Physical Sciences and Mathematics Commons^™

Research On High-Performance Emulation Technology Of Starlink Constellation Based On Cloud Platform, Yuan Liu, Xinyi Xue, Xiaofeng Wang

Journal of System Simulation

Abstract: Network emulation on Starlink constellation is an important verification and evaluation tool for the design and construction of low earth orbit constellations in the future. Aiming at the characteristics of large-scale and complex structure of the Starlink network, a high-performance satellite network emulation system is designed. Based on the distributed network emulation architecture of cloud platform, through the development of STK Engine underlying interface, satellite model library storage optimization and asynchronous message transmission technology, the rapid deployment of Starlink constellation is carried out, and has good scalability. The experimental results show that the proposed method can carry out …

Herbicide-Resistance In Turf Systems: Insights And Options For Managing Complexity, Jennifer H. Allen, David Ervin, George Frisvold, James T. Brosnan, James D. Mccurdy, Rebecca G. Bowling, Aaron J. Patton, Matthew T. Elmore, Travis W. Gannon, Lambert B. Mccarty, Multiple Additional Authors

Public Administration Faculty Publications and Presentations

Due to complex interactions between social and ecological systems, herbicide resistance has classic features of a “wicked problem.” Herbicide-resistant (HR) Poa annua poses a risk to sustainably managing U.S. turfgrass systems, but there is scant knowledge to guide its management. Six focus groups were conducted throughout the United States to gain understanding of socio-economic barriers to adopting herbicide-resistance management practices. Professionals from major turfgrass sectors (golf courses, sports fields, lawn care, and seed/sod production) were recruited as focus-group participants. Discussions emphasized challenges of the weed management of turfgrass systems as compared to agronomic crops. This included greater time constraints for …

Symplectic Reduction Along A Submanifold, Peter Crooks, Maxence Mayrand

Mathematics and Statistics Faculty Publications

We introduce the process of symplectic reduction along a submanifold as a uniform approach to taking quotients in symplectic geometry. This construction holds in the categories of smooth manifolds, complex analytic spaces, and complex algebraic varieties, and has an interpretation in terms of derived stacks in shifted symplectic geometry. It also encompasses Marsden-Weinstein-Meyer reduction, Mikami-Weinstein reduction, the pre-images of Poisson transversals under moment maps, symplectic cutting, symplectic implosion, and the Ginzburg-Kazhdan construction of Moore-Tachikawa varieties in topological quantum field theory. A key feature of our construction is a concrete and systematic association of a Hamiltonian G-space 𝔐_𝐺,𝑆 to …

Effects Of Pier Shading On Salt Marsh Plants In Mississippi, Daniel Taylor

Master's Theses

Saltmarshes are important environments that are valuable to both humans and wildlife. As saltmarshes are under threat from erosion, sea level rise, and human development, efforts should be made to conserve them. The vegetation that occupies these environments are vital to the continued preservation of saltmarshes. This study focuses on one potential threat, the effect that pier shading has on prominent saltmarsh plants of Mississippi, Sporobolus alterniflorus and Juncus roemarianus. Sample piers were selected in the three coastal counties of Mississippi and visited at two time periods (2006 and 2021). I focused on the use of irradiance measurements at …

Characterization Of 1d And 2d Materials With Tip-Enhanced Raman Spectroscopy, María Olivia Avilés

Electronic Thesis and Dissertation Repository

Carbon-based materials, such as 1D single-walled carbon nanotubes (SWCNT) or 2D graphene, are promising materials for a variety of applications in energy storage, biosensors, and medical imaging applications. Similarly, beyond graphene, 2D transition metal dichalcogenides (TDM) that can have either a metallic or semiconducting character have gained interest for potential applications in electronics and photonics. Specifically, metallic TMDs such as vanadium disulfide (VS₂) show potential applications in optoelectronics and lithium-ion batteries. On the other hand, semiconducting TDMs like tungsten disulfide (WS₂) show a direct band gap, making them interesting for photovoltaic applications, transistors, or photodetectors. The …

Water: Arizona's Ticking Time Bomb, Bailey Wambold

Access*: Interdisciplinary Journal of Student Research and Scholarship

For a landlocked state dominated by desert, Arizona has done an exceptional job supporting tremendous development and population growth with limited water resources. However, as climate change and anthropogenic environmental degradation further stress the region’s already-strained water resources, the future of Arizona’s still-growing populace hangs in the balance as current water policies and practices are proving inherently unsustainable. Despite an abundance of literature citing the consequences of a liberal attitude towards water in an arid climate, a myopic focus on promoting Arizona’s economic and political growth has resulted in the state’s modern need to adopt previously-unseen conservation measures in order …

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Remote Surface Optical Phonon Scattering In Ferroelectric Ba0.6Sr0.4Tio3 Gated Graphene, Hanying Chen, Tianlin Li, Yifei Hao, Anil Rajapitamahuni, Zhiyong Xiao, Stefan Schoeche, Mathias Schubert, Xia Hong

Xia Hong Publications

We report the effect of remote surface optical (RSO) phonon scattering on carrier mobility in monolayer graphene gated by ferroelectric oxide. We fabricate monolayer graphene transistors back-gated by epitaxial (001) Ba0.6Sr0.4TiO3 films, with field effect mobility up to 23,000 cm² V⁻¹ s⁻¹ achieved. Switching ferroelectric polarization induces nonvolatile modulation of resistance and quantum Hall effect in graphene at low temperatures. Ellipsometry spectroscopy studies reveal four pairs of optical phonon modes in Ba_0.6Sr_0.4TiO₃, from which we extract RSO phonon frequencies. The temperature dependence of resistivity in graphene can be well accounted for …

Comparative Behavioral Ecotoxicology Of Inland Silverside Larvae Exposed To Pyrethroids Across A Salinity Gradient, Sara J. Hutton, Samreen Siddiqui, Emily I. Pedersen, Christopher Y. Markgraf, Amelie Segarra, Michelle L. Hladik, Richard E. Connon, Susanne M. Brander

United States Geological Survey: Staff Publications

Pyrethroids, a class of commonly used insecticides, are frequently detected in aquatic environments, including estuaries. The influence that salinity has on organism physiology and the partitioning of hydrophobic chemicals, such as pyrethroids, has driven interest in how toxicity changes in saltwater compared to freshwater. Early life exposures in fish to pyrethroids cause toxicity at environmentally relevant concentrations, which can alter behavior. Behavior is a highly sensitive endpoint that influences overall organism fitness and can be used to detect toxicity of environmentally relevant concentrations of aquatic pollutants. Inland Silversides (Menidia beryllina), a commonly used euryhaline model fish species, were exposed …

Population Health Metrics During The Early Stages Of The Covid-19 Pandemic: Correlative Pilot Study, Marie A. Severson, David A. Cassada, Victor C. Huber, Daniel D. Snow, Lisa M. Mcfadden

Nebraska Water Center: Faculty Publications

Background: COVID-19 has caused nearly 1 million deaths in the United States, not to mention job losses, business and school closures, stay-at-home orders, and mask mandates. Many people have suffered increased anxiety and depression since the pandemic began. Not only have mental health symptoms become more prevalent, but alcohol consumption has also increased during this time. Helplines offer important insight into both physical and mental wellness of a population by offering immediate, anonymous, cheap, and accessible resources for health and substance use disorders (SUD) that was unobstructed by many of the mandates of the pandemic. Further, the pandemic also …

Ultrafast Electron Diffraction From Transiently Aligned Asymmetric Top Molecules: Rotational Dynamics And Structure Retrieval, Kyle Wilkin, Yanwei Xiong, Haoran Zhao, Sri Bhavya Muvva, S. K. Saha, Martin Centurion

Department of Physics and Astronomy: Faculty Publications

Ultrafast electron diffraction (UED) from aligned molecules in the gas phase has successfully retrieved structures of both linear and symmetric top molecules. Alignment of asymmetric tops has been recorded with UED but no structural information was retrieved. We present here the extraction of two-dimensional structural information from simple transformations of experimental diffraction patterns of aligned molecules as a proof-of-principle for the recovery of the full structure. We align 4-fluorobenzotrifluoride with a linearly polarized laser and show that we can distinguish between atomic pairs with equal distances that are parallel and perpendicular to the aligned axis. We additionally show with numerical …

Randomly Generating The 3d Mesostructure Of Soil Rock Mixtures Based On The Full In Situ Digital Image Processed Information, Zhengsheng Li, Haiyang Yi, Cheng Zhu, Zhuang Zhuo, Guoshuan Liu

Henry M. Rowan College of Engineering Departmental Research

Understanding the occurrence and evolution of geological disasters, such as landslides and debris flows, is facilitated by research on the performance of soil rock mixes (SRM). Recently, more and more researchers have been interested in studying the mesostructure reconstruction process of SRM. The present mesostructure generation approaches, however, have several weaknesses. One of the weaknesses is that they do not consider the impact of particle shape and therefore cannot ensure similarity to the in situ SRMs. In this study, a new mesostructure generation method that randomly generates SRMs based on the full in situ digital image processing (DIP) information is …

Predicting Guiding Entities For Entity Aspect Linking, Shubham Chatterjee, Laura Dietz

Computer Science Faculty Research & Creative Works

Entity linking can disambiguate mentions of an entity in text. However, there are many different aspects of an entity that could be discussed but are not differentiable by entity links, for example, the entity "oyster" in the context of "food" or "ecosystems". Entity aspect linking provides such fine-grained explicit semantics for entity links by identifying the most relevant aspect of an entity in the given context. We propose a novel entity aspect linking approach that outperforms several neural and non-neural baselines on a large-scale entity aspect linking test collection. Our approach uses a supervised neural entity ranking system to predict …

Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their consumption patterns enables targeting specific groups of consumers for DR. Traditional clustering algorithms use standard distance measurement to find the distance between two points. The results produced by clustering algorithms such as K-means, K-medoids, and Gaussian Mixture Models depend on the clustering parameters or initial clusters. In contrast, our methodology uses a shape-based approach that combines Agglomerative Hierarchical Clustering (AHC) with Dynamic Time Warping (DTW) to classify …

Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger

Electrical and Computer Engineering Publications

This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern …

Pausing While Programming: Insights From Keystroke Analysis, Raj Shrestha, Juho Leinonen, Albina Zavgorodniaia, Arto Hellas, John M. Edwards

Computer Science Student Research

Pauses in typing are generally considered to indicate cognitive processing and so are of interest in educational contexts. While much prior work has looked at typing behavior of Computer Science students, this paper presents results of a study specifically on the pausing behavior of students in Introductory Computer Programming. We investigate the frequency of pauses of different lengths, what last actions students take before pausing, and whether there is a correlation between pause length and performance in the course. We find evidence that frequency of pauses of all lengths is negatively correlated with performance, and that, while some keystrokes initiate …

Towards High Performing And Reliable Deep Convolutional Neural Network Models For Typically Limited Medical Imaging Datasets, Kaoutar Ben Ahmed

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence (AI) is “The science and engineering of making intelligent machines, especially intelligent computer programs”. Artificial Intelligence has been applied in a wide range of fields including automobiles, space, robotics, and healthcare.

According to recent reports, AI will have a huge impact on increasing the world economy by 2030 and it's expected that the greatest impact will be in the field of healthcare. The global market size of AI in healthcare was estimated at USD 10.4 billion in 2021 and is expected to grow at a high rate from 2022 to 2030 (CAGR of 38.4%). Applications of AI in …

Optimal Quantization For Some Triadic Uniform Cantor Distributions With Exact Bounds, Mrinal Kanti Roychowdhury

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Let {Sj:1≤j≤3} be a set of three contractive similarity mappings such that Sj(x)=rx+j−12(1−r) for all x∈R, and 1≤j≤3, where 0

Let {Sj:1≤j≤3}">{Sj:1≤j≤3}{Sj:1≤j≤3} be a set of three contractive similarity mappings such that Sj(x)=rx+j−12(1−r)">Sj(x)=rx+j−12(1−r)Sj(x)=rx+j−12(1−r) for all x∈R">x∈Rx∈R, and 1≤j≤3">1≤j≤31≤j≤3, where 0P has support the Cantor set generated by the similarity mappings Sj">SjSj for 1≤j≤3">1≤j≤31≤j≤3. Let r0=0.1622776602">r0=0.1622776602r0=0.1622776602, and r1=0.2317626315">r1=0.2317626315r1=0.2317626315 (which are ten digit rational approximations of two real numbers). In this paper, for 00n-means and the nth quantization errors for the triadic uniform Cantor distribution P for all positive integers n≥2">n≥2n≥2. Previously, …

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Ideating Xai: An Exploration Of User’S Mental Models Of An Ai-Driven Recruitment System Using A Design Thinking Approach, Helen Sheridan, Dympna O'Sullivan, Emma Murphy

Conference Papers

Artificial Intelligence (AI) is playing an important role in society including how vital, often life changing decisions are made. For this reason, interest in Explainable Artificial Intelligence (XAI) has grown in recent years as a means of revealing the processes and operations contained within what is often described as a black box, an often-opaque system whose decisions are difficult to understand by the end user. This paper presents the results of a design thinking workshop with 20 participants (computer science and graphic design students) where we sought to investigate users' mental models when interacting with AI systems. Using two personas, …

Mountain Rivers Reveal The Earthquake Hazard Of Geologic Faults In Silicon Valley, Felipe Aron, Samuel A. Johnstone, Andreas Mavrommatis, Robert Sare, Frantz Maerten, John P. Loveless, Curtis W. Baden, George E. Hilley

Geosciences: Faculty Publications

The 1989, Mw = 6.9 Loma Prieta earthquake resulted in tens of lives lost and cost California almost 3% of its gross domestic product. Despite widespread damage, the earthquake did not clearly rupture the surface, challenging the identification and characterization of these hidden hazards. Here, we show that they can be illuminated by inverting fluvial topography for slip-and moment accrual-rates—fundamental components in earthquake hazard assessments—along relief-generating geologic faults. We applied this technique to thrust faults bounding the mountains along the western side of Silicon Valley in the San Francisco Bay Area, and discovered that these structures may be capable of …

Educational Equivalency Of Raspberry Pi Clusters In High-Performance Computing, Victoria A. Steckline, Robert Houghton

Mountain Plains Business Conference

Abstract

High-performance computing is a difficult subject to teach in an academic setting, given the exorbitant costs and technical difficulties. Raspberry Pi single-board computers have been used in recent years to create clusters that function as mini high-performance computers. The purpose of this research is to evaluate the educational equivalence of building a Raspberry Pi cluster in comparison to running a high-performance computing environment. For this research, an eight-node cluster was built and tested in comparison to a laptop. Through the process of building the cluster, skills learned were documented to evaluate the educational value. This research concludes that the …

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An Investigation Of The Reconstruction Capacity Of Stacked Convolutional Autoencoders For Log-Mel-Spectrograms, Anastasia Natsiou, Luca Longo, Seán O'Leary

Conference Papers

In audio processing applications, the generation of expressive sounds based on high-level representations demonstrates a high demand. These representations can be used to manipulate the timbre and influence the synthesis of creative instrumental notes. Modern algorithms, such as neural networks, have inspired the development of expressive synthesizers based on musical instrument timbre compression. Unsupervised deep learning methods can achieve audio compression by training the network to learn a mapping from waveforms or spectrograms to low-dimensional representations. This study investigates the use of stacked convolutional autoencoders for the compression of time-frequency audio representations for a variety of instruments for a single …

Using Active Source Seismology To Image The Palos Verdes Fault Damage Zone As A Function Of Distance, Depth, And Geology, Travis Alongi, Emily E. Brodsky, Jared Kluesner, Daniel Brothers

United States Geological Survey: Staff Publications

Fault damage zones provide a window into the non-elastic processes of an earthquake. Geological and seismic tomography methods have been unable to measure damage zones at depth with sufficient spatial sampling to evaluate the relative influence of depth, distance, and lithological variations. Here, we identify and analyze the damage zone of the Palos Verdes Fault offshore southern California using two 3D seismic reflection datasets. We apply a novel algorithm to identify discontinuities attributed to faults and fractures in large seismic volumes and examine the spatial distribution of fault damage in sedimentary rock surrounding the Palos Verdes Fault. Our results show …

Tutorial: Neuro-Symbolic Ai For Mental Healthcare, Kaushik Roy, Usha Lokala, Manas Gaur, Amit Sheth

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

Synthesis Of Novel Dna-Binding Polyamides To Prevent Cancer-Related Gene Overexpression, Huy Q. Nguyen

Dissertations

Pyrrole-imidazole polyamides (PIPs) are nanomolecular compounds designed to fit in the tight space of DNA minor grooves. As analogs of Netropsin and Distamycin A, PIPs are specifically designed to recognize the base pairs of DNA sequences. PIPs have many biological applications, such as regulating gene expression, biochemistry pathway regulations, and suppressing the development of cancer cells. SETMAR gene is the chimeric fusion of the SET domain with the mariner transposase. Its protein (Metnase) has functions involving DNA repairs in the NHEJ pathway, regulating gene expression, DNA decatenation, etc. Despite not having an active transposable element, SETMAR still has an unknown …

Potential Of Vision Transformers For Advanced Driver-Assistance Systems: An Evaluative Approach, Andrew Katoch

Electronic Thesis and Dissertation Repository

In this thesis, we examine the performance of Vision Transformers concerning the current state of Advanced Driving Assistance Systems (ADAS). We explore the Vision Transformer model and its variants on the problems of vehicle computer vision. Vision transformers show performance competitive to convolutional neural networks but require much more training data. Vision transformers are also more robust to image permutations than CNNs. Additionally, Vision Transformers have a lower pre-training compute cost but can overfit on smaller datasets more easily than CNNs. Thus we apply this knowledge to tune Vision transformers on ADAS image datasets, including general traffic objects, vehicles, traffic …

Fine Tuning The Pore Surface In Zirconium Metal−Organic Frameworks For Selective Ethane/Ethylene Separation, Yuchen Hu, Yanshu Shi, Yi Xie, Rebecca Shu Hui Khoo, Christian Fiankor, Xu Zhang,, Banglin Chen, Jian Zhang

Chemistry Department: Faculty Publications

Ethylene is an important chemical feedstock for production of polymers and high-value organic chemicals, and yet its conventional purification process is plagued with high consumption of energy. Metal−organic frameworks (MOFs) provide a suitable adsorption platform for selective ethane/ ethylene separation thanks to their structural diversity, tunable pore characteristics, designable pore sizes, and high pore volumes. Although there are empirical design rules like avoiding open metal sites and creating nonpolar pore surfaces for development of adsorptive MOFs, it is still challenging to design robust MOFs that can realize direct ethane-selective separation. Herein, we systematically designed and synthesized three Zr-MOFs based on …

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No abstract provided.