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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 2024 American Institutes for Research

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 …


The Aim To Decentralize Economic Systems With Blockchains And Crypto, Mary Lacity 2024 The Sam M. Walton College of Business at the University of Arkansas

The Aim To Decentralize Economic Systems With Blockchains And Crypto, Mary Lacity

Arkansas Law Review

As an information systems (“IS”) professor, I wrote this Article for legal professionals new to blockchains and crypto. This target audience likely is most interested in crypto for its legal implications—depending on whether it functions as currencies, securities, commodities, or properties; however, legal professionals also need to understand crypto’s origin, how transactions work, and how they are governed.


Piecing Together Performance: Collaborative, Participatory Research-Through-Design For Better Diversity In Games, Daniel L. Gardner, LouAnne Boyd, Reginald T. Gardner 2024 Chapman University

Piecing Together Performance: Collaborative, Participatory Research-Through-Design For Better Diversity In Games, Daniel L. Gardner, Louanne Boyd, Reginald T. Gardner

Engineering Faculty Articles and Research

Digital games are a multi-billion-dollar industry whose production and consumption extend globally. Representation in games is an increasingly important topic. As those who create and consume the medium grow ever more diverse, it is essential that player or user-experience research, usability, and any consideration of how people interface with their technology is exercised through inclusive and intersectional lenses. Previous research has identified how character configuration interfaces preface white-male defaults [39, 40, 67]. This study relies on 1-on-1 play-interviews where diverse participants attempt to create “themselves” in a series of games and on group design activities to explore how participants may …


Weed Seed Wizard Case Study - An Early Harvest Versus A Late Harvest, Department of Primary Industries and Regional Development, Western Australia 2024 Department of Primary Industries and Regional Development, Western Australia

Weed Seed Wizard Case Study - An Early Harvest Versus A Late Harvest, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity research reports

The Weed Seed Wizard is a national collaborative project that uses paddock management information to predict weed emergence and crop losses now and in the future.

The Weed Seed Wizard is a computer simulation tool that:

  • applies to all Australian grain growing areas
  • helps growers understand and manage weed seedbanks on their farms
  • uses farm management records to simulate how different crop rotations, weed control techniques, irrigation, grazing and harvest management tactics can affect weed numbers, the weed seedbank and yields
  • uses farm-specific management and site-specific weather
  • is multi-species

See www.dpird.wa.gov.au for further information on Weed Seed Wizard.

This case …


Weed Seed Wizard Scenario - Herbicide Resistance In Wild Radish In Moora, Western Australia, Department of Primary Industries and Regional Development, Western Australia 2024 Department of Primary Industries and Regional Development, Western Australia

Weed Seed Wizard Scenario - Herbicide Resistance In Wild Radish In Moora, Western Australia, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity research reports

The Weed Seed Wizard is a national collaborative project that uses paddock management information to predict weed emergence and crop losses now and in the future.

The Weed Seed Wizard is a computer simulation tool that:

  • applies to all Australian grain growing areas
  • helps growers understand and manage weed seedbanks on their farms
  • uses farm management records to simulate how different crop rotations, weed control techniques, irrigation, grazing and harvest management tactics can affect weed numbers, the weed seedbank and yields
  • uses farm-specific management and site-specific weather
  • is multi-species

See www.dpird.wa.gov.au for further information on Weed Seed Wizard.

This Western …


Leveraging Software Testing Techniques To Explain, Analyze, And Debug Machine Learning Models, Sunny Shree 2024 University of Texas at Arlington

Leveraging Software Testing Techniques To Explain, Analyze, And Debug Machine Learning Models, Sunny Shree

Computer Science and Engineering Dissertations - Archive

Machine learning (ML) algorithms are changing many aspects of modern life by analyzing data, identifying patterns, and making predictive decisions across industries such as healthcare, transportation, finance, and e-commerce. However, ML models often operate as "black boxes," making it difficult to interpret their decision-making processes. This lack of transparency creates challenges in testing, debugging, and understanding model behavior, which affects user trust and raises concerns about trustworthiness, accountability, reliability, and fairness in high-stakes applications.

Explainable Artificial Intelligence (XAI) aims to address these challenges by providing tools and methods that explain the decision-making processes of ML models in a way that …


Github Uncovered: Revealing The Social Fabric Of Software Development Communities, Abduljaleel Al Rubaye 2024 University of Central Florida

Github Uncovered: Revealing The Social Fabric Of Software Development Communities, Abduljaleel Al Rubaye

Graduate Thesis and Dissertation 2023-2024

The proliferation of open-source software development platforms has given rise to various online social communities where developers can seamlessly collaborate, showcase their projects, and exchange knowledge and ideas. GitHub stands out as a preeminent platform within this ecosystem. It offers developers a space to host and disseminate their code, participate in collaborative ventures, and engage in meaningful dialogues with fellow community members. This dissertation embarks on a comprehensive exploration of various facets of software development communities on GitHub, with a specific focus on innovation diffusion, repository popularity dynamics, code quality enhancement, and user commenting behaviors. This dissertation introduces a popularity-based …


Improving The Accuracy Of Software Models Using Refinement And Mutation Testing, Ana Jovanovic 2024 University of Texas at Arlington

Improving The Accuracy Of Software Models Using Refinement And Mutation Testing, Ana Jovanovic

Computer Science and Engineering Dissertations - Archive

Writing correct software models is important in today’s society. Unfortunately, software development is an error-prone task that frequently leads to buggy software. That is why users, both novices and experts, make use of additional techniques and tools to make software more reliable and correct. One of the languages that proposes a solution to this is Alloy. Alloy is a declarative language based on first order logic. Its main advantage is the ability to describe complex systems using concise formal logic. To verify the model and its properties, Alloy uses the Alloy Analyzer, an SAT-based verification tool that supports fully automatic …


A 3-Step, Open-Data, Ride-Hailing Ridership Model With Pricing Applications, Richard A. Mucci 2024 University of Kentucky

A 3-Step, Open-Data, Ride-Hailing Ridership Model With Pricing Applications, Richard A. Mucci

Theses and Dissertations--Civil Engineering

Researchers and practitioners studied the effects ride-hailing had in cities before the covid-19 pandemic. Previous research found ride-hailing to produce negative externalities, such as reducing transit ridership and increasing congestion in various cities. Since the pandemic, ride-hailing ridership has nearly recovered to pre-pandemic levels in Chicago. Ride-hailing ridership has grown steadily since the pandemic while a rider’s willingness to share their trip stagnated. Ride-hailing ridership nearly recovering to pre-covid levels in Chicago suggests that transportation planners, and policy makers, will need to continue assessing the impacts ride-hailing trips have in their cities.

Pickup and drop off locations in the Chicago …


Cyclistai: A Smartphone Solution For Cyclist Stress Assessment Using Deep Learning, Aairish Singh 2024 University of Texas at Arlington

Cyclistai: A Smartphone Solution For Cyclist Stress Assessment Using Deep Learning, Aairish Singh

Computer Science and Engineering Theses - Archive

Cycling presents a compelling solution for promoting personal health and environmental well-being, particularly for short-distance travel. Despite its numerous advantages, cycling uptake in the United States remains disproportionately low, primarily due to safety concerns. Traditional frameworks for assessing cyclist stress are hindered by their impracticality and inability to provide real-time evaluations. Self-report surveys and physiological measurements offer alternative approaches but suffer from limitations such as retrospective reporting biases and accessibility challenges, respectively. This thesis introduces CyclistAI, a novel smartphone-based cyclist stress assessment model that leverages context sensing. By combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) techniques, CyclistAI …


Development Of A Collaborative Research Platform For Efficient Data Management And Visualization Of Qubit Control, Devanshu Brahmbhatt 2024 University of Texas at Arlington

Development Of A Collaborative Research Platform For Efficient Data Management And Visualization Of Qubit Control, Devanshu Brahmbhatt

Computer Science and Engineering Theses - Archive

This thesis introduces QubiCSV, a pioneering open-source platform for quantum computing field. With an emphasis on collaborative research, QubiCSV addresses the critical need for specialized data management and visualization tools in qubit control. The platform is crafted to overcome the challenges posed by the high costs and complexities associated with quantum experimental setups. It emphasizes efficient utilization of resources through shared ideas, data, and implementation strategies. One of the primary obstacles in quantum computing research has been the ineffective management of extensive calibration data and the inability to visualize complex quantum experiment outcomes effectively. QubiCSV fills this gap by offering …


Escape The Planet: Revolutionizing Game Design With Novel Oop Techniques, Qusai Kamal Fannoun 2024 Minnesota State University, Mankato

Escape The Planet: Revolutionizing Game Design With Novel Oop Techniques, Qusai Kamal Fannoun

All Graduate Theses, Dissertations, and Other Capstone Projects

Mobile devices are continuously evolving and greater computing power and graphics capabilities are being introduced every year. As a result, there is an increasing demand for challenging and engaging mobile games that leverage these advanced features. This project explores best design practices using the development of Escape the Planet, which is an intricate maze game for mobile devices in which players navigate using a spaceship that is trapped in a hostile planet’s maze while avoiding obstacles and enemy attacks. The goal is to safely guide the spaceship out of the maze without colliding into walls or taking bullets from defensive …


A Secure And Privacy-Preserving Signature Protocol Using Quantum Teleportation In Metaverse Environment, Pankaj Kumar, Vivek Bharmaik, Sunil Prajapat, Garima Thakur, Ashok Kumar Das, Sachin Shetty, Joel J. P. C. Rodrigues 2024 Central University of Himachal Pradesh

A Secure And Privacy-Preserving Signature Protocol Using Quantum Teleportation In Metaverse Environment, Pankaj Kumar, Vivek Bharmaik, Sunil Prajapat, Garima Thakur, Ashok Kumar Das, Sachin Shetty, Joel J. P. C. Rodrigues

VMASC Publications

The burgeoning concept of the metaverse as an interconnected virtual space represents the forefront of the next-generation internet. Quantum teleportation, known for its prowess in ensuring secure and reliable communications, stands poised to revolutionize interactions within this immersive digital realm. In this context, we propose a comprehensive interaction protocol tailored for the metaverse environment. The designed protocol entails two fundamental components: first, the interaction between a user and their avatar, facilitated by a secure seven-qubit entangled state; and second, the interaction between two avatars, enabled through an efficient two-qubit entangled state. To fortify the protocol’s resilience, quantum key distribution (QKD) …


Designing A Blockchain-Empowered Telehealth Artifact For Decentralized Identity Management And Trustworthy Communication: Interdisciplinary Approach, Xueping Liang, Nabid Alam, Tahmina Sultana, Eranga Bandara, Sachin Shetty 2024 Florida International University

Designing A Blockchain-Empowered Telehealth Artifact For Decentralized Identity Management And Trustworthy Communication: Interdisciplinary Approach, Xueping Liang, Nabid Alam, Tahmina Sultana, Eranga Bandara, Sachin Shetty

VMASC Publications

Background: Telehealth played a critical role during the COVID-19 pandemic and continues to function as an essential component of health care. Existing platforms cannot ensure privacy and prevent cyberattacks.

Objective: The main objectives of this study are to understand existing cybersecurity issues in identity management and trustworthy communication processes in telehealth platforms and to design a software architecture integrated with blockchain to improve security and trustworthiness with acceptable performance.

Methods: We improved personal information security in existing telehealth platforms by adopting an innovative interdisciplinary approach combining design science, social science, and computer science in the health care domain, with prototype …


Language Models For Rare Disease Information Extraction: Empirical Insights And Model Comparisons, Shashank Gupta 2024 University of Kentucky

Language Models For Rare Disease Information Extraction: Empirical Insights And Model Comparisons, Shashank Gupta

Theses and Dissertations--Computer Science

End-to-end relation extraction (E2ERE) is a crucial task in natural language processing (NLP) that involves identifying and classifying semantic relationships between entities in text. This thesis compares three paradigms for end-to-end relation extraction (E2ERE) in biomedicine, focusing on rare diseases with discontinuous and nested entities. We evaluate Named Entity Recognition (NER) to Relation Extraction (RE) pipelines, sequence-to-sequence models, and generative pre-trained transformer (GPT) models using the RareDis information extraction dataset. Our findings indicate that pipeline models are the most effective, followed closely by sequence-to-sequence models. GPT models, despite having eight times as many parameters, perform worse than sequence-to-sequence models and …


Integrating Arcgis And Redux Using Middleware, Vishnu Vardhan Reddy Rapuru 2024 Michigan Technological University

Integrating Arcgis And Redux Using Middleware, Vishnu Vardhan Reddy Rapuru

Dissertations, Master's Theses and Master's Reports

The integration of ArcGIS with Redux through middleware presents a novel approach to managing state in geospatial applications. This report outlines the process and benefits of combining ArcGIS’s robust mapping and analytics capabilities with Redux’s predictable state container for JavaScript apps. It begins with an introduction to both technologies, followed by a detailed discussion on the architecture design, focusing on the role of middleware as the linchpin in this integration[1]. The paper highlights the benefits, such as improved state management and application performance, and addresses the challenges encountered during the integration process. Implementation details are provided, including the setup of …


Weed Seed Wizard Scenario - Glyphosate Resistance In Barnyard Grass In Goondiwindi, Queensland, Department of Primary Industries and Regional Development, Western Australia 2024 Department of Primary Industries and Regional Development, Western Australia

Weed Seed Wizard Scenario - Glyphosate Resistance In Barnyard Grass In Goondiwindi, Queensland, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity research reports

The Weed Seed Wizard is a national collaborative project that uses paddock management information to predict weed emergence and crop losses now and in the future.

The Weed Seed Wizard is a computer simulation tool that:

  • applies to all Australian grain growing areas
  • helps growers understand and manage weed seedbanks on their farms
  • uses farm management records to simulate how different crop rotations, weed control techniques, irrigation, grazing and harvest management tactics can affect weed numbers, the weed seedbank and yields
  • uses farm-specific management and site-specific weather
  • is multi-species

See www.dpird.wa.gov.au for further information on Weed Seed Wizard.

This Queensland …


Embedding Software Engineering In Mixed Methods: Computationally Enhanced Risk Communication, Ann Marie Reinhold, Madison H. Munro, Elizabeth A. Shanahan, Ross J. Gore, Barry C. Ezell, Clemente I. Izurieta 2024 Montana State University

Embedding Software Engineering In Mixed Methods: Computationally Enhanced Risk Communication, Ann Marie Reinhold, Madison H. Munro, Elizabeth A. Shanahan, Ross J. Gore, Barry C. Ezell, Clemente I. Izurieta

VMASC Publications

Mixed methods research ameliorates many convergent research challenges within the contemporary sociotechnical landscape. We suggest the integration of software engineering in mixed methods studies is a critical step to address some of the remaining and persistent challenges. One such research challenge where software engineering is particularly well suited is in hazard preparedness—in particular, the creation of risk communication messages to mitigate or prevent harm. Computationally enhanced risk communication is convergent research that integrates software engineering and social science research for the benefit of protecting humans and infrastructure. To this end, we developed a mixed methods framework for the efficient construction …


A Self-Supervised Knowledge Distillation Approach To Anomaly Detection In X-Ray Imagery, Kaden Quinn McEldowney 2024 West Virginia University

A Self-Supervised Knowledge Distillation Approach To Anomaly Detection In X-Ray Imagery, Kaden Quinn Mceldowney

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many cargo containers enter the United States every day by truck, rail, and sea. As a result of the large number of cargo containers entering the United States, not all of them can be thoroughly inspected. Most of these containers contain properly documented and legal cargo, but some people take advantage of this situation by hiding illicit items in the cargo containers such as drugs. To more efficiently and thoroughly inspect cargo containers, Customs and Border Protection (CBP) uses X-ray imaging machines to obtain images that reveal the interior of cargo containers. These X-ray images must be inspected to ensure …


Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers 2024 Central Washington University

Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers

All Master's Theses

The development of electric vehicles is currently considered one of the most innovative areas in manufacturing. Largely driven by the desire to reduce greenhouse emissions, electric vehicles are seen as a viable alternative to internal combustion engine cars. Starting from consumer cars, a dedicated effort is being made to translate this into commercial vehicles for freight and delivery. This research introduces a novel adaptive Nawaz, Enscore, Ham (NEH) algorithm with constrained nearest neighbor subtour (NEH-NN). This algorithm is tested on the standard benchmark problems in literature and used as a seed solution for the Genetic Algorithm (GA). The performance and …


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