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Biomechanical Simulation Of Cardiovascular Implantable Electronic Device Leads With Residual Properties, Anmar Mahdi Salih Jan 2024

Biomechanical Simulation Of Cardiovascular Implantable Electronic Device Leads With Residual Properties, Anmar Mahdi Salih

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Implantable leads used in pacemakers, defibrillators, and cardiac resynchronization therapy are designed for in-vivo applications, yet their longevity is inevitably shaped by the conditions within the human body. The mechanical behavior of these leads can be affected over time, necessitating the evaluation of their residual properties. Two main insulators, silicone, and polyurethane are commonly used for the outer insulation of cardiac leads. Understanding the long-term performance of these insulators is crucial for ensuring the reliability and safety of cardiac implantable devices. The research aims to assess the long-term mechanical properties and performance of implantable leads utilized in cardiovascular implantable electronic …

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A Spectrophotometric Determination Of Strontium Complexation With Methylthymol Blue, Adebayo Comlan Djanman Jan 2024

A Spectrophotometric Determination Of Strontium Complexation With Methylthymol Blue, Adebayo Comlan Djanman

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This study examines the complexation behavior of methylthymol blue (MTB) with strontium, particularly focusing on its application in addressing environmental concerns related to radiotoxic 90Sr. Using spectrophotometric techniques, the binding interactions were analyzed at pH = 7.50, 9.60, and 12.20. Results indicate that MTB forms a 1:1 complex with strontium at pH = 7.50, while at pH = 9.60 and 12.20 were assumed to influence complexation due to changes in ligand deprotonation and electrostatic interactions. Equilibrium constants (K1) = 22 (± 2) and molar absorptivities, ε1 = 6.3 x 10^3 (± 0.0008) L·mol⁻¹·cm⁻¹, and ε2 = 9.73 x (± 0.2)10^3 …

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Investigation Of Ion Pairing And Clustering Leading To The Nucleation Of Fluorite Using Ion Selective Electrode Potentiometry, Courtney L. Crone Jan 2024

Investigation Of Ion Pairing And Clustering Leading To The Nucleation Of Fluorite Using Ion Selective Electrode Potentiometry, Courtney L. Crone

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Previously, mineral nucleation was described by Classical Nucleation Theory (CNT), a theory based on the thermodynamic properties of bulk materials. However, an alternative model, known as the Prenucleation Cluster Pathway, has been increasingly used to describe nucleation of minerals. This model considers the presence of thermodynamically stable ion clusters known as “prenucleation clusters” (PNCs). In the present research, the nucleation mechanism of calcium fluoride was investigated to identify evidence of PNCs by means of the ion-selective electrode (ISE) method, where a CaCl2 solution was titrated into a NaF solution while investigating the effects of saturation level and the aqueous ratio …

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An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire Jan 2024

An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire

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Hardware Trojans are malicious circuits, hidden in integrated circuits (ICs) which pose a significant threat to security. Detection of hardware Trojans is important to build trust, verify, and make the semiconductor ICs process secure. The existing hardware Trojan detection methods are generally destructive, require intricate comparisons, or require a long time for reverse engineering. In the initial phase of this study, the substitution of supervised hardware Trojan detection methods in ASICs chips is explored with unsupervised approaches, thereby eliminating the dependence on golden references. The Trojan detection uses a ring oscillator (RO) based on NAND as the power monitor. Frequency …

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Examining The Effects Of Parameter Correlation And Its Implications For Models Of Learning And Retention: A Large Scale Model Validation : Examining The Effects Of Parameter Correlation And Its Implications For Models Of Learning Andretention: A Large Scale Model Validation, Michael Gordon Collins Jan 2024

Examining The Effects Of Parameter Correlation And Its Implications For Models Of Learning And Retention: A Large Scale Model Validation : Examining The Effects Of Parameter Correlation And Its Implications For Models Of Learning Andretention: A Large Scale Model Validation, Michael Gordon Collins

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Mathematical models of learning and retention have long been developed in psychology for both basic and applied research. For basic research, models of learning and retention attempt to explain how individuals acquire and retain information over time. While for applied research, models of learning and retention are used to inform education and training decisions. In both of these applications, the primary purpose of using a model is to fit and predict the performance of individuals. However, little attention has been paid to the interpretation of a model’s free parameters (i.e., learning and decay rates) and the effect that a model’s …

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Investigation Of Spalart-Allmaras Turbulence Model For Vortex Flows, Abigail Rayna Kerestes Jan 2024

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, …

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Understanding Impact Of Graph Structure On Knowledge Graph Embedding, Brandon Dave Jan 2024

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 …

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Seismic Refraction Mapping Of The Pre-Glacial Teays River Valley In West Central Ohio Using A Seismic Reflection Dataset, Matthew L. Klempp Ii Jan 2024

Seismic Refraction Mapping Of The Pre-Glacial Teays River Valley In West Central Ohio Using A Seismic Reflection Dataset, Matthew L. Klempp Ii

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The Teays River Valley is an ancient river valley system that existed before the Pleistocene Ice Age and spanned present-day Illinois, Indiana, Ohio, West Virginia, and Virginia. During the Pleistocene Ice Age, the Teays River Valley was buried by advancing continental glaciers and meltwater throughout most of its length. Due to the Teays’ average width of roughly 2 miles and burial depth of approximately 200 meters (656 feet), the Ohio Geological Survey has been pursuing geophysical methods to map the location and depth of the Teays River Valley in Ohio. The present study is a refraction analysis using the first …

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Ai-Enabled Hardware Security Approach For Aging Classification And Manufacturer Identification Of Sram Pufs, Harshdeep Singh Jan 2024

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 …

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Ml-Assisted Side Channel Security Approaches For Hardware Trojan Detection And Puf Modeling Attacks, Niraj Prasad Bhatta Jan 2024

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 …

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Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick Jan 2024

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. …

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Investigating Calcium Levels During Excitation-Contraction Coupling In Model Huntington's Disease Skeletal Muscle, Pooneh Hajmirza Mohammadi Kamalabadi Jan 2024

Investigating Calcium Levels During Excitation-Contraction Coupling In Model Huntington's Disease Skeletal Muscle, Pooneh Hajmirza Mohammadi Kamalabadi

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One of the less studied aspects of Huntington’s disease (HD) is its impact on skeletal muscle function. Recent studies have suggested that HD patients exhibit altered muscle function and reduced muscle strength, which may be related to defects in Ca2+ handling during excitation-contraction coupling (ECC). However, the underlying mechanisms of these alterations remain poorly understood. This study aims to determine if the myoplasmic Ca2+ during ECC is reduced in late-stage R6/2 (mouse model of HD) muscle fibers compared to age-matched controls during twitch or tetanic stimulation. Such a decrease would help explain weakness or fatigue in the model HD muscle. …

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Effects Of Geometric Isomerism On Benzothiazole-Carbazole Based Tadf Emitters In Poly(Arylene Ether)S, Grace Olive Jan 2024

Effects Of Geometric Isomerism On Benzothiazole-Carbazole Based Tadf Emitters In Poly(Arylene Ether)S, Grace Olive

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Thermally activated delayed fluorescence (TADF) small molecules have dominated the literature for their use in OLED devices. The use of TADF polymers has been employed to correct for processing issues that small molecules face, providing increased thermal stability and supportive electronic structures. A TADF chromophore based on a 2-(2,6-difluorophenyl)-benzothiazole-carbazole donor-acceptor pair was synthesized via a copper (I) catalyzed reaction. The chromophore exhibited peak absorption at 340 nm and emission at 477 nm. The resulting chromophore was incorporated into a poly(arylene ether) (PAE) backbone via nucleophilic aromatic substitution (NAS) with 4,4’-biphenol, 4,4’-difluorodiphenyl sulfone, and 2-(2,6-difluorophenyl)-benzothiazole as comonomers. UV/Vis analysis of the …

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Distribution And Fate Of Selected Non-Point Source Pollutants In The Dayton Streams And Tributaries: Effect Of Land Use In An Urban Watershed, Smriti Bastakoti Jan 2024

Distribution And Fate Of Selected Non-Point Source Pollutants In The Dayton Streams And Tributaries: Effect Of Land Use In An Urban Watershed, Smriti Bastakoti

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This study investigates the distribution of water pollutants in the urban and suburban watershed (Beavercreek Sub-watershed (BCS) and Little Beavercreek Sub-watershed (LBS)) of Dayton, Ohio USA focusing on the relationship between water quality and land use types based on 2021 land use maps obtained from MRLC. These watersheds are home for aquatic life and regulate the flow of surface water and recharge groundwater so, it is crucial to maintain good water quality by balancing urbanization and farmland within these two watersheds. We analyzed chloride, nitrate, and sulfate using ion chromatography (IC) and orthophosphate using UV/Vis Spectrophotometry. Additionally, three pesticides (Atrazine, …

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Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer Jan 2024

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 …

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Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich Jan 2024

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 …

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Multi-Semantic-Stage Neural Networks For Robust And Interpretable Deep Learning, Christopher J. Menart Jan 2024

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 …

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Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi Jan 2024

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 …

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Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson Jan 2024

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 …

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Pneumonia Detection With Limited And Imbalanced Data Using Energy-Based Out-Of-Distribution Technique, Jasbin Karki Jan 2024

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 …

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Test-Time Backdoor Attack Using Universal Perturbation, Jesse Alexander Smith Jan 2024

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 …

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Semantics-Aware Text-Guided Aerial Image Synthesis By Feature Augmented Diffusion Models, Douglas J. Townsell Jan 2024

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 …

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Development Of Sulfur-Based N-Heterocyclic Carbenes And Their Potential Energy Applications, Kalpana Sampath Jan 2024

Development Of Sulfur-Based N-Heterocyclic Carbenes And Their Potential Energy Applications, Kalpana Sampath

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N-heterocyclic carbenes (NHCs), a characteristic 5-membered ring structure, contain a carbene carbon and at least one nitrogen atom. The presence of nitrogen atoms in the cyclic structure has two effects on its electronic structure: it withdraws σ-electrons and donates π-electrons to the carbene carbon, significantly enhancing the electronic richness and stability of the carbene center. Incorporating heteroatoms like sulfur, oxygen, or phosphorus into the NHC framework has paved the way for advanced developments in their structural properties. The incorporation of additional aromatic ring/heteroatom into NHC offers novel pathways for functionalization, ultimately broadening its scope of potential applications. The primary goal …

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Functionalized 1,4-Naphthoquinone-Annulated N-Heterocyclic Carbenes For Biomedical Applications, Dilsha Samanali Wickramasinghe Jan 2024

Functionalized 1,4-Naphthoquinone-Annulated N-Heterocyclic Carbenes For Biomedical Applications, Dilsha Samanali Wickramasinghe

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Gold has long been recognized for its medicinal applications, dating back centuries. The use of N-heterocyclic carbenes (NHCs), stable, tunable ligands, has revolutionized the development of metal complexes, particularly those involving gold. Among these, Au-NHC complexes have shown significant promise in treating various diseases, especially arthritis and cancer. More recently, our research has focused on synthesizing dual-targeting naphthoquinone-annulated NHC-based gold(I) complexes, which have demonstrated impressive therapeutic potential in cancer treatment. This emphasizes the growing importance of gold-based complexes in developing more selective and effective cancer therapies. By strategically tuning the electronic and steric properties of these complexes, we have explored …

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Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, And Scarcity, Bradley T. Ashmore Jan 2024

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 …

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Investigating The Effects Of Human Astroviruses On Aquaporins And Tight Junction Proteins In Vitro, Makalia T. Robinson Jan 2024

Investigating The Effects Of Human Astroviruses On Aquaporins And Tight Junction Proteins In Vitro, Makalia T. Robinson

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Human Astroviruses (HAstV) are positive sense non-enveloped single stranded RNA viruses. HAstV is divided into classical (serotype 1-8) and non-classical (HAstVMLB 1-3 and HAstV-VA1-5) astroviruses. Classical HAstV is known to cause diarrhea in children, elderly, and immunocompromised patients. Additionally, the etiology of nonclassical HAstV remains unknown. However, recent studies have implicated non-classical HAstV closely associated with immunocompromised patients diagnosed neurological diseases like acute encephalitis. The mechanisms by which HAstV cause diarrhea is currently unknown. Aquaporins (AQPs) are integral membrane proteins that regulate the movement of water and small uncharged molecules across the cell membrane in response to osmotic gradients. Tight …

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A Trusted Adversarial Ml Countermeasure Approach For Secure And Resilient Ai-Driven Hardware Trojan Detection, Mohammed G M Alkurdi Jan 2024

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 …

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Role Of Urban Parks In Carbon Sequestration– A Case Study Of Safari Park, Karachi, Pakistan, Amna Bano, Minzah Shehzad, Hasnain Kazmi, Jamshaid Iqbal Dec 2023

Role Of Urban Parks In Carbon Sequestration– A Case Study Of Safari Park, Karachi, Pakistan, Amna Bano, Minzah Shehzad, Hasnain Kazmi, Jamshaid Iqbal

Journal of Bioresource Management

Urban parks besides their recreational use can be the potential source of climate mitigation through carbon sequestration. Present study aims to identify the carbon sequestration potential of Safari Park which is by far the largest public park of Karachi established in 1970 covering an area of 0.72 km2. A total of 153 individual trees belonging to 25 species and 14 families were included in the study. Five dominant species with highest Important Value Index (IVI) were Cocos nucifera (14.62 %), Azadirachta indica (14.21 %), Guaiacum officinale (9.93 %), Washington robusta (9.31 %) and Delonix regia (7.11 %). The …

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College Of Graduate Programs And Honors Studies Newsletter - December 2023, College Of Graduate Programs And Honors Studies, Wright State University Dec 2023

College Of Graduate Programs And Honors Studies Newsletter - December 2023, College Of Graduate Programs And Honors Studies, Wright State University

College of Graduate Programs and Honors Studies Newsletter

A five page newsletter created by the College of Graduate Programs and Honors Studies at Wright State University. This newsletter includes a upcoming events, message from the dean, and more.

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Cvii: Enhancing Interpretability In Intelligent Sensor Systems Via Computer Vision Interpretability Index, Hossein Mohammadi, Krishnaprasad Thirunarayan, Lingwei Chen Dec 2023

Cvii: Enhancing Interpretability In Intelligent Sensor Systems Via Computer Vision Interpretability Index, Hossein Mohammadi, Krishnaprasad Thirunarayan, Lingwei Chen

Computer Science and Engineering Faculty Publications

In the realm of intelligent sensor systems, the dependence on Artificial Intelligence (AI) applications has heightened the importance of interpretability. This is particularly critical for opaque models such as Deep Neural Networks (DNN), as understanding their decisions is essential, not only for ethical and regulatory compliance, but also for fostering trust in AI-driven outcomes. This paper introduces the novel concept of a Computer Vision Interpretability Index (CVII). The CVII framework is designed to emulate human cognitive processes, specifically in tasks related to vision. It addresses the intricate challenge of quantifying interpretability, a task that is inherently subjective and varies across …

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