Digital Commons Network^™

Evaluating Chatgpt-5 For Misuse Case Diagram Generation: An Empirical Evaluation, Alia Alzarooni, Yasser Khan, Hassan Alsayegh, Mohamed El-Attar, Rima Grati

All Works

Misuse case diagrams are a widely adopted technique in security requirements engineering, enabling analysts to model adversarial threats and derive countermeasures early in the software development lifecycle. However, manual construction of these diagrams is prone to incompleteness and subjectivity, requiring significant security expertise. Large language models (LLMs) such as ChatGPT present a promising opportunity to automate this process, yet their effectiveness for generating structured security modeling artifacts remains largely unexplored. This paper presents an exploratory study evaluating ChatGPT-5's ability to generate misuse case diagrams directly from textual security requirements, using 12 case studies of varying complexity spanning small, medium, and …

Aoi-Aware Agentic Federated Mixture-Of-Digital-Twin Experts For 6g Vehicular Edge Intelligence, Asadullah Tariq, Mohamed Adel Serhani, Ikbal Taleb, Shayma Alkobaisi, Tariq Qayyum, Irfan Ud Din

All Works

Digital twin-enabled vehicular edge intelligence is expected to become a fundamental service paradigm for sixth-generation (6G) intelligent transportation systems. However, the performance of such systems depends not only on model accuracy, but also on the freshness of digital twin states, timeliness of inference, privacy-preserving model training, and efficient use of heterogeneous edge resources. Existing DT-assisted federated learning and edge mixture-of-experts solutions optimize digital twin synchronization, distributed learning, and sparse inference largely independently, without allowing digital twin states to actively govern expert specialization, expert refreshing, and distributed orchestration. Nevertheless, the joint problem of how digital twins should guide federated expert specialization, …

Drone Authentication System Using Radio Frequency Fingerprinting, Jamila Muhsen Alnuaimi, Shamma Ghaleb Almansoori, Noura Ahmed Alrumeithi, Richard Ikuesan

All Works

The widespread integration of unmanned aerial vehicles (UAVs) across domains such as logistics, surveillance, and emergency response has introduced critical security challenges, particularly unauthorized access, identity spoofing, and drone cloning. Traditional software-based authentication methods, including GPS tracking and encryption, have proven inadequate against advanced cyber-physical threats. This paper proposes a secure and automated drone authentication framework based on Radio Frequency (RF) fingerprinting, leveraging intrinsic hardware-level signal imperfections to generate unique and unclonable drone identities. Using Random Forest classifiers, the system captures, preprocesses, and analyses RF features to distinguish between authorized and unauthorized UAVs. Validation with real-world RF datasets demonstrates high …

Human Factors In Visual Attention: Gender Differences In Engagement With Male-Oriented Ads, Mohamed Basel Almourad, Emad Bataineh, Zelal Wattar, Mohammed Hussain

All Works

In today's competitive market, it is increasingly important to understand how visual design shapes customer behaviour. This study examines the decision drivers influencing female customers' purchase choices when buying male-oriented products as gifts, identifying the visual components of advertisements that attract them by analysing the relationship between purchase intention and visual attention. Results show that participants with higher purchase intent focused more on product imagery and branding, indicating that visual appeal, perceived quality, and brand familiarity significantly guide their decisions, with brand awareness speeding up decision-making by reducing the need for repeated visual checks. Conversely, those with low purchase intent …

Towards A Context-Aware Driving Assistance System (Ca-Das): Advancing Intelligent Vehicular Safety Through Multimodal Context Integration, Fatma Outay, Siham Farrag, Anjum Zameer, Ansar Yassar

All Works

Driving-related behavioural factors are responsible for 90% of traffic collisions. The rapid growth of urbanization and the complexity of the traffic conditions demand a smart, efficient, and flexible transportation system. The advancement of transportation through technologies such as the Internet of Things (IoT) and AI have reshaped the way that drivers interact with their vehicles and the surrounding environment. In this paper, we propose a comprehensive Context-Aware Driving Assistance System (CA-DAS) that employs sensor fusion, semantic context modelling, along with a machine-learning-based approach to provide personalised and proactive driving assistance across dynamic scenarios. The proposed CA-ADS was developed using a …

From Image To Insight: Evaluating Llm Accuracy In Understanding Uml Use Case Diagrams With Claude, Mohamed El-Attar, Yasser Khan, Mahmood Niazi, Sajjad Mahmood, Mohammad Alshayeb

All Works

UML use case diagrams are a prominent artefact of requirements engineering, capturing the functional scope of a software system in terms of actors, use cases, and their stereotyped relationships. The emergence of multimodal large language models with image understanding capabilities raises the question of whether such models can reliably extract structured construct-level information from use case diagram images. This paper reports an empirical evaluation of Claude on the task of counting 14 notational construct types from a corpus of 78 computer-generated UML use case diagrams, assessed against manually verified ground truth annotations. Results reveal a strongly differentiated accuracy profile: Claude …

Epistemic Edge: Subjective Logic Guardrails For Llm-Driven Iot Actuation, Muntaser Syed, Marius Silaghi

Electrical Engineering and Computer Science Student Publications

Deploying large language models (LLMs) as decision-making agents in safety-critical Internet of Things (IoT) systems introduces risks that purely behavioral guardrails, such as action whitelists, cannot fully address. This paper presents Epistemic Edge, a four-tier neuro-symbolic pipeline that augments LLM-driven actuation with subjective logic (SL) uncertainty quantification, temporal decay, and dual guardrails combining epistemic threshold checks with behavioral whitelists. We evaluate seven locally-deployed models: three PrismML Bonsai 1-bit models (1.7B, 4B, 8B), three 4-bit quantized models (Qwen3-8B, Llama 3.2-3B, Phi-3.5-mini), and the DeepSeek-R18B reasoning model, across eight ablation conditions and five IoT actuation scenarios (2,800 controlled trials). We further validate …

A Virtual Model Of Data Centre Cooling, Younis Osama Abdelsalam, Tim Persoons, Sajad Alimohammadi

Research Outputs: 2025-Present

This study presents a calibrated, hybrid spreadsheet-based model developed to simulate the cooling energy consumption of a commercial-scale data centre in Dublin, Ireland. The model leverages five years of high-resolution, sub metered data, including chilled water flow rates, ambient conditions, and IT electrical load, offering a rare empirical foundation for system-level energy analysis. Existing modelling approaches often rely on simplified laboratory case studies, synthetic datasets, or isolated component analysis, limiting their relevance to operational facilities. This study introduces an innovative hybrid modelling framework that bridges the gap between black-box machine learning and rigid physics-only simulations. A key innovation is the …

Predictive Analytics For Optimising Delivery Performance In Supply Chain Management, Vishwanath Sai Krishna Teja

ICT

Supply chain management has always been a challenging area where delivery delays stand as one of its main ongoing issues. Many companies continue to use outdated data collection systems despite the advancements in data collection tools. This study investigates how predictive analytics can help companies to prevent their operational problems from reaching their customers.

In this study, two datasets were used. The first is the Data Co Smart Supply Chain dataset which covers order level operations from 2015 to 2018, and the second is the World Bank Logistics Performance Index, which covers logistics quality across more than 160 countries. After …

Balancing Accuracy And Discovery: A Bias-Aware Evaluation Framework For Music Recommendation, Jose Luis Maidana

ICT

Music recommender systems play an important role in helping users navigate large catalogues, but their reliance on historical interaction data can reinforce popularity bias and limit the visibility of less popular, long-tail items. This research develops and evaluates a bias-aware framework for assessing and mitigating popularity bias in music recommendation using implicit user-item interaction data. The study first quantifies popularity bias through inequality and long-tail metrics, before evaluating two baseline recommender approaches: a non-personalised Most-Popular model and a personalised Matrix Factorisation model. Their performance is assessed using both predictive accuracy measures, including Precision, Recall and NDCG, and beyond-accuracy measures relating …

Association Of Mhc Class Ii Gene Polymorphisms With Gastroenteritis Susceptibility In Shiraz Cats, Taghrid Hamza, Basma M Hendam, Ahmed Ateya, Usama Abou-Ismail

Mansoura Veterinary Medical Journal

BACKGROUND: The aim of this study is to consider the genetic alterations in the major histocompatibility complex (MHC) gene and its effect on Gastroenteritis tolerance/susceptibility in Shiraz cats.

METHODS: Blood samples were collected into tubes containing EDTA as anticoagulant from twenty Shiraz Tom cats (10 healthy and 10 suffering from gastroenteritis) to extract DNA. Then, PCR was performed to amplify a 500-bp fragment of the MHC gene.

RESULT: Genetic analysis via PCR-DNA sequencing identified specific single-nucleotide polymorphisms (SNPs) within the MHC gene, namely A115C, G399T, and A363G. The A363G variant was linked to increased disease risk (OR=13.44), while …

Gliders On The Sca Model, Alexa Renner

Mathematical Sciences Technical Reports (MSTR)

The Stranded Cellular Automata (SCA) model consists of a grid of cells which can each contain between zero and two strands apiece and two turning rules that control when strands turn and when they cross. While patterns on this model have been studied previously, such research has not needed an algebraic description of the model. We provide a formal algebraic definition of patterns on the model, define gliders on the model in a way which is semi-compatible with definitions of gliders in other cellular automata models, and classify all 1- and 2-stranded gliders on this model. In addition, we prove …

Against Doctrinal Siloing: Harmonizing Fiscal Federalism And The U.S. Constitution, David Gamage, Darien Shanske

Faculty Publications

This Essay argues that constitutional law’s treatment of fiscal federalism has fractured into a bewildering collection of doctrinal silos. Federal spending that pressures states, federal preemption of state taxes, the Dormant Commerce Clause, sovereign immunity, Section 5 of the Fourteenth Amendment, and the federal taxing power are all analyzed through distinct tests, even when they implicate the same basic conflict between federal authority and state fiscal autonomy. The result is not just theoretical confusion but inconsistent constitutional answers. Current doctrine can protect states from comparatively modest liabilities while leaving uncertain whether Congress may displace large swaths of state revenue authority. …

Exercise Rehabilitation And Functional Capacity In An Older Adult Cancer Survivor, Ibsaa G. Benti

Research Papers

No abstract provided.

Therapeutic Landscape Of Early Symptomatic Alzheimer's Disease Translated Into Everyday Practice For Geriatric Providers., Melissa J Bailey-Taylor, Paula Morrow, James Hendrix, Katherine E. Galluzzi, Golnosh Sharafsaleh

PCOM Scholarly Works

Alzheimer's disease (AD) accounts for 60-80% of all dementia cases. Recent advances in diagnostic biomarkers of early symptomatic AD (ie, mild cognitive impairment and mild dementia due to AD) and amyloid-targeting therapies (ATTs) have the potential to improve outcomes for patients with AD. Two ATTs (donanemab and lecanemab) are currently approved and available for use in the US. Both ATTs can slow disease progression as well as cognitive and functional decline in patients with early symptomatic AD. Treatment with ATTs is associated with specific safety concerns such as amyloid-related imaging abnormalities. Therefore, the benefit versus risk profile needs to be …

The Middle School Transition: Exploring Student Perceptions On The Transition From Elementary To Middle School, Cody T. Weed

Education Dissertations

The purpose of this study was to understand middle school students’ perceptions of their transition from elementary school to better learn the interactions and dynamics that unfold between them and their immediate environment. The middle school transition is a pivotal developmental phase marked by significant logistical, academic, and social–emotional challenges. Grounded in transition theory, the 4S framework, and stage-environment fit theory, this research explores the interactions between students and their new environment. Utilizing an embedded design mixed-methods approach, this study surveyed sixth-grade students at a public middle school in Eastern Washington. The goal was to illuminate students’ needs and concerns …

Pat Conroy First Edition Book Collection - Accession 1747, Donald Patrick Conroy

Manuscript Collection

The Pat Conroy First Edition Book Collection consists of first edition publications authored by Donald Patrick “Pat” Conroy (1945–2016), an acclaimed American novelist whose work is closely associated with the cultural, social, and physical landscapes of the South Carolina Lowcountry. Many of the volumes in this collection are signed by the author, enhancing their research and evidentiary value.

The collection spans Conroy’s literary career from his debut memoir The Boo (1970) through The Death of Santini (2013), a reflective work that revisits characters and themes central to his earlier writings. Included are major novels, memoirs, and nonfiction works such as …

Pxaa: A Root-Cause Decision-Support System For Airline Passenger Complaints Using Sentiment Analysis And Complaint Classification, Adélia Acacio Da Silva, Stefani Rabelo De Campos Nunes

ICT

PXAA (Passenger Experience Analytics Assistant) is a machine learning and decision-support prototype developed to analyse airline passenger complaints using sentiment analysis and complaint classification techniques. The project follows the CRISP-DM methodology and uses airline passenger reviews collected from AirlineQuality.com through Python web scraping. Natural language processing (NLP) techniques were applied to clean and preprocess the textual data, while logistic Regression was used to classify passenger sentiment into positive, negative and neutral categories.

The project also implemented rule-based complaint classification to identify common complaint themes such as delays, baggage issues, customer service problems, comfort issues, payments/refund complaints and communication failures. These …

Design And Evaluation Of A Supervised Machine Learning-Based Intrusion Detection System., Tarquin Qazi

ICT

This project involves designing and evaluating a supervised machine-learning-based intrusion detection system (IDS) using the CIC-IDS2017 dataset. The project is structured around the cross-industry standard process for data mining (CRISP-DM) framework. The dataset comprises over 2.8 million labelled instances and was cleaned and reduced from 78 to 63 features via redundancy analysis. These data were used to train and tune three supervised classifiers: Logistic Regression algorithm as a linear baseline, a Decision Tree algorithm and a Random Forest algorithm. Hyperparameter optimisation was conducted using RandomizedSearchCV with 3-fold cross-validation, optimising for the F1-macro scoring metric.

While the random forest performed similarly …

Comparative Economic Impact Modelling Of Floods Vs Drought On A Global Scale, Diogo Lemos Aguiar, Paulo Henrique Oliveira Machado

ICT

Climate change is generating unprecedented economic losses through extreme weather events, yet comparative predictive analysis between different hazard types remains limited. This report presents a Machine Learning–Based Comparative Economic Impact Modelling System designed to predict and compare the economic damages caused by floods and droughts on a global scale. The system integrates historical disaster records from the EM-DAT International Disaster Database with country-level socioeconomic indicators from the World Bank's World Development Indicators, applying supervised regression modelling to a unified dataset of 1,301 disaster events across 133 countries from 2000 to 2025. XGBoost and a Multi-Layer Perceptron Neural Network were evaluated …

Predicting Co₂ Emissions From Cattle-Driven Deforestation In The Amazon Rainforest Using Machine Learning, Daniel Ambrosio, Suelen Rocha

ICT

Deforestation has become a major environmental issue worldwide, especially in the Amazon Rainforest, which is known as one of the world’s largest carbon sinks. This region has been significantly impacted by cattle farming, contributing to increased CO₂ emissions and land degradation. As Brazil is one of the world’s largest beef producers and exporters, the environmental impact of livestock production has attracted increasing attention from organisations, governments, and sustainability analysts.

This project aims to analyse the relationship between cattle farming, deforestation, and CO₂ emissions in the Amazon using Machine Learning. Using the CRISP-DM framework, the project explored each stage of the …

A Review On Biomass-Derived Hard Carbon Anodes For Sodium-Ion Batteries : From Carbon Precursors To Storage Mechanisms, Anqi Lu, Jiaqian Qin

Journal of Metals, Materials and Minerals

The rapid development of sustainable energy technologies has intensified the demand for cost-effective and high-performance energy storage systems. Sodium-ion batteries (SIBs) are regarded as one of the most promising alternatives to lithium-ion batteries (LIBs) owing to their low cost, abundant sodium resources, and similar electrochemical mechanisms to LIBs. Hard carbon (HC) has attracted significant attention as the predominant anode material for SIBs due to its low cost, structural tunability, and availability from diverse precursors. Nevertheless, challenges remain, including the unclear Na+ storage mechanism, limited rate capability, and strong dependence on precursor type. This review systematically summarizes recent advances in HC …

Mechanical Properties And Crystallization Of Polybutylene Terephthalate Reinforced With Glass Flakes And Aluminum Powder, Nattakarn Hongsriphan, Pajaera Patanathabutr

Journal of Metals, Materials and Minerals

This research investigated mechanical properties and crystallization of poly(butylene terephthalate) composites by adding glass flakes (GF) and aluminum particles (Al). The concentration of the GF was 3 wt% or 5 wt%, and the Al was 0.5 wt% or 1.0 wt%. The stress-strain curves of the PBT-based composites showed yielding and necking. The PBT/GF/Al composites with GF/Al ratios of 3/0.5 wt/wt%, 3/1.0 wt/wt%, 5/0.5 wt/wt%, and 5/1.0 wt/wt% had Young’s moduli of 11.44%, 11.70%, 16.81%, and 19.31% higher than that of neat PBT, respectively. In the presence of Al at 1.0 wt%, the flexural modulus of the PBT/GF/Al composites increased to …

Synthesis, Structure, And Electrochemical Properties Of The Ni(Oh)2/Nimoo4 Composite On The Rgo/Nf Template For Hybrid Battery-Supercapacitor Electrodes, Retno Asih, Haniffudin Nurdiansah, Rogabe Sianipar, Ida Ayu Gayatri, Lukman Noerochim, Diah Susanti, Isao Watanabe, Darminto Darminto

Journal of Metals, Materials and Minerals

The growing demand for renewable and sustainable energy has intensified research on advanced energy-storage systems that can deliver both high energy and power densities. In this study, a Ni(OH)2/ NiMoO4 composite on a reduced graphene oxide/nickel foam (rGO/NF) template was synthesized through a hydrothermal and electrodeposition route to construct a hybrid battery-supercapacitor electrode. The unique hierarchical design combines the pseudocapacitive activity of Ni(OH)2/NiMoO4 with the excellent conductivity of rGO and the high surface area of NF, enabling efficient electron and ion transport. Structural and morphological analyses confirm the successful formation of the Ni(OH)2/NiMoO4/rGO/NF architecture. The electrode exhibits a specific capacitance …

Effect Of Cu Content On Microstructure, Morphology, And Antibacterial Properties Of Ti-Cu Alloy Thin Films, Chittra Kedkaew, Phalakorn Khwansungnoen, Tanattha Rattana

Journal of Metals, Materials and Minerals

Ti-Cu alloy thin films exhibit considerable potential for the development of advanced antibacterial surfaces, particularly for biomedical applications. In this research, Ti-Cu binary alloy thin films with a wide range of Cu content from 25.8 at% to 77.8 at% were deposited using magnetron co-sputtering with pure Ti and Cu as the targets. The composition of Cu in the films can be controlled by the applied power of Cu targets. This study investigated the effect of Cu content on the microstructural, morphological, and antibacterial properties using X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), Atomic force microscopy (AFM), X-ray photoelectron …

Contributions Of Carbon Content And Cooling Rate On Phase Transformations And Mechanical Properties Of Sintered Fe-1.5cr-0.2mo-Xc Alloys, Mantana Yaruan, Wantana Koetniyom, Thanyaporn Yotkaew, Nattaya Tosangthum, Ruangdaj Tongsri

Journal of Metals, Materials and Minerals

Microstructural development in sintered Fe-1.5Cr-0.2Mo-xC alloys, produced under different cooling rates of 0.1℃∙s‒1 and 5.4℃∙s‒1, was investigated. It was found that, in slowly sintered Fe-1.5Cr-0.2Mo-xC alloys, the microstructure changed from hypoeutectoid to eutectoid and to hypereutectoid steel microstructural features with increasing carbon content. Under the fast-cooling rate of 5.4℃∙s‒1, the microstructural change with respect to the increase of carbon content involved the competition between the formation of ferrite + carbide mixture and that of martensite-austenite constituent. The increase of tensile strength of slowly cooled sintered Fe-1.5Cr-0.2Mo-xC alloys with increasing carbon content was attributed to …

Effect Of Garnet Incorporation On The Functional Properties Of Sunscreens, Parinya Chakartnarodom, Kanyarat Munmani, Sureerat Polsilapa, Duangrudee Chaysuwan, Wichit Prakaypan, Passakorn Sonprasarn, Edward Laitila, Nuntaporn Kongkajun

Journal of Metals, Materials and Minerals

Garnet, a silicate mineral, was investigated as a replacement for the TiO2-based compound in sunscreen formulations. Samples containing garnet were evaluated for color shade, viscosity, sun protection factor (SPF), and water resistance. Substituting the TiO2-based compound with garnet reduced both viscosity and SPF but markedly enhanced water resistance. This improvement is attributed to the physical reinforcement provided by garnet particles, which strengthen the sunscreen film and reduce wash-off under water exposure. Garnet incorporation also altered the product’s appearance from white to a darker brownish-beige tone, improving visual compatibility with a wider range of skin tones.

Effects Of Welding Currents On Microstructure And Corrosion Behaviors Of Inconel 625 Cladding On 2.25cr-1mo Steel By Hot-Wire Tig, Supparat Saeheng, Hein Zaw Oo, Prapas Muangjunburee

Journal of Metals, Materials and Minerals

Hot-wire tungsten inert gas (HW-TIG) cladding has been applied to the steam turbine rotor welding repair. This study investigated the effects of welding currents on microstructure, hardness, and corrosion behavior. The experiments were conducted using four different welding currents applied to bead-on-plate Inconel 625 welds on a 2.25Cr-1Mo steel substrate as the steam turbine rotor material. The selected welding currents were 125 A, 150 A, 175 A, and 200 A. The percentages of weld dilution for different welding currents were also evaluated. Higher welding currents increased weld dilution, weld bead width, and HAZ size. As the welding current increased, the …

Properties And Printability Of Polylactic Acid Films : An Effect Of Polyglutamate Coated Natto As A Bio-Plasticizer, Natrata Thitinardwong, Thira Chavarnakul, Kawee Srikulkit

Journal of Metals, Materials and Minerals

Polylactic acid (PLA) film, a biodegradable alternative to petroleum-based plastics, has gained significant attention for sustainable packaging applications. However, its limited screen-printability remains a barrier to broader commercial use. This study aims to enhance the screen-printability of PLA film by incorporating a polyglutamate coated natto (designated as Nat-M). PLA/Nat-M films having 1%, 3%, and 5% Nat-M were prepared and evaluated for their key performance indicators, including ink adhesion (ASTM D3359), tone reproduction accuracy, and printing resolution. The screen-printing resolution was optimized between 400 DPI and 500 DPI (dots per inch) to achieve optimal tone reproduction and edge sharpness. Additionally, ink …

A Top-Electrode-Based Liquid-Solid Triboelectric Nanogenerator For Energy Harvesting And Ethanol Detection, Subrat Bhol, Nakul Charan Sahu, Sunit Gaurav Mohanty, Vicky Raj Maddala, Basanta Kumar Panigrahi, Premkumar Bhosale

Journal of Metals, Materials and Minerals

Liquid-solid triboelectric nanogenerators (LS-TENGs) offer a promising avenue for self-powered energy harvesting and sensing by exploiting contact electrification at fluid-dielectric interfaces, where droplet dynamics drive charge separation for electrical output without external power. In this work, a top-electrode LS-TENG was fabricated using a polytetrafluoroethylene (PTFE) film on a PMMA substrate with deionised water droplets, achieving an open-circuit voltage of ‒3.4 V, short-circuit current of 3.6 μA, and peak power of 1.48 nW at 100 MΩ under optimised conditions of 2 cm drop height, 45° tilt, and 50 μL volume. Performance scaled with droplet kinetics and volume due to enhanced contact …