Physical Sciences and Mathematics Commons^™

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 …

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

Analysis

No abstract provided.

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 …

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 …

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

Tissue Decay Tested In Modern Metasequoia Leaves: Implications For Early Diagenesis Of Leaves In Fossil Lagerstätten, Caitlyn R. Witkowski, Qin Leng, Christopher W. Reid, Liang Feng, Hong Yang

Science and Technology Department Faculty Journal Articles

Sedimentary deposits yielding extraordinarily-preserved fossils (known as Lagerstätten) may provide significant insights into the physiology and environments of ancient plants, particularly when the fossils represent their original characteristics with limited diagenetic modifications. To better understand molecular, isotopic, and morphological changes during the early stages of diagenesis, degradation experiments were conducted in two time series: 1) a laboratory decay series using fungi on leaves over the course of a month and 2) a natural decay series with leaves collected from different stages of leaf senescence and early diagenesis. Both experiments used modern leaves of the dawn redwood Metasequoia glyptostroboides …

Santa Clara Magazine, Volume 63 Number 1, Summer 2022, Santa Clara University

Santa Clara Magazine

16 - SHARED DREAMS Meet incoming University President Julie Sullivan, the first layperson and woman selected to lead SCU. Leslie Griffy

20 - BD KNOWS BEST Discovering who you really are, being grateful, and dinosaurs with BD Wong. Lauren Loftus.

22 - SWEPT AWAY Being homeless in Silicon Valley is particularly deadly. One professor explores why so many die in a land of such excess. Leslie Griffy .

28 - ON THE OUTSIDE A first-person account of being wrongly convicted, as told by Arturo Jimenez.

30 - BOOKED AND BUSY The secret behind the Hollywood success of so many Bronco …

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 …

Challenging Predictions Of Inflationary Models With Cmb Data, Richik Bhattacharya, Atanu Debnath, Esha Sajjanhar, Shravani Sardeshpande, Pablo Tenorio Hernández, José Ricardo Torres Heredia

2022 REYES Proceedings

Cosmic inflation offers the best known explanations for many of the observed features of the Universe, such as its flatness. An imprint of the qualities of this mechanism is left in the cosmic microwave background (CMB), which can be instrumental to confirm inflation. Unfortunately, there is a plethora of inflationary models, which are a priori in the same footing. It is conceivable that contrasting the predictions of the various models with the measured values of the parameters of CMB data and other cosmological observables shall allow one to single out the successful theory of inflation. In this work we provide …

Sdq: Stochastic Differentiable Quantization With Mixed Precision, Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric Xing, Kwang Ting Cheng

Machine Learning Faculty Publications

In order to deploy deep models in a computationally efficient manner, model quantization approaches have been frequently used. In addition, as new hardware that supports mixed bitwidth arithmetic operations, recent research on mixed precision quantization (MPQ) begins to fully leverage the capacity of representation by searching optimized bitwidths for different layers and modules in a network. However, previous studies mainly search the MPQ strategy in a costly scheme using reinforcement learning, neural architecture search, etc., or simply utilize partial prior knowledge for bitwidth assignment, which might be biased on locality of information and is sub-optimal. In this work, we present …

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

Arkansas Water Resources Center 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 …

Action-Sufficient State Representation Learning For Control With Structural Constraints, Biwei Huang, Chaochao Lu, Liu Leqi, Josã© Miguel Hernã¡Ndez-Lobato, Clark Glymour, Bernhard Schã¶Lkopf, Kun Zhang

Machine Learning Faculty Publications

Perceived signals in real-world scenarios are usually high-dimensional and noisy, and finding and using their representation that contains essential and sufficient information required by downstream decision-making tasks will help improve computational efficiency and generalization ability in the tasks. In this paper, we focus on partially observable environments and propose to learn a minimal set of state representations that capture sufficient information for decision-making, termed Action-Sufficient state Representations (ASRs). We build a generative environment model for the structural relationships among variables in the system and present a principled way to characterize ASRs based on structural constraints and the goal of maximizing …

Gradient-Free Method For Heavily Constrained Nonconvex Optimization, Wanli Shi, Hongchang Gao, Bin Gu

Machine Learning Faculty Publications

Zeroth-order (ZO) method has been shown to be a powerful method for solving the optimization problem where explicit expression of the gradients is difficult or infeasible to obtain. Recently, due to the practical value of the constrained problems, a lot of ZO Frank-Wolfe or projected ZO methods have been proposed. However, in many applications, we may have a very large number of nonconvex white/black-box constraints, which makes the existing zeroth-order methods extremely inefficient (or even not working) since they need to inquire function value of all the constraints and project the solution to the complicated feasible set. In this paper, …

Identification Of Linear Non-Gaussian Latent Hierarchical Structure, Feng Xie, Biwei Huang, Zhengming Chen, Yangbo He, Zhi Geng, Kun Zhang

Machine Learning Faculty Publications

Traditional causal discovery methods mainly focus on estimating causal relations among measured variables, but in many real-world problems, such as questionnaire-based psychometric studies, measured variables are generated by latent variables that are causally related. Accordingly, this paper investigates the problem of discovering the hidden causal variables and estimating the causal structure, including both the causal relations among latent variables and those between latent and measured variables. We relax the frequently-used measurement assumption and allow the children of latent variables to be latent as well, and hence deal with a specific type of latent hierarchical causal structure. In particular, we define …

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.

Why Time Seems To Pass Slowly For Unpleasant Experiences And Quickly For Pleasant Experiences: An Explanation Based On Decision Theory, Laxman Bokati, Vladik Kreinovich

Departmental Technical Reports (CS)

It is known that our perception of time depends on our level of happiness: time seems to pass slower when we have unpleasant experiences and faster if our experiences are pleasant. Several explanations have been proposed for this effect. However, these explanations are based on specific features of human memory and/or human perception, features that, in turn, need explaining. In this paper, we show that this effect can be explained on a much more basic level of decision theory, without utilizing any specific features of human memory or perception.

Monotonic Bit-Invariant Permutation-Invariant Metrics On The Set Of All Infinite Binary Sequences, Irina Padilla, Vladik Kreinovich

Departmental Technical Reports (CS)

In a computer, all the information about an object is described by a sequence of 0s and 1s. At any given moment of time, we only have partial information, but as we perform more measurements and observations, we get longer and longer sequence that provides a more and more accurate description of the object. In the limit, we get a perfect description by an infinite binary sequence. If the objects are similar, measurement results are similar, so the resulting binary sequences are similar. Thus, to gauge similarity of two objects, a reasonable idea is to define an appropriate metric on …

Physical Trajectories Are Smooth, With Velocities At Least As Continuous As Brownian Motion, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

The fact that the kinetic energy of a particle cannot exceed its overall energy implies that the velocity -- i.e. the derivative of the trajectory -- should be bounded. This means, in effect, that all the trajectories are differentiable (smooth). However, at first glance, there seems to be no direct requirement that the velocities continuously depend on time. In this paper, we show that the properties of electromagnetic field necessitate that the velocities are continuous functions of time -- moreover, that they are at least as continuous as the Brownian motion.

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.

Spiking Neural Networks And Their Applications: A Review, Kashu Yamazaki, Viet-Khao Vo-Ho, Darshan Bulsara, Ngan Le

Computer Science and Computer Engineering Faculty Publications and Presentations

The past decade has witnessed the great success of deep neural networks in various domains. However, deep neural networks are very resource-intensive in terms of energy consumption, data requirements, and high computational costs. With the recent increasing need for the autonomy of machines in the real world, e.g., self-driving vehicles, drones, and collaborative robots, exploitation of deep neural networks in those applications has been actively investigated. In those applications, energy and computational efficiencies are especially important because of the need for real-time responses and the limited energy supply. A promising solution to these previously infeasible applications has recently been given …

Search For Z′ →Μ+Μ- In The Lμ-Lτ Gauge-Symmetric Model At Belle, T. Czank, I. Jaegle, A. Ishikawa, I. Adachi, K. Adamczyk, H. Aihara, D. M. Asner, T. Aushev, R. Ayad, V. Babu, S. Bahinipati, P. Behera, J. Bennett, F. Bernlochner, M. Bessner, V. Bhardwaj, B. Bhuyan, T. Bilka, J. Biswal

Faculty and Student Publications

We search for a new gauge boson Z′ that couples only to heavy leptons and their corresponding neutrinos in the process e+e-→Z′(→μ+μ-)μ+μ-, using a 643 fb-1 data sample collected by the Belle experiment at or near the ϒ(1S,2S,3S,4S,5S) resonances at the KEKB collider. While previous searches for Z′ performed a data-based estimation of the initial state radiation effect, our search for the Z′ is the first to include effects due to initial state radiation in the signal simulated samples that were used in estimating the detection efficiency. No signal is observed in the Z′ mass range of 0.212-10 GeV/c2, and …

B ¯ →D (∗)ℓ X ¯ Decays In Effective Field Theory With Massive Right-Handed Neutrinos, Alakabha Datta, Hongkai Liu, Danny Marfatia

Faculty and Student Publications

We calculate the complete differential decay distributions for the B meson decays, B¯→D(∗)ℓX¯, to a massive right-handed (RH) neutrino in the low-energy effective field theory (LEFT) framework. We find that a massive RH neutrino does not introduce any new angular structures compared to the massless case, but can cause significant distortions in angular observables. We study the phenomenology of low-energy four-fermion operators permitted by the standard model effective field theory (SMEFT) extended with RH neutrinos (SMNEFT). We show that to explain the positive value of the difference in forward-backward asymmetries, ΔAFBAFBμ-AFBe, tentatively inferred from Belle data, the RH neutrino must …

Evaluation Of Silver Nanoparticles Attached To Methylene Blue As An Antimicrobial Agent And Its Cytotoxicity, Somon Hakimov

Masters Theses & Specialist Projects

Antibiotics resistance is considered as one of the greatest public health challenges of our time. In this work, we have synthesized silver nanoparticles (Ag NPs) using pulsed liquid ablation in different medium of growth and later combined with methylene blue (MB) to evaluate its potential as an effective photodynamic therapy agent. Ag NPs were synthesized by pulsed laser ablation technique in Polyvinylpyrrolidone (PVP), citrate, and Polyvinyl alcohol (PVA). The Ag NPs were characterized using transmission electron microscopy (TEM), UV-Visible (UV-Vis), and photoluminescence (PL) spectra. Next, Ag NPs were coupled with MB and used to deactivate the Gram-negative bacteria, Escherichia coli …

Reply To Response By Fbi Laboratory Filed In Illinois V. Winfield And Affidavit By Biederman Et Al. (2022) Filed In Us V. Kaevon Sutton (2018 Cf1 009709), Susan Vanderplas, Kori Khan, Heike Hofmann, Alicia Carriquiry

Department of Statistics: Faculty Publications

1 Preliminaries

1.1 Scope

The aim of this document is to respond to issues raised in Federal Bureau of Investigation¹ and Alex Biedermann, Bruce Budowle & Christophe Champod.²

1.2 Conflict of Interest

We are statisticians employed at public institutions of higher education (Iowa State University and University of Nebraska, Lincoln) and have not been paid for our time or expertise when preparing either this response or the original affidavit.³ We provide this information as a public service and as scientists and researchers in this area.

1.3 Organization

The rest of the document precedes as follows: we begin …

Analysis Of Hawk Mountain Sanctuary Observation Data From 1976 Through 2021, Dale E. Parson

Computer Science and Information Technology Faculty

The primary objective is to correlate climate change data to changes in raptor observations at the Hawk Mountain Sanctuary in northern Berks County, Pennsylvania. Additional objectives include uncovering trends in climate observations at Hawk Mountain's North Lookout and the Allentown Airport throughout the observation period, and to examine trends in raptor observation properties independent of climate changes.

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.

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 …