Physical Sciences and Mathematics Commons^™

Modifed Playfair For Text File Encryption And Meticulous Decryption With Arbitrary Fillers By Septenary Quadrate Pattern, N. Sugirtham, R. Sherine Jenny, B. Thiyaneswaran, S. Kumarganesh, C. Venkatesan, K. Martin Sagayam, Lam Dang, Linh Dinh, Helen Dang

Mathematics and Computer Studies: Faculty Publications

Cryptography secures data and serves to ensure the confidentiality of records. Playfair is a cryptographic symmetrical algorithm that encrypts statistics based on key costs. This secret is shared with an authorized person to retrieve data. In the conventional pattern, there is an area complexity and deficiency in letters, numbers, and special characters. This hassle has been overcome in previous studies by editing pattern dimensions. The fillers used throughout the enciphering were not eliminated during the retrieval process, which resulted in the indiscrimination of the retrieved statistics. The proposed method uses a separate quadrate pattern that strengthens the Playfair cipher and …

A Road Map For Developing Novel Decision Support System (Dss) For Disseminating Integrated Pest Management (Ipm) Technologies, Franck B.N. Tonle, Saliou Niassy, Milliam M.Z. Ndadji, Maurice T. Tchendji, Armand Nzeukou, Bester T. Mudereri, Kennedy Senagi, Henri E.Z. Tonnang

All Peer-Reviewed Publications

Integrated Pest Management (IPM) technologies offer effective solutions to reduce the negative effects of crop pests while considering human and environmental health. However, disseminating these technologies faces several barriers, with one of the most significant being the lack of farmer awareness regarding their availability, deployment, and uptake. Digital tools are perceived as a new form of leverage for overcoming these barriers. This study analyzes current IPM digital tools and their potential to boost farmers’ awareness of the deployment and adoption of IPM technologies. From a software engineering perspective, this study aims to emphasize the critical functionalities and limitations of various …

Characterizing Catalyst Function And Transformations In The Plasma Reduction Of Co2 On Atomic Layer Deposition-Synthesized Catalysts, Samuel Keith Conlin, Hamed Mehrabi, David Parette, Eva M. Nichols, Robert H. Coridan

Chemistry & Biochemistry Faculty Publications and Presentations

The enhancement of CO₂ reduction in atmospheric-pressure, non-thermal plasma has been shown using a variety of catalyst systems with ranging composition, particle sizes, and morphologies. Improvements in CO₂ conversion can be attained by choice of catalyst material. However, inhomogeneity in the material distribution arising from the synthesis affects the catalytically active surface area and dielectric environment that modulates the plasma properties near the catalyst. Atomic layer deposition (ALD) can be used to control the composition of ultra-thin layers on support materials. We used ALD to synthesize metal oxide catalyst coatings on high surface area supports. We found that …

Retardation Effects In Atom-Wall Interactions, T. Das, C. A. Ullrich, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

The onset of retardation effects in atom-wall interactions is studied. It is shown that the transition range from the 1/z3 short-range (van der Waals) interaction to the 1/z4 long-range (Casimir) retarded interaction critically depends on the atomic properties and on the dielectric function of the material. For simple non-alkali-metal atoms (e.g., ground-state hydrogen and ground-state helium) interacting with typical dielectric materials such as intrinsic silicon, the transition to the retarded regime is shown to proceed at a distance of about 10 nm (200 Bohr radii). This is much shorter than typical characteristic absorption wavelengths of solids. Larger transition regimes are …

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

Iowa Waste Reduction Center Newsletter

Contents:

--- Conference Season in Full Swing
--- ISOSWO Student Conference Scholarship Deadline
--- Diane Albertson Memorial Scholarship
--- Keeping Tabs on PFAS
--- Coating Workshop Coming to Des Moines
--- Important Reminders

Southern Maine, New Hampshire, And Northern Massachusetts Continental Shelf Geophysical Database: 2022 Field Campaign – Grain Size Data, Station Summaries, And Seafloor Photographs, Larry G. Ward, Rachel C. Morrison, Michael Bogonko

Data Catalog

Presented in this data report are the geophysical data collected during a major field campaign in 2022, with the purpose of obtaining ground truth for the expansion and improvement of high-resolution surficial geology maps of the western Gulf of Maine (WGOM) and for the description of reference sites developed for future evaluations of acoustic systems (Ward et al., 2021a; 2021b). Data from the UNH Ocean Engineering 972 Hydrographic Field Course classes in 2021 and 2022 are also included. This expansion of the geophysical database is being used to verify seafloor classifications in previously mapped areas that lack sufficient data, and …

Dl-Drl: A Double-Level Deep Reinforcement Learning Approach For Large-Scale Task Scheduling Of Multi-Uav, Xiao Mao, Guohua Wu, Mingfeng Fan, Zhiguang Cao, Witold Pedrycz

Research Collection School Of Computing and Information Systems

Exploiting unmanned aerial vehicles (UAVs) to execute tasks is gaining growing popularity recently. To address the underlying task scheduling problem, conventional exact and heuristic algorithms encounter challenges such as rapidly increasing computation time and heavy reliance on domain knowledge, particularly when dealing with large-scale problems. The deep reinforcement learning (DRL) based methods that learn useful patterns from massive data demonstrate notable advantages. However, their decision space will become prohibitively huge as the problem scales up, thus deteriorating the computation efficiency. To alleviate this issue, we propose a double-level deep reinforcement learning (DL-DRL) approach based on a divide and conquer framework …

Artificial Intelligence Model Predicts Sudden Cardiac Arrest Manifesting With Pulseless Electric Activity Versus Ventricular Fibrillation, Hoang Nhat Pham, Angelo Salvucci, Jonathan Jui, Kyndaron Reinier, Piotr J Slomka, Sumeet S Chugh

Faculty, Staff and Student Publications

BACKGROUND: There is no specific treatment for sudden cardiac arrest (SCA) manifesting as pulseless electric activity (PEA) and survival rates are low; unlike ventricular fibrillation (VF), which is treatable by defibrillation. Development of novel treatments requires fundamental clinical studies, but access to the true initial rhythm has been a limiting factor.

METHODS: Using demographics and detailed clinical variables, we trained and tested an AI model (extreme gradient boosting) to differentiate PEA-SCA versus VF-SCA in a novel setting that provided the true initial rhythm. A subgroup of SCAs are witnessed by emergency medical services personnel, and because the response time is …

Improved Subseasonal Prediction Of South Asian Monsoon Rainfall Using Data-Driven Forecasts Of Oscillatory Modes, Eviatar Bach, Venkat Krishnamurthy, Safa Mote, Jagadish Shukla, A. Surjalal Sharma, Eugenia Kalnay, Michael Ghil

Mathematics and Statistics Faculty Publications and Presentations

Predicting the temporal and spatial patterns of South Asian monsoon rainfall within a season is of critical importance due to its impact on agriculture, water availability, and flooding. The monsoon intraseasonal oscillation (MISO) is a robust northwardpropagating mode that determines the active and break phases of the monsoon and much of the regional distribution of rainfall. However, dynamical atmospheric forecast models predict this mode poorly. Data-driven methods for MISO prediction have shown more skill, but only predict the portion of the rainfall corresponding to MISO rather than the full rainfall signal. Here, we combine state-of-the-art ensemble precipitation forecasts from a …

Forests Are Chill: The Interplay Between Thermal Comfort And Mental Wellbeing, Loïc Gillerot, Kevin Rozario, Pieter De Frenne, Rachel Oh, Quentin Ponette, Aletta Bonn, Winston T. L. Chow, Douglas Godbold, Matthias Steinparzaer, Daniela Haluza, Dries Landuyt, Bart Muys, Kris Verheyen

Research Collection College of Integrative Studies

As global warming and urbanisation intensify unabated, a growing share of the human population is exposed to dangerous heat levels. Trees and forests can effectively mitigate such heat alongside numerous health co-benefits like improved mental wellbeing. Yet, which forest types are objectively and subjectively coolest to humans, and how thermal and mental wellbeing interact, remain understudied. We surveyed 223 participants in peri-urban forests with varying biodiversity levels in Austria, Belgium and Germany. Using microclimate sensors, questionnaires and saliva cortisol measures, we monitored intra-individual changes in thermal and mental states from non-forest baseline to forest conditions. Forests reduced daytime modified Physiologically …

Semantic Segmentation Of Longitudinal Thermal Images For Identification Of Hot And Cool Spots In Urban Areas, Vasantha Ramani, Pandarasamy Arjunan, Kameshwar Poolla, Clayton Miller

Research Collection College of Integrative Studies

This work presents the analysis of semantically segmented, longitudinally, and spatially rich thermal images collected at the neighborhood scale to identify hot and cool spots in urban areas. An infrared observatory was operated over a few months to collect thermal images of different types of buildings on the educational campus of the National University of Singapore. A subset of the thermal image dataset was used to train state-of-the-art deep learning models to segment various urban features such as buildings, vegetation, sky, and roads. It was observed that the U-Net segmentation model with ‘resnet34’ CNN backbone has the highest mIoU score …

Fisheries Research Report No. 339: Assessment Of The Status Of The South Coast Demersal Scalefish Resource, Jeffrey V. Norriss, Sybrand A. Hesp, David V. Fairclough, Rubie Evans-Powell, B. Hancock, Emily A. Fisher, Tim Leary, Nick Jarvis

Fisheries Research Reports

This document provides the 2023 risk-based weight of evidence stock assessments for snapper, Bight redfish, hapuku, blue morwong, and Western blue groper for 2023 in the South Coast Bioregion (SCB).

The Fourier–Legendre Series Of Bessel Functions Of The First Kind And The Summed Series Involving 1F2 Hypergeometric Functions That Arise From Them, Jack C. Straton

Physics Faculty Publications and Presentations

The Bessel function of the first kind JN^(kx) is expanded in a Fourier–Legendre series, as is the modified Bessel function of the first kind IN^(kx). The purpose of these expansions in Legendre polynomials was not an attempt to rival established numerical methods for calculating Bessel functions but to provide a form for JN^(kx) useful for analytical work in the area of strong laser fields, where analytical integration over scattering angles is essential. Despite their primary purpose, one can easily truncate the series at 21 terms to provide 33-digit accuracy that matches the IEEE extended precision in …

Dataset Of Arabic Spam And Ham Tweets, Sanaa Kaddoura, Safaa Henno

All Works

This data article provides a dataset of 132421 posts and their corresponding information collected from Twitter social media. The data has two classes, ham or spam, where ham indicates non-spam clean tweets. The main target of this dataset is to study a way to classify whether a post is a spam or not automatically. The data is in Arabic language only, which makes the data essential to the researchers in Arabic natural language processing (NLP) due to the lack of resources in this language. The data is made publicly available to allow researchers to use it as a benchmark for …

Developing A Success Model Of A Social Student Relationship Management System, Wasef Mater, Monther Aldwairi, Nasim Matar, Waleed Al-Rahmi

All Works

Social media's significance in higher education has increased due to its capacity to enhance participation, communication, teamwork, and information sharing. Important notifications, updates, and reminders can be promptly received by all members of the university community, assuring that information is shared with everyone. The objective of this study is to develop a model for a Customer Relationship Management (CRM) system in higher education that is based on social media and intends to increase student satisfaction, loyalty, and profitability. It blends the idea of trust with Delone Mclean success model. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to evaluate the …

Robust Permissioned Blockchain Consensus For Unstable Communication In Fanet, Zihao Wang, Hang Wang, Zhuowen Li, Xinghua Li, Yinbin Miao, Yanbing Ren, Yunwei Wang, Zhe Ren, Deng, Robert H.

Research Collection School Of Computing and Information Systems

The utilization of blockchain technology as a distributed information sharing system has gained widespread adoption across various domains. However, its application to Flying Ad-Hoc Network (FANET), characterized by severe packet loss, poses significant challenges. The high packet loss rates in FANETs can result in decreased consensus success rates and negatively impact information sharing consistency and efficiency. In this paper, we proposed RoUBC, a novel consensus scheme for Flying Ad-Hoc Networks (FANET), which is based on the Raft protocol and is designed to address the challenges posed by the severe packet loss network in FANET. The proposed scheme consists of two …

Imitate The Good And Avoid The Bad: An Incremental Approach To Safe Reinforcement Learning, Minh Huy Hoang, Tien Mai, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

A popular framework for enforcing safe actions in Rein- forcement Learning (RL) is Constrained RL, where trajectory based constraints on expected cost (or other cost measures) are employed to enforce safety and more importantly these constraints are enforced while maximizing expected reward. Most recent approaches for solving Constrained RL convert the trajectory based cost constraint into a surrogate problem that can be solved using minor modifications to RL methods. A key drawback with such approaches is an over or under- estimation of the cost constraint at each state. Therefore, we provide an approach that does not modify the trajectory based …

Pam3s: Progressive Two-Stage Auction-Based Multi-Platform Multi-User Mutual Selection Scheme In Mcs, Bin Luo, Xinghua Li, Yinbin Miao, Man Zhang, Ximeng Liu, Yanbing Ren, Xizhao Luo, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Mobile crowdsensing (MCS) has been applied in various fields to realize data sharing, where multiple platforms and multiple Mobile Users () have appeared recently. However, aiming at mutual selection, the existing works ignore making ' utilities with the limited resources and platforms' utilities while achieving the desired sensing data quality maximum as far as possible. Thus, they cannot motivate both and platforms to participate. To address this problem, standing on both sides of and platforms with conflicting interests, we propose a Progressive two-stage Auction-based Multi-platform Multi-user Mutual Selection scheme (). Specifically, in, we treat mutual selection as a two-stage auction …

Reverse Multi-Choice Dialogue Commonsense Inference With Graph-Of-Thought, Li Zheng, Hao Fei, Fei Li, Bobo Li, Lizi Liao, Donghong Ji, Chong Teng

Research Collection School Of Computing and Information Systems

With the proliferation of dialogic data across the Internet, the Dialogue Commonsense Multi-choice Question Answering (DC-MCQ) task has emerged as a response to the challenge of comprehending user queries and intentions. Although prevailing methodologies exhibit effectiveness in addressing single-choice questions, they encounter difficulties in handling multi-choice queries due to the heightened intricacy and informational density. In this paper, inspired by the human cognitive process of progressively excluding options, we propose a three-step Reverse Exclusion Graph-of-Thought (ReX-GoT) framework, including Option Exclusion, Error Analysis, and Combine Information. Specifically, our ReX-GoT mimics human reasoning by gradually excluding irrelevant options and learning the reasons …

Handling Long And Richly Constrained Tasks Through Constrained Hierarchical Reinforcement Learning, Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Safety in goal directed Reinforcement Learning (RL) settings has typically been handled through constraints over trajectories and have demonstrated good performance in primarily short horizon tasks. In this paper, we are specifically interested in the problem of solving temporally extended decision making problems such as robots cleaning different areas in a house while avoiding slippery and unsafe areas (e.g., stairs) and retaining enough charge to move to a charging dock; in the presence of complex safety constraints. Our key contribution is a (safety) Constrained Search with Hierarchical Reinforcement Learning (CoSHRL) mechanism that combines an upper level constrained search agent (which …

Simple Image-Level Classification Improves Open-Vocabulary Object Detection, Ruohuan Fang, Guansong Pang, Xiao Bai

Research Collection School Of Computing and Information Systems

Open-Vocabulary Object Detection (OVOD) aims to detect novel objects beyond a given set of base categories on which the detection model is trained. Recent OVOD methods focus on adapting the image-level pre-trained vision-language models (VLMs), such as CLIP, to a region-level object detection task via, eg., region-level knowledge distillation, regional prompt learning, or region-text pre-training, to expand the detection vocabulary. These methods have demonstrated remarkable performance in recognizing regional visual concepts, but they are weak in exploiting the VLMs' powerful global scene understanding ability learned from the billion-scale image-level text descriptions. This limits their capability in detecting hard objects of …

Market-Gan: Adding Control To Financial Market Data Generation With Semantic Context, Haochong Xia, Shuo Sun, Xinrun Wang, Bo An

Research Collection School Of Computing and Information Systems

Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making. Despite the development of financial market simulation methodologies, existing frameworks often struggle with adapting to specialized simulation context. We pinpoint the challenges as i) current financial datasets do not contain context labels; ii) current techniques are not designed to generate financial data with context as control, which demands greater precision compared to other modalities; iii) the inherent difficulties in generating context-aligned, high-fidelity data given the non-stationary, noisy nature of financial data. To address these challenges, our contributions are: i) we proposed the Contextual …

New Effective Transformational Computational Methods, Jun Zhang, Ruzong Fan, Fangyang Shen, Junyi Tu

Publications and Research

Mathematics serves as a fundamental intelligent theoretic basis for computation, and mathematical analysis is very useful to develop computational methods to solve various problems in science and engineering. Integral transforms such as Laplace Transform have been playing an important role in computational methods. In this paper, we will introduce Sumudu Transform in a new computational approach, in which effective computational methods will be developed and implemented. Such computational methods are straightforward to understand, but powerful to incorporate into computational science to solve different problems automatically. We will provide computational analysis and essentiality by surveying and summarizing some related recent works, …

Agricultural Groundcover Update January 2024, Justin Laycock

Natural resources published reports

Summary

• About 94% of the grainbelt had adequate (more than 50%) vegetative groundcover to prevent wind erosion in January 2024.
• In the northern half of the grainbelt, a larger-than-average area has 51–60% groundcover, which is expected to decrease to below 50% over the coming months.
• Just under 6% of the grainbelt (855,000 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion. West Midlands Ag Soil Zone had the highest risk of wind erosion and 14.5% of this farmland had inadequate groundcover.
• Less than 0.5% of the grainbelt had a high to very high risk of wind …

Broadening Participation Of Teachers In Computing: Examining Postsecondary Educational Experiences And Prospective Educators’ Cs Teaching Interests, Robert Schwarzhaupt, Alexsandra Galanis, Joanna Goode, Kate Blanchard, Jill Bowdon, Joseph P. Wilson

Journal of Computer Science Integration

Teacher shortages in K–12 computer science (CS) education negatively impact students’ access to CS courses, exposure to CS concepts, and interest in CS-related careers. To address CS teacher shortages, this study seeks to understand factors related to expressing a preference to teach CS among prospective teachers. The study team analyzed data from 27,700 prospective teacher applications accepted into the 2016–2020 Teach For America (TFA) corps (cohorts). The TFA corps is an alternative teacher development program that recruits and prepares participants to obtain their teaching certification while they work for at least two years in underserved communities on a temporary teaching …

Characterizing Linearizable Qaps By The Level-1 Reformulation-Linearization Technique, Lucas Waddell, Warren Adams

Faculty Journal Articles

The quadratic assignment problem (QAP) is an extremely challenging NP-hard combinatorial optimization program. Due to its difficulty, a research emphasis has been to identify special cases that are polynomially solvable. Included within this emphasis are instances which are linearizable; that is, which can be rewritten as a linear assignment problem having the property that the objective function value is preserved at all feasible solutions. Various known sufficient conditions for identifying linearizable instances have been explained in terms of the continuous relaxation of a weakened version of the level-1 reformulation-linearization-technique (RLT) form that does not enforce nonnegativity on a subset …

Residual Optical Absorption From Native Defects In Cdsip2 Crystals, Timothy D. Gustafson, Nancy C. Giles, Elizabeth M. Scherrer, Kevin T. Zawilski, Peter G. Schunemann, Kent L. Averett, Jonathan E. Slagle, Larry E. Halliburton

Faculty Publications

CdSiP₂ crystals are used in optical parametric oscillators to produce tunable output in the mid-infrared. As expected, the performance of the OPOs is adversely affected by residual optical absorption from native defects that are unintentionally present in the crystals. Electron paramagnetic resonance (EPR) identifies these native defects. Singly ionized silicon vacancies (V^-_Si) are responsible for broad optical absorption bands peaking near 800, 1033, and 1907 nm. A fourth absorption band, peaking near 630 nm, does not involve silicon vacancies. Exposure to 1064 nm light when the temperature of the CdSiP₂ crystal is near 80K converts …

Struvite-Phosphorus Effects On Greenhouse Gas Emissions And Plant And Soil Response In A Furrow-Irrigated Rice Production System In Eastern Arkansas, Diego Della Lunga, Kristofor R. Brye, Trenton L. Roberts, Jonathan Brye, Michelle Evans-White, Christopher G. Henry, Daniel J. Lessner, Chandler Arel

Crop, Soil and Environmental Sciences Faculty Publications and Presentations

Phosphorus (P) fertilizers with low water solubility, like struvite (MgNH₄PO₄·6H₂O), have been identified to possibly reduce nutrient losses in furrow-irrigated cropping systems. However, there is a lack of research on the impacts of P and nitrogen (N) fertilization on greenhouse gas [GHG; i.e., methane (CH₄), nitrous oxide (N₂O), and carbon dioxide (CO₂)] production in furrow-irrigated rice (Oryza sativa). The objective of this study was to evaluate the effects of electrochemically precipitated struvite (ECST), chemically precipitated struvite (CPST), triple superphosphate (TSP), diammonium phosphate (DAP), environmentally smart nitrogen …

Exciton Dynamics, Interaction, And Transport In Monolayers Of Transition Metal Dichalcogenides, Saroj Chand

Dissertations, Theses, and Capstone Projects

Monolayers Transition metal dichalcogenides (TMDs) have attracted much attention in recent years due to their promising optical and electronic properties for applications in optoelectronic devices. The rich multivalley band structure and sizable spin-orbit coupling in monolayer TMDs result in several optically bright and dark excitonic states with different spin and valley configurations. In the proposed works, we have developed experimental techniques and theoretical models to study the dynamics, interactions, and transport of both dark and bright excitons.

In W-based monolayers of TMDs, the momentum dark exciton cannot typically recombine optically, but they represent the lowest excitonic state of the system …

Low Elevation Coastal Zone (Lecz) Population Social Vulnerability And Risk: A Spatial Analysis Based On The 2015-16 National Family Health Survey (Nfhs-4) Of India, Paradorn Wongchanapai

Dissertations, Theses, and Capstone Projects

Background & Problem Statement:

This study assessed social vulnerability and risk to hydroclimate hazards of Indian urban and rural populations in the Low Elevation Coastal Zone (LECZ), a contiguous coastal area with elevations less than 10 meters. The LECZ is considered an at-risk area as hydroclimate hazards tend to be heightened. Moreover, being the most populous country in the world, any hydroclimate hazards that hit the LECZ would disproportionately impact a large number of Indian populations. Understanding the social vulnerability and risk of the LECZ populations can help mitigate and prevent potential adverse outcomes for the populations.

Importantly, this study …