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Articles 1291 - 1320 of 14323
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Accelerating Homomorphic Encryption In Risc-V Architectures With Hardware Based Number Theory Transform, Zachary Legg
Accelerating Homomorphic Encryption In Risc-V Architectures With Hardware Based Number Theory Transform, Zachary Legg
Theses and Dissertations
Fully Homomorphic Encryption is an encryption paradigm enabling computations on encrypted data without the need for decryption. Such behavior is promising for securing DoD cloud computing but is also computationally demanding. To alleviate some of the computational load and accelerate FHE schemes, this research proposes adding a hardware accelerator, for the Number Theory Transform (NTT) operation, to a RISC-V processor. Thus enhancing FHE capabilities for potentially resource-constrained devices.
Analyzing The Effects Of Atmospheric Turbulence On Polarization-Entangled Photon Pairs Using Quantum State Tomography, Noah S. Everett
Analyzing The Effects Of Atmospheric Turbulence On Polarization-Entangled Photon Pairs Using Quantum State Tomography, Noah S. Everett
Theses and Dissertations
To help in building a quantum-based communication link, we experimentally designed a system to simulate atmospheric turbulence and characterize its effects on a polarization-entangled photon-pair source. The simulated turbulence is constructed using two afocal optical systems with a phase plate inserted in each to mimic both weak and strong atmospheric turbulence respectively. After propagation, quantum state tomography (QST) is performed on each pair to reconstruct the density matrix of the pair’s overall polarization state. In characterization of the simulated turbulence, we were able to reach strengths up to a D/r0 of 18.2, which begins to approach the strong turbulent regime. …
Generalized Characterization Of Biaxial Media Using Ultra-Wideband Multi-Static Focused Beam System With Polarimetric Calibration, Jeffrey P. Massman
Generalized Characterization Of Biaxial Media Using Ultra-Wideband Multi-Static Focused Beam System With Polarimetric Calibration, Jeffrey P. Massman
Theses and Dissertations
Novel metamaterial and metasurface realizations provide unique control of the electromagnetic wave dispersion but present many challenges for accurate constitutive parameter extraction. One measurement approach commonly employed is a freespace non-destructive focus beam system. Modern implementations are configured with multi-static dual-polarized capabilities for characterizing complex materials and offer many advantages by enabling ultra-wideband sampling, multiple measurement degrees of freedom and larger sample sizes. Practical electromagnetic material characterization of complex bianisotropic media requires the advancement of wave propagation analysis and calibration schemes. This research focuses on generalized biaxial media characterization and multi-static focused beam system metrology with polarimetric calibration schemes and …
Analysis Of Countermeasures Against Remote And Local Power Side Channel Attacks Using Correlation Power Analysis, Aurelien Tchoupou Mozipo, John M. Acken
Analysis Of Countermeasures Against Remote And Local Power Side Channel Attacks Using Correlation Power Analysis, Aurelien Tchoupou Mozipo, John M. Acken
Electrical and Computer Engineering Faculty Publications and Presentations
Countermeasures and deterrents to power side-channel attacks targeting the alteration or scrambling of the power delivery network have been shown to be effective against local attacks where the malicious agent has physical access to the target system. However, remote attacks that capture the leaked information from within the IC power grid are shown herein to be nonetheless effective at uncovering the secret key in the presence of these countermeasures/deterrents. Theoretical studies and experimental analysis are carried out to define and quantify the impact of integrated voltage regulators, voltage noise injection, and integration of on-package decoupling capacitors for both remote and …
Pa2blo: Low-Power, Personalized Audio Badge, Hemanth Sabbella, Dulaj Sanjaya Weerakoon, Manoj Gulati, Archan Misra
Pa2blo: Low-Power, Personalized Audio Badge, Hemanth Sabbella, Dulaj Sanjaya Weerakoon, Manoj Gulati, Archan Misra
Research Collection School Of Computing and Information Systems
We present the hardware design and software pipeline for an ultra-low power device, in the form factor of a wearable badge, that supports energy efficient sensing, processing and wireless transfer of human voice commands and interactions. The proposed system, called PA2BLO, is envisioned to support both: (a) real-time, scalable, authorized voice based interaction and control of devices and appliances, and (b) longitudinal, low-power logging of natural voice interactions. PA2BLO in-troduces two key novel capabilities. First, it includes a low power, low-complexity voice authentication module that is able to reliably authenticate an authorized user only using low sampling rate (500 Hz) …
Multilayered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo
Multilayered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is, however, challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This article, therefore, proposes a multilayered Mult timescale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. in the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy …
Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan
Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
A novel optimal trajectory tracking scheme is introduced for nonlinear continuous-time systems in strict feedback form with uncertain dynamics by using neural networks (NNs). The method employs an actor-critic-based NN back-stepping technique for minimizing a discounted value function along with an identifier to approximate unknown system dynamics that are expressed in augmented form. Novel online weight update laws for the actor and critic NNs are derived by using both the NN identifier and Hamilton-Jacobi-Bellman residual error. A new continual lifelong learning technique utilizing the Fisher Information Matrix via Hamilton-Jacobi-Bellman residual error is introduced to obtain the significance of weights in …
Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch
Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch
Chemistry Faculty Research & Creative Works
Biomedical Datasets Distill Many Mechanisms Of Human Diseases, Linking Diseases To Genes And Phenotypes (Signs And Symptoms Of Disease), Genetic Mutations To Altered Protein Structures, And Altered Proteins To Changes In Molecular Functions And Biological Processes. It Is Desirable To Gain New Insights From These Data, Especially With Regard To The Uncovering Of Hierarchical Structures Relating Disease Variants. However, Analysis To This End Has Proven Difficult Due To The Complexity Of The Connections Between Multi-Categorical Symbolic Data. This Article Proposes Symbolic Tree Adaptive Resonance Theory (START), With Additional Supervised, Dual-Vigilance (DV-START), And Distributed Dual-Vigilance (DDV-START) Formulations, For The Clustering Of …
Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen
Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen
Faculty Publications
It has been recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth’s anomaly magnetic field immersed in overwhelming complex signals for magnetic navigation in a GPS-denied environment. The accuracy of the detected anomaly field corresponds to a positioning accuracy in the range of 10–40 m. To increase the accuracy and reduce the uncertainty of weak signal detection as well as to directly obtain the position information, we exploit the machine-learning model of random forests that combines the output of multiple decision trees to give optimal values of the physical …
Development Of A Criterion Assessing The Level Of Relationship Of Multiple Identified Characteristics For Classification, Mirzoyan Mirzaaxmedovich Kamilov, Oybek Zokirovich Koraboshev, Bobomurod Mamitjonovich Tojiboev
Development Of A Criterion Assessing The Level Of Relationship Of Multiple Identified Characteristics For Classification, Mirzoyan Mirzaaxmedovich Kamilov, Oybek Zokirovich Koraboshev, Bobomurod Mamitjonovich Tojiboev
Chemical Technology, Control and Management
This article discusses an optimized version of the standard design developed by Yu.I.Zhuravlev, an optimization procedure through an algebraic approach based on precedent algorithms that solves the problem of pattern identification. The formation of the convex hull of the recognition operator and corrective procedures of information models by mutual compensation of each other was also studied. In addition, the functional connection of recognition operators and the definition of idempotent connection of operators are analyzed.
Automated Workflow For Redox Potentials And Acidity Constants Calculations From Machine Learning Molecular Dynamics, Feng Wang, Jun Cheng
Automated Workflow For Redox Potentials And Acidity Constants Calculations From Machine Learning Molecular Dynamics, Feng Wang, Jun Cheng
Journal of Electrochemistry
Redox potentials and acidity constants are key properties for evaluating the performance of energy materials. To achieve computational design of new generation of energy materials with higher performances, computing redox potentials and acidity constants with computational chemistry have attracted lots of attention. However, many works are done by using implicit solvation models, which is difficult to be applied to complex solvation environments due to hard parameterization. Recently, ab initio molecular dynamics (AIMD) has been applied to investigate real electrolytes with complex solvation. Furthermore, AIMD based free energy calculation methods have been established to calculate these physical chemical properties accurately. However, …
Confirmation Of Anomalous-Heat Report, Steven B. Krivit, Melvin H. Miles
Confirmation Of Anomalous-Heat Report, Steven B. Krivit, Melvin H. Miles
Journal of Electrochemistry
This study identifies, for the first time, critical calculation errors made by Nathan Lewis and his co-authors, in their study presented on May 1, 1989, at the American Physical Society meeting in Baltimore, Maryland. Lewis et al. analysed calorimetrically measured heat results in nine experiments reported by Martin Fleischmann and his co-authors. According to the Lewis et al. analysis, each of the experiments, where calculated for no recombination, showed anomalous power losses. When we used the same raw data, our corrected calculations indicate that each experiment showed anomalous power gains. As such, these data suggest the possibility of a new, …
Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool
Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool
Henry M. Rowan College of Engineering Departmental Research
Artificial intelligence and neuroscience have a long and intertwined history. Advancements in neuroscience research have significantly influenced the development of artificial intelligence systems that have the potential to retain knowledge akin to humans. Building upon foundational insights from neuroscience and existing research in adversarial and continual learning fields, we introduce a novel framework that comprises two key concepts: feature distillation and re-consolidation. The framework distills continual learning (CL) robust features and rehearses them while learning the next task, aiming to replicate the mammalian brain's process of consolidating memories through rehearsing the distilled version of the waking experiences. Furthermore, the proposed …
Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley
Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley
Dissertations and Theses
This thesis outlines the design of an IQ Test Bench that allows for experimentation of quadrature modulation techniques. Quadrature modulation utilizes two signals I and Q, 90° out of phase from each other, to greatly increase communication data rates. Using Desmos, a thorough mathematical analysis of waveform mixing is presented, and constellation diagrams are plotted from the results. From this an ancient fire signaling technique known as the Polybius Square is encoded into the system. The IQ Test Bench is built from fundamental components that would be contained within an RFFE: a local oscillator and two frequency mixers. The LO …
Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar
Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a fast hyperparameter optimization algorithm based on the benefits and shortcomings of the standard grid search (GS) algorithm for support vector regression (SVR). This presented GS-inspired algorithm, called fast grid search (FGS), was tested on benchmark datasets, and the impact of FGS on prediction accuracy was primarily compared with the GS algorithm on which it is based. To validate the efficacy of the proposed algorithm and conduct a comprehensive comparison, two additional hyperparameter optimization techniques, namely particle swarm optimization and Bayesian optimization, were also employed in the development of models on the given datasets. The evaluation of …
Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu
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
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
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: …
Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish
Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish
Theses and Dissertations
Greenhouse Networked Control Systems (NCS) are popular applications in modern agriculture due to their ability to monitor and control various environmental factors that can affect crop growth and quality. However, designing and operating a greenhouse in the context of NCS could be challenging due to the need for highly available and cost-efficient systems. This thesis presents a design methodology for greenhouse NCS that addresses these challenges, offering a framework to optimize crop productivity, minimize costs, and improve system availability and reliability. It contributes several innovations to the field of greenhouse NCS design. For example, it recommends using the 2.4GHz frequency …
A Time Synchronized Multi-Hop Mesh Network With Crystal-Free Nodes, Filip Maksimovic, Austin Patel, David C. Burnett, Thomas Watteyne, Kristofer S.J. Pister
A Time Synchronized Multi-Hop Mesh Network With Crystal-Free Nodes, Filip Maksimovic, Austin Patel, David C. Burnett, Thomas Watteyne, Kristofer S.J. Pister
Electrical and Computer Engineering Faculty Publications and Presentations
In this work we propose and demonstrate a protocol for a time synchronized channel hopping mesh network for wireless transceivers that use exclusively imprecise and inaccurate on-chip oscillators. This protocol is built on an IEEE 802.15.4 physical layer radio that enables interoperability with protocols such as 6TiSCH or Thread. A calibration-bootstrapped multi-hop mesh network is demonstrated with a single crystal-enabled node acting as the root. The protocol is designed to create a multi-hop mesh while compensating noisy and drifting oscillators and timers. With a 4 s synchronization period, an experimental implementation of the network maintains, in the worst case, 1.8 …
Mechanical And Electromagnetic Properties Of Incorporating Graphene Oxide In Cementitious Mixtures, Cherif Khalil
Mechanical And Electromagnetic Properties Of Incorporating Graphene Oxide In Cementitious Mixtures, Cherif Khalil
Theses and Dissertations
This multidisciplinary study aimed at investigating the impact of incorporating graphene oxide (GO) on the mechanical properties and electromagnetic (EM) shielding effectiveness of cementitious mixtures, as well as critically examining the mechanism with which GO affects their microstructure properties. Analysis of the literature review showed that there are discrepancies in reporting the impact of GO on the mortar mix. Consequently, this study focuses on exploring the cause for such discrepancies and identifies three main factors which are thoroughly investigated. The factors were the different sonication energies applied to the GO (Shear Mixing, 1.5 kJ/ml, 3 kJ/ml and 6 kJ/ml), the …
Reliable Outdoor Ai-Based Autonomous Uav Localization And Trajectory Tracking Using Cellular Networks, Ghada Afifi
Reliable Outdoor Ai-Based Autonomous Uav Localization And Trajectory Tracking Using Cellular Networks, Ghada Afifi
Theses and Dissertations
Unmanned aerial vehicles (UAVs) are becoming an integral part of numerous commercial and military applications. In many of these applications, the UAV is required to self-navigate in highly dynamic urban environments. Existing localization and trajectory planning techniques, which rely mainly on the Global Positioning System (GPS), do not provide an effective real-time solution for self-localization and path planning, particularly in dense urban environments. The purpose of this thesis is to study the localization and trajectory planning of UAVs independent of GPS systems or other detectable mobile signals. We propose to utilize the broadcast signals from existing cellular networks to localize …
Adversarial Robustness With Partial Isometry, Loic Shi-Garrier, Nidhal Carla Bouaynaya, Daniel Delahaye
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 …
Electron Trajectories And Critical Current In A Two-Dimensional Planar Magnetically Insulated Crossed-Field Gap, Xiaojun Zhu, Jack K. Wright, N. R. Sree Harsha, Jim Browning, Allen L. Garner
Electron Trajectories And Critical Current In A Two-Dimensional Planar Magnetically Insulated Crossed-Field Gap, Xiaojun Zhu, Jack K. Wright, N. R. Sree Harsha, Jim Browning, Allen L. Garner
Electrical and Computer Engineering Faculty Publications and Presentations
The critical current in a one-dimensional (1D) crossed-field gap is defined by the transition from a cycloidal flow to a near-Brillouin (nB) state characterized by electron flow orthogonal to both the electric and magnetic fields and uniform virtual cathode formation. Motivated by recent studies on space-charge-limited current in non-magnetic diodes, we assess the meaning of critical current in a magentically insulated two-dimensional (2D) planar crossed-field geometry. Particle-in-cell (PIC) simulations demonstrate that binary behavior between a laminar and turbulent state does not occur in 2D because the virtual cathode is nonuniform. Rather than a distinct nB state above the critical current …
Electron Effective Mass In Gan Revisited: New Insights From Terahertz And Mid-Infrared Optical Hall Effect, Nerijus Armakavicius, Sean Knight, Philipp Kühne, Vallery Stanishev, Dat Q. Tran, Steffen Richter, Alexis Papamichail, Megan Stokey, Preston Sorensen, Ufuk Kilic, Mathias Schubert, Plamen P. Paskov, Vanya Darakchieva
Electron Effective Mass In Gan Revisited: New Insights From Terahertz And Mid-Infrared Optical Hall Effect, Nerijus Armakavicius, Sean Knight, Philipp Kühne, Vallery Stanishev, Dat Q. Tran, Steffen Richter, Alexis Papamichail, Megan Stokey, Preston Sorensen, Ufuk Kilic, Mathias Schubert, Plamen P. Paskov, Vanya Darakchieva
Department of Electrical and Computer Engineering: Faculty Publications
Electron effective mass is a fundamental material parameter defining the free charge carrier transport properties, but it is very challenging to be experimentally determined at high temperatures relevant to device operation. In this work, we obtain the electron effective mass parameters in a Si-doped GaN bulk substrate and epitaxial layers from terahertz (THz) and mid-infrared (MIR) optical Hall effect (OHE) measurements in the temperature range of 38–340 K. The OHE data are analyzed using the well-accepted Drude model to account for the free charge carrier contributions. A strong temperature dependence of the electron effective mass parameter in both bulk and …
Unsupervised Blstm-Based Electricity Theft Detection With Training Data Contaminated, Qiushi Liang, Shengjie Zhao, Jiangfan Zhang, Hao Deng
Unsupervised Blstm-Based Electricity Theft Detection With Training Data Contaminated, Qiushi Liang, Shengjie Zhao, Jiangfan Zhang, Hao Deng
Electrical and Computer Engineering Faculty Research & Creative Works
Electricity theft can cause economic damage and even increase the risk of outage. Recently, many methods have implemented electricity theft detection on smart meter data. However, how to conduct detection on the dataset without any label still remains challenging. In this article, we propose a novel unsupervised two-stage approach under the assumption that the training set is contaminated by attacks. Specifically, the method consists of two stages: (1) a Gaussian mixture model is employed to cluster consumption patterns with respect to different habits of electricity usage, and with the goal of improving the accuracy of the model in the posterior …
Machiavellianism And Security: Leveraging Queries At Llms For Black Hat Operations, Niroop Sugunaraj, Prakash Ranganathan
Machiavellianism And Security: Leveraging Queries At Llms For Black Hat Operations, Niroop Sugunaraj, Prakash Ranganathan
Electrical Engineering Posters and Presentations
Critical infrastructure like the power grid are at risk from increasing cyber threats due to the growth of distributed energy resources ( relying heavily on internet connectivity Compromised DER endpoints are susceptible to cyber attacks and it is important to first identify evolving cybersecurity issues in widely deployed architectures, communication protocols, and networks Information produced from artificial intelligence ( based co pilots are emerging threats that can offer convenient and detailed playbooks to compromise DERs through multiple attack vectors even for a non technical black hat community and should therefore be considered as a repository for unethical hackers
Detection And Classification Of Sporadic E Using Convolutional Neural Networks, J. A. Ellis, Daniel J. Emmons, M. B. Cohen
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 (Es), 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
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 …
Capacitive Electrode Based Moisture Measurement Converter Errors And How To Eliminate Them, Hamdam Jabborov, Temurbek Rashidov
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 …