Digital Commons Network^™

Design, Optimization, And Hardware Deployment Of A Deep Learning Model For Gps Spoofing Detection Using Gnss Satellite Receiver Protocol Data, Clarizza Morales Chacon

Electrical and Computer Engineering ETDs

The contemporary GPS infrastructure plays a vital role in advancing Position, Navigation, and Timing (PNT) applications across various sectors, including transportation, commerce, finance, and aviation. To provide a robust and authenticated infrastructure for users, it is important to develop a methodology for verifying the authenticity of satellite navigation signals, especially in civilian applications using the C/A code. This thesis explores Machine Learning (ML) techniques, focusing on the analysis of Global Navigation Satellite System (GNSS) protocol messages like UBX and NMEA to detect anomalies in receiver and satellite behavior, indicative of potential spoofing. The research demonstrates the deployment of Machine Learning …

The Automated Wheelchair, Jonathan Doksa Kamba Ngoyi

Honors College Theses

Automation refers to the use of technology to execute tasks through programmed instructions and automated control mechanisms to ensure accurate execution. This minimizes human involvement and encompasses various fields, including business process automation. A notable form of automation is assistive technology, which refers to any device or software that enhances individuals' learning, communication, or overall functionality. This can range from advanced tools like computers to simpler aids like walking sticks. Assistive technology aims to promote inclusivity and participation, particularly among individuals with disabilities, the elderly, and those with non-communicable diseases.

The Automated Airport Wheelchair is a culmination of prior projects …

Comparative Evaluation Of Investigation Methods For Estimating The Load-Dependent State Of Charge And End Of Discharge Of A Multirotor Uav Battery, Hanna Dibbern, Morten Roßberg, Claudia Werner

Journal of Aviation Technology and Engineering

As the scope of multirotor unmanned aerial vehicle (UAV) applications increases, more attention is being paid to UAV energy requirements, which vary depending on the mission profile. To obtain accurate information about the UAV battery during flight, the idea of a digital twin including a battery state estimation model is promising. For battery state estimation, a Kalman filter combination is the preferred approach in the literature. Comparing different Kalman filters, the unscented Kalman filter has a more accurate estimation for nonlinear systems compared to the extended Kalman filter. In the application of UAV flight with load-dependent flight missions, the comparison …

Stereoscopic-Based Mass Properties Estimation For Warhead Fragments, Alessia Nocerino, Katharine Larsen, Riccardo Bevilacqua, Elisabetta L. Jerome

Student Works

FRAGMENTATION characteristics such as spatial distribution, number of fragments, fragment velocity, and fragment mass can be used to characterize the lethality of a fragmenting weapon or any metal cased explosive [1,2]. However, most warhead tests and evaluations are limited to static arena testing, where fragment characteristics must be collected by hand. Recently, stereoscopic imaging techniques have been added to static arena tests. Using this method, position tracks can be collected for each fragment, and then velocity information can be found. This paper proposes a method to estimate the mass and moment of inertia using data collected by a stereoscopic imaging …

Ambient Air Emission Profiles Of Polycyclic Aromatic Hydrocarbons Around A Typical University Power House In Nigeria, Oyetunji Okedere

Tanzania Journal of Engineering and Technology (TJET)

The level of electricity generation in Nigeria is presently grossly inadequate. Consequently, the productive sectors of the economy do not presently enjoy an uninterrupted supply of electrical energy from the country’s national grid and the downtime is in most cases too much. Using diesel-fueled electric power generators has become an attractive alternative to meet the shortfall in the energy supply gap. In this study, the levels of polycyclic aromatic hydrocarbons in the vicinity of the diesel-fueled electric power generators operated by Osun State University, Osogbo, Nigeria were investigated with a view to ascertain the priority levels and carcinogenic PAHs. Since …

Employment Of Intelligent Predictive Maintenance On Thermal Power Plant Component Parts Taking Condenser Vacuum As A Case Study, Titus Ajewole

Tanzania Journal of Engineering and Technology (TJET)

This work proposes deployment of machine learning in the maintenance of individual constituent parts of steam power plant assemblages. With the condenser vacuum of a steam turbine (in a six-turbine plant assemblage) taken as a case study, information on the past operating parameters of the selected plant component was used to forecast its future working condition. Based on Exponential Gaussian Process of Regression, a model was developed, trained using the diachronic operational data, and employed in determining the future. A quantitative evaluation was employed to provide the distribution of the test values of the data about the lines of regression, …

Novel Systems Engineering Framework Analysis Of Photovoltaic Models And Equations, Peter R. Michael

USF Tampa Graduate Theses and Dissertations

This dissertation analyzes Photovoltaic PV equations and models for silicon based systems from a Systems Engineering framework. Background information includes an introduction, a summary of the state of PV use, a brief history of photovoltaics, and the detailed derivation of equations that enable the finding of the PV parameters contained in the PV models.The novel inquiry, leveraging systems engineering frameworks, includes three areas useful in analyzing PV equations and models. The first is a statistical verification of common simplifications of PV equations at the primary conditions of short circuit, open circuit, and maximum power. Additional analysis shows other simplifications that …

Optimal Inverter-Based Resource Installation To Minimize Technical Energy Losses In Distribution Systems, Felipe B. Dantas, Damasio Fernandes, Washington L.A. Neves, Alana K.X.B. Branco, Flavio Costa

Michigan Tech Publications

This paper proposes an algorithm for the optimal installation of inverter-based resources (IBR) composed of wind energy conversion systems, photovoltaic systems, and battery energy storage systems in distribution systems using genetic algorithm (GA) and the cuckoo search (CS) as optimization techniques. The OpenDSS software is used to calculate the power flow in the distribution system with different penetration levels of IBRs. It is used a standard load shape of the IEEE 123 bus system programmed in OpenDSS and irradiance, temperature, and wind speed curves from Brazil. The proposed algorithm, using a genetic algorithm and cuckoo search, was able to define …

Frequency Stability Constrained Grid Operation With High Penetration Of Renewables, Ningchao Gao

Electronic Theses and Dissertations

Achieving carbon neutrality necessitates a significant integration of renewable energy into power systems. However, the swift implementation of fluctuating renewable energy (VRE) sources such as solar photovoltaics (PV) exacerbates real time power imbalances due to the randomness and uncertainty associated with VRE power generation. Further, the declining reliance on conventional synchronous generators (SGs) for system inertia presents considerable challenges in maintaining frequency stability, especially following disturbances.

Two possible solutions are proposed to address the first issue. Firstly, a speedy real time generation dispatch can be scheduled to allocate generation resources within short time intervals to effectively respond to changes in …

Custom Led Dashboard Integration For The Cal Poly Racing Team, Josue Hernandez

Computer Engineering

The Custom LED Dashboard Integration was made for the Cal Poly Racing Team, specifically the BAJA division. The dashboard was made as a way to combat the current limitations endured from the past methods used to display critical information of the vehicle to the car. The display was made to combat issues of limited quantity of data being able to be displayed to the driver and its small readability was an issue, the display helped combat that by providing a greater quantity of data being able to be sent and displayed on the display and the information being displayed having …

Real-Time Object Tracking With Yolov5 And Recurrent Network On A Hardware Platform, Mohammed Abdulhakeem Alameri

Theses

The advancement of computer vision, particularly in the domain of object tracking, involves the integration of conventional feature-based approaches with contemporary deep learning methodologies. The initial phase of object detection plays a fundamental role in generating prospective objects for further tracking, and its level of success has a direct influence on the overall effectiveness of the tracking process. Many of the methods used to generate candidate objects start with object detection, and then object tracking algorithms are developed to link the object instances together to create the trajectories.
The primary difficulties in object tracking pertain to the establishment of reliable …

Electrophertic Deposition And Characterization Of Molybdenum Disulfide On Silicon Substrates, Alex J. Young

LSU Doctoral Dissertations

The electrical characteristics of 2D materials such as high electron mobility and current density are of great interest to various fields from optoelectronics to renewable energy. Researchers have focused their efforts on transition metal dichalcogenides (TMDCs) due to their direct energy band gap. One such TMDC that has garnered much attention is molybdenum disulfide (MoS2). MoS2 has electrical properties comparable to graphene and is a TMDC with characteristics amenable to applications such as solar cells and sensors. Commonly deposited through time-consuming and complex deposition methods such as chemical vapor deposition (CVD), the viability of MoS2 as an electronic material will …

Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman

Research outputs 2022 to 2026

Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, …

Metric Algorithms Of Symbol Detection For Determining A Group Of Significant Objects, Sherzod Ismoiljonovich Yuldashev

Chemical Technology, Control and Management

This article examines the algorithm of nearest neighbors, which widely uses metric classification algorithms and the combinatorial theory of reconnection with the precedent information in solving practical recognition problems. One of the most important issues in the development of image recognition systems is that the image recognition system determines the characteristics of objects. Most pattern recognition methods are used in the process of recognizing not all objects of the training sample, but a certain part of the objects. The formation of a training sample by filtering objects according to the level of importance for metric classification algorithms is carried out …

Study Of Technological Multi-Stage Modes Of Refining Vegetable Oils, Elyor Erkinovich Samadov

Chemical Technology, Control and Management

The work reflects the current state of the technology for obtaining refined vegetable oils and identifies trends in their improvement and further development in the environment of industrial automation using modern methods of distributed monitoring, building control, and management systems for technological processes of refining vegetable oils. The influence of technological modes of refining vegetable oils on the efficiency of diffusion extraction of free fatty acids (FFA) has been studied and the indirect pH-metric measurement of FFA concentration has been substantiated.

Development Of An Imitation Model Of The Vulcanization Process In The Production Of Elastomeric Composites, Toshtemir Avezov, Mirxalil Agzamovich Ismailov

Chemical Technology, Control and Management

In the article, a systematic approach to the mathematical modeling of the production process of complex multi-stage elastomeric composites was considered, which allows to take into account the stoichiometric relationship of the chemical reaction in the process. Based on the chemical reaction occurring in the mixer, a kinetic model of the elastomer composites production process is proposed, which is the basis for obtaining the main functional relationship of the mathematical model for the mixer, the main quality indicator of the process. The proposed systematic approach in the form of a mathematical model based on the stoichiometric relationship and the …

Synthesis Problem Of Adaptive Control Systems For Multi-Channel And Multi-Mode Objects, Jasur Usmonovich Sevinov, Abdishukurov Maqsud O'G'Li Shavkat Mr, Nasriddin Xasanovich Bobomurodov

Chemical Technology, Control and Management

The issue of synthesis of an adaptive control system for multi-channel and multi-mode objects is considered. Development that of effective adaptive control algorithms for nonlinear dynamic systems ensure quality indicators of processes. In technological processes, it is necessary to control several parameters or several systems at the same time. For such a process control system, an adaptive control system is created. Work has been carried out on structural projects for the installation of adaptive systems. The stable requirements for the correction of adaptive control systems are seen. A review of several parametric deviation detections, based on the reference model and …

Trends In The Development And Improvement Of Glass Furnaces And Monitoring And Control Systems, N.R Yusupbekov, O'Tkir U. Xolmanov

Chemical Technology, Control and Management

The theory and practice of establishing industrial automation systems for glass furnaces and installations as they are right now are taken into consideration. Comparative analysis is based on publications over the last 20 years in the field being studied. On the basis of an analysis of the review materials, generalizations are made that form the basis for proposals aimed at modernizing and improving the technology and instrumentation of fuel combustion processes in gas-burning furnaces and installations, as well as monitoring and control systems for technological processes occurring in glass furnaces and installations.

Normalized Linearly-Combined Chaotic System: Design, Analysis, Implementation And Application, Md Sakib Hasan, Anurag Dhungel, Partha Sarathi Paul, Maisha Sadia, Md Razuan Hossain

Faculty and Student Publications

This work presents a general framework for developing a multi-parameter 1-D chaotic system for uniform and robust chaotic operation across the parameter space. This is important for diverse practical applications where parameter disturbance may cause degradation or even complete disappearance of chaotic properties. The wide uninterrupted chaotic range and improved chaotic properties are demonstrated with the aid of stability analysis, bifurcation diagram, Lyapunov exponent (LE), Kolmogorov entropy, Shannon entropy, and correlation coefficient. We also demonstrate the proposed system’s amenability to cascading for further performance improvement. We introduce an efficient Field-Programmable Gate Array (FPGA)-based implementation and validate its chaotic properties using …

Multiple Reflections And The Near-Field Effects On A Metamaterial Quarter-Wave Plate, James Davis, Durdu Güney

Michigan Tech Publications

Metamaterial-based quarter-wave plates (QWPs) have emerged as promising candidates for advanced polarization control in a variety of optical applications, owing to their unique properties, such as ultra-thin profiles and tailored spectral responses. We design an ultra-thin, high-efficiency, and broadband QWP in transmission mode based on a TiO2" role="presentation" style="box-sizing: border-box; max-height: none; display: inline; line-height: normal; font-size: 13.2px; font-size-adjust: none; overflow-wrap: normal; text-wrap-mode: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; color: rgb(34, 34, 34); font-family: Arial, Arial, Helvetica, sans-serif; position: relative;">22/Au grating structure. We show that multiple reflections and …

Novel Fpga Speed Grade Authentication Method For Counterfeit Identification, Ana Maria Camacho Negrete

USF Tampa Graduate Theses and Dissertations

Today's society runs on modern microelectronics. Whether it is our computers, smartphones and tablets, navigation systems, and even automobiles, the impact of inferior components on our society's functioning is a well-known and serious challenge.Inferior components, in this context, refer to non-specification compliant parts that are known to enter the global supply chain either due to manufacturing/quality control errors or intentional component counterfeiting by non-OEM (original equipment manufacturer) sources. This thesis discusses the latter, which is a well-documented and growing challenge that poses a serious risk to every sector of our society. This has been further exacerbated by the global pandemic-driven …

Generation Of Dna Oligomers With Similar Chemical Kinetics Via In-Silico Optimization, Michael Tobiason, Bernard Yurke, William L. Hughes

Electrical and Computer Engineering Faculty Publications and Presentations

Networks of interacting DNA oligomers are useful for applications such as biomarker detection, targeted drug delivery, information storage, and photonic information processing. However, differences in the chemical kinetics of hybridization reactions, referred to as kinetic dispersion, can be problematic for some applications. Here, it is found that limiting unnecessary stretches of Watson-Crick base pairing, referred to as unnecessary duplexes, can yield exceptionally low kinetic dispersions. Hybridization kinetics can be affected by unnecessary intra-oligomer duplexes containing only 2 base-pairs, and such duplexes explain up to 94% of previously reported kinetic dispersion. As a general design rule, it is recommended that unnecessary …

Lactation Physiokinetics—Using Advances In Technology For A Fresh Perspective On Human Milk Transfer, Jimi Francis, Paul Flynn, Maisha Naowar, Premananda Indic, Darby Dickton

Electrical Engineering Faculty Publications and Presentations

Introduction: Though the nature of breastfeeding is critical, scant information is available on how the action of the milk transfer from mother to infant is regulated in humans, where the points of dysfunction are, and what can be done to optimize breastfeeding outcomes. While better therapeutic strategies are needed, before they can be devised, a basic scientific understanding of the biomechanical mechanisms that regulate human milk transfer from breast to stomach must first be identified, defined, and understood. Methods: Combining systems biology and systems medicine into a conceptual framework, using engineering design principles, this work investigates the use of biosensors …

Study Of Improved Sorting Weighting Cfar Detectors For Gaussian Environment, Souad Chabbi, Khadidja Belhi, M'Hamed Hamadouche

Emirates Journal for Engineering Research

The goal of this paper is to improve the detection performance and the false alarm regulation of the conventional order statistics Constant False Alarm Rate (OS-CFAR) detectors in a non-homogeneous Gaussian environment. To this end, we design and study the New Sorting Weighting (NSW-) and the Modified Sorting Weighting (MSW-) CFAR detectors. We find closed forms of the detection ( ) and the false alarm ( ) probabilities for both detectors. Moreover, we identify the optimum pairs of weights that maximize the and ensure a constant . Finally, we prove through Monte Carlo simulations that these detectors provide better detection …

Cyber-Physical Multi-Robot Systems In A Smart Factory: A Networked Ai Agents Approach, Zixiang Nie

USF Tampa Graduate Theses and Dissertations

This dissertation focuses on addressing the technical challenges of non-stationarity in smart factories through the use of cyber-physical AI agents. Industry 4.0 and smart manufacturing with smart factories as a central role, have a growing demand for Just-in-Time (JIT) and on-demand production, as well as mass customization—all while maintaining high productivity, resource efficiency and resilience. This research positions Multi-Robot Systems (MRS)-driven smart factories. The heterogeneous production and transportation robots in an MRS collaborate to form multiple real-time adjusted production flows achieving the flexibility to accommodate such on-demand, mass customization.

However, the implementation of MRS introduces new sets of challenges, including …

Enhancing Exploration-Exploitation In Harmony Search For Airborne Hyperspectral Imaging Band Selection (E3hs), Mohammed Abdulmajeed Moharram, Divya Meena Sundaram

Turkish Journal of Electrical Engineering and Computer Sciences

Hyperspectral imaging has emerged as a prominent area of research in the field of remote sensing science. However, hyperspectral images (HSIs) pose a notable challenge due to the presence of numerous irrelevant and redundant spectral bands exhibiting high correlation. Therefore, it is necessary to enhance the classification performance for HSI processing by selecting the most relevant discriminative spectral bands. To this end, this paper introduces a metaheuristic search method called enhancing exploration-exploitation in harmony search (E3HS). The standard harmony search suffers from many weaknesses, such as premature convergence and falling easily into the local optimum. Consequently, E3HS was proposed to …

Multi-View Brain Tumor Segmentation (Mvbts): An Ensemble Of Planar And Triplanar Attention Unets, Snehal Rajput, Rupal Kapdi, Mehul Raval, Mohendra Roy

Turkish Journal of Electrical Engineering and Computer Sciences

3D UNet has achieved high brain tumor segmentation performance but requires high computation, large memory, abundant training data, and has limited interpretability. As an alternative, the paper explores using 2D triplanar (2.5D) processing, which allows images to be examined individually along axial, sagittal, and coronal planes or together. The individual plane captures spatial relationships, and combined planes capture contextual (depth) information. The paper proposes and analyzes an ensemble of uniplanar and triplanar UNets combined with channel and spatial attention for brain tumor segmentation. It investigates the significance of each plane and analyzes the impact of uniplanar and triplanar ensembles with …

Hybrid Machine Learning Model To Predict Chronic Kidney Diseases Using Handcrafted Features For Early Health Rehabilitation, Amjad Rehman, Tanzila Saba, Haider Ali, Narmine Elhakim, Noor Ayesha

Turkish Journal of Electrical Engineering and Computer Sciences

Chronic kidney diseases proliferate due to hypertension, diabetes, anemia, obesity, smoking etc. Patients with such conditions are sometimes unaware of first symptoms, complicating disease diagnosis. This paper presents chronic kidney disease (CKD) prediction model to classify CKD patients from NCKD (Non-CKD). The proposed study has two main stages. First, we found the odds ratio through logistic regression and comparison test to identify early risk factors from kidneys? MRI and differentiate CKD from NCKD subjects. In stage 2, LR, LDA, MLP classifiers were applied to predict CKD and NCKD by extracting features from MRI. The odds ratio of blood glucose random …

Cognitive Digital Modelling For Hyperspectral Image Classification Using Transfer Learning Model, Mohammad Shabaz, Mukesh Soni

Turkish Journal of Electrical Engineering and Computer Sciences

Deep convolutional neural networks can fully use the intrinsic relationship between features and improve the separability of hyperspectral images, which has received extensive in recent years. However, the need for a large number of labelled samples to train deep network models limits the application of such methods. The idea of transfer learning is introduced into remote sensing image classification to reduce the need for the number of labelled samples. In particular, the situation in which each class in the target picture only has one labelled sample is investigated. In the target domain, the number of training samples is enlarged by …

Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson

Turkish Journal of Electrical Engineering and Computer Sciences

Millions of people throughout the world suffer from the complicated and crippling condition of chronic pain. It can be brought on by several underlying disorders or injuries and is defined by chronic pain that lasts for a period exceeding three months. To better understand the brain processes behind pain and create prediction models for pain-related outcomes, machine learning is a potent technology that may be applied in Functional magnetic resonance imaging (fMRI) chronic pain research. Data (fMRI and T1-weighted images) from 76 participants has been included (30 chronic pain and 46 healthy controls). The raw data were preprocessed using fMRIprep …