Digital Commons Network^™

A Parallel Methodology For Early Fake News Detection Based On Hybrid Features On Social Media, Asmaa Mohemed Elsaieed Dr

Journal of Engineering Research

The increased use of social media platforms has made it easier to publish and distribute news items, but it has also opened up new opportunities for distributing fake news. Fake news is information that has been written with the goal of misleading or deceiving readers. As a result, there is a need for efficient false news identification tools where the information can be gathered from the text of posts or from publicly available social data (such as user information or feedback on articles or the social network). The detection of fake news in its early stages is a major challenge. …

Optimizing Resume Authenticity And Ats Compatibility With Llm Feedback Integration, Katie He, Justin Lau

College of Engineering Summer Undergraduate Research Program

Resume generation using Large Language Models (LLMs) like ChatGPT is becoming increasingly popular for automating the creation of customized resumes, but significant user modification is often required before submission. Common issues include poor alignment with job descriptions, inflated qualifications, and lack of authenticity, which undermine the effectiveness of LLM-generated resumes. This project addresses these challenges by integrating feedback from Applicant Tracking Systems (ATS) to guide LLMs in producing resumes that accurately reflect an applicant’s qualifications and better align with job-specific requirements. By optimizing the model's output through ATS feedback, the project aims to create more authentic, tailored, and ATS-compatible resumes, …

Attitude Control Of A Flexible Flapping Wing Uav Based On Fuzzy Logic, Reed M. Paulson, Tyson Chen, Diego Del Real, Nico Morrison

College of Engineering Summer Undergraduate Research Program

This project revolves around creating an a attitude controller for a hovering flexible flapping wing UAV that is based on a flying hummingbird. We based our model from a paper by Banazadeh and Taymourtash1 , First replicating the open-loop results using the nonlinear dynamic model and the equations of motion (seen below) while considering aerodynamic loads. Once replicated, we then used fuzzy logic to model the dynamic model. Subsequently, we designed a fuzzy controller to stabilize the hovering mode. We then considered and detailed future work needed to make further progress in this area.

Investigating Gender Bias In Large Language Models Through Text Generation, Shweta Soundararajan, Sarah Jane Delany

Conference papers

Large Language Models (LLMs) have swiftly become essential tools across diverse text generation applications. However, LLMs also raise significant ethical and societal concerns, particularly regarding potential gender biases in the text they produce. This study investigates the presence of gender bias in four LLMs: ChatGPT 3.5, ChatGPT 4, Llama 2 7B, and Llama 2 13B. By generating a gendered language dataset using these LLMs, focusing on sentences about men and women, we analyze the extent of gender bias in their outputs. Our evaluation is two-fold: we use the generated dataset to train a gender stereotype detection task and measure gender …

Unveiling Similarities In The Code Of Life: A Detailed Exploration Of Dna Sequence Matching Algorithm, Mahmoud Y. Shams, Romany M. Farag, Dalia A. Aldawody, Huda E. Khalid, Ahmed K. Essa, Hazem M. El-Bakry, A. A. Salama

Neutrosophic Systems with Applications

Identifying similar DNA sequences is crucial in various biological research endeavors. This paper delves into the intricate workings of a specific algorithm designed for this purpose. We provide a systematic explanation, exploring how the algorithm handles user input, reads stored DNA sequences, utilizes the Word2Vec model for vector representation, and calculates sequence similarity using diverse metrics like Cosine Similarity and Neutrosophic Distance. Additionally, the paper explores the incorporation of neutrosophic values to account for uncertainty in the comparisons. Finally, we discuss the extraction of results, including matched sequences, similarity scores, and accuracy measures. This in-depth exploration provides a clear understanding …

An Approach To Multi-Attribute Decision-Making Based On Single-Valued Neutrosophic Hesitant Fuzzy Aczel-Alsina Aggregation Operator, Raiha Imran, Kifayat Ullah, Zeeshan Ali, Maria Akram

Neutrosophic Systems with Applications

A single-valued Neutrosophic hesitant fuzzy set (SVNHFS) is a combination of a single-valued neutrosophic set (SVNS) and hesitant fuzzy set (HFS) that has been developed to address insufficient, unreliable, and vague environments in which each element has several possible options determined by the truthiness, indeterminacy and falsity value. By considering this, in this paper, we have proposed the Aczel-Alsina aggregation operator (AAAO) for SVNHFS, which is more flexible t-norm and t-conorm than the other and due to the flexible nature of parameters to solve Multi-Attribute decision making (MADM) problems. Further, the score function, accuracy function, and certainty function of SVNHFS …

An Agent-Based Approach For Designing A Sustainable Supplier Selection In Stochastic Environment: A Simulation Study, Sheida Etemadidavan

Engineering Management & Systems Engineering Theses & Dissertations

In the 21st century, businesses are constantly striving for competitive advancement and increasing their economic performance in the rapidly changing market. Collaboration with other businesses and partnerships with them are becoming more common. As such, businesses are starting to invest in finding the right partners to stay competitive in an ever-changing business landscape. Suppliers play a crucial role in businesses' decision-making as they provide the materials, goods, and services necessary for a company to operate and succeed. Therefore, their selection, management, and relationship must be carefully considered to ensure optimal performance and profitability. A sustainable framework in a business's relationship …

Evaluation Of Renewable Energy Sources For A Sustainable Future: A Multi-Criteria Decision-Making Approach, Mai Mohamed, Asmaa Elsayed

Neutrosophic Systems with Applications

The urgent global challenges of climate change, energy security, and environmental degradation highlight the need for sustainable energy solutions. Renewable energy sources (RES) present a viable pathway towards sustainability by mitigating greenhouse gas emissions, reducing reliance on fossil fuels, and fostering economic resilience. Purpose: The purpose of this paper is to propose an advanced Multi-Criteria Decision-Making (MCDM) approach to evaluate various RES by integrating environmental, economic, technological, social acceptance, and resource availability criteria, to identify the most suitable RES for sustainable energy solutions. Methodology: The study employs a hybrid method combining Type-2 Neutrosophic Numbers (T2NN) with LOPCOW (Logarithmic Percentage Change …

Mention Detection In Turkish Coreference Resolution, Şeni̇z Demi̇r, Hani̇fi̇ İbrahi̇m Akdağ

Turkish Journal of Electrical Engineering and Computer Sciences

A crucial step in understanding natural language is detecting mentions that refer to real-world entities in a text and correctly identifying their boundaries. Mention detection is commonly considered a preprocessing step in coreference resolution which is shown to be helpful in several language processing applications such as machine translation and text summarization. Despite recent efforts on Turkish coreference resolution, no standalone neural solution to mention detection has been proposed yet. In this article, we present two models designed for detecting Turkish mentions by using feed-forward neural networks. Both models extract all spans up to a fixed length from input text …

Enhancing Dtc Control Of Im Using Fuzzy Logic And Three-Level Inverter: A Comparative Study, Siham Mencou, Majid Benyakhlef, Elbachir Tazi

Turkish Journal of Electrical Engineering and Computer Sciences

Direct torque control is the most appropriate strategy for induction motor drive systems, due to its considerable ability to reduce the impact of of machine parameter variations, while offering fast dynamic response and simplified control implementation. However, persistent problems associated with high torque ripple and variable switching frequencies prevent its widespread adoption. To overcome these limitations, several techniques have been developed, in particular the use of multi-level inverters and fuzzy logic algorithms. This article proposes an in-depth evaluation of these techniques in a MATALB/Simulink environment, under various operational conditions. The main objective is to provide a detailed performance analysis of …

Text-To-Model Transformation: Natural Language-Based Model Generation Framework, Aditya Akundi, Joshua Ontiveros, Sergio Luna

Mechanical Engineering Faculty Publications

System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though NLP effectively extracts and analyzes raw text data, such as text-based requirement documents, to assist in design specification, natural language, inherent complexity, and variability pose challenges in accurately interpreting the data. In this paper, we explore the integration of NLP with SysML to automate the generation of system models from input textual requirements. We propose a model …

Neuro-Symbolic Ai For Deep Analysis Of Social Media Big Data, Vedant Khandelwal, Manas Gaur, Ugur Kursuncu, Valerie Shalin, Amit P. Sheth

Faculty Publications

This tutorial introduces a neuro-symbolic AI framework to analyze big data from social media platforms. Integrating human-curated knowledge through symbolic AI with the pattern recognition capabilities of neural networks enhances the adaptability and efficiency of traditional neural network approaches. Knowledge-guided zero-shot learning techniques enable swift adaption to new linguistic contexts and emerging events [6]. Participants will explore how to design, develop, and utilize these models in specific domains, such as public health surveillance, that require dynamic adaptation to new terminologies. This session The tutorial aims to equip attendees with practical skills and a deep understanding of how to apply neuro-symbolic …

Utilizing Deep Learning In Smart Glass System To Assist The Blind And Visually Impaired, Asmaa A. Hekal, Mohamed S. Sharaf, Ahmed A. Sayed, Ibrahim R. Abdelrahman, Ahmed A. Salem, Ahmed M. Elhussieny, Saeed Y. Kouta, Eman S. Abass

Future Engineering Journal

This paper presents a groundbreaking assistive technology designed to empower visually impaired individuals in their daily lives. With an estimated global population of 2.2 billion facing visual impairments, addressing the challenges they encounter is of paramount importance. The research introduces a comprehensive electronic device integrating advanced computer vision and deep learning techniques. The system incorporates real-time object detection, robust facial recognition, and precise currency denomination identification. Powered by a Raspberry Pi 4 Model B+ and an ESP32-CAM Development Board, the device offers users unparalleled environmental awareness. Utilizing YOLOv4-tiny for object detection and a hybrid face recognition model combining HaarCascades, Histogram …

Aligning Human And Computational Coherence Evaluations, Jia Peng Lim, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Automated coherence metrics constitute an efficient and popular way to evaluate topic models. Previous work presents a mixed picture of their presumed correlation with human judgment. This work proposes a novel sampling approach to mining topic representations at a large scale while seeking to mitigate bias from sampling, enabling the investigation of widely used automated coherence metrics via large corpora. Additionally, this article proposes a novel user study design, an amalgamation of different proxy tasks, to derive a finer insight into the human decision-making processes. This design subsumes the purpose of simple rating and outlier-detection user studies. Similar to the …

Climate Change Prediction Model Using Mcdm Technique Based On Neutrosophic Soft Functions With Aggregate Operators, Kainat Muniba, Muhammad Naveed Jafar, Asma Riffat, Jawaria Mukhtar, Adeel Saleem

Neutrosophic Systems with Applications

The increasing impact of climate change necessitates innovative approaches in modeling and prediction to mitigate its adverse effects. This paper introduces a novel methodology integrating Neutrosophic Soft Functions (NSFs) into climate change prediction frameworks. NSFs, a hybrid of Neutrosophic Set Theory and Soft Set Theory, provide a flexible framework for handling uncertain and imprecise information inherent in climate data. This study explores the application of NSFs in capturing the complex interplay of various climatic variables, including temperature, precipitation, humidity, and atmospheric pressure, thereby enhancing the accuracy and reliability of climate change predictions. By incorporating NSFs into existing predictive models, such …

Abnormal Event Detection Using Hypergraph Based Multiple Objects Tracking Techniques In Surveillance Videos, Palanivel S

Theses and Dissertations

Abnormal event detection aims to identify the events that deviate from expected normal patterns. This work primarily focuses on detection of rare events in public places. The existing research challenges in a video-based surveillance systems for the vehicle have been analysed and presence of abnormal objects in traffic-oriented videos have been detected. A novel approach for event summarization and rare event detection has been proposed in this work. The key ingredient in this work is the incorporation of Hypergraph (HG) matching.

Despite the reasonable amount of success achieved by a large number of researchers over the globe, distinguishing important videos …

Recent Evolution In Thermochemical Transformation Of Municipal Solid Wastes To Alternate Fuels, Tumpa R. Sarker, Lucky Khatun, Bangladesh Agricultural University, Rostom Ali, Shariful Islam, Sagor Chowdhury, Kazi Sakibur Rahman, Nafis Sadique Sayem, Akm S. Rahman

Publications and Research

The management of solid waste poses a worldwide obstacle in the pursuit of a sustainable society. This issue has intensified with the increase in waste production caused by rapid population expansion, industrialization, and urbanization. The continuously growing volume of municipal solid waste, particularly the substantial volume of organic waste, along with improper disposal practices, results in the release of greenhouse gases and other harmful airborne substances which simultaneously causes health risks and socioeconomic concerns. This article examines various waste-to-energy (energy production in the form of heat and electricity) concepts as well as waste-to-materials (various value-added materials including biofuel, biochemical, char, …

From Saving To Budgeting: Unpacking The Impact Of A Culturally Relevant Financial Literacy Summer Program- $Mart Money, Renee S. Gibert, Imani Adams, Sungwoo Kang

Lyles School of Civil Engineering Faculty Publications

Culturally Relevant Pedagogy (CRP) is an educational framework that illustrates how to foster educational excellence through a focus on cultural competence, critical consciousness, and academic success, which aims to empower students by making education more applicable and responsive to their lived experiences (Ladson-Billings, Citation1995). This study elucidates the efficacy of CRP within financial literacy education, as implemented in a STEAM (Science, Technology, Engineering, Arts, and Mathematics) summer enrichment program. Our objective is to explore the extent to which CRP influences student perceptions of their personal finances through an understanding of financial literacy. Employing a qualitative methods approach, we reviewed transcripts, …

Balancing Results From Ai-Based Geostatistics Versus Fuzzy Inference By Game Theory Bargaining To Improve A Groundwater Monitoring Network, Masoumeh Hashemi, Richard C. Peralta, Matt Yost

Plants, Soils and Climate Student Research

An artificial intelligence-based geostatistical optimization algorithm was developed to upgrade a test Iranian aquifer's existing groundwater monitoring network. For that aquifer, a preliminary study revealed that a Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) more accurately determined temporally average water table elevations than geostatistical kriging, spline, and inverse distance weighting. Because kriging is usually used in that area for water table estimation, the developed algorithm used MLP-ANN to guide kriging, and Genetic Algorithm (GA) to determine locations for new monitoring well location(s). For possible annual fiscal budgets allowing 1-12 new wells, 12 sets of optimal new well locations are reported. Each …

Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy

Publications

Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance.

An Exploration Of Dimensionality Reduction Of Dynamics On Lie Groups Via Structure-Aware Canonical Correlation Analysis, Wooyoung Chung

Master's Theses

Incorporating prior knowledge into a data-driven modeling problem can drastically improve performance, reliability, and generalization outside of the training sample. The stronger the structural properties, the more effective these improvements become. Manifolds are a powerful nonlinear generalization of Euclidean space for modeling finite dimensions. When additionally assuming that the manifold carries (Lie) group structure, this imposes a drastically stricter global constraint. The range of their applications is very wide and includes the important case of robotic tasks. We apply this idea to Canonical Correlation Analysis (CCA). In traditional CCA one constructs a hierarchical sequence of maximal correlations of up to …

Domain Specific Aspect Extraction For Product Design, Divyam Sobti

Master's Theses

As technology advances, computers become increasingly proficient at interpreting and translating human language into machine-understandable text. With the help of algorithms in natural language processing (NLP), machines can now translate textual data. These algorithms help identify and extract specific text components known as aspects. The aspects represent specific attributes or topics within textual data. For instance, an Amazon review states,“ This phone has good battery life but poor camera quality,” and attributes like ‘battery life’ and ‘camera quality’ represent aspects in the text. Aspect extraction is a pivotal process involving identifying and isolating key features or topics within text. This …

Natural Language Processing For Automated Sysml Diagram Generation, Joshua Andre Ontiveros

Theses and Dissertations

This thesis explores the applications of natural language processing (NLP) techniques in model-based system engineering (MBSE) to help generate System Modeling Language (SysML) diagrams. MBSE is a method that aids in enhancing traditional engineering practices by modeling to help improve understanding and communication in systems development. SysML, one of the modeling languages for MBSE, helps represent a system's architecture, behavior, and information flow. Translating systems requirements and specifications into SysML models can be time-consuming and can lead to errors when created manually. Automating the creation of SysML diagrams from textual descriptions with the help of NLP techniques can aid in …

Home Care Work Of Caregivers For Mexican American Adults With Dementia: A Culturally Informed Model Integrating Work System Analyses And Health Disparities Research Framework, Laura Cristina Tovar Felix

Open Access Theses & Dissertations

Dementia is an umbrella term for different diseases such as Alzheimer's, vascular dementia, Lewy body, frontotemporal, and mixed dementias. Dementia is caused by a variety of diseases that cause damage to brain cells interfering with the ability of brain cells to communicate between each other. Dementia is associated with different types of brain cell damage in a specific region of the brain (What Is Dementia?, 2024).Dementia affects 55 million people worldwide, where the most affected population is the low-income and the middle-income countries. (Greenblat, 2023). Every 20 years the number almost double, and by 2039 is estimated to reach 78 …

An Efficient Neutrosophic Approach For Evaluating Possible Industry 5.0 Enablers In Consumer Electronics: A Case Study, Mai Mohamed, Asmaa Elsayed, Bilal Arain, Jun Ye

Neutrosophic Systems with Applications

With the use of cutting-edge technologies like artificial intelligence (AI), robotics, and the Internet of Things (IoT), Industry 5.0 represents a breakthrough move towards a sustainable and human-centered industrial future. Industry 5.0 endeavors to transform industries such as consumer electronics by emphasizing sustainability and collaboration, in contrast to its predecessors, who only concentrated on automation and efficiency. Along with improved manufacturing efficiency and product innovation, this change in the consumer electronics sector also redefines the human-machine interaction. This paper proposes a novel hybrid integrating model that combines the Entropy Weight Method (EWM), Best-Worst Method (BWM), and an acronym in Portuguese …

Enrichment Of Turkish Question Answering Systems Using Knowledge Graphs, Okan Çi̇ftçi̇, Fati̇h Soygazi̇, Selma Teki̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Recent capabilities of large language models (LLMs) have transformed many tasks in Natural Language Processing (NLP), including question answering. The state-of-the-art systems do an excellent job of responding in a relevant, persuasive way but cannot guarantee factuality. Knowledge graphs, representing facts as triplets, can be valuable for avoiding errors and inconsistencies with real-world facts. This work introduces a knowledge graph-based approach to Turkish question answering. The proposed approach aims to develop a methodology capable of drawing inferences from a knowledge graph to answer complex multihop questions. We construct the Beyazperde Movie Knowledge Graph (BPMovieKG) and the Turkish Movie Question Answering …

Waging Peace On The Final Frontier 64th Academy Assembly Proceedings, Space And Defense, Madison Walker

Space and Defense

In October 2022, the 64th annual Academy Assembly at the U.S. Air Force Academy took up the theme of “Waging Peace on the Final Frontier.” The following are proceedings of roundtables held by select undergraduates from around the country on questions of space policy & strategy.

Heritage Preservation In Egyptian Villages And Centers, Azza Elsakka Ahmed Abdalwahaab , Ebtehal Fady Shareef

Journal of Engineering Research

Heritage holds deep significance as a collective memory and a source of pride for any society. However, in today's world, it has evolved beyond its symbolic status and emerged as a crucial factor in human development across various dimensions. Preserving and restoring heritage has thus become an urgent issue that demands extensive cooperation between governments, international society, and community associations.

A Stable Isotope Study To Investigate Water Movement In The Los Lagos Region Of Southern Chile, Kritan Subedi

Civil Engineering ETDs

The Los Lagos region in southern Chile, located in northwest Patagonia, features rain-fed agricultural lands, glacial lakes, forests, farmlands, and volcanic soils. This study investigates water movement within a micro-basin using stable isotope analysis and hydrological modeling over eight weeks. It aims to develop a conceptual model of water movement by elucidating interactions between precipitation, soil water, and streamflow. Findings highlight the critical role of deeper soil layers in sustaining streamflow during dry spells and indicate that soil acts as a buffer, maintaining hydrological continuity despite variable precipitation. Improved understanding of these dynamics can inform watershed management and water resource …

Book Review: Credible: The Power Of Expert Leaders, Carl L. Tolbert

The Journal of Values-Based Leadership

Amanda Goodall’s (2023) book Credible: The Power of Expert Leaders argues why expert leaders are needed more now than ever across all organizational domains. Goodall describes the book as a chronicle of the “natural experiment” showcasing failures of nonexperts leading various sized groups and organizations, also citing parallel success by expert leaders (p. 1). The book is divided into eight chapters, starting with the introduction and examining the need for experts, the recruitment and development of experts, and finally, the organizational environment to sustain experts. The introduction begins as a corollary to Nichols’ (2024) work regarding how society no longer …