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Articles 61 - 90 of 1369
Full-Text Articles in Engineering
Investigation Of Spalart-Allmaras Turbulence Model For Vortex Flows, Abigail Rayna Kerestes
Investigation Of Spalart-Allmaras Turbulence Model For Vortex Flows, Abigail Rayna Kerestes
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Conventional turbulence models often predict behaviors opposite as to what is observed in flows subject to rotation. In this type of flow scenario, rotation typically induces turbulence suppression. To address this limitation, a modification to the Spalart Allmaras Model with Rotation Correction (SA-R) was proposed to enhance the original Spalart Allmaras Model’s sensitivity to rotation and curvature. To test the validity and accuracy of this modification, two cases were investigated. The first case involved an axisymmetric rotating pipe. A Reynolds Number of 37,000 was implemented and the initial and boundary conditions established by Zaets et. al. were utilized. Initially non-rotating, …
Understanding Impact Of Graph Structure On Knowledge Graph Embedding, Brandon Dave
Understanding Impact Of Graph Structure On Knowledge Graph Embedding, Brandon Dave
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The effectiveness of a deployed knowledge graph is commonly evaluated with defined use-cases from domain experts. This poses challenges during the development cycle in determining how to represent data. Developers of a knowledge graph can optionally include semantics into a knowledge graph by abstracting the data representation in such a way that mirrors information as it exists in the real world. Consequently, the abstraction is represented by additional layers, resulting in performant differences in knowledge graph embedding; such as, the embedded model's ability to infer facts between entities through link predictions. This thesis presents a comprehensive analysis of the performance …
Ai-Enabled Hardware Security Approach For Aging Classification And Manufacturer Identification Of Sram Pufs, Harshdeep Singh
Ai-Enabled Hardware Security Approach For Aging Classification And Manufacturer Identification Of Sram Pufs, Harshdeep Singh
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Semiconductor microelectronics integrated circuits (ICs) are increasingly integrated into modern life-critical applications, from intelligent infrastructure and consumer electronics to the Internet of Things (IoT) and advanced military and medical systems. Unfortunately, these applications are vulnerable to new hardware security attacks, including microelectronics counterfeits and hardware modification attacks. Physical Unclonable Functions (PUFs) are state-of-the-art hardware security solutions that utilize process variations of integrated circuits for device authentication, secret key generation, and microelectronics counterfeit detection. The negative impact of aging on Static Random Access Memory Physical Unclonable Functions (SRAM PUFs) has significant consequences for microelectronics authentication, security, and reliability. This research thoroughly …
Ml-Assisted Side Channel Security Approaches For Hardware Trojan Detection And Puf Modeling Attacks, Niraj Prasad Bhatta
Ml-Assisted Side Channel Security Approaches For Hardware Trojan Detection And Puf Modeling Attacks, Niraj Prasad Bhatta
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Hardware components are becoming prone to threats with increasing technological advances. Malicious modifications to such components are increasing and are known as hardware Trojans. Traditional approaches rely on functional assessments and are not sufficient to detect such malicious actions of Trojans. Machine learning (ML) assisted techniques play a vital role in the overall detection and improvement of Trojan. Our novel approach using various ML models brings an improvement in hardware Trojan identification with power signal side channel analysis. This study brings a paradigm shift in the improvement of Trojan detection in integrated circuits (ICs). In addition to this, our further …
Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick
Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick
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This research illustrates a high-security wireless communication method using a joint radar/communication waveform, addressing the vulnerability of traditional low probability of detection (LPD) waveforms to hostile receiver detection via cyclostationary processing (CSP). To mitigate this risk, RF steganography is used, concealing communication signals within linear frequency modulation (LFM) radar signals. The method integrates reduced phase-shift keying (RPSK) modulation and variable symbol duration, ensuring secure transmission while evading detection. Implementation is validated through software-defined radios (SDRs), demonstrating effectiveness in covert communication scenarios. Results include analysis of message reception and cyclostationary features, highlighting the method's ability to conceal messages from hostile receivers. …
Experimental Validation Of Two Highly Loaded Low Pressure Turbine Blades At High Speed Low Reynolds Number Conditions, Ryan Sauder
Experimental Validation Of Two Highly Loaded Low Pressure Turbine Blades At High Speed Low Reynolds Number Conditions, Ryan Sauder
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In the constant search for more efficient engines, one approach to gain performance is to reduce the weight of the low pressure turbine (LPT) module. This module can account for up to 30% of the total engine weight [1], and a reduction in LPT weight results in clear gains to engine performance and a reduction in engine cost. High lift airfoils accomplish this weight reduction by each blade extracting a larger amount of work from the flow and thus requiring fewer blades to drive the compressor when compared to conventional blades. However, high lift LPT blades, quantified by a high …
Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer
Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer
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Performing automatic target recognition (ATR) on full-size aircraft targets using inverse synthetic aperture radar (ISAR) data is challenging and expensive. The use of scale models and radar systems of such large targets saves time and reduces facility requirements. This study examines the feasibility of performing ATR on 1:144 scale model airplanes at Ka-band. The scale model and Ka-band radar simulate the collection of full-scale targets at VHF-band. The phase history measurement collections were completed in the Sensors and Signals Exploitation Laboratory (SSEL) at Wright State University. To ensure sufficient data for training and testing, the phase history data was augmented …
Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich
Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich
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To address the issues of limited target data in the Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) problem set, synthetic data is often used to aid in filling the gap. This paper covers an in depth look at the use of colorization, dynamic range adjustment, and target extraction as data augmentation techniques to improve the accuracy of deep learning networks trained on synthetic SAR data. The use of multiple different data augmentations combine to dramatically improve the accuracy of a common Convolutional Neural Network (CNN) over the use of standard synthetic data. A comparison of increasing fraction of measured …
Multi-Semantic-Stage Neural Networks For Robust And Interpretable Deep Learning, Christopher J. Menart
Multi-Semantic-Stage Neural Networks For Robust And Interpretable Deep Learning, Christopher J. Menart
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Deep neural networks have great representational power. However, most deep neural nets today optimize directly for performance on a single task defined only by labeled training data. This excludes potential sources of knowledge and ways of learning which could improve their performance, and address challenges, such as explainability, which are pressing to the field. We propose a framework for neural network architecture which generalizes it to a graph of many semantically-meaningful variables. We call it the Multi-Semantic-Stage Neural Network (MSSNN). An MSSNN models its domain as a web of conditional probabilities, i.e. a collection of inter-related tasks which can learn …
Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi
Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi
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Lithium-ion batteries are an integral component of energy storage systems for renewable energy applications owing to their high energy density. Extensive research has therefore been carried out, utilizing both experimental and computational methods, to aid in a deeper understanding of lithium-ion batteries. Challenges related to efficiency, safety and thermal management persist, particularly during high current draw, extreme temperature conditions and extreme dynamic current operation such as in electric vehicles. This thesis work presents an electrochemical-thermal model of a lithium-ion battery that simulates and analyzes the variation of electrical behavior, chemical behavior and thermal behavior. The electrochemical model is developed by …
Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson
Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson
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The uncertainty of the standard calibration procedure for radar cross-section (RCS) measurement is studied for different targets measured in the near-field from 550 to 700 GHz. Using common calibration spheres and squat cylinders mounted on a styrofoam pedestal at waterline (zero-degrees elevation), the calibration difference measure is determined for each target. Similarly, the difference metric is determined for square trihedral and tophat targets placed on a ground plane and measured at different elevation angles. The mean calibration measure is calculated using the dual calibration target method and repeated measurements in an anechoic chamber. The specific THz system is described and …
Pneumonia Detection With Limited And Imbalanced Data Using Energy-Based Out-Of-Distribution Technique, Jasbin Karki
Pneumonia Detection With Limited And Imbalanced Data Using Energy-Based Out-Of-Distribution Technique, Jasbin Karki
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The automated detection of pneumonia through chest X-ray presents a critical challenge in medical diagnostics, particularly due to the restrictions of limited and imbalanced chest X-ray data for training AI models. Traditional methods that depend on softmax confidence scores can be overconfident even when generating erroneous outputs especially when they are processing completely new inputs, leading to unreliable diagnostic results. This research addresses challenges in AI models which aim to develop a robust pneumonia detection system using an Energy-Based Out-of-Distribution (OOD) technique that can work effectively even with limited and imbalanced data. The study focused on creating a more reliable …
Test-Time Backdoor Attack Using Universal Perturbation, Jesse Alexander Smith
Test-Time Backdoor Attack Using Universal Perturbation, Jesse Alexander Smith
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The rapid growth and widespread reliance on machine learning (ML) systems across critical applications such as healthcare, autonomous driving, and cybersecurity have un- derscored their transformative potential and heightened their susceptibility to adversarial attacks and vulnerabilities. This thesis investigates vulnerabilities in ML models, focusing on backdoor attacks, including naive backdoor attack, feature collision backdoor attack, hidden trigger backdoor attack, and test-time backdoor attack using universal perturbation technique. These methodologies demonstrate how adversaries can automate and conceal malicious behaviors to achieve specific objectives, posing significant challenges to ML model integrity and trustworthiness. The research provides a comprehensive analysis of the theoretical …
Performance Degradation Of Gan Hemts Under Rf Aging: Implications For Wireless Communications Standards, Nathan Grant
Performance Degradation Of Gan Hemts Under Rf Aging: Implications For Wireless Communications Standards, Nathan Grant
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This study examines the aging effects of GaN HEMTs, focusing on the CG2H40010 device under conditions that mimic the high-power, high-frequency environments of wireless communication systems. With the increasing adoption of GaN technology in RF applications, understanding its degradation mechanisms under CW stress and modulated signal characterization is essential for predicting device lifetime and ensuring performance standards for modern communication systems. RFALT was employed to stress the device using CW signals, while key performance metrics, such as gain compression, gate leakage, ACP, and EVM, were assessed using W-CDMA signals to replicate real-world dynamic stresses. The findings reveal that CW stress …
Novel Approaches To Treatment Of Hyperexcitability In Skeletal Muscle, Phillip Vance Walker Ii
Novel Approaches To Treatment Of Hyperexcitability In Skeletal Muscle, Phillip Vance Walker Ii
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Myotonia Congenita (MC) is a rare, inherited ion channelopathy caused by a loss-of-function mutation in the CLCN1 gene. The resulting downregulation of the skeletal muscle chloride channel (ClC-1) results in hyperexcitable skeletal muscle fibers that fire action potentials involuntarily. Patients with MC suffer from debilitating stiffness due to myotonia, described clinically as delayed muscle relaxation following voluntary contraction. Skeletal muscle is a unique system we use in this study to advance our understanding of the pathophysiology underlying MC, and other channelopathies characterized by hyperexcitable cells (i.e., forms of epilepsy and cardiac arrhythmia). Furthermore, re-assessing what makes anti-myotonic drugs such as …
A Novel In-Vitro Approach To Investigate The Molecular Interaction Between Inhaled Particles And The Human Pulmonary Surfactant System, Bryan Mayville
A Novel In-Vitro Approach To Investigate The Molecular Interaction Between Inhaled Particles And The Human Pulmonary Surfactant System, Bryan Mayville
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The deployment of military personnel to austere environments poses significant pulmonary health risks from inhalation of particulates including sand, dust, pollution, and heavy machinery exhaust. When particles are less than 10 µm in diameter, they can penetrate deep within the alveoli and embed within the protective lung surfactant monolayer. Here, absorption of surfactant lipids to the particle surface disrupts the essential monolayer configuration needed to reduce surface tension and prevent atelectasis, thus leading to disease. Currently, there are no in vitro surfactant-producing lung cell models capable of studying the effects of inhaled particles on the human pulmonary surfactant system. A549 …
Insights Into Hyperkalemic Periodic Paralysis: Novel Mechanisms And Treatments, Christopher Dupont
Insights Into Hyperkalemic Periodic Paralysis: Novel Mechanisms And Treatments, Christopher Dupont
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Hyperkalemic Periodic Paralysis (hyperKPP) is an inherited channelopathy that leads to incapacitating episodes marked by severe skeletal muscle weakness or total paralysis, often accompanied by muscular stiffness (myotonia). The periods of muscle dysfunction are thought to be caused by the elevation in extracellular potassium (K). This autosomal dominant disorder is associated with mutations in the skeletal muscle voltage-gated sodium channel (Nav1.4). A multitude of inciting factors have been documented, including rest post-exertion, a potassium-rich diet, exposure to cold temperatures, psychological stressors, and fatigue. Given the variability of the triggers and the debilitating manifestation of symptoms, individuals afflicted by hyperKPP have …
Semantics-Aware Text-Guided Aerial Image Synthesis By Feature Augmented Diffusion Models, Douglas J. Townsell
Semantics-Aware Text-Guided Aerial Image Synthesis By Feature Augmented Diffusion Models, Douglas J. Townsell
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Aerial imagery provides crucial insights for various fields, including remote monitoring, environmental assessment, and autonomous navigation. However, the availability of aerial image datasets is limited due to privacy concerns and imbalanced data distribution, impeding the development of robust deep learning models. While recent text-guided generative models have shown promise in synthesizing high-quality images, they fall short in handling the unique challenges of aerial imagery, including densely packed objects, intricate spatial relationships, and the absence of paired text-aerial image datasets. To tackle these limitations, we propose STARS, a groundbreaking framework for Semantic-aware Text-guided Aerial image Refinement and Synthesis. STARS introduces a …
Comparative Analysis Of Motoneuronal C-Bouton Structural Alterations In Als And Aging, Shelby Nicole Ward
Comparative Analysis Of Motoneuronal C-Bouton Structural Alterations In Als And Aging, Shelby Nicole Ward
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Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by motor neuron (MN) death resulting in paralysis and eventually death. ALS has greater prevalence in older populations sharing characteristics with aging like muscle weakness and MN type specific degeneration. MNs innervate skeletal muscles and control muscle contraction through their excitability which is altered in both conditions. C-Boutons are a cholinergic, excitatory synaptic input to MNs and have been studied in ALS and aging but have produced inconsistent findings and undesired gaps. We used immunohistochemistry to label mouse lumbar spinal cord and separate MN types. 60x imaging and automated analysis was …
Sex-Driven Alterations In Aging Alpha Motoneurons: Exploring Size, Type, Density, And Kv2.1 Channel Expression, Kalin R. Gerber
Sex-Driven Alterations In Aging Alpha Motoneurons: Exploring Size, Type, Density, And Kv2.1 Channel Expression, Kalin R. Gerber
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This research explores how motor neurons (MNs) and Kv2.1 clustering change with age, emphasizing sex differences and MN subtypes. We found that MN density decreases with age in both sexes, while soma size increases in male mice. FF MNs were the most affected, and old weak mice had smaller MNs than their stronger counterparts, underscoring FF MN vulnerability. Baseline studies revealed that FF and FI MNs have larger Kv2.1 clusters compared to FR and S MNs. Female mice had smaller, denser Kv2.1 clusters than male mice, suggesting less clustering in females. With age, Kv2.1 clusters grew larger but became less …
Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, And Scarcity, Bradley T. Ashmore
Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, And Scarcity, Bradley T. Ashmore
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The digital landscape is ever-evolving. In recent years the amount of bot traffic, traffic generated by autonomous applications over the internet has increased significantly. Many bots perform useful and needed functions, however, malicious bots are known sources of both common and emerging security threats. Denial-of-Services (DoS), information theft, and credential stuffing have all been conducted by malicious software running on unknowingly infected machines. The dichotomy of useful bots operating in the same networks as malicious bots combined with novel bot attacks and an ever-increasing number of personal devices connecting to the Internet drives the need for continued advancement of malicious …
A Trusted Adversarial Ml Countermeasure Approach For Secure And Resilient Ai-Driven Hardware Trojan Detection, Mohammed G M Alkurdi
A Trusted Adversarial Ml Countermeasure Approach For Secure And Resilient Ai-Driven Hardware Trojan Detection, Mohammed G M Alkurdi
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Semiconductor microelectronics Integrated Circuits (ICs) are increasingly integrated into critical life applications including medical, aerospace, and Internet of things. Their increasing importance as a technology gave rise to critical concerns regarding their security. This has led to the focus of the research community on hardware Trojans, which are malicious modifications to the ICs with undesirable outcomes. Their detection is becoming increasingly critical, with many researchers proposing methods to do so such as reverse engineering, logic testing, and side-channel analysis. Many of these proposals utilize machine learning methods to detect these malicious modifications with high accuracy and confidence. However, machine learning …
Additively Manufactured Polymeric Surface-Based Lattice Structures For Vibration Attenuation, Imabin Kelvin Ekpelu
Additively Manufactured Polymeric Surface-Based Lattice Structures For Vibration Attenuation, Imabin Kelvin Ekpelu
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The focus of this study was to select triply periodic minimal surface (TPMS) structures made of 3D-printed polymers. The primary variables in this study were: TPMS shape, lattice volume ratio, and lattice material. Vibration absorption was characterized by damping ratio via transmissibility at the system’s natural frequency. The vibration testing was performed using an electro-dynamic shaker, a known mass, an input/control accelerometer, and an output/response accelerometer. The 3D-printed absorber/lattice was mounted to the shaker baseplate and a mass will be mounted on top of the absorber. One accelerometer will be mounted to the shaker baseplate and the other will be …
Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh
Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh
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The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. Increased reliance on IoT raised serious information security concerns. This dissertation presents three systems for analyzing and classifying IoT traffic using Deep Learning (DL) models, and a large dataset is built for systems training and evaluation. The first system studies the effect of combining raw data and engineered features to optimize the classification of encrypted and compressed IoT traffic using Engineered Features Classification (EFC), Raw Data Classification (RDC), and combined Raw Data and Engineered Features Classification (RDEFC) approaches. Our results demonstrate …
Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha
Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha
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Smart cities have emerged to tackle many critical problems that can thwart the overwhelming urbanization process, such as traffic jams, environmental pollution, expensive health care, and increasing energy demand. This Master thesis proposes efficient and high-quality cloud-based machine-learning solutions for efficient and sustainable smart cities environment. Different supervised machine-learning models for air quality predication (AQP) in efficient and sustainable smart cities environment is developed. For that, ML-based techniques are implemented using cloud-based solutions. For example, regression and classification methods are implemented using distributed cloud computing to forecast air execution time and accuracy of the implemented ML solution. These models are …
Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers
Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers
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Myotonia congenita is an inherited skeletal muscle disorder caused by loss-of-function mutation in the CLCN1 gene. This gene encodes the ClC-1 chloride channel, which is almost exclusively expressed in skeletal muscle where it acts to stabilize the resting membrane potential. Loss of this chloride channel leads to skeletal muscle hyperexcitability, resulting in involuntary muscle action potentials (myotonic discharges) seen clinically as muscle stiffness (myotonia). Stiffness affects the limb and facial muscles, though specific muscle involvement can vary between patients. Interestingly, respiratory distress is not part of this disease despite muscles of respiration such as the diaphragm muscle also carrying this …
Friend Or Foe? The Role Of Transforming Growth Factor-Β (Tgfβ) Signaling In Calcineurin Inhibitor-Induced Renal Damage, Adaku Uwe
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With its incorporation into clinical practice in the early 1980s, the class of pharmacological agents known as calcineurin inhibitors (CNIs) quickly became the cornerstone of immunosuppressive therapy post-organ transplantation. However, its use is limited by irreversible kidney damage in the form of renal fibrosis. The molecular mechanism by which CNIs induce renal fibrosis remains to be better understood, and to date, there are no specific therapeutic strategies to mitigate this damage. This dilemma presents a critical need to explain mechanisms by which CNIs cause renal damage. Kidneys of patients on chronic CNI therapy show increased expression of the proinflammatory cytokine …
Lipin1 Overexpression Ameliorates The Dystrophic Phenotype In Mdx Mice By Enhancing Myofiber Membrane Integrity, Abdullah Alshudukhi
Lipin1 Overexpression Ameliorates The Dystrophic Phenotype In Mdx Mice By Enhancing Myofiber Membrane Integrity, Abdullah Alshudukhi
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Duchenne muscular dystrophy (DMD) is a severe disease characterized by a progressive muscle fiber loss. DMD affects approximately 1 in 3500 male births worldwide. Patients die at early ages due to failure of respiratory and cardiac functions. DMD is caused by mutations in dystrophin gene. Loss of dystrophin leads to disruption of the membrane integrity and necroptosis in skeletal muscles of DMD patients contributing to muscle fiber loss. Currently, effective therapies for DMD have not been established. The goal of this project is to find mechanisms that may improve muscle function/structure despite dystrophin deficiency. Our data show that the expression …
Unfolding The Link Between The Axon Initial Segment, Endoplasmic Reticulum Stress, And Cognitive Impairment In Type 2 Diabetes, Jennae Shelby
Unfolding The Link Between The Axon Initial Segment, Endoplasmic Reticulum Stress, And Cognitive Impairment In Type 2 Diabetes, Jennae Shelby
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Dementia and mild cognitive impairment are well recognized comorbidities of type 2 diabetes, termed diabetic encephalopathy, that lack in course modifying treatment options. The axon initial segment (AIS) is a critical mediator of neuronal output. Shortening of AIS length has been shown to decrease neuronal excitability and is implicated in diabetic encephalopathy. AIS shortening may be reversible, hence investigating the mechanism responsible could address this significant gap in patient care by providing new therapeutic targets. Endoplasmic reticulum (ER) stress, a cellular condition that activates the unfolded protein response has been implicated in diabetic encephalopathy. Here, using immunocytochemistry in primary mouse …
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
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Identifying the version of the Solidity compiler used to create an Ethereum contract is a challenging task, especially when the contract bytecode is obfuscated and lacks explicit metadata. Ethereum bytecode is highly complex, as it is generated by the Solidity compiler, which translates high-level programming constructs into low-level, stack-based code. Additionally, the Solidity compiler undergoes frequent updates and modifications, resulting in continuous evolution of bytecode patterns. To address this challenge, we propose using deep learning models to analyze Ethereum bytecodes and infer the compiler version that produced them. A large number of Ethereum contracts and the corresponding compiler versions is …