Physical Sciences and Mathematics Commons^™

Somewhat Surprisingly, (Subjective) Fuzzy Technique Can Help To Better Combine Measurement Results And Expert Estimates Into A Model With Guaranteed Accuracy: Digital Twins And Beyond, Niklas Winnewisser, Michael Beer, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

To understand how different factors and different control strategies will affect a system -- be it a plant, an airplane, etc. -- it is desirable to form an accurate digital model of this system. Such models are known as digital twins. To make a digital twin as accurate as possible, it is desirable to incorporate all available knowledge of the system into this model. In many cases, a significant part of this knowledge comes in terms of expert statements, statements that are often formulated by using imprecise ("fuzzy") words from natural language such as "small", "very possible", etc. To translate …

How To Gauge Inequality And Fairness: A Complete Description Of All Decomposable Versions Of Theil Index, Saeid Tizpaz-Niari, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In general, in statistics, the most widely used way to describe the difference between different elements of a sample if by using standard deviation. This characteristic has a nice property of being decomposable: e.g., to compute the mean and standard deviation of the income overall the whole US, it is sufficient to compute the number of people, mean, and standard deviation over each state; this state-by-state information is sufficient to uniquely reconstruct the overall standard deviation. However, e.g., for gauging income inequality, standard deviation is not very adequate: it provides too much weight to outliers like billionaires, and thus, does …

Update From Aristotle To Newton, From Sets To Fuzzy Sets, And From Sigmoid To Relu: What Do All These Transitions Have In Common?, Christian Servin, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we show that there is a -- somewhat unexpected -- common trend behind several seemingly unrelated historic transitions: from Aristotelian physics to modern (Newton's) approach, from crisp sets (such as intervals) to fuzzy sets, and from traditional neural networks, with close-to-step-function sigmoid activation functions to modern successful deep neural networks that use a completely different ReLU activation function. In all these cases, the main idea of the corresponding transition can be explained, in mathematical terms, as going from the first order to second order differential equations.

How To Make A Decision Under Interval Uncertainty If We Do Not Know The Utility Function, Jeffrey Escamilla, Vladik Kreinovich

Departmental Technical Reports (CS)

Decision theory describes how to make decisions, in particular, how to make decisions under interval uncertainty. However, this theory's recommendations assume that we know the utility function -- a function that describes the decision maker's preferences. Sometimes, we can make a recommendation even when we do not know the utility function. In this paper, we provide a complete description of all such cases.

Paradox Of Causality And Paradoxes Of Set Theory, Alondra Baquier, Bradley Beltran, Gabriel Miki-Silva, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Logical paradoxes show that human reasoning is not always fully captured by the traditional 2-valued logic, that this logic's extensions -- such as multi-valued logics -- are needed. Because of this, the study of paradoxes is important for research on multi-valued logics. In this paper, we focus on paradoxes of set theory. Specifically, we show their analogy with the known paradox of causality, and we use this analogy to come up with similar set-theoretic paradoxes.

Number Representation With Varying Number Of Bits, Anuradha Choudhury, Md Ahsanul Haque, Saeefa Rubaiyet Nowmi, Ahmed Ann Noor Ryen, Sabrina Saika, Vladik Kreinovich

Departmental Technical Reports (CS)

In a computer, usually, all real numbers are stored by using the same number of bits: usually, 8 bytes, i.e., 64 bits. This amount of bits enables us to represent numbers with high accuracy -- up to 19 decimal digits. However, in most cases -- whether we process measurement results or whether we process expert-generated membership degrees -- we do not need that accuracy, so most bits are wasted. To save space, it is therefore reasonable to consider representations with varying number of bits. This would save space used for representing numbers themselves, but we would also need to store …

Data Fusion Is More Complex Than Data Processing: A Proof, Robert Alvarez, Salvador Ruiz, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

Empirical data shows that, in general, data fusion takes more computation time than data processing. In this paper, we provide a proof that data fusion is indeed more complex than data processing.

How To Fairly Allocate Safety Benefits Of Self-Driving Cars, Fernando Munoz, Christian Servin, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we describe how to fairly allocated safety benefits of self-driving cars between drivers and pedestrians -- so as to minimize the overall harm.

Using Known Relation Between Quantities To Make Measurements More Accurate And More Reliable, Niklas Winnewisser, Felix Mett, Michael Beer, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Most of our knowledge comes, ultimately, from measurements and from processing measurement results. In this, metrology is very valuable: it teaches us how to gauge the accuracy of the measurement results and of the results of data processing, and how to calibrate the measuring instruments so as to reach the maximum accuracy. However, traditional metrology mostly concentrates on individual measurements. In practice, often, there are also relations between the current values of different quantities. For example, there is usually an known upper bound on the difference between the values of the same quantity at close moments of time or at …

Combating Financial Crimes With Unsupervised Learning Techniques: Clustering And Dimensionality Reduction For Anti-Money Laundering, Ahmed N. Bakry, Almohammady S. Alsharkawy, Mohamed S. Farag, Kamal R. Raslan

Al-Azhar Bulletin of Science

Anti-Money Laundering (AML) is a crucial task in ensuring the integrity of financial systems. One keychallenge in AML is identifying high-risk groups based on their behavior. Unsupervised learning, particularly clustering, is a promising solution for this task. However, the use of hundreds of features todescribe behavior results in a highdimensional dataset that negatively impacts clustering performance.In this paper, we investigate the effectiveness of combining clustering method agglomerative hierarchicalclustering with four dimensionality reduction techniques -Independent Component Analysis (ICA), andKernel Principal Component Analysis (KPCA), Singular Value Decomposition (SVD), Locality Preserving Projections (LPP)- to overcome the issue of high-dimensionality in AML data and …

Graph Neural Network Guided By Feature Selection And Centrality Measures For Node Classification On Homophilic And Heterophily Graphs, Asmaa M. Mahmoud, Heba F. Eid, Abeer S. Desuky, Hoda A. Ali

Al-Azhar Bulletin of Science

One of the most recent developments in the fields of deep learning and machine learning is Graph Neural Networks (GNNs). GNNs core task is the feature aggregation stage, which is carried out over the node's neighbours without taking into account whether the features are relevant or not. Additionally, the majority of these existing node representation techniques only consider the network's topology structure while completely ignoring the centrality information. In this paper, a new technique for explaining graph features depending on four different feature selection approaches and centrality measures in order to identify the important nodes and relevant node features is …

Moid Using New Sets Of Universal Functions, Ayman Homda, Hany R. Dwidar, Abdelaziz A. Bakry, M.N. Mohamad Ismail, Ahmed El-Raffie

Al-Azhar Bulletin of Science

In this paper, based on Goodyear's time transformation formula, we used a set of modified universal functions to construct the minimum distance function between any two celestial objects. We determined the distance between objects in space under a specific time constraint. We used the continued fractions method for quick convergence of the distance function. We used the inverse series to obtain a first initial guess to solve the convergence equation. Furthermore, the Lagrange multiplier method was used to determine the minimum distance between the two objects under the specified time constraint. We constructed an algorithm and applied it with the …

Applications Of Survival Estimation Under Stochastic Order To Cancer: The Three Sample Problem, Sage Vantine

Honors Program Theses and Research Projects

Stochastic ordering of probability distributions holds various practical applications. However, in real-world scenarios, the empirical survival functions extracted from actual data often fail to meet the requirements of stochastic ordering. Consequently, we must devise methods to estimate these distribution curves in order to satisfy the constraint. In practical applications, such as the investigation of the time of death or the progression of diseases like cancer, we frequently observe that patients with one condition are expected to exhibit a higher likelihood of survival at all time points compared to those with a different condition. Nevertheless, when we attempt to fit a …

Robot Proficiency Self-Assessment Using Assumption-Alignment Tracking, Xuan Cao

Theses and Dissertations

A robot is proficient if its performance for its task(s) satisfies a specific standard. While the design of autonomous robots often emphasizes such proficiency, another important attribute of autonomous robot systems is their ability to evaluate their own proficiency. A robot should be able to conduct proficiency self-assessment (PSA), i.e. assess how well it can perform a task before, during, and after it has attempted the task. We propose the assumption-alignment tracking (AAT) method, which provides time-indexed assessments of the veracity of robot generators' assumptions, for designing autonomous robots that can effectively evaluate their own performance. AAT can be considered …

Low Cost Magnetometer Calibration And Distributed Simultaneous Multipoint Ionospheric Measurements From A Sounding Rocket Platform, Joshua W. Milford

Doctoral Dissertations and Master's Theses

Low-cost and low-size-weight-and-power (SWaP) magnetometers can provide greater accessibility for distributed simultaneous measurements in the ionosphere, either onboard sounding rockets or on CubeSats. The Space and Atmospheric Instrumentation Laboratory (SAIL) at Embry-Riddle Aeronautical University has launched a multitude of sounding rockets in recent history: one night-time mid-latitude rocket from Wallops Flight Facility in August 2022 and three mid-latitude rockets from White Sands Missile Range during the October 2023 annular solar eclipse. All rockets had a comprehensive suite of instruments for electrodynamics and neutral dynamics measurements. Among this suite was one science-grade three-axis fluxgate magnetometer (Billingsley TFM65VQS / TFM100G2) and up …

Creating A Sustainabili-Tour, Lily Dubray, Caden Fisher, Allison Gross, Morgan Hrivnak, Emily Kilstrom, Sushant Mukhia, Hannah Nelin, Sam Parrish, Waverly Patterson, Bowen Rand, Caleb Swanson, Wyatt Wiebelhaus

Sustainability & Environment Projects

Executive Summary

The University of South Dakota has taken significant steps to become more sustainable in the last few years. Students, faculty, and administrators have worked together to raise awareness and advance sustainability on campus. Because of these efforts, the University of South Dakota was recently recognized by the Association for the Advancement of Sustainability in Higher Education as a STARS Bronze Institution based on our accomplishments in campus sustainability.

Every year, Dr. Meghann Jarchow teaches the Sustainability Capstone course, leading a class of seniors on a semester-long project aimed at furthering community sustainability by synthesizing student expertise. Throughout …

An Investigation On The Intricacies Of Epigenetic Modulations In The Pathogenesis Of Human Papillomavirus-Associated Cervical Cancer: A Comprehensive Meta-Narrative Synthesis, Jade Carolina Cabello, Marcella Victoria Ras, Katelyn Thy Nhung Tran, Athit Voytas

Research Methods Poster Session 2024

Abstract

Objective: To conduct a meta-analysis of the available and relevant literature on E1/E2 genes and their affect on the epigenetics of Human Papillomavirus caused uterine cervical cancer.

Background/Significance: Human Papillomavirus is strongly linked to cervical cancer, and cervical cancer is the fourth most common type of cancer in women. 99.7% of patients with cervical cancer have a “high risk HPV genotype” which factors greatly into the causation if their diagnosis. The HPV vaccine that came out in 2006 has greatly decreased cervical cancer in the population as well as increased the preventative chances of highly susceptible individuals.

Methods: To …

Modeling And Numerical Analysis Of The Cholesteric Landau-De Gennes Model, Andrew L. Hicks

LSU Doctoral Dissertations

This thesis gives an analysis of modeling and numerical issues in the Landau-de Gennes (LdG) model of nematic liquid crystals (LCs) with cholesteric effects. We derive various time-step restrictions for a (weighted) $L^2$ gradient flow scheme to be energy decreasing. Furthermore, we prove a mesh size restriction, for finite element discretizations, that is critical to avoid spurious numerical artifacts in discrete minimizers that is not well-known in the LC literature, particularly when simulating cholesteric LCs that exhibit ``twist''. Furthermore, we perform a computational exploration of the model and present several numerical simulations in 3-D, on both slab geometries and spherical …

Rethinking Plagiarism In The Era Of Generative Ai, James Hutson

Faculty Scholarship

The emergence of generative artificial intelligence (AI) technologies, such as large language models (LLMs) like ChatGPT, has precipitated a paradigm shift in the realms of academic writing, plagiarism, and intellectual property. This article explores the evolving landscape of English composition courses, traditionally designed to develop critical thinking through writing. As AI becomes increasingly integrated into the academic sphere, it necessitates a reevaluation of originality in writing, the purpose of learning research and writing, and the frameworks governing intellectual property (IP) and plagiarism. The paper commences with a statistical analysis contrasting the actual use of LLMs in academic dishonesty with educator …

Hydrologic Impact Index For The Pinhoti Hiking Trail, Allie Field

Theses

This study aimed to identify flood-prone areas along the Pinhoti Trail and Chinnabee Silent Trail in the Talladega National Forest. Using the Hydrology Flood Index layer that was created using several essential data layers, the research aimed to provide campers, hikers, nature enthusiasts, and trail maintenance teams with information about areas at a higher risk of flash flooding. The Hydrology Flood Index layer rates the risk of flooding on a scale of 1 to 4, with level 1 indicating a low risk of flooding and level 4 indicating an extremely high risk. The data layers for analyzing flood hazards for …

Groundwater In Nebraska, Troy E. Gilmore, Jesse T. Korus Dr.

Conservation and Survey Division

What is groundwater? Groundwater is water that fills and moves between spaces in underground rocks, gravel, sand, or other materials.

Iowa Waste Reduction Center Newsletter, April 2024, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

In this issue:

--- Office of International Engagement Thanks Volunteers
--- A Quick Glance at EPA’s New PFAS Regulations
--- Strategic Goals Workshop Update
--- Celebrating Earth Day 2024

Exploring Quaternion Neural Network Loss Surfaces, Jeremiah Bill, Bruce A. Cox

Faculty Publications

This paper explores the superior performance of quaternion multi-layer perceptron (QMLP) neural networks over real-valued multi-layer perceptron (MLP) neural networks, a phenomenon that has been empirically observed but not thoroughly investigated. The study utilizes loss surface visualization and projection techniques to examine quaternion-based optimization loss surfaces for the first time. The primary contribution of this research is the statistical evidence that QMLP models yield smoother loss surfaces than real-valued neural networks, which are measured and compared using a robust quantitative measure of loss surface “goodness” based on estimates of surface curvature. Extensive computational testing validates the effectiveness of these surface …

Finding The Perfect Purple: An Exploration Of Glaze Making And Chemical Safety In The Pottery Studio, Kara Eppard, Michael Hough

ASPIRE 2024

This project was undertaken as an IDS-100H course linkage between ceramics and chemistry. Through time spent reviewing literature and time in the studio, a project was developed that allowed the application of technical skills of each discipline in a creative fashion. The creative focus of the project was to find a suitable purple glaze to utilize on a previously thrown pottery collection. During the project techniques in glaze making were explored. Over 25 glazes were tested, and two firing techniques were explored. Additionally, safety within the pottery studio was increased through aspects such as the development of an MSDS, and …

The Social Pot: A Social Media Application, Reid Long

Honors Projects

The Social Pot is a web application that allows a user to post to Instagram and X simultaneously from one place. The user creates a Social Pot Account and from there can set their Instagram username and password within the home page. Once the user attempts to post, it will redirect them to login to X which once successful will make the tweet. Used the API 'instagram-private-api'. User needed to give access to my X Project which in turn gave an Auth token (via X redirect URL). The auth token was then sent to my endpoint in order to get …

Visualizing The Standard Deviation Via Revolution Using R/Rstudio, Hieu Nguyen '25, Trung Pham '25, Mamunur Rashid, Jyotirmoy Sarkar

Student Research

The standard deviation is a commonly used statistical measure to quantify the level of variation present in a set of numbers or in a random variable. Sarkar and Rashid (2016) introduced an interpretation of the population standard deviation as the radius of a cylinder with a volume equivalent to that of the solid of revolution when the 2-D graph of the empirical cumulative distribution function is revolved about the vertical line through the mean. This article demonstrates step-by-step how to use the RevSD package in R/RStudio to visualize the standard deviation of data using this innovative technique. The RevSD package …

A Computer Vision Solution To Cross-Cultural Food Image Classification And Nutrition Logging​, Rohan Sethi, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

The US is a culturally and ethnically diverse country, and with this diversity comes a myriad of cuisines and eating habits that expand well beyond that of western culture. Each of these meals have their own good and bad effects when it comes to the nutritional value and its potential impact on human health. Thus, there is a greater need for people to be able to access the nutritional profile of their diverse daily meals and better manage their health. A revolutionary solution to democratize food image classification and nutritional logging is using deep learning to extract that information from …

Uni Science Education Update Conference, Save The Date Flier, Spring 2024, University Of Northern Iowa. Science Education Program.

Science Education Update Conference Documents

Announcement for the 2024 Science Education Update Conference.

Fluorescence Microscopy With Deep Uv, Near Uv, And Visible Excitation For In Situ Detection Of Microorganisms, Noel Case, Nikki Johnston, Jay Nadeau

Physics Faculty Publications and Presentations

We report a simple, inexpensive design of a fluorescence microscope with light-emitting diode (LED) excitation for detection of labeled and unlabeled microorganisms in mineral substrates. The use of deep UV (DUV) excitation with visible emission requires no specialized optics or slides and can be implemented easily and inexpensively using an oblique illumination geometry. DUV excitation (<280 >nm) is preferable to near UV (365 nm) for avoidance of mineral autofluorescence. When excited with DUV, unpigmented bacteria show two emission peaks: one in the near UV ∼320 nm, corresponding to proteins, and another peak in the blue to green range, corresponding to …

Comparison Of Emissions Across Tobacco Products: A Slippery Slope In Tobacco Control, Ahmad El-Hellani, Ayomipo Adeniji, Hanno C. Erythropel, Thomas Lamb, Qixin Wang, Vladimir Mikheev, Robert Strongin, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

In this narrative review, we highlight the challenges of comparing emissions from different tobacco products under controlled laboratory settings (using smoking/ vaping machines). We focus on tobacco products that generate inhalable smoke or aerosol, such as cigarettes, cigars, hookah, electronic cigarettes, and heated tobacco products. We discuss challenges associated with sample generation including variability of smoking/vaping machines, lack of standardized adaptors that connect smoking/vaping machines to different tobacco products, puffing protocols that are not representative of actual use, and sample generation session length (minutes or number of puffs) that depends on product characteristics. We also discuss the challenges of physically …