Mathematics Commons^™

Invariance Explains Empirical Success Of Many Intelligent Techniques, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many applications of intelligent computing, we need to choose an appropriate function -- e.g., an appropriate re-scaling function, or an appropriate aggregation function. In applications of intelligent techniques, the problem of selecting an optimal function is usually too complex or too imprecise to be solved analytically, so the best functions are found empirically, by trying a large number of alternatives. In this paper, we show that in many such cases, the resulting empirical choice can be explained by natural invariance ideas. Example range from applications to building blocks of intelligent techniques -- such as aggregation (including hierarchical aggregation) and …

Why Exponential Almon Lag Works Well In Econometrics: An Invariance-Based Explanation, Laxman Bokati, Vladik Kreinovich

Departmental Technical Reports (CS)

In many econometric situations, we can predict future values of relevant quantities by using an empirical formula known as exponential Almon lag. While this formula is empirically successful, there have been no convincing theoretical explanation for this success. In this paper, we provide such a theoretical explanation based on general invariance ideas.

Seemingly Counter-Intuitive Features Of Good-To-Great Companies Actually Make Perfect Sense: Possible Algorithmics-Based Explanations, Francisco Zapata, Eric Smith, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In the late 1990s, researchers analyzed what distinguishes great companies from simply good ones. They found several features that are typical for great companies. Interestingly, most of these features seem counter-intuitive. In this paper, we show that from the algorithmic viewpoint, many of these features make perfect sense. Some of the resulting explanations are simple and straightforward, other explanations rely on complex not-well-publicized results from theoretical computer science.

Teaching Euclidean Geometry Using Proof And Dynamic Geometry Software, Cheryl Stoddard

Mathematics Graduate Theses

This paper examines incorporating proofs and dynamic geometry software when teaching Euclidean geometry to produce deeper understanding of geometric relationships for middle and secondary level students. The utilization of technology through classroom investigations and activities has shown to have an impact on the achievement scores on posttests and in the development of mathematical proof.

Asymptotic Classes, Pseudofinite Cardinality And Dimension, Alexander Van Abel

Dissertations, Theses, and Capstone Projects

We explore the consequences of various model-theoretic tameness conditions upon the behavior of pseudofinite cardinality and dimension. We show that for pseudofinite theories which are either Morley Rank 1 or uncountably categorical, pseudofinite cardinality in ultraproducts satisfying such theories is highly well-behaved. On the other hand, it has been shown that pseudofinite dimension is not necessarily well-behaved in all ultraproducts of theories which are simple or supersimple; we extend such an observation by constructing simple and supersimple theories in which pseudofinite dimension is necessarily ill-behaved in all such ultraproducts. Additionally, we have novel results connecting various forms of asymptotic classes …

Introduction To Mathematical Analysis I - 3rd Edition, Beatriz Lafferriere, Gerardo Lafferriere, Mau Nam Nguyen

PDXOpen: Open Educational Resources

Video lectures explaining problem solving strategies are available.

This set of lecture notes is meant to provide students with a strong foundation in mathematical analysis. Such a foundation is crucial for future study of deeper topics of analysis. Students should be familiar with most of the concepts presented here after completing the calculus sequence. However, these concepts will be reinforced through rigorous proofs.

Introduction to Mathematical Analysis II contains lecture notes that complement this book, with sections on integration, numerical series, series of functions, and selected advanced topics. Together, both volumes support a one semester or two-quarter course on introductory …

Fabrications And Applications Of Micro/Nanofluidics In Oil And Gas Recovery: A Comprehensive Review, Junchen Liu, Yandong Zhang, Mingzhen Wei, Xiaoming He, Baojun Bai

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Understanding fluid flow characteristics in porous medium, which determines the development of oil and gas oilfields, has been a significant research subject for decades. Although using core samples is still essential, micro/nanofluidics have been attracting increasing attention in oil recovery fields since it offers direct visualization and quantification of fluid flow at the pore level. This work provides the latest techniques and development history of micro/nanofluidics in oil and gas recovery by summarizing and discussing the fabrication methods, materials and corresponding applications. Compared with other reviews of micro/nanofluidics, this comprehensive review is in the perspective of solving specific issues in …

Darboux Transformation And Solitonic Solution To The Coupled Complex Short Pulse Equation, Bao-Feng Feng, Liming Ling

School of Mathematical & Statistical Sciences Faculty Publications

The Darboux transformation (DT) for the coupled complex short pulse (CCSP) equation is constructed through the loop group method. The DT is then utilized to construct various exact solutions including bright soliton, dark-soliton, breather and rogue wave solutions to the CCSP equation. In case of vanishing boundary condition (VBC), we perform the inverse scattering analysis to understand the soliton solution better. Breather and rogue wave solutions are constructed in case of non-vanishing boundary condition (NVBC). Moreover, we conduct a modulational instability (MI) analysis based on the method of squared eigenfunctions, whose result confirms the condition for the existence of rogue …

Definite Condition Of The Evolutionary (P)Over-Right-Arrow(X)-Laplacian Equation, Huashui Zhan, Zhaosheng Feng

School of Mathematical & Statistical Sciences Faculty Publications

For the nonlinear degenerate parabolic equations, how to find an appropriate boundary value condition to ensure the well-posedness of weak solution has been an interesting and challenging problem. In this paper, we develop the general characteristic function method to study the stability of weak solutions based on a partial boundary value condition.

The Local Lifting Problem For Curves With Quaternion Actions, George Mitchell

Dissertations, Theses, and Capstone Projects

The lifting problem asks whether one can lift Galois covers of curves defined over positive characteristic to Galois covers of curves over characteristic zero. The lifting problem has an equivalent local variant, which asks if a Galois extension of complete discrete valuation rings over positive characteristic, with algebraically closed residue field, can be lifted to characteristic zero. In this dissertation, we content ourselves with the study of the local lifting problem when the prime is 2, and the Galois group of the extension is the group of quaternions. In this case, it is known that certain quaternion extensions cannot be …

Generalization Of Bi-Canonical Degrees, Joseph Brennan, Laura Ghezzi, Jooyoun Hong, Wolmer Vasconcelos

Publications and Research

We discuss invariants of Cohen-Macaulay local rings that admit a canonical module ω. Attached to each such ring R, when ω is an ideal, there are integers–the type of R, the reduction number of ω–that provide valuable metrics to express the deviation of R from being a Gorenstein ring. In (Ghezzi et al. in JMS 589:506–528, 2017) and (Ghezzi et al. in JMS 571:55–74, 2021) we enlarged this list with the canonical degree and the bi-canonical degree. In this work we extend the bi-canonical degree to rings where ω is not necessarily an ideal. We also discuss generalizations to rings …

Computation Of Risk Measures In Finance And Parallel Real-Time Scheduling, Yajuan Li

Dissertations

Many application areas employ various risk measures, such as a quantile, to assess risks. For example, in finance, risk managers employ a quantile to help determine appropriate levels of capital needed to be able to absorb (with high probability) large unexpected losses in credit portfolios comprising loans, bonds, and other financial instruments subject to default. This dissertation discusses the computation of risk measures in finance and parallel real-time scheduling.

Firstly, two estimation approaches are compared for one risk measure, a quantile, via randomized quasi-Monte Carlo (RQMC) in an asymptotic setting where the number of randomizations for RQMC grows large, but …

Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu

Dissertations

This dissertation summarizes computational results from applying reinforcement learning and deep neural network to the designs of artificial microswimmers in the inertialess regime, where the viscous dissipation in the surrounding fluid environment dominates and the swimmer’s inertia is completely negligible. In particular, works in this dissertation consist of four interrelated studies of the design of microswimmers for different tasks: (1) a one-dimensional microswimmer in free-space that moves towards the target via translation, (2) a one-dimensional microswimmer in a periodic domain that rotates to reach the target, (3) a two-dimensional microswimmer that switches gaits to navigate to the designated targets in …

Parameter Selection In Fully Homomorphic Encryption Schemes And Fhe Applications, Cavidan Yakupoglu

Dissertations

Quantum computing has been gaining momentum as a result of recent technological advances. Existing cryptographic systems rely on the difficult problems that can be solved by sufficiently powerful quantum computers. As the quantum age approaches, the desire to discover new difficult problems that cannot be solved by quantum systems has increased. Lattice-based cryptography is a prominent tool for the post-quantum era that facilitates the implementation of encryption systems for practical applications.

The Learning with Error (LWE) and Ring-LWE problems introduce new lattice hardness assumptions that have been incorporated into public-key cryptosystems to facilitate the implementation of numerous privacy-enhancing applications. Fully …

Computing Rational Powers Of Monomial Ideals, Pratik Dongre, Benjamin Drabkin, Josiah Lim, Ethan Partida, Ethan Roy, Dylan Ruff, Alexandra Seceleanu, Tingting Tang

Department of Mathematics: Faculty Publications

This paper concerns fractional powers of monomial ideals. Rational powers of a monomial ideal generalize the integral closure operation as well as recover the family of symbolic powers. They also highlight many interesting connections to the theory of convex polytopes. We provide multiple algorithms for computing the rational powers of a monomial ideal. We also introduce a mild generalization allowing real powers of monomial ideals. An important result is that given any monomial ideal I, the function taking a real number to the corresponding real power of I is a step function which is left continuous and has rational …

Frobenius Objects In The Category Of Spans, Ivan Contreras, Molly Keller, Rajan Amit Mehta

Mathematics Sciences: Faculty Publications

We consider Frobenius objects in the category Span, where the objects are sets and the morphisms are isomorphism classes of spans of sets. We show that such structures are in correspondence with data that can be characterized in terms of simplicial sets. An interesting class of examples comes from groupoids.

Our primary motivation is that Span can be viewed as a set-theoretic model for the symplectic category, and thus Frobenius objects in Span provide set-theoretic models for classical topological field theories. The paper includes an explanation of this relationship.

Given a finite commutative Frobenius object in Span, one can obtain …

A New Technique For Solving Neutral Delay Differential Equations Based On Euler Wavelets, Mutaz Mohammad, Alexander Trounev

All Works

An effective numerical scheme based on Euler wavelets is proposed for numerically solving a class of neutral delay differential equations. The technique explores the numerical solution via Euler wavelet truncated series generated by a set of functions and matrix inversion of some collocation points. Based on the operational matrix, the neutral delay differential equations are reduced to a system of algebraic equations, which is solved through a numerical algorithm. The effectiveness and efficiency of the technique have been illustrated by several examples of neutral delay differential equations. The main advantages and key role of using the Euler wavelets in this …

Constructions And Analyses Of Efficient Symmetric-Key Primitives For Authentication And Encryption., Sebati Ghosh Dr.

Doctoral Theses

In symmetric key cryptography there are two fundamental objectives, viz. 1. confidentiality or secrecy of message from unexpected party and 2. authentication of message which includes authenticating the source of the message as well as integrity of the message against any unwanted modification. Let us first concentrate on confidentiality. In classical symmetric key cryptography two parties, say Alice and Bob, first secretly exchange a key-pair (e, d). Later, if Alice wishes to send a secret message m ∈ M to Bob, she computes c = Ee(m) and transmits c to Bob. Upon receiving c, Bob computes Dd(c) = m and …

Morphological Network: Network With Morphological Neurons., Ranjan Mondal Dr.

Doctoral Theses

Image processing with traditional approaches mainly use the tools of linear systems. However, linear approaches are not well suited and may even fail to solve problems involving geometrical aspects of the image. Thus, nonlinear geometric approaches like morphological operations are very popular in those cases. Morphological operations are nonlinear operations based on a set and lattice-theoretic methodology for image analysis that are capable of describing the geometrical structure of image objects quantitatively. It is suitable for various problems in image processing, computer vision, and pattern recognition. While solving problems with morphology, a particular structuring element is defined. Structuring elements have …

Properties Of Meromorphic Spiral-Like Functions Associated With Symmetric Functions, Daniel Breaz, Luminița-Ioana Cotîrlă, Elangho Umadevi, Kadhavoor R. Karthikeyan

All Works

To consolidate or adapt to many studies on meromorphic functions, we define a new subclass of meromorphic functions of complex order involving a differential operator. The defined function class combines the concept of spiral-like functions with other studies pertaining to subclasses of multivalent meromorphic functions. Inclusion relations, integral representation, geometrical interpretation, coefficient estimates and solution to the Fekete-Szegö problem of the defined classes are the highlights of this present study. Further to keep up with the present direction of research, we extend the study using quantum calculus. Applications of our main results are given as corollaries.

Domain Of Exotic Laplacian Constructed By Wiener Integrals Of Exponential White Noise Distributions, Luigi Accardi, Un Cig Ji, Kimiaki Saitô

Journal of Stochastic Analysis

No abstract provided.

Duality For Asymptotic Invariants Of Graded Families, Michael Dipasquale, Thái Thành Nguyễn, Alexandra Seceleanu

Department of Mathematics: Faculty Publications

The starting point of this paper is a duality for sequences of natural numbers which, under mild hypotheses, interchanges subadditive and superadditive sequences and inverts their asymptotic growth constants.

We are motivated to explore this sequence duality since it arises naturally in at least two important algebraic-geometric contexts. The first context is Macaulay- Matlis duality, where the sequence of initial degrees of the family of symbolic powers of a radical ideal is dual to the sequence of Castelnuovo-Mumford regularity values of a quotient by ideals generated by powers of linear forms. This philosophy is drawn from an influential paper of …

Decorrelated Deep Neural Networks: Learning Bias Invariant & Scanner Independent Features, And Causal Relationships Using A Novel Deep Learning Methods Based On Distance Correlation, Pranita Patil

Dissertations and Theses

Advancements in deep learning or deep neural networks have made it possible to reach expert-level performance in a variety of applications, even in challenging situations. However, a central challenge in all deep learning, as well as machine learning applications, is dealing with its dependency on the quality of data which can be significantly impacted by biases, confounders, and irrelevant variations in data which leads to spurious relationships and erroneous decisions. The main purpose of this dissertation is to build a robust deep learning model which considers and mitigates these biases. Another challenge with the deep learning model is learning associations …

Statistical Analysis Methods Applied To Early Outpatient Covid-19 Treatment Case Series Data, Eleftherios Gkioulekas, Peter A. Mccullough, Vladimir Zelenko

School of Mathematical & Statistical Sciences Faculty Publications

When confronted with a public health emergency, significant innovative treatment protocols can sometimes be discovered by medical doctors at the front lines based on repurposed medications. We propose a statistical framework for analyzing the case series of patients treated with such new protocols, that enables a comparison with our prior knowledge of expected outcomes, in the absence of treatment. The goal of the proposed methodology is not to provide a precise measurement of treatment efficacy, but to establish the existence of treatment efficacy, in order to facilitate the binary decision of whether the treatment protocol should be adopted on an …

Mathspark: Sparking Student Curiosity Through Hands-On, Inquiry-Based Mathematics Explorations Inspired By Funds Of Knowledge, Katrina Baha, Kaliyah Clyde, Mikaela Morris, Perla Myers Phd, Amanda Ruiz Phd

Creative Collaborations: Annual Showcase of Undergraduate Research

Abstract: Much of the existing research focuses on the questions teachers ask students, but there is very little information about the questions students ask. The main purpose of this research was to explore ways to engage students in asking their own questions in the learning of mathematics, and to create a scale to help educators categorize the types of questions students ask. We created and used inquiry-based, funds of knowledge-rich lessons with productive struggle opportunities to promote curiosity (Calleja, 2016) and elicit student questions to develop and test our question categorization scale.

The Art Of Analysis, Christopher Hammond

Open Educational Resources

Christopher Hammond, Professor of Mathematics at Connecticut College, has written an introductory textbook in real analysis. This resource is freely available for anyone to use, either individually or in a classroom setting.

The primary innovation of this text is a new perspective on teaching the theory of integration. Most introductory analysis courses focus initially on the Riemann integral, with other definitions discussed later (if at all). The paradigm being proposed is that the Riemann integral and the “generalized Riemann integral” should be considered simultaneously, not separately – in the same manner as uniform continuity and continuity. Riemann integrability is simply …

Disjoint And Simultaneously Hypercyclic Pseudo-Shifts, Nurhan Çolakoğlu, Özgür Martin, Rebecca Sanders

Mathematical and Statistical Science Faculty Research and Publications

We characterize disjoint and simultaneously hypercyclic tuples of unilateral pseudo-shift operators on ℓ^p(ℕ) . As a consequence, complementing the results of Bernal and Jung, we give a characterization for simultaneously hypercyclic tuples of unilateral weighted shifts. We also give characterizations for unilateral pseudo-shifts that satisfy the Disjoint and Simultaneous Hypercyclicity Criterions. Contrary to the disjoint hypercyclicity case, tuples of weighted shifts turn out to be simultaneously hypercyclic if and only if they satisfy the Simultaneous Hypercyclicity Criterion.

On The Thom Isomorphism For Groupoid-Equivariant Representable K-Theory, Zachary J. Garvey

Dartmouth College Ph.D Dissertations

This thesis proves a general Thom Isomorphism in groupoid-equivariant KK-theory. Through formalizing a certain pushforward functor, we contextualize the Thom isomorphism to groupoid-equivariant representable K-theory with various support conditions. Additionally, we explicitly verify that a Thom class, determined by pullback of the Bott element via a generalized groupoid homomorphism, coincides with a Thom class defined via equivariant spinor bundles and Clifford multiplication. The tools developed in this thesis are then used to generalize a particularly interesting equivalence of two Thom isomorphisms on TX, for a Riemannian G-manifold X.

Towards Fast Weak Adversarial Training To Solve High Dimensional Parabolic Partial Differential Equations Using Xnode-Wan, Paul Valsecchi Oliva, Yue Wu, Cuiyu He, Hao Ni

School of Mathematical & Statistical Sciences Faculty Publications

Due to the curse of dimensionality, solving high dimensional parabolic partial differential equations (PDEs) has been a challenging problem for decades. Recently, a weak adversarial network (WAN) proposed in Zang et al. (2020)[17] offered a flexible and computationally efficient approach to tackle this problem defined on arbitrary domains by leveraging the weak solution. WAN reformulates the PDE problem as a generative adversarial network, where the weak solution (primal network) and the test function (adversarial network) are parameterized by the multi-layer deep neural networks (DNNs). However, it is not yet clear whether DNNs are the most effective model for the parabolic …

Modeling, Analysis, And Simulation To Reveal The Mechanisms Of Ciliary Beating, Louis Woodhams

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cilia are microscopic cellular appendages that help us breathe by clearing our airways, maintain the health of our central nervous system by circulating cerebrospinal fluid, and allow us to reproduce by transporting eggs and propelling sperm cells. Cilia even determine the asymmetry of our internal organs during embryonic development. However, the mechanisms underlying ciliary beating are not fully understood. Questions remain as to how arrays of the motor protein dynein generate the propulsive waveforms observed in cilia and how structural elements within the cilium and its connection to the cell deform during beating. In the current work, mathematical modeling, analysis, …