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Articles 69061 - 69090 of 291657

Full-Text Articles in Physical Sciences and Mathematics

Equichordal Tight Fusion Frames And Biangular Orthopartitionable Tight Frames, Benjamin R. Mayo Sep 2021

Equichordal Tight Fusion Frames And Biangular Orthopartitionable Tight Frames, Benjamin R. Mayo

Theses and Dissertations

An equichordal tight fusion frame (ECTFF) is a sequence of equidimensional subspaces of a Euclidean space that achieves equality in Conway, Hardin and Sloane's simplex bound, and so is a type of optimal Grassmannian code. In the special case where its subspaces have dimension one, an ECTFF corresponds to an equiangular tight frame (ETF); such frames have minimal coherence and so are useful for compressed sensing. More generally, an ECTFF will yield a frame with minimal block coherence when its subspaces are pairwise isoclinic, namely when it is an equi-isoclinic tight fusion frame (EITFF). In this dissertation, we generalize the …

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Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood Sep 2021

Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood

Theses and Dissertations

This research considers the problem of an intruder attempting to traverse a defender's territory in which the defender locates and employs disparate sets of resources to lower the probability of a successful intrusion. The research is conducted in the form of three related research components. The first component examines the problem in which the defender subdivides their territory into spatial stages and knows the plan of intrusion. Alternative resource-probability modeling techniques as well as variable bounding techniques are examined to improve the convergence of global solvers for this nonlinear, nonconvex optimization problem. The second component studies a similar problem but …

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Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge Sep 2021

Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge

Theses and Dissertations

Clustering weather data is a valuable endeavor in multiple respects. The results can be used in various ways within a larger weather prediction framework or could simply serve as an analytical tool for characterizing climatic differences of a particular region of interest. This research proposes a methodology for clustering geographic locations based on the similarity in shape of their temperature time series over a long time horizon of approximately 11 months. To this end an emerging and powerful class of clustering techniques that leverages deep learning, called deep representation clustering (DRC), are utilized. Moreover, a time series specific DRC algorithm …

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Improved Out-Of-Plane Brdf Measurement And Modeling, Todd V. Small Sep 2021

Improved Out-Of-Plane Brdf Measurement And Modeling, Todd V. Small

Theses and Dissertations

The bi-directional reflectance distribution function (BRDF) describes the directional (spatial) nature of light’s reflectance from a material surface. When incident light of a particular wavelength strikes a material surface from a particular direction, portions of that incident light will be reflected into various directions in various amounts, depending on the material’s surface characteristics. Historically, the vast majority of BRDF measurement and modeling research has focused on reflection within the plane-of incidence (in-plane) and dealt primarily with simplified isotropic BRDFs. Remote sensing applications, such as satellite light curve analysis, typically rely on closed-form microfacet models for efficiency. There are many factors, …

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Representing The Derivative Of Trace Of Holonomy, Jeffrey Peter Kroll Sep 2021

Representing The Derivative Of Trace Of Holonomy, Jeffrey Peter Kroll

Dissertations, Theses, and Capstone Projects

Trace of holonomy around a fixed loop defines a function on the space of unitary connections on a hermitian vector bundle over a Riemannian manifold. Using the derivative of trace of holonomy, the loop, and a flat unitary connection, a functional is defined on the vector space of twisted degree 1 cohomology classes with coefficients in skew-hermitian bundle endomorphisms. It is shown that this functional is obtained by pairing elements of cohomology with a degree 1 homology class built directly from the loop and equipped with a flat section obtained from the variation of holonomy around the loop. When the …

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Reproductive Characteristics Of Red Snapper Lutjanus Campechanus On Artificial Reefs In Different Jurisdictions, Catheline Y. M. Froehlich, Adam M. Lee, Ramiro Oquita, Carlos E. Cintra-Buenrostro, J. Dale Shively Sep 2021

Reproductive Characteristics Of Red Snapper Lutjanus Campechanus On Artificial Reefs In Different Jurisdictions, Catheline Y. M. Froehlich, Adam M. Lee, Ramiro Oquita, Carlos E. Cintra-Buenrostro, J. Dale Shively

School of Earth, Environmental, & Marine Sciences Faculty Publications

Reproductive activity of Red Snapper Lutjanus campechanus (Poey, 1860) at artificial reefs (ARs) are only recently being investigated. Yet, the management of the fishery differs on a regional basis with state and federal jurisdictions, and reproductive differences among regions have not been investigated. To compare the reproductive activity of L. campechanus among state (inshore) and federal (offshore) jurisdictions, individuals were collected in the northwestern Gulf of Mexico from four ARs on a quarterly basis for 2 yrs. Inshore sites exhibited fishing pressure year round whereas offshore sites only had fishing season open during a few months of summer. Collected individuals …

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Quartz Grain Microtextures Illuminate Pliocene Periglacial Sand Fluxes On The Antarctic Continental Margin, Sandra Passchier, Melissa A. Hansen, Jessica Rosenberg Sep 2021

Quartz Grain Microtextures Illuminate Pliocene Periglacial Sand Fluxes On The Antarctic Continental Margin, Sandra Passchier, Melissa A. Hansen, Jessica Rosenberg

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

On high-latitude continental margins sediment is supplied from land to the deep sea through a variety of processes, including iceberg and sea-ice rafting, and bottom current transport. The accurate reconstruction of sediment fluxes from these sources through time is important in palaeoclimate reconstructions. The goal of this study was to assess a shift in the intensity of glacial processes, iceberg and sea-ice rafting during the Pliocene through an investigation of coarse sediment deposited at the AND-2A site in the Ross Sea and at International Ocean Discovery Program Site U1359 on the Antarctic continental rise. Terrigenous particle-size distributions and suites of …

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A New Case Of Separability In A Quartic Hénon-Heiles System, Nicola Sottocornola Sep 2021

A New Case Of Separability In A Quartic Hénon-Heiles System, Nicola Sottocornola

All Works

There are four quartic integrable Hénon-Heiles systems. Only one of them has been separated in the generic form while the other three have been solved only for particular values of the constants. We consider two of them, related by a canonical transformation, and we give their separation coordinates in a new case.

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Advancing Proper Dataset Partitioning And Classification Of Visual Search And The Vigilance Decrement Using Eeg Deep Learning Algorithms, Alexander J. Kamrud Sep 2021

Advancing Proper Dataset Partitioning And Classification Of Visual Search And The Vigilance Decrement Using Eeg Deep Learning Algorithms, Alexander J. Kamrud

Theses and Dissertations

Electroencephalography (EEG) classification of visual search and vigilance tasks has vast potential in its benefits. In future human-machine teaming systems, EEG could act as the tool for operator state assessment, enabling AI teammates to know when to assist the operator in these tasks, with the potential to lead to increased safety of operations, better training systems for our operators, and improved operational effectiveness. This research investigates deep learning methods which utilize EEG signals to classify the efficiency of an operator's search and to classify whether an operator is in a decrement during a vigilance type task, and investigates performing these …

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Determining Physical Characteristics Through Information Leakage In 802.11ac Beamforming, Albert D. Taglieri Sep 2021

Determining Physical Characteristics Through Information Leakage In 802.11ac Beamforming, Albert D. Taglieri

Theses and Dissertations

The risk of information leakage in 802.11ac allows an eavesdropper to monitor wireless traffic and correlate physical locations between devices, as well as environment changes such as the motion of a person. Previous pattern-analysis mitigation methods, which used nonexistent devices to fool an eavesdropper, are not effective in an 802.11ac network, because devices on the network can be correlated to their physical location, which a nonexistent device does not have. Further, additional information about motion in the target environment can be observed and analyzed, providing a new potential for pattern analysis and sensing. 802.11ac makes it possible to plug in …

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Profiling Atmospheric Turbulence Using A Dynamically Ranged Rayleigh Beacon System, Steven M. Zuraski Sep 2021

Profiling Atmospheric Turbulence Using A Dynamically Ranged Rayleigh Beacon System, Steven M. Zuraski

Theses and Dissertations

The effect of turbulence on a long range imaging system manifest as an image blur effect usually quantified by the phase distortions present in a system. The blurring effect is conceivably understood on the basis of measured strength of atmospheric turbulence profiled within the propagation volume. One method for obtaining a turbulence strength profile is by use of a dynamically ranged Rayleigh beacon system that exploits strategically varied beacon ranges along the propagation path, effectively deducing estimates of specific path segment contributions of the blurring aberrations affecting an optical imaging system. A system utilizing this technique has been designed, and …

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Characterizing Convolutional Neural Network Early-Learning And Accelerating Non-Adaptive, First-Order Methods With Localized Lagrangian Restricted Memory Level Bundling, Benjamin O. Morris Sep 2021

Characterizing Convolutional Neural Network Early-Learning And Accelerating Non-Adaptive, First-Order Methods With Localized Lagrangian Restricted Memory Level Bundling, Benjamin O. Morris

Theses and Dissertations

This dissertation studies the underlying optimization problem encountered during the early-learning stages of convolutional neural networks and introduces a training algorithm competitive with existing state-of-the-art methods. First, a Design of Experiments method is introduced to systematically measure empirical second-order Lipschitz upper bound and region size estimates for local regions of convolutional neural network loss surfaces experienced during the early-learning stages. This method demonstrates that architecture choices can significantly impact the local loss surfaces traversed during training. Next, a Design of Experiments method is used to study the effects convolutional neural network architecture hyperparameters have on different optimization routines' abilities to …

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Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom Sep 2021

Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom

Theses and Dissertations

Space launch operations at Kennedy Space Center and Cape Canaveral Space Force Station (KSC/CCSFS) are complicated by unique requirements for near-real time determination of risk from lightning. Lightning forecast weather sensor networks produce data that are noisy, high volume, and high frequency time series for which traditional forecasting methods are often ill-suited. Current approaches result in significant residual uncertainties and consequentially may result in forecasting operational policies that are excessively conservative or inefficient. This work proposes a new methodology of wavelet-enabled semiparametric modeling to develop accurate and timely forecasts robust against chaotic functional data. Wavelets methods are first used to …

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Improvements To Emissive Plume And Shock Wave Diagnostics And Interpretation During Pulsed Laser Ablation Of Graphite, Timothy I. Calver Sep 2021

Improvements To Emissive Plume And Shock Wave Diagnostics And Interpretation During Pulsed Laser Ablation Of Graphite, Timothy I. Calver

Theses and Dissertations

This dissertation covers nanosecond pulsed laser ablation of graphite for 4-5.7 J/cm2 fluences with 248 nm and 532 nm lasers in 1-180 Torr helium, argon, nitrogen, air, and mixed gas. Three experiments were performed to improve the interpretation of common diagnostics used to characterize pulsed laser ablation, find simple but universal scaling relationships for comparing dynamics across different materials and ablation conditions, and provide a systematic analysis of graphite emissive plume and shock wave dynamics. A scaling of the Sedov-Taylor energy ratio was developed and validated for a range of studies despite differences in wavelength, pulse duration, fluence, and …

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Evaluation Of Wind Data Reliability By Using Logarithmic And Power Laws: A Case Study In Southern Iraq, Ahmed B. Khamees, Saif F. Yaseen, Khalid S. Heni, Mudar Ahmed Abdulsattar Aug 2021

Evaluation Of Wind Data Reliability By Using Logarithmic And Power Laws: A Case Study In Southern Iraq, Ahmed B. Khamees, Saif F. Yaseen, Khalid S. Heni, Mudar Ahmed Abdulsattar

Karbala International Journal of Modern Science

In this study, two sites were investigated in the southern region of Iraq: Ali AL-Gharbi and AL-Salman in Mesan and AL-Muthana provinces, respectively. A theoretical extrapolation between wind speed and height was carried out for both locations each month using the Logarithmic Law. Power Law was also applied to achieve calculations of wind shear coefficient (α) by using the actual data collected from the meteorological mast installed in each site at three levels of 10 m, 30 m, and 50 m, at an interval of ten minutes. To compare the effects of each law, two laws are employed.

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Polystyrene Molecular Weight Determination Of Submicron Particles Shell, Airat Z. Sakhabutdinov, Safaa.M.R.H. Hussein, Alsu R. Ibragimova Ph.D., Vladimir Kuklin Ph.D., Maxim Petrovich Danilaev, L.Y. Zaharova Aug 2021

Polystyrene Molecular Weight Determination Of Submicron Particles Shell, Airat Z. Sakhabutdinov, Safaa.M.R.H. Hussein, Alsu R. Ibragimova Ph.D., Vladimir Kuklin Ph.D., Maxim Petrovich Danilaev, L.Y. Zaharova

Karbala International Journal of Modern Science

The method of determination of the molecular weight of the polystyrene, which is formed as the shell on the surfaces of submicron aluminum oxide particles is considered in the paper. This method is based on the sedimentation of submicron particles, covered by polymer molecules, in a solvent for polystyrene. It is shown that the average polystyrene molecular weight is 39500±11250 amu, when the polymer shells on the surfaces of submicron particles (Al2O3) are formed by the vapor-phase method.

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Adaptive Reconstruction Of The Heterogeneous Scan Line Etm+ Correction Technique, Heba Kh. Abbas, Salema S. Salman, Rash Awad Abtan, Anwar H. Al-Saleh, Ali A. Al-Zuky Aug 2021

Adaptive Reconstruction Of The Heterogeneous Scan Line Etm+ Correction Technique, Heba Kh. Abbas, Salema S. Salman, Rash Awad Abtan, Anwar H. Al-Saleh, Ali A. Al-Zuky

Karbala International Journal of Modern Science

ETM+ is a land-imaging sensor with great and wide use in many fields, however, after May 2003, because of a technical defect in the sensor´s system scan line corrector SLC, it started giving images of earth containing black gap lines at a 22% rate. These gaps made the process of analyzing and extracting accurate information from these images difficult and complicated. Therefore, scientists have developed many techniques to remove the gap lines from all ETM+ band-images and complete the missing data. In this study, three different ETM+ time images with a 16-day interval between them were used to fill gap …

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Two-Dimensional Quantitative Profiling Of Cell Morphology With Serous Effusion By Unsupervised Machine Learning Analysis, Safaa Al-Qaysi Ph.D., Ding Dai Md Ph.D., Heng Hong Md Ph.D., Yuhua Wen Ph.D., X.H. Hu Ph.D. Aug 2021

Two-Dimensional Quantitative Profiling Of Cell Morphology With Serous Effusion By Unsupervised Machine Learning Analysis, Safaa Al-Qaysi Ph.D., Ding Dai Md Ph.D., Heng Hong Md Ph.D., Yuhua Wen Ph.D., X.H. Hu Ph.D.

Karbala International Journal of Modern Science

Cytological evaluation of serous effusion specimens is an important part of cancer diagnosis. In this study we performed two-dimensional (2D) morphometric features and clustering analysis for development of useful techniques for identification and differentiation of malignant and begin cells in serous effusion specimens extracted from ten patients with clinical symptoms of pleural and peritoneal effusion. Our findings show that the two-dimensional (2D) morphometric features and clustering analysis are useful techniques for identification and differentiation of malignant and begin cells in serous effusion specimens, which can lead to development of new methods for rapid cells profiling in clinical application.

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Modeling Vitexin And Isovitexin Flavones As Corrosion Inhibitors For Aluminium Metal, Abdullahi Muhammad Ayuba, Umaru Umar Aug 2021

Modeling Vitexin And Isovitexin Flavones As Corrosion Inhibitors For Aluminium Metal, Abdullahi Muhammad Ayuba, Umaru Umar

Karbala International Journal of Modern Science

Theoretically, the aluminium corrosion inhibitive performance of vitexin (VTX) and isovitexin (SVT) were evaluated with a view of establishing the mechanism of the inhibition process. Calculations which include the consideration of several global descriptors were studied to describe and correlate the reactivity of the molecules with the computed descriptors. First and second-order condensed Fukui functions were employed to analyze local reactivity parameters, while simulations involving the adsorbed molecules on Al (1 1 0) surface were conducted through quench dynamic simulations and the mechanism of physical adsorption was established with SVT relatively been a better inhibitor on Al surface than VTX.

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Stability-Delay Efficient Cluster-Based Routing Protocol For Vanet, Ahmed Jawad Kadhim Al-Shaibany Ph.D Aug 2021

Stability-Delay Efficient Cluster-Based Routing Protocol For Vanet, Ahmed Jawad Kadhim Al-Shaibany Ph.D

Karbala International Journal of Modern Science

Vehicular Ad hoc Network (VANET) can be used in safety applications to transfer information about some events (e.g. accidents) with minimum time. Sending this information is achieved by using a routing algorithm. A large number of cluster-based routing schemes were presented for VANET. Unfortunately, the mobility of vehicles in unexpected directions negatively affects the performance of these schemes, destroys the network links, and decreases the routes' stability. This problem leads to repeat route discovery and maintenance operations and, as a result increases the overhead and delay. Thus, they are not an optimal selection for safety applications. Moreover, the cluster-based policies …

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A New Chaotic Image Cryptosystem Based On Plaintext-Associated Mechanism And Integrated Confusion-Diffusion Operation, Ahmed Kareem Shibeeb, Mohammed Hussein Ahmed, Ahmed Hashim Mohammed Aug 2021

A New Chaotic Image Cryptosystem Based On Plaintext-Associated Mechanism And Integrated Confusion-Diffusion Operation, Ahmed Kareem Shibeeb, Mohammed Hussein Ahmed, Ahmed Hashim Mohammed

Karbala International Journal of Modern Science

In modern chaotic image cryptosystems, the initial values generated for the chaotic system are carried out based on the hash function or summation result of the image pixels. Also, the confusion-diffusion structure is often typically split into two different components. However, it decreases the cryptosystem security because the independent structure can be cryptanalysis separately. A practical chaotic image cryptosystem based on plaintext-associated mechanism and integrated confusion-diffusion operation has been developed in this research paper to enhance the encryption reliability. The initial values of the four-dimensional chaotic system are updated by using the pixel values and locations to increase the sensitivity …

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Editorial Board Aug 2021

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

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An Empirical Study Of Thermal Attacks On Edge Platforms, Tyler Holmes Aug 2021

An Empirical Study Of Thermal Attacks On Edge Platforms, Tyler Holmes

Symposium of Student Scholars

Cloud-edge systems are vulnerable to thermal attacks as the increased energy consumption may remain undetected, while occurring alongside normal, CPU-intensive applications. The purpose of our research is to study thermal effects on modern edge systems. We also analyze how performance is affected from the increased heat and identify preventative measures. We speculate that due to the technology being a recent innovation, research on cloud-edge devices and thermal attacks is scarce. Other research focuses on server systems rather than edge platforms. In our paper, we use a Raspberry Pi 4 and a CPU-intensive application to represent thermal attacks on cloud-edge systems. …

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High Speed Impact On Graphene Composites, Giovanny A. Espitia Aug 2021

High Speed Impact On Graphene Composites, Giovanny A. Espitia

Symposium of Student Scholars

Since the isolation of Graphene occurred in 2004, numerous studies attempting to exploit the properties of this carbon allotrope have been conducted. Graphene exists in a 2-D manner with sp2 bonds, which provides the allotrope with great electrical, conductive, and mechanical properties. In this paper however, we will focus on the latter in order to examine the feasibility of graphene composites for bulletproof material in the military. Pure graphene sheets count with high porosity density that leads to structural defects as well as poor mechanical properties due to physical contact being sole retainer. For this reason, the selected composite is …

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Investigating The Proton Transfer Dynamics And Vibrational Spectrum Of Hydrogen Oxalate Using Driven Molecular Dynamics Simulations, Martina Kaledin, Dominick Pierre-Jacques, Olivia Cochran, Dayana Salazar, Dalton Boutwell, Martina Kaledin Aug 2021

Investigating The Proton Transfer Dynamics And Vibrational Spectrum Of Hydrogen Oxalate Using Driven Molecular Dynamics Simulations, Martina Kaledin, Dominick Pierre-Jacques, Olivia Cochran, Dayana Salazar, Dalton Boutwell, Martina Kaledin

Symposium of Student Scholars

In this computational chemistry work, we describe ab initio calculations and assignment of infrared (IR) spectra of an intramolecular H-bonding system hydrogen oxalate, C2O4H–. The mechanism and dynamics of proton transfer are of fundamental importance in chemistry and biology. In C2O4H–, proton transfer occurs along the non-linear path. Previous experimental studies are signaling very strong coupling between OH stretch mode and low frequency motions. We calculated IR spectra at 300 K using the direct molecular dynamics (MD) method at the MP2/ aug-cc-pVDZ level of theory and assigned the …

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Molecular Vibrations Of Symmetric Molecules: Raman Scattering Driven Molecular Dynamics Method, Martina Kaledin, Dominick Pierre-Jacques, Ciara Tyler, Jason Dyke Aug 2021

Molecular Vibrations Of Symmetric Molecules: Raman Scattering Driven Molecular Dynamics Method, Martina Kaledin, Dominick Pierre-Jacques, Ciara Tyler, Jason Dyke

Symposium of Student Scholars

This project focuses on developing a novel computational technique to study molecular vibrations through infrared (IR) and Raman scattering Driven Molecular Dynamics (DMD) method. While the main criterion for IR absorption is a net change in the dipole moment in a molecule as it vibrates, presently we wish to predict and analyze vibrational spectra to study symmetric vibrational modes that are IR inactive or weakly active while strongly Raman active. A newly developed method was tested on CO2, H2O, CH4, and C20 molecules. Students optimized the molecular structures, obtained vibrational frequencies, and IR …

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Therapeautic Cerium Oxide Nanoparticles, Angel E. Vasquez Aug 2021

Therapeautic Cerium Oxide Nanoparticles, Angel E. Vasquez

Symposium of Student Scholars

The overall goal of the research project is to create a glass that produces cerium oxide nanoparticles and as an efficient delivery mechanism. Cerium is able to exist as Ce3+ and Ce4+ because it has two partially filled subshells. This coexistence allows cerium oxide to have antioxidant properties that reduce the number of free radicals in that body that are associated with cancer, diabetes, and neurodegenerative diseases. In our laboratory, using a soluble borate glass, cerium oxide nanoparticles are created to coexist in Ce3+ and Ce4+ valences This borate glass composition is doped with different amounts of Cerium(IV) Oxide and …

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Physical Properties Of Polar Magnetic Oxides Hofewo6 Aug 2021

Physical Properties Of Polar Magnetic Oxides Hofewo6

Symposium of Student Scholars

Polar magnetic oxides are interesting systems to study due to the possibility of hosting functional properties such as ferroelectricity, piezoelectricity, etc. In this work, a new compound HoFeWO6 is synthesized using high-temperature solid-state reaction and characterized using x-ray diffraction, neutron diffraction, magnetization measurements, and dielectric measurements. The x-ray and neutron diffraction results indicate that HoFeWO6 crystallizes in polar (non-centrosymmetric and achiral) orthorhombic structure P n a 21. The magnetization measurements indicate that HoFeWO6 exhibit paramagnetic to antiferromagnetic transition at TN = 18 K. The dielectric properties at room temperature indicate that the dielectric constant decreases with …

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Learning Environment Containerization Of Machine Learning For Cybersecurity, Hao Zhang Aug 2021

Learning Environment Containerization Of Machine Learning For Cybersecurity, Hao Zhang

Symposium of Student Scholars

Machine learning plays a critical role in detecting and preventing in the field of cybersecurity. However, many students have difficulties on configuring the appropriate coding environment and retrieving datasets on their own computers, which, to some extent, wastes valuable time for learning core contents of machine learning and cybersecurity. In this paper, we propose an approach with learning environment containerization of machine learning algorithm and dataset. This will help students focus more on learning contents and have valuable hand-on experience through Docker container and get rid of the trouble of configuration coding environment and retrieve dataset. This paper provides an …

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Spam Email Detection: Comparison Between Naïve Bayes And Neural Network, Zhuolin Li Aug 2021

Spam Email Detection: Comparison Between Naïve Bayes And Neural Network, Zhuolin Li

Symposium of Student Scholars

Classification is an important technique to deal with cybersecurity threats. In this paper, we detect spam emails from publicly available dataset using Naive Bayes and Neural Network (NN). The results from experiments show that for data sets with more balanced for classification, the accuracy of Naive Bayes is better than NN

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