Computer Engineering Commons^™

Cooperative Guidance Method Considering Impact Time And Area Sealing, Zheng Guo, Guofei Li, Hua Xiong, Yunjie Wu

Journal of System Simulation

Abstract: To address the problem of multi-vehicle cooperative strike against maneuvering targets, a cooperative guidance method considering impact time control and terminal area sealing was proposed. The distributed disturbance observer was utilized to estimate target maneuvers. Based on the consensus errors of the impact time, the cooperative guidance law in the line-of-sight direction was proposed to achieve simultaneous hits on targets at a specified time. By considering the motion states of targets, the instructions of the terminal area sealing were designed to construct the sliding mode surface and design the line-of-sight guidance law, so as to ensure the convergence of …

Cybersecurity Risks Of Freight Rail As Critical Infrastructure, Kira Sun

Discovery Undergraduate Interdisciplinary Research Internship

Our project implements simulated train engineers to operate model train engines on a hybrid twin of a freight rail system. We can then use the model and simulate cyber-security attacks to demonstrate the risks and effects of the attacks. Using existing model train hardware and an Arduino running open-source software, DCC-EX and JMRI, we can control the train engines and various track components and sensors. We program each engine to make safe decisions about what speed and direction to take, using information provided by the various sensors and light signals around the track. When attacks occur, the engines can have …

Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn

Doctoral Dissertations

The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …

A Novel Hybrid Intrusion Detection Model: A New Metaheuristic Approach For Feature Selection Based On Ai Techniques For Cyber Threat Detection, Maryam Mahdi Alhusseini, Alireza Rouhi

Iraqi Journal for Computer Science and Mathematics

The rapid increase in internet usage, digital transformation, and the rise of interconnected devices have greatly expanded the attack surface, introducing new and evolving cybersecurity challenges. Conventional security solutions frequently have difficulty adjusting to complex threats and the vast dimensionality of network traffic data, particularly in the case of imbalanced datasets. To tackle these challenges, this research introduces a Hybrid Intrusion Detection System (HyIDS-EVO) that combines the Energy Valley Optimizer (EVO) for feature selection and dimensionality reduction with machine learning classifiers, which include Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), and K-Nearest Neighbors (KNN). The system’s effectiveness …

Envis: A User-Centered Web-Based Tool For Interactive Visualization Of Environmental Geospatial Data, Saima Sanjida Shila

LSU Master's Theses

Data visualization is an essential part of analyzing environmental geospatial data. Despite having the availability of large environmental datasets, there remains a lack of easily accessible, user-friendly, and interactive visualization tools in this field. Therefore, this study aims to develop a user-friendly and easily available web-based visualization tool. Before developing the tool, we conducted a survey of researchers at the LSU Coastal Studies Institute to collect their opinions on currently available visualization tools. In the survey, 55% of participants responded between somewhat satisfied to dissatisfied with their current visualization tools. Most of the participants mentioned two major limitations of existing …

Cv: Young "Paul" Kim (Computer Engineering), Young "Paul" Kim

ECaMS Department Faculty Curricula Vitae

No abstract provided.

A Robust And Energy-Efficient Federated Ids For Iiot Using Spiking Neural Networks And Differential Evolution With Adversarial Resilience, Mohammad Othman Nassar

Iraqi Journal for Computer Science and Mathematics

The Industrial Internet of Things (IIoT) is faced with increasing cybersecurity threats that require lightweight, fast, and resilient intrusion detection systems (IDS). This study presents a novel federated IDS framework that integrates federated learning (FL), Spiking Neural Networks (SNNs), and differential evolution (DE). The use of SNNs within a federated context is a rare and innovative contribution that enables effective temporal feature extraction from IIoT traffic. DE is employed as a global optimization mechanism, enhancing robustness and generalization beyond conventional federated aggregation. To further strengthen resilience, synthetic adversarial noise is injected during training, allowing evaluation in realistic poisoning scenarios. The …

Design Considerations For Conversational Agents To Assess The Social-Emotional Well-Being Of Young Children In Low-Income South African Communities, Lucretia A. Williams, Elizabeth A. Ankrah, Catherine E. Draper, Caylee J. Cook, Franceli L. Cibrian, Jesus A. Beltran, Kimberley D. Lakes, Gillian R. Hayes

Engineering Faculty Articles and Research

A variety of digital technologies have been used to support early childhood development (ECD) programs in low-income South African communities. Even though technology has provided opportunities to increase access to health interventions, the lack of trust and socio-economic constraints under which these tools would need to work pose complex challenges. We examine home visitors’ work processes, experiences, and preferences of a conversational agent to support their work of administering social-emotional well-being assessments to young children ages 0-5. Analysis of the results of focus groups with 51 home visitors indicates the need for designing conversational agents that support ECD in the …

Utilizing A Virtual Firewall Appliance For Introducing And Reinforcing The Concepts And Implementation Of Devices To Improve Security In A Computing Environment, Stanley Mierzwa, Christopher Eng

Center for Cybersecurity

The educational realm of higher education cybersecurity curriculum continues to evolve to provide more opportunities for experiential hands-on and work role-related practical applications of technology solutions. Gaining greater competencies is quickly becoming a normal requirement for such programs that are designated by the National Security Agency Center of Academic Excellence programs. The work roles of cybersecurity include a variety of knowledge, skills, and abilities, depending on the category of the activity or task. Firewalls have been a staple cybersecurity, network security, and information security device and strategy to protect organization networks and computing environments. This paper will provide details and …

Seeing What Matters: Safety-Critical Semantic Segmentation Via Transfer Learning On Construction Sites, Obiora J. Odugu

LSU Master's Theses

Autonomous robots are increasingly deployed on construction sites for tasks such as progress monitoring, inspection, and safety assessment. For these robots to operate effectively, they must perceive and interpret complex, dynamic environments populated by workers, machinery, and unstructured terrain. Achieving reliable perception depends on high performing semantic segmentation models trained on large volumes of annotated data—an expensive and logistically challenging requirement in construction due to privacy restrictions, variable site access, and slow digitalization. This research addresses the challenge of limited labeled data by investigating transfer learning as a label-efficient approach for construction-site segmentation. Specifically, it explores whether road construction imagery—abundant …

Truck Drivers And Autonomous Trucks: A Topic Modeling Analysis Of Truck Driver Posts, Noah Britt, Amy M. Schuster, Shubham Agrawal, Chu-Hsiang Chang, Jenna A. Van Fossen, Elizabeth A. Mack, Sheila R. Cotten

Publications

Social media provides a rich, alternative data source to interviews or survey-based research to study hard-to-reach populations (e.g., truck drivers, because of their transient work structure and unique subculture). This study uses public social media posts from the largest trucking forum in the United States to examine truck drivers’ views on autonomous trucks (ATs), which are poised to transform the trucking industry. We expand on traditional qualitative strategies of analyzing social media data by combining newer methods, including BERT-based topic modeling, sentiment analysis, stance detection, emotion analysis, topic similarity, and location analysis through a social interaction network, to analyze a …

Cal Poly (Cp) Legged Robot, Sebastian Barboza, Jonathan Mchale, Isabella Sorensen, Isaac Golan

Mechanical Engineering

The Navy spends $60 billion annually on dangerous ship maintenance performed by sailors. To save lives and resources, the Naval Surface Warfare Center (NSWC) is looking for robots to replace sailors and navigate ships to perform various tasks. Robots with tracks and wheels have been most recently explored by NSWC, however they have encountered significant problems navigating the ships, especially through naval ship doorways with a significant ledge. By using a legged robot, our team hopes to solve these problems and have a robot that can navigate the ship with relative ease and stability.

Towards Automated And Explainable Insider Threat Response In Electronic Health Records: A Role-Aware Machine Learning Framework, Luca Lippi Ornstil

Master's Theses

Healthcare remains a prime target for cyberattacks, with insider misuse and credential compromise posing major risks to Electronic Health Records (EHRs). This thesis introduces a role-aware, explainable anomaly detection and response framework integrated with OpenEMR to address post-authentication threats. Four models—Local Outlier Factor (LOF), Isolation Forest, Autoencoder, and Graph Neural Network (GNN)—detect behavioral deviations across temporal, device, and role-based features, with LOF serving as the primary runtime detector. A configurable policy engine maps anomaly severity to proportional actions, from email alerts to read-only restrictions or account suspension, all reversible and auditable. Evaluation on real EHR logs shows the system’s operational …

Analysis Of A Cloud-Based Robot Motion Planning System, Yusif Mardanzade, Latafat Abbas Gardashova

Chemical Technology, Control and Management

As a result of the integration of cloud computing technologies into the field of robotics, the concept of "cloud robotics" has emerged. Unlike traditional robots, cloud-based robot systems remove computation, memory, and even some software from the local device and rely on remote resources obtained over the network. This approach ensures that robots are not limited only by their internal computing capabilities and allows them to take advantage of the wide range of opportunities offered by the cloud infrastructure. As a result, robots have access to large databases, highly parallel computing, and collective learning capabilities anytime and anywhere. In addition, …

Crisis Observatory: Extracting Credible Signals During A Crisis In The Age Of Llms, Kuan-Chieh Lo, Pranav Maneriker, Sriram Sai Ganesh, Dominik Winecki, Kelly Garrett, Ayaz Hyder, Arnab Nandi, Valerie Shalin, Shannon A. Bowen Ph.D., Amit Sheth, Srinivasan Parthasarathy

Publications

Systems for crisis response have required several different models for the analysis of unstructured text, such as identifying needs, locations, topics, routing, and matching of needs with available responders. Large Language Models (LLMs) have replaced task-specific models across various language processing tasks. However, LLMs are known to be limited by their training data, collected before the crisis. In this demo, we explore the use of LLMs for crisis response scenarios with rapidly evolving information environments. We show how the augmentation of these models with external reliable sources of crisis-specific information can help build adaptive systems for response. The demonstration video …

Environment Mapping And Gps-Based Trailer Parking Using Low-Cost Peripheral Sensors And Post-Processing Algorithms, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper explores the merit of software data optimization through two practical examples: environment mapping & GPS navigation.

Sistemas De Información Geográfica En La Era De La Digitalización, Jairo Eduardo Márquez Díaz, Luis Gonzalo Benavides Ramírez, Arles Prieto Moreno, Martha Andrea Manrique Castro

Ingeniería

En la era digital, la información geográfica es esencial para la toma de decisiones en áreas como la planificación urbana, la gestión de recursos naturales y la seguridad. Los Sistemas de Información Geográfica (SIG) se han establecido como herramientas indispensables para gestionar, analizar y visualizar datos georreferenciados que permite la creación de mapas digitales y la toma de decisiones basada en evidencia. Este libro aborda los fundamentos, las tecnologías y las aplicaciones de los SIG, explorando su evolución y su potencial en un entorno digital en constante transformación. A lo largo de sus cinco capítulos, el libro aborda temas esenciales …

Mosquito Classification And Explainability From Image Data Via Deep Learning Techniques, Farhat Binte Azam

USF Tampa Graduate Theses and Dissertations

According to the World Health Organization (WHO), mosquitoes are the deadliest animals on Earth, responsible for more human deaths annually than any other species. Mosquito-borne illnesses continue to pose severe risks to global health. In 2015 alone, there were an estimated 214 million malaria cases worldwide. Similarly, a 2016 report from the Centers for Disease Control and Prevention (CDC) revealed that Puerto Rico’s Department of Health received over 62,500 suspected cases of Zika, with 29,345 confirmed positive cases. In 2019, Southeast Asia experienced its worst dengue outbreak in recorded history. Of the approximately 4,500 mosquito species distributed across 34 genera, …

Blockchain-Driven Pharma Supply Chains Towards Industry 6.0, Vijay Ramasamy R

Theses and Dissertations

The pharmaceutical supply chain is undergoing an unprecedented evolution in the wake of Industry 6.0, driven by the need for heightened transparency, security, and real-time intelligence. However, current systems suffer from legacy Enterprise Resource Planning (ERP) constraints, the risk of counterfeit products, temperature sensitivity, and scalability issues due to the surge in Internet of Things (IoT) data.

This research proposes a unified, blockchain-based framework that integrates legacy ERP systems, advanced AI driven forecasting, IoT-enabled traceability, and quantum-enhanced blockchain security to modernize pharmaceutical supply chains.

The study begins by addressing interoperability between ERP and blockchain using middleware and smart contracts, facilitating …

Retracted: Analysis Of Energy Sector Co2 Emanations Using Wavelet-Based Numerical Technique, Yeshwanth R., Kumbinarasaiah S.

Iraqi Journal for Computer Science and Mathematics

This study aims to present the modified Chebyshev wavelet collocation method (CWCM) to investigate and obtain the numerical approximation of $CO_2$ emissions from the energy sector utilizing the fractional mathematical model. The need for energy rises as the population grows. Burning fossil fuels produces a significant portion of the world's energy, which raises the atmospheric concentration of $CO_2$ and causes global warming. The combination of mathematical modeling studies and numerical simulations allows us to understand the $CO_2$ emissions from the energy sector. Our objective is to build an operational matrix of integration (OMI) based on Chebyshev wavelets and use it …