Digital Commons Network^™

Referent Data For Investigations Of Upper Limb Accelerometry: Harmonized Data From Three Cohorts Of Typically-Developing Children, Catherine E Lang, Catherine R Hoyt, Jeffrey D Konrad, Kayla R Bell, Natasha Marrus, Marghuretta D Bland, Keith R Lohse, Allison E Miller

2020-Current year OA Pubs

AIM: The rise of wearable sensing technology shows promise for addressing the challenges of measuring motor behavior in pediatric populations. The current pediatric wearable sensing literature is highly variable with respect to the number of sensors used, sensor placement, wearing time, and how data extracted from the sensors are analyzed. Many studies derive conceptually similar variables via different calculation methods, making it hard to compare across studies and clinical populations. In hopes of moving the field forward, this report provides referent upper limb wearable sensor data from accelerometers on 25 variables in typically-developing children, ages 3-17 years.

METHODS: This is …

Enhancing Energy Efficiency With A Dynamic Trust Measurement Scheme In Power Distribution Network, Yilei Wang, Xin Sun, Guiping Zheng, Ahmar Rashid, Sami Ullah, Hisham Alasmary, Muhammad Waqas

Research outputs 2022 to 2026

The application of Intelligent Internet of Things (IIoT) in constructing distribution station areas strongly supports platform transformation, upgrade, and intelligent integration. The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer, with the former using intelligent fusion terminals for real-time data collection and processing. However, the influx of multiple low-voltage in the smart grid raises higher demands for the performance, energy efficiency, and response speed of the substation fusion terminals. Simultaneously, it brings significant security risks to the entire distribution substation, posing a major challenge to the smart grid. In response to these challenges, a …

Agent-Interacted Big Data-Driven Dynamic Cartoon Video Generator, Yasmin Makki Mohialden, Abbas Akram Khorsheed, Nadia Mahmood Hussien

Mesopotamian Journal of Big Data

This study presents a novel method for animating videos using three Kaggle cartoon faces data sets. Dynamic interactions between cartoon agents and random backgrounds, as well as Gaussian blur, rotation, and noise addition, make cartoon visuals look better. This approach also evaluates video quality and animation design by calculating the backdrop colour's average and standard deviation, ensuring visually appealing material. This technology uses massive datasets to generate attractive animated videos for entertainment, teaching, and marketing.

Generalized Time Domain Prediction Model For Motor Imagery-Based Wheelchair Movement Control, Z. T. Al-Qaysi, M. S. Suzani, Nazre Bin Abdul Rashid, Reem D. Ismail, M. A. Ahmed, Rasha A. Aljanabi, Veronica Gil-Costa

Mesopotamian Journal of Big Data

Brain-computer interface (BCI-MI)-based wheelchair control is, in principle, an appropriate method for completely paralyzed people with a healthy brain. In a BCI-based wheelchair control system, pattern recognition in terms of preprocessing, feature extraction, and classification plays a significant role in avoiding recognition errors, which can lead to the initiation of the wrong command that will put the user in unsafe condition. Therefore, this research's goal is to create a time-domain generic pattern recognition model (GPRM) of two-class EEG-MI signals for use in a wheelchair control system. This GPRM has the advantage of having a model that is applicable to unknown …

Face Morphing Attacks Detection Approaches: A Review, Essa Mokna Namis, Khalid Shakir Jasim, Sufyan Al-Janabi

Mesopotamian Journal of Big Data

Face recognition systems (FRSs) that are applied by real-time applications such as border control are vulnerable to attacks such as face morphing, which blends two or more facial images into a single morphed image. The vulnerability of FRSs to many types of attacks, including both direct and indirect attacks, as well as face-morphing attacks, has garnered significant attention from the biometric field. A morphing attack aims to undermine the security of an FRS at an automated border control (ABC) gate by using an electronic machine-readable travel document (eMRTD) or e-passport that is acquired using a morphed face image. Most countries …

Advanced Machine Learning Approaches For Enhanced Gdp Nowcasting In Syria Through Comprehensive Analysis Of Regularization Techniques, Khder Alakkari, Bushra Ali, Mostafa Abotaleb, Rana Ali Abttan, Pushan Kumar Dutta

Mesopotamian Journal of Big Data

This study addresses the challenge of nowcasting Gross Domestic Product (GDP) in data-scarce environments, with a focus on Syria, a country facing significant economic and political instability. Utilizing a dataset from 2010 to 2022, three machine learning algorithms Elastic Net, Ridge, and Lasso were applied to model GDP dynamics based on macroeconomic indicators, commodity prices, and high-frequency internet search data from Google Trends. Among these, the Lasso regression model, noted for its variable selection and sparsity promotion, proved most effective in capturing Syria's complex economic realities, achieving the lowest Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). …

Harnessing The Potential Of Artificial Intelligence In Managing Viral Hepatitis, Guma Ali, Maad M. Mijwil, Ioannis Adamopoulos, Bosco Apparatus Buruga, Murat Gök, Malik Sallam

Mesopotamian Journal of Big Data

Viral hepatitis continues to be a serious global health concern, impacting millions of people, putting a strain on healthcare systems across the world, and causing significant morbidity and mortality. Traditional diagnostic, prognostic, and therapeutic procedures to address viral hepatitis are successful but have limits in accuracy, speed, and accessibility. Artificial intelligence (AI) advancement provides substantial opportunities to overcome these challenges. This study investigates the role of AI in revolutionizing viral hepatitis care, from early detection to therapy optimization and epidemiological surveillance. A comprehensive literature review was conducted using predefined keywords in the Nature, PLOS ONE, PubMed, Frontiers, Wiley Online Library, …

A Framework For Automated Big Data Analytics In Cybersecurity Threat Detection, Mohamed Ariff Ameedeen, Rula A. Hamid, Theyazn H. Aldhyani, Laith Abdul Khaliq Al-Nassr, Sunday Olusanya Olatunji, Priyavahani Subramanian

Mesopotamian Journal of Big Data

This research presents a novel framework designed to enhance cybersecurity through the integration of Big Data analytics, addressing the critical need for scalable and real-time threat detection in large-scale environments. Utilizing technologies such as Apache Kafka for efficient data ingestion, Apache Flink for stream processing, and advanced machine learning models like LSTM and Autoencoders, the framework offers robust anomaly detection capabilities. It also includes automated response mechanisms using SOAR and XDR systems, significantly improving response times and accuracy in threat mitigation. The proposed solution not only addresses current challenges in handling vast and complex data but also paves the way …

Hybrid Spotted Hyena Based Load Balancing Algorithm (Hshlb), Raed A. Hasan, Mustafa M. Akawee, Enas F. Aziz, Omar A. Hammood, Aws Saad Showket, Husniyah Jasim, Mohammed A. Alkhafaji, Omar K. Ahmed, Khalil Yasin

Mesopotamian Journal of Big Data

In this paper, we delve into the core of our proposed dynamic load balancing mechanism, the Hybrid Spotted Hyena based Load Balancing algorithm (HSHLB). We begin by presenting a comprehensive overview of the Spotted Hyena Optimization Algorithm (SHOA) and the fundamental behaviors it encompasses, namely migration and attacking. We then introduce the Load Balancing Algorithm (LB) and outline its principles, emphasizing its distinct characteristics. Recognizing the strengths and weaknesses of both SHOA and LB, we embark on a journey to hybridize these two optimization techniques, resulting in the potent HSHLB. We elucidate the intricate process of combining these algorithms, elucidating …

Automated Water Quality Assessment Using Big Data Analytics, Yasmin Makki Mohialden, Nadia Mahmood Hussien, Saba Abdulbaqi Salman

Mesopotamian Journal of Big Data

Water is one of the world's most precious resources, essential to life. Industrial waste, agricultural runoff, and urban discharge degrade water, rendering it unfit for consumption. Water quality monitoring and evaluation are more important than ever. Big Data analytics is used to examine water quality utilizing enormous datasets of pH, hardness, solids concentration, chloramine, sulfate, conductivity, organic carbon, trihalomethanes, and turbidity. This work classifies water potability, which is vital for human consumption, using strong machine learning on massive datasets. Classifiers were Random Forest, Gradient Boosting, and Support Vector Machine on 3,276 water bodies. The Random Forest classifier obtained the highest …

Understanding The Impact Of Covid-19 On Online Eating Disorder Communities On Reddit, Md Al Amin

Computer Science

Like precedent disease outbreaks, COVID-19 has immense implications for health challenges. The social restrictions and disruption in daily activities pose a psychological burden for humans worldwide and may be particularly detrimental for individuals with mental disorders. Psychological stressors stemming from the COVID-19 pandemic and resultant stay-at-home orders may exacerbate Eating Disorder(ED)- related triggers and present a challenging environment for individuals with anorexia nervosa, bulimia nervosa, and binge eating disorder. In this research, we aim to comprehend how COVID-19 has affected individuals with eating disorders through a comparative analysis of data obtained from online communities. We developed a tool for extracting …

Augmented Reality And Cross-Device Interaction For Seamless Integration Of Physical And Digital Scientific Papers, Md Ochiuddin Miah

Computer Science

Researchers face the challenge of efficiently navigating vast scientific literature while valuing printed papers in the digital age. Printed materials facilitate deeper engagement and comprehension, leading to superior exam performance and enhanced retention. However, existing digital tools often need to pay more attention to the needs of researchers who value the tactile benefits of printed documents. In response to this gap, we introduce AR-PaperSync, a transformative solution that leverages Augmented Reality (AR) and cross-device interaction technology. AR-PaperSync seamlessly integrates the physical experience of printed papers with the interactive capabilities of digital tools. Researchers can effortlessly navigate inline citations, manage saved …

Hack24f: Using Ai To Support Teachers Working With Young Children With Challenging Behaviors, Muqing Zhang, Bennie Bendiksen, Songtian Zeng

Paul English Applied Artificial Intelligence (AI) Institute Publications

While coaching or mental health consultation can be a promising approach to support educators (Kang-Yi et al., 2018), the cost can be substantial and many school districts find it difficult to hire qualified personnel to coach the educators in need. Previous research has attempted to utilize mobile technology to support parents in addressing children with challenging behaviors (Meadan et al., 2016). There are few tools available to support teachers and that attempt to integrate AI technology in the program design and implementation. Our objective is to develop a prototype AI-based tool called Trick-or-Treat to support teachers in identifying and developing …

Performance Measurement In A Custom Production Process Model Using The Process Mining Approach: A Systematic Literature Review, Wawa Wikusna, Mustafid, Ferry Jie

Research outputs 2022 to 2026

This study aims to explore and develop a method for measuring supply chain performance influenced by customer demand in custom product production. The research method used is a systematic literature review, focusing on measuring key indicators and evaluating supply chain performance. This study highlights the importance of Key Performance Indicators (KPIs) as an evaluation tool, which helps make decisions more effective and efficient in the supply chain. By using the Supply Chain Operation Reference (SCOR) model supported by the Analytic Hierarchy Process (AHP) and the normalization of the Snorm De Boer Score, this study shows a systematic measurement process from …

Exact Testing For Heteroscedasticity In A Two-Way Layout In Variety Frost Trials When Incorporating A Covariate, Angelika A. Pilkington, Brenton R. Clarke, Dean A. Diepeveen

Grain and Other Field Crops Research Articles

Two-way layouts are common in grain industry research where it is often the case that there are one or more covariates. It is widely recognised that when estimating fixed effect parameters, one should also examine for possible extra error variance structure. An exact test for heteroscedasticity, when there is a covariate, is illustrated for a data set from frost trials in Western Australia. While the general algebra for the test is known, albeit in past literature, there are computational aspects of implementing the test for the two way when there are covariates. In this scenario the test is shown to …

Physiological Evidence Of Escalating Stress During Covid-19: A Longitudinal Assessment Of Child Welfare Workers, Austin Griffiths, Kim Link, Kara Haughtigan, Oliver W.J. Beer, Lindsey Powell, David Royse

School of Health Professions

Studies have shown that stress has contributed to employee turnover and retention problems for agencies, and at the individual level, chronic stress has been associated with coronary heart disease, anxiety, depression, and many other negative effects. In the past, the extent of stress one has felt has been measured by subjective paper-and-pencil instruments; however, recent technological advances have improved our ability to obtain accurate biofeedback assessments from wearable instruments. The Kentucky Child Welfare Workforce Wellness Initiative is the first known study to explore physiological stress in a sample (n = 32) of child welfare professionals using biometric technology (Firstbeat Bodyguard …

A Gis Tool For Optimal Forage Species Selection, David B. Hannaway, Christopher Daly, Michael D. Halbleib, Linda Brewer, Sophie Baur, Chelsea Clark, Emilie Krecklow, Scott Bassett

IGC Proceedings (1977-2023)

To determine appropriate forage species for US ecoregions, geographic information technologies (GIS) are being used to create climatic and soil factor maps. Excel spreadsheets and RStudio are used to create response functions of forage species to minimum and maximum temperature, annual precipitation, soil pH, soil salinity, and salinity. National forage data and expert opinion will evaluate quantitative tolerances, seasonal yield profiles, and pollinator suitability. These maps and agronomic and livestock use information will be shared with forage specialists and farmers to provide alternatives for improved perenniality, increased diversity, and system circularity. Future work will include development and evaluation of climate …

Enhancing Medical Chatbots With Image Diagnosis, Swatisri Chavali

Master's Projects

Medical chatbots, at the conjunction of artificial intelligence and healthcare, are the very cornerstone of a transformative force in diagnostic capabilities and communication channels for healthcare professionals. The history of this journey, from early chatbot models to sophisticated systems, is born out of a relentless pursuit of accuracy and contextual understanding. This proposal acknowledges the critical role played by NLTK in raising the interpretability and communicative capabilities of intelligent systems, meeting challenges that arise from varying writing styles and accommodating the standards of the medical field. The integration of NLTK is a linchpin, bridging the gap between sophisticated technological architectures …

59th International Congress On Medieval Studies, Medieval Institute, Western Michigan University

International Congress on Medieval Studies Archive

The printed program of the 59th International Congress on Medieval Studies (May 9–11, 2024), together with the Corrigenda.

Lis Journals' Lack Of Participation In Wikidata Item Creation, Eric Willey, Susan Radovsky

Faculty and Staff Publications – Milner Library

There are many items in Wikidata representing scholarly articles. However, these items have been created mostly by volunteer Wikidata editors and not systematically by journal publishers or editors, which can lead to gaps and inconsistencies in the datasets. This article presents findings from a survey investigating practices of library and information studies (LIS) journals in Wikidata item creation. Believing that a significant number of LIS journal editors would be aware of Wikidata and some would be creating Wikidata items for their publications, the authors sent a survey asking 138 English-language LIS journal editors if they created Wikidata items for materials …

Consulting With An Embedded Librarian: Student Perceptions On The Value Of Required Research Meetings, Susan Franzen, Caitlin Stewart, Mallory Jallas, Joshua Newport

Faculty and Staff Publications – Milner Library

Objective: This qualitative research project was undertaken to discover how students perceive the embedded librarian in their nursing class. The researchers determined how a required group research meeting was valued by students and whether that value warranted the necessary time and energy by an embedded librarian.

Methods: Researchers conducted focus groups with twenty-three students from two different sections of the same nursing research methods undergraduate course. Students’ responses to a series of five questions were recorded within Zoom and supplemented by handwritten notes. Data was coded by hand and patterns that emerged from the five focus groups were …

Book Challenges And Collection Development In Academic Libraries, Cindy Hohl, Michael Fernandez, Rachel E. Scott

Faculty and Staff Publications – Milner Library

In March 2024, the American Library Association reported a “record number of unique book titles challenged in 2023.” These challenges can have a chilling effect on the work of librarians seeking to collect materials inclusive of human identities, religions, and experiences. The LRTS editors asked current American Library Association President Cindy Hohl to consider the intersection of book challenges and collection development in academic libraries.

Beyond A Land Acknowledgement: Taking A First Step Towards Reparative Action, David X. Lemmons, Tarida Anantachai, Kat Bell, Jason Byrd, Heather James, Erika Quintana, Gerie Ventura, Mea Warren

Foley Library Scholarship

The Logistics Committee of the Conference on Academic Library Management (CALM)’s 2023 conference posed a question early on in conference planning: what if we rejected the traditional model of land acknowledgements? In answering that question, the committee embarked on a year-long process to radically revise the statement to one focused on reparative action. This article covers the revision process, including what inspired it and how the committee structured their work.

When The Forest Goes Silent: Effects Of Human Foot Traffic On Communication And Diversity Of Passerine Birds., Ruby Andes

IdeaFest 2024

No abstract provided.

Increasing Chiropractic Prevalence In Black Communities, Mckenna Bartlett

IdeaFest 2024

No abstract provided.

A Prediction Model Of Nathan's Jacket Preferences, Nathan Boone

IdeaFest 2024

No abstract provided.

College Corps: Big Brothers Big Sisters College Corp Experience, Ivory Browning

IdeaFest 2024

No abstract provided.

American Pikas Responses To Long And Short Alarm Calls During Mid-Summer In Lassen National Forest, California, Thomas Butler

IdeaFest 2024

No abstract provided.

Media Coverage Of The Klamath Dam Removal, Jessie Cretser-Hartenstein, Oden Taylor, Jillian Wells, Emma Wilson, Gabriel Zucker

IdeaFest 2024

No abstract provided.

Agent-Based Modeling Of Microglia Behavior In The Context Of Alzheimer's Disease, Emmanuel Mezzulo, Cheyenne Ty, Amanda Case, Abigail Penland, Kamila Larripa

IdeaFest 2024

No abstract provided.