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Articles 1 - 15 of 15
Full-Text Articles in Physical Sciences and Mathematics
Social Justice Mathematics: Classroom Practices That Give Students Rigor While Building Agency, Emily Marquise
Social Justice Mathematics: Classroom Practices That Give Students Rigor While Building Agency, Emily Marquise
Masters Theses
The purpose of this study is to examine the impact of a social justice approach to mathematics instruction. While many students have math aversion, students in low socioeconomic communities exhibit this to a higher degree putting them at a disadvantage as they progress through their educational career. More than 3.4 million K-12 students in the United States come from families that earn less than the median income yet achieve scores in the top percentile (Wyner et al., 2007). This raises the question of why so many students in low-socioeconomic settings are not given rigorous content that will keep them competitive …
Targeting Macrophytes: Increased Water Quality Through Optimized Vegetation Considerations For Constructed Wetlands, Austin Mcbrady
Targeting Macrophytes: Increased Water Quality Through Optimized Vegetation Considerations For Constructed Wetlands, Austin Mcbrady
Masters Theses
This study of constructed wetland design investigated relationships between macrophyte species selection and planting density for water quality improvement. A lab-scale wetland was compared against a pilot-scale wetland in San Antonio, Texas at Mitchell Lake to measure differences in effluent water quality improvement using three native macrophyte species. Using a novel, two-phase method, a targeting macrophyte was identified from among other species based on its marked capability for improving water quality factors, then was planted in varied majority densities to compare differences in treatment effectiveness. The results of this study showed that this complimentary approach to wetland design displayed significant …
Perception Of Bias In Chatgpt: Analysis Of Social Media Data, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Ahmed El Noshokaty, Tareq Nasralah
Perception Of Bias In Chatgpt: Analysis Of Social Media Data, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Ahmed El Noshokaty, Tareq Nasralah
Computer Information Systems Faculty Publications
In this study, we aim to analyze the public perception of Twitter users with respect to the use of ChatGPT and the potential bias in its responses. Sentiment and emotion analysis were also analyzed. Analysis of 5,962 English tweets showed that Twitter users were concerned about six main types of biases, namely: political, ideological, data & algorithmic, gender, racial, cultural, and confirmation biases. Sentiment analysis showed that most of the users reflected a neutral sentiment, followed by negative and positive sentiment. Emotion analysis mainly reflected anger, disgust, and sadness with respect to bias concerns with ChatGPT use.
A Control Study Analysis Application Of Unoccupied Aerial Systems (Drones) To Monitor Eutrophication, Chrystal Mata
A Control Study Analysis Application Of Unoccupied Aerial Systems (Drones) To Monitor Eutrophication, Chrystal Mata
Water Resources Science and Technology Theses and Graduate Research Reports
Unmanned Aircraft systems (UAS) can offer a valuable perspective for detecting and monitoring for eutrophication in bodies of water by providing high-resolution images and data assignments for algal blooms and nutrient levels. Eutrophication, the process by which water bodies become enriched with nutrients, has emerged as a critical factor in evaluating and maintaining water quality. In this study, we use DJI Inspire Pro 1 equipped with a Zenmuse X3 camera, attached with a Parrot Sequoia multispectral sensor was used to in conjunction with algorithms to retrieve Chlorophyll parameters for monitoring eutrophication. Although water quality parameters such as pH, nitrate, phosphate, …
Trashed: A Review Of Anthropogenic Litter In An Urban Watershed, John D. Hamilton
Trashed: A Review Of Anthropogenic Litter In An Urban Watershed, John D. Hamilton
Water Resources Science and Technology Theses and Graduate Research Reports
Urban creeks, streams and rivers have become an unfortunate destination for trash pollution. Within an urban watershed trash pollution is harmful to fish, wildlife, public health, contributes to microplastic proliferation, and aesthetically tarnishes an otherwise unscathed ecosystem. With lots of attention focused on trash in marine and coastal ecosystems, this study aims to contribute to the growing research on inland urban watersheds and their involvement. This study highlights issues associated with trash pollution, and investigates the associated vectors, origins, behaviors, and contributing factors that create trash ladened urban watersheds. Datasets and site surveys from repeated trash cleanups in three creekside …
Recognition Of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, And Optical Character Recognition (Ocr) Techniques, Khalid Nahar, Izzat Alsmadi, Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Hasan Gharaibeh, Ali Saeed Almuflih, Fahad Alasim
Recognition Of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, And Optical Character Recognition (Ocr) Techniques, Khalid Nahar, Izzat Alsmadi, Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Hasan Gharaibeh, Ali Saeed Almuflih, Fahad Alasim
All Faculty Scholarship
Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its applications shows significant work in English and Chinese, while little research is conducted in other languages, such as Arabic. To fill this gap, we propose a hybrid model that combines feature extraction with deep learning models and then uses machine learning (ML) and optical character recognition (OCR) methods and applies grid and random search optimization algorithms to obtain …
Risk Assessment Of Urban Development In The Recharge Zone Of The Karstic Edwards Aquifer: A Literature Survey And Analysis, Julie Ybarra
Risk Assessment Of Urban Development In The Recharge Zone Of The Karstic Edwards Aquifer: A Literature Survey And Analysis, Julie Ybarra
Water Resources Science and Technology Theses and Graduate Research Reports
The Edwards Aquifer is a unique groundwater system and provides drinking water for millions of people in Central Texas. Central Texas has seen an increase in urban development across this region and poses a threat to its water supply and water quality. A literature review and an analysis of existing risk assessment frameworks was conducted to gather information about the Edwards Aquifer and other karst aquifers around the world. The information gathered from the literature review and analysis assisted in the development of the Edwards Aquifer Vulnerability Interface. This tool identifies vulnerable areas in the Edwards Aquifer and can strengthen …
U2-Net: A Very-Deep Convolutional Neural Network For Detecting Distracted Drivers, Nawaf Alsrehin, Mohit Gupta, Izzat Alsmadi, Saif Addeen Alrababah
U2-Net: A Very-Deep Convolutional Neural Network For Detecting Distracted Drivers, Nawaf Alsrehin, Mohit Gupta, Izzat Alsmadi, Saif Addeen Alrababah
All Faculty Scholarship
In recent years, the number of deaths and injuries resulting from traffic accidents has been increasing dramatically all over the world due to distracted drivers. Thus, a key element in developing intelligent vehicles and safe roads is monitoring driver behaviors. In this paper, we modify and extend the U-net convolutional neural network so that it provides deep layers to represent image features and yields more precise classification results. It is the basis of a very deep convolution neural network, called U2-net, to detect distracted drivers. The U2-net model has two paths (contracting and expanding) in addition to a fully-connected dense …
Self-Supervised Learning Application On Covid-19 Chest X- Ray Image Classification Using Masked Autoencoder, Xin Xing, Gongbo Liang, Chris Wang, Nathan Jacobs, Ai-Ling Lin
Self-Supervised Learning Application On Covid-19 Chest X- Ray Image Classification Using Masked Autoencoder, Xin Xing, Gongbo Liang, Chris Wang, Nathan Jacobs, Ai-Ling Lin
All Faculty Scholarship
The COVID-19 pandemic has underscored the urgent need for rapid and accurate diagnosis facilitated by artificial intelligence (AI), particularly in computer-aided diagnosis using medical imag- ing. However, this context presents two notable challenges: high diagnostic accuracy demand and limited availability of medical data for training AI models. To address these issues, we proposed the implementation of a Masked AutoEncoder (MAE), an innovative self-supervised learning approach, for classifying 2D Chest X-ray images. Our approach involved performing imaging reconstruction using a Vision Transformer (ViT) model as the feature encoder, paired with a custom-defined decoder. Additionally, we fine-tuned the pretrained ViT encoder using …
Identification Of Unsuccessful Students In General Chemistry, G. Robert Shelton, Joseph M. Simpson, Diana Mason
Identification Of Unsuccessful Students In General Chemistry, G. Robert Shelton, Joseph M. Simpson, Diana Mason
All Faculty Scholarship
The Networking for Science Advancement (NSA) team collected data from multiple general chemistry courses at nine universities within a broad geographic setting in a majority-minority US state. Data include diagnostic scores on the Math-Up Skills Test (MUST), quantitative literacy/quantitative reasoning (QL/QR) quiz, along with student demographics, and overall course grades. From these data the team determined how automaticity skills in procedural arithmetic and quantitative literacy and reasoning can be used to predict success in lower-division chemistry courses. By expanding this dataset, we extended our investigations to discover what characterizes successful and unsuccessful students in general chemistry, first and second semesters …
Predictability Of The Must (Math-Up Skills Test), Diana Mason, G. Robert Shelton
Predictability Of The Must (Math-Up Skills Test), Diana Mason, G. Robert Shelton
All Faculty Scholarship
In the USA for the most part, completion of a first-semester general chemistry (Chem I) course lays the foundation deemed necessary for understanding second-semester general chemistry (Chem II) topics. Successful completion of Chem I and II gives students permission to progress to organic chemistry I (O-Chem). A series of studies undertaken by the NSA (Networking for Science Advancement) Texas team began in 2016. Texas is one of five majority-minority states in the USA and hosts a significant Hispanic population. The purpose of this research line is to evaluate the influence of basic arithmetic automaticity (what students can do without a …
Detecting Ai Generated Text Using Neural Networks, Jesus Guerrero
Detecting Ai Generated Text Using Neural Networks, Jesus Guerrero
Masters Theses
For humans, distinguishing machine generated text from human written text is men- tally taxing and slow. NLP models have been created to do this more effectively and faster. But, what if some adversarial changes have been added to the machine generated text? This thesis discusses this issue and text detectors in general.
The primary goal of this thesis is to describe the current state of text detectors in research and to discuss a key adversarial issue in modern NLP transformers. To describe the current state of text detectors a Systematic Literature Review was done on 50 relevant papers to machine-centric …
Enhanced Convolutional Neural Network For Non-Small Cell Lung Cancer Classification, Yahya Tashtoush, Rasha Obeidat, Abdallah Al-Shorman, Omar Darwish, Mohammad A. Al-Ramahi, Dirar Darweesh
Enhanced Convolutional Neural Network For Non-Small Cell Lung Cancer Classification, Yahya Tashtoush, Rasha Obeidat, Abdallah Al-Shorman, Omar Darwish, Mohammad A. Al-Ramahi, Dirar Darweesh
Computer Information Systems Faculty Publications
Lung cancer is a common type of cancer that causes death if not detected
early enough. Doctors use computed tomography (CT) images to diagnose
lung cancer. The accuracy of the diagnosis relies highly on the doctor's
expertise. Recently, clinical decision support systems based on deep learning
valuable recommendations to doctors in their diagnoses. In this paper, we
present several deep learning models to detect non-small cell lung cancer in
CT images and differentiate its main subtypes namely adenocarcinoma,
large cell carcinoma, and squamous cell carcinoma. We adopted standard
convolutional neural networks (CNN), visual geometry group-16 (VGG16),
and VGG19. Besides, we …
Mining Health Informatics Job Advertisements: Insights For Higher Education Programs And Job Seekers, Ahmed El Noshokaty, Mohammad A. Al-Ramahi, Omar El-Gayar, Abdullah Wahbeh, Tareq Nasralah
Mining Health Informatics Job Advertisements: Insights For Higher Education Programs And Job Seekers, Ahmed El Noshokaty, Mohammad A. Al-Ramahi, Omar El-Gayar, Abdullah Wahbeh, Tareq Nasralah
Computer Information Systems Faculty Publications
This paper used web scraping and data mining to analyze 831 health informatics job advertisements on indeed.com. Results showed that 87% of jobs explicitly required a college degree in a related field, 41% of jobs preferred a graduate degree, while 29% preferred or required professional certification. The analysis showed that preferred skills were analytics problem solving, communication skills, oral communication, interpersonal skills, project management, statistics, and critical thinking. The analysis also showed that college degrees, certifications, and the above-mentioned skill set are in high demand for working in the field of health informatics, especially in states with large populations and …
Conversational Agents For Mental Health And Well-Being: Discovering Design Recommendations Using Text Mining, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Ahmed El Noshokaty, Tareq Nasralah
Conversational Agents For Mental Health And Well-Being: Discovering Design Recommendations Using Text Mining, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Ahmed El Noshokaty, Tareq Nasralah
Computer Information Systems Faculty Publications
Conversational agents are increasingly being used by the general population due to shortages in healthcare providers and specialists, and limited access to treatments. They are also used by people to deal with loneliness and lack of companionship. As these apps are increasingly replacing real humans, there is a need to explore their design features and limitations for better design of conversational apps. Using text mining and topic modeling, this study analyzed a total of 126,610 reviews about Replika, a popular and well-established conversational agent mobile app. Our results emphasized current practices for designing conversational apps while at the same time …