Digital Commons Network^™

Adaptive Workload Management For Enhanced Function Performance In Serverless Computing, Priyanka Ashok Birajdar, V. Harsha, Anurag Satpathy, Sourav Kanti Addya

Computer Science Faculty Research & Creative Works

Serverless computing streamlines application deployment by removing the need for infrastructure management, but fluctuating workloads make resource allocation challenging. To solve this, we propose an adaptive workload manager that intelligently balances workloads, optimizes resource use, and adapts to changes with auto-scaling, ensuring efficient and reliable serverless performance. Preliminary experiments demonstrate an ≈ 0.6X% and 2X% improvement in execution time and resource utilization compared to the First-Come-First Serve (FCFS) scheduling algorithm.

Elastic Scheduling For Graceful Degradation Of Mixed-Criticality Systems, Zhuoran Sun, Marion Sudvarg, Christopher Gill

Computer Science Faculty Research & Creative Works

Many mixed-criticality system models drop all jobs of low-criticality tasks when a criticality mode switch occurs, ensuring that high-criticality tasks still can meet their deadlines in the new mode. However, this means that even important low-criticality tasks are discarded, which may not be acceptable in some systems in practice. This paper addresses that distinction between criticality and importance through a new Inelastic Graceful Earliest Deadline First with Virtual Deadlines (IG-EDF-VD) scheme that upon a criticality mode switch only discards the least important low-criticality tasks necessary to ensure feasibility. Moreover, we consider elastic scheduling within our mixed-criticality model (EG-EDF-VD), using compression …

Massera’S Theorem On Arbitrary Discrete Time Domains, Martin Bohner, Jaqueline G. Mesquita, Sabrina Streipert

Mathematics and Statistics Faculty Research & Creative Works

We present a general version of Massera's theorems for arbitrary discrete domains, based on a newly introduced definition for both linear and nonlinear equations. For scalar nonlinear equations, we identify sufficient conditions that ensure each µ-bounded solution approaches a periodic solution asymptotically. In the case of linear systems, we prove that the presence of a µ-bounded solution necessarily leads to a periodic solution. We also provide some examples to show the practical implications of our findings.

On The Sharpness Of A Korn’S Inequality For Piecewise H1 Space And Its Applications, Qingguo Hong, Young Ju Lee, Jinchao Xu

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we investigate the sharpness of a Korn's inequality for piecewise H1 space and its applications. We first revisit a Korn's inequality for the piecewise H1 space based on general polygonal or polyhedral decompositions of the domain. We express the Korn's inequality with minimal jump terms. Then we prove that such minimal jump conditions are sharp for achieving the Korn's inequality. The sharpness of the Korn's inequality and explicitly given minimal conditions can be used to test whether any given finite element spaces satisfy Korn's inequality, immediately as well as to build or modify nonconforming finite elements for …

Estimation And Model Misspecification For Recurrent Event Data With Covariates Under Measurement Errors, Ravinath Alahakoon, Gideon K.D. Zamba, Xuerong Meggie Wen, Akim Adekpedjou

Mathematics and Statistics Faculty Research & Creative Works

For subject i, we monitor an event that can occur multiple times over a random observation window [0, (Formula presented.)). At each recurrence, p concomitant variables, (Formula presented.), associated to the event recurrence are recorded—a subset ((Formula presented.)) of which is measured with errors. To circumvent the problem of bias and consistency associated with parameter estimation in the presence of measurement errors, we propose inference for corrected estimating equations with well-behaved roots under an additive measurement errors model. We show that estimation is essentially unbiased under the corrected profile likelihood for recurrent events, in comparison to biased estimations under a …

Multi-Valued Variational Inequalities For Variable Exponent Double Phase Problems: Comparison And Extremality Results, Siegfried Carl, Vy Khoi Le, Patrick Winkert

Mathematics and Statistics Faculty Research & Creative Works

We prove existence and comparison results for multi-valued variational inequalities in a bounded domain Ω of the form (Formula presented.) where A:W1,H(Ω)→W1,H(Ω)∗ given by (Formula presented.) for u∈W1,H(Ω), is the double phase operator with variable exponents and W1,H(Ω) is the associated Musielak–Orlicz Sobolev space. First, an existence result is proved under some weak coercivity condition. Our main focus aims at the treatment of the problem under consideration when coercivity fails. To this end we establish the method of sub–super-solution for the multi-valued variational inequality in the space W1, H(Ω) based on appropriately defined sub- and super-solutions, which yields the existence …

Existence Results For A Discrete Fractional Boundary Value Problem, David Barilla, Martin Bohner, Giuseppe Caristi, Shapour Heidarkhani, Shahin Moradi

Mathematics and Statistics Faculty Research & Creative Works

In this study, we investigate the existence of at least one solution and the existence of an infinite number of solutions for a discrete fractional boundary value problem. Requiring an algebraic condition on the nonlinear term for small values of the parameter and requiring an additional asymptotical behavior of the potential at zero, we investigate the existence of at least one nontrivial solution for the problem. Moreover, under suitable assumptions on the oscillatory behavior of the nonlinearity at infinity, for exact collections of the parameter, we discuss the existence of a sequence of solutions for the problem. We also present …

Floquet Theory For First-Order Delay Equations And An Application To Height Stabilization Of A Drone’S Flight, Martin Bohner, Alexander Domoshnitsky, Oleg Kupervasser, Alex Sitkin

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we proposed a version of the Floquet theory for delay differential equations. We demonstrated that very natural assumptions for control in technical applications can lead us to a one-dimensional fundamental system. This approach allowed researchers to work with classical methods used in the case of ordinary differential equations. On this basis, new original unexpected results on the exponential stability were proposed. For example, in the equation x' (4)+a(t)x(t—-T(7)) = 0, t € [0, co), we avoided the assumption on the smallness of the product sup,j9,.) 41 SUP;< {9,00) TD) < 3/2 for asymptotic stability. We obtained that in the case of w-periodic coefficient and delay, the fact that the period w was situated in a corresponding interval can lead to exponential stability. We then applied our new tests of stability to the stabilization of a drone's flight, where smallness of the noted above product could not be achieved from a technical point of view. For an equation with periodic coefficient and delay, we got a formula of the solution's representation on the semiaxis.

A Unified Concept Of Periodicity On Any Time Scale And Applications, Martin Bohner, Jaqueline G. Mesquita, Sabrina H. Streipert

Mathematics and Statistics Faculty Research & Creative Works

We introduce a novel definition of periodicity on arbitrary time scales, dependent on a strictly increasing and differentiable function. This removes the commonly used and restrictive assumption of a periodic time scale to define periodic functions. Our new definition furthermore allows for a wider class of functions to be studied using the theory of periodic systems. After providing crucial properties of these periodic functions, such as the translation invariance of integrals of periodic functions, we apply the concept of this new periodicity to linear dynamic equations. We provide necessary and sufficient conditions for a linear dynamic equation to have such …

Enhanced Kneser-Type Oscillation Criteria For Second-Order Functional Quasilinear Dynamic Equations On Time Scales, Taher S. Hassan, Elvan Akın, Bassant M. El-Matary, Ioan Lucian Popa, Mouataz Billah Mesmouli, Ismoil Odinaev, Akbar Ali

Mathematics and Statistics Faculty Research & Creative Works

This work presents new Kneser-type oscillation criteria for second-order quasilinear functional dynamic equations defined on arbitrary unbounded above time scales. Our approach employs the Riccati transformation technique in conjunction with the integral averaging method. The results show a significant improvement over recent Kneser-type oscillation criteria. We provided several illustrative examples to highlight the importance of our findings.

Photoionization Of Spin-Polarized Rydberg Atoms Out Of A Continuous Wave Optical Dipole Trap, Kevin Lee Romans

Doctoral Dissertations

"Recent research has demonstrated the need for a fully differential experiment on the photoionization of ⁶Li Rydberg atoms in a continuous wave (cw) laser field, as this would provide a new path forward for studying never before accessible atom-light interactions. Rydberg atoms are back in the focus of intense research due to their peculiar properties, which make them interesting candidates for quantum optics and information applications. In this work, we study the ionization of such Rydberg atoms, due to their interaction with a trapping laser field, by utilizing a reaction microscope (ReMi) capable of measuring photoelectron momentum distributions with …

Parallel Algorithms For Large Scale Dynamic Graph Analysis, Arindam Khanda

Doctoral Dissertations

A complex system of interacting entities in contemporary scenarios, be it biological, technological, or social, can be represented using graphs. Dynamic graphs, unlike their static counterparts, are ones in which the underlying topology changes over time. These networks act as a model for numerous systems, from transportation to social interactions, capturing the ever-evolving nature of real-world phenomena. However, the inherent temporality of these networks presents a unique set of challenges and the traditional static graph algorithms often fall short in efficiency and applicability. In our research, we delve into the complexities presented by large dynamic networks and suggest various methodologies …

A New Formulation Of Hardy-Type Dynamic Inequalities On Time Scales, Martin Bohner, Irena Jadlovská, Ahmed I. Saied

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we introduce a novel formulation of dynamic Hardy-type inequalities on a time scale, motivated by a recently established convexity approach in the Haar measure. The classical Hardy inequality is refined so that the classical Lebesgue-measure constant is replaced by the sharp constant 1. We obtain time-scale analogues on finite intervals with best constants, and, for nonincreasing and nondecreasing functions, reversed inequalities with explicit weights described by incomplete β-functions. To establish our results, we employ two distinct time scales and apply the chain rule, together with the substitution rule, the derivative of inverse functions, and Fubini's theorem for …

Digital Twin-Centered Hybrid Data-Driven Multi-Stage Deep Learning Framework For Enhanced Nuclear Reactor Power Prediction, James Daniell, Kazuma Kobayashi, Ayodeji Alajo, Syed Bahauddin Alam

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

The accurate and efficient modeling of nuclear reactor transients is crucial for ensuring safe and optimal reactor operation. Traditional physics-based models, while valuable, can be computationally intensive and may not fully capture the complexities of real-world reactor behavior. This paper introduces a novel hybrid digital twin-focused multi-stage deep learning framework that addresses these limitations, offering a faster and more robust solution for predicting the final steady-state power of reactor transients. By leveraging a combination of feed-forward neural networks with both classification and regression stages, and training on a unique dataset that integrates real-world measurements of reactor power and controls state …

Impact Of Surface And Physical Property On Multiphase Flow In Sealed Vessel: Liquid Dropdown Performance, Mehedi Hasan Tusar, Palash K. Bhowmik, Kazuma Kobayashi, Syed Bahauddin Alam, Shoaib Usman

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

This study explores multi-phase (i.e., liquid-gas) and multi-fluid (i.e., air-water, and water-silicone oil) flow-pattern and flow-blockage physics phenomena for wall wettability conditions ranging from superhydrophilic to superhydrophobic cases in sealed vessels utilizing computational fluid dynamics (CFD) simulation tools and volume-of-fluid (VOF) method with sharp interface modeling. Detailed modeling and simulation (M&S) of such physics phenomena—in which liquid (e.g., water) stands over top of gas (e.g., air or steam) in a closed channel and exhibited flow blockage, flow reversal related challenges—are pivotal for design, analysis, and qualification of component-level (e.g., heat pipes, heat exchangers) to system-level (e.g., emergency core cooling systems …

Characterization And Leaching Feasibility Studies Of Copper Flue Dust For The Recovery Of Main And Trace Metals, Fardis Nakhaei, Marek Locmelis, Lana Alagha, Michael S. Moats, Carlos Eyzaguirre, Cory Smith

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Although copper smelter dust (CSD) is classified as hazardous waste, it also serves as a valuable secondary resource, offering potential for the recovery of critical elements. In this study, CSD samples were collected from the waste heat boiler (WHB) and electrostatic precipitator (ESP) units connected to the flash smelting furnace at a copper smelter. The representative samples were extensively characterized by particle size, and chemical and mineralogical analyses. Following sample characterization, leaching experiments were performed to evaluate the potential extraction of Cu, Fe, As, Zn, Pb, In, Ga, and Ge from the flue dusts. Distilled water, H2SO4, and HCl were …

Designing Robust Quasi-2d Perovskites Thin Films For Stable Light-Emitting Applications, Sharmistha Khan, Reshna Shrestha, Mengru Jin, Doyun Kim, Guan Lin Chen, Ruipeng Li, Yijia Gu, Qing Tu, Namyoung Ahn, Wanyi Nie

Materials Science and Engineering Faculty Research & Creative Works

Quasi-2D perovskite made with organic spacers co-crystallized with inorganic cesium lead bromide inorganics is demonstrated for near unity photoluminescence quantum yield at room temperature. However, light emitting diodes made with quasi-2D perovskites rapidly degrade which remains a major bottleneck in this field. In this work, It is shown that the bright emission originates from finely tuned multi-component 2D nano-crystalline phases that are thermodynamically unstable. The bright emission is extremely sensitive to external stimuli and the emission quickly dims away upon heating. After a detailed analysis of their optical and morphological properties, the degradation is attributed to 2D phase redistribution associated …

Evaluating Tropospheric Delay Modeling For Enhanced Geospatial Accuracy, Adeyinka Olaoluwa Olaseinde

Masters Theses

Interferometric Synthetic Aperture Radar (InSAR) is a vital technique for monitoring ground surface deformation across large spatial scales. However, variability in atmospheric water vapor, pressure, and temperature introduces tropospheric delays that can significantly affect measurement accuracy. These delays are often corrected using outputs from numerical weather prediction (NWP) models. RAiDER, an open-source Python package, facilitates this by estimating tropospheric delays using models such as the High-Resolution Rapid Refresh (HRRR). Previous studies have shown that weather model–based corrections can substantially reduce atmospheric noise in InSAR data but also highlight persistent residual errors, especially at spatial scales smaller than the model grid …

The Structure, Properties And Dissolution Behaviors Of Phosphate Glasses, Han Zhang

Doctoral Dissertations

The poor chemical durability remains a critical challenge for the application of phosphate glasses. This study investigates the compositional influences on the structure, properties and chemical durability of Li2O-ZnO-P₂O₅ glasses. Their structural characteristics were analyzed utilizing high-performance liquid chromatography, Raman spectroscopy, and X-ray photoelectron spectroscopy. The incorporation of (Li2O+ZnO) in LZeq glasses depolymerizes the phosphate network. In LZ40P and LZ45P glasses, Li⁺ initially replaces Zn²⁺ associated with non-bridging oxygens (NBOs) in Q² tetrahedra. Once the substitution in Q² is complete, further Li⁺ incorporation leads to the replacement of Zn²⁺ in Q^{1 …}

Effects Of Climate Change On Fungal Diversity And Function In Streams, Syeda Tasfia Imam

Masters Theses

"This study investigated the impact of climate change, particularly drought, on leaf decomposition and associated fungal and macroinvertebrate communities in freshwater ecosystems. With climate change, streams may experience altered hydrology, leading to shifts in community composition and biogeochemical processes. Fungi decompose organic matter, facilitate nutrient cycling, and support food webs. However, drought can disrupt these processes by reducing water availability, causing declines in fungal diversity and activity. I examined leaf breakdown and associated biota in 13 stream sites across varying hydrologic conditions, from perennial to ephemeral flow patterns. Flow duration varied during the 8-week study. Leaf breakdown was significantly related …

Environmental Pollutants: A Risk For Premature Aging And Transgenerational Toxicity, Alex Kathleen Daniels

Masters Theses

"This thesis aims to identify interactions between C. elegans’ reproductive system and global pollutants such as microplastics, HgCl₂, nicotine, and pesticides. Human exposure to these pollutants and their effect on reproduction can be analyzed using the C. elegans as a model organism. Systematic analysis of matricidal hatching, progeny production, germline apoptosis, and lifespan assays determined effects on reproduction and reproductive aging. Through my experiments, it was determined that no significant effects were produced from the selected polystyrene, polyethylene, vape juice, nicotine hemi sulfate salt, imidacloprid, or glyphosate regarding matricidal hatching or progeny production. I confirmed that HgCl₂ induced significant effects …

Transfection Of Ionizable Lipid Nanoparticles On Raw 264.7 And Mda-Mb-231, Lavanya Bhargava

Masters Theses

"This thesis investigates the preparation, characterization, and transfection efficiency of various ionizable lipid nanoparticles (LNPs) formulated for the delivery of mRNA encoding enhanced green fluorescent protein (EGFP) in RAW 264.7 macrophages and MDA-MB-231 breast cancer cell lines. The ionizable cationic lipid studied are ALC-035, C12-200, C14-4, PPZ-A10, DLin-MC3-DMA. The study addresses the need for effective gene delivery systems to provide a safe and versatile platform that protects and transports nucleic acids into target cells. LNPs were synthesized using microfluidic mixing methods, incorporating lipid components such as the cationic lipids, DSPE, DOPE, cholesterol and PEG lipids to achieve controlled particle sizes, …

Lidar From The Skies: A Uav-Based Approach For Efficient Object Detection And Tracking, Baya Cherif

Masters Theses

"Recently, there has been a growing interest in deploying the Light Detection and Ranging (LiDAR) technology to gain traction in the autonomous vehicle industry, its applications are expanding into areas like smart cities, agriculture, and renewable energy. This work proposes an advanced approach to enhance aerial traffic monitoring using Li- DAR. We aim to provide accurate, real-time object detection and tracking from an aerial perspective by integrating Unmanned Aerial Vehicle (UAV) with LiDAR, culminating in a smart UAV-integrated LiDAR (A-LiD) sensor for traffic surveillance. We introduce an adapted version of one of the newest methods of the cutting-edge 3D object …

On Optimizing Sensor Data Collection, Processing, And Storage For Industrial Additive Manufacturing, Steven Thompson

Masters Theses

The widespread adoption of digital data management methods for transformative technologies, such as additive manufacturing (AM), within the aerospace industry is impeded by poor interoperability between AM component manufacturing processes. Moreover, data quality may be compromised due to sensor failures or other corruptions. Additionally, massive amounts of data are collected during these processes, often needing to remain accessible for decades. These storage costs can place a significant financial burden on smaller suppliers. This work aims to make digital data management methods more affordable and, therefore, approachable for smaller suppliers.

First, the design and initial implementation of an affordable and adaptable …

Augmentation Of Quality Of Service, Security, And Trust In Edge-Enhanced Iot Networks Leveraging Blockchain, Kyle Matthew Whitlatch

Masters Theses

The meteoric rise of the Internet of Things (IoT) has led to multiple architectural schemas to handle the data these devices create. Edge-enhancement is a technique where groups of IoT report to a median layer to aggregate the data before relaying to the endpoint. These edges also open opportunities to perform more operations to ensure devices are behaving properly before committing the data to long term storage. By interconnecting these edges with a technology like blockchain, it is possible to have an interconnected and responsive system to ensure the Quality of Service (QoS) of the IoT devices within the architecture …

Auto-Tuning And Applications Of Transient Voltage Suppressor Models In Full-Wave Simulations, Daniel Peter Szanto

Masters Theses

System efficient electrostatic design (SEED) combines full-wave geometry information with SPICE models of non-linear protection devices, typically transient voltage suppression (TVS) diodes, to allow optimization and validation of electrostatic design (ESD) protection early in the design process. TVS models have previously been developed which may be used in SPICE simulation tools like Keysight ADS, but these models could not be used directly in full-wave simulation tools like CST Studio. A process was developed for converting existing ADS models of TVS devices to a form that can be used within a CST full wave/SPICE hybrid simulation. Three TVS models were converted …

Constraint Programming For Optimized Degree Paths, Mitchell Lee Skaggs

Masters Theses

This work presents a degree planning tool developed as part of the Pervasive Cyberinfrastructure for Personalized eLearning and Instructional Support (PERCEPOLIS) project which generates complete, valid, and personalized degree paths at any point from admission to graduation. This eliminates tedious calculation and double-checking, allowing advisors to focus on a student’s long-term plans and students to proactively explore potential degree paths. The original research contribution of this work is the use of a unified model for academic requirements to automatically translate complex, real-world curricula into a constraint programming model that can be quickly optimized based on personalized student criteria.

Automatically translating …

System Design For Highly Accurate And Efficient Target Detection In Triaxial Testing, Qingqing Fu

Masters Theses

Accurate and automated recognition of coded targets is crucial for high-precision photogrammetry-based measurements in triaxial testing. Traditional recognition methods, including those based on deep learning and table decoding, often struggle with issues such as perspective distortion, rotation, and variable lighting, leading to unreliable results. While deep learning approaches offer some improvements, they remain computationally intensive and sensitive to environmental factors.

This thesis introduces an innovative system that replaces deep learning algorithms with a blob analysis-based method for efficient and robust recognition of coded targets. The system also employs newly designed solid points of varying sizes and patterns, eliminating the need …

Ground Testing Of Cryogenic Environments In Vacuum Conditions, Lucas A. Scott

Masters Theses

The environment in the vacuum of space is unforgiving and ever-changing. Not only facing the lack of a protective atmosphere, but powerful radiation and extreme temperature ranges as well. Equipment destined for space must be hardened to withstand them. Just launching satellites that are theoretically able to survive these conditions is unfeasibly costly in the event of failure. Because of this, spacecraft must be tested in a simulated environment that can match the harsh climate in space. Therefore, it is the goal of the Gas and Plasma Dynamics Lab's (GPDL) to test and prove specific methods of recreating these conditions. …

Critical Behavior Ofthedilutedquasi-Onedimensionalquantum Ising Model, Logan Bradley Sowadski

Masters Theses

We explore the phase transition in the diluted quasi-one-dimensional quantum Ising model. We begin by giving an introduction to the Ising model followed by derivations of the properties and observables. A brief overview of Monte-Carlo simulations is also given focusing on two algorithms that make simulations for physically realizable systems possible, the Metropolis and Wolff algorithms. We finally discuss the concept of random disorder in the system and the effects this can have on the bulk of the system.

These concepts are then directly applied to a quasi-one-dimensional Ising model. Motivated by recent experiments on the spin-chain material cobalt niobate, …