Feature Selection Methods In Machine Learning With Class Imbalance, Martha Asare
Theses and Dissertations
Class imbalance is a common issue in various real-world machine learning applications such as medical diagnosis and fraud detection, where one class significantly predominates over the other(s). Conventional methods often lead to biased models that favor the majority class, which can negatively impact the performance of the minority class. To address this issue, techniques like Synthetic Minority Oversampling Technique (SMOTE), Adaptive Synthetic Sampling (ADASYN), and NearMiss have been employed to adjust the class distribution. However, these techniques may not effectively capture the nuances when the feature space is noisy, irrelevant, or high-dimensional. This thesis presents a novel approach that combines …
Rabi Oscillations And Entanglement Between Two Rydberg Atoms In An Optical Cavity Studied By The Jaynes-Cummings Model And Quantum Circuits On Qiskit, Francisco D. Santillan
Rabi Oscillations And Entanglement Between Two Rydberg Atoms In An Optical Cavity Studied By The Jaynes-Cummings Model And Quantum Circuits On Qiskit, Francisco D. Santillan
Theses and Dissertations
Rydberg atoms are highly excited atoms in which one electron has a large principal quantum number. Due to their unusual atomic properties, Rydberg atoms are promising building blocks of two-qubit gates and light-atom quantum interfaces in quantum information processing. For two atoms at close distance (< 10 mm) the Rydberg blockade prevents the two atoms to be simultaneously in the excited state whereas this blockade is absent for atoms far apart. Recently, this effect was used to engineer a quantum processor based on two-dimensional arrays of neutral atoms which are trapped and transported by optical tweezers. Motivated by these experiments, we study the light-atom interaction and entanglement of two Rydberg atoms interacting by the Rydberg blockade in an optical cavity using the Jaynes-Cummings model. We find a rich variety of Rabi oscillations and entanglement as a function of initial conditions and interaction time, which may be used to generate two-qubit gates. Furthermore, we develop and simulate a quantum circuit of this system using Qiskit, an open-source software development kit designed to emulate the operation of a real Quantum Computer.
Density Functional Theory Calculations On Electronic And Optical Properties Of Mos2/Metal Heterojunction, Mos2/Graphene/Metal Vertical Heterostructure Interfaces And Sulfur Vacancies On Mos2/Au, Shishir Timilsena
Theses and Dissertations
In this study, we conducted a comprehensive investigation on computational simulations and analyses of heterostructures formed by two-dimensional (2D) molybdenum disulfide (MoS2) and graphene (Gr) on various metal coated substrates, including gold (Au), copper (Cu), nickel (Ni), and platinum (Pt). The frequency-dependent dielectric function (ɛ(ω)), refractive index (n), and reflectivity (R) are determined using light polarization parallel and perpendicular to the c axis of the 2D layers. Our findings reveal that MoS2/Au, MoS2/Cu, and MoS2/Pt heterostructures exhibit a direct bandgap at the K-point of the Brillouin zone, whereas their corresponding MoS2/MoS2/Metal structures present an indirect bandgap. The reduced interlayer spacing …
Vessel Delay Detection And Pattern Mining From Ais Data, Naznin Ara
Vessel Delay Detection And Pattern Mining From Ais Data, Naznin Ara
Theses and Dissertations
The maritime industry relies on the Automated Identification System (AIS) for real-time vessel tracking and navigation. This thesis focuses on detecting vessel delays and mining delay patterns from AIS data, which are crucial for improving shipping schedules, port operations, and global trade logistics. The research begins with rigorous data preprocessing, including noise reduction, data interpolation, and anomaly detection, to ensure high-quality AIS data as well as focuses on detecting vessel delays and mining delay patterns from AIS data to enhance maritime operations. Advanced machine learning models analyze temporal and spatial features to detect delays, considering vessel type, speed, and route. …
Thermodynamic Feasibility Of Potential Nano-Energetic Systems Based On Metal Oxynitrides, Manoj Chhetri
Thermodynamic Feasibility Of Potential Nano-Energetic Systems Based On Metal Oxynitrides, Manoj Chhetri
Theses and Dissertations
A computational study was undertaken with the objective of identifying the nano-energetic systems containing aluminum as fuel and metal oxynitrides as oxidizer, aiming to achieve an exothermic reaction characterized by the maximum values of gas generation, adiabatic combustion temperature, and energy release. For the thermodynamic calculation, nine systems based on metal oxynitrides were taken using the THERMO software that works based on the Gibbs free energy minimization, together with HSC Chemistry 7 to calculate the thermodynamic equilibrium concentrations of reactants and products corresponding gas generation, temperature and energy release by varying the fuel to oxidizer ratio. Among all the chosen …
Benchmarking Machine Learning Algorithms For The Prediction Of Gas Adsorption In Metal-Organic Framework Materials, Juan G. Benitez
Benchmarking Machine Learning Algorithms For The Prediction Of Gas Adsorption In Metal-Organic Framework Materials, Juan G. Benitez
Theses and Dissertations
Metal-organic frameworks (MOFs) are nanoporous materials with a structure and chemistry that can be tailored with precision to support a variety of applications, such as gas storage, drug delivery, catalysis, and sensing. Central to the realization of these applications is the need to model adsorption in MOFs. However, if the goal is to screen a large number of the hundreds of thousands of MOFs discovered, conventional high-throughput molecular simulations are prohibitively demanding in terms of computational resources. Therefore, efficient approaches are required to efficiently identify suitable MOFs for specific applications. In our work, machine learning (ML) models to predict adsorption …
La1-Xsrxcoo3 Perovskite: Antimicrobial Properties And Pvdf Based Piezoelectric Nanogenerator For Energy Storage Through Self-Induced Polling, S M. Anyet Ullah Shohag
La1-Xsrxcoo3 Perovskite: Antimicrobial Properties And Pvdf Based Piezoelectric Nanogenerator For Energy Storage Through Self-Induced Polling, S M. Anyet Ullah Shohag
Theses and Dissertations
Piezoelectric Nanogenerators (PENGs), which can produce electrical energy from mechanical energy via ferroelectric effect, are one of the ambient sources of green energy. PENGs have gathered a huge attention due to cost-effectiveness, mechanical stability, and easy installation process. In this experiment, different weight percent of Sr2+ doped Lanthanum Cobaltite (La1- XSrXCoO3) perovskite, a ferroelectric material, was synthesizes by using a simple combination of sol-gel and molten-salt process and then characterization by X-ray diffraction, and scanning electron microscopy ensures the uniform morphology of nano cubes. Poly (vinylidene difluoride) (PVDF), N,N-dimethylformamide and acetone solution were used to make a flexible film using …
Exploratory Analysis In Rio Grande Valley Real Estate Development, Mathew C. Sosa
Exploratory Analysis In Rio Grande Valley Real Estate Development, Mathew C. Sosa
Theses and Dissertations
The aim of this thesis is to apply exploratory data analysis and machine learning (ML) to answer critical questions in real estate development within the Rio Grande Valley (RGV). The real estate development sector is highly dynamic and relies on multiple integrated systems and planning to bring new homes to the market. Customer Relationship Management (CRM) software and real estate listing services, such as Redfin, are utilized to manage the customer lifecycle and analyze the local market, respectively. Two of the most crucial aspects of the customer lifecycle are the first home tour and deal closing. This paper explores the …
Redefining Spaces Of Resistance Against Capitalism And Patriarchy: A Study Of Females In Society And The Family As Presented By Mrs. Warren’S Profession (1893) By Bernard Shaw And A Raisin In The Sun (1959) By Lorraine Hansberry, Jennifer L. Gonzalez
Theses and Dissertations
These plays show how conflicts concerning race, gender, and class stem from economic distress, racial discrimination, and patriarchal oppression. Within such intersections lie distinct realities of capitalism which simultaneously upholds patriarchal ideals that can only be best understood through a Marxist-Feminist lens. This thesis pays attention to how racism and discrimination functions to isolate certain groups of people from reaching social mobility. The first chapter analyzes Mrs. Warren’s Profession to demonstrate how Mrs. Warren decision to enter into prostitution cannot simply be reduced to a question of morality, but rather a question of society’s conditions that place women into certain …
Temperature-Dependent Optical Constants Of Vanadium Dioxide Thin Films Deposited On Polar Dielectrics, Imtiaz Ahmad, Satya R. Kachiraju, Sundar Kunwar, Zachary M. Brown, Pinku Roy, Matthew Gaddy, Vladimir Kuryatkov, Yejin Kwon, Ayrton A. Bernussi, Myoung-Hwan Kim
Temperature-Dependent Optical Constants Of Vanadium Dioxide Thin Films Deposited On Polar Dielectrics, Imtiaz Ahmad, Satya R. Kachiraju, Sundar Kunwar, Zachary M. Brown, Pinku Roy, Matthew Gaddy, Vladimir Kuryatkov, Yejin Kwon, Ayrton A. Bernussi, Myoung-Hwan Kim
Physics & Astronomy Faculty Publications
Coating polar dielectrics with thin film vanadium dioxide (VO2) enables one to exploit the temperature-dependent phase transition within VO2 to actively tune and modulate surface phonon polaritons at mid-infrared. However, controlling the behavior of such systems requires intimate knowledge of the temperature-dependent optical constants of VO2, which depend greatly on the growth conditions and substrate material. Here, we accurately determine the complex optical constants of VO2 on polar dielectrics across the insulator-to-metal phase transition (IMT) using only normal incident reflectance spectra by analyzing the reflectance with Kramers–Kronig relations and thin film Fresnel equations. This non-ellipsometry technique offers an …
Observation Of Gravitational Waves From The Coalescence Of A 2.5–4.5 M⊙ Compact Object And A Neutron Star, A. Abac, R. Abbott, I. Abouelfettouh, F. Acernese, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Volker Quetschke, Wenhui Wang
Observation Of Gravitational Waves From The Coalescence Of A 2.5–4.5 M⊙ Compact Object And A Neutron Star, A. Abac, R. Abbott, I. Abouelfettouh, F. Acernese, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Volker Quetschke, Wenhui Wang
Physics & Astronomy Faculty Publications
We report the observation of a coalescing compact binary with component masses 2.5–4.5 M⊙ and 1.2–2.0 M⊙ (all measurements quoted at the 90% credible level). The gravitational-wave signal GW230529_181500 was observed during the fourth observing run of the LIGO–Virgo–KAGRA detector network on 2023 May 29 by the LIGO Livingston observatory. The primary component of the source has a mass less than 5 M⊙ at 99% credibility. We cannot definitively determine from gravitational-wave data alone whether either component of the source is a neutron star or a black hole. However, given existing estimates of the maximum neutron star mass, we find …
Application Of Electrical Impedance Tomography To Cementitious Composites, Hugo Zazueta
Application Of Electrical Impedance Tomography To Cementitious Composites, Hugo Zazueta
Theses and Dissertations
This thesis explores the feasibility of using Electrical Impedance Tomography (EIT) for detecting damage in cementitious composites. Cementitious composites, such as concrete and cement mortar, are insulating; any conductive properties arise from the moisture within their pores and capillary structures. The proposed concept herein is that formed internal damages in cementitious composites consequently alter their pore and capillary structure, which can then be detected through EIT imaging. To construct tomographic images, the Gaussian Newton (GN) reconstruction algorithm, enhanced with priors, was employed. The results were then compared across different reconstruction processes. Cylindrical cement pastes and cement mortar samples were prepared, …
Intrinsic Universality In Tile Automata And Related Results, Elise C. Grizzell
Intrinsic Universality In Tile Automata And Related Results, Elise C. Grizzell
Theses and Dissertations
The Tile Automata (TA) model describes self-assembly systems in which monomers can build structures and transition with an adjacent monomer to change their states. This paper shows that seeded TA is a non-committal intrinsically universal model of self-assembly. We present a single universal Tile Automata system containing approximately 4600 states that can simulate (a) the output assemblies created by any other Tile Automata system Γ, (b) the dynamics involved in building Γ’s assemblies, and (c) Γ’s internal state transitions. It does so in a non-committal way: it preserves the full non-deterministic dynamics of a tile’s potential attachment or transition by …
Microwave Spectroscopy And Large Amplitude Motion Of Chlorosulfonic Acid (Clso2oh), Aaron J. Reynolds, Diego E. Rodriguez, Wei Lin, Kenneth R. Leopold
Microwave Spectroscopy And Large Amplitude Motion Of Chlorosulfonic Acid (Clso2oh), Aaron J. Reynolds, Diego E. Rodriguez, Wei Lin, Kenneth R. Leopold
Physics & Astronomy Faculty Publications
The high-resolution rotational spectrum of chlorosulfonic acid (ClSO2OH) has been studied using both broadband and cavity-based Fourier transform microwave spectrometers over the frequency range of 5–18 GHz. a-, b-, and c-type transitions have been recorded for both the 35Cl and 37Cl isotopologues. The observation of c-type lines establishes that the molecule lacks a plane of symmetry and suggests that the OH group can undergo large amplitude motion between equivalent structures. Interconversion between these structures can be achieved via internal rotation through two inequivalent barriers occurring at Cl-S-O-H torsional angles of 0 or 180 degrees. As in …
Robust Hydropower Planning Balances Energy Generation, Carbon Emissions And Sediment Connectivity In The Mekong River Basin, M. Tangi, Rafael Schmitt, Rafael M. Almeida, S. Bossi, Alexander S. Flecker, F. Sala, A. Castelletti
Robust Hydropower Planning Balances Energy Generation, Carbon Emissions And Sediment Connectivity In The Mekong River Basin, M. Tangi, Rafael Schmitt, Rafael M. Almeida, S. Bossi, Alexander S. Flecker, F. Sala, A. Castelletti
School of Earth, Environmental, & Marine Sciences Faculty Publications
We present a framework for strategic dam planning under uncertainty, which includes GHG emissions mitigation as a novel objective. We focus on the Mekong River Basin, a fast‐developing region heavily relying on river‐derived ecosystem services. We employ a multi‐objective evolutionary algorithm to identify strategic dam portfolios for different hydropower expansion targets, using process‐related and statistical models to derive indicators of sediment supply disruption and GHG emissions. We introduce a robust optimization approach that explores variations in optimal portfolio compositions for more than 5,000 state‐of‐ the‐world configurations, regarding sediment origins and trapping and GHG emissions. Thus, we can rank dam projects' …
Increasing The Robustness Of Machine Learning By Adversarial Attacks, Gourab Mukhopadhyay
Increasing The Robustness Of Machine Learning By Adversarial Attacks, Gourab Mukhopadhyay
Theses and Dissertations
By perturbation or physical attacks any machine can be fooled into predicting something else other than the intended output. There are training data based on which the model is trained to predict unknown things. The objective was to create noises and shades of different levels on the images and do experiments for measuring accuracy and making the model classify the traffic signs. When it comes to adding shades to the pictures, pixels were modified for three different layers of the pictures. The experiment also shows that with the shadows getting deeper, the accuracies drop significantly. Here, some changes in pixels …
Nilpotent Global Centers Of Generalized Polynomial Kukles System With Degree Three, Hebai Chen, Zhaosheng Feng, Rui Zahg
Nilpotent Global Centers Of Generalized Polynomial Kukles System With Degree Three, Hebai Chen, Zhaosheng Feng, Rui Zahg
School of Mathematical & Statistical Sciences Faculty Publications
In this paper, we study and characterize the nilpotent global centers of a generalized polynomial Kukles system with degree three. A sufficient and necessary condition of global centers is established under certain parametric conditions.
Answers To Frequently Asked Questions About The Pulsar Timing Array Hellings And Downs Curve, Joseph D. Romano, Bruce Allen
Answers To Frequently Asked Questions About The Pulsar Timing Array Hellings And Downs Curve, Joseph D. Romano, Bruce Allen
Physics & Astronomy Faculty Publications
We answer frequently asked questions (FAQs) about the Hellings and Downs correlation curve—the ‘smoking-gun’ signature that pulsar timing arrays (PTAs) have detected gravitational waves (GWs). Many of these questions arise from inadvertently applying intuition about the effects of GWs on LIGO-like detectors to the case of pulsar timing, where not all of it applies. This is because Earth-based detectors, like LIGO and Virgo, have arms that are short (km scale) compared to the wavelengths of the GWs that they detect (≈102–104 km). In contrast, PTAs respond to GWs whose wavelengths (tens of light-years) are much shorter than their arms (a …
Enhancing Traffic Safety And Connectivity: A Data-Driven Multi-Step-Ahead Vehicle Headway Prediction Leveraging High-Resolution Vehicular Trajectories, Mohamadhossein Noruzoliaee, Fatemeh Nazari, The University Of Texas Rio Grande Valley
Enhancing Traffic Safety And Connectivity: A Data-Driven Multi-Step-Ahead Vehicle Headway Prediction Leveraging High-Resolution Vehicular Trajectories, Mohamadhossein Noruzoliaee, Fatemeh Nazari, The University Of Texas Rio Grande Valley
Civil Engineering Faculty Publications
Vehicle headway, defined as the time elapsed between two successive vehicles passing a roadway point, is a key mesoscopic-scale measure in traffic flow theory with safety-critical transportation applications, such as preemptive collision avoidance warning systems as well as connected and autonomous vehicle (CAV) platoon control. Hence, it is crucial to accurately predict vehicle headway over sufficiently long future horizons (i.e., multi-step-ahead prediction) to be applicable for downstream safety-critical applications. This is a challenging task due to several random factors influencing headway, including inter- and intra-driver heterogeneity, asymmetric car-following driving behavior, and vehicle heterogeneity under mixed traffic of different vehicle classes. …
Personalized Driving Using Inverse Reinforcement Learning, Rodrigo J. Gonzalez Salinas
Personalized Driving Using Inverse Reinforcement Learning, Rodrigo J. Gonzalez Salinas
Theses and Dissertations
This thesis introduces an autonomous driving controller designed to replicate individual driving behaviors based on a provided demonstration. The controller employs Inverse Reinforcement Learning (IRL) to formulate the reward function associated with the provided demonstration. IRL is implemented through a dual-feedback loop system. The inner loop utilizes Q-learning, a model-free reinforcement learning technique, to optimize the Hamilton-Jacobi-Bellman (HJB) equation and derive an appropriate control solution. The outer loop leverages this derived control solution to generate parameters for the reward function, which are subsequently integrated into the HJB equation. The ultimate control policy is deduced from the final reward function obtained …
A Theory Of Innovation Diffusion: A Simulation Study, Chiquan Guo, Sudipto Sarkar, Sergio Garcia, Russell Adams
A Theory Of Innovation Diffusion: A Simulation Study, Chiquan Guo, Sudipto Sarkar, Sergio Garcia, Russell Adams
Marketing Faculty Publications
This study uses the agent-based modeling technique to discover propositions on innovation diffusion that are empirically testable. It finds the adoption rate is positively related to (1) the size of the population, (2) the degree of heterogeneity in consumer learning in the population, (3) the degree of heterogeneity in consumer innovativeness in the population, and (4) the fit-in- desire in the population for innovation. This research adds insights to the innovation diffusion literature and lays the groundwork for future empirical research.
Detection And Mitigation Of Misleading Pheromone Trails In Foraging Robot Swarms, Ryan Luna, Qi Lu
Detection And Mitigation Of Misleading Pheromone Trails In Foraging Robot Swarms, Ryan Luna, Qi Lu
Computer Science Faculty Publications
This study addresses the overlooked aspect of security in swarm robotics by exploring the vulnerabilities of stigmergic communication in foraging robot swarms. More specifically, we study the swarm's susceptibility to attacks that introduce misleading pheromone trails. Simulated scenarios in which detractor robots lay misleading trails to deceive benign foraging robots effectively reduce the foraging performance of the swarm. We analyze the impact of the attack on the swarm and evaluate the reduction of foraging efficiency. We introduce a defense mechanism using distance-based clustering (DBSCAN) along with a cluster grouping method to isolate large batches of detractors early in the simulation. …
Tuning Pid Controller For Quadrotor Using Particle Swarm Optimization, Eric X. Rodriguez, Qi Lu
Tuning Pid Controller For Quadrotor Using Particle Swarm Optimization, Eric X. Rodriguez, Qi Lu
Computer Science Faculty Publications
Energy expenditure for quadrotor control has a likelihood of being costly given parameter-dependent controllers that are less than optimal. The cost can grow proportionally when applied to multiple quadrotors for tracking and collaborative navigation tasks. This research aims to establish a basic approach to tuning PID (Proportional-Integral-Derivative) parameters for a simulated quadrotor drone. A PID controller for autonomy provides a straightforward method for correcting robotic movement based on its current state. However, applying a PID system to a flight controller poses challenges with an inherently under-actuated system, which includes the likelihood of large overshoots and lengthy adjustment times. To address …