Digital Commons Network^™

On Cartan’S Examples Of Isoparametric Hypersurfaces And Their Focal Submanifolds, Thomas E. Cecil, Patrick J. Ryan

Mathematics and Computer Science Department Faculty Scholarship

This paper is a survey of Cartan’s examples of isoparametric hypersurfaces in spheres and their focal submanifolds that were described in his fundamental work on the subject, which appeared in four papers [2]–[5] published during the period 1938–1940.

Valentine's Day 2026 - U.S. Government Resources, Raquel Estrada

Library Display Posters

A collection of U.S. Government–produced materials celebrating Valentine’s Day. The poster features fun facts from the U.S. Census Bureau and includes links to Valentine’s Day cards created by various federal agencies, such as the U.S. Fish and Wildlife Service, NOAA, the Department of Energy, and the National Park Service.

Valentine's Day 2026 - De-Stress Activities, Raquel Estrada

Library Display Posters

No abstract provided.

Integrating Future Factory-To-Factory (F2f) Manufacturing Through System Of Systems Engineering (Sose): A Framework For Capability Beyond Constituent Systems, Polinpapilinho F. Katina, Hengtao Tang Ph.D., Anouar Hallioui

Faculty Publications

System of Systems Engineering (SoSE) is an emerging discipline focused on the design, integration, and evolution of metasystems—composed of multiple autonomous yet interdependent systems. These systems of systems (SoS) offer capabilities that exceed those of any individual constituent systems by enabling synergistic coordination, interoperability, and dynamic adaptation across diverse operational contexts. This study pursued three primary objectives: (i) to examine the role of integration in enabling emergent capabilities beyond those of individual systems, (ii) to explore SoSE as a framework for orchestrating Future Factory-to-Factory (F2F) Manufacturing, and (iii) to assess the implications of SoSE to address volatile, uncertain, complex, and …

Muscle Endurance Exercise Training Improves Health Factors In Middle Aged Individuals, Gregory Wallace

Doctorate in Kinesiology

This study examined the effects of an eight-week Muscle Endurance Exercise Training (MEET) program on body composition (BC), cardiorespiratory fitness (CRF), and muscle endurance (ME) in healthy adults. Thirty-one participants (M_age = 39.03 ± 13.82 years) completed pre- and post-intervention assessments of body mass index (BMI), body fat percentage (BF%), waist-to-hip ratio (WHR), CRF via the 3-minute YMCA Step Test, and ME using push-up and sit-up tests to failure. Paired-samples t-tests and Wilcoxon signed-rank tests were used to determine statistical significance. Results revealed no significant change in BMI (p = .103), while BF% (p = .020) and WHR (p = …

Mobility, Migration, And Cultural Political Economy: Personal Narratives Of Immigration Policy, Max Crumley-Effinger

Journal of Comparative & International Higher Education

This study embraces the opportunity to explore students’ immigration experiences from a cultural political economy (CPE) perspective, beginning with a review of literature relevant to understanding students’ perspectives of host nation international student mobility and migration (ISM) policy, followed by an outline of the CPE theoretical framework. The study’s methodology is presented, outlining how findings were obtained through a qualitative content analysis of interviews with 40 international students studying in Australia, Canada, and the United States. Findings are then presented through the words of study participants, highlighting how international students connect their ISM policy experiences with the local CPE contexts …

Safety Of Carotid Endarterectomy In The Elderly And Octogenarian Population: A Nationwide Study Including 80,000 Patients, Victor Gabriel El-Hajj, Joanna Roy, Basel Musmar, Wi Jin Kim, Michael Rizzuto, Nathaniel Ellens, Rabab Alshahrani, Victor Staartjes, Adrian Elmi-Terander, Ramachandra Tummala, Stavropoula Tjoumakaris, Michael Gooch, Robert Rosenwasswer, Ziad Khabbaz, Pascal Jabbour

Department of Neurosurgery Faculty Papers

INTRODUCTION: Carotid endarterectomy (CEA) is an established procedure for stroke prevention in patients with carotid artery stenosis. While CEA is considered safe in younger patients, perioperative risks in octogenarians remain debated, with current guidelines classifying the procedure as "high-risk" in this patient population. This study aimed to evaluate short-term outcomes of CEA across age groups and to assess whether comorbidity burden better predicts outcomes than chronological age.

METHODS: The ACS-NSQIP database (2013-2020), was used to identify patients eligible for inclusion. The cohort was stratified based on age <  60, 60-80, and > 80 years. Propensity score matching and multivariable logistic regression were used to compare …

Amir Nyke Lee

African American Funeral Programs

No abstract provided.

Doctor's Gift Helps Keep Health Care Close To Home, Bill Dabney

University of Mississippi News

"Love this clinic! I went here as a kid and now my kids go here. Dr. Vig is the best." – Percyanna Henderson

Charting A New Era To Modernize United States Infant Formula Regulation, Douglas G Burrin, Amy B Hair, Sharon M Donovan

Children’s Nutrition Research Center Staff Publications

No abstract provided.

Delivering Inclusive Cultural Offers For Social Prescribing: A Realist Evaluation Involving Older People From Global Majority Backgrounds And Cultural Sector Providers In The Uk, Debra Westlake, Kamal R. Mahtani, Geoffrey Wong, Jordan Gorenberg, Marta Santillo, Kerryn Husk, Sofia Vougioukalou, Ruthanne Baxter, Shoba Dawson, Caroline M. Potter, Harriet Warburton, Beth Mcdougall, Stephanie Tierney

Peninsula Medical School

Introduction: Research shows cultural activities benefit older people's wellbeing, but little is known about why individuals from global majority (minority ethnic) groups engage less with the mainstream cultural sector, or how it could adapt to meet their needs and encourage engagement. The TOUS study (Tailoring cultural Offers with and for diverse older Users of Social prescribing) investigated the question: What tailoring is needed, how, when and for whom, to optimise cultural offers as part of social prescribing for older people (aged 60+) from global majority groups?. Methods: The TOUS study involved focused ethnographies with six cultural-sector organisations throughout the United …

Lakeisha N. Hall

African American Funeral Programs

Funeral program for Lakeisha N. Hall. Service was held on February 14, 2026.

Ms. Shemika L Simmons

African American Funeral Programs

Program for the funeral of Shemika L Simmons held at St. Paul CME on February 14th, 2026

Pediatric Inflammatory Bowel Disease Tissue Classification From Pathology Slide Images: Detecting Phenotypes Using Computer Vision, Chloe Martin-King, Ali Nael, Louis Ehwerhemuepha, Blake Calvo, Quinn Gates, Jamie Janchoi, Elisa Ornelas, Melissa Perez, Andrea Venderby, John Miklavcic, Peter Chang, Aaron Sassoon, Brian Rubio, Ghislaine Barrigan, Kenneth Grant

Food Science Faculty Articles and Research

Background and Aims

Methods

Results …

Evaluating Celebrity Influence On Brand Attention, Emotion, And Memory, Noela Michael, Thomas Zoega Ramsoy, Ian Michael

All Works

This study focuses on the growing trend of celebrities being used as influencers in marketing, with firms investing substantially in celebrity endorsements. The study examines the effectiveness of celebrity influencers in destination marketing, comparing their influence with that of non-celebrity influencers. Neuroscience tools and methods were used to understand how cognitive and emotional factors impact consumer decisions and their likelihood to travel. The results show that employing a celebrity does not always increase audience engagement and attention toward the destination. The average person perceives the celebrity as a whole rather than focusing on one specific feature. Moreover, there were no …

Models Of Change: Communicating To Your Funder And Stakeholders How You Believe Your Project Will Succeed, Jean Mclaughlin, Thuy Vu, Noe Vargas Hernandez, Arturo A. Fuentes

Civil Engineering Faculty Publications

No abstract provided.

Anfis And Rbfnn Efficacy And Timescale Dependence In Spei-Based Drought Prediction Using Meteorological Inputs, Alisa Afendi, Muhamad Usman Tariq, Shuhaida Ismail, Azizul Azhar Ramli

Journal of Informatics and Web Engineering

Drought is a slow-onset natural disaster that has far-reaching effects on agriculture, water security, and socio-economic systems, especially in climate-vulnerable countries such as Malaysia. It is imperative to predict droughts for prompt mitigation efforts. In this paper, the influence of temporal scale on drought modelling has been put into discussion by analyzing a comparison between two machine learning (ML) models: Adaptive Neuro-Fuzzy Inference System (ANFIS); Radial Basis Function Neural Network (RBFNN) based on Standardized Precipitation Evapotranspiration Index (SPEI) as depicting drought. The SPEI of four timescale categories (SPEI-3, SPEI-6, SPEI-9, and SPEI-12) were calculated weekly and monthly (two different temporal …

Re: Genetic Screening Of Genome-Wide Association Studies-Derived Risk Loci For Type 2 Diabetes Mellitus: Confirmation In The North Indian Population, Mostafa Saadat

Sultan Qaboos University Medical Journal

No abstract provided.

Spatial Abilities In Aging Adults With Down Syndrome, Yingying Jennifer Yang, Romal Bhullar, Sonia Conde

Department of Psychology Faculty Scholarship and Creative Works

INTRODUCTION

People with Down syndrome (DS) have a higher likelihood of developing Alzheimer's disease (AD). Deficits in spatial abilities could serve as early indicators of AD. We examined age effects on visuospatial construction and visuomotor integration in DS and whether spatial tasks could distinguish various extents of cognitive decline in DS.

METHODS

We used the Alzheimer's Biomarkers Consortium–Down Syndrome project dataset, where 376 DS participants completed a series of cognitive measures.

RESULTS

Age effects were found in visuomotor integration but not in visuospatial construction. Both abilities declined with AD progression. While both abilities showed relatively poor discrimination between cognitively stable …

Vehicle Re-Identification System Using Residual Network With Instance-Batch Normalization, Wei Jie Low, Kah-Ong Michael Goh, Check-Yee Law, Connie Tee, Yong-Wee Sek, Md Ismail Hossen

Journal of Informatics and Web Engineering

Vehicle Re-identification (Re-ID) has become extremely important due to the increasing number of vehicles on the road and its potential to address traffic-related challenges. As a result, there is also a growing need for efficient methods to track and identify vehicles across multiple traffic cameras. One of the biggest challenges of this task is the variations in vehicle appearances across different camera angles. This is because vehicles can appear significantly different when captured from various camera angles and viewpoints. Furthermore, the current vehicle Re-ID solutions typically require extensive coding knowledge, making it inaccessible to many potential users. Therefore, we focus …

Editorial: Intelligent Systems And The Next Wave Of Digital Innovation, Hairulnizam Mahdin

Journal of Informatics and Web Engineering

The field of artificial intelligence (AI), machine learning and intelligent automation has become pervasive in our modern digital world. It extends from business and public services to environmental management and even into people's daily experiences with technology. In this special issue "Intelligent Systems and the Next Wave of Digital Innovation," published in the Journal of Informatics and Web Engineering, reviews several studies to explore the increasing role of intelligent systems in current society and their importance. Some of the more significant areas of discussion are how to formalize the expectations for explainable AI, evaluating face recognition models in the real …

Robust Medical Image Prediction Via Adaptive Reconstruction: Bridging The Gap In Low-Quality Data, Prateek Singhal, Madan Singh

Journal of Informatics and Web Engineering

Medical image prediction plays a very significant role in clinical decision-making and early detection and diagnosis of different diseases. However, the quality of medical images has a huge impact on the predictive models' accuracy. Poor-quality data usually occurs due to problems like noise, artifacts, and low resolution and poses a major challenge for reliable medical image prediction. Framework advances medical image analysis through three novel contributions firstly, A hybrid architecture combining wavelet-based denoising with deep learning (DL) enhancement (unlike existing single-approach methods). Secondly, Cross-modality robustness validated on low-quality CT/MRI/X-rays from real clinics (versus modality-specific solutions), and lastly, A closed-loop system …

Efficiency Of Neo4j In Designing And Analysing Graph Database For Air Quality Analysis Of Indian Metro Cities, Jiten Chavda, Kishan Bharvad, Rishap Parmar, Nidhi Arora

Journal of Informatics and Web Engineering

The analysis of the Air Quality Index (AQI) is currently a popular subject in the area of sustainable research, as it is crucial for investigating and analysing the effects of air pollutants on human health in urban environments. It has been identified over the last decade that airborne pollution has become a critical issue and will remain an important concern in India in the coming years. In recent years, a variety of models and algorithms utilizing big data techniques have been developed for the analysis of air quality data. In this paper, we suggest monitoring and feature analysis of air …

Hybrid Sentiment Analysis Model For Customer Feedback Interpretation Using Lexicon, Machine Learning And Deep Learning Techniques, Jou Jia Yi, Lew Sook Ling, Tan Li Tao

Journal of Informatics and Web Engineering

Customer feedback is pivotal in enhancing service quality and user satisfaction across digital platforms. However, traditional sentiment analysis methods often struggle with informal languages, contextual nuances, and aspect-specific opinions. In this paper, a hybrid sentiment analysis framework is proposed, utilizing lexicon-based (VADER), machine learning (Support Vector Machine and Random Forest), and deep learning (BERT) techniques to achieve improved sentiment classification accuracy and interpretability compared to previous studies. The framework incorporates advanced preprocessing techniques, such as emoji normalization, handling of negation, and detection of intensifiers, to better capture emotional information in user-generated content. The objectives of this study are to develop …

An Empirical Evaluation Of Machine Learning Methods And Text Classifiers For Sentiment Analysis Of Online Consumer Reviews, Pei Qin Lo, Sew Lai Ng, Li-Xian Jiao

Journal of Informatics and Web Engineering

This study aims to identify the best predictive model for analysing online product reviews (OPRs) in the electronics industry, with a secondary focus on leveraging unstructured customer feedback to support product improvement. Using a dataset of 9,675 Oppo mobile phone reviews, this study employs three classification models—Random Forest, Support Vector Machine (SVM) and Logistic Regression–paired with Term Frequency-Inverse Document Frequency (TF-IDF) or bidirectional encoder representation transformer (BERT) as the embedding models to analyse customer sentiment and derive actionable insights. The methodology features a comprehensive analysis pipeline that includes text preprocessing with the Natural Language Toolkit (NLTK), feature extraction using) vectorization …

A Conceptual Framework On Development Of Sign Language Chatbot For E-Commerce, Salma Jahan Nisha, Nabhan Salih, Wan-Noorshahida Mohd-Isa

Journal of Informatics and Web Engineering

This study proposes and validates a conceptual framework using a sign language (SL) chatbot in the e-commerce domain to improve accessibility. Currently, the use of SL is a less-explored area in online platforms. It is difficult for any communication-challenged person to interact online for buying products and services, using a chatbot, particularly for people using SL. The objective of this study is to introduce a novel hybrid architecture using SL Recognition with a conversational-based chatbot agent via a custom Application Programming Interface (API) in e-commerce platforms. Our work proposes a combined hybrid chatbot framework model using Convolutional Neural Network (CNN) …

Dynamic Multi-Layered Hardware Obfuscation With Behavioral Drift Locking For Sat-Resistant Designs, Ahmed Yehia Salah Mohamed Emish

Theses and Dissertations

The globalization of the semiconductor supply chain has introduced critical vulnerabilities, including intellectual property (IP) piracy, reverse engineering, and hardware tampering. While traditional logic locking offers a baseline of defense, the emergence of powerful Boolean satisfiability (SAT) solvers has rendered many static obfuscation techniques ineffective. This work proposes a Dynamic Multi- Layered Hardware Obfuscation Framework that utilizes Behavioral Drift Locking (BDL) to provide a robust defense-in-depth against advanced adversarial models. The methodology integrates four synergistic layers: • Dynamic Key Management using a time-dependent rotation mechanism that updates keys every clock cycle to prevent static analysis. • Control Obfuscation through opcode …

Editorial Preview For February 2026 Issue, Fong-Yee Lee, Su-Cheng Haw

Journal of Informatics and Web Engineering

The February 2026 issue presents 17 research papers within its regular section, covering a wide range of areas including Artificial Intelligence (AI), Machine Learning (ML), Web and Cloud Technologies, Recommender Systems and Software Engineering. The collection reflects JIWE’s ongoing effort to advance research in the informatics and web engineering domain. A special thematic section, guest-edited by Prof. Ts. Dr. Hairulnizam Bin Mahdin, centers on “Intelligent Systems and the Next Wave of Digital Innovation”. This section studies the pervasive role of AI and machine learning in multiple sectors of industrial automation and disaster preparedness. These studies also emphasize on trust, transparency, …

Radiology Report Generation Using Deep Learning And Web-Based Deployment For Chest X-Ray Analysis, David Agbolade, Peyman Heydarian, Shakeel Ahmad

Journal of Informatics and Web Engineering

The huge rise in the number of medical images has caused a major problem in radiology departments. Radiologists are now working harder than ever, which affects the quality of their diagnoses and patient care. It takes 15 to 30 minutes to write a manual radiological report for each case, and different people may see things differently. Modern departments process over 230 cases a week, which causes long delays in diagnosis. Automated report generation systems that are already in use have a lot of problems, such as not being able to be interpreted clinically, not having enough Digital Imaging and Communications …

Deep Learning-Based Automatic Detection And Diagnosis Of Tuberculosis From Chest X-Ray Images: A Comprehensive Analysis, Paschal C. Ahanotu, Deborah A. Adedigba, Raza Hasan, Sellappan Palaniappan

Journal of Informatics and Web Engineering

Tuberculosis (TB) continues to be one of the foremost public health issues in the world, and remains the second most salient communicable cause of death after COVID-19. In 2022, TB accounted for 10.6 million new infections and 1.3 million deaths globally. Conventional diagnostic approaches involving sputum smear microscopy, culture assays, and GeneXpert MTB/RIF are characterized by excessive turnaround times, elevated costs, and dependency on specialised infrastructure and trained personnel. These constraints are exacerbated in resource-poor countries, resulting in delayed diagnosis, delayed therapy initiation, and enhanced disease transmission. This work investigates the application of deep learning algorithms to automatically diagnose TB …