Digital Commons Network^™

Synthetic Health Data: Real Ethical Promise And Peril, W. Nicholson Price Ii, Daniel Susser

Other Publications

Modern health research and development faces a dilemma. On the one hand, there is more data than ever — in electronic health records, in lab research, in public datasets, and on the internet — from which to extract potentially transformative scientific insights and to use as the basis for developing breakthrough health care technologies. On the other hand, using this data entails various risks: threats to patient privacy, skewed samples and approaches to analysis that can perpetuate demographic and other biases, and uneven access to data about rare conditions and small patient subgroups. Generating synthetic data has emerged as one …

Long- And Short-Term Weather Variables Affect Capture Rates In Western Painted Turtles (Chrysemys Picta Bellii) In Marshall Co., South Dakota, Amy Dolan, Heather L. Waye, Peter Dolan

Biology Publications

Turtle populations are declining globally, and yet accurate long-term population surveys are often lacking. Even amongst widespread species, information on long-term population trends is largely missing. As such, studies on demographics, population structure, and factors that affect capture efficacy are needed. In 2019 we began a long-term study on Western Painted Turtles (Chrysemys picta bellii) in the Couteau des Prairie habitat in northeastern South Dakota. We captured turtles using several trapping techniques and investigated the effects of short- and long-term weather variables on catch per unit effort. Temperature was positively associated with daily capture rates, showing the strongest …

Identifying Accessibility Improvement Opportunities For Global Environmental Communication Websites, Alicia Mason, Josh Compton, Sakshi Bhati

Faculty Submissions

Digital environmental information presented with low web accessibility reduces parti-cipation in environmental advocacy and information seeking behaviors for many people with disabilities, creating a consequential digital divide. We use WEB AIM computer automated analysis of web accessibility to assess the general accessibility of online environmental communication messages. Results show 95.3% of the popular websites in our sample had indicators of potentially critical accessibility errors. Our findings highlight the importance of addressing digital environmental information accessibility shortcomings so that educational, informational and persuasive environ-mental messages can increase environmental literacy of vulnerable populations and help to bridge the digital divide.

A Digital Platform That Integrates Biogeographic, Molecular, And Phenotypic Relationships Of Wild Plants, Fruits, And Associated Insects In Kenya, Bonface Odhiambo Onyango

All Master’s Theses

Museum biocollections contribute to exploratory studies on insects, which are increasingly providing insights into their interactions with fruits. Scientists at the International Centre of Insect Physiology and Ecology (icipe) conducted a study which documented data on biocollections of wild plants, fruits, and associated insects. Despite publishing this study, most of the data records remained secluded within icipe. In addition, the biocollections lacked associated molecular data information limiting the understanding of their phylogenetic relationships.The aim of this study was to digitize the icipe biocollections and integrate the corresponding publicly available molecular barcodes. First, a database was designed.Second, respective barcodes were retrieved …

Multicolor Bipartite Ramsey Number Of Double Stars, Gregory M. Decamillis

Honors Undergraduate Theses

The core idea of Ramsey theory is that complete disorder is impossible. Given a large structure, no matter how complex it is, we can always find a smaller substructure that has some sort of order. For positive integers $n, m$, the double star $S(n,m)$ is the graph consisting of the disjoint union of two stars $K_{1,n}$ and $K_{1,m}$ together with an edge joining their centers. The $k$-color bipartite Ramsey number of $ S(n,m)$, denoted by $r_{bip}(S(n,m);k)$, is the smallest integer $N$ such that, in any $k$-coloring of the edges of the complete bipartite graph $K_{N,N}$, there is a monochromatic copy …

Preschool Classroom Behavior In Context: Development And Validation Of The Spanish Form Of The Adjustment Scales For Preschool Intervention (Aspi), Rebecca Jane Bulotsky-Shearer, Paul A. Mcdermott, Jenna Futterer, Michael Lopez, Mileidis Gort

Archives of Assessment Psychology

The purpose of the study was to validate the context scale scores for the Spanish language form of the Adjustment Scales for Preschool Intervention (ASPI) for use by early childhood teachers from Spanish-speaking backgrounds. Exploratory and confirmatory factor analyses in a diverse sample of preschool children from low-income families (N = 4,077) revealed two dimensions of context scales of behavioral adjustment: Problems in Preschool Classroom Contexts Requiring Disciplined Behavior and Problems in Contexts Requiring Engaged Behavior. ASPI dimension scores across Spanish and English language forms were horizontally equated through item response theory (IRT). Criterion-related validity using multilevel models was established …

Secure Container-Based High Performance Computing Architecture , Holger Gantikow

School of Engineering, Computing and Mathematics Theses

This PhD thesis addresses the evolving landscape of High Performance Computing (HPC) by focusing on the critical challenge of securing the use of container virtualisation within HPC environments. The traditional approach to security for HPC operators is being challenged by a growing number of cyber security threats such as hacks and resource misuse. In addition, the risk of insider attacks is increasing, overall requiring a re-evaluation of security strategies, which in many cases are still based on a high level of trust in users.This is further aggravated by the increasing demand to open up HPC environments to novel users and …

Enhancing Pitch Stability In Floating Wind Platforms: The Hydrodynamic Effects Of Thin Plates, Ignacio Pregnan Johannesen

School of Engineering, Computing and Mathematics Theses

The Floating Offshore Wind Turbines (FOWT) technology is still at an early stage looking for ways to make it competitive. In the case of semi-submersible FOWT the large structure has been pointed as an option to tackle the final energy price and therefore, smaller/cheaper platforms are desired. However, this would have implications on the platform hydrodynamic performance. This thesis discusses the use of thin disks as pitch motion suppression surfaces for FOWT platforms, employing three methodologies; potential flow, Computational Fluid Dynamics (CFD) and Experiments. With NEMOH a boundary element method code, the added mass and excitation forces/moments were calculated for …

Data Security And User Authentication In Public Cloud Computing Environments, Nelson Vasconcelos Soares Dos Santos

School of Engineering, Computing and Mathematics Theses

Cloud computing has become a prevalent paradigm for organisations and individuals, offering a range of services and resources that enable the efficient management, processing and storage of large quantities of data. However, despite its numerous advantages, cloud computing also presents significant challenges related to data security and user authentication. The distributed nature of cloud environments, coupled with the relinquishment of control over data to cloud service providers, has raised concerns regarding data vulnerability to various types of attacks, such as data breaches, malware injection, and denial of service. Moreover, traditional password and token-based authentication methods have been shown to be …

The Assessment Of Floating Offshore Wind Turbines In Extreme Conditions, Andre Onife Alwyn White

School of Engineering, Computing and Mathematics Theses

The purpose of this research is to assess if a floating offshore wind turbine (FOWT) system that is suitable for the environmental conditions in the Scottish North Sea (SNS) is also suitable for the environmental conditions in the Jamaica Caribbean Sea (JCS). A FOWT within Jamaica is an important structure because it produces renewable energy which helps to reduce the dependence on fossil fuel as the primary source of energy. At the same time, it also contributes to reducing global warming caused by climate change effects. These structures, therefore, must be robust enough to withstand the most extreme environmental conditions …

Investigating The Roles Of Plants, Fungi, And Biocrusts In Nutrient Movement Within Dryland Ecosystems, Catherine E. Cort

Open Access Theses & Dissertations

In dryland ecosystems, plant productivity and microbial decomposition are often separated in space and time due to the asynchronous availability of soil moisture and organic matter inputs. It has been proposed that fungi play a key functional role in connecting these cycles by facilitating movement of water, carbon (C), and nitrogen (N) through a network of shared hyphae between plant roots and biological soil crust (biocrust) communities at the soil surface. This connection, also known as the â??fungal loop,â?? effectively re-couples processes of nutrient release and uptake between primary producers and minimizes ecosystem N losses due to leaching, erosion, and …

Towards Trust And Reputation As A Service In Society 5.0, Stephan Olariu, Ravi Mukkamala, Meshari Aljohani

Computer Science Faculty Publications

Our paper was inspired by the recent Society 5.0 initiative of the Japanese Government which seeks to create a sustainable human-centric society by putting to work recent advances in technology. One of the key challenges in implementing Society 5.0 is providing trusted and secure services for everyone to use. Motivated by this challenge, this paper makes three contributions that we summarize as follows: Our first main contribution is to propose a novel blockchain and smart contract-based trust and reputation service design to reduce the uncertainty associated with buyer feedback in marketplaces that we expect to see in Society 5.0. Our …

An Extensive Examination Of The Iot And Blockchain Technologies In Relation To Their Applications In The Healthcare Industry, Karthik Kumar Vaigandla, Madhu Kumar Vanteru, Mounika Siluveru

Mesopotamian Journal of Computer Science

Numerous domains have been transformed by the communication technologies made possible by the Internet of Things (IoT), one of which is health monitoring systems. Patterns associated with diseases and health conditions can be identified through the utilization of machine learning and cutting-edge AI techniques. Currently, scientific endeavours are concentrated on enhancing IoT-enabled applications such as medical report administration, prescription traceability, and infectious disease surveillance through the amalgamation of blockchain technology(BCT) and machine learning(ML) models. Although recent advancements have attempted to increase the adaptability of blockchain(BC) and ML for IoT applications, there are still a number of crucial considerations that must …

New Recruitment Approach Based On Logistic Regression Model, Ishraq Hatif Abd Almajed, Ghalia Nassreddine, Joumana Younis

Mesopotamian Journal of Computer Science

Artificial intelligence (AI) is a pivotal technological advancement developed by humans with the aim of enhancing the quality of human existence.  It signifies the capacity of a computerized machine resembling a robot to execute tasks typically performed by humans and replicate human behavior. Machine learning (ML), a subfield of AI, involves the construction of systems that acquire the ability to make predictions about new output values by leveraging existing data, without the need for human interaction. Currently, ML has been incorporated into various fields, including but not limited to medical diagnosis, image processing, prediction, classification, learning association, commerce, finance, and …

A Comparative Study Of Chest Radiographs And Detection Of The Covid 19 Virus Using Machine Learning Algorithm, Shaimaa Q. Sabri, Jahwar Y. Arif, Ghada A. Taqa, Ahmet Çınar

Mesopotamian Journal of Computer Science

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak that is causing coronavirus disease 2019 is being deemed a pandemic because of its quick spread around the globe.  Because chest X-ray pictures have shown to be beneficial in monitoring a variety of lung disorders, they have recently been utilized to monitor COVID-19 disease. It takes time to manually analyze a lot of chest X-ray pictures. Several previous studies have suggested machine-learning (ML)-based techniques for COVID-19 detection from chest X-ray pictures as a solution to this issue. Though little effort has been made to use traditional machine learning (ML) methods, the …

Examining Ghana's National Health Insurance Act, 2003 (Act 650) To Improve Accessibility Of Artificial Intelligence Therapies And Address Compensation Issues In Cases Of Medical Negligence, George Benneh Mensah, Maad M. Mijwil, Mostafa Abotaleb

Mesopotamian Journal of Computer Science

Objective: Examine Ghana’s National Health Insurance Act (Act 650) to identify coverage gaps limiting artificial intelligence (AI) therapy access and address medical negligence liability issues surrounding automated healthcare systems. Methods: Legal and regulatory analysis of Act 650 were conducted, review of academic literature on global uptake of AI interventions and medical negligence principles were elucidated, examination of case studies implementing pilot AI therapy programs under insurance schemes were considered. Results & Conclusions: Act 650 lacks clear provisions for funding innovative AI treatments with proven efficacy and undefined negligence determination guidelines involving AI systems, contributing to accessibility and accountability issues. Proposed …

Data Mining Utilizing Various Leveled Clustering Procedures On The Position Of Workers In A Data Innovation Firm, Hussein Alkattan, Noor Razzaq Abbas, Oluwaseun A. Adelaja, Mostafa Abotaleb, Guma Ali

Mesopotamian Journal of Computer Science

The reason of this paper is to clarify dynamic clustering, the divisive and agglomerative dynamic clustering techniques. It fundamentally centers on the concept of the divisive different leveled shapes as well known as the top-down approach by creating a workflow appear, dendrograms, clustered data table which accumulated the clusters based the chosen property, and appear the isolated between each cluster with the assistance of an data mining device called Python. The DIANA dynamic approach utilized data tests of the list of laborers in a Data Advancement firm to induce clusters from the position column inside the data test table. In …

Deep Learning Model For Hand Movement Rehabilitation, Reem D. Ismail, Qabas A. Hameed, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Fatimah N. Ameen

Mesopotamian Journal of Computer Science

Electroencephalography (EEG) can control machines for human purposes, especially for disabled people doing rehabilitation exercises or regular tasks. Brain-computer interface (BCI) for Robotic hand uses deep learning to convert (EEG) brain activity into orders for robotic hand allowing users to move their hands right or left by the movement imagining. It could enable paralyzed individuals to perform basic hand movements and help in rehabilitation robots that help stroke patients regain hand function by offering guided exercises based on machine learning interpretations of their movements and intents. Artificial intelligence algorithms, particularly deep learning, classify and recognize patterns and intents implicit brainwaves …

Potato Disease Identification Using Transfer Learning Approaches, Tarza Hasan Abdullah

Mesopotamian Journal of Computer Science

Potato crop is one of the prominent consumed foods by human beings. When potato crops are infected by diseases it affects farmers negatively and to run in a loss. Therefore, early detection of the potato crop disease can play a vital role in minimizing the loss of the farmers. Nowadays, artificial intelligence technologies, more specifically deep learning techniques, provide solutions to many crops disease-related problems. However, training deep learning models requires a high computational power and huge amount of data as they are data hungry models. Also, designing a custom CNN models a difficult task and there are some variations …

Enhancing Motion Detection In Video Surveillance Systems Using The Three-Frame Difference Algorithm, Suhaib Qassem Yahya Al-Hashemi, Majid Salal Naghmash, Ahmad Ghandour

Mesopotamian Journal of Computer Science

This paper outlines a methodology for motion detection in video surveillance systems, leveraging advanced algorithms and TCP/IP networks for real-time data acquisition and analysis. The primary focus is on the implementation of the Three-Frame Difference Algorithm, which detects moving targets by analyzing the differences between three consecutive video frames. This method significantly reduces redundant data transmission and storage, addressing the challenges posed by limited wireless network capabilities. The surveillance model, designed in MATLAB using SIMULINK, integrates computer vision systems with embedded coders to facilitate effective communication and processing of video data. The results demonstrate the system's capability to detect motion …

Computer Networking And Cloud-Based Learning/Teaching Environment Using Virtual Labs Tools: A Review And Future Aspirations, Mishall Al-Zubaidie, Raad A. Muhajjar, Lauy Abdulwahid Shihabe

Mesopotamian Journal of Computer Science

Physical laboratories for practical classrooms in computer networks can be prohibitively expensive, as well as requiring regular hardware/software upgrades. With Netkit and similar software, network laboratories can be set up in a computer lab, but the setup is complicated and each student still needs their own computer. Thanks to the Cloud-based infrastructure, Netkit is now available in pre-configured Amazon elastic compute Cloud (EC2) instances. This research reviews and introduces educational computer networks. Furthermore, a web interface is used to allow remote access to numerous lab scripts instantiated on the Cloud. This study also describes how to use the Cloud to …

Credit Card Fraud Detection Based On Deep Learning Models, El-Sayed M. El-Kenawy, Ahmed Mohamed Zaki, Wei Hong Lim, Abdelhameed Ibrahim, Marwa M. Eid, Ahmed Osman Osman, Ahmed M. Elshewey

Mesopotamian Journal of Computer Science

Credit card fraud detection (FD) protects consumers and financial institutions by identifying suspicious or unauthorized transactions. To improve security and reduce false positives, fraud detection systems can analyze transaction data patterns in real time using advanced machine learning (ML) and deep learning (DL). This paper exploits DL models to detects transactional data which includes anomalies through Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) to verify data and mitigate fraud. The models used precision, recall, F1-score, and AUC on a balanced shared 559856-record Kaggle repository dataset. The RNN model detected anomalies with 99.39% accuracy, 0.9939 …

A Comprehensive Survey On Rare Event Prediction, Chathurangi Shyalika Jayakody Kankanamalage, Ruwan Wickramarachchi, Amit Sheth

Publications

Rare event prediction involves identifying and forecasting events with a low probability using machine learning (ML) and data analysis. Due to the imbalanced data distributions, where the frequency of common events vastly outweighs that of rare events, it requires using specialized methods within each step of the ML pipeline, i.e., from data processing to algorithms to evaluation protocols. Predicting the occurrences of rare events is important for real-world applications, such as Industry 4.0, and is an active research area in statistics and ML. This paper comprehensively reviews the current approaches for rare event prediction along four dimensions: rare event data, …

Growing South Dakota (Winter 2024), College Of Agriculture, Food And Environmental Sciences

Growing South Dakota (Publication of the College of Agriculture, Food and Environmental Sciences)

[Page] 3 Continuing a Leadership Journey
/="/">[Page] 5 CAFES Leadership Team Grows
/="/">[Page] 7 Award-Winning Faculty & Staff
/="/">[Page] 9 New Endowment Holders Recognized
/="/">[Page] 10 Inaugural Precision Livestock Field School Offered at SDSU Cottonwood Field Station
/="/">[Page] 11 SDSU Celebrates Professional Program in Veterinary Medicine Students [Page] 13 Clay Carlson, SDSU Meat Science Graduate Student Approaches School and Life with Winning Mindset
/="/">[Page] 15 SDSU Alumni has been selected as the Head Coach of the South Dakota State University Livestock Judging Team
/="/">[Page] 16 Livestock Units Promote Hands-On Learning & Premier Research …

Can Informed Consent Solve Ai Bias?, W. Nicholson Price Ii

Reviews

Artificial intelligence (AI) is moving increasingly rapidly into health care (as indeed into everything else). But it has problems there (as indeed everywhere else!). What’s to be done, in particular, about the deeply embedded biases along racial and other lines that permeate the whole world of health and, as such, are likely to be encoded in AI?

Khiara Bridges gives an answer that seems mild but carries roots of revolution. In Race in the Machine: Racial Disparities in Health and Medical AI, she argues that informed consent is a key lever to pull in fighting these racial disparities. But not …

Assessing And Understanding Soil Characteristics​, Amy Papineau

UNH Cooperative Extension

No abstract provided.

Gluon Helicity From Global Analysis Of Experimental Data And Lattice Qcd Ioffe Time Distributions, J. Karpie, R. M. Whitehill, W. Melnitchouk, C. Monahan, K. Orginos, J.-W. Qui, D. G. Richards, N. Sato, S. Zafeiropoulos, Jefferson Lab Angular Momentum And Hadstruc Collaboration

Physics Faculty Publications

We perform a new global analysis of spin-dependent parton distribution functions with the inclusion of Ioffe time pseudodistributions computed in lattice QCD (LQCD), which are directly sensitive to the gluon helicity distribution, Δg. These lattice data have an analogous relationship to parton distributions as do experimental cross sections, and can be readily included in global analyses. We focus in particular on the constraining capability of current LQCD data on the sign of Δg at intermediate parton momentum fractions x, which was recently brought into question by analysis of data in the absence of parton positivity constraints. …

Dual-Energy Electron Storage Ring, B. Dhital, Y. S. Derbenev, A. Hutton, H. Zhang, G. A. Krafft, Y. Zhang, F. Lin, V. S. Morozov

Physics Faculty Publications

A dual-energy electron storage ring is a novel concept initially proposed to cool hadron beams at high energies. The design consists of two closed rings operating at significantly different energies: the low-energy ring and the high-energy ring. These two rings are connected by an energy recovery linac (ERL) that provides the necessary energy difference. The ERL features superconducting radio-frequency (SRF) cavities that first accelerate the beam from the low energy E_L to the high energy E_H and then decelerate the beam from E_H to E_L in the next pass. The different SRF cavities in the ERL …

On-Field Agroecosystem Research Experience: An Undergraduate Perspective, Elysee Ndayishimiye, Japhet Dushimeyesu, Yvon Ukwishaka, Chittaranjan Ray, David Fleisher, Dennis Timlin, Vangimalla Reddy, Arindam Malakar

Journal of Contemporary Water Research and Education

Undergraduate hands-on research can foster innovation and critical thinking among young scholars to delve into real-world challenges. Specifically, exploring the critical nexus between water usage and agricultural yield, can foster academic growth and holds the key to addressing global food security in an era of increasing environmental constraints, where students can unlock insights crucial to enhancing crop yield and sustainability. Investigating the intricate relationship between water management and crop productivity through undergraduate research is exemplified in this article. Undergraduate students acquired hands-on research experience by collecting, processing, and analyzing destructive (crop biomass samples) and non-destructive (plant height, nodes, and leaf …

Environmental Attitudes Of Local Government Scholars In Tiaong, Quezon, Philippines, Justine A. Marasigan, Ma. Larissa Lelu P. Gata

Journal of Public Affairs and Development

This study aimed to analyze the environmental attitudes of local government scholars in Tiaong, Quezon, Philippines. The quantitative research design was used to determine the level of environmental attitudes using the New Ecological Paradigm (NEP) Scale. It was also utilized to examine the relationship between environmental attitudes and independent variables which include demographic characteristics such as age, gender, and economic status, academic background such as student classification, scholastic standing, scholarship privileges, and membership in student and/or youth organizations, and experience with ecological extremes. A total of 301 respondents participated in an online survey administered through Google Forms ®. The respondents …