Digital Commons Network^™

Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The utilization of remote sensing products for vehicle detection through deep learning has gained immense popularity, especially due to the advancement of unmanned aerial vehicles (UAVs). UAVs offer millimeter-level spatial resolution at low flight altitudes, which surpasses traditional airborne platforms. Detecting vehicles from very high-resolution UAV data is crucial in numerous applications, including parking lot and highway management, traffic monitoring, search and rescue missions, and military operations. Obtaining UAV data at desired periods allows the detection and tracking of target objects even several times during a day. Despite challenges such as diverse vehicle characteristics, traffic congestion, and hardware limitations, the …

Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai

Turkish Journal of Electrical Engineering and Computer Sciences

Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …

Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy

Turkish Journal of Electrical Engineering and Computer Sciences

Local differential privacy (LDP) has recently emerged as an accepted standard for privacy-preserving collection of users’ data from smartphones and IoT devices. In many practical scenarios, users’ data needs to be collected repeatedly across multiple iterations. In such cases, although each collection satisfies LDP individually by itself, a longitudinal collection of multiple responses from the same user degrades that user’s privacy. To demonstrate this claim, in this paper, we propose longitudinal attacks against iterative data collection with LDP. We formulate a general Bayesian adversary model, and then individually show the application of this adversary model on six popular LDP protocols: …

Room Temperature Polaritonic Soft-Spin Xy Hamiltonian In Organic–Inorganic Halide Perovskites, Kai Peng, Wei Li, Natalia G. Berloff, Xiang Zhang, Wei Bao

Department of Electrical and Computer Engineering: Faculty Publications

Exciton–polariton condensates, due to their nonlinear and coherent characteristics, have been employed to construct spin Hamiltonian lattices for potentially studying spin glass, critical dephasing, and even solving optimization problems. Here, we report the room-temperature polariton condensation and polaritonic soft-spin XY Hamiltonian lattices in an organic–inorganic halide perovskite microcavity. This is achieved through the direct integration of highquality single-crystal samples within the cavity. The ferromagnetic and antiferromagnetic couplings in both one- and two-dimensional condensate lattices have been observed clearly. Our work shows a nonlinear organic–inorganic hybrid perovskite platform for future investigations as polariton simulators.

Rational Design Of Heterostructured Nanomaterials For Accelerating Electrocatalytic Hydrogen Evolution Reaction Kinetics In Alkaline Media, Hai-Bin Ma, Xiao-Yan Zhou, Jia-Yi Li, Hong-Fei Cheng, Ji-Wei Ma

Journal of Electrochemistry

Owing to the merits of high energy density, as well as clean and sustainable properties, hydrogen has been deemed to be a prominent alternative energy to traditional fossil fuels. Electrocatalytic hydrogen evolution reaction (HER) has been considered to be mostly promising for achieving green hydrogen production, and has been widely studied in acidic and alkaline solutions. In particular, HER in alkaline media has high potential to achieve large-scale hydrogen production because of the increased durability of electrode materials. However, for the currently most prominent catalyst Pt, its HER kinetics in an alkaline solution is generally 2–3 orders lower than that …

Stability Of A Solid Oxide Cell Stack Under Direct Internal-Reforming Of Hydrogen-Blended Methane, Ya-Fei Tang, An-Qi Wu, Bei-Bei Han, Hua Liu, Shan-Jun Bao, Wang-Lin Lin, Ming Chen, Wan-Bing Guan, Subhash C. Singhal

Journal of Electrochemistry

In this work, the long-term stability and degradation mechanism of a direct internal-reforming solid oxide fuel cell stack (IR-SOFC stack) using hydrogen-blended methane steam reforming were investigated. An overall degradation rate of 2.3%·kh^–1 was found after the stack was operated for 3000 hours, indicating a good long-term stability. However, the voltages of the two cells in the stack were increased at the rates of 3.38 mV·kh^–1 and 3.78 mV·kh^–1, while the area specific resistances of the three metal interconnects in the stack were increased to 0.276 Ω·cm², 0.254 Ω·cm² and 0.249 Ω·cm^{2 …}

Adversarial Robustness With Partial Isometry, Loic Shi-Garrier, Nidhal Carla Bouaynaya, Daniel Delahaye

Henry M. Rowan College of Engineering Departmental Research

Despite their remarkable performance, deep learning models still lack robustness guarantees, particularly in the presence of adversarial examples. This significant vulnerability raises concerns about their trustworthiness and hinders their deployment in critical domains that require certified levels of robustness. In this paper, we introduce an information geometric framework to establish precise robustness criteria for (Formula presented.) white-box attacks in a multi-class classification setting. We endow the output space with the Fisher information metric and derive criteria on the input–output Jacobian to ensure robustness. We show that model robustness can be achieved by constraining the model to be partially isometric around …

Power Grid Resiliency Enhancement Against Flood-Induced Hazards, Mohadese Movahednia

LSU Doctoral Dissertations

Natural disasters, such as floods, may damage power system assets and lead to widespread and long outages. The impact of flood can be alleviated by preventive actions such as installing tiger dams around power substations before the flood. In this regard, it is imperative that critical substations are identified in terms of the connected load and imposed costs to the system. This study presents a resource allocation approach for protecting power substations against flood events a day ahead of the event. First, the required information for the model is extracted. Flood probability distribution functions are used to generate several flood …

Exploring Forward Scattering Mechanisms In Tio2 With Carbon Quantum Dots: Insights Into Photovoltaic Applications, Mona Samir, Zahraa Ismail, Ahmed M. Agour, Hassan Nageh, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

Market Analysis And Bidding Strategy Of Hybrid Renewable Energy Systems Considering Emissions, Fatma Elzahraa, Mohamed Elnemr, Samir Dawoud

Journal of Engineering Research

The competition in the electricity markets makes it difficult to choose a suitable strategy for maximizing profit while reducing harmful emissions. To have an adequate energy price for consumers while minimizing the harmful emissions to the atmosphere and maximizing profits of all participants in the electricity market needs an aggressive bidding strategy. Developing these bidding strategies with the integration of renewable energy (RE) in the electricity market became important. This research studies various bidding strategies for maximizing profits in the deregulated energy market since participants are keen on developing bidding strategies considering emissions. These bidding strategies will consider the integration …

Detection And Classification Of Sporadic E Using Convolutional Neural Networks, J. A. Ellis, Daniel J. Emmons, M. B. Cohen

Faculty Publications

In this work, convolutional neural networks (CNN) are developed to detect and characterize sporadic E (E_s), demonstrating an improvement over current methods. This includes a binary classification model to determine if Es is present, followed by a regression model to estimate the Es ordinary mode critical frequency (foEs), a proxy for the intensity, along with the height at which the Es layer occurs (hEs). Signal-to-noise ratio (SNR) and excess phase profiles from six Global Navigation Satellite System (GNSS) radio occultation (RO) missions during the years 2008–2022 are used as the inputs of the model. Intensity (foEs) and the …

Side Lobe Level Reduction And Array Thinning Of Concentric Circular Antenna Arrays, Alzahraa H. Nosier, Ahmed M. Elkhawaga, Mohamed E. Nasr, Nessim M. Mahmoud, Amr H. Hussein

Mansoura Engineering Journal

This paper presents a new beamforming technique based on the hybrid combination of the convolution algorithm (CA) and the genetic algorithm (GA) for reducing side lobe level (SLL) and array thinning of concentric circular antenna arrays (CCAA), which is denoted as C/GA technique. The CA determines the excitations of the elements, while the GA optimizes the radii of the circular arrays to adjust the half-power beamwidth (HPBW). For CCAA consisting of uniform feeding circular arrays, we assume that there are excitation coefficients that are distributed symmetrically around the array center and arranged in a vector. The excitation vector is convolved …

Improvement Of Convective Drying Equipment, A Ponasenko, Jasur Safarov, Shaxnoza Sultanova

Technical science and innovation

Drying of agricultural raw materials is an energy-consuming but integral process. Therefore, increasing the efficiency of drying and improving the quality indicators of dried material at minimum material and energy costs is relevant for producers of agricultural products. By present time numerous researches on improvement of constructions and processes of work of dryers providing satisfactory parameters of energy saving have been carried out. In some scientific materials it is shown that the use of generative gas and straw as fuel allows to reduce energy costs for the drying process in the fluidised bed dryer by 10-30%, the quality of seeds …

Mathematical Modeling Of Fruit Drying And System Analysis Of The Process (On The Example Of Persimmon), Gani Dadayev, Jasur Safarov, Shakhnoza Sultanova, Qobiljon Muxiddinov

Technical science and innovation

Vegetable raw materials, as an object of drying, are characterized by a large amount of water and a low content of dry substances. Vegetable raw materials have a capillary-porous structure. Food products contain both bound and free moisture at the same time. The removal of moisture from the material during drying depends on the total moisture content and the form of connection of moisture with the material. Adsorption and osmotic - bound moisture is retained at the interface of colloidal particles with the environment. Food products contain both bound and free moisture at the same time. The quantitative ratio between …

Capacitive Electrode Based Moisture Measurement Converter Errors And How To Eliminate Them, Hamdam Jabborov, Temurbek Rashidov

Technical science and innovation

The article discusses the errors associated with the moisture measuring transducer that is based on the cylindrical electrode, along with their sources and calculation formulas for error elimination. The initial capacitance of the capacitive electrode humidity converter is dependent on its geometric parameters, such as the radii of the electrodes and their length. Accurate calculation of these geometric parameters enables the reduction of regular measurement errors in the input and switching circuit of the moisture converter to a minimum value, resulting in a significant increase in the informativeness and accuracy of the output signal. Consequently, some sources of measurement errors …

Clpfudatabase: A Suite Of R Packages For Energy Conversion Chain Analysis, Matthew Kuperus Heun, Zeke Marshall, Emmanuel Aramendia

University Faculty Publications and Creative Works

Energy flowing through societal energy conversion chains (ECCs) enables economic activity and facilitates human flourishing. To understand economic growth and human well-being, the field of societal energy analysis (Common, 1976) evaluates ECCs from the primary stage (resources extracted from the environment, such as coal, oil, natural gas, wind, and solar), to the final stage (energy purchased by consumers, such as refined petroleum and electricity), to the useful stage (energy desired by the end user, such as heat, motion, and light), and sometimes to energy services (such as thermal comfort, transport, and illumination). Societal exergy analysis (SEA) (Ertesvåg, 2001), an extension …

Synthesis Of Gold Nanoparticle-Coated Graphite Electrodes For The Improved Detection Of Arsenic In Water Samples, Erika Hagen, Thom Spence Phd

[Archive] Belmont University Research Symposium (BURS)

Drinking water, especially tap, is often contaminated with some concentration of heavy metal ions, with two important ones being lead and arsenic. These ions often find their way into the water through household plumbing and service lines, municipal waste disposal, or natural mineral deposits. This is becoming a major concern for public health care professionals as consuming high levels of heavy metals can be detrimental to health. The acceptable limit of lead in drinking water is 15 parts per billion (ppb), however, many devices for analyzing samples are not able to reliably detect heavy metals at that level, at least …

Deep Transfer Learning For Detection Of Upper And Lower Body Movements: Transformer With Convolutional Neural Network, Kyle Lacroix, Davoud Gholamiangonabadi, Ana Luisa Trejos, Katarina Grolinger

Electrical and Computer Engineering Publications

When humans repeat the same motion, the tendons, muscles, and nerves can be damaged, causing Repetitive Stress Injuries (RSI). If the repetitive motions that lead to RSI are recognized early, actions can be taken to prevent these injuries. As Human Activity Recognition (HAR) aims to identify activities employing wearable or environment sensors, HAR is the first step toward identifying repetitive motions. Deep learning models, such as Convolutional Neural Networks (CNNs), have seen great success in recognizing activities for participants whose data are used in the model training; however, their accuracy drops for new participants as people move in different ways. …

Federated Learning For Sentiment Analysis In Presence Of Non-Iid Data: Sensitivity Of Deep Learning Models, Davoud Gholamiangonabadi, Katarina Grolinger

Electrical and Computer Engineering Publications

In sentiment analysis, data are commonly distributed across many devices, and traditional machine learning requires transferring these data to a central location exposing data to security and privacy risks. Federated Learning (FL) avoids this transfer by training a model without requiring the clients/devices to share their local data; however, FL performance drops when data are not Independent and Identically Distributed (non-IID), such as when label distribution or data size vary across clients. Although techniques for non-IID data have been proposed primarily in the image domain, the sensitivity of various deep learning models to non-IID data needs to be examined. Consequently, …

Dung Dkar Cloak: Exploring Soft Interfaces For Sonic Interactions, Judit Eszter Kárpáti, Esteban De La Torre

Textile Society of America: Symposium Proceedings

The importance of crossmodal interaction within the contemporary cultural, technological and scientific panorama has evidently gained significant attention due to its remarkable advantages in creating a meaningful, interwoven, and integrated experience. The use and recontextualization of textiles in such exploratory quest into the human senses has proven to be critical. Computational science, algorithmic logic and digital devices have always been rooted and closely interwoven with textile crafts and practices. Recent technological advancements have further combined technology and textile, generating interactive textile surfaces, constructing endless possibilities for multisensorial experiences. In this presentation we will examine how we can weave a sensitive …

Study Of A Multi-Agent Containment Problem Under Communication Constraints And Defense From Malicious Agents, Braulio Mora

Mechanical and Aerospace Engineering Theses - Archive

This thesis investigates a multi-agent containment problem where a fast evader, moving at a constant speed and heading, attempts to escape a circular containment region. A team of slow pursuers possess a nonzero capture radius and seek to capture the evader before escape. The research addresses two primary scenarios: one involving the team of pursuers, with no communication network, being constrained to the edge of the containment region, and the second involving a team of pursuers, with a communication network, not being constrained to the edge of the containment region. Both scenarios study the influence of malicious agents in the …

Nonlinear Guidance And Control Of Unmanned Aerial Manipulators For Delivering A Payload On A Moving Platform, Ravi Gyawali

Mechanical and Aerospace Engineering Theses - Archive

Unmanned Aerial manipulators (UAMs) are a class of Unmanned Aerial Vehicles (UAVs) equipped with a manipulator. By combining the aerial mobility of a UAV with a manipulator's dexterity, these hybrid systems can perform a wide range of complex tasks while reducing risks and costs. As a result, they are increasingly being utilized for military, industrial, and agricultural applications.

The thesis presents a novel approach for a multi-UAM system to collaboratively deliver a payload on a stationary or maneuvering platform. A sliding-mode-based guidance law, sourced from existing literature, is integrated with a combined control technique for the UAVs and their respective …

Dueling Robot, Abigail Coy

All Undergraduate Projects

This project was undertaken as a personal challenge to combine a Mechanical Engineering Technology degree and an Electrical Engineering Technology degree into a single final project showing the cumulative knowledge gained. It was determined that a robot to participate in Western Allied Robotics would be designed and manufactured for the 3 lb. weight class.

A two-part power system was designed to provide more power to the weapon arm. This design combined a compressive spring’s kinetic energy with the torque from the electric motor. Research determined all of the purchased components required and analysis were performed to determine the geometry and …

Reinforcement Learning For Optimal Kicking Actions In Humanoid Robotics: Advancing Robotic Autonomy And Versatility, Suresh Dodda, Sathish Kumar Chintala, Sukender Reddy Mallreddy, Sharath Chandra Macha, Yashwanth Vasa, Sapan Bharadwaj Bonala, Navin Kamuni, Sujatha Alla

Engineering Management & Systems Engineering Faculty Publications

Acquiring the necessary skills to perform a work effectively and efficiently requires a significant investment of time and computing power. Previous applications of Reinforcement Learning (RL) for action optimization in humanoid robotics have shown how promising this technology is for moving robotics towards true autonomy and versatility. Therefore, this study offers the first use of RL to create an entirely optimal kicking action for the Alderbaran Nao robot. Kicking motions that were steady, precise, quick, and able to kick farther than any existing RoboCup squad were generated by optimizing for a multi-objective reward function. We demonstrate that the ideal kicking …

Accurate And Time Efficient Signal Integrity And Power Integrity Modeling Of High-Speed Digital Systems, Chaofeng Li

Doctoral Dissertations

"Signal integrity (SI) and power integrity (PI) play an important role in the modern high-speed digital system design, which are closely related to the printed circuit board (PCB) dielectric material property, the PCB interconnect performance, and the power delivery network (PDN) on PCB. Generally, the full-wave simulation is used to accurately analyze and evaluate the designed PCB. But full-wave simulation is not a good option for the complex PCB structure with high aspect ratio, for example, PCB vias, and PDN, which will require significant computing time and storage resources. Equivalent circuit models have been developed to efficiently predict the electrical …

Exploratory Prompting Of Large Language Models To Act As Co-Pilots For Augmenting Business Process Work In Document Classification, Jose Ramon Ilagan, Joseph Benjamin R. Ilagan, Claire Louisse Basallo, Zachary Matthew Alabastro

Quantitative Methods and Information Technology Faculty Publications

Businesses deal with different types of documents containing unstructured documents. The data in these documents must be converted into digital forms other automated systems could only process. One generic use case is document classification, which usually involves manual transformation due to human understanding needed in the process. These documents go beyond those generated through regular business transactions and operations and also include web-based content such as online news, blogs, e-mails, and various digital libraries. Recent developments in robotic process automation (RPA) and artificial intelligence (AI) aim to automate the otherwise expensive, time-consuming, and repetitive manual steps. Through more powerful natural …

Otfs Modulation For High Mobility Wireless Channels, Sandip K C

All Graduate Theses, Dissertations, and Other Capstone Projects

In today's world, billions of devices are being connected to the internet primarily through wireless means, making this connectivity increasingly important. Managing these connections becomes complex, especially for moving devices such as drones and high-speed trains, which require seamless and reliable connectivity even at high speeds. Maintaining a stable connection in fast-moving environments is challenging but essential for the operation of these technologies. Traditional communication systems like OFDM face significant challenges in high mobility environments, struggling to cope with the rapid changes and dynamic conditions that high-speed movements introduce. To address this, OTFS is proposed as a solution. This novel …

Design Of Circular Piecewise Mimo Antenna For 5g Applications, Hassan Ali Ragheb, Faris Gamal, Mariam Housam

Electrical Engineering

The study under consideration demonstrates that optimally designed and executed mobile antenna are necessary to provide the remarkable performance that 5G networks are expected to offer. This work demonstrates the design and implementation of a multi-input multi-output (MIMO) antenna which is important for wireless communications. For increased coverage, efficacy, and capacity Beamforming, polarization diversity, and MIMO capabilities are among the important design components that are emphasized here. The design is simulated using HFSS and consists of 4 elements of antenna that combine to form a piecewise circular-shaped patch. Each element acts as a monopole. The single-element results show a resonance …

The Impact Of Dissolved Organic Matter On Photodegradation Rates, Byproduct Formations, And Degradation Pathways For Two Neonicotinoid Insecticides In Simulated River Waters, Josephus F. Borsuah, Tiffany L. Messer, Daniel D. Snow, Steven D. Comfort, Shannon Bartelt-Hunt

UK CARES Faculty Publications

The influences of dissolved organic matter (DOM) on neonicotinoid photochemical degradation and product formation in natural waters remain unclear, potentially impacting the sustainability of river systems. Therefore, our overall objective was to investigate the photodegradation mechanisms and phototransformation byproducts of two neonicotinoid pesticides, imidacloprid and thiamethoxam, under simulated sunlight at the microcosm scale, to assess the implications of DOM for insecticide degradation in rivers. Direct and indirect photolysis were investigated using twelve water matrices to identify possible reaction pathways with two DOM sources and three quenching agents. Imidacloprid, thiamethoxam, and potential degradants were measured, and reaction pathways identified. The photodegradation …

All-Optical Signal Processing With Fiber-Based Parametric Wavelength Converters, Cheng Guo

Electrical Engineering Dissertations - Archive

The optical signal degradation by optical amplifier noise set the fundamental limit of link reach in the fiber-optics networks. The industrial solution is to use the optical-electrical-optical (OEO) regenerator to clean up the noise at the expense of high-speed electronics and extra cost of laser and photodetectors. All-optical signal processing, enabled by nonlinear optics and optical fiber, intrinsically provides 2-order of magnitude higher processing bandwidth and seamless interface to fiber communication channels. However, there is no robust phase-preserving regenerator that has been experimentally demonstrated without sophisticated polarization tuning and without instable interferometric structure. In this project, we explore the applications …