Digital Commons Network^™

Expression Of Concern: Improved Harmony Search Algorithm For Sdn Controller Placement, Yousra Abdul Alsahib S. Aldeen, Ahmed T. Sadiq, Abeer E. Abed, Omar F. Hussain, Syed Hamid Hussain Madni

Iraqi Journal for Computer Science and Mathematics

EXPRESSION OF CONCERN FOR: Y. A. A. S. Aldeen, A. T. Sadiq, A. E. Abed, O. F. Hussain, and S. H. H. Madni, ``Improved Harmony Search Algorithm for SDN Controller Placement,'' Iraqi Journal for Computer Science and Mathematics, vol. 6, no. 2, 2025, Article 12. DOI: https://doi.org/10.52866/2788-7421.1249.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss2/12.

Reason for Expression of Concern: The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “Exact Solutions of M-fractional Complex Ginzburg-Landau Equation via Two Analytical Methods (Manuscript 1267)”. Exact Solutions of M-fractional: : : The journal has initiated an additional …

Expression Of Concern: Exact Solutions Of M-Fractional Complex Ginzburg-Landau Equation Via Two Analytical, Nematollah Kadkhoda, Mojtaba Baymani, Maad M. Mijwil, Mostafa Abotaleb

Iraqi Journal for Computer Science and Mathematics

EXPRESSION OF CONCERN FOR: N. Kadkhoda, M. Baymani, M. M. Mijwil, and M. Abotaleb, ``Exact Solutions of M-fractional Complex Ginzburg-Landau Equation via Two Analytical Methods,'' Iraqi Journal for Computer Science and Mathematics, vol. 6, no. 3, 2025, Article 11. DOI: https://doi.org/10.52866/2788-7421.1267.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/11.

Reason for Expression of Concern: The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “Exact Solutions of M-fractional Complex Ginzburg-Landau Equation via Two Analytical Methods (Manuscript 1267)”. Exact Solutions of M-fractional: : : The journal has initiated an additional editorial assessment of the article’s methodology, …

Expression Of Concern: Artificial Intelligence In Education: Mathematics Teachers' Perspectives, Practices And Challenges, Mohammad A. Tashtoush, Yousef Wardat, Rommel Al Ali, Shoeb Saleh

Iraqi Journal for Computer Science and Mathematics

EXPRESSION OF CONCERN FOR: M. A. Tashtoush, Y. Wardat, R. A. Ali, and S. Saleh, ``Artificial Intelligence in Education: Mathematics Teachers' Perspectives, Practices and Challenges,'' Iraqi Journal for Computer Science and Mathematics, vol. 5, no. 1, 2024, Article 20. DOI: https://doi.org/10.52866/ijcsm.2024.05.01.004.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol5/iss1/20.

Reason for Expression of Concern: The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in ``Artificial Intelligence in Education: Mathematics Teachers' Perspectives''. The journal has initiated an additional editorial assessment of the article's methodology, data provenance, and reported outcomes to confirm their reliability and reproducibility.
This …

Expression Of Concern: A Lightweight U-Net Model For Accurate Skin Lesion Segmentation, Fallah H. Najjar, Karrar A. Kadhim, Farhan Mohamed, Mohd Shafry Mohd Rahim, Asniyani Nur Haidar Abdullah

Iraqi Journal for Computer Science and Mathematics

EXPRESSION OF CONCERN FOR: F. H. Najjar, K. A. Kadhim, F. Mohamed, M. S. Mohd Rahim, and A. N. Haidar Abdullah, ``A Lightweight U-Net Model for Accurate Skin Lesion Segmentation,'' Iraqi Journal for Computer Science and Mathematics, vol. 6, no. 2, 2025, Article 1. DOI: https://doi.org/10.52866/2788-7421.1230.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss2/1.

Reason for Expression of Concern: The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in ``A Lightweight U-Net Model for Accurate Skin Lesion Segmentation (Manuscript 1230)''. the journal has initiated an additional editorial assessment of the article's methodology, data provenance, and …

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.

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 …

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 …

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 …

The Heart Seat™: An In Home Cardiovascular Monitoring Device, Archana Venkataramani

Theses

Heart failure (HF) is one of the most common disorders, affecting an estimated 64 million people globally. Although heart failure incidence is stabilizing in some countries, prevalence is rising because of an aging population, improved post-myocardial infarction survival, and advances in treatment. High mortality, morbidity, reduced quality of life, and significant healthcare costs are results of heart failure (Shahim et al., 2023). Recurrent heart failure episodes are associated with an increased risk of death. Heart monitoring systems exist in several forms, including implantable cardiac devices, wearable and portable monitors, and remote patient monitoring systems. Each type differs in monitoring needs, …

Navigating Care And Self-Care: Understanding Latina Caregivers’ Prioritization And Engagement In Self-Care Practices, Denise A. Longoria, John M. Gonzalez, Romeo Escobar, Nelda Rodriguez

School of Social Work Faculty Publications

Introduction: Latina caregivers face significant physical and mental health risks due to the demands of caregiving. The decision to become a caregiver is often influenced by various factors including cultural values such as familismo and marianismo. It is essential that caregivers recognize the importance of self-care to prevent burnout. Without self-care, caregivers face an increased risk of stress, which can negatively affect physical and emotional health.

Methods: A qualitative approach using focus groups to explore Latina caregivers’ understanding and engagement in self-care.

Results: Findings suggested that participants understand the need for self-care; however, family and cultural needs were prioritized. When …

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 …

Optimised Data Integration Using Transformer Model And Resource Description Framework, Jerome Aondongu Achir, Muhammad Abdulkarim, Mohammed Abdullahi

Journal of Informatics and Web Engineering

Organizations have become highly reliant on a range of data sources that span structured, semi-structured, and unstructured data types. These repositories allow large-scale storage for faster ingestion and analytics but pose tremendous challenges of integration owing to schema and contextual differences. Traditional data integration methods, such as the ontology-based Resource Description Framework (RDF), are often inadequate when dealing with these challenges. They specifically struggle with the dynamic evolution of the schema of data sources, context-aware interpretation, and achieving interoperability across heterogeneous data sources. This paper presents an integrated system that augments resource description knowledge with token embeddings using the attention …

Sentiment-Based Music Recommendation System Using Natural Language Processing For Emotion-Aware Song Suggestions, Yu Bui Xuan, S. Prabha Kumaresan, Naveen Palanichamy, Mohamed Uvaze Ahamed Ayoobkhan

Journal of Informatics and Web Engineering

Music plays a vital role in influencing emotions, mood, and mental health. However, classical music recommendation systems mostly rely on listening to history, genre preference, or popularity, ignoring the listener’s mood. Motivation to go further in this area gave birth to this study, where a new sentiment-based music recommendation system is being designed by incorporating Natural Language Processing (NLP) and Machine Learning (ML) techniques to provide emotion-aware song recommendations. The system collects various audio features such as valence, energy, tempo, and danceability from music distribution platforms such as Spotify, which are well-known indicators for classifying the emotional tone of a …

A Unified Cloud-Based System For The Tyre Retail Industry: Design And Implementation Of Tracktive, William Theo Wei Loon, Siew-Chin Chong, Kian-Ming Lim, Lee-Ying Chong, Kuok-Kwee Wee

Journal of Informatics and Web Engineering

In the Malaysian concurrent tyre retailing industry, most of the business activities are carried out in the traditional labour-intensive ways. This manual process is prone to inefficiencies, increases operating costs and increases the likelihood of error. The current paper outlines Tracktive, a unified and cloud-based solution that was conceptualized and built to automate the industry by centralizing the ordering of tyres, inventory and order management to a single cloud-based platform. Tracktive is built on microservice architecture and event-driven architecture and deployed with the help of a simulated cloud environment. All the core functional modules are independent, scalable modules, each having …

Xai -Driven Explainability For Cardiovascular Diseases Prediction, Jacqueline Dike, Jarutas Andritsch

Journal of Informatics and Web Engineering

The adoption of artificial intelligence (AI) in cardiovascular disease prediction has significantly improved risk stratification, offering new avenues for early diagnosis and preventive care. With the growing availability of electronic health records and structured clinical datasets, machine learning (ML) and deep learning (DL) models have demonstrated strong predictive capabilities. However, despite their performance, its adoption in healthcare is often constrained by the lack of transparency and interpretability in many ML and DL models. This lack of explainability undermines clinical trust and raises ethical concerns. In high-stakes domains such as CVD prediction, clinicians require not only accurate outputs but also clear …

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 …

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, …

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 …

Ontology-Based E-Commerce Recommender System: A Hybrid Semantic Filtering Approach, Jocelyn Pua, Su-Cheng Haw, Lucia Dwi Krisnawati, Shaymaa Al-Juboori, Gee-Kok Tong

Journal of Informatics and Web Engineering

The rapid growth of e-commerce has led to product overload, which has resulted in personalized product discovery becoming a crucial problem for consumers. Classic recommender systems (RS), which rely heavily on content-based filtering or collaborative filtering, tend to face well-known problems such as cold start, data sparsity, and ignorance of semantics. Such constraints frequently result in irrelevant or redundant suggestions, thereby lowering the user satisfaction and conversions. This study presents a hybrid ontology-based e-commerce recommender system that combines symbolic reasoning with deep semantic matching. The system is based on a Neo4j graph database to capture structured product relationships and is …

Test Case Prioritization Using Ant Colony Optimization To Improve Fault Detection And Time, Nurezayana Zainal, Muhammad Sh Salleh, Nur Atiqah Wahidah Sulaiman, Ammar Alazab, Nur Liyana Sulaiman

Journal of Informatics and Web Engineering

Regression testing plays a critical role in ensuring the reliability and quality of software following continuous integration and development. However, executing all test cases during regression testing can be time-consuming and resource-intensive. Test Case Prioritization (TCP) addresses this challenge by determining an optimal execution order of test cases that maximizes early fault detection while minimizing execution time. Optimization algorithms contribute significantly to enhancing the effectiveness of TCP while utilizing limited resources. This study proposes an Ant Colony Optimization (ACO) algorithm to address the TCP problem, leveraging its strength in navigating complex search spaces inspired by the foraging behavior of real …

Flood Disaster Preparedness And Response Using A Web-Based Integrated Flood Management System (Ifms), Mohamed Abdiraman Abdirahim, Abd Samad Bin Hasan Basari, Malik Bader Alazzam, Muhammad Shukri Bin Che Lah, Rabiah Binti Ahmad, Aida Binti Mustapha

Journal of Informatics and Web Engineering

Floods are one of the most frequent and damaging natural hazards in Malaysia, especially in low-lying places, such as Batu Pahat and Johor. National flood monitoring systems, such as InfoBanjir and Malaysian Meteorological Department (MET) Malaysia, have disjointed data pools, late updates, and inadequate public access. In this paper, we present an IFMS, which is a contemporary web platform developed to integrate national flood management systems through data collection, automatic processing, dynamic visualization tools, and others. The system architecture consists of three main layers: IoT-enabled flood sensors, centralized web server, and responsive user interfaces. Backend processing is performed using Laravel, …

An Enhanced Glowworm Swarm Optimization For Minimizing Surface Roughness In Die Sinking Electrical Discharge Machining, Nurezayana Zainal, Muhammad Ammar S.M. Shahrom, Mohamad Firdaus Ab. Aziz, Salama A. Mostafa, Anis Farhan Kamaruzzaman, Nor Bakiah Abd. Warif

Journal of Informatics and Web Engineering

Electric Discharge Machining (EDM) is a non-traditional machining process that utilizes electric sparks between an electrode and a workpiece submerged in a dielectric fluid to ablate a material. It is commonly used in die-making, aerospace, automotive manufacturing, and medical manufacturing, because it can machine hard and complex materials with high precision. In this work, a Surface Roughness Optimization for EDM (SRO-EDM) model is proposed to investigate the machining performance of the die-sinking EDM process of titanium alloys. A regression-based combined approach of Glowworm Swarm Optimization (GSO) and a Two-Factor Interaction (2FI) model has been proposed to investigate the impact of …

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 …

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) …

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 = …

A Proposed Vision To Activate Smart Urban Growth Concepts For The New Egyptian Cities, Nirman M. El-Sayed, Mamdouh A. Al-Minshawi

Mansoura Engineering Journal

Smart urban growth is the ideal solution to urban problems within the cities of the fourth generation in Egypt, and despite this, most of them depend on traditional urban thought without activating "Smart Urban Growth", which is known to maintain lands from deterioration and make societies suitable for living and providing the necessary services. The goal of research to set standards to activate smart urban growth as a thought that keeps pace with sustainable urban development and Egypt's 2030 vision, work to use the global smart cities approach and how they reach intelligence. While the research follows the "analytical" deductive …

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 …

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 …

Characterizing Indoor Surface Voc Contamination After The 2025 Los Angeles Fires, Brett W. Stinson, Emily Lei, Elliott T. Gall

Mechanical and Materials Engineering Faculty Publications and Presentations

We quantify volatile organic compound (VOC) emissions from indoor surface swabs and portable air cleaner (PAC) filters collected in a home 30 days after the 2025 Los Angeles wildland-urban interface (WUI) fires. We calculate emissions for 17 fire-relevant compounds. Surface emissions exceeded those of clean controls, and emissions from a windowsill in a room without a PAC were ∼15× and ∼2× higher for benzene and toluene, respectively, than rates reported in the literature for comparable materials unaffected by smoke/soot. Particle filters installed in PACs at the start of the fire emitted aromatics at rates comparable to those reported in a …