Digital Commons Network^™

Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding

Journal of System Simulation

Abstract: The breakthrough of LLMs has provided powerful tools for social network research, advancing multi-agent social network simulation into a new era. This review systematically examined recent progress in LLM-driven multi-agent social network simulation research through a integrated perspective of multi-disciplines such as artificial intelligence, psychology, communication studies, and sociology. A three-tiered research system, which has gradually formed in this field and encompassed micro-level individual behaviors, meso-level interactive relations, and macro-level system emergence, was summarized. At the micro-level, research focuses on individual human behavior simulation, and numerous studies are dedicated to developing human-like agents with complex cognitive and affective architectures …

Optical Textures Of A Uniform Liquid Crystal Lattice: Monte Carlo Simulations With Newton Colors And Mueller Matrix Analysis, Yakup Emül

Turkish Journal of Physics

The optical textures of a uniform liquid crystal (LC) molecule lattice structure were explored through Monte Carlo (MC) simulations, combined with Mueller matrix (MM) formalism and Newton’s color theory. These simulations utilized a Lebwohl-Lasher (LL) type interacting LC lattice under periodic boundary conditions, generating ensemble-averaged configurations at two temperature regimes (kBT = 0.9 and 1.2), corresponding respectively to nematic and isotropic states. These configurations were then incorporated into the MM framework to evaluate the polarization states of transmitted light. To visually interpret the resulting interference phenomena, we propose a new visualization method based on a modern interpretation of Newton’s color …

Outburst Characteristics Of Transient  Low-Mass X-Ray Binary 4u 1608-52, Can Güngör

Turkish Journal of Physics

We present a detailed analysis of the long-term X-ray light curve of 4U 1608–52, focusing on fast-rising exponential-decay (FRED) outbursts, low-intensity states, and quiescent intervals. By calibrating the onset times of the outbursts, we identify three distinct classes for the FRED-type events: (i) the long-high outbursts, exceeding ~50 d in duration with peak count rates above ~40 cnt s-1; (ii) the short-medium outbursts, with durations of ~20 d and peak count rates of ~30-50 cnt s-1; and (iii) the short-low outbursts, also lasting ~20 d but reaching only ~20-30 cnt s-1 at peak. Furthermore, we examine the relation between preoutburst …

New Measurement And Analysis For The 15N + 11B Elastic Scattering System, Nurlan Amangeldi, İsmai̇l Boztosun, Dauren Soldatkhan, Bakytbek Mauyey, Kanat Makhanov, Raimbek Akhat, Aida Anuar, Gani Yergaliuly

Turkish Journal of Physics

New experimental data on the elastic scattering of the nuclear process 15N+11B at an energy of Elab=26.25 MeV were obtained on the DC-60 cyclotron of the INP RK. Based on a semi-microscopic analysis of the interaction of an accelerated 15N ion with 1p-shell nuclei 11B the effectiveness of the new B3Y-Fetal potential was studied. . The difference between the B3Y-Fetal potential and the traditional Yukawa potentials (M3Y-Reid and M3Y-Paris) is that its density-dependent parameters are determined from the saturation condition of nuclear matter at low energy. Analysis was performed on double folding optical model (DFOM) and so no for other …

Hybrid 3d Modelling Framework For Indoor Navigation Using Federated Learning And Internet Of Things-Enabled Edge Devices, Noopur Tyagi, Jaiteg Singh, Saravjeet Singh, Ahmad Ali Alzubi, Farman Ali, Sukhjit Singh Sehra, Babar Shah

All Works

Background There has been a recent trend towards using three-dimensional (3D) models to enhance spatial awareness and maximize resource utilization in complex environments. 3D building model can be used in various applications, such as real-time guidance and tracking the positions of individuals in multi storied buildings. Cities are now being modeled and studied in three dimensions as an improved method of urban planning. Method This study proposes an advanced indoor navigation framework that combines 3D modelling, federated learning (FL), and Internet of Things (IoT) integration to deliver reliable floor-level localization and real-time guidance. In Phase 1, highly accurate 3D models …

Re: Conditional Approval Letter With Comments For Butte Priority Soils Operable Unit (Bpsou) Draft Final 2026 Interim Site-Wide Surface Water Monitoring Quality Assurance Project Plan (Qapp) (Dated February 4, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Satellites, Urban Heat, And Environmental Justice: Community As The Bridge Between Analysis And Action, Joshua B. Fisher, Ambar Rivera, Ava Cison, Ashley Agatep, Kainani Tacazon, Sophia Spiegleman, Alison Mckenery, Rio E. Fisher, Reginald Archer, Jason A. Douglas

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Heat waves are increasing in frequency, intensity, magnitude, and duration, causing a disproportionate impact on marginalized communities exposed to urban heat islands. Newly emerging spaceborne thermal sensing instruments, such as ECOSTRESS and Hydrosat, now have the capabilities to measure urban surface temperatures accurately at the block level (< 100 m) and with enough frequency to capture transient heat waves (daily to subweekly). Such data are critical for monitoring and informing policy and mitigation efforts, such as resurfacing, green space, cooling stations, and medical mobilization. These serve to advance environmental justice and reduce health risks—and deaths—among the most vulnerable: minority, low-income, elderly, those with physical- and mental-health preconditions, unhoused, children, and outdoor workers. While scientists have increasingly used satellite data to quantify urban heat islands and risks to communities, there remains a significant gap in action resulting from such analyses—a figurative and literal “valley of death.” Reviewing over 500 scientific publications, we identify a critical lack of engagement with the communities being analyzed (10.9%; n = 58); yet, community engagement is key to bridging such analysis with subsequent action. Here, we demonstrate how participatory community engagement directly with data and analysis leads to increased policy changes and mitigation efforts. Our framework has immediate implications for how scientists may augment their work and thought processes to achieve …

Empowering Neurodiverse Talent In Cybersecurity Through Fair And Inclusive Ai Education, Sheikh Rabiul Islam, Yansi Keim, Mohiuddin Ahmed, Maanak Gupta, Ingrid Russell, Mahmoud Abdelsalam

Research outputs 2022 to 2026

Cybersecurity demands creativity, persistence, and sharp pattern recognition—strengths frequently reported among neurodivergent people (e.g., autism, ADHD, dyslexia). Yet AI-driven hiring pipelines can systematically disadvantage neurodivergent applicants by misreading communication styles or valuing narrow proxies of “fit.” Demand for cybersecurity talent is growing, and experts note that neurodiverse individuals are both underrepresented and highly valuable to security teams. However, progress remains uneven without targeted educational interventions [1]. We present a curricular module that simultaneously (a) centers neurodiversity as a strength in the cybersecurity workforce and (b) trains students to audit and redesign AI hiring systems using open-source fairness and explainability toolkits …

Molecular Detection Of Genes Encoded For Biofilm Formation In Bacteria Isolated From The Oral Cavity Of Patients, Tebarek Al-Taei, Ali A. Al-Hisnawi

Karbala International Journal of Modern Science

Background: A biofilm is a collection of the microbial cells attached to the surface that are encased in a matrix of extracellular polymers. Biofilm formation creates a physical and chemical barrier that prevents antibiotics from reaching bacterial cells, resulting in treatment failure and reinfection. The present study aimed to investigate the biofilm formation in bacteria isolated from the oral cavity of patients.

Methods: In this study, 150 bacterial isolates were obtained from tooth and gum surface swabs of male and female patients of different ages who visited specialized centers and dental clinics in Babylon City after they were clinically diagnosed …

A Virtual Community Math Circle, Skona Brittain, Sayonita Ghosh Hajra, Steve Heller, Daniel Hodgins, Peter Petto, Gabriella Pinter, Lauren Rose, A. Gwinn Royal, Asmita Sodhi

Journal of Math Circles

The Julia Robinson Mathematics Festival (JRMF) Community Math Circle is free, volunteer-run, and online. We collaborate with JRMF and use their activities in our events. Started during the pandemic, the Community Math Circle continues to thrive. We have about 40 participants attending every month, typically kids aged 6 to 13, teachers, facilitators, and other adults. This article describes how our event is organized, planned, and executed, and how we train facilitators. We will also offer reflections on our successes and challenges.

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.

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 …

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) …

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 …

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 …

Ai-Driven Malware Analysis And Detection: A Comprehensive Survey Of Techniques, Trends And Challenges, Salman Khan, Hasnat Raza, Mansoor Alam

Journal of Informatics and Web Engineering

Malware represents the most critical threat in cybersecurity, meant to compromise the security for any individual or any organization. These are covert software, designed to perform malicious act like data theft, data alteration, and to interrupt a normal operation of the services. The persistent evolution of malware has called for more sophisticated techniques in its detection and prevention, resulted into direct need of Artificial Intelligence in cybersecurity. Artificial intelligence, using machine learning techniques and rising concepts like neural networks has greatly improved the traditional static and dynamic ways of detecting malware. Advances in AI-driven solutions have made them much more …

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 …

Real-Time Posture Monitoring For Effective Exercise Using Mediapipe Python, Wan Izzul Wafiq Wan Noor Asmawi, S. Prabha Kumaresan

Journal of Informatics and Web Engineering

Maintaining proper posture during exercise is crucial for preventing injuries and maximizing workout efficiency. This project aims to develop a real-time posture monitoring system using MediaPipe and OpenCV to provide instant feedback on the exercise form. The system captures video input through a webcam, processes it using OpenCV, and utilizes MediaPipe’s pose-estimation model to detect key body landmarks. By analysing the joint angles and comparing them to predefined optimal postures, the system evaluates the user’s form and provides corrective feedback in real time. This approach eliminates the need for expensive wearable sensors, making posture monitoring more accessible and user friendly. …

Design And Implementation Of A Web-Based Lecture Timetable Scheduling System, Suraj Abubakar, Mohammed Kabir Dauda, Maryam Abdullahi Musa, Bala Muhammad Muhammad

Journal of Informatics and Web Engineering

Timetable management is a controversial but core administrative activity at tertiary learning institutions, normally saturated with timetabling clashes, resource wastage, and communication breakdowns. This study describes the development and validation of a Web-Based Lecture Timetable Scheduling System (WLTSS) for Abubakar Tafawa Balewa University (ATBU) Department of Computer Science. The system was implemented to automatically and effectively build, modify, and publicize lecture timetables. On Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), JavaScript, and React as frontend technologies, the system provides an adaptable interface with real-time data updates through the Reacts component model foundation. MySQL and Node.js are used to run …

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 …

Solar Wind–Magnetosphere Coupling During The September 2025 Cme: Multi-Spacecraft Analysis Using Mms And Omni Data, Skylar G. Butler, Margret Stanley

Student Research Symposium (SRS)

A sequence of two coronal mass ejections (CMEs) impacted Earth in early September 2025, producing consecutive geomagnetic disturbances. The first CME, launched on 31 August 2025 and observed as a halo in SOHO/LASCO imagery, reached Earth on 1 September (~20:45 UTC), generating a clear interplanetary shock. OMNI 1-min solar-wind data show a sudden rise in |B| from ≈ 5 nT to > 25 nT, proton density and velocity increases (≈ 350 → 600 km s⁻¹), and a southward IMF Bz interval that drove enhanced coupling. The Kyoto Dst index recorded a sudden storm commencement followed by a minimum of −75 nT …

Project G.L.E.N. (Enhancing Tornado Research: A Foundation For Transistioning The Enhanced Fujita Scale), Alexis Peshehonoff, Makaylei Huggins, Bernard Muich, Nicholas Fazzolari, Liam John, Harris Meyer, Jakob Graudons, Nicholas Krasznavolgyi, Stephen Syvertson, Aditya Bhattacharya, Kai Hong, Augustine Balish, Zachary Ort, Erin Rhoden

Student Research Symposium (SRS)

"Project G.L.E.N., formally known as “Enhancing Tornado Research: A Case for Transitioning the Enhanced Fujita Scale,” is an ongoing initiative aimed at advancing tornado research through the development and deployment of an unmanned tornado probe. Through the Gale Level Environmental Navigator (G.L.E.N.) probe, a remote-controlled unit equipped with specialized meteorological sensors and innovative design features, we aim to collect real-time, onsite data from within tornadoes. This approach allows for direct measurement of internal atmospheric conditions such as wind speeds, pressure fluctuations, temperature, humidity, and other storm dynamics while removing human risk from tornado interception, significantly enhancing the safety of storm …

Assessing The Threat Of Southern Pine Beetle To Pitch Pine In Acadia National Park, Caroline R. Kanaskie, Mark J. Ducey, Jeff R. Garnas

Faculty Publications

Many of the mountain summits of Acadia National Park (ACAD) are dominated by Pinus rigida (Pitch Pine). The ACAD Pitch Pine population is particularly valuable due to its position at the northernmost edge of the species’ range, its association with unique animal and plant communities, and its contribution to the aesthetics of the park. Pitch Pine is host to Dendroctonus frontalis (Southern Pine Beetle [SPB]). As the name suggests, SPB is native to the southeastern US, and can kill large numbers of healthy pines via mass-attack. With warming winters, SPB can establish and persist further north than ever before, presenting …