Computer Engineering Commons^™

Collaborative Online Interactive Laboratory On Software Defined Radio Fundamentals, Otilia Popescu, Dimitrie C. Popescu, Emanuel Puschita

Engineering Technology Faculty Publications

Teaching of fundamentals of communication systems varies widely across programs in US and abroad, mainly due to the type of undergraduate engineering programs and the depth of the communications field within the curricula. The variety is spread across electrical engineering and electrical engineering technology programs, and programs with focus on telecommunications or which only offer core or elective courses in communications. Adding to the variety, some programs include hands-on laboratory courses, others include simulation-based laboratories most of the time using Matlab, while others may only include lecture courses with no labs. The accessibility of the new software defined radio (SDR) …

Investigation Of A Busemann Intake At Negative Angle Of Attack, Mark E. Noftz, Andrew N. Bustard, Nicholas J. Bisek, Thomas J. Juliano, Joseph S. Jewell

Publications

A high-speed, shape-transitioned, inward-turning intake was tested in Purdue’s Boeing/AFOSR Mach 6 Quiet Tunnel. The inlet model, called the Indiana Inlet (INlet), had a total contraction ratio of 4.68:1 and a design point of Mach 6 at 0° angle of attack. The model was outfitted with a suite of high-frequency pressure transducers, and the external flowfield was imaged with high-speed schlieren photography. The INlet was tested under low freestream disturbance levels for a variety of freestream unit Reynolds numbers and at-4° angle of attack. An unsteady shockwave near the leading edge of the inlet forebody, indicative of boundary layer separation, …

Ai-Driven Traffic Scene Understanding Using Static Lidar Sensors, Elham Binshaflout, Chaima Zaghouani, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Sameh Najeh, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

Traffic congestion and road safety remain critical challenges in urban environments, driving the need for more effective traffic monitoring solutions. While recent advancements in computer vision have enhanced traffic perception, the dynamic viewpoint of autonomous vehicles is often insufficient for comprehensive traffic management. To address this gap, we propose an AI-driven framework for enhanced traffic scene understanding using static LiDAR sensors at road intersections. The system collects 3D point clouds from roadside static LiDAR sensors, providing a complete view of vehicles and pedestrians. We integrate state-of-the-art 3D object detection (i.e., PV-RCNN) and instance segmentation models (i.e., PointGroup3heads) to accurately identify …

Annotated 3d Point Cloud Dataset For Traffic Management In Simulated Urban Intersections, Elham Binshaflout, Chaima Zaghouani, Nawfal Guefrachi, Charalampos Antoniadis, Hakim Ghazzai, Ahmad Alsharoa, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

Ensuring accurate traffic perception and road safety in complex urban environments remains a significant challenge. Advanced traffic monitoring increasingly relies on deep learning, which requires large data volumes. However, existing datasets are often limited to CCTV video footage or focus on dynamic scenarios captured by sensors mounted on ego vehicles. This narrow perspective reduces the effectiveness of comprehensive traffic monitoring, particularly for LiDAR sensors, which typically capture only the vehicle's viewpoint and miss critical areas such as intersections and pedestrian crossings. To address these limitations, we propose a holistic strategy for rapid data collection in urban settings using simulated 3D …

Exploring Student Satisfaction In Learning With Podcast Applications: A Qualitative Study Based On Open-Ended Questions, Indah Permatasari, Peny Meliaty Hutabarat, Erni Adelina

Jurnal Vokasi Indonesia

This study aims to explore student satisfaction with the use of podcasts as a learning medium in the Non-News Radio Production course. A qualitative approach was used, with three open-ended questions posed to students: (1) What different experiences did you have when listening to the course material via podcast?(2) Did listening to the course material through podcasts help you focus on understanding the material? And why? And (3) provide your opinion on the Adapto podcast material shared during the Non-News Radio Production course in the 4th semester. The data obtained was thematically analyzed to identify the main emerging themes. The …

Real-Time Congestion Control And Load Optimization In Cloud-Manets Using Predictive Algorithms, Preeti Rani, Mohammed Hussien Falaah

NJF Intelligent Engineering Journal

Cloud-MANET environments require a system to balance load and control congestion. As a result of integrating real-time network metrics with predictive traffic algorithms, the proposed model optimizes the management of dynamic topologies, network bandwidth constraints, and fluctuating traffic loads. In addition to energy-aware multi-path routing, the framework incorporates adaptive congestion control mechanisms to ensure data transmission is efficient and stable. This algorithm provides higher packet delivery ratios, reduces end-to-end delays, and increases throughput over existing algorithms, according to the evaluation results. Hybrid Cloud-MANET systems can benefit from this approach by optimizing resource utilization and network performance.

A Practical Intrusion Detection Approach For Arp Spoofing And Mitm In Local Area Networks, Hiba Bazzi, Ali Nassar, Mustafa El Bizri, Ali M. Haidar Prof.

BAU Journal - Science and Technology

In modern network environments, the increasing sophistication of cyberattacks poses significant risks, particularly through Address Resolution Protocol (ARP) spoofing and Man-in-the-Middle (MITM) attacks, which exploit vulnerabilities in local area networks. Existing tools often focus on detection or protection at the client side, leaving network-wide detection and response largely unaddressed. This paper presents a novel intrusion detection tool specifically designed to identify ARP spoofing and MITM attacks in real-time within local area networks. The system leverages Python and Scapy for low-level packet analysis and Flask for an intuitive web-based dashboard. Key features include network monitoring, attack detection through ARP table comparisons, …

Online Learning Transition: An Analysis Of Proactive Institutional Assistance In Reducing Difficulties During The Covid-19 Pandemic, Mohammed Yahya Alghamdi

BAU Journal - Science and Technology

The COVID-19 pandemic caused major changes in the education system, with a shift to online learning, and experience has shown that transitioning from face-to-face instruction is difficult. This study involved 80 academic staff members from Al-Baha University in Saudi Arabia to learn about the benefits, limitations, and institutional support of online education in the setting of an epidemic. The study answers two primary questions: The first study question was, What difficulties did instructors face when they switched to online instruction? While the second research question was, How did institutional support influence the transition to online instruction? The study’s research methodology …

Energy Efficiency Optimization In Integrated Sensing And Communication Networks, Arianna M. Santamaria Penafiel

Electrical and Computer Engineering ETDs

In the emerging landscape of Integrated Sensing and Communication (ISAC) networks, achieving energy efficiency while concurrently performing sensing and communication tasks remains challenging. This paper introduces a new framework, a novel solution that empowers User Equipment (UEs) to make informed decisions regarding their transmission power allocation, optimizing the energy efficiency of sensing, communication, and data reporting to the gNB (gNodeB) functions. Initially, a novel ISAC network paradigm is proposed, where the gNB employs rewards, such as monetary incentives, to motivate UEs to engage in sensing, data collection, and reporting within its coverage area based on the principles of Contract Theory. …

Exploring Smart Thermostat, Don P. Dang

2024 Fall Honors Capstone Projects - Archive

This study examines the security, privacy, and compatibility challenges associated with smart thermostats in smart home systems. Smart thermostats, as part of the growing Internet of Things (IoT) ecosystem, face vulnerabilities such as unauthorized access, data breaches, and inconsistent security protocols. Using a mixed-methods approach, this research evaluates encryption techniques, communication protocols (Zigbee, Z-Wave, Wi Fi), and user behaviors that impact system security and efficiency. Key findings indicate that 35% of users are concerned about hacking risks, while 25% express data privacy concerns. Many users lack awareness of security measures, such as firmware updates and password management, which increases vulnerabilities. …

Leveraging P4 Programmable-Hardware Switches For In-Network Pmu Packet Recovery, Evan Michael Bonar

Electrical Engineering and Computer Science Undergraduate Honors Theses

Phasor Measurement Unit (PMU) systems are essential for real-time power grid monitor- ing but often face data loss due to network delays, equipment malfunctions, or transmis- sion errors. Traditional centralized recovery solutions introduce significant latency and scalability challenges. This thesis presents a P4-based in-network recovery mechanism that embeds detection and recovery directly into the data plane of P4-enabled programmable switches, significantly reducing recovery time and infrastructure complexity. Using the Aurora 610 switch, the system detects missing packets via sequence number analysis and recovers magnitudes with an efficient register-based algorithm.

Evaluation demonstrates high accuracy and low latency, achieving a mean absolute …

Bonsai Merkle Tree Streams: Bulk Memory Verification Unit For Trusted Program Verification System, Richard J. Rios

Master's Theses

Today, all modern computing systems are undoubtedly vulnerable to numerous types of attacks that could be targeted toward any layer of the system from dedicated hardware to highly abstracted software. Unfortunately, many devices and systems naturally contain inadequately protected components or software modules that un- dermine their security as a whole. Additionally, security is heavily variable system to system, and has a huge dependence on adequate implementation and ongoing support from device and software manufacturers. To address these various security issues in a very general way, TrustGuard, a containment security system utilizing an external device called the Sentry that would …

Basic Safety Message Generation Through A Video-Based Analytics For Potential Safety Application, Abyad Enan

All Theses

With the advancement of modern artificial intelligence techniques, computer vision can play a vital role in enhancing roadway safety by reducing the risk of imminent collisions. To do so, a vision-based safety application is required, where a roadside camera can monitor the roadway traffic and predict potential risks of crashes in real-time. If any risky situation or behavior is observed that may lead to a crash, then a safety application can send warnings to the vehicles at risk. For vision-based safety applications on a roadway section, it is important to accurately monitor each vehicle’s location, speed, acceleration, heading direction, etc. …

Co-Emulation Of Robotics And Software-Defined Radio Based 5g Wireless Communications., Bhaskara Venkata Raju Garuda

Electronic Theses and Dissertations

The convergence of robotics and 5G wireless communication technologies has opened new avenues for real-time, dynamic robotic applications. This dissertation introduces a novel framework that integrates the Robot Operating System (ROS), Software-Defined Radios (SDRs), and 5G wireless networks to achieve seamless coemulation of robotic systems. The research emphasizes the unique features of 5G, such as ultra-low latency and high throughput, which enable critical applications like remote surgery, industrial automation, and autonomous vehicles. The methodology combines ROS for robotic control, SDRs for programmable communication channels, and 5G testbeds for high-speed, reliable data transmission. The experimental evaluation focuses on both position-based and …

Protocol Transformations Across Osi Network Stack Layers For Attack, Evasion, And Defense, Nathan Tusing

All Dissertations

Network endpoints frequently contend with errors and deviations within protocols. Many factors account for these deviations including noise, tampering, and algorithm implementations. Intermediate nodes are expected to modify instantiated protocols and not guarantee correctness. This ability to modify traffic enables all sides of network security to alter security and performance properties of protocols, and we define this intermediary modification of an instantiated protocol as a transformation. Protocol transformations traverse layers of the OSI reference model and changes a protocol's time series byte sequence. Within this thesis, we show that this framework applies to multiple domains and protocols. Common examples of …

Juegos De Rol En El Desarrollo De Projectpipe: Una Inmersión En El Uso De Metodologías De Diseño, Julieth A. Gómez Hernández, Cristian C. Orozco Ospina, Nicolas Restrepo Henao

Journal of Roleplaying Studies and STEAM

En el entorno digital actual, la evolución del concepto de juegos de rol ha llevado al desarrollo de aplicaciones web interactivas y educativas. En sintonía con este planteamiento, se presenta la siguiente propuesta, que adopta una metodología integrada para aprovechar la versatilidad del método de Bruno Munari y el Diseño Centrado en el Usuario (DCU). La metodología de Munari descompone la gestión macro del proyecto en pasos manejables; mientras que el DCU se enfoca en la creación de una interfaz intuitiva y funcional mediante prototipos iterativos y pruebas continuas de usabilidad. Como complemento a estas estrategias se integra la metodología …

Data Security In The Apple Ecosystem: An Evaluation, Kayrene Woods

Cybersecurity Undergraduate Research Showcase

This study provides a comprehensive evaluation of data security within the Apple ecosystem, focusing on the company’s privacy policies, user perceptions, and the effectiveness of its App Store review processes. Employing an interdisciplinary methodology, the research examines Apple’s commitment to data protection, emphasizing transparency and user trust. A survey of user experiences revealed varying levels of engagement and understanding of Apple’s privacy practices, with only 32.8% of respondents having read the Privacy Policy and mixed opinions on its clarity. Additionally, concerns persist about third-party app security, with 39.7% of users expressing apprehension and skepticism about Apple’s App Store review process. …

Security Vulnerabilities In Mobile Operating Systems Used In Iot Devices: An Examination Of Current Challenges And Countermeasures, Isain Cortes Jr.

Cybersecurity Undergraduate Research Showcase

No abstract provided.

Integrating Humanities Into Cybersecurity Education: Enhancing Ethical, Historical, And Sociopolitical Understanding In Technical Training, Joseph Frusci

Journal of Cybersecurity Education, Research and Practice

The increasing complexity of cybersecurity challenges necessitates a holistic educational approach that integrates both technical skills and humanistic perspectives. This article examines the importance of infusing humanities disciplines such as history, ethics, political science, sociology, law, and anthropology—into cybersecurity education. Through a pilot course developed for Staten Island Technical High School, aligned with the New York State K-12 Computer Science and Digital Fluency Standards, students were introduced to an interdisciplinary curriculum that combined technical cybersecurity training with historical analysis, ethical reasoning, and sociopolitical context. The results of pre- and post-course assessments demonstrated significant improvements in critical thinking, ethical decision-making, and …

Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin, Ruairí De Fréin, Alexander Mutiso Mutua Mr

Articles

Electric vehicle (EV) drivers in urban areas face range anxiety due to the fear of running out of charge without timely access to charging points (CPs). The lack of sufficient numbers of CPs has hindered EV adoption and negatively impacted the progress of sustainable mobility. We propose a CP distribution algorithm that is machine learning-based and leverages population density, points of interest (POIs), and the most used roads as input parameters to determine the best locations for deploying CPs. The objects of the following research are as follows: (1) to allocate weights to the three parameters in a $6$ km …

Training An Ai To Detect Injection Attacks Using A Hands On Approach, Aedan Tredinnick

Cybersecurity Undergraduate Research Showcase

This paper presents a practical approach to training an AI model to detect injection attacks, focusing on the creation of a manufactured dataset via structured hands-on methods. By establishing a vulnerable web server using XAMPP and DVWA (Damn Vulnerable Web Application), the research aims to simulate various injection attacks and capture relevant network traffic data. The paper discusses the methodology of data collection, AI model development, and performance evaluation.

Nature Inspired Optimization For Spectrum Sensing And Allocation In Cognitive Radio Networks, Saravanan R

Theses and Dissertations

Cognitive radio (CR) refers to intelligent radio technology that scans its environment to optimize spectrum use and adjusts its parameters accordingly. It employs a communication system that is aware of its surroundings, including spectrum usage and availability. A key aspect of CR is identifying idle channels by analyzing traffic patterns using effective learning strategies.

However, CRNs face challenges such as cross-layer design issues, spectrum sensing errors, hidden node problems, and complex spectrum management. Spectrum sensing is critical for accessing unused radio spectrum while minimizing interference. Efficient sensing techniques must be cost-effective, fast, and capable of detecting weak primary signals. Although …

Synthetic Network Creation And Visualization, Kaylee Sloat, Jeremy Evert

Student Research

The code in the repository, “synthetic_network_creation_and_visualization” is inspired by the foundational work presented in "NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks" by Shashank Pandit, Duen Horng Chau, Samuel Wang, and Christos Faloutsos.

Link to the original paper:https://kilthub.cmu.edu...

You Want Me To Do What? But I Can’T Read That... Cataloging Soviet Russia Space Exploration Books, Katherine Loving, Phillip Fitzsimmons

Faculty Books & Book Chapters

The Al Harris Library received a donation of the archive of retired astronaut General Thomas P. Stafford. The continually growing collection includes over 200 boxes containing NASA reports, professional and personal pictures, videos, and more. Part of the collection is the approximately 700 books used for research by Stafford and his co-author Michael Cassutt to write the memoir We Have Capture: Tom Stafford and the Space Race (2002). Half of these books are a collection of Soviet-era Russia (USSR) space program books and periodicals written in Russian. Michael Cassutt has characterized the books as the most comprehensive collection about the …

Instructional Systems Design: The Diffusion And Adoption Of Technology: (Volume 2), Cassandra Celaya (Author), Pamela J. Downing (Author), Jessica Shifflett (Author), Debbie Gdula (Author), Tracie Barr (Author), Miguel Ramlatchan (Author & Editor)

University Administration Bookshelf

Instructional designers, instructional systems designers, and other educational technologists are, by their nature, innovators. These professionals apply and extend the applied science of learning, systems, communication, and instructional design theory to help students learn. Technology in some capacity is used to make the connections between subject matter experts, teachers, instructors, and their learners. It is common for instructional designers to seek new tools, techniques, and innovations for the improvement of learning, access, quality, and student satisfaction. However, the adoption and diffusion of new educational technology and innovation is a complex process that depends on many variables. Understanding these processes and …

Exploration Of Esp32 Vulnerabilities And Malware, Charles T. Moreno

College of Engineering Summer Undergraduate Research Program

The rapid expansion of the Internet of Things (IoT) has revolutionized industries by enabling connected smart devices to monitor, communicate, and automate tasks in real-time. Central to the functioning of many IoT systems are microcontrollers like the ESP32, a versatile and low-cost microcontroller known for its integrated Wi-Fi and Bluetooth capabilities. The ESP32's powerful processing, energy efficiency, and adaptability make it a popular choice for IoT applications ranging from smart home devices to industrial automation. However, as IoT adoption grows, so too do the security challenges posed by vulnerabilities in these devices, particularly within ESP32-based systems. For this project, I …

Devices And Dining: A Cross-Cultural Analysis Of Mobile Device Use In Italian And American Restaurants, O'Malley Jenkins

Senior Theses

The field of technology ethics has seen increasing growth and interest over the years. Many have begun to consider the impacts of technology’s use and whether it is being employed in a healthy manner by users. However, there has been limited investigation into whether the ways in which technology use varies across cultures. This study begins to address this gap by researching Italian and American device usage in fast food settings. Non-participant naturalistic observations were used to record data for 89 Italian and 88 American customers of fast food restaurants. Analysis of the collected data indicates that Americans use their …

Cyber Threat Intelligence Sharing In Nigeria, Muhammad Abubakar Nainna, Julian Bass, Lee Speakman

Communications of the IIMA

Cybersecurity challenges are common in Nigeria. Sharing cyber threat intelligence is essential in addressing the extensive challenges posed by cyber threats. It also helps in meeting regulatory compliance. There are a range of impediments that prevent cyber threat intelligence sharing. We hypothesise that we want to maximise this cyber threat intelligence sharing to resist malicious attackers. Therefore, this research investigates factors influencing threat intelligence sharing in Nigeria's cyber security practitioners. To achieve this aim, we conducted research interviews with 14 cyber security practitioners using a semi-structured, open-ended interview guide, which was recorded and transcribed. We analysed the data using an …

Federated Learning Systems For Mobile Sensing Data, Xiaopeng Jiang

Dissertations

Federated Learning (FL) has emerged as a new distributed Deep Learning (DL) paradigm that enables privacy-aware training and inference on mobile devices with help from the cloud. This dissertation presents a comprehensive exploration of FL with mobile sensing data, covering systems, applications, and optimizations.

First, a mobile-cloud FL system, FLSys, is designed to balance model performance with resource consumption, tolerate communication failures, and achieve scalability. In FLSys, different DL models with different FL aggregation methods can be trained and accessed concurrently by different apps. In addition, FLSys provides advanced privacy-preserving mechanisms and a common API for third-party app developers to …

Faids: Artificial Intelligence Developmental Systems Framework For Predicting And Preventing Cyberattacks In Supply Chain Networks, Lordt Becklines

Research & Publications

Cyber threats and attacks disrupt and damages supply chain networks (SCNs), which are complex and interlinked. Current methods to predict and prevent cyberattacks are inadequate and ineffective. This research proposes an AI developmental systems framework (FAIDS) to protect SCNs from cyberattacks. The framework has four components: (1) an AI threat intelligence system; (2) an AI risk assessment system; (3) an AI decision support system; and (4) an AI learning and adaptation system. The framework is tested on a simulated retail SCN. The results show that the framework can predict and prevent cyberattacks and improve the network's resilience and security. The …