Physical Sciences and Mathematics Commons^™

How Viscosity Of An Asphalt Binder Depends On Temperature: Theoretical Explanation Of An Empirical Dependence, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich

Departmental Technical Reports (CS)

Pavement must be adequate for all the temperatures, ranging from the winter cold to the summer heat. In particular, this means that for all possible temperatures, the viscosity of the asphalt binder must stay within the desired bounds. To predict how the designed pavement will behave under different temperatures, it is desirable to have a general idea of how viscosity changes with temperature. Pavement engineers have come up with an empirical approximate formula describing this change. However, since this formula is purely empirical, with no theoretical justification, practitioners are often somewhat reluctant to depend on this formula. In this paper, …

Why In Mond -- Alternative Gravitation Theory -- A Specific Formula Works The Best: Complexity-Based Explanation, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Based on the rotation of the stars around a galaxy center, one can estimate the corresponding gravitational acceleration -- which turns out to be much larger than what Newton's theory predicts based on the masses of all visible objects. The majority of physicists believe that this discrepancy indicates the presence of "dark" matter, but this idea has some unsolved problems. An alternative idea -- known as Modified Newtonian Dynamics (MOND, for short) is that for galaxy-size distances, Newton's gravitation theory needs to be modified. One of the most effective versions of this idea uses so-called simple interpolating function. In this …

Non-Localized Physical Processes Can Help Speed Up Computations, Be It Hidden Variables In Quantum Physics Or Non-Localized Energy In General Relativity, Michael Zakharevich, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

While most physical processes are localized -- in the sense that each event can only affect events in its close vicinity -- many physicists believe that some processes are non-local. These beliefs range from more heretic -- such as hidden variables in quantum physics -- to more widely accepted, such as the non-local character of energy in General Relativity. In this paper, we attract attention to the fact that non-local processes bring in the possibility of drastically speeding up computations.

Graph Approach To Uncertainty Quantification, Hector A. Reyes, Cliff Joslyn, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional analysis of uncertainty of the result of data processing assumes that all measurement errors are independent. In reality, there may be common factor affecting these errors, so these errors may be dependent. In such cases, the independence assumption may lead to underestimation of uncertainty. In such cases, a guaranteed way to be on the safe side is to make no assumption about independence at all. In practice, however, we may have information that a few pairs of measurement errors are indeed independent -- while we still have no information about all other pairs. Alternatively, we may suspect that for …

Systems Approach Explains Why Low Heart Rate Variability Is Correlated With Depression (And Suicidal Thoughts), Francisco Zapata, Eric Smith, Vladik Kreinovich

Departmental Technical Reports (CS)

Depression is a serious medical problem. If diagnosed early, it can usually be cured, but if left undetected, it can lead to suicidal thoughts and behavior. The early stages of depression are difficult to diagnose. Recently, researchers found a promising approach to such diagnosis -- it turns out that depression is correlated with low heart rate variability. In this paper, we show that the general systems approach can explain this empirical relation.

An Argument In Favor Of Piecewise-Constant Membership Functions, Marina Tuyako Mizukoshi, Weldon Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Theoretically, we can have membership functions of arbitrary shape. However, in practice, at any given moment of time, we can only represent finitely many parameters in a computer. As a result, we usually restrict ourselves to finite-parametric families of membership functions. The most widely used families are piecewise linear ones, e.g., triangular and trapezoid membership functions. The problem with these families is that if we know a nonlinear relation y = f(x) between quantities, the corresponding relation between membership functions is only approximate -- since for piecewise linear membership functions for x, the resulting membership function for y is not …

Which Interval-Valued Alternatives Are Possibly Optimal If We Use Hurwicz Criterion, Marina Tuyako Mizukoshi, Weldon Lodwick, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, for each alternative i, we do not know the corresponding gain xi, we only know the interval [li,ui] of possible gains. In such situations, a reasonable way to select an alternative is to choose some value α from the interval [0,1] and select the alternative i for which the Hurwicz combination α*ui + (1 − α)*li is the largest possible. In situations when we do not know the user's α, a reasonable idea is to select all alternatives that are optimal for some α. In this paper, we describe a feasible algorithm for such a selection.

Standard Interval Computation Algorithm Is Not Inclusion-Monotonic: Examples, Marina Tuyako Mizukoshi, Weldon Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

When we usually process data, we, in effect, implicitly assume that we know the exact values of all the inputs. In practice, these values comes from measurements, and measurements are never absolutely accurate. In many cases, the only information about the actual (unknown) values of each input is that this value belongs to an appropriate interval. Under this interval uncertainty, we need to compute the range of all possible results of applying the data processing algorithm when the inputs are in these intervals. In general, the problem of exactly computing this range is NP-hard, which means that in feasible time, …

Epistemic Vs. Aleatory: Case Of Interval Uncertainty, Marina Tuyako Mizukoshi, Weldon Lodwick, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

Interval computations usually deal with the case of epistemic uncertainty, when the only information that we have about a value of a quantity is that this value is contained in a given interval. However, intervals can also represent aleatory uncertainty -- when we know that each value from this interval is actually attained for some object at some moment of time. In this paper, we analyze how to take such aleatory uncertainty into account when processing data. We show that in case when different quantities are independent, we can use the same formulas for dealing with aleatory uncertainty as we …

Will Nanotechnology Bring In The Judgement Day?, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

There are many current and prospective positive aspects of nanotechnology. However, while we look forward to its future successes, we need to keep our eyes open and be prepared for what will really be a future shock: that quantum computing – an inevitable part of nanotechnology – will enable the future folks to read all our encrypted messages and thus, learn everything that we wanted to keep secret. This will be really the Judgement Day, when all our sins will be open to everyone. How we will react to it? Will this destroy our civilization? Let us hope that the …

Sulfonated Styrene Grafted Sebs/Abs Made By Additive Manufacturing For Ion Exchange Applications, Avianna Elaine Gallegos

Open Access Theses & Dissertations

An interpenetrating polymer network (IPN) for cation exchange applications was synthesized from a blend of styrene-ethylene/butylene-styrene (SEBS) and acrylonitrile butadiene styrene (ABS), which was 3D printed, grafted with crosslinked polystyrene (PS), and sulfonated. A method for styrene grafting was applied to reduce the damage to polymer phases caused by the sulfonation reaction. Styrene and divinylbenzene monomers were introduced to the IPN and induced with heat treatment to polymerize in situ. The graft copolymerization reaction was enhanced with varying quantities of benzoyl peroxide as a chemical initiator. The samples were subsequently sulfonated with chlorosulfonic acid in dichloroethane and functionalized for ion …

Achieving Safe Use Of Advanced Materials In Drinking Water Through Novel Nano Analytics And Enabling Electrification Using Green Catalyst, Kenneth Ray Flores

Open Access Theses & Dissertations

The accumulation of engineered nanomaterials (ENMs) in environmental sectors will continue to increase as more applications are discovered for their unique properties and characteristics. Additionally, the presence of nanomaterials in the environment becomes exacerbated as more consumer products containing nanoparticles are approved for use. It is debated whether the toxic effects of nanoparticles stem from the particles themselves, ionic species, or formation of secondary particles. Therefore, understanding the behavior of nanoparticles in the environment becomes key to discerning the toxicological effects of nanoparticles. Many advancements have been made with ICP-MS to understand the behavior of nanoparticles in the environmental systems, …

Classification Of Nuclear Pastas Through Alpha Shapes Model, Daniela Ramirez Chavez

Open Access Theses & Dissertations

The nuclear pasta is important because is an astromaterial with incredible strength that may be a source for gravitational waves, which observe from the rotation of neutron stars. The characterization of the pasta is vital because the nuclear phases have transport properties - compressibility, neutrino opacity, thermal conductivity, and electrical conductivity - associated with their shape for which neutron stars may be sensitive. These properties could interpret observations of supernova neutrinos, magnetic field decay, and crust cooling of accreting neutron stars. Here, we study the nuclear pasta using alpha shapes to achieve a phase characterization with the Minkowski functionals (area, …

Time Series Classification With Multistage Modeling Using Deep Learning, James Arthur

Open Access Theses & Dissertations

Time series classification (TSC) can be efficiently implemented with several techniques. Many techniques are based on analyzing 1-D signals in the time series data. In this work, we make an intrinsic analytical implementation of a new time series classification that involves a two-stage process. Firstly, by using Recurrence Plots (RP), we transform the time series into 2D images. The second stage consists in taking advantage of deep learn- ing models to perform our classification. The image illustration of time series introduces different feature types that are not available for all 1D signals, and therefore our classifi- cation problem is treated …

Region Detection & Segmentation Of Nissl-Stained Rat Brain Tissue, Alexandro Arnal

Open Access Theses & Dissertations

People who analyze images of biological tissue rely on the segmentation of structures as a preliminary step. In particular, laboratories studying the rat brain delineate brain regions to position scientific findings on a brain atlas to propose hypotheses about the rat brain and, ultimately, the human brain. Our work intersects with the preliminary step of delineating regions in images of brain tissue via computational methods.

We investigate pixel-wise classification or segmentation of brain regions using ten histological images of brain tissue sections stained for Nissl substance. We present a deep learning approach that uses the fully convolutional neural network, U-Net, …

Glacier Segmentation From Remote Sensing Imagery Using Deep Learning, Bibek Aryal

Open Access Theses & Dissertations

Large-scale study of glaciers improves our understanding of global glacier change and is imperative for monitoring the ecological environment, preventing disasters, and studying the effects of global climate change. In recent years, remote sensing imagery has been preferred over riskier and resource-intensive field visits for tracking landscape level changes like glaciers. However, periodic manual labeling of glaciers over a large area is not feasible due to the considerable amount of time it requires while automatic segmentation of glaciers has its own set of challenges. Our work aims to study the challenges associated with segmentation of glaciers from remote sensing imagery …

Online/Incremental Learning To Mitigate Concept Drift In Network Traffic Classification, Alberto R. De La Rosa

Open Access Theses & Dissertations

Communication networks play a large role in our everyday lives. COVID19 pandemic in 2020 highlighted their importance as most jobs had to be moved to remote work environments. It is possible that the spread of the virus, the death toll, and the economic consequences would have been much worse without communication networks. To remove sole dependence on one equipment vendor, networks are heterogeneous by design. Due to this, as well as their increasing size, network management has become overwhelming for network managers. For this reason, automating network management will have a significant positive impact. Machine learning and software defined networking …

Nano-Engineered Soft Magnets: Potential Application In Water Treatment, Hyperthermia And Molecular (Organic) Magnets, Yohannes Weldemariam Getahun

Open Access Theses & Dissertations

Scrutinizing the remarkable and tunable properties of magnetic materials at a nanoscale size "There's Plenty of Room at the Bottom..." Richard Feynman, this study attempts to find sustainable solutions to some of the deteriorating environmental, health, and energy problems the world is encountering. Due to their simple preparation, surface adaptability, and tunable magnetic and optical properties, magnetic nanoparticles have been extensively investigated in water treatment, cancer therapy, data storage, and more. However, relying on non-reusable and chemical-based treatment agents in water, complex and costly cancer treatment procedures and molecular magnets that operate far below room temperature limited those attempts from …

Evaluation Of Effect Of Preprocessing Algorithms On Resting State Fmri Data, Hortencia Josefina Hernandez

Open Access Theses & Dissertations

Graph theory modeling is a common modeling approach in neurobiology research studies. These models are useful since they describe patterns of connection for regions of interest in the brain using resting state fMRI images. The standard rule of thumb is to threshold the observed activation levels prior to model building. It is reasonable to assume that the use of this threshold affects the statistical distribution of commonly reported centrality metrics from the graph theory model, such as degree, betweenness, and closeness. In this study we examine the differential effect of using the standard approaches versus alternative direct thresholds and incorporation …

Application Of Flo-Sic To F-Electron Systems: Sixth Row Elements And Ligated Molecules, Alexander Irun Johnson

Open Access Theses & Dissertations

Density functional theory - the most widely used theoretical method to study atoms,molecules, and solids - suffers from the well-known self-interaction error. A solution to the problem was suggested by Perdew and Zunger [1], who showed the self-interaction error can be removed with self-interaction correction. In 2014, Pederson showed a unitary transformation can be performed on the Kohn-Sham orbitals to generate Fermi-Löwdin orbitals which improve atomization energies, and avoid the computational costs of solving the localization equations.[2] This method is known as the Fermi-Löwdin Orbital Self-Interaction Correction (FLO-SIC). Until now, the FLO-SIC methodology has been used for atoms not containing …

Black And Brown Carbon Optical Characterization In The El Paso - Ciudad Juarez Airshed, Pamela I. Lara

Open Access Theses & Dissertations

Black (EBC) and Brown (BrC) Carbon are ubiquitous constituents of atmospheric particulate matter that affect peopleâ??s health, disrupt ecosystems, and modulate local and global climate. Tracking the local deposition and sources of these aerosol particles is essential to better understanding their multidimensional environmental impact. The main goal of the current study is to measure the absorption coefficient (Babs) of particles within the Planetary Boundary Layer (PBL) of the El Paso (US)–Ciudad Juárez (Mexico) airshed and assess the contribution of black and brown carbon particles to the total optical absorption. Measurements were taken during winter (January, 2022), spring (May, 2022), and …

The Qualification Of Sealability And Creep Relaxation Of Additively Manufactured Zytel Gaskets For Pem Fuel Cells, Robert Lazarin

Open Access Theses & Dissertations

The purpose of this thesis is to study the feasibility of low-cost additive manufacturing of gaskets for proton exchange membrane fuel cells exposed to extreme temperature conditions ranging from -55°C to 100°C. With the growing popularity and decreasing costs of additive manufacturing technologies, specifically Material Extrusion (ME), research is being conducted to determine the feasibility of ME components. Thermally cycled PEMFCs may exhibit accelerated gasket deterioration, therefore, the mechanical stability of material extruded gaskets following a harsh thermal cycle must be assessed. The feasibility of the material extruded gaskets will be proven by manufacturing optimization and mechanical testing. The target …

Synthetic Data Generation For Intelligent Inspection Of Structural Environments, Noshin Habib

Open Access Theses & Dissertations

Automated detection of cracks and corrosion in pavements and industrial settings is essential to a cost-effective approach to maintenance. Deep learning has paved the path for vast levels of improvement in the area. Such models require a plethora of data with accurate ground truth and enough variation for the model to generalize to the data, which is notwidely available. There has been recent progress in computer graphics being used for the creation of synthetic data to address the issue of deficient data availability, but it is limited to specific objects, such as cars and human beings. Textures and deformities within …

Modulation Of Non-Diffracting Hermite Gaussian Beams And Nonlinear Optical Microscopy For Nanoscale Sulfur Imaging, Gilberto Navarro

Open Access Theses & Dissertations

Hermite Gaussian beams are the solutions of the scalar paraxial wave equation in Cartesian coordinates. A method was developed to modulate the intensity profile of non-diffracting Hermite Gaussian (HG) beams. The original HG beamâ??s intensity profile consists of high intense corner lobes and low intense central lobes which is not ideal for structured illumination in light-field microscopy. The modulated HG beams were generated by multiplying the original HGâ??s beam envelope by a super-Gaussian envelope to modify the intensity profile to attain equal intensity lobes. The propagation of the original HG beam and modulated HG beam were compared to determine that …

A Case Study In Design, Construction, And Operation Of A Meromictic Solar Pond In Texas, Usa, Bianca Paola Meneses Brassea

Open Access Theses & Dissertations

Over the last four decades, meromictic solar ponds have been the subject of limnological studies and engineering research. A case of practical interest is the salinity gradient solar pond (SGSP). SGSP science and technologies have been systemically advanced in El Paso, Texas. This dissertation aims to share lessons learned in designing, constructing, and operating the El Paso Solar Pond, a NaCl-based solar pond that achieved high-temperature performance over two decades, commencing in 1984. Many of the practical lessons learned have not been published and are thus not readily available in archival journals, and this contribution provides a remedy. The value …

Analyzing And Quantifying The Impact Of Software Diversification On Return-Oriented Programming (Rop) Based Exploits, David Reyes

Open Access Theses & Dissertations

With the implementation of modern software mitigation techniques such: as Address Space Layout Randomization (ASLR), stack canaries, and the No-Execute bit (N.X.), attackers can no longer achieve arbitrary code execution simply by injecting shellcode into a vulnerable buffer and redirecting execution to this vulnerable buffer. Instead, attackers have pivoted to Return Oriented Programming (ROP) to achieve the same arbitrary code execution. Using this attack method, attackers string together ROP gadgets, assembly code snippets found in the target binary, to form what are known as ROP Chains. Using these ROP Chains, attackers can achieve the same malicious behavior as previous code …

Fabrication And Characterization Of Iron-Based Catalysts For The Dehydrogenation Of Fossil Fuels, Victoria Isabel Reyes

Open Access Theses & Dissertations

For a prosperous and sustainable future, hydrogen is an encouraging solution due to its simple transition for industrial decarbonization and synergy for economic development. Paradoxically, current hydrogen production pathways release substantial amount of greenhouse gases into the atmosphere contributing to climate change. To keep up with increasing demand, hydrogen could be produced through microwave-assisted thermocatalytic dehydrogenation of fossil fuels without emitting carbon dioxide. This requires specified catalysts to meet the requirements of hydrogen yield and selectivity. The objective of the present research is to fabricate, characterize, and compare iron-based alumina (FeAl_x O_y) catalysts produced via solution combustion synthesis and iron-based …

Magnetic Structures Of Sawtooth Olivines Mn2six 4 (X = S, Se) Determined Through Neutron Powder Diffraction, Melaku Sisay Tafere

Open Access Theses & Dissertations

In olivine chalcogenide Mn2SiX 4 (X = S, Se) compounds, the Mn lattice produces a sawtooth, which is of critical significance in magnetism due to the potential for manifesting at bands in the magnon spectrum, a crucial component in magnonics. The compounds Mn2SiS4 and Mn2SiSe4 in Mn2SiX 4 family undergo antiferromagnetic phase transitions at T â?? 85 K and â?? 66 K, respectively, as determined from the specific heat, Cp(T). The average and local crystal structuresare determined using synchrotron X-ray, neutron diffraction, and X-ray total scattering data followed by Rietveld and pair distribution function (PDF) analysis. It is found from …

Identifying Particulate Matter Spatial Variation In The El Paso Del Norte Region Using Land-Use Regression Modeling And Data Obtained From A Network Of Low-Cost Sensors, Leonardo Demetrio Vazquez-Raygoza

Open Access Theses & Dissertations

The emergence and rise in popularity of low-cost sensors for atmospheric observation aresetting a new precedent in identifying emission hotspots and providing high-resolution spatial and temporal data. Furthermore, low-cost sensors are becoming popular among institutions and the public, allowing community scientists to become more involved in air quality monitoring. However, concerns about the accuracy and precision of low-cost sensors have been questioned. Most recent research has focused on the utility of real-time monitoring and calibration requirements for these sensors. A low-cost monitoring project has deployed sensors in the El Paso del Norte region in low and high annual average daily …

Radio Frequency Fingerprinting And Its Application To Scada Environments, Evan White

Open Access Theses & Dissertations

With the introduction of IoT into ICS and smartgrid environments there has been a mod-ernization of communication protocols through the internet. This has led to the use of features such as TCP/IP but with it comes modernized attack vectors against these sys- tems. These attacks can be Man In the Middle (MITM), rogue device communication and device cloning. To prevent these attacks, this thesis deploys Radio Frequency Fingerprint- ing (RFF) techniques to verify the uniqueness and legitimacy of known devices. It is crucial to employ security measures within ICS that do not add to the network complexity as this effects …