Digital Commons Network^™

Ai-Enabled Hardware Security Approach For Aging Classification And Manufacturer Identification Of Sram Pufs, Harshdeep Singh

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Semiconductor microelectronics integrated circuits (ICs) are increasingly integrated into modern life-critical applications, from intelligent infrastructure and consumer electronics to the Internet of Things (IoT) and advanced military and medical systems. Unfortunately, these applications are vulnerable to new hardware security attacks, including microelectronics counterfeits and hardware modification attacks. Physical Unclonable Functions (PUFs) are state-of-the-art hardware security solutions that utilize process variations of integrated circuits for device authentication, secret key generation, and microelectronics counterfeit detection. The negative impact of aging on Static Random Access Memory Physical Unclonable Functions (SRAM PUFs) has significant consequences for microelectronics authentication, security, and reliability. This research thoroughly …

Ml-Assisted Side Channel Security Approaches For Hardware Trojan Detection And Puf Modeling Attacks, Niraj Prasad Bhatta

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Hardware components are becoming prone to threats with increasing technological advances. Malicious modifications to such components are increasing and are known as hardware Trojans. Traditional approaches rely on functional assessments and are not sufficient to detect such malicious actions of Trojans. Machine learning (ML) assisted techniques play a vital role in the overall detection and improvement of Trojan. Our novel approach using various ML models brings an improvement in hardware Trojan identification with power signal side channel analysis. This study brings a paradigm shift in the improvement of Trojan detection in integrated circuits (ICs). In addition to this, our further …

Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick

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This research illustrates a high-security wireless communication method using a joint radar/communication waveform, addressing the vulnerability of traditional low probability of detection (LPD) waveforms to hostile receiver detection via cyclostationary processing (CSP). To mitigate this risk, RF steganography is used, concealing communication signals within linear frequency modulation (LFM) radar signals. The method integrates reduced phase-shift keying (RPSK) modulation and variable symbol duration, ensuring secure transmission while evading detection. Implementation is validated through software-defined radios (SDRs), demonstrating effectiveness in covert communication scenarios. Results include analysis of message reception and cyclostationary features, highlighting the method's ability to conceal messages from hostile receivers. …

Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer

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Performing automatic target recognition (ATR) on full-size aircraft targets using inverse synthetic aperture radar (ISAR) data is challenging and expensive. The use of scale models and radar systems of such large targets saves time and reduces facility requirements. This study examines the feasibility of performing ATR on 1:144 scale model airplanes at Ka-band. The scale model and Ka-band radar simulate the collection of full-scale targets at VHF-band. The phase history measurement collections were completed in the Sensors and Signals Exploitation Laboratory (SSEL) at Wright State University. To ensure sufficient data for training and testing, the phase history data was augmented …

Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich

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To address the issues of limited target data in the Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) problem set, synthetic data is often used to aid in filling the gap. This paper covers an in depth look at the use of colorization, dynamic range adjustment, and target extraction as data augmentation techniques to improve the accuracy of deep learning networks trained on synthetic SAR data. The use of multiple different data augmentations combine to dramatically improve the accuracy of a common Convolutional Neural Network (CNN) over the use of standard synthetic data. A comparison of increasing fraction of measured …

Multi-Semantic-Stage Neural Networks For Robust And Interpretable Deep Learning, Christopher J. Menart

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Deep neural networks have great representational power. However, most deep neural nets today optimize directly for performance on a single task defined only by labeled training data. This excludes potential sources of knowledge and ways of learning which could improve their performance, and address challenges, such as explainability, which are pressing to the field. We propose a framework for neural network architecture which generalizes it to a graph of many semantically-meaningful variables. We call it the Multi-Semantic-Stage Neural Network (MSSNN). An MSSNN models its domain as a web of conditional probabilities, i.e. a collection of inter-related tasks which can learn …

Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi

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Lithium-ion batteries are an integral component of energy storage systems for renewable energy applications owing to their high energy density. Extensive research has therefore been carried out, utilizing both experimental and computational methods, to aid in a deeper understanding of lithium-ion batteries. Challenges related to efficiency, safety and thermal management persist, particularly during high current draw, extreme temperature conditions and extreme dynamic current operation such as in electric vehicles. This thesis work presents an electrochemical-thermal model of a lithium-ion battery that simulates and analyzes the variation of electrical behavior, chemical behavior and thermal behavior. The electrochemical model is developed by …

Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson

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The uncertainty of the standard calibration procedure for radar cross-section (RCS) measurement is studied for different targets measured in the near-field from 550 to 700 GHz. Using common calibration spheres and squat cylinders mounted on a styrofoam pedestal at waterline (zero-degrees elevation), the calibration difference measure is determined for each target. Similarly, the difference metric is determined for square trihedral and tophat targets placed on a ground plane and measured at different elevation angles. The mean calibration measure is calculated using the dual calibration target method and repeated measurements in an anechoic chamber. The specific THz system is described and …

Pneumonia Detection With Limited And Imbalanced Data Using Energy-Based Out-Of-Distribution Technique, Jasbin Karki

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The automated detection of pneumonia through chest X-ray presents a critical challenge in medical diagnostics, particularly due to the restrictions of limited and imbalanced chest X-ray data for training AI models. Traditional methods that depend on softmax confidence scores can be overconfident even when generating erroneous outputs especially when they are processing completely new inputs, leading to unreliable diagnostic results. This research addresses challenges in AI models which aim to develop a robust pneumonia detection system using an Energy-Based Out-of-Distribution (OOD) technique that can work effectively even with limited and imbalanced data. The study focused on creating a more reliable …

Test-Time Backdoor Attack Using Universal Perturbation, Jesse Alexander Smith

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The rapid growth and widespread reliance on machine learning (ML) systems across critical applications such as healthcare, autonomous driving, and cybersecurity have un- derscored their transformative potential and heightened their susceptibility to adversarial attacks and vulnerabilities. This thesis investigates vulnerabilities in ML models, focusing on backdoor attacks, including naive backdoor attack, feature collision backdoor attack, hidden trigger backdoor attack, and test-time backdoor attack using universal perturbation technique. These methodologies demonstrate how adversaries can automate and conceal malicious behaviors to achieve specific objectives, posing significant challenges to ML model integrity and trustworthiness. The research provides a comprehensive analysis of the theoretical …

Semantics-Aware Text-Guided Aerial Image Synthesis By Feature Augmented Diffusion Models, Douglas J. Townsell

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Aerial imagery provides crucial insights for various fields, including remote monitoring, environmental assessment, and autonomous navigation. However, the availability of aerial image datasets is limited due to privacy concerns and imbalanced data distribution, impeding the development of robust deep learning models. While recent text-guided generative models have shown promise in synthesizing high-quality images, they fall short in handling the unique challenges of aerial imagery, including densely packed objects, intricate spatial relationships, and the absence of paired text-aerial image datasets. To tackle these limitations, we propose STARS, a groundbreaking framework for Semantic-aware Text-guided Aerial image Refinement and Synthesis. STARS introduces a …

Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, And Scarcity, Bradley T. Ashmore

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The digital landscape is ever-evolving. In recent years the amount of bot traffic, traffic generated by autonomous applications over the internet has increased significantly. Many bots perform useful and needed functions, however, malicious bots are known sources of both common and emerging security threats. Denial-of-Services (DoS), information theft, and credential stuffing have all been conducted by malicious software running on unknowingly infected machines. The dichotomy of useful bots operating in the same networks as malicious bots combined with novel bot attacks and an ever-increasing number of personal devices connecting to the Internet drives the need for continued advancement of malicious …

A Trusted Adversarial Ml Countermeasure Approach For Secure And Resilient Ai-Driven Hardware Trojan Detection, Mohammed G M Alkurdi

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Semiconductor microelectronics Integrated Circuits (ICs) are increasingly integrated into critical life applications including medical, aerospace, and Internet of things. Their increasing importance as a technology gave rise to critical concerns regarding their security. This has led to the focus of the research community on hardware Trojans, which are malicious modifications to the ICs with undesirable outcomes. Their detection is becoming increasingly critical, with many researchers proposing methods to do so such as reverse engineering, logic testing, and side-channel analysis. Many of these proposals utilize machine learning methods to detect these malicious modifications with high accuracy and confidence. However, machine learning …

Uncertainty Quantification In Large Language Models Through Convex Hull Analysis, Ferhat Ozgur Catak, Murat Kuzlu

Engineering Technology Faculty Publications

Uncertainty quantification approaches have been more critical in large language models (LLMs), particularly high-risk applications requiring reliable outputs. However, traditional methods for uncertainty quantification, such as probabilistic models and ensemble techniques, face challenges when applied to the complex and high-dimensional nature of LLM-generated outputs. This study proposes a novel geometric approach to uncertainty quantification using convex hull analysis. The proposed method leverages the spatial properties of response embeddings to measure the dispersion and variability of model outputs. The prompts are categorized into three types, i.e., ’easy’, ’moderate’, and ’confusing’, to generate multiple responses using different LLMs at varying temperature settings. …

Perceptions Of Lightboard Videos On Engineering Students' Engagement For Learning: A Mixed-Methods Case Study, Rana Sanyal

Graduate Research Theses & Dissertations

Purpose. Researchers have recommended using comprehensive visual materials in engineering courses, as visuals instill more information in students than auditory information and they have the ability to engage students more effectively than other types of content and to convey the nuances of non-verbal communication. The purpose of this study was to explore the perceptions of engineering students on incorporating technologically advanced video course materials (TAVCM) created with lightboard technology on their engagement in learning. Theoretical Framework. The theoretical framework was based upon an integrative learning environment that incorporated many theories of cognitive learning. The Cognitive Theory of Multimedia Learning (CTML) …

Relative Comparison Of Modern Computing To Computer Technology Of Ages, Iwasan D. Kejawa Dr., Hailly Rubio Ms.

School of Computing: Faculty Publications

Abstract

Abstract

Are there differences and similarities between the computer technology of today and yesterdays. Research had shown that there had been tremendous improvements from the computers of ages (traditional Computers) as we enter the 21st century. Both the physicality and the functionalities of computers have changed but some remain the same. The memory capacity and functions have changed, but all are still based on the old concepts of yesteryears.

Collaborations, Not Competitions, Can Reduce Gender Disparities In Robotics, Sonia Roberts, Alysson Light

Feminist Pedagogy

No abstract provided.

Python Manual: A Learning Guide For Structural Engineering Students, Aaron Dewey, Kennedy Gomez, Meileen Yee

Architectural Engineering

This Python programming manual is a resource to assist architectural, civil, or structural engineering students as they learn to create scripts to solve various structural analysis and dynamics problems. Beyond providing guidance on Python libraries that enable numerical and symbolic mathematics (NumPy, SciPy, SymPy), the manual also focuses on the creation of tabular and plot outputs useful to communicate results through technical reports (Pandas, Matplotlib).

The content of this document was developed based on detailed review of curriculum for three architectural engineering computing courses typically offered to upper class students at Cal Poly, San Luis Obispo as well as surveys …

Educational Robotics And Computational Thinking In Elementary School Students, Sonia D. Jordan

Electronic Theses and Dissertations

This study examined the role of educational robotics in fostering computational thinking in elementary settings, both in classrooms and extracurricular programs. Among growing concerns over K–12 students’ computational thinking deficits, the research evaluated the impact of Lego EV3 and VEX IQ platforms. Data was sourced from lesson plans, student work surveys, and teacher interviews and then subjected to thematic analysis using a qualitative approach. The participants were Texas educators engaged in robotics instruction, even though specific robotics statistics are absent in the Texas Education Agency. Instructional strategies varied from hands-on experiences to translating mathematical concepts into robotic actions. A key …

Cognitive Function Among Military Veterans With Stem Occupations., Justin T Mcdaniel, Kevin N Hascup, Erin R Hascup, Ugochukwu G Ezigbo, Amanda M Weidhuner, Harvey Henson, David L Albright

Articles

No abstract provided.

Cognitive Function Among Military Veterans With Stem Occupations., Justin T Mcdaniel, Kevin N Hascup, Erin R Hascup, Ugochukwu G Ezigbo, Amanda M Weidhuner, Harvey Henson, David L Albright

Articles

No abstract provided.

An Introductory Course In Electrical Circuits And Coding For Deaf And Deafblind Middle School Students, Becca Leininger, Christina Yang, Makayla Quinn, Jeffrey Jalkio, Rahaf Bahajry, Mellissa Ingabire, Annmarie Thomas

Journal of Science Education for Students with Disabilities

in is the first Deaf charter school in the United States, opening in 1993. The school serves students in the Twin Cities and Western Wisconsin from ages 2 to 21 who are primarily Deaf, DeafBlind and Hard of Hearing students, often being visual and/or tactile learners. All students who attend have Individualized Education Plans (IEPs) and fall under the special education category, defined by the Minnesota Department of Education as students who “have a disability and need specialized instruction” (Minnesota Department of Education, n.d.). At , students are instructed in American Sign Language (ASL) and English is primarily taught through …

Infographic: Girls’ Interest In Engineering, Dominique Russell

Teacher infographics

It's well-known that women are underrepresented in participation in STEM education and the STEM workforce. The 2021 Youth in STEM study surveyed participants about their awareness and perception of STEM subjects and careers. As this infographic shows, the findings reveal age is important for girls when it comes to interest in studying engineering.

Imagination To Innovation: Design Thinking For Young Learners, Lindsey Herlehy, Cassandra Armstrong

Publications & Research

Design thinking is the intersection of engineering design and social-emotional learning. Today’s learners must be empathetic problem solvers capable of defining problems and designing appropriate solutions to meet the needs of the user. In this session, participants will experience design thinking through literature-based scenarios appropriate for early learners. They will analyze and compare their own models to those of others and compose a lesson that will engage students in the design thinking process.

Families Engineering Together In Communities And At Home: Facilitation Guide, Amber Simpson, Adam V. Maltese, Peter Knox, Jungsun Kim, Jing Yang, Sawsan Werfelli, Kelli Paul, Monika Mayer

Teaching, Learning and Educational Leadership Faculty Scholarship

In this publication, we present a program that serves as a bridge between families and learning environments of all kinds, and provides a pathway for engineering design to be incorporated into the everyday lives of families and kids. Supporting families in their home environment, the program offers a fun and approachable introduction to thinking about engineering and bringing these concepts to life. Conversation and engagement between children and caregivers is so important during elementary school years - this program encourages families to think about, discuss, and experience engineering in a fun and accessible way in their home and community environments. …

A Globalized Optimization Schema For Automated Fiber Placement Processing Parameters, Matthew John Godbold

Theses and Dissertations

Automated Fiber Placement is an advanced manufacturing technique for industrial-scale composite structures. Advanced robotics coupled with composite manufacturing results in faster and more consistent results than previously obtained through hand layup. The complexity and interconnectedness of the automated fiber placement process provides a difficult challenge for traditional modeling techniques. Modeling within automated fiber placement currently utilizes physics-based modeling to inform the translation of a design to a manufacturing plan. The intricacy of the automated fiber placement process dictates that attempts at modeling or optimizing these processes are often limited in their scope. Physics-based modeling for manufacturing typically involves numerous interacting …

An Animated Introduction To Digital Logic Design, John D. Carpinelli

Open and Affordable Textbooks

There is a newer edition of this textbook available here.

This book is designed for use in an introductory course on digital logic design, typically offered in computer engineering, electrical engineering, computer science, and other related programs. Such a course is usually offered at the sophomore level. This book makes extensive use of animation to illustrate the flow of data within a digital system and to step through some of the procedures used to design and optimize digital circuits.

All of the animations for this book can be found here: https://digitalcommons.njit.edu/dld-animations/

Comparing Polytechnic And Liberal Arts Institutions: Leaks In The System, Ryan Drew Baldwin

Seton Hall University Dissertations and Theses (ETDs)

The United States has long been a pioneer in higher education, yet the last few decades have proven challenging in maintaining its lead in the science, technology, engineering, and mathematics fields (STEM). Students entering postsecondary education and participating in a STEM degree face increased academic rigor and this study’s goal is to better understand factors that influence their retention. There are many psychosocial, environmental, and academic variables that may impact a student’s retention and this study aims to investigate how those variables inform a students likelihood of being retained and if there are meaningful differences between polytechnic and non-polytechnic institutions.

The Interpretation Of Measurement, Austin David O'Connor

Legacy Theses & Dissertations (2009 - 2024)

The interpretation of measurement representations, such as blueprints and 3D models, has been debated in engineering offices and philosophical colloquiums alike. A resurgence has begun in the philosophical literature which focuses on the recent International System of Units (SI) change in the base unit definitions. Additionally, a recent revision in the form of ASME Y14.5-2018 has been adopted by prominent engineering firms in America. This revision limits the number of viable interpretations for the Geometric Dimensioning & Tolerancing (GD&T) system of blueprint guidelines, which is meant to more effectively streamline communication between differing industries regarding part features and allowable extremities. …

Forecasting Retention Among At-Risk College Freshmen Students Through Completion Of A Stem Intervention, Edna Orozco

Theses and Dissertations

Science, Technology, Engineering, and Mathematics (STEM) areas are one of the fastest-growing majors in the nation, engineering, is projected to add the second largest number of new jobs from 2016 to 2026 with 140,000 new jobs (Torpey, 2018). Unfortunately, there is a disparity between enrollment and graduation rates (Chen, 2015; Lucas & Spina, 2022). According to the National Center for Education Statistics (NCES) (2017) despite all the research done throughout decades to improve the issue of retention in STEM areas about half of the students who pursue a degree in Science, Technology, Engineering, or Mathematics (STEM) will either leave or …