Physical Sciences and Mathematics Commons^™

Combination Of High Ph And An Antioxidant Improves Chemical Stability Of Two-Dimensional Transition-Metal Carbides And Carbonitrides (Mxenes) In Aqueous Colloidal Solutions, Shuohan Huang, Vadym Mochalin

Chemistry Faculty Research & Creative Works

MXenes, a large family of two-dimensional (2D) transition-metal carbides/nitrides, have attracted increased attention in recent years because of their excellent electronic, mechanical, thermal, and optical properties. Studying chemical properties of MXenes is important to prolong the shelf life of their colloids and provide robust performance of MXenes in devices and applications. While the role of MXene reactivity with the environment, including water and components of air, is becoming more recognized, less is known about the role of parameters influencing the reactivity. In this work, we investigate the individual and combined effects of the pH and antioxidant on chemical stability of …

Response Of Surface And Atmospheric Parameters Associated With The Iran M 7.3 Earthquake, Feng Jing, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Multiparameter observed from satellite, including microwave brightness temperature, skin temperature, air temperature, and carbon monoxide, have been analyzed to identify the anomalous signals associated with the M 7.3 Iran earthquake of November 12, 2017. Besides removing the multiyear variability of parameters as background, the effect of surface and atmosphere of a dust storm event in Middle East region during October 29–November 1 is considered to distinguish the possible anomalies associated with the earthquake. The characteristic behaviors of surface and atmospheric parameters clearly show the signals associated with the M 7.3 earthquake and the dust storm event. The multiple parameters at …

Fuzzy Reasoning Procedure For Ontologies Based On Rough Membership Approximation, Armand Florentin Donfack Kana, Babatunde Opeoluwa Akinkunmi

Future Computing and Informatics Journal

One of the major challenges in modeling a real-world domain is how to effectively represent uncertain and incomplete knowledge of that domain. Several techniques for representing uncertainty in ontologies have been proposed with some of the techniques lacking provision for vague inference. The classical tableaux-based algorithm does not provide the flexibility for reasoning over such vague ontologies. However, several extensions of the tableaux-based algorithm have been proposed to cope with fuzzy reasoning. Similarly, several alternative reasoning methods for incomplete, inconsistent, and uncertain ontologies have been proposed. One of the major limitations of most of those techniques is that they require …

Textual Emotion Detection Approaches: A Survey, Mahinda Mahmoud Samy Zidan, Ibrahim Elhenawy, Ahmed R. Abas, Mahmoud Othman

Future Computing and Informatics Journal

Over the past decades, social media attracted individuals to express their feelings on any topic or item, resulting in an incremental growth in the size of created data. These feelings and unstructured data paved the path for business organizations to gather information and build statistical analysis. Various machine learning and natural language processing-based approaches are used for sentiment and emotion analysis. Moreover, deep learning-based approaches recently gained popularity due to their remarkable performance in text analysis. This paper provides a comprehensive overview of the prominent machine learning models applied in emotion analysis. It explores various emotion analysis taxonomies, in addition …

An Empirical Study Towards An Automatic Phishing Attack Detection Using Ensemble Stacking Model, Mahmoud Othman, Hesham Hassan

Future Computing and Informatics Journal

Phishing attacks have become one of the most attacks facing internet users, especially after the COVID-19 pandemic, as most organizations have transferred part or most of their work and communication to become online using well-known tools, like email, Zoom, WebEx, etc. Therefore, cyber phishing attacks have become progressively recent, directly and frankly reflecting the designated website, allowing the attacker to observe everything while the victim is exploring Webpages. Hence, utilizing Artificial Intelligence (AI) techniques has become a necessary approach that could be used to detect such attacks automatically. In this paper, we introduce an empirical analysis for automatic phishing detection …

Breeding Ecology Of Mottled Ducks In Southwestern Louisiana, Elizabeth Sophia Bonczek

LSU Doctoral Dissertations

Mottled ducks are a resident species found in the southern United States that rely on coastal marsh and associated habitat to fulfill the needs of the entirety of their annual cycle. Population monitoring has revealed declines in western Gulf Coast (WGC) mottled ducks since 2008. Mottled duck populations are influenced by survival and recruitment, and changes in these factors may contribute to population declines. The overarching goal of this project was to identify the mechanisms potentially limiting WGC mottled ducks.

I captured adult female mottled ducks during molt on Rockefeller Wildlife Refuge and adjacent lands in southwestern Louisiana from 2017–2019. …

A Comparative Study On Deep Learning Models For Text Classification Of Unstructured Medical Notes With Various Levels Of Class Imbalance, Hongxia Lu, Louis Ehwerhemuepha, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Background

Discharge medical notes written by physicians contain important information about the health condition of patients. Many deep learning algorithms have been successfully applied to extract important information from unstructured medical notes data that can entail subsequent actionable results in the medical domain. This study aims to explore the model performance of various deep learning algorithms in text classification tasks on medical notes with respect to different disease class imbalance scenarios.

Methods

In this study, we employed seven artificial intelligence models, a CNN (Convolutional Neural Network), a Transformer encoder, a pretrained BERT (Bidirectional Encoder Representations from Transformers), and four typical …

The Interaction And Orientation Of Peptide Kl4 In Model Membranes, Drew Marquardt, Brad Van Oosten, Maksymilian Dziura, Joanna R. Long, Thad A. Harroun

Chemistry and Biochemistry Publications

We report on the orientation and location of synthetic pulmonary surfactant peptide KL4, (KLLLL)4K, in model lipid membranes. The partitioning depths of selectively deuterated leucine residues within KL4 were determined in DPPC:POPG (4:1) and POPC:POPG (4:1) bilayers by oriented neutron diffraction. These measurements were combined with an NMR-generated model of the peptide structure to determine the orientation and partitioning of the peptide at the lipid–water interface. The results demonstrate KL4 adopting an orientation that interacts with a single membrane leaflet. These observations are consistent with past 2H NMR and EPR studies (Antharam et al., 2009; Turner et al., 2014).

Understanding Compactness Through Primary Sources: Early Work Uniform Continuity To The Heine-Borel Theorem, Naveen Somasunderam

Analysis

No abstract provided.

Asymmetric Control Of Light At The Nanoscale, Christos Argyropoulos

Department of Electrical and Computer Engineering: Faculty Publications

Breaking reciprocity at the nanoscale can produce directional formation of images due to the asymmetric nonlinear optical response of subwavelength anisotropic resonators. The self-induced passive non-reciprocity has advantages compared to magnet or time modulation approaches and may impact both classical and quantum photonics.

Monitoring Whitebark Pine Stand Health In The Central Washington Cascades, Nancy H. Parra, Teresa J. Lorenz, Taza D. Schaming, Alison Scoville

Student Published Works

Whitebark pine (Pinus albicaulis) plays a vital role in colonizing newly disturbed areas, providing shade for other tree species to germinate, and supplying food for a variety of birds and mammals, such as Clark’s Nutcrackers (Nucifraga columbiana) and grizzly bears (Ursus arctos horribilis). Decline of whitebark pine populations has been attributed to several factors, including white pine blister rust (Cronartium ribicola), mountain pine beetle (Dendroctonus ponderosae) outbreaks, and fire exclusion. In 2009, the U.S. Forest Service began to install permanent plots in whitebark pine stands in Washington and Oregon as …

Can You Master This? : Initial Attempts At Specifications-Based Grading In Introductory Chemistry, Laura Kopff

Faculty Publications & Research

The Illinois Mathematics and Science Academy (IMSA) requires all incoming students to complete a one-semester introductory chemistry course in their sophomore year – Scientific Inquiries in Chemistry (SI-Chem). This course has historically been taught using a traditional grading/assessment model, however, in the Spring of 2021, a switch was made to a specification-based grading system. One motivating factor in this decision is an institutional shift to an equity-focused grading approach, and an analysis of our historical assessment model indicated areas for improvement.

Our initial foray into specifications grading was during the Spring of 2021 semester, when all of our courses were …

The Close Agn Reference Survey (Cars): Tracing The Circumnuclear Star Formation In The Super-Eddington Nls1 Mrk 1044, N. Winkel, T. A. Davis, I. Smirnova-Pinchukova, V. N. Bennert, F. Combes, M. Gaspari, K. Jahnke, J. Neumann, C. P. O'Dea, M. Pérez-Torres, M. Singha, G. R. Tremblay, H. W. Rix

Physics

Context. The host galaxy conditions for rapid supermassive black hole growth are poorly understood. Narrow-line Seyfert 1 (NLS1) galaxies often exhibit high accretion rates and are hypothesized to be prototypes of active galactic nuclei (AGN) at an early stage of their evolution.

Aims. We present adaptive optics (AO) assisted VLT MUSE NFM observations of Mrk 1044, the nearest super-Eddington accreting NLS1. Together with archival MUSE WFM data, we aim to understand the host galaxy processes that drive Mrk 1044’s black hole accretion.

Methods. We extracted the faint stellar continuum emission from the AGN-deblended host and performed spatially resolved emission line …

A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian Lyons, James Finocchiaro, Misha Novitsky, Chris Korpela

Faculty Publications

Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …

Watershed Prioritization To Reduce Nutrient Export: A Framework For The State Of Arkansas Based On Ambient Water Quality Monitoring Data, Erin Grantz, Brian E. Haggard

Technical Reports

The annual formation of the Northern Gulf of Mexico hypoxic zone is driven by nutrient loading from the Mississippi-Atchafalaya River Basin (MARB). Member States of The Mississippi River/Gulf of Mexico Hypoxia Task have developed statewide strategies to identify priorities and opportunities for nutrient export reduction in the MARB. In 2014, the State of Arkansas joined the Task Force and initiated an Arkansas Nutrient Reduction Strategy (ANRS), which currently prioritizes ten Hydrologic Unit Code 8 (HUC-8) watersheds (ANRD, 2014). These priority watersheds were not selected based on measured in-stream nutrient concentrations or trends, which impedes quantitative assessment, goal setting, and linking …

Derivation And Analysis Of A Discrete Predator–Prey Model, Sabrina H. Streipert, Gail S.K. Wolkowicz, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

We derive a discrete predator–prey model from first principles, assuming that the prey population grows to carrying capacity in the absence of predators and that the predator population requires prey in order to grow. The proposed derivation method exploits a technique known from economics that describes the relationship between continuous and discrete compounding of bonds. We extend standard phase plane analysis by introducing the next iterate root-curve associated with the nontrivial prey nullcline. Using this curve in combination with the nullclines and direction field, we show that the prey-only equilibrium is globally asymptotic stability if the prey consumption-energy rate of …

Deep Convolution Neural Networks For Image Classification, Arun D. Kulkarni

Computer Science Faculty Publications and Presentations

Deep learning is a highly active area of research in machine learning community. Deep Convolutional Neural Networks (DCNNs) present a machine learning tool that enables the computer to learn from image samples and extract internal representations or properties underlying grouping or categories of the images. DCNNs have been used successfully for image classification, object recognition, image segmentation, and image retrieval tasks. DCNN models such as Alex Net, VGG Net, and Google Net have been used to classify large dataset having millions of images into thousand classes. In this paper, we present a brief review of DCNNs and results of our …

A Review Of Impact Assessments For Deep-Sea Fisheries On The High Seas, Laura Kaikkonen, Lissette Victorero, Matthew Gianni, Teresa Amaro, Sofia Graça Aranha, Peter J. Auster, David M. Bailey, James Bell, Angelika Brandt, Jeff Drazen, Malcolm R. Clark, Cherisse Du Preez, Isa Elegbede Olalekan, Elva Escobar-Briones, Eva Giacomello, Kerry L. Howell, Andrew F. Johnson, Lisa Levin, Lucien Maloueki, Rosanna J. Milligan, Tina N. Molodtsova, Stephen Oduware, Tabitha R R Pearman, Christopher K. Pham, Sofia P. Ramalho, Ashley A. Rowden, Tracey Sutton, Michelle Taylor, Les Watling, Patience Whitten

Marine & Environmental Sciences Faculty Reports

The intensity of deep-sea fisheries on the high seas and the impacts on the marine environment call for effective measures to ensure that fishing does not compromise the commitments established for protecting biodiversity in the deep ocean by the United Nations. In order to prevent significant adverse impacts (SAIs) on vulnerable marine ecosystems (VMEs), high seas fishing nations agreed to stop fishing activities where VMEs are known or likely to occur unless the fishing can be managed to prevent SAIs on VMEs. To determine whether fishing activities can be conducted in a sustainable manner that prevents impacts on VMEs, States …

How To Detect The Fundamental Frequency: Approach Motivated By Soft Computing And Computational Complexity, Eric Freudenthal, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Psychologists have shown that most information about the mood and attitude of a speaker is carried by the lowest (fundamental) frequency. Because of this frequency's importance, even when the corresponding Fourier component is weak, the human brain reconstruct this frequency based on higher harmonics. The problems is that many people lack this ability. To help them better understand moods and attitudes in social interaction, it is therefore desirable to come up with devices and algorithms that would reconstruct the fundamental frequency. In this paper, we show that ideas from soft computing and computational complexity can be used for this purpose.

Over-Measurement Paradox: Suspension Of Thermonuclear Research Center And Need To Update Standards, Hector Reyes, Saeid Tizpaz-Niari, Vladik Kreinovich

Departmental Technical Reports (CS)

In general, the more measurements we perform, the more information we gain about the system and thus, the more adequate decisions we will be able to make. However, in situations when we perform measurements to check for safety, the situation is sometimes opposite: the more additional measurements we perform beyond what is required, the worse the decisions will be: namely, the higher the chance that a perfectly safe system will be erroneously classified as unsafe and therefore, unnecessary additional features will be added to the system design. This is not just a theoretical possibility: exactly this phenomenon is one of …

Why Would Anyone Invest In A High-Risk Low-Profit Enterprise?, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Strangely enough, investors invest in high-risk low-profit enterprises as well. At first glance, this seems to contradict common sense and financial basics. However, we show that such investments make perfect sense as long as the related risks are independent from the risks of other investments. Moreover, we show that an optimal investment portfolio should allocate some investment to this enterprise.

Why Shapley Value And Its Variants Are Useful In Machine Learning (And In Other Applications), Laxman Bokati, Olga Kosheleva, Vladik Kreinovich, Nguye Ngoc Thach

Departmental Technical Reports (CS)

Shapley value -- a useful way to allocate gains in cooperative games -- has been very successful in machine learning (and in other applications beyond cooperative games). This success is somewhat puzzling, since the usual derivation of the Shapley value is based on requirements like additivity that are natural in cooperative games and but not ents like additivity and is, thus, applicable in the machine learning case as well.

Why Rectified Power (Repu) Activation Functions Are Efficient In Deep Learning: A Theoretical Explanation, Laxman Bokati, Vladik Kreinovich, Joseph Baca, Natasha Rovelli

Departmental Technical Reports (CS)

At present, the most efficient machine learning techniques is deep learning, with neurons using Rectified Linear (ReLU) activation function s(z) = max(0,z), in many cases, the use of Rectified Power (RePU) activation functions (s(z))^p -- for some p -- leads to better results. In this paper, we explain these results by proving that RePU functions (or their "leaky" versions) are optimal with respect that all reasonable optimality criteria.

Search For The Radiative Penguin Decays B0 → Ks0 Ks0 Γ In The Belle Experiment, H. B. Jeon, K. H. Kang, H. Park, I. Adachi, H. Aihara, S. Al Said, D. M. Asner, H. Atmacan, T. Aushev, R. Ayad, V. Babu, S. Bahinipati, P. Behera, K. Belous, J. Bennett, F. Bernlochner, M. Bessner, V. Bhardwaj, B. Bhuyan

Faculty and Student Publications

We report results from the first search for the rare penguin-dominated decay mode B0→KS0KS0γ, which can result from the production of tensor mesons f(1270) and f′(1525) in association with a photon. The search uses the full data sample of 772×106 BB¯ pairs collected with the Belle detector at the KEKB asymmetric-energy e+e- collider. No statistically significant signals are observed in the KS0KS0 invariant mass range 1 GeV/c2

Modeling The Electronic Properties For Cnt Interacted With Zno, Cuo, And Co3o4, Mohamed Morsy

Nanotechnology Research Centre

No abstract provided.

Zero Trust Architecture: Framework And Case Study, Cody Shepherd

Cyber Operations and Resilience Program Graduate Projects

The world and business are connected and a business does not exist today that does not have potentially thousands of connections to the Internet in addition to the thousands of connections to other various parts of its own infrastructure. That is the nature of the digital world we live in and there is no chance the number of those interconnections will reduce in the future. Protecting from the “outside” world with a perimeter solution might have been enough to reduce risk to an acceptable level in an organization 20 years ago, but today’s threats are sophisticated, persistent, abundant, and can …

Whole Farm Net Zero: Approaches To Quantification Of Climate Regulation Ecosystem Services At The Whole Farm Scale. Vermont Payment For Ecosystem Services Technical Report #7, Christopher Bonasia, Lindsey Ruhl, Benjamin Timothy Dube, Alissa C. White, Heather M. Darby

UVM Extension Faculty Publications

In this report, approaches to the quantification of climate mitigation ecosystem services at the whole farm scale are reviewed and summarized for easy comparison. Eight quantification tools, and three case studies demonstrating possible tool applications, are summarized to fulfill the requirements of the Technical Services Contract—Task 7. Information from a combination of literature review and expert interviews served to document the inputs, outputs, strengths, weaknesses, opportunities, and threats for each quantification tool. This research was conducted in service to the Vermont Soil Health and Payment for Ecosystem Services (PES) Working Group (VT PES working group). It is our hope that …

Image-Based Crack Detection By Extracting Depth Of The Crack Using Machine Learning, Nishat Tabassum

Theses and Dissertations

Concrete structures have been a major aspect of social infrastructure since the ancient Roman times, so they have been used for many centuries. Concrete is used for the durability and support it provides to buildings and bridges. Assessing the state of these structures is important in preserving the longevity of structures and the safety of the public. Detecting cracks in their early stage allows repairs to be made without the need to replace the whole structure, so it reduces the cost. Traditional methods are slowly falling behind as technology advances and an increase in demand for a practical method of …

Strategic Signaling For Utility Control In Audit Games, Jianan Chen, Qin Hu, Honglu Jiang

Informatics and Engineering Systems Faculty Publications and Presentations

As an effective method to protect the daily access to sensitive data against malicious attacks, the audit mechanism has been widely deployed in various practical fields. In order to examine security vulnerabilities and prevent the leakage of sensitive data in a timely manner, the database logging system usually employs an online signaling scheme to issue an alert when suspicious access is detected. Defenders can audit alerts to reduce potential damage. This interaction process between a defender and an attacker can be modeled as an audit game. In previous studies, it was found that sending real-time signals in the audit …

Fair, Equitable, And Just: A Socio-Technical Approach To Online Safety, Daricia Wilkinson

All Dissertations

Socio-technical systems have been revolutionary in reshaping how people maintain relationships, learn about new opportunities, engage in meaningful discourse, and even express grief and frustrations. At the same time, these systems have been central in the proliferation of harmful behaviors online as internet users are confronted with serious and pervasive threats at alarming rates. Although researchers and companies have attempted to develop tools to mitigate threats, the perception of dominant (often Western) frameworks as the standard for the implementation of safety mechanisms fails to account for imbalances, inequalities, and injustices in non-Western civilizations like the Caribbean. Therefore, in this dissertation …