Digital Commons Network^™

Supply Chain Network Based On Blockchain And Intelligent Agent, Hiba Hamdi Hassan, Rana Fareed Ghani

Journal of Soft Computing and Computer Applications

In agricultural supply chains, the complexity and indeterminacy pose serious challenges to traceability, reliability and confidence today. This challenge is especially acute in the olive oil industry where adulteration, wrong labeling, and uneven chemical quality threaten the actual well-being of producers and consumers. The project aims to design a blockchain-based hybrid architecture with intelligent agents (FNNs) to enhance transparency, reliability and responsiveness in the olive oil supply chain. The Blockchain component enables a completely open, tamper-proof ledger to be built in a very decentralized way and preserved as an archive of every account of its transactions. The intelligent agents contribute …

Intelligent Extensible Markup Language Encryption Using Type-2 Fuzzy Logic, Faiez Musa Lahmood Alrufaye, Seham Ahmed Hashem

Journal of Soft Computing and Computer Applications

Financial and commercial institutions increasingly rely on Extensible Markup Language (XML) files as a standard means of exchanging data. However, this extensive use has created serious security challenges due to the fact that these files contain sensitive information such as bank card numbers and expiration dates. Relying on traditional full file encryption methods achieves a high degree of security, but it causes problems related to the large file sizes that consume memory and the long encryption and decryption times, which reduces the efficiency of systems when dealing with a large number of daily transactions. Methods based on Type-1 Fuzzy Logic …

Hate Speech Detection Using Optimized Feature Representation Via Spiral-Grey Wolf Optimizer-Based Machine Learning Approaches, Noor S. Farhan, Matheel E. Abdulmunim, Hasanen S. Abdullah

Journal of Soft Computing and Computer Applications

Hate speech detection is crucial as social media diversifies. This research present a lightweight, scalable system using traditional machine learning methods along with a new approach called Spiral-Grey Wolf Optimizer (S-GWO).

S-GWO effectively selects key features that consider both meaning and content from the Term Frequency Inverse Document Frequency (TF-IDF) space, leading to high-quality representation without excessive computing power.

The propoused system was tested on Arabic and another English datasets using six machine learning methods: SVM, RF, LR, KNN, NB, and SGD. It achieved 92% accuracy and F1 score on the Arabic dataset, while reaching 100% accuracy on the English …

A Method Of Heuristic Human-Llm Collaborative Source Search, Yi Chen, Sihang Qiu, Zhengqiu Zhu, Yatai Ji, Yong Zhao, Rusheng Ju

Journal of System Simulation

Abstract: Traditional source search algorithms are prone to local optimization, and source search methods combining crowdsourcing and human-AI collaboration suffer from low cost-efficiency due to human intervention. In this study, we proposed a lightweight human-AI collaboration framework that utilized multi-modal large language models (MLLMs) to achieve visual-language conversion, combined chain-of-thought (CoT) reasoning to optimize decision-making, and constructed a heuristic strategy that incorporated probability distribution filtering and a balance between exploitation and exploration. The effectiveness of the framework was verified by experiments. The human-AI alignment heuristic strategy with large language model adaptation design provides a new idea to reduce manual …

3d Point Cloud Analysis With Classification, Segmentation And Few-Shot Learning, Jiajing Chen

Dissertations - ALL

Deep learning for 3D point cloud analysis has made significant progress, yet several critical challenges, including the following, remain underexplored: (1) traditional max-pooling operations discard a substantial portion of learned features, resulting in information loss and inefficient use of computational resources; (2) existing few-shot point cloud classification models lack robustness when faced with occlusion, missing points, and limited training data; (3) semantic segmentation methods often fail to fully exploit background–foreground interactions, leading to reduced accuracy. Moreover, in domains such as gait recognition and visual program synthesis, research has been largely dominated by 2D-based approaches, leaving the potential of point cloud …

Advancements In Perfect Matchings Within Neutrosophic Fuzzy Graphs: Theory And Applications, Muhammad Saeed, Fatima Razaq

Neutrosophic Systems with Applications

Graph theory has been widely used in exemplifying relational structure, and a greater generalization to fuzzy and neutrosophic space enables the exemplification of uncertainty, indeterminacy, and inconsistency in complex systems. Some of these extensions include the neutrosophic fuzzy graphs that provide a more detailed description of the loose relations between the vertices and the edges. However, unlike in classical graph theory, where the concepts of matching and perfect matching are well developed, very little has been studied on how the two concepts can be extended to neutrosophic fuzzy graphs. To seal this gap, the current paper develops and defines the …

Integrating Mcdm Techniques For Optimized Task Offloading In Multi-Uav- Enaled Mobile Edge Computing System, Amira Salam

Neutrosophic Systems with Applications

Carefully choosing a task offloading strategy is crucial for optimizing task scheduling and offloading strategies in a multi-UAV system. Regarding cost, responsiveness, scalability, and data security, each strategy has pros and cons. As a result, selecting the best offloading technique is essential to multi-UAV mobile edge computing task scheduling optimization. A methodical and well-informed decision-making process accomplishes this.

The current study introduces a new hybrid methodology for the multi-criteria decision-making (MCDM) model, known as IVNs-DEMATEL-ANP-VIKOR. The purpose of this model is to find and choose an efficient task offloading strategy. With this method, we use IVNs-DEMATEL to show how different …

Tests Without Borders: A Global Approach To Measuring Visualization Literacy, Olivia A. Guess

McKelvey School of Engineering Graduate Student Theses & Dissertations

Visualization literacy assessments shape how we understand people's ability to interpret data, yet most existing instruments embed Western datasets and assumptions that limit their relevance for global audiences. This thesis argues that because data is personal, assessments must also be culturally grounded. We introduce a unified framework for adapting the Mini-VLAT into 22 regionally responsive short-form assessments, each retaining the structure of the original test while incorporating datasets and scenarios tailored to specific regions around the world. To demonstrate how such adaptations can be customized and validated, we present a detailed case study of a Ghana-adapted Mini-VLAT, developed in collaboration …

Ankimedbench: Evaluating Hierarchical Medical Knowledge In Language Model Embeddings, Neel Patel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Despite achieving over 90% accuracy on medical benchmarks, recent studies show physicians cannot effectively leverage language models to improve clinical reasoning. Current benchmarks test isolated factual recall, but clinical practice requires hierarchical navigation through diagnostic categories—starting broad and narrowing systematically from chest pain to cardiovascular pathology to myocardial infarction to specific STEMI types. Existing evaluations cannot measure whether models preserve this taxonomic structure essential for clinical reasoning.

We introduce AnkiMedBench, built from 16,512 medical flashcards used by students preparing for licensing exams. Cards are organized across six hierarchy levels spanning 16 broad medical specialties to 672 specific diseases and conditions. …

Parameter-Efficient Multimodal Adaptation: Ocr-Integrated Lora For Textvqa And Captioning, Karthik Ganesh Malini

Master's Theses

Vision-Language Models (VLMs) have emerged as transformative technologies for multimodal AI, yet they face significant hurdles in processing text-rich images required for enterprise applications like document understanding, medical imaging, and industrial inspection. Current VLMs struggle with accurate text extraction and reasoning, often exhibiting high hallucination rates and poor Optical Character Recognition (OCR) token utilization. To address these limitations, this research presents a comprehensive framework for optimizing parameter-efficient Low-Rank Adaptation (LoRA) fine-tuning strategies on state-of-the-art architectures, including LLaVA-1.5 and BLIVA-FlanT5. Our methodology integrates enhanced OCR token utilization, faithful caption generation, and specific hallucination mitigation techniques. We employ a multi-dimensional evaluation protocol …

Irregularities In The Dynamics Of Large Networks: Cases On Social Networks And The Internet, Dheeman Saha, Abdullah Mueen, Shuang Luan, Afsah Anwar, Yangsun Hong

Computer Science ETDs

Dynamic networks capture evolving relationships among entities, and irregularities in their behavior often signal significant events. This dissertation investigates such irregularities across social and infrastructural networks. First, we analyze Twitter (prior to its rebranding to X) to characterize influencers, introducing a follower-overlap similarity measure that identifies micro-influencers beyond content-based methods.

We then examine election-related irregularities by comparing suspended and non-suspended accounts during the 2020 U.S. presidential election, revealing behavioral patterns linked to misinformation and coordinated manipulation.

Next, we develop an algorithm to infer post-specific diffusion networks, reconstructing who-saw-from-whom pathways for tweets at scale. This method uncovers structural differences in diffusion …

Optimizing Military Fighter Jet Selection: A Decision Analysis Approach For Nuclear-Capable Aircraft, Eni Kelechi Ofong

Theses and Dissertations

This research investigates the strategic decision-making process involved in selecting a nuclear-capable fighter aircraft for NATO (North Atlantic Treaty Organization) nations in Europe. In adaptation to the continuously changing technology landscape and the necessity for enhanced deterrence capabilities, this study evaluates three potential aircraft: the legacy Panavia Tornado (PA-200), the widely deployed F-16 Fighting Falcon (F-16), and the advanced F-35 Lightning II (F-35). Each platform presents distinct advantages and limitations regarding operational performance, mission adaptability, cost-effectiveness, and long-term sustainability. To systematically assess these alternatives, the study employs various decision analysis frameworks, including Multi-Criteria Decision Analysis (MCDA), single dimensional value function …

Analytical Assessment Of Pedestrian Crashes On Low-Speed Corridors, Therezia Matongo, Deo Chimba

Civil and Architectural Engineering Faculty Research

This study presents a comprehensive statewide analysis of pedestrian-involved crashes recorded in Tennessee between 2002 and 2025. We evaluated the influence of roadway, traffic, environmental, and socioeconomic factors on pedestrian crash frequency and severity with substantial components focused on lighting impacts including dark and nighttime. A multi-method analytical framework was implemented, combining descriptive statistics, non-parametric tests, regression analysis, and advanced machine learning techniques including the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the gradient boosting model (XGBoost). Results indicated that dark and nighttime conditions accounted for a disproportionate share of severe crashes—fatal and serious injuries under dark conditions reached over 40%, …

Prism (Proxy Recognition And Inclusion Scoring Method), Destiny Raburnel, Crystal Tubbs, Md Abdullah Al Hafiz Khan

Symposium of Student Scholars

AI-driven automated hiring tools are reshaping how companies find talent, but they often reproduce the hidden biases embedded in their training data. Our project, PRISM (Proxy Recognition and Inclusion Scoring Method), investigates how subtle demographic signals, specifically first names associated with gender and race, influence AI resume screening even when candidates have identical qualifications. We built a controlled dataset of resumes that are identical in every way except for the applicant's first name, with each resume using a racially neutral surname to isolate how first names alone affect scoring. We tested these resumes against job postings in technology, healthcare, and …

Philosophy Of Culinary Arts: Reading Truth Through Language And Taste, Devi Dwi Purwanto, Aji Prasetya Wibawa, Syaad Patmanthara

Bulletin of Culinary Art and Hospitality

The development of Natural Language Processing (NLP) technology has transformed the way we analyze and understand culinary arts through a digital approach. NLP enables the transformation of empirical and sensory culinary knowledge into structured data that can be analyzed computationally. This technology opens up opportunities to explore the relationships between ingredients, techniques, and flavors in culinary arts, as well as to represent culinary reality in a more organized form. This study aims to identify how NLP can represent the relationships between ingredients, techniques, and flavors in culinary arts and their impact on the structure of culinary knowledge from an epistemological, …

Smart Pireps: Leveraging Technology To Simplify Pilot Weather Reporting In General Aviation, Emma Hellwege

Honors Projects

This honors project examines how emerging aviation technologies can support or automate components of Pilot Weather Reports (PIREPs) to improve reporting accuracy, reduce pilot workload, and increase participation within the general aviation (GA) community. PIREPs provide essential real-time weather observations—such as turbulence, icing, and visibility—that supplement automated systems and enhance situational awareness for pilots, air traffic control, and meteorologists. However, reports are vastly underutilized due to workload constraints, inconsistent training, voice-only submission methods, and technological disparities across the GA fleet.

Through a structured analysis of federal aviation documentation, sensor capabilities, human factors research, and recent advancements in automation, this study …

Integrating A “World -Class” Safety System Into Diverse Teams, Mark D. Keller

ASEM Capstones

2025 ASEM 620 Capstone Project

Environmental Risk Assessment Of Textile Waste From Bio-Engineered Fibers In The Fashion Industry, Aayush Pankaj Agarwal, Harshit Soral, Irmak Aktan, Karol Montserrat Gonzalez Saad, Maria Daniela Saa Espinosa, Sheetal Suhas Dhanuka, Yi Yang

Harrisburg University Dissertations and Theses

The global fashion industry generates over 92 million tons of textile waste annually, a figure projected to increase significantly by 2030. Bio-engineered fibers, including bacterial cellulose, mycelium-based leather, and recombinant protein textiles emerge as sustainable alternatives to conventional fibers. Despite their promise, recent evidence suggests that these fibers may pose environmental risks at the end-of-life stage, such as incomplete biodegradation in landfills, microfiber shedding, and chemical leaching from dyes and coatings. The purpose of this study is to examine how these risks are represented through scientific literature, corporate sustainability reports, and policy frameworks, and to identify strategies for integrating risk …

“Shaping Academic Teaching At The Crossroads Of Ethics And Artificial Intelligence”, Workshop At Warsaw University Of Technology, Warsaw, 25 September 2024, Julia Braniewska, Bartłomiej Skowron

Yearbook of Antitrust and Regulatory Studies

This document is a report on the workshop, “Shaping Academic Teaching at the Crossroads of Ethics and Artificial Intelligence”, which formed a component of the “Ethics and AI” conference hosted by Warsaw University of Technology.

Digital Solutions For Bridging Language Barriers: Designing And Testing An App For Construction Spanish Safety Communication On Construction Jobsites, Adrian Cappella

All Theses

Language barriers between English-speaking supervisors and Spanish-speaking workers create safety risks on U.S. construction jobsites. Hispanic workers face higher injury and fatality rates, with miscommunication being a major contributing factor. Existing translation tools lack the accuracy, cultural context, and jobsite relevance needed for effective safety communication.

In this study a mobile application with construction-specific safety phrases in English and Spanish was designed and field tested. The research included a literature review, phrase collection and validation with industry experts, application development and design with a computer science collaborator, and usability testing with supervisors and workers. Surveys and field trials measured navigation, …

Enhancing Ad/Adrd Management Through Ihelpcare: A Compliant And Culturally Sensitive Ai-Driven Digital Healthcare Platform, Trisha Bhowmick

Master's Theses

The digital healthcare field is expanding fast, and now it requires platforms that use advanced technology and maintain robust data security and compliance practices. In the present paper, we present the main structure, key methods, and compliance strategies of the digital healthcare system iHelpCare, which, while fully meeting the HIPAA/GDPR requirements, provides health services more accessible, efficient, and inclusive. The proposed platform is powered by AI for personalized care solutions, with the main emphasis on preventive health management and providing tools for people with disabilities.

iHelpCare achieves real-time patient monitoring while securing medical data management and easy communication between patients, …

Evaluating Psychosocial Stressors And Mental Well-Being Of Construction Professionals From The Management Standpoint: An Exploratory Study, Md Tauhidul Karim

Masters Theses

Construction professionals face persistent workplace stressors that undermine their mental well-being outcomes. Despite progress in general job-related stressors, social and interpersonal aspects of psychosocial stressors traditionally remain underexplored in the construction management research. The present study examines how social and interpersonal factors influence construction workers’ mental well-being and how management’s awareness, responsiveness, and strategic roles evolved in the transition of the COVID-19 pandemic at the organizational level. An integrative mixed-methods approach was employed, combining a systematic literature review, a bibliometric analysis, and an exploratory case study to capture the current landscape of mental well-being and management standpoints in the US …

Analyzing Patterns In Hofstede’S Cultural Dimensions Towards Individual Ai Receptiveness For Affective Experiences, Maggie Yang

Master's Theses

The use of artificial intelligence (AI) has significantly advanced efficient decision-making, with trust in algorithmic decisions shown to vary by cultural upbringing [1]. As AI becomes increasingly embedded in everyday life, it is essential to examine how cultural values affect trust in AI in subjective contexts that extend beyond purely quantitative analysis, like the personal interpretation of art. This work utilizes Hofstede’s cultural dimensions to investigate potential patterns in receptiveness towards AI predictions during art interpretation, providing insight into individual susceptibility to bias in AI-assisted affective analysis.

The study leveraged a cultural dimension survey and a custom Java program connected …

Evaluating Large Language Models For Requirements Engineering And Verification: A Comparative Analysis Of Gpt-5 And Gemini 3 Pro, Guadalupe Nevarez

Open Access Theses & Dissertations

Large Language Models (LLMs) are increasingly viewed as viable tools for Systems Engineering, yet empirical data regarding their effectiveness in generating engineering-quality requirements remains limited. This thesis compares the performance of GPT-5 and Gemini 3 Pro in generating system functional requirements for the Miner Guardian Drone, a prototype UAV designed for minefield remediation. Both models were provided with identical prompts and tasked with producing 15 functional requirements. Two independent raters evaluated the outputs using a nine-dimensional quality rubric aligned with IEEE 29148 and INCOSE guidelines to ensure rigorous assessment. The difference between the models was analyzed using descriptive statistics and …

Colaboración, Discurso Y Técnicas: La Resistencia Simbólica En El Sueño De La Sultana (Isabel Herguera, 2023), Nerea Cuenca-Orellana

GDI. Revista de investigación de Género, Diseño e Innovación

La película El sueño de la sultana (Isabel Herguera, 2023) reinterpreta el cuento utópico homónimo de Rokeya Sakhawat Hossain (1905) realizando una exploración visual que combina animación, archivo y testimonio. El presente trabajo propone un análisis de la obra desde cuatro puntos clave e interrelacionados: la autoría colaborativa y femenina, los discursos visuales, los lenguajes y técnicas, y las formas de resistencia simbólica con el objetivo principal de establecerla como un caso práctico de diseño feminista contemporáneo.

En primer lugar, se examina el proceso de creación de la película como práctica colaborativa transnacional, donde la animación se convierte en un …

Factors Affecting The Cost Of Dynamic Architecture During The Execution Phase, Lamiaa Mohamed Said Elsherif, Eman N. Shaqour, Abdullah Badawy Mohammed, Sherif Mohamed Sabry El Attar

HBRC Journal

This study is part of a larger study on the factors affecting the cost of dynamic architecture during three phases (design, execution and operation), A research paper on the design phase has been published. and we will specialize in this research by studying the execution phase.

This research study is based on identifying the main factors affecting the cost of dynamic, buildings by conducting a questionnaire and analyzing it statistically by using IBM SPSS Statistics 25. To get to the definition of dynamic architecture and Types of movement directions in dynamic buildings.

By studying each of the principles of movement …

Retrieval Augmented Framework For Deepfake Audio Detection, Avinash Saxena

Master's Theses

The widespread use of AI-based audio deepfakes threatens severely to undermine media integrity and public trust. Speech synthesis techniques have improved dramatically in voice conversion (VC) and text-to-speech (TTS) in recent years, making forgeries sound highly realistic, and concerns are raised about possible malevolent uses. Existing state-of-the-art techniques for identifying fake speech have proven to be effective in some cases but are still limited in application and robustness when faced with novel attacking strategies, different acoustic conditions, or alternative linguistic domains. To address some of these limitations, the current research presents a novel deepfake audio detection system based on personalized …

Transdisciplinary Perspectives On Ai: The Fourth Annual Conference Of The European Culture And Technology Laboratory, Connell Vaughan, Ioana Madalina Moldovan, Silivan Moldovan, Noel Fitzpatrick

Books/Book Chapters

The fourth annual conference of the ECT Lab+ was hosted by Technical University of Cluj-Napoca over two days in October 2024 at the Cluj Innovation Park. The conference brought together experts from the Arts, Humanities, Social Sciences, Technology, and other fields to discuss and reflect on the advent of Artificial Intelligence and how the associated technologies are transforming how we live, work and study. Under the title Transdisciplinary perspectives on AI: Alternative Histories, Current Practices and Possible Futures the conference moved beyond simplistic technophila and technophobia to consider whether we can co-evolve with these new technologies which combine machine learning …

Recognition Of Bangla And English Words In Bengali Texts Using A Modified Bert-Base-Ner Model, Md Parvez Hossain, Ohidujjaman Ohidujjaman, Mohammad Shorif Uddin, Mohammad Nurul Huda, Tetsuya Shimamura

Iraqi Journal for Computer Science and Mathematics

A fusion of Bangla and English words is frequently utilized, especially on social media. This phenomenon significantly hampers the learning and preservation of the Bengali language among future generations. This paper proposes a model to recognize Bangla and English words in Bengali texts. In addition, this study converts the detected English words into standard Bangla words. In this work, we redesign the BERT-base-NER model using the training input dataset. BERT is chosen for its strong contextual representation capabilities, which are well-suited to noisy and informal text. BERT-base-NER provides strong contextual embeddings but treats token labels independently, lacking explicit modeling of …

Predicting The Next Trending Hussaini Poems: A Machine Learning Approach Based On Textual And Engagement Features, Elaf Adel Abbas

AUIQ Technical Engineering Science

Hussaini’s poem videos have garnered substantial viewership on digital platforms; nevertheless, the determinants of why just a select number achieve “trending” status remain inadequately comprehended. This study presents a machine learning approach aimed at forecasting the trending potential of Hussaini poetry videos through the integration of text- and interaction-based variables. A dataset including 270 YouTube videos was generated, encompassing each video’s title and audience engagement parameters, including views, likes, comments, duration, and upload time. Textual attributes were converted using TF-IDF representations, whereas numerical attributes were standardized and amalgamated via a unified ColumnTransformer pipeline. Five machine learning classifiers—Naive Bayes, Logistic Regression, …