Digital Commons Network^™

Sea-Level Rise And Regional Economic Adjustment On The U.S. Gulf Coast, Md A M Hasif, Juhee Lee, Robin A. Choudhury

School of Earth, Environmental, & Marine Sciences Faculty Publications

Sea-level rise (SLR) poses escalating risks to the U.S. Gulf Coast, where critical industries, infrastructure, and populations are concentrated in low-lying areas. This study estimates the short- and long-run economic effects of SLR using a panel autoregressive distributed lag-pooled mean group framework applied to county-level data from 26 coastal counties across five Gulf Coast states from 2005 to 2021. Over this period, mean sea level increased by approximately 11 cm on average across counties, with cumulative changes ranging from about 4 cm to over 24 cm and substantial cross-county variation, providing a meaningful empirical setting for identifying economic adjustment. We …

Investigating The Impact Of Outreach Programmes On Second Level Students In Formal And Informal Computer Science Education In Ireland, Karen Nolan

Doctoral

Computer Science (CS) education at second-level in Ireland has undergone significant development, including the introduction of the Leaving Certificate Computer Science (LCCS). However, the existing literature examined demonstrated that access to and participation in CS education is uneven, resulting in many students having limited exposure CS at second-level before making educational choices. At the same time, students who elect to study LCCS require appropriate support as they engage with programming and other aspects of a relatively new formal curriculum. This thesis investigates the function of school-based CS outreach in helping students at these various phases of their second-level CS education …

What Makes An Analogy Effective For Students’ Learning Of Mathematics? Conceptualising Analogy Effectiveness For Teaching Mathematics, Vesife Hatisaru, Steven Richardson

Research outputs 2022 to 2026

Analogies are commonly used in mathematics teaching as a means to promote understanding of new potentially abstract concepts, by linking them to well-understood contexts. Despite strong intuition that analogies are helpful in supporting students’ learning of mathematics, there is a lack of agreement on how to objectively judge the utility or conceptual affordances of these analogies. In this paper, we aim to conceptualise how to assess the effectiveness of an analogy by employing Gentner’s structure-mapping theory to analogies and explore two teacher-made analogies (the ‘child-mother’ and the ‘machine’) for learning the formal definition of a function as illustrative examples. By …

Geometric And Operational Design Principles For Autonomous Haulage Systems In Open-Pit Mining: A Systematic Review, Justina Senam Lotsu, Samuel Frimpong, Muhammad Azeem Raza

Mining Engineering Faculty Research & Creative Works

The rapid deployment of autonomous haulage systems (AHSs) in open-pit mining has significantly altered haul road geometric design requirements, as autonomous trucks operate under strict kinematic constraints related to turning radius, gradient, and braking performance. Since haulage accounts for 50–60% of total mining costs, optimizing haul road geometry is critical for improving operational efficiency, energy consumption, and safety. This study presents a systematic review of 50 highly relevant studies selected from 81 candidate publications published between 2003 and 2025 through structured database searches and citation chaining. The review synthesizes current developments in haul road layout optimization, turning radius accommodation, gradient …

Metrological Characterization Of Pavement Friction Measurements For High-Friction Surface Treatments: Si Traceability, Uncertainty Evaluation, And Adhesion–Hysteresis Separation Via Water–Soap Bpt Protocol, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Laboratory friction measurements are central to material screening for High-Friction Surface Treatments (HFST), yet metrological aspects including a proposed metrological traceability framework or uncertainty, and reproducibility are consistently underreported. This study applies a metrology-aligned framework to British Pendulum Tester (BPT) measurements performed in three states: dry, wet (water), and water–soap to assess operational adhesion and hysteresis components, document traceability to the International System of Units (SI), and report GUM-style uncertainty with covariance for the adhesion difference. Measurements were obtained for calcined bauxite (CB) and rhyolite (Rhy) in HFST and Coarse gradations across seven polishing protocols (baseline; LAA-1000/2000; MDA-105/180; PSV-10 h/20 …

Flexural Performance Of Deficient Rc Beams Repaired With Gfrp Composite, Zena Aljazaeri, Hayder Alghazali, Zuhair Al-Jaberi, John J. Myers

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Fiber-reinforced polymer composite materials have been improved for use in repairing and strengthening existing infrastructure over the past few decades. This case study focuses on the effect of confinement with GFRP strips on the structural performance of out-of-service beams in bridge applications due to the impact of over-height vehicles or inadequate lap-spliced reinforcements. In this study, beams with inadequate lap splices in the tension zone were utilized to mimic the damaged area in out-of-service RC beams. The proposed repair technique is a glass fiber-reinforced polymer (GFRP) composite in the form of longitudinal sheets and U-wrapped strips. The experimental study determined …

Editorial For The Special Issue “Advances And Applications Of Polymer Gels For Subsurface Energy And Storage”, Baojun Bai, Jingyang Pu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polymer gels are essential functional materials for subsurface energy operations, playing a critical role in conformance control, fluid diversion, hydraulic fracturing, and leakage mitigation. As reservoirs become increasingly complex and the demand for sustainable energy grows, continued innovation in gel technologies is crucial. This editorial introduces a Special Issue titled "Advances and Applications of Polymer Gels for Subsurface Energy and Storage," which compiles seven original research articles exploring recent developments in gel synthesis, characterization, and applications. The featured studies highlight the versatility of polymer gels, including nanoparticle-reinforced composites, foam–gel hybrids, recrosslinkable preformed particle gels, and advanced fracturing fluids. The contributions …

Collecting Holistic Evidence On Agroecology Performance To Accelerate Sustainable Food System Transitions, Sarah K. Jones, Andrea Cecilia Sánchez, Chris Dickens, Matthias S. Geck, Chaturangi Wickramaratne, Veronique Alary, Peter Bolo, Dennis Junior Choruma, Somphasith Douangsavanh, Modou Gueye Fall, Gatien Falconnier, Shweta Gupta, Chris Kettle, Smitha Krishnan, Sylvia Nyawira, Guillermo Orjuela-Ramirez, Boko Michel Orounladji, Piedad Pareja, Telma Sibanda, Christine Lamanna

All Peer-Reviewed Publications

A growing body of research shows the potential of agroecology for enabling a shift to planet-friendly and socially just agrifood systems through context-specific transition pathways. We conduct a scoping review to identify and evaluate the potential of 42 existing agroecology adherence and/or agricultural performance assessment tools to generate credible, legitimate, salient and transferable evidence to inform these transitions. Results show that while multiple relevant tools exist, each of them can be strengthened in at least one area. While most tools are transferable (low time and resource requirements) and have legitimacy (open access with transparent methods), tools have variable saliency (holistic …

Machine Learning-Enabled Chemical Ecology For Integrated Pest Management: From Volatiles To Field Applications, Steve B.S. Baleba, Victor O. Omondi, Pascal Aigbedion-Atalor, Emmanuel Peter, Souleymane Diallo, Komi Mensah Agboka

All Peer-Reviewed Publications

Machine learning is transforming chemical ecology by accelerating the discovery and deployment of semiochemical-based tools for precision pest management. These advances are particularly important in the face of climate change, pesticide resistance, and the growing need for sustainable agricultural intensification. This review synthesizes how machine learning can be applied across the semiochemical discovery and implementation pipeline, from chemical signal detection to field deployment and decision support for integrated pest management. We review major machine learning approaches and demonstrate how they extract biologically relevant information from high-dimensional chemical, electrophysiological, behavioral, sensor, and field datasets. These methods accelerate semiochemical discovery, prioritize candidate …

From Suitability To Invasion Risk: Integrating Correlative And Mechanistic Models For Predicting The Potential Distribution Of The Red Palm Weevil, Abdelmutalab G.A. Azrag, Komi Mensah Agboka, Elfatih M. Abdel-Rahman, Rehemah Gwokyalya, Seid A. Kemal, Hamadttu A.F. El-Shafie, Mohamed A. Bob, Samira A. Mohamed, Sunday Ekesi, Abdou Tenkouano

All Peer-Reviewed Publications

The red Palm Weevil (RPW) Rhynchophorus ferrugineus is the most devastating pest of palm trees and is responsible for significant economic and biodiversity losses worldwide. The larvae bore deep into the trunk or crown for feeding, resulting in extensive tunneling and mortality of the trees. In this study, we developed a hybrid modeling framework for RPW that integrates ecological niche modeling (ENMs) with a temperature-driven risk index (RI). The ENM was developed from the RPW occurrence data, while the RI was driven from temperature-dependent life history traits of RPW. The two approaches were combined through a weighted additive method to …

Quantile Normalisation Enables Interpretable Spatial Prioritisation Of Persistence-Related Mechanistic Suitability Under Uncertainty For Tomato Red Spider Mite (Tetranychus Evansi) In Africa, Komi Mensah Agboka, Luca Rossini, Quinto Juma Meltus, Bonoukpoè Mawuko Sokame, Abdulmutallab G.A. Azrag, Thomas Dubois, Elfatih M. Abdel-Rahman

All Peer-Reviewed Publications

Mechanistic trait models are increasingly considered to estimate persistence-related suitability for invasive species, although translating reproduction metrics into operational indicators for spatial decision-making remains challenging. Branching-process transformations are widely applied to convert mechanistic reproduction numbers into probabilities of establishment; however, such transformations may compress spatial gradients when persistence is broadly feasible. Using tomato red spider mite (Tetranychus evansi) as a case study across Africa, this study developed an uncertainty-aware, physiologically-based model and generated spatially explicit estimates of expected reproduction (R0). We compared three representations: raw mechanistic suitability, branching-process persistence probability, and quantile-normalised suitability. Although all representations preserved rank ordering, branching …

Learning 1-Bit Lidar-Based Localization With Auxiliary Objective, Kaijie Yin, Zhiyuan Zhang, Tian Gao, Wentao Zhu, Cheng-Zhong Xu, Hui Kong

Research Collection School Of Computing and Information Systems

6-DoF LiDAR-based localization is a fundamental capability for autonomous systems operating in large-scale outdoor environments. Many deep-learning-based localization methods have achieved promising performance so far. However, as one of the always-on modules competing for limited on-board computational resources, the localization module is expected to consume only a small portion of the overall compute budget. Most existing learning-based methods are still too heavy for this purpose. In contrast, binary neural networks (BNNs) offer an appealing solution, but the 1-bit compression causes severe information loss and performance drop. In this paper, we address this challenge by proposing Binarized LiDAR-based Localization (BiLoc), the …

Smart: When Is It Actually Worth Expanding A Speculative Tree?, Lifu Wang, Pan Zhou

Research Collection School Of Computing and Information Systems

Tree-based speculative decoding accelerates autoregressive generation by verifying a branching tree of draft tokens in a single targetmodel forward pass. However, existing methods prioritize maximizing token-level likelihood or the number of accepted tokens while ignoring a critical “efficiency paradox”: the computational overhead of drafting and verifying big trees can grow super-linearly, particularly at scale. This often leads to negative wall-clock speedup when batch sizes increase or hardware saturation limits are reached. To address this, we propose SMART, a System-aware Marginal Analysis framework for Runtime Tree construction. SMART reformulates tree expansion as a hardware-aware optimization problem that directly maximizes end-toend speedup. …

Paper Wasp Species Polistes Fuscatus (Hymenoptera: Vespidae) Tracks Urban Lead (Pb) Levels More Than Polistes Dominula, Lindsey R. Kemmerling, Anna L. Lovat, Allison A. Hanka, Emilie C. Snell-Rood

The Great Lakes Entomologist

Lead (Pb) is a persistent, toxic pollutant with widespread but inequitably distributed impacts, especially for humans in urban areas. The impacts of lead pollution on other organisms is largely unknown, even as they commonly experience exposure to lead alongside humans. We tested hypotheses regarding the lead concentrations of paper wasps across a gradient of pollution relative to soil and human lead levels, and correlations with wasp body condition. We collected two species of paper wasp across an urban gradient of lead pollution: Polistes fuscatus (Fabricius) (Hymenoptera: Vespidae), native to our study location, and Polistes dominula (Christ), nonnative to our study …

Long-Term Monitoring And Response Of Papaipema Sciata Bird (Lepidoptera: Noctuidae) To Prescribed Fire In Michigan (Usa), Gregory J. Norwood, Logan M. Rowe, Brett A. Degregorio, David L. Cuthrell, Aaron D. Meredith, Steven M. Gray

The Great Lakes Entomologist

The Culver’s root borer moth (Papaipema sciata) (Lepidoptera: Noctuidae) is a rare Noctuid that requires Culver’s root (Veronicastrum virginicum) to complete its lifecycle within remnant native grasslands and open woodlands in the midwest and northeast United States. We report on 26 years of monitoring this species’ colonization of Culver’s root stems at Algonac State Park (ASP) in Michigan, where prairies have been maintained by prescribed fire since 1990. P. sciata is considered fire sensitive because eggs spend the dormant season in the combustible prairie litter and duff near host plants. The objectives were to determine the …

Enhancing Ecg Classification Using Systematic Cubic Spline Control Points With Deep Neural Networks, Hussein Qahtan Khalaf, Abeer Tariq Maolood, Nor Shahida Mohd Shah

Engineering and Technology Journal

The healthcare industry has undergone substantial growth over the past few years. Despite the development of medical technology, the diagnosis of cardiac arrhythmia is still a significant challenge for modern diagnostic methods for correct and efficient classification of electrocardiogram (ECG) signals, especially in cases of class imbalance and the complexity of the arrhythmia. This study proposes a novel deep learning model where the class imbalance problem is addressed using the Synthetic Minority Oversampling Technique (SMOTE) and the effect of signal resolution on the classification is investigated using Cubic Spline (CS) interpolation and Lightweight Deep Neural Network (CSLWDNN). Both the MIT-BIH …

Neural Network Modelling Of Magnetic Effects In Solid-State Transformer Performance Under Variable Magnetic Operating Conditions, Godfrey Murairidzi Gotora, Blessed Ziyambe, Emanuel Rashayi

Engineering and Technology Journal

Solid State transformers (SSTs) are pivotal for renewable energy integration and smart grids, yet their performance is critically limited by non-linear magnetic effects such as core losses, flux- density saturation, and magnetising-inductance drift, that conventional analytical methods and prior artificial neural network (ANN) studies have struggled to model simultaneously across the electrical, thermal and magnetic domains. This study develops and evaluates a unified multi-output ANN framework that predicts six SST performance indicators which are efficiency, power density, total harmonic distortion, temperature rise, core loss and magnetising inductance from six operating variables (switching frequency, duty cycle, load current, ambient temperature, input …

The Mathematical Model Predicts Peripheral Blood Cd34+ Cell Yield And Blood Volume Processing For Peripheral Blood Stem Cell Apheresis., Rattaporn Vichitratchaneekorn, Kanokpol Siriphanthong, Kanokwan Chinbordee, Phandee Watanaboonyongcharoen, Ponlapat Ronjnuckarin

Chulalongkorn Medical Journal

Introduction: The accurate prediction of stem cell yields is important for planning peripheral blood stem cell (PBSC) collection. This study aimed to develop a formula forecasting required blood volume processing to ensure adequate CD34+ cell products.

Methods: Data from donors and patients who underwent PBSC apheresis conducted at a tertiary care hospital were reviewed. BD FACSCanto™ II and Navios EX flow cytometry machines were used to determine the pre-collection CD34+ cell counts (preCD34).

Results: Of 50 donors and 85 patients, 145 leukapheresis procedures were performed. Linear regression models accurately predicted absolute CD34+ cell yields from pre-apheresis values, supporting optimal procedural …

Cmsi Translations #35: How To Leverage The "Butterfly Effect" To Cause The Collapse Of "Taiwan Independence" Elements?, Su Ming

CMSI Translations

Intelligent Tools for Designing Operational Concepts: Intelligent Agents Innovating Mechanisms for Victory

If a large model is likened to a machine, interacting via conversation is akin to a worker manually operating that machine. Although machine tools have significantly reduced human workloads, “manual operation” still entails challenges: demanding skill requirements for operators; difficulty in resolving complex, specialized tasks through conversation alone; difficulty in standardizing and reusing repetitive workflows; susceptibility to hallucinations; and the time- and labor-intensive nature of verifying results. To this end, the Department of Theoretical Innovation Research has proposed a technical roadmap for programming large models. The underlying concept …

Illinois Model Programs Of Study Guide: Education (Draft For Public Comment), Education Systems Center

Practitioner Toolkits and Resources

This draft was available for public comment through September 30, 2026. A final version will be released in October 2026.

Illinois Model Programs Of Study Guide: Digital Technology (Draft For Public Comment), Education Systems Center

Practitioner Toolkits and Resources

This draft was available for public comment through September 30, 2026. A final version will be released in October 2026.

Optimal Procedure For Measuring The Parameters Of Optical Signals Considering Noise, Yuriy Gennadyevich Shipulin, Azimjon Mamadaliyevich Xusanov

Chemical Technology, Control and Management

It has been shown that to achieve the required level of measurement accuracy and reliability, it is necessary to transition from quality control of finished products to quality management based on cost-effective methods during the stages when product properties are formed. It is shown that the complexity of measuring optical signal parameters during analysis or synthesis requires them to be considered as part of a general information processing system. Based on the nonlinear filtration method, an optimal procedure for measuring a variable position in time against a background of spatial noise was obtained. Structural diagrams of optimal measuring instruments for …

Determination Of The Content Of Water-Soluble Vitamins In The Composition Of Beet Beetroot Composition, Jasur Esirgapovich Safarov, Shakhnoza Abduvaxitovna Sultanova, Muhammad Rasul Oglu Najafli, Doston Ishmuhammat Ugli Samandarov

Chemical Technology, Control and Management

The aim of this study was to determine the content of water-soluble vitamins in various parts of beetroot (pulp, leaves and stems) that had been subjected to various drying methods in a bid to explore the effect of physical processes, i.e., the application of ultrasound, on micronutrient preservation. The experiments were performed at the Department of Service Technologies of Tashkent State Technical University, and chromatographic analysis was performed in the Institute of Bioorganic Chemistry of the Academy of Sciences of the Republic of Uzbekistan. Chromatography was performed on Agilent-1200 chromatograph with Exlipse XDB C18 column and diode array detector using …

Fast Algorithms For Combined Synthesis Of Dynamic Object Control Systems, Isomiddin Khakimovich Siddikov, Gulchexra Alimova

Chemical Technology, Control and Management

The paper considers the issues of combined synthesis of a control system for a nonlinear dynamic object. The combined synthesis algorithms are based on the hybrid application of the theory of ordinary differential equations in the Cauchy form and the theory of automatic control. In this case, the dynamics of the control system are described in the input-output representation and by state-space equations. Algorithms for solving stabilization problems, finite control, and the inverse dynamics problem are presented in explicit form. These algorithms are based on the concept of reducibility of a general Cauchy-form system to the block-canonical Frobenius form. The …

Analysis Of The Throttle Settings Under Uncertain Information, Latafat Gardashova, Nihad Afandi

Chemical Technology, Control and Management

Although classical fuzzy logic controllers are capable of modelling non-linear control systems, they fail to consider the reliability of linguistic information, sensor measurements, and expert knowledge. In this paper, an intelligent controller based on the use of Z-numbers is developed for steam-turbine throttle control. Linguistic information and its confidence degree are considered simultaneously in such a controller. The temperature and pressure values are taken as input variables, while the throttle rotation is selected as the controller output variable. At first, the Z-number representation system is constructed to include the credibility of linguistic measurements and control rules. Then, a Mamdani Type-1 …

Guardians Of The Record (Cs2 Edition): Heaps, Queues, And A Scarce Oracle, Ilan Goodman

Generative AI Teaching Activities

Students defend Wikipedia from vandals with data structures instead of infrastructure: a sliding-window edit-velocity tracker (hash map of queues), a hand-built binary min-heap, and a budget-bounded top-K selection decide which few suspicious edits earn a question to an expensive, rate-limited Oracle — a stand-in for a real LLM.

Clinic-In-A-Box: A Portable, Software-Defined Cyber Range For Realistic, Scenario-Based Cybersecurity Training, Ethan Chumley, Aaron Nair, Royce Yaezenko, Joshua Payne, Veronika Kyles, Paul Wagner, Robert J. Honomichl, Ryan Straight, Shengjie Xu

Journal of Cybersecurity Education, Research and Practice

Realistic, hands-on cybersecurity training has traditionally depended on fixed infrastructure such as dedicated lab hardware, cloud subscriptions, or permanent network connectivity, limiting where and how often it can be delivered. This paper presents the design and implementation of a portable, scenario-based cybersecurity training platform housed in a single travel case and built from commodity hardware, type-1 hypervisor virtualization, containerized service orchestration, and software-defined networking. The platform clones, isolates, and resets complete lab environments on demand, allowing the same physical system to support repeated classroom, workshop, or field deployments with minimal manual reconfiguration. Training scenarios are grounded in generated organizational profiles …

Between Digital Transformation And Regulatory Vacuum: Cybersecurity Of Public Services In Mozambique, Faztudo Languisse Eng.

Journal of Cybersecurity Education, Research and Practice

The rapid expansion of digital public services in Mozambique—including e-government platforms, digital health systems, and electronic tax administration—has outpaced the development of a coherent legal framework for cybersecurity. While Law No. 3/2017 (Electronic Transactions Law) of 9 January 2017 introduced foundational data-protection principles, Mozambique long lacked a dedicated cybersecurity regulatory authority, mandatory security standards, and formal incident-notification mechanisms. This regulatory vacuum exposed critical public services to escalating cyber risks as digital transformation was actively promoted as a development priority. This article examines the legal and institutional gaps in Mozambique's cybersecurity governance framework prior to the 2026 Cybersecurity and Cybercrime Laws, …

Design Of A Smart Esp32-Based Iot Prototype Using Azure Iot Hub For Automatic Detection, Neutralization, And Safe Disposal Of Acidic And Basic Chemical Waste In Laboratory Environments, M.J. Fernando, K.C.K.V. Samarathunga, G.A. Heshan, J.A.D.S.R. Jayasinghe, K.S.R Perera, K.G.C.M. Perera, K.D.T.D. Jayasuriya, S.M.H.M. Koswatta

Journal of Innovation in Science, Engineering and Technology

The generation of acidic and alkaline laboratory waste remains an enduring safety and environmental problem in educational institutions, research laboratories, and small-scale industrial settings. In many such environments, neutralization is still performed manually through intermittent pH measurement and operator judgement. This practice is slow, inconsistent, and potentially hazardous, particularly when corrosive substances are involved. The present study proposes and evaluates a smart Internet of Things (IoT) prototype that automates the detection, neutralization, and monitoring of laboratory chemical waste by integrating edge intelligence with secure cloud telemetry.
The proposed system is centered on an ESP32-S3-N16R8 microcontroller, a DFRobot SEN0161 pH sensor, …

Validation Of A Home-Based Tool For Preschool Children Fall Prevention: A Rasch Analysis, Devie Fitri Octaviani, Fatma Lestari, Indang Trihandini, Dadan Erwandi

Kesmas

Unintentional falls are a leading cause of injury among preschool children, primarily occurring in home environments, yet validated tools to assess household fall prevention capacity in low- and middle-income countries remain limited. This study aimed to develop and psychometrically validate the Home-Based Preschool Fall Prevention Instrument using the Rasch Measurement Model. A cross-sectional validation study was conducted in Depok City, Indonesia, involving 167 primary caregivers of preschool children enrolled in kindergartens selected through multistage cluster random sampling. The instrument was developed based on an etiological injury model, socio-ecological perspectives, and risk management principles, and comprised four main factors: child, home, …