Physical Sciences and Mathematics Commons^™

Investigating Continual Learning Strategies In Neural Networks, Christopher Tam, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

This paper explores the role of continual learning strategies when neural networks are confronted with learning tasks sequentially. We analyze the stability-plasticity dilemma with three factors in mind: the type of network architecture used, the continual learning scenario defined and the continual learning strategy implemented. Our results show that complementary learning systems and neural volume significantly contribute towards memory retrieval and consolidation in neural networks. Finally, we demonstrate how regularization strategies such as elastic weight consolidation are more well-suited for larger neural networks whereas rehearsal strategies such as gradient episodic memory are better suited for smaller neural networks.

Draft Final 2022 Insufficiently Reclaimed Sites Sampling Bres No. 08 – Belle Of Butte Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

On The Computability Of Primitive Recursive Functions By Feedforward Artificial Neural Networks, Vladimir A. Kulyukin

Computer Science Faculty and Staff Publications

We show that, for a primitive recursive function h(x, t), where x is a n-tuple of natural numbers and t is a natural number, there exists a feedforward artificial neural network 𝔑(x, t), such that for any n-tuple of natural numbers z and a positive natural number m, the first m + 1 terms of the sequence {h(z, t)} are the same as the terms of the tuple (𝔑(z, 0), ... ,𝔑(z, m)).

Assessment Of First-Phase Covid-19 Pandemic In Europe Using Hierarchical Clustering Based On Principal Components Analysis, Sanjay Kumar, Evrim Oral

School of Public Health Faculty Publications

It is of great interest for researchers to assess the COVID-19 pandemic in Europe. Grouping of COVID-19-affected regions is an effective way to monitor and optimize planning to combat the disease. This paper applied hierarchical clustering based on principal components analysis (HCPCA) to COVID-19 data from affected European countries. Considering several attribute indices, we obtained a new set of indicators using principal components analysis to aggregate and reduce the dimension of attribute indices of affected countries. Further, we obtained groups of affected countries subject to their similarity using hierarchical clustering to the reduced observations of new attributes indices of these …

Evocative And Provocative Image-Making In The Age Of Generative Ai, Julian Kilker

Tradition Innovations in Arts, Design, and Media Higher Education

Editorial for inaugural AI-focused special issue of Tradition-Innovations in Arts, Design, and Media Higher Education, published under the auspices of the Alliance for the Arts in Research Universities (a2ru). Discusses three articles by five authors in this issue: (1) Choreographing Shadows: Interdisciplinary collaboration to orchestrate ethical image-making by Mark Burchick and Diana Pasulka; (2) Giving Up Control: Hybrid AI-augmented workflows for image-making by Joshua Vermillion; and (3) Hands are Hard: Unlearning how we talk about machine learning in the arts by Adam Hyland and Oscar Keyes.

Editing this special issue explored several key questions: What does “innovation” mean when …

Leading K-12 Community Responsiveness To Cyber Threats Via Education Of School Community, Michele Kielty, A. Renee Staton

Journal of Cybersecurity Education, Research and Practice

Cyber threats have escalated in recent years. Many of these threats have been direct and vicious attacks on K-12 systems. Educators are rarely trained on how to address cyber threats from a systemic and educational perspective when such challenges arise in their school buildings. This article explains the cyber threats that are looming large for K-12 systems and provides concrete tools for school leaders to employ in order to provide preventive education to their school communities.

Whittle, Charles Edward, Jr., 1931-2012 (Sc 3698), Manuscripts & Folklife Archives

Manuscript Collection Finding Aids

Finding aid only for Manuscripts Small Collection 3698. Well-illustrated biographical volume on the life, career and family of Charles E. Whittle, Jr., a Brownsville, Kentucky native who served as a physics professor at Western Kentucky University and at Centre College, and as a senior scientist at Oak Ridge Associated Universities, Oak Ridge, Tennessee.

Envariance As A Symmetry In Quantum Mechanics And Applications To Statistical Mechanics, Paul Bracken

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

A quantum symmetry called entanglement-assisted invariance, also called envariance, is introduced. It is studied with respect to the process of performing quantum measurements. An apparatus which interacts with other physical systems, which are called environments, exchanges a single state with physical states equal in number to that of the possible outcomes of the experiment. Correlations between the apparatus and environment give rise to a type of selection rule which prohibits the apparatus from appearing in a superposition corresponding to different eigenvalues of the pointer basis of the apparatus. The eigenspaces of this observable form a natural basis for the apparatus …

Enhancement Of Er Luminescence From Bridge-Type Photonic Crystal Nanocavities With Er, O-Co-Doped Gaas, Zhidong Fang, Jun Tatebayashi, Ryohei Homi, Masayuki Ogawa, Hirotake Kajii, Masahiko Kondow, Kyoko Kitamura, Brandon Mitchell, Shuhei Ichikawa, Yasufumi Fujiwara

Physics & Engineering Faculty Publications

A bridge-type photonic crystal (PhC) nanocavity based on Er,O-codoped GaAs is employed to realize enhancement of Er luminescence. By adjusting the structural design and measurement temperature, the cavity mode's wavelength can be coupled to Er luminescence. The peak emission intensity from an Er-2O defect center was enhanced 7.3 times at 40 nW pump power and 77 K. The experimental Q-factor is estimated to be over 1.2 x 104, and the luminescence intensity shows superlinearity with excitation power, suggesting Er luminescence amplification. This result would pave the way towards the realization of highly efficient single-photon emitters based on rare-earth elements.

Parallel Element-Based Algebraic Multigrid For H (Curl) And H (Div) Problems Using The Parelag Library, Delyan Z. Kalchev, Panayot S. Vassilevski, Umberto Villa

Mathematics and Statistics Faculty Publications and Presentations

This paper presents the use of element-based algebraic multigrid (AMGe) hierarchies, implemented in the Parallel Element Agglomeration Algebraic Multigrid Upscaling and Solvers (ParELAG) library, to produce multilevel preconditioners and solvers for H (curl) and H (div) formulations. ParELAG constructs hierarchies of compatible nested spaces, forming an exact de Rham sequence on each level. This allows the application of hybrid smoothers on all levels and the Auxiliary-Space Maxwell Solver or the Auxiliary-Space Divergence Solver on the coarsest levels, obtaining complete multigrid cycles. Numerical results are presented, showing the parallel performance of the proposed methods. As a part of the exposition, this …

The Public's Perception Of An Earthquake Early Warning System: A Study On Factors Influencing Continuance Intention, Marion Lara L. Tan, Lauren J. Vinnell, Alvin Patrick M. Valentin, Raj Prasanna, Julia S. Becker

Quantitative Methods and Information Technology Faculty Publications

This paper investigates the perceptions of the New Zealand public towards the Android Earthquake Alert (AEA) system, a public-facing earthquake early warning system. Specifically, it examines the public’s continuance intention towards the AEA system and the influencing factors of satisfaction, confirmation, perceived usefulness, and perceived trust. To gather insights into the public’s perceptions regarding the AEA system, this study distributed online surveys following two separate earthquake alert events on 12 October and 22 October 2021. A total of 524 and 671 participants responded to the two events’ surveys, providing valuable data for analysis and exploration. Structural Equation Modelling of the …

Three-Dimensional Rgo/Cnt/G-C3n4 Macro Discs As An Efficient Peroxymonosulfate Activator For Catalytic Degradation Of Sulfamethoxazole, Rajan Arjan Kalyan Hirani, Abdul Hannan, Nasir Rafique, Lei Shi, Wenjie Tian, Haitao Wang, Hongqi Sun

Research outputs 2022 to 2026

Over the past few years, advanced oxidation processes (AOPs) have shown promising efficiencies for wastewater remediation. Carbocatalysis, in particular, has been exploited widely thanks to its sustainable and economical properties but has an issue of recovery and reusability of the catalysts. To address this, three-dimensional (3D) binary and ternary graphene-based composites in the form of macro discs were created to activate peroxymonosulfate (PMS) for catalytic oxidation of sulfamethoxazole (SMX). Graphene oxide served as the base, while graphitic carbon nitride (g-C3N4) and/or single-walled carbon nanotubes (SWCNTs) were added. Among the various discs synthesized, rGNTCN discs (ternary composite) were proven to be …

Fortifying Iot Against Crimpling Cyber-Attacks: A Systematic Review, Usman Tariq, Irfan Ahmed, Muhammad Attique Khan, Ali Kashif Bashir

Karbala International Journal of Modern Science

The rapid growth and increasing demand for Internet of Things (IoT) devices in our everyday lives create exciting opportunities for human involvement, data integration, and seamless automation. This fully interconnected ecosystem considerably impacts crucial aspects of our lives, such as transportation, healthcare, energy management, and urban infrastructure. However, alongside the immense benefits, the widespread adoption of IoT also brings a complex web of security threats that can influence society, policy, and infrastructure conditions. IoT devices are particularly vulnerable to security violations, and industrial routines face potentially damaging vulnerabilities. To ensure a trustworthy and robust security framework, it is crucial to …

Smart Service Function Chain System For Dynamic Traffic Steering Using Reinforcement Learning (Chrl), Ahmed Nadhum, Ahmed Al-Saadi

Karbala International Journal of Modern Science

The rapid development of the Internet and network services coupled with the growth of communication infrastructure necessitates the employment of intelligent systems. The complexity of the network is heightened by these systems, as they offer diverse services contingent on traffic type, user needs, and security considerations. In this context, a service function chain offers a toolkit to facilitate the management of intricate network systems. However, various traffic types require dynamic adaptation in the sets of function chains. The problem of optimizing the order of service functions in the chain must be solved using the proposed approach, along with balancing the …

New Quantum Genetic Algorithm Based On Constrained Quantum Optimization, Mohammed R. Almasaoodi, Abdulbasit M. A. Sabaawi, Sara El Gaily, Sándor Imre

Karbala International Journal of Modern Science

In the past decades, many quantum algorithms have been developed. The main obstacle that prevents the widespread implementation of these algorithms is the small size of the available quantum computer in terms of qubits. Blind Quantum Computation (BQC) holds the promise of handling this issue by delegating computation to quantum remote devices. Here, we introduce a novel Constrained Quantum Genetic Algorithm (CQGA) that selects the optimum extreme (minimum or maximum) value of a constrained goal function (or a vast unsorted database) with very low computational complexity. Since the convergence speed to the optimal solution for the Constrained Classical Genetic Algorithm …

Hprop: Hierarchical Privacy-Preserving Route Planning For Smart Cities, Francis Tiausas, Keiichi Yasumoto, Jose Paolo Talusan, Hayato Yamana, Hirozumi Yamaguchi, Shameek Bhattacharjee, Abhishek Dubey, Sajal K. Das

Computer Science Faculty Research & Creative Works

Route Planning Systems (RPS) are a core component of autonomous personal transport systems essential for safe and efficient navigation of dynamic urban environments with the support of edge-based smart city infrastructure, but they also raise concerns about user route privacy in the context of both privately owned and commercial vehicles. Numerous high-profile data breaches in recent years have fortunately motivated research on privacy preserving RPS, but most of them are rendered impractical by greatly increased communication and processing overhead. We address this by proposing an approach called Hierarchical Privacy-Preserving Route Planning (HPRoP), which divides and distributes the route-planning task across …

Sublinear Time Motif Discovery From Multiple Sequences, Bin Fu, Yunhui Fu, Yuan Xue

Computer Science Faculty Publications and Presentations

In this paper, a natural probabilistic model for motif discovery has been used to experimentally test the quality of motif discovery programs. In this model, there are k background sequences, and each character in a background sequence is a random character from an alphabet, Σ. A motif G = g1g2 . . . gm is a string of m characters. In each background sequence is implanted a probabilistically-generated approximate copy of G. For a probabilistically-generated approximate copy b1b2 . . . bm of G, every character, bi , is probabilistically generated, such that the probability for bi 6= gi is …

Comparing A Georgia Reservoir With Solar-Powered Mixers To Another Without Mixers: Assessing Thermal And Oxygen Saturation And Nutrient Dispersion, Melissa Hage, Jordan Hasty, Hannah Miller

Georgia Journal of Science

Harmful algal blooms (HABs) have been increasing over the last 50 years due to anthropogenic nutrient enrichment and increasing temperatures. One HAB control method is the use of solar-powered mixers. In this study we investigated the timing of thermal stratification, depth of the thermocline and oxycline, and dispersion of nutrients within the water column by comparing two reservoirs in Georgia, U.S.A. over a three-year period – Lake Varner (LV), which utilizes mixers, and Hard Labor Creek Reservoir (HLCR), which does not. Our data show that the onset of thermal stratification is within ± 2 days and appears at the same …

Study Of Behaviour Change And Impact On Infectious Disease Dynamics By Mathematical Models, Tianyu Cheng

Electronic Thesis and Dissertation Repository

This thesis uses mathematical models to study human behaviour changes' effects on infectious disease transmission dynamics. It centers on two main topics. The first concerns how behaviour response evolves during epidemics and the effects of adaptive precaution behaviour on epidemics. The second topic is how to build general framework models incorporating human behaviour response in epidemiological modelling.

In the first project, based on the fact that a fraction of the epidemiologically susceptible population is actually susceptible due to precautions, we present a novel perspective on understanding the infection force, incorporating human protection behaviours. This view explains many existing infection force …

Healthcare Ai: A Revised Quebec Framework For Nursing Education, Maggie Lattuca, Diane Maratta, Ute Beffert, Annie Chevrier, Laura Winer

Quality Advancement in Nursing Education - Avancées en formation infirmière

Artificial Intelligence Health Technologies (AIHT) are taking their place in the practice of nursing. However, the curricula have not evolved to include competencies required of nursing graduates to incorporate their impact on theory and practice. This project was born of an identified need by nurse educators to articulate new competencies grounded in the literature and expert knowledge. Based on extensive literature reviews and an iterative process of expert validation, this paper provides recommendations for five new competencies that will be needed for nurses to use AIHT responsibly, ethically, and intelligently in the best interests of patient care. The methodology started …

The Fierce Green Fire: Vol. 14 Issue 6, Wofford College Environmental Studies Program

The Fierce Green Fire

No abstract provided.

Machine Learning‑Assisted Low‑Dimensional Electrocatalysts Design For Hydrogen Evolution Reaction, Jin Li, Naiteng Wu, Jian Zhang, Hong‑Hui Wu, Kunming Pan, Yingxue Wang, Guilong Liu, Xianming Liu, Zhenpeng Yao, Qiaobao Zhang

Chemistry Department: Faculty Publications

Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water. Nevertheless, the conventional "trial and error" method for producing advanced electrocatalysts is not only cost-ineffective but also time-consuming and labor-intensive. Fortunately, the advancement of machine learning brings new opportunities for electrocatalysts discovery and design. By analyzing experimental and theoretical data, machine learning can effectively predict their hydrogen evolution reaction (HER) performance. This review summarizes recent developments in machine learning for low-dimensional electrocatalysts, including zero-dimension nanoparticles and nanoclusters, one-dimensional nanotubes and nanowires, two-dimensional nanosheets, as well as other electrocatalysts. In particular, the effects of descriptors and algorithms on screening low-dimensional electrocatalysts …

Understanding The Soil Water Dynamics During Excess And Deficit Rainfall Conditions Over The Core Monsoon Zone Of India, Mangesh M. Goswami, Milind Mujumdar1, Bhupendra Bahadur Singh, Madhusudan Ingale, Naresh Ganeshi, Manish Ranalkar, Trenton E. Franz, Prashant Srivastav, Dev Niyogi, R Krishnan, S N. Patil

School of Natural Resources: Faculty Publications

Observations of soil moisture (SM) during excess and deficit monsoon seasons between 2000 to 2021 present a unique opportunity to understand the soil water dynamics (SWD) over core monsoon zone (CMZ) of India. This study aims to analyse SWD by investigating the SM variability, SM memory (SMM), and the coupling between surface and subsurface SM levels. Particularly intriguing are instances of concurrent monsoonal extremes, which give rise to complex SWD patterns. Usually, it is noted that a depleted convective activity and persistence of higher temperatures during the pre-monsoon season leads to lower SM, while monsoon rains and post-monsoon showers support …

Deep Learning For Plant Bioinformatics: An Explainable Gradient-Based Approach For Disease Detection, Muhammad Shoaib, Babar Shah, Nasir Sayed, Farman Ali, Rafi Ullah, Irfan Hussain

All Works

Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a …

Dtitd: An Intelligent Insider Threat Detection Framework Based On Digital Twin And Self-Attention Based Deep Learning Models, Zhi Qiang Wang, Abdulmotaleb El Saddik

Computer Vision Faculty Publications

Recent statistics and studies show that the loss generated by insider threats is much higher than that generated by external attacks. More and more organizations are investing in or purchasing insider threat detection systems to prevent insider risks. However, the accurate and timely detection of insider threats faces significant challenges. In this study, we proposed an intelligent insider threat detection framework based on Digital Twins and self-attentions based deep learning models. First, this paper introduces insider threats and the challenges in detecting them. Then this paper presents recent related works on solving insider threat detection problems and their limitations. Next, …

Residential Metals Abatement Program Investigation Summary Report (Non-Residential Parcels – Indoor Dust) - Butte Central Elementary And Middle School, Environmental Resource Management (Erm)

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Residential Metals Abatement Program Investigation Summary Report (Non-Residential Parcels – Indoor Dust) - Kennedy Elementary School, Environmental Resource Management (Erm)

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Residential Metals Abatement Program Investigation Summary Report (Non-Residential Parcels – Indoor Dust) Kennedy Elementary School, Environmental Resource Management (Erm)

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Use And Effectiveness Of Wildlife Exits Designed For Ocelots And Other Mesocarnivores On A South Texas Highway, Zarina N. Sheikh, Jamie E. Langbein, Kevin W. Ryer, Md Saydur Rahman, Christopher A. Gabler, John H. Young Jr., Richard Kline

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Movement is a key component of survival and reproduction, often causing wildlife to cross heavily trafficked highways, resulting in road mortalities by oncoming vehicles. Fencing and crossing structures are commonly regarded as effective mitigation structures to reduce these mortalities. In south Texas, ten wildlife exits (WE) were installed along State Highway 100 in conjunction with existing mitigation structures to provide the US endangered ocelot (Leopardus pardalis), a medium-sized spotted wild cat, a safe option to escape the right of way (ROW). The objectives of this study were to determine the effectiveness and species usage and to estimate the …

Adoption Of Cybersecurity Policies By Local Governments 2020, Donald F. Norris Phd, Laura K. Mateczun Jd

Journal of Cybersecurity Education, Research and Practice

This paper should be of interest to the readers of this journal because it addresses a subject that has received little scholarly attention; namely, local government cybersecurity. The U.S. has over 90,000 units of local government, of which almost 39,000 are “general purpose” units (i.e., municipalities, counties, towns and townships). On average, these governments do not practice cybersecurity effectively (Norris, et al., 2019 and 2020). One possible reason is that they do not adopt and/or implement highly recommended cybersecurity policies. In this paper, we examine local government adoption or lack of adoption of cybersecurity policies using data from three surveys. …