Physical Sciences and Mathematics Commons^™

Potato Disease Identification Using Transfer Learning Approaches, Tarza Hasan Abdullah

Mesopotamian Journal of Computer Science

Potato crop is one of the prominent consumed foods by human beings. When potato crops are infected by diseases it affects farmers negatively and to run in a loss. Therefore, early detection of the potato crop disease can play a vital role in minimizing the loss of the farmers. Nowadays, artificial intelligence technologies, more specifically deep learning techniques, provide solutions to many crops disease-related problems. However, training deep learning models requires a high computational power and huge amount of data as they are data hungry models. Also, designing a custom CNN models a difficult task and there are some variations …

Enhancing Motion Detection In Video Surveillance Systems Using The Three-Frame Difference Algorithm, Suhaib Qassem Yahya Al-Hashemi, Majid Salal Naghmash, Ahmad Ghandour

Mesopotamian Journal of Computer Science

This paper outlines a methodology for motion detection in video surveillance systems, leveraging advanced algorithms and TCP/IP networks for real-time data acquisition and analysis. The primary focus is on the implementation of the Three-Frame Difference Algorithm, which detects moving targets by analyzing the differences between three consecutive video frames. This method significantly reduces redundant data transmission and storage, addressing the challenges posed by limited wireless network capabilities. The surveillance model, designed in MATLAB using SIMULINK, integrates computer vision systems with embedded coders to facilitate effective communication and processing of video data. The results demonstrate the system's capability to detect motion …

Computer Networking And Cloud-Based Learning/Teaching Environment Using Virtual Labs Tools: A Review And Future Aspirations, Mishall Al-Zubaidie, Raad A. Muhajjar, Lauy Abdulwahid Shihabe

Mesopotamian Journal of Computer Science

Physical laboratories for practical classrooms in computer networks can be prohibitively expensive, as well as requiring regular hardware/software upgrades. With Netkit and similar software, network laboratories can be set up in a computer lab, but the setup is complicated and each student still needs their own computer. Thanks to the Cloud-based infrastructure, Netkit is now available in pre-configured Amazon elastic compute Cloud (EC2) instances. This research reviews and introduces educational computer networks. Furthermore, a web interface is used to allow remote access to numerous lab scripts instantiated on the Cloud. This study also describes how to use the Cloud to …

Cyberbullying Text Identification: A Deep Learning And Transformer-Based Language Modeling Approach, Khalid Saifullah, Muhammad Ibrahim Khan, Suhaima Jamal, Iqbal H. Sarker

Research outputs 2022 to 2026

In the contemporary digital age, social media platforms like Facebook, Twitter, and YouTube serve as vital channels for individuals to express ideas and connect with others. Despite fostering increased connectivity, these platforms have inadvertently given rise to negative behaviors, particularly cyberbullying. While extensive research has been conducted on high-resource languages such as English, there is a notable scarcity of resources for low-resource languages like Bengali, Arabic, Tamil, etc., particularly in terms of language modeling. This study addresses this gap by developing a cyberbullying text identification system called BullyFilterNeT tailored for social media texts, considering Bengali as a test case. The …

Accretion Of Warm Chondrules In Weakly Metamorphosed Ordinary Chondrites And Their Subsequent Reprocessing, Alexander M. Ruzicka, Richard C. Hugo, Jon M. Friedrich, Michael Tyler Ream

Geology Faculty Datasets

To better understand chondrite accretion and subsequent processes, the textures, crystallography, deformation, and compositions of some chondrite constituents in ten lithologies of different cluster texture strength were studied in seven weakly metamorphosed (Type 3) and variably shocked ordinary chondrites (Ragland—LL3 S1, Tieschitz—H/L3 S1, NWA 5421—LL3 S2, NWA 5205—LL3 S2, NWA 11905—LL3-5 S3, NWA 5781—LL3 S3, NWA 11351—LL3-6 S4) using optical and electron microscopy and microtomography techniques. Results support a four-stage model for chondrite formation. This includes 1) limited annealing following collisions during chondrule crystallization and rapid cooling in space prior to accretion, as evidenced by olivine microstructures consistent with dislocation …

Latent Space Dynamics Learning For Stiff Collisional-Radiative Models, Xuping Xie, Qi Tang, Xianzhu Tang

Mathematics & Statistics Faculty Publications

In this work, we propose a data-driven method to discover the latent space and learn the corresponding latent dynamics for a collisional-radiative (CR) model in radiative plasma simulations. The CR model, consisting of high-dimensional stiff ordinary differential equations, must be solved at each grid point in the configuration space, leading to significant computational costs in plasma simulations. Our method employs a physics-assisted autoencoder to extract a low-dimensional latent representation of the original CR system. A flow map neural network is then used to learn the latent dynamics. Once trained, the reduced surrogate model predicts the entire latent dynamics given only …

Sky Smiley Face, John Adam

Mathematics & Statistics Faculty Publications

The article discusses the formation of a circumzenithal arc (CZA) in the sky, caused by specific light ray paths through hexagonal ice crystals in cirrus clouds. The CZA is visible when the Sun's altitude is about 32° or less. The text includes questions for readers to explore the physics behind the formation of CZAs and circumhorizontal arcs (CHAs). The author acknowledges photographers for providing images and invites readers to find answers online.

Earthquakes And Seismic Waves: Solutions For Fermi Questions, March 2024, John Adam

Mathematics & Statistics Faculty Publications

Solution to Question 1: To estimate h, we take the geometric mean of 1 km and 70 km, or ~8 km, and take ρ ≈ 2500 kg/m³.

Hence, δl ≈ 4 × 0.05 × (2.5 × 10³ kg/m³) × (10 m/s²) × (8 × 10³ m) × (2 × 10⁴ m) × 0.1 ÷ (3 × 10¹⁰ kg · m⁻¹ · s⁻²) ≈ 1.3 m. (Note that this is not meant to be an estimate of the width of the Icelandic rock fracture in the photograph, though it appears to be of the right order …

Cats, Dogs, And Roll Waves, John Adam

Mathematics & Statistics Faculty Publications

This article discusses the phenomenon of roll waves, which are shock-like patterns separated by smooth profiles that occur in flood waves. The author mentions that in a steady-state situation, the drag forces on the water in the channel are balanced by the down-slope gravitational force. The article also includes questions for readers to estimate the speed and length of the roll waves, as well as determine the stability of the flow. The author provides additional information about the Chezy formula, an empirical equation used in fluid mechanics to estimate the mean flow velocity of open channel flow.

Cats, Dogs, And Roll Waves: Solutions For Fermi Questions, April 2024, John Adam

Mathematics & Statistics Faculty Publications

On a hot afternoon in western North Carolina, the heavens opened and (to mix metaphors) it started raining “cats and dogs.” The rain was torrential, and soon a river of water was flowing downhill into the parking lot. In rivers and dam spillways, these are known as flood waves. The picture shows a particular type of flood waves known s roll waves—shock-like patterns separated by smooth profiles. In a steady-state situation, the drag forces on the water in the channel are balanced by the down-slope gravitational force. The dimensionless friction coefficient is C, the stream depth is h, v is …

Uniform Convergence Of Deep Neural Networks With Lipschitz Continuous Activation Functions And Variable Widths, Yuesheng Xu, Haizhang Zhang

Mathematics & Statistics Faculty Publications

We consider deep neural networks (DNNs) with a Lipschitz continuous activation function and with weight matrices of variable widths. We establish a uniform convergence analysis framework in which sufficient conditions on weight matrices and bias vectors together with the Lipschitz constant are provided to ensure uniform convergence of DNNs to a meaningful function as the number of their layers tends to infinity. In the framework, special results on uniform convergence of DNNs with a fixed width, bounded widths and unbounded widths are presented. In particular, as convolutional neural networks are special DNNs with weight matrices of increasing widths, we put …

Hyperparameter Estimation For Sparse Bayesian Learning Models, Feng Yu, Lixin Shen, Guohui Song

Mathematics & Statistics Faculty Publications

Sparse Bayesian learning (SBL) models are extensively used in signal processing and machine learning for promoting sparsity through hierarchical priors. The hyperparameters in SBL models are crucial for the model’s performance, but they are often difficult to estimate due to the nonconvexity and the high-dimensionality of the associated objective function. This paper presents a comprehensive framework for hyperparameter estimation in SBL models, encompassing well-known algorithms such as the expectation-maximization, MacKay, and convex bounding algorithms. These algorithms are cohesively interpreted within an alternating minimization and linearization (AML) paradigm, distinguished by their unique linearized surrogate functions. Additionally, a novel algorithm within the …

Shadow Hands, John Adam

Mathematics & Statistics Faculty Publications

The article titled "Shadow hands" discusses a statement made by authors Dave Lynch and Bill Livingston in their book "Color and Light in Nature." The authors state that when you cast a shadow with your hand onto a piece of paper, the sharpness of the shadow's edge diminishes as you raise your hand above the surface. This fuzzy outer edge of the shadow is called the penumbra, and its width divided by its distance from your hand is always a constant fraction of about 1/112. The article poses two questions related to this statement and asks readers to explain it …

The Geometry Of Dynamic Time-Dependent Best-Worst Choice Pairs, Sasanka Adikari, Norou Diawara, Haim Bar

Mathematics & Statistics Faculty Publications

There has been increasing interest in best–worst discrete choice experiments (BWDCEs) in health economics, transportation research, and other fields over the last few years. BWDCEs have distinct advantages compared to other measurement approaches in discrete choice experiments (DCEs). A systematic study of best–worst (BW) choice pairs can be traced back to the 1990s. Recently, new ideas have been introduced to the subject. Calculating utility helps measure the attractiveness of BW choices. The goal of this paper is twofold. First, we extend the idea of the BW choice pair to include dynamic, time-dependent transition probability and capture utility at each time …

Pigeon Strike!: Solutions For Fermi Questions, October 2024, John Adam

Mathematics & Statistics Faculty Publications

This article, titled "Pigeon strike!: Solutions for Fermi Questions, October 2024," discusses the estimation of various physics-related questions regarding a pigeon striking a window. The author estimates the momentum and kinetic energy of the bird prior to hitting the window, as well as the force, pressure, and wingspan of the bird during impact. The author assumes an inelastic collision between the bird and the window, and provides calculations and explanations for their estimations. The article concludes with the author's observation that the estimated wingspan aligns with that of an adult pigeon.

Modeling Apparent Pb Loss In Zircon U-Pb Geochronology, Glenn R. Sharman, Matthew A. Malkowski

Geosciences Faculty Publications and Presentations

The loss of radiogenic Pb from zircon is known to be a major factor that can cause inaccuracy in the U–Pb geochronological system; hence, there is a need to better characterize the distribution of Pb loss in natural samples. Treatment of zircon by chemical abrasion (CA) has become standard practice in isotope dilution–thermal ionization mass spectrometry (ID-TIMS), but CA is much less commonly employed prior to in situ analysis via laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) or secondary ionization mass spectrometry (SIMS). Differentiating the effects of low levels of Pb loss in Phanerozoic zircon with relatively low-precision in situ U–Pb …

Synthetic Approaches Of Carbohydrate Based Self-Assembling Systems, Guijun Wang, Anji Chen, Pramod Aryal, Jonathan Bietsch

Chemistry & Biochemistry Faculty Publications

Carbohydrate-based self-assembling systems are essential for the formation of advanced biocompatible materials via a bottom-up approach. The self-assembling of sugar-based small molecules has applications encompassing many research fields and has been studied extensively. In this focused review, we will discuss the synthetic approaches for carbohydrate-based self-assembling (SA) systems, the mechanisms of the assembly, as well as the main properties and applications. This review will mainly cover recent publications in the last four years from January 2020 to December 2023. We will essentially focus on small molecule self-assembly, excluding polymer-based systems, which include various derivatives of monosaccharides, disaccharides, and oligosaccharides. Glycolipids, …

Visible Opacities Of S-Type Stars: The D³Φ–A³Δ Band System Of Zro, Peter F. Bernath, Manish Bhusal, Jacques Liévin

Chemistry & Biochemistry Faculty Publications

ZrO is a well-studied metal monoxide because of its astrophysical importance in characterizing S stars. The bands of the d³Φ–a³Δ system (γ system) with v′≤4 and v" ≤ 5 are rotationally analyzed using the PGOPHER program to provide spectroscopic constants. The high-resolution ZrO emission spectrum was recorded with a Fourier transform spectrometer using a high-temperature carbon furnace source. New ab initio calculations of the transition dipole moment were carried out in order to determine the vibronic band strengths. The spectroscopic constants, along with the band strengths, are used to calculate a line list for the γ system. This line list …

The Impact Of Biochar's Physicochemical Properties On Sorption Of Perfluorooctanoic Acid (Pfoa), Karen Ane Skjennum, Katinka M. Krahn, Erlend Sørmo, Raoul Wolf, Aleksandar I. Goranov, Patrick G. Hatcher, Thomas Hartnik, Hans Peter H. Arp, Andrew R. Zimmerman, Yaxin Zhang, Gerard Cornelissen

Chemistry & Biochemistry Faculty Publications

To better characterize properties governing the sorption of per- and polyfluoroalkyl substances (PFAS) to biochar, twenty-three diverse biochars were characterized and evaluated as sorbents for perfluorooctanoic acid (PFOA). Biochars were produced at various temperatures, using two different technologies, and made from sewage sludge, food waste reject, wood wastes, and one reference substrate (wood pellets). The biochars were characterized in terms of surface area, pore volume and pore size distributions, elemental composition, leachable elements, ash content, pH, zeta potential, condensed aromatic carbon (ConAC) content (determined by benzenepolycarboxylic acid (BPCA) markers), and their -OH functional group content (infrared spectroscopy). PFOA sorption isotherms …

Sea Level Rise Driven Groundwater Inundation: Effects Of Island Hydrogeology On Freshwater Lens Dynamics, Lauren K. Mancewicz

Dissertations, Master's Theses and Master's Reports

Groundwater inundation due to sea level rise poses a threat to fresh groundwater availability in coastal areas, and small islands are particularly vulnerable. On an island, when sea level rises, the freshwater lens also rises due to the difference in density between the salt and fresh groundwater. As the water table rises above the land surface it forms a lake and the water is exposed to additional evaporative losses, reducing the amount of fresh water available. This work aims to improve our understanding of groundwater inundation due to sea level rise and the impact of different hydrogeologic settings and phenomena …

Applications Of Independent And Identically Distributed (Iid) Random Processes In Polarimetry And Climatology, Dan Kestner

Dissertations, Master's Theses and Master's Reports

The unifying theme of this thesis is the characterization of “perfect randomness,” i.e., independent and identically distributed (IID) stochastic processes as these are applied in physical science. Two specific and mathematically distinct applications are chosen: (i) Radar and optical polarimetry; (ii) Analysis of time series in meteorology. In (i), IID process of a special kind, namely, with a distribution defined by symmetry, is used to link its multivariate Gaussian density to uniformity on the Poincaré sphere. This “statistical ellipsometry” approach is then used to relate polarimetric mismatches or imbalances to ellipsometric variables and suitably chosen cross-correlation measures. In (ii), recently …

Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa

Dissertations, Master's Theses and Master's Reports

Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), …

Dependence Of Energy Transfer On Curvature Similarity In Collisions Involving Curved Shock Fronts, Justin Cassell

Dissertations, Master's Theses and Master's Reports

In high-speed collisions of projectiles, pressure exerted by a resulting shock wave is so high that even solids begin to flow and hydrodynamics becomes relevant. Jetting results from hydrodynamic instability driving the evolution of an interface following shock loading. Our emphasis in this dissertation is mitigation of instabilities via several shocks and, specifically, the transfer of energy from a shock wave to another object. To that end, in 2022 and 2023 while on-site, we adapted Lawrence Livermore National Laboratory (LLNL) to explore the effects of shock front geometry on the transfer of energy during shock collisions via numerous computer simulations. …

The Integration Of Neuromorphic Computing In Autonomous Robotic Systems, Md Abu Bakr Siddique

Dissertations, Master's Theses and Master's Reports

Deep Neural Networks (DNNs) have come a long way in many cognitive tasks by training on large, labeled datasets. However, this method has problems in places with limited data and energy, like when planetary robots are used or when edge computing is used [1]. In contrast to this data-heavy approach, animals demonstrate an innate ability to learn by communicating with their environment and forming associative memories among events and entities, a process known as associative learning [2-4]. For instance, rats in a T-maze learn to associate different stimuli with outcomes through exploration without needing labeled data [5]. This learning paradigm …

Integrating Arcgis And Redux Using Middleware, Vishnu Vardhan Reddy Rapuru

Dissertations, Master's Theses and Master's Reports

The integration of ArcGIS with Redux through middleware presents a novel approach to managing state in geospatial applications. This report outlines the process and benefits of combining ArcGIS’s robust mapping and analytics capabilities with Redux’s predictable state container for JavaScript apps. It begins with an introduction to both technologies, followed by a detailed discussion on the architecture design, focusing on the role of middleware as the linchpin in this integration[1]. The paper highlights the benefits, such as improved state management and application performance, and addresses the challenges encountered during the integration process. Implementation details are provided, including the setup of …

Discontinuous Galerkin Methods For Compressible Miscible Displacements And Applications In Reservoir Simulation, Yue Kang

Dissertations, Master's Theses and Master's Reports

This dissertation contains research on discontinuous Galerkin (DG) methods applied to the system of compressible miscible displacements, which is widely adopted to model surfactant flooding in enhanced oil recovery (EOR) techniques. In most scenarios, DG methods can effectively simulate problems in miscible displacements.
However, if the problem setting is complex, the oscillations in the numerical results can be detrimental, with severe overshoots leading to nonphysical numerical approximations. The first way to address this issue is to apply the bound-preserving
technique. Therefore, we adopt a bound-preserving Discontinuous Galerkin method
with a Second-order Implicit Pressure Explicit Concentration (SIPEC) time marching
method to …

Optimizing Php Api Calls With Pagination And Caching, Parsharam Reddy Sudda

Dissertations, Master's Theses and Master's Reports

The Keweenaw Time Traveler (KeTT) project is devoted to mapping the historical and social landscapes of the Keweenaw Peninsula. During the project, it was discovered that the server-side performance needed improvement. To address this issue, the "Optimizing PHP API Calls with Pagination and Caching" initiative was launched. This initiative focused on refining API calls, implementing server caching and pagination, and fortifying security against common vulnerabilities. The project successfully mitigated risks associated with SQL Injection and XSS through meticulous code enhancements while improving error handling. Additionally, the introduction of Scroll-Induced Pagination optimized data delivery, significantly reducing response times, and elevating the …

Study Of Particle Accelerators In The Universe With The Hawc Observatory, Rishi Babu

Dissertations, Master's Theses and Master's Reports

HESS J1809-193 is an unidentified TeV source discovered in 2007 by the High Energy Stereoscopic System(H.E.S.S.) Collaboration. The emission originates in a region that is rich in cosmic-ray accelerators, including several supernova remnants and pulsars, including SNR G11.1+0.1, SNR G11.0-0.0, and the young radio pulsar PSR J1809-1917. Originally classified as a pulsar wind nebula candidate, recent studies show the peak of the TeV region overlapping with a system of molecular clouds and revising the original classification for other scenarios, including a pure hadronic scenario. This dissertation presents the morphological and spectral study of HESS J1809-193 using 2139 days of data …

Chemical Synthesis Of Sensitive Dna, Komal Chillar

Dissertations, Master's Theses and Master's Reports

Over the past decades, researchers have tried various chemical methods to synthesize modified oligodeoxynucleotides (ODNs, i.e. short segments of DNAs). Traditional ODN synthesis methods require strong basic, and nucleophilic conditions for the deprotection and cleavage of the ODN from the solid support. However, the sensitive ODNs containing labile functionalities are vulnerable to such harsh conditions. Sensitive ODNs have a wide range of applications in research and pharmaceuticals. To synthesize sensitive ODNs, researchers devised different strategies but no practical methods have been developed. To overcome these challenges, we developed alkyl Dim alkyl Dmoc technology. This innovative technology uses weakly basic and …

Understanding The Controls Of Seasonal Stream Temperature And Hydrological Monitoring Of Forested Watersheds In The Western Upper Peninsula Of Michigan, Eli A. Paulen

Dissertations, Master's Theses and Master's Reports

Accurately predicting stream temperature is vital to protect the environment and its most sensitive aquatic species. Tools for forecasting stream temperature rely on in situ data that affect thermal response of natural water systems. Stream and meteorological data were analyzed from the western Upper Peninsula of Michigan for the 2016-2023 water years to determine which factors affected stream temperatures. Through the application of multivariable linear regression models, our analysis identified air temperature as the primary determinant of stream temperature. However, the air-stream temperature relationship varied significantly over temporal scales, improving with increasing in time averaging. The air-stream temperature relationship was …