Digital Commons Network^™

Gis-Based Volunteer Cotton Habitat Prediction And Plant-Level Detection With Uav Remote Sensing, Tianyi Wang, Xiaohan Mei, J. Alex Thomasson, Chenghai Yang, Xiongzhe Han, Pappu Kumar Yadav, Yeyin Shi

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Volunteer cotton plants germinate and grow at unwanted locations like transport routes and can serve as hosts for a harmful cotton pests called cotton boll weevils. The main objective of this study was to develop a geographic information system (GIS) framework to efficiently locate volunteer cotton plants in the cotton production regions in southern Texas, thus reducing time and economic cost for their removal. A GIS network analysis tool was applied to estimate the most likely routes for cotton transportation, and a GIS model was created to identify and visualize potential areas of volunteer cotton growth. The GIS model indicated …

Interval-Type Fuzzy Linear Fractional Programming Problem In Neutrosophic Environment: A Fuzzy Mathematical Programming Approach, Hamiden Abd El- Wahed Khalifa, Pavan Kumar

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Fuzzy Boundary Value Problem Under Generalized Hukuhara Differentiability, Bassem A. Kamal, A. A. Salama, M. Shokry, Magdi S. El-Azab, Galal I. El-Baghdady

Neutrosophic Sets and Systems

No abstract provided.

Single Valued Neutrosophic Vikor And Its Application To Wastewater Treatment Selection, Nor Liyana Amalini Mohd Kamal, Lazim Abdullah, Fu Ming Yee, Ilyani Abdullah, Nazanin Vafaei

Neutrosophic Sets and Systems

No abstract provided.

New Notions On Neutrosophic Random Variables, Carlos Granados

Neutrosophic Sets and Systems

No abstract provided.

View On Neutrosophic Over Topologized Domination Graphs, R.Narmada Devi, G. Muthumari

Neutrosophic Sets and Systems

No abstract provided.

On Independence Neutrosophic Random Variables, Carlos Granados, José Sanabria

Neutrosophic Sets and Systems

No abstract provided.

Neutrosophic Sets And Systems, Vol. 47, 2021, Florentin Smarandache, Mohamed Abdel-Basset, Said Broumi

Neutrosophic Sets and Systems

No abstract provided.

Secure And Privacy-Preserving Crowdsensing Using Smart Contracts: Issues And Solutions, Alfredo J. Perez, Sherali Zeadally

Computer Science Faculty Publications

The advent of Blockchain and smart contracts is empowering many technologies and systems to automate commerce and facilitate the exchange, tracking and the provision of goods, data and services in a reliable and auditable way. Crowdsensing systems is one type of systems that have been receiving a lot of attention in the past few years. In crowdsensing systems consumer devices such as mobile phones and Internet of Things devices are used to deploy wide-scale sensor networks. We identify some of the major security and privacy issues associated with the development of crowdsensing systems based on smart contracts and Blockchain. We …

Activation Of The Α1Β2Γ2l Gaba Receptor By Physiological Agonists, Spencer R Pierce, Allison L Germann, Gustav Akk

Open Access Publications

The Cl

A Comparison Of The Flipped Classroom Model For Medical Student Education In Ophthalmology Before And During The Covid-19 Pandemic, Kelly H. Yom, Ryan J. Diel, Pavlina S. Kemp

Journal of Academic Ophthalmology

Abstract

Background The coronavirus disease 2019 (COVID-19) pandemic has necessitated a shift of medical education to online learning in lieu of traditional clinic-based rotations. The flipped classroom model, which has been shown to be an effective approach to the medical student ophthalmology curriculum, shows promise as a method of learning that can be shared virtually. As such, the aim of this study was to investigate the effectiveness of a flipped classroom approach to the primary care-focused ophthalmology clerkship delivered entirely online in the face of the COVID-19 pandemic.

Methods Medical students who completed the 2-week introductory clinical ophthalmology clerkship from …

A Multilayer Network Model Of The Coevolution Of The Spread Of A Disease And Competing Opinions, Kaiyan Peng, Zheng Lu, Vanessa Lin, Michael R. Lindstrom, Christian Parkinson, Chuntian Wang, Andrea L. Bertozzi, Mason A. Porter

School of Mathematical & Statistical Sciences Faculty Publications

During the COVID-19 pandemic, conflicting opinions on physical distancing swept across social media, affecting both human behavior and the spread of COVID-19. Inspired by such phenomena, we construct a two-layer multiplex network for the coupled spread of a disease and conflicting opinions. We model each process as a contagion. On one layer, we consider the concurrent evolution of two opinions — pro-physical-distancing and anti-physical-distancing — that compete with each other and have mutual immunity to each other. The disease evolves on the other layer, and individuals are less likely (respectively, more likely) to become infected when they adopt the pro-physical-distancing …

A Report From The Nihr Uk Working Group On Remote Trial Delivery For The Covid-19 Pandemic And Beyond, Jane A.H. Masoli, Kim Down, Gary Nestor, Sharon Hudson, John T. O’Brien, James D. Williamson, Carolyn A. Young, Camille Carroll

Peninsula Medical School

Abstract Background Prior to the COVID-19 pandemic, the majority of clinical trial activity took place face to face within clinical or research units. The COVID-19 pandemic resulted in a significant shift towards trial delivery without in-person face-to-face contact or “Remote Trial Delivery”. The National Institute of Health Research (NIHR) assembled a Remote Trial Delivery Working Group to consider challenges and enablers to this major change in clinical trial delivery and to provide a toolkit for researchers to support the transition to remote delivery. Methods The NIHR Remote Trial Delivery Working Group evaluated five key domains of the trial delivery pathway: …

Processing Binding Data Using An Open-Source Workflow, Errol L G Samuel, Secondra L Holmes, Damian W Young

Faculty, Staff and Students Publications

The thermal shift assay (TSA)—also known as differential scanning fluorimetry (DSF), thermofluor, and Tm shift—is one of the most popular biophysical screening techniques used in fragment-based ligand discovery (FBLD) to detect protein–ligand interactions. By comparing the thermal stability of a target protein in the presence and absence of a ligand, potential binders can be identified. The technique is easy to set up, has low protein consumption, and can be run on most real-time polymerase chain reaction (PCR) instruments. While data analysis is straightforward in principle, it becomes cumbersome and time-consuming when the screens involve multiple 96- or 384-well plates. There …

Constructivist Peer Review In Music Theory And Composition Courses: Technologies And Practice, Brendan Mcconville

Journal of the Association for Technology in Music Instruction

This article considers the supporting technologies and practices for effective semi-anonymous peer review in traditional music theory and composition-related courses: orchestration, arranging, and composition. A coordinated approach probes two questions nested within one broad case study: (1) does the use of peer review in music theory and composition-related courses create meaningful, constructivist-inspired learning experiences, and (2) what web technologies can efficiently and effectively accomplish its activities? The article first provides a constructivist theoretical framework; next, it explains the methodologies, technologies, and resulting feedback from using peer review in a three-course study; and finally it provides concluding remarks on the many …

Volume 29, Summer 2002 Communication And Theater Association Of Minnesota Journal

Communication and Theater Association of Minnesota Journal

Complete digitized volume (volume 29, Summer 2002) of Communication and Theater Association of Minnesota Journal.

Volume 28, Summer 2001 Communication And Theater Association Of Minnesota Journal

Communication and Theater Association of Minnesota Journal

Complete digitized volume (volume 28, Summer 2001) of Communication and Theater Association of Minnesota Journal

Volume 30, Summer 2003 Communication And Theater Association Of Minnesota Journal

Communication and Theater Association of Minnesota Journal

Complete digitized volume (volume 30, Summer 2003) of Communication and Theater Association of Minnesota Journal.

Volume 31, Summer 2004 Communication And Theater Association Of Minnesota Journal

Communication and Theater Association of Minnesota Journal

Complete digitized volume (volume 31, Summer 2004) of Communication and Theater Association of Minnesota Journal

Volume 32, Summer 2005 Communication And Theater Association Of Minnesota Journal

Communication and Theater Association of Minnesota Journal

Complete digitized volume (volume 32, Summer 2005) of Communication and Theater Association of Minnesota Journal.

Volume 33, Summer 2006 Communication And Theater Association Of Minnesota Journal

Communication and Theater Association of Minnesota Journal

Complete digitized volume (volume 33) of Communication and Theater Association of Minnesota Journal.

[2021 Winner] Incarceration As A New Age Form Of Slavery For People Of Color And Racism In The United States, Tessa Rosasco

Ethnic Studies Research Paper Award

Throughout the history of the United States, racial disparity has been rampant. This is especially true in relation to the population of people of color imprisoned in the U.S. My paper discusses the racial inequality in America, especially that of African Americans, and how people of color have been unjustly treated in a historically racist and unjust system. Special emphasis has been given to the portrayal of African Americans in the media and how presidential rhetoric and agendas have harmed communities of color.

Aspect-Based Sentiment Analysis Of Movie Reviews, Samuel Onalaja, Eric Romero, Bosang Yun

SMU Data Science Review

This study investigates a comparison of classification models used to determine aspect based separated text sentiment and predict binary sentiments of movie reviews with genre and aspect specific driving factors. To gain a broader classification analysis, five machine and deep learning algorithms were compared: Logistic Regression (LR), Naive Bayes (NB), Support Vector Machine (SVM), and Recurrent Neural Network Long-Short-Term Memory (RNN LSTM). The various movie aspects that are utilized to separate the sentences are determined through aggregating aspect words from lexicon-base, supervised and unsupervised learning. The driving factors are randomly assigned to various movie aspects and their impact tied to …

Access Barriers To Telehealth, Quynh Chau, Amita Behuria Pathak, Daniel Turner, Jacquelyn Cheun, Carl Noe

SMU Data Science Review

Abstract. Telehealth has long been touted as an efficient and cost-effective way to deliver health care services to patients. The COVID-19 global pandemic hastened the adoption of this technology in the United States. Despite its promises, telehealth as a technology-based model of health service delivery has also highlighted access to care inequities in the form of uneven utilization across various patient demographics. This research uses machine learning and publicly available data sources to describe telehealth utilization based on social determinants of care. The implications of this application can be used to inform health care providers of how to target efforts …

Reading Level Identification Using Natural Language Processing Techniques, William Arnost, Ellen Lull, Joseph Schueder, Joseph Engler

SMU Data Science Review

This paper investigates using the Bidirectional Encoder Representations from Transformers (BERT) algorithm and lexical-syntactic features to measure readability. Readability is important in many disciplines, for functions such as selecting passages for school children, assessing the complexity of publications, and writing documentation. Text at an appropriate reading level will help make communication clear and effective. Readability is primarily measured using well-established statistical methods. Recent advances in Natural Language Processing (NLP) have had mixed success incorporating higher-level text features in a way that consistently beats established metrics. This paper contributes a readability method using a modern transformer technique and compares the results …

Modeling Electric Energy Generation In Ercot During Extreme Weather Events And The Impact Renewable Energy Has On Grid Reliability, Adam R. Ruthford, Bivin Sadler

SMU Data Science Review

This paper shows the inadequacy of current grid backup supplies, their ongoing threat to grid reliability, and the increased risk of customer blackouts. This paper also examines reliability concerns caused by renewable energy sources under more normal operating conditions. This paper seeks to model the impacts of extreme weather on ERCOTs grid. Unusual weather patterns require that the electrical grid operates in conditions outside normal operating parameters. Electrical system demand can spike well above normal levels. At the same time, weather influences can change the operating envelope of electrical generation equipment. The ERCOT grid has changed from its’ traditional mix …

Emotion Integrated Music Recommendation System Using Generative Adversarial Networks, Mrinmoy Bhaumik, Patrica U. Attah, Faizan Javed

SMU Data Science Review

Music can stimulate emotions within us; hence is often called the “language of emotion.” This study explores emotion as an additional feature in generating a playlist with a deep learning model to improve the current music recommendation system. This study will sample emotions from certain subjects for each song in a sample of the data. Since the effect of music on emotion is subjective and is different person to person, this study would need a considerable number of subjects to reduce subjectivity. Due to the limited resources, a portion of the data will be labeled with emotion from subjects and …

Alternative Methods For Deriving Emotion Metrics In The Spotify® Recommendation Algorithm, Ronald M. Sherga Jr., David Wei, Neil Benson, Faizan Javed

SMU Data Science Review

Spotify's® recommendation algorithm tailors music offerings to create a unique listening experience for each user. Though what this recommender does is highly impressive, there is always room for improvement given that these techniques are not fully prescient. This study posits that in addition to creating certain features based on audio analysis, incorporating new features derived from album art color as well as lyrical sentiment analysis may provide additional value to the end user. This team did not find that a significant difference existed between color valence and Spotify® valence; however, all other comparisons resulted in statistically significant difference of means …

Clinical Diagnosis Support With Convolutional Neural Network By Transfer Learning, Spencer Fogleman, Jeremy Otsap, Sangrae Cho

SMU Data Science Review

Breast cancer is prevalent among women in the United States. Breast cancer screening is standard but requires a radiologist to review screening images to make a diagnosis. Diagnosis through the traditional screening method of mammography currently has an accuracy of about 78% for women of all ages and demographics. A more recent and precise technique called Digital Breast Tomosynthesis (DBT) has shown to be more promising but is less well studied. A machine learning model trained on DBT images has the potential to increase the success of identifying breast cancer and reduce the time it takes to diagnose a patient, …

Fashion, Identity And The Muslim-American Narrative, Shireen Soliman

Artizein: Arts and Teaching Journal

In this pivotal time, assumptions, boundaries, power structures and relationships within society are being reconsidered and reimagined. My research project, “Fashion, Identity and the Muslim- American Narrative” builds off of well-established prior models and responds to this moment. Through this multidisciplinary, multimedia design workshop series geared towards Muslim American female adolescents, we are able to leverage the powerful intersection of design, technology, community, social media and social justice. In this affirming, enlightening space, we use fashion, dress and personal narrative as the springboard and means of exploring the intrinsic connection between social and emotional issues surrounding identity development, social justice …