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2024

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Conditional Constrained And Unconstrained Quantization For Probability Distributions, Megha Pandey, Mrinal Kanti Roychowdhury Jan 2024

Conditional Constrained And Unconstrained Quantization For Probability Distributions, Megha Pandey, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we present the idea of conditional quantization for a Borel probability measure P on a normed space Rk. We introduce the concept of conditional quantization in both constrained and unconstrained scenarios, along with defining the conditional quantization errors, dimensions, and coefficients in each case. We then calculate these values for specific probability distributions. Additionally, we demonstrate that for a Borel probability measure, the lower and upper quantization dimensions and coefficients do not depend on the conditional set of the conditional quantization in both constrained and unconstrained quantization.

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Structure Of Fine Selmer Groups In Abelian P-Adic Lie Extensions, Debanjana Kundu, Filippo Alberto Edoardo Nuccio Mortarino Majno Di Capriglio, Sujatha Ramdorai Jan 2024

Structure Of Fine Selmer Groups In Abelian P-Adic Lie Extensions, Debanjana Kundu, Filippo Alberto Edoardo Nuccio Mortarino Majno Di Capriglio, Sujatha Ramdorai

School of Mathematical & Statistical Sciences Faculty Publications

This paper studies fine Selmer groups of elliptic curves in abelian p -adic Lie extensions. A class of elliptic curves are provided where both the Selmer group and the fine Selmer group are trivial in the cyclotomic Z p -extension. The fine Selmer groups of elliptic curves with complex multiplication are shown to be pseudonull over the trivializing extension in some new cases. Finally, a relationship between the structure of the fine Selmer group for some CM elliptic curves and the Generalized Greenberg's Conjecture is clarified.

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Flow And Stability Of Three-Dimensional Rotating Viscoelastic Jet, Daniel N. Riahi Jan 2024

Flow And Stability Of Three-Dimensional Rotating Viscoelastic Jet, Daniel N. Riahi

School of Mathematical & Statistical Sciences Faculty Publications

We consider rotationally driven nonlinear viscoelastic jet. In contrast to previous unrealistic planar studies with no gravity effect, we investigate here realistic three-dimensional jet with gravity effect. Using theoretical and computational methods, we develop models for such jet and its stability and determine the solutions. We find three-dimensional jet with gravity effect leads to faster and thinner jet. For jet arc length higher than its exit diameter, our calculation with typical parameter values shows that jet radius is smaller by a factor of more than 1.4 and jet speed is higher by factor of more than 2 as are compared …

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Ivermectin, Colleen Aldous, Eleftherios Gkioulekas, Philip Oldfield Jan 2024

Ivermectin, Colleen Aldous, Eleftherios Gkioulekas, Philip Oldfield

School of Mathematical & Statistical Sciences Faculty Publications

No abstract provided.

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Enhanced Resolution Method For Electromagnetic Vortex Imaging Based On Electromagnetic Information Theory, Da Liu, Hongyin Shi, Ting Yang, Zhijun Qiao Jan 2024

Enhanced Resolution Method For Electromagnetic Vortex Imaging Based On Electromagnetic Information Theory, Da Liu, Hongyin Shi, Ting Yang, Zhijun Qiao

School of Mathematical & Statistical Sciences Faculty Publications

The electromagnetic vortex imaging possesses independent orbital angular momentum with orthogonal degrees of freedom (DoF), which implies the existence of enhanced information capacity. However, high-mode orbital angular momentum (OAM) beams have stringent generation conditions and inefficient information carrying capacity, which results in limited resolution. This paper proposes a method to combine the electromagnetic information theory (EIT) with the traditional electromagnetic vortex imaging technique, which allows one may obtain more target azimuth information. The DoF, as the main component of information, has been increased to achieve higher azimuth resolution. First, the propagation and imaging model for the electromagnetic vortex with statistical …

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Optimizing Energy Consumption In Smart Homes Using Ga-Lstm, Akibor Junior Chukwuka, Bakare-Bolaji Moyosoreoluwa, Baboucarr Dibba Jan 2024

Optimizing Energy Consumption In Smart Homes Using Ga-Lstm, Akibor Junior Chukwuka, Bakare-Bolaji Moyosoreoluwa, Baboucarr Dibba

School of Mathematical & Statistical Sciences Faculty Publications

The need to optimize energy consumption arises from the inadequate energy supply many homes face. However, to optimize energy consumption in a home, one must be equipped with the knowledge of the energy consumption rate and energy supply rate in the home. This paper proposed the use of a Long Short-Term Memory (LSTM) model optimized by Genetic Algorithm (GA) to optimize the energy consumption in a smart home. The model was designed using 8 input variables, which were observed weather information of a given region over a span of 350 days. The data set was split into a training data …

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Heuristics For Anti-Cyclotomic ℤp-Extensions, Debanjana Kundu, Lawrence C. Washington Jan 2024

Heuristics For Anti-Cyclotomic ℤp-Extensions, Debanjana Kundu, Lawrence C. Washington

School of Mathematical & Statistical Sciences Faculty Publications

This paper studies Iwasawa invariants in anti-cyclotomic towers. We do this by proposing two heuristics supported by computations. First we propose the Intersection Heuristics: these model “how often” the p-Hilbert class field of an imaginary quadratic field intersects the anti-cyclotomic tower and to what extent. Second we propose the Invariants Heuristics: these predict that the Iwasawa invariants 𝜆 and 𝜇 usually vanish for imaginary quadratic fields where p is non-split.

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2024 Viewbook, Office Of Admissions Jan 2024

2024 Viewbook, Office Of Admissions

Viewbook

At IMSA, you will be part of a community of 652 diverse students passionate about learning. Located in suburban Aurora, IMSA’s campus consists of seven residence halls spread across 97 acres. While living and learning on campus, you’ll make new friends, encounter new ideas, and learn to live independently. You will also have the opportunity to explore over 85 clubs, organizations, and IHSAsponsored co-curricular and athletic programs. IMSA provides a safe, nurturing environment. Professional Resident Counselors (RCs) live in each hall and will help you navigate your home away from home through the Residential Life Curriculum. Through this curriculum, you’ll …

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Riemannian Frameworks For The Harmonization Of Resting-State Functional Mri Scans, Nicolas Honnorat, Sudha Seshadri, Ron Killiany, John Blangero, David C. Glahn, Peter T. Fox, Mohamad Habes Jan 2024

Riemannian Frameworks For The Harmonization Of Resting-State Functional Mri Scans, Nicolas Honnorat, Sudha Seshadri, Ron Killiany, John Blangero, David C. Glahn, Peter T. Fox, Mohamad Habes

School of Medicine Publications

Magnetic Resonance Imaging provides unprecedented images of the brain. Unfortunately, scanners and acquisition protocols can significantly impact MRI scans. The development of statistical methods able to reduce this variability without altering the relevant information in the scans, often coined harmonization methods, has been the topic of an increasing research effort supported by the recent growth of publicly available neuroimaging data sets and new possibilities for combining them to achieve greater statistical power. In this work, we focus on the challenges specifically raised by the harmonization of resting-state functional MRI scans. We propose to harmonize resting-state fMRI scans by reducing the …

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A Survey On Artificial Intelligence In Cybersecurity For Smart Agriculture: State-Of-The-Art, Cyber Threats, Artificial Intelligence Applications, And Ethical Concerns, Guma Ali, Maad M. Mijwil, Bosco Apparatus Buruga, Mostafa Abotaleb, Ioannis Adamopoulos Jan 2024

A Survey On Artificial Intelligence In Cybersecurity For Smart Agriculture: State-Of-The-Art, Cyber Threats, Artificial Intelligence Applications, And Ethical Concerns, Guma Ali, Maad M. Mijwil, Bosco Apparatus Buruga, Mostafa Abotaleb, Ioannis Adamopoulos

Mesopotamian Journal of Computer Science

Wireless sensor networks and Internet of Things devices are revolutionizing the smart agriculture industry by increasing production, sustainability, and profitability as connectivity becomes increasingly ubiquitous. However, the industry has become a popular target for cyberattacks. This survey investigates the role of artificial intelligence (AI) in improving cybersecurity in smart agriculture (SA). The relevant literature for the study was gathered from Nature, Wiley Online Library, MDPI, ScienceDirect, Frontiers, IEEE Xplore Digital Library, IGI Global, Springer, Taylor & Francis, and Google Scholar. Of the 320 publications that fit the search criteria, 180 research papers were ultimately chosen for this investigation. The review …

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Segment Anything: A Review, Firas Hazzaa, Innocent Udoidiong, Akram Qashou, Sufian Yousef Jan 2024

Segment Anything: A Review, Firas Hazzaa, Innocent Udoidiong, Akram Qashou, Sufian Yousef

Mesopotamian Journal of Computer Science

Segment Anything (SA) is a state-of-the art method for universal object segmentation, which does not need task-specific training. Herein, we emphasize that SA can overcome the limitations of traditional segmentation frameworks based on requiring extensive manually annotated datasets and predefined architectures, as extensively documented in this review. SB supercharges performance and reduces cost by combining Mutual Information learning with an Efficient Transformer architecture, benefiting from a substantially larger pool of in-the-wild data. In this paper we review SA and its specific key innovations generality, resource boundedness, and scalability to large datasets. We also face obstacles such as data biases, computational …

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An Optimized Model For Liver Disease Classification Based On Bpso Using Machine Learning Models, El-Sayed M. El-Kenawy, Nima Khodadadi, Abdelhameed Ibrahim, Marwa M. Eid, Ahmed M. Osman, Ahmed M. Elshewey Jan 2024

An Optimized Model For Liver Disease Classification Based On Bpso Using Machine Learning Models, El-Sayed M. El-Kenawy, Nima Khodadadi, Abdelhameed Ibrahim, Marwa M. Eid, Ahmed M. Osman, Ahmed M. Elshewey

Mesopotamian Journal of Computer Science

Liver disease (LD) is a world health concern that requires accurate diagnostic methods. This study proposes an optimized machine learning model (ML) based on BPSO for LD classification using a shared public dataset from kaggle Indicates to liver patients from India. The paper used six ML models such as Random Forest (RF), Support Vector Machine (SVM), Dummy Classifier (DC), Extra Trees Classifier (ET), K-Nearest Neighbors (KNN), and Logistic Regression (LT) to evaluate the performance. Through observations we detected that ET achieved an accuracy of 79.82%. The BPSO hyperparameter optimization optimized ET to enhance accuracy to reach 85%. The paper used …

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Machine Learning Techniques To Predictive In Healthcare: Hepatitis C Diagnosis, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi Jan 2024

Machine Learning Techniques To Predictive In Healthcare: Hepatitis C Diagnosis, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi

Mesopotamian Journal of Artificial Intelligence in Healthcare

The accurate prediction and classification of medical data, such as Hepatitis C, play a significant role in upgrading symptomatic accuracy and treatment planning. This study utilized progressed machine learning algorithms, including RF, SVR, and Gradient Boosting, to analyze features and predict outcomes viably. By coordination robust preprocessing strategies and feature engineering, the models tended to missing values and categorical transformations, enabling exact predictions from complex datasets. The models accomplished high accuracy and unwavering quality in execution, as prove by comparative measurements and validation results. These discoveries highlight the potential of machine learning in increasing clinical decision-making and emphasize the require …

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Hybrid Model Approaches For Accurate Time Series Predicting Of Covid-19 Cases, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Benson Turyasingura Jan 2024

Hybrid Model Approaches For Accurate Time Series Predicting Of Covid-19 Cases, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Benson Turyasingura

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study compares the performance of ARIMA, LSTM, and hybrid models in predicting COVID-19 cases and analyzing forecast errors. Utilizing real-world data, the models were assessed for accuracy and trend prediction over numerous months. Heatmaps of prediction errors revealed that the hybrid model reliably outperformed ARIMA and LSTM by accomplishing lower error extents. The findings highlight the preferences of combining statistical and deep learning approaches for time series predicting. The results contribute to progressing predicting accuracy, which is basic for pandemic response arranging and public health administration.

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A Comprehensive Review On Cryptographic Techniques For Securing Internet Of Medical Things: A State-Of-The-Art, Applications, Security Attacks, Mitigation Measures, And Future Research Direction, Wamusi Robert, Asiku Denis, Adebo Thomas, Aziku Samuel, Simon Peter Kabiito, Zaward Morish, Guma Ali Jan 2024

A Comprehensive Review On Cryptographic Techniques For Securing Internet Of Medical Things: A State-Of-The-Art, Applications, Security Attacks, Mitigation Measures, And Future Research Direction, Wamusi Robert, Asiku Denis, Adebo Thomas, Aziku Samuel, Simon Peter Kabiito, Zaward Morish, Guma Ali

Mesopotamian Journal of Artificial Intelligence in Healthcare

As healthcare becomes increasingly dependent on the Internet of Medical Things (IoMT) infrastructure, it is essential to establish a secure system that guarantees the confidentiality and privacy of patient data. This system must also facilitate the secure sharing of healthcare information with other parties within the healthcare ecosystem. However, this increased connectivity also introduces cybersecurity attacks and vulnerabilities. This comprehensive review explores the state-of-the-art in the IoMT, security requirements in the IoMT, cryptographic techniques in the IoMT, application of cryptographic techniques in securing the IoMT, security attacks on cryptographic techniques, mitigation strategies, and future research directions. The study adopts a …

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Cross-Temporal Hierarchical Forecast Reconciliation Of Natural Gas Demand, Colin O. Quinn, George F. Corliss, Richard J. Povinelli Jan 2024

Cross-Temporal Hierarchical Forecast Reconciliation Of Natural Gas Demand, Colin O. Quinn, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction …

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Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer Jan 2024

Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer

Research outputs 2022 to 2026

Hydrogen is a clean fuel that can potentially completely decarbonize the energy supply chain and mitigate global warming. Hydrogen – a highly volatile gas – however, needs to be separated from CO2 during H2 production, and also from cushion gas in H2 geo-storage projects; in addition, large-scale H2 storage is a key obstacle. We thus tested and chemically upgraded common sub-bituminous coal as a material for H2-CO2 separation and H2 storage. The coal adsorbed significant amounts of H2 and CO2 and demonstrated an excellent H2-CO2 separation efficiency if chemically modified. The work presented here thus provides fundamental data required for …

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On Design Load Prediction And Extreme Response Modelling Of Floating Offshore Renewable Energy Structures, Tom Tosdevin Jan 2024

On Design Load Prediction And Extreme Response Modelling Of Floating Offshore Renewable Energy Structures, Tom Tosdevin

School of Engineering, Computing and Mathematics Theses

FLOATING offshore renewable energy (FORE) is a marginal industry and as such cost reductions are essential in order for it to become competitive with other forms of electricity generation. Design practices for evaluating the extreme responses of FORE devices are still under consideration by standards authorities, thus methods that enable potential speeding up of the design and development phases, particularly physical model testing are needed. Probabilistic design approaches have proved effective in bringing down costs in the aerospace and automobile industries and so provide a potential route to viability by allowing partial safety factors to be reduced. However, the scarcity …

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Investigation And Modelling Of A Cortical Learning Algorithm In The Neocortex, Damir Dobric Jan 2024

Investigation And Modelling Of A Cortical Learning Algorithm In The Neocortex, Damir Dobric

School of Engineering, Computing and Mathematics Theses

Many algorithms today provide a good machine learning solution in the specific problem domain, like pattern recognition, clustering, classification, sequence learning, image recognition, etc. They are all suitable for solving some particular problem but are limited regarding flexibility. For example, the algorithm that plays Go cannot do image classification, anomaly detection, or learn sequences. Inspired by the functioning of the neocortex, this work investigates if it is possible to design and implement a universal algorithm that can solve more complex tasks more intelligently in the way the neocortex does. Motivated by the remarkable replication degree of the same and similar …

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Strategic Alignment, Performance, And The Moderating Effect Of Regulatory Fit, Hayden T. Gunnell, Steven D. Smith, Travis W. Steadman Jan 2024

Strategic Alignment, Performance, And The Moderating Effect Of Regulatory Fit, Hayden T. Gunnell, Steven D. Smith, Travis W. Steadman

Faculty Publications

We examine how the alignment of performance measurement and strategy affects performance on a multidimensional task. Our experiment varies both the strategy (speed versus accuracy) of the hypothetical firm for which participants work and the individual performance measure that is reported to them, creating two conditions of clear alignment and two of clear misalignment. We find that while workers are responsive to the performance measure regardless of its alignment, they are also sensitive to the strategy such that costly alignment effects are observed. We also predict and find that workers respond asymmetrically to misalignment in accuracy performance but not in …

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Zno Varistors—Preparation Of Nano And Micro Sized Powders By Mechanical Methods For Low And High Voltage Varistors, Maura Kelleher Jan 2024

Zno Varistors—Preparation Of Nano And Micro Sized Powders By Mechanical Methods For Low And High Voltage Varistors, Maura Kelleher

Books/Book Chapters

ZnO-Bi2O3-Sb2O3 varistors are as essential today as they have been since their discovery five decades ago. Their role is to protect other electronic components against oncoming surges of electrons and survive. The demands on varistors are increasing. Electronic components are becoming smaller and more sensitive, and the metal oxides from which varistors are made are precious. Every aspect of their structure (macro, micro, nano and atomic) determines how they perform and survive. Each stage and variable within the powder metallurgy process is important. The mechanical methods in preparing nano and micro sized metal oxide powders are outlined in this chapter.

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Influence Of Seasonality And Public-Health Interventions On The Covid-19 Pandemic In Northern Europe, Gerry A. Quinn, Michael Connolly, Norman E. Fenton, Steven J. Hatfill, Paul Hynds, Coilín Óhaiseadha, Karol Sikora, Willie Soon, Ronan Connolly Jan 2024

Influence Of Seasonality And Public-Health Interventions On The Covid-19 Pandemic In Northern Europe, Gerry A. Quinn, Michael Connolly, Norman E. Fenton, Steven J. Hatfill, Paul Hynds, Coilín Óhaiseadha, Karol Sikora, Willie Soon, Ronan Connolly

Articles

Background: Most government efforts to control the COVID-19 pandemic revolved around non-pharmaceutical interventions (NPIs) and vaccination. However, many respiratory diseases show distinctive seasonal trends. In this manuscript, we examined the contribution of these three factors to the progression of the COVID-19 pandemic. Methods: Pearson correlation coefficients and time-lagged analysis were used to examine the relationship between NPIs, vaccinations and seasonality (using the average incidence of endemic human beta-coronaviruses in Sweden over a 10-year period as a proxy) and the progression of the COVID-19 pandemic as tracked by deaths; cases; hospitalisations; intensive care unit occupancy and testing positivity rates in six …

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Structure-Function Relationship Of Oat Flour Fractions When Blended With Wheat Flour: Instrumental And Nutritional Quality Characterization Of Resulting Breads, Mahmoud Said Rashed, Milica Pojić, Ciara Mcdonagh, Eimear Gallagher, Jesus M. Frias, Shivani Pathania Jan 2024

Structure-Function Relationship Of Oat Flour Fractions When Blended With Wheat Flour: Instrumental And Nutritional Quality Characterization Of Resulting Breads, Mahmoud Said Rashed, Milica Pojić, Ciara Mcdonagh, Eimear Gallagher, Jesus M. Frias, Shivani Pathania

Articles

Abstract: The present work investigated the structure-function relationship of dry fractionated oat flour (DFOF) as a techno-functional ingredient using bread as a model system. Mechanically, DFOF fractions (F), that is, F1: <224 µm, F2: 250–280 µm, F3: 280–500 µm, F4: 500–600 µm, and whole oat flour (F5) were blended with white wheat flour at 10%, 30%, and 50% substitution levels for bread making. The blended flours, doughs, and bread samples were assessed for their techno-functional, nutritional, and structural characteristics. The results of Mixolab and the Rapid Visco Analyzer show that the 50% substituted F3 fraction exhibits the highest water absorption properties (69.53%), whereas the 50% F1 fraction exhibits the highest peak viscosity of the past slurry. Analysis of bread samples revealed a lower particle size of DFOF fractions and higher supplementation levels, increased β-glucan levels (0.13–1.29 g/100 bread (db), reduced fermentable monosaccharides, that is, glucose (1.44–0.33 g/100 g), and fructose (1.06–0.28 g/100 g). The effect of particle size surpassed the substitution level effect on bread volume reduction. The lowest hardness value for F1 is 10%, and the highest value for F2 is 50%. The total number of cells in the bread slice decreased from the control to the F4 fraction (50%). Multi-criteria analysis indicated that DFOF fractions produced breads with similar structure and higher nutritional value developed from white wheat flour. Practical Application: The use of mechanically fractionated oat flours fractions in white wheat flour breads can improve the nutritional profile without affecting the physical properties of the bread product. Based on the oat flour fractions, bakers and food processing companies can tailor the bread formulations for high β-glucan, high fiber, and low reduced sugar claims.

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Review Of Computational Models For Large-Scale Mdao Of Urban Air Mobility Concepts, Darshan Sarojini, Marius L. Ruh, Jiayao Yan, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Han Zhao, Joshua J. Krokowski, Michael Warner, Sebastiaan Pc Van Schie, Ashley Cronk, Alexandre T. R. Guibert, Jeffrey T. Chambers, Lauren Wolfe, Rachel Doring, Robin Despins, Cibin Joseph, Ryan Anderson, Andrew Ning, Hyunjune Gill, Seongkyu Lee, Zeyu Cheng, Zhi Cao, Chunting Mi, Y Shirley Meng, Christopher Silva, Jiun-Shyan Chen, H. Alicia Kim, John T. Hwang Jan 2024

Review Of Computational Models For Large-Scale Mdao Of Urban Air Mobility Concepts, Darshan Sarojini, Marius L. Ruh, Jiayao Yan, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Han Zhao, Joshua J. Krokowski, Michael Warner, Sebastiaan Pc Van Schie, Ashley Cronk, Alexandre T. R. Guibert, Jeffrey T. Chambers, Lauren Wolfe, Rachel Doring, Robin Despins, Cibin Joseph, Ryan Anderson, Andrew Ning, Hyunjune Gill, Seongkyu Lee, Zeyu Cheng, Zhi Cao, Chunting Mi, Y Shirley Meng, Christopher Silva, Jiun-Shyan Chen, H. Alicia Kim, John T. Hwang

Faculty Publications

The advent of Urban Air Mobility (UAM) has necessitated a paradigm shift in aircraft design from traditional regression methods to physics-based analysis and the use of modern computational methods. This paper explores the intricacies of UAM aircraft design, acknowledging the limitations of historical empirical equations and advocating for the use of physics-based tools in the early stages of the design process. It underscores the importance of Multidisciplinary Design, Analysis, and Optimization (MDAO) as a means to integrate physics-based tools for conceptual design, facilitating decisions on configuration and sizing. The paper presents a comprehensive survey and review of computational models across …

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Learning From Secondary Blended Teaching Practitioners: Selecting Activities And Connecting In-Person And Online Learning, Michelle Jensen, Charles R. Graham, Cecil R. Short Jan 2024

Learning From Secondary Blended Teaching Practitioners: Selecting Activities And Connecting In-Person And Online Learning, Michelle Jensen, Charles R. Graham, Cecil R. Short

Faculty Publications

Implementation of blended teaching (BT) practices is increasing rapidly in K-12 classrooms. This trend creates an urgent need for professional development to support BT. An understanding of how experienced teachers implement BT can inform teacher educators and professional development leaders as they develop training to support this practice. We interviewed 24 secondary educators implementing BT strategies to determine what activities they include in the online space and how they connect them to in-person learning. Qualitative thematic analysis of the interviews revealed that experienced blended teachers used a variety of online activities, providing opportunities for learners to interact with content, other …

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Chatbots Mitigate Help-Seeking Avoidance, James Gaskin, Eva Blondeel, Ryan Schuetzler, Rachel Serre, Jacob Steffen, David A. Wood Jan 2024

Chatbots Mitigate Help-Seeking Avoidance, James Gaskin, Eva Blondeel, Ryan Schuetzler, Rachel Serre, Jacob Steffen, David A. Wood

Faculty Publications

This research explores the transformative role of large language model (LLM) chatbots in fostering help-seeking behaviors among introverted and underrepresented students in educational settings. Despite the importance of help-seeking for academic success, certain groups exhibit avoidance behaviors due to self-presentation concerns and stereotype threats. By integrating LLM chatbots as non-judgmental, anonymous teaching assistants in an introductory information systems course, the study demonstrates how technology can mitigate these behaviors and promote inclusivity. The chatbots provided real-time, unbiased support, significantly enhancing the students' willingness to engage in help-seeking behaviors without fear of judgment. This practical application of chatbots not only supports academic …

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Development Of Realistic Hazard Scenarios In A Malaysian Driving Simulator For Education, Cheng Yun Quan, Sarina Mansor, Chin Ji Jian, Hezerul Abdul Karim, Ban Kar Weng Jan 2024

Development Of Realistic Hazard Scenarios In A Malaysian Driving Simulator For Education, Cheng Yun Quan, Sarina Mansor, Chin Ji Jian, Hezerul Abdul Karim, Ban Kar Weng

School of Engineering, Computing and Mathematics

In this paper, we present the development of a driving education prototype simulator, aiming to address dangerous traffic situations frequently encountered in daily life, particularly in urban areas like Klang Valley, Malaysia. Our initial driving simulator version focused on track-based training tailored to Malaysian driving exams, but we recognized its limitations in preparing learner drivers for real-world challenges due to the lack of risk. To add the value of study to our project, we designed three scenarios based on common dangerous situations observed in dashboard camera (dashcam) footage from Malaysian drivers. Due to the lack of reliable openly discussed methods …

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Wave Energy Extraction From Rigid Rectangular Compound Floating Plates, S. Michele, S. Zheng, E. Renzi, J. Guichard, A. G.L. Borthwick, D. M. Greaves Jan 2024

Wave Energy Extraction From Rigid Rectangular Compound Floating Plates, S. Michele, S. Zheng, E. Renzi, J. Guichard, A. G.L. Borthwick, D. M. Greaves

School of Engineering, Computing and Mathematics

We present a theoretical model to analyse the hydrodynamics of wave energy converters (WECs) comprised of three-dimensional, rigid, floating, compound rectangular plates in the open sea. The hydrodynamic problem is solved by means of Green's theorem and a free-surface Green's function. Plate motion is predicted through decomposition into rigid natural modes. We first analyse the case of a single rectangular plate and validate our model against experimental results from physical model tests undertaken in the COAST laboratory at the University of Plymouth. Then we extend our theory to complex shapes and arrays of plates and examine how the geometry, incident …

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Modelling Reservoir Sediment Flushing Through A Bottom Tunnel With An Initially Covered Intake, Yining Sun, Ji Li, Zhixian Cao, Jinxin Liu, Huan Xu, Alistair G.L. Borthwick Jan 2024

Modelling Reservoir Sediment Flushing Through A Bottom Tunnel With An Initially Covered Intake, Yining Sun, Ji Li, Zhixian Cao, Jinxin Liu, Huan Xu, Alistair G.L. Borthwick

School of Engineering, Computing and Mathematics

Sediment flushing through a bottom tunnel is one of the most effective methods to alleviate reservoir sedimentation. However, the multi-physical hydro-sediment-morphological processes of reservoir sediment flushing through an initially covered bottom tunnel intake have remained poorly understood, and a physically enhanced and practically viable mathematical model is required. The present study uses an integrated model to resolve sediment flushing through an initially covered bottom tunnel intake. The proposed model couples a two-dimensional double layer-averaged model for the reservoir with a one-dimensional model for the bottom tunnel by means of numerical fluxes calculations at the inner boundary. The governing equations are …

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Nonlinear Spatial Evolution Of Degenerate Quartets Of Water Waves, Conor Heffernan, Amin Chabchoub, Raphael Stuhlmeier Jan 2024

Nonlinear Spatial Evolution Of Degenerate Quartets Of Water Waves, Conor Heffernan, Amin Chabchoub, Raphael Stuhlmeier

School of Engineering, Computing and Mathematics

In this manuscript we investigate the Benjamin–Feir (or modulation) instability for the spatial evolution of water waves from the perspective of the discrete, spatial Zakharov equation, which captures cubically nonlinear and resonant wave interactions in deep water without restrictions on spectral bandwidth. Spatial evolution, with measurements at discrete locations, is pertinent for laboratory hydrodynamic experiments, such as in wave flumes, which rely on time-series measurements at fixed gauges installed along the facility. This setting is likewise appropriate for experiments in electromagnetic and plasma waves. Through a reformulation of the problem for a degenerate quartet, we bring to bear techniques of …

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