Engineering Commons^™

Simulation Study On Adaptive Signal Control Of Deformed Intersection Based On Lstm-Gnn, Kun Chen, Liang Chen, Jiming Xie, Fengbo Liu, Taixiong Chen, Lukuan Wei

Journal of System Simulation

Abstract: Aiming at the traffic congestion at deformed intersections, an improved adaptive traffic signal control scheme based on deep learning is designed, the scheme integrates the adaptive signal control of LSTM and GNN at deformed intersections. LSTM is used to capture the dependence between time series traffic data, while GNN is used to construct a spatial interaction model between lanes. By integrating the information of time and space dimensions, the model can dynamically adjust the phase duration of signal lights according to real-time traffic conditions. The results indicate that the LSTM-GNN adaptive control scheme improves overall traffic throughput efficiency by …

Modeling And Simulation Of Dual-Podded-Propulsion Ship Motions, Bing Han, Yunhe Lin, Yuhang Chen, Zhouhua Peng

Journal of System Simulation

Abstract: Aiming at the autonomous navigation control requirements of the Dalian Maritime University's dual-purpose intelligent research and training ship "Xin Hong Zhuan," the design of the motion model for this dual-podded-propulsion ship is carried out. Utilizing an MMG model structure, it calculates the hull's hydrodynamic viscous forces, single/dual-propeller thrust, and hydrodynamic forces acting on the podded propulsion units. Based on data from sea trials and open-water propeller tests, straight-navigation resistance is derived via data fitting, while a method using simulated turning circle tests and PSO algorithms is proposed to determine some hydrodynamic coefficients, refining existing empirical formulas. The model's maneuvering …

Research On Scenario-Driven Virtual Simulation Test Method For Autonomous Escort Function Of Habor Tugs, Shijie Li, Jialin Li, Jialun Liu, Chengqi Xu, Zhilin Dong

Journal of System Simulation

Abstract: In order to comprehensively construct the test scenarios and verify the reliability of the tugboat autonomous companionway function, a scenario-driven virtual simulation test method for the tugboat autonomous companionway function is proposed. Based on the relative heading, relative speed and relative position of the target ship and the tugboat, the test cases of the tugboat autonomous companionway scenario are generated, and the complexity of the test cases is evaluated by using the fifthorder Bessel curve. The autonomous companion navigation function of the tug is verified through simulation experiments on the complex typical test scenarios without and with obstacles. The …

Construction Method Of Digital Twin System For High-Low Temperature Test Chamber, Qinghua Chen, Zuoyou Liang, Weijuan Guan, Jiadong Ji, Ping Liu

Journal of System Simulation

Abstract: In view of the construction requirements of the digital twin system of the high-low temperature test chamber, the EMQX server with MQTT as the communication protocol is used for data transmission. Driven by real-time data, real-time dynamic interactive mapping between the physical entity and the virtual model is realized. The neural network model and genetic algorithm are used to evaluate and predict the running state of the equipment and provide the system adjustment strategy, so as to realize the whole climate, life and working condition of the staff to understand the running state of the equipment, and effectively ensure …

Cooperative Guidance For Multigroup Flight Vehicles Against Multiple Targets With Separated Impact Time, Guofei Li, Shituo Li, Yilun Huangfu, Yueyang Hua, Yunjie Wu, Zongyu Zuo

Journal of System Simulation

Abstract: To cope with cooperative guidance against multiple targets, a distributed cooperative guidance for multigroup flight vehicles to strike multiple targets with separated impact time is proposed. The collaborative variables for multigroup flight vehicles with separated impact time are given, and the guidance law in the line of sight (LOS) is proposed. The guidance laws on the normal and lateral directions of the LOS are proposed to make the LOS deflection angle rate and LOS the inclination angle rate converge rapidly, which ensures that each vehicle is able to strike the target. The finite-time convergence of the proposed guidance laws …

Automatic Multi-Objective Optimization Based On Dynamic Storage Location Allocation Strategy, Juan Chen, Wang Zheng, Qianqian Liu, Bin Lu

Journal of System Simulation

Abstract: Based on the dynamic storage allocation strategy, the two-stage optimization model is constructed with the whole warehouse as the main optimization body, in order to meet the safety and rationality of the storage allocation goals, and to meet the dispatching goals of the shortest operation time and the lowest energy consumption of each stacke. The upper and lower levels of the model are typical multi-objective optimization problems, and the ideal solution of the upper level model will be the initial condition of the lower level model. The multi-objective genetic algorithm is used to solve the ideal solution of the …

Soft Sensor Modeling Based On Adaptive Sparse Broad Learning System⋅, Kangping Du, Lin Sui, Weili Xiong

Journal of System Simulation

Abstract: To address the challenges posed by nonlinearity and the coupling of multiple features in complex industrial processes, resulting in increased model complexity and decreased performance, a soft sensor modeling method based on adaptive sparse broad learning system is proposed. Building upon the lateral enhancement transmission of features, the trace least absolute shrinkage and selection operator (LASSO) is further used to optimize the feature weights of the network, adaptively adjusting the penalty intensity based on the correlation between different variables to enhance the feature extraction capabilities of the model. The Dropout mechanism is introduced in the enhanced part, and the …

Enhanced Artificial Gorilla Algorithm For Mobile Robot Path Planning, Chen Ye, Peng Shao, Shaoping Zhang, Wenting Li, Tengming Zhou

Journal of System Simulation

Abstract: To address the issues of susceptibility to local optima and slow convergence in mobile robot path planning within complex terrain scenarios, an enhanced artificial gorilla troops optimizer with integration of quadratic interpolation and elite individual genetic strategies (QGGTO) is proposed. The algorithm integrates quadratic interpolation and elite individual genetic strategies to promote information exchange among candidate solutions, thereby accelerating convergence, while maintaining population diversity to avoid local optima. For complex terrains containing both regular and irregular obstacles, a cost function that comprehensively considers walking distance, safety, and turning angles is constructed to uniformly evaluate the path planning performance of …

Dynamic Path Planning For Robotic Arms Based On An Improved Ppo Algorithm, Yuhang Wan, Zilu Zhu, Chunfu Zhong, Yongkui Liu, Tingyu Lin, Lin Zhang

Journal of System Simulation

Abstract: Aiming at the increased environmental uncertainties and more difficult modeling for robotic arm path planning in unstructured environments, an approach to dynamic path planning of robotic arms based on an improved PPO algorithm is proposed. In order to solve the problem that the input length of the state space is not fixed due to the change of number of obstacles in dynamic environment, an environmental state input processing method based on the LSTM network is proposed, and the network structure of PPO algorithm is also improved; a reward function is designed based on the artificial potential field method, and …

Multi-Model Based Iterative Method For System-Of-Systems Architecture Design, Xuemeng Zhao, Tianzhu Ren, Zhemei Fang

Journal of System Simulation

Abstract: In order to solve the problems of difficulties in expressing dynamic characteristics and lack of decision analysis support in developing models of the department of defense architecture framework (DoDAF), an integrated iterative method for combat SoS architecture design is proposed. The DoDAF architecture model integrates and expresses combat-related information from multiple perspectives; the ExtendSim executable model simulates the emergence behavior and dynamic characteristics of combat SoS architecture in multiple scenarios; and the decision model quantitatively analyzes and selects architecture schemes by multi-objective decision rules. Ultimately, a SoS architecture integrated iterative design method of "view-simulate-decide-iterate" is formed. The design process …

Self-Supervised Defect Detection Via Discriminative Enhancement-Based Distillation Learning, Zhiyuan Feng, Ying Chen

Journal of System Simulation

Abstract: To address the issues of scarce and unknown types of abnormal defect data and the lack of diversity in anomaly representation in conventional knowledge distillation defect detection methods, a self-supervised distillation learning method based on discriminative enhancement is proposed. An attention-based multi-scale feature fusion module is proposed, which enhances the capability of anomaly representation by amplifying the multi-scale feature differences between the student network and the teacher network. A discriminative network composed of a feature reweighting module and a decoder is designed to generate more accurate anomaly score maps by further emphasizing the anomaly features in the teacher network, …

Research On Robot Dynamic Obstacle Avoidance Method Based On Improved A* And Dynamic Window Algorithm, Yan Zhang, Binghua Li, Tao Huo, Rong Liu

Journal of System Simulation

Abstract: Aiming at the problems that the traditional A* algorithm has too many extension nodes and path turning points, and can't deal with dynamic obstacles in complex environment, a robot obstacle avoidance method combining improved A* algorithm and DWA algorithm is proposed. The A* algorithm improves the neighborhood expansion method and effectively avoids the problem of redundant nodes in the classical four-neighborhood expansion and the path through the obstacle in the eight-neighborhood expansion. A quadrant selection method is proposed, which can effectively reduce the number of extended nodes in the path search process. The redundant point elimination strategy is proposed …

A Drl⁃Based Approach For Distributed Equipment Nodes Selection, Ziyi Wang, Kai Zhang, Dianwei Qian, Yuzhen Liu

Journal of System Simulation

Abstract: Aiming at the problem of insufficient solution speed and poor generalization of traditional algorithms in large-scale scenarios, this paper intelligently solves the large-scale distributed equipment system preference problem based on deep reinforcement learning. According to the characteristics of distributed equipment system combat, using the complex network to its graph form modeling, and based on the attention mechanism to the equipment between the connecting edge relationship for the characterization, in order to build a distributed equipment system digital simulation environment. Simulation results show that compared with the genetic evolutionary algorithm, the obtained model has obvious advantages in terms of solution …

Effect Of Cage Eccentricity On Moment Capacity Of Drilled Shafts, Jason Schaefer Steinbach

USF Tampa Graduate Theses and Dissertations

During the construction of drilled shafts, reinforcement cages can be inadvertently placed eccentrically. Current codes, such as ACI 318 and AASHTO LRFD Bridge Specifications, assume there is little impact from such movements within the drilled shaft or that cage centering provisions are sufficiently robust. This thesis will explore the impact that reinforcement cage eccentricity has on the bending capacity of drilled shafts and propose new strength reduction and resistance factors for tension-controlled failure in drilled shafts.

A total of 208 drilled shafts across eleven counties within the state of Florida were tested using thermal integrity profiling to identify the worst …

Towards Sustainable Manufacturing: A Framework For Resource Conservation And Waste Mitigation, Mahmood Talal Sultan

Thesis/ Dissertation Defenses

The manufacturing industry drives economic expansion, but it also contributes significantly to environmental change and shortages of resources. Therefore, the transformation to sustainable manufacturing has become an urgent need, driven by worldwide efforts to address climate change, minimize waste, and protect valuable assets. This thesis develops a robust framework tailored to the manufacturing sector, focusing on resource conservation and waste reduction. The framework is built on the identification and categorization of Key Performance Indicators (KPIs) and assessment tools, which address five major implementation challenges: complex supply chains, regulatory barriers, economic challenges, technological limitations, and social and cultural challenges.

To build …

Artificial Intelligence In Surveillance And Privacy, Elizabeth D. Brasher

NEXUS: The Liberty Journal of Interdisciplinary Studies

This paper attempts to provide insight into the new and developing world of artificial intelligence and its integration into surveillance technologies. These technologies being implemented by the government, retail companies, healthcare organizations, and more, all raise ethical questions and implications addressed in this article; other topics, such as the integration of Christian ethics and responsibilities, are also explored.

Empowering Tanzanian Education: Personalized And Accessible Test Preparation, Brian Wiebe, Shiv Jhalani

Computer Science and Engineering Senior Theses

Only 20% of students performed well enough on their secondary exams to continue their A-level studies. This challenge exists due to a lack of resources, classroom overcrowding, and absenteeism of the instructors. The project focuses on improving the pass rate for these national exams; we have built an intelligent quiz generating platform that helps Tanzanian students prepare more effectively for exams by meeting user needs including active recall, answer explanations, increasing difficulty, and filtered studying. Students can select the subject, form level, topic, and the difficulty level, and the platform provides different types of questions, including true/false, multiple choice, and …

Bridging Virtual Robots And Physical Tasks Via Augmented Reality, Xiangfei Kong

USF Tampa Graduate Theses and Dissertations

Entry to human-robot interaction research, e.g., conducting empirical experiments, faces a significant economic barrier due to the high cost of physical robots, ranging from thousands to tens of thousands. This cost issue also severely limits the field’s ability to replicate user studies and reproduce the results to verify their reliability, thus offering more confidence to incorporate these findings. Although virtual reality (VR) user studies present a potential solution, it is unclear whether we can confidently transfer the findings to physical robots and physical environments because VR isolates both the physical robot and the physical world where robots operate. To address …

Embedding-Based Deep Learning Frameworks For Multimodal Oncology Data Integration, Aakash Gireesh Tripathi

USF Tampa Graduate Theses and Dissertations

This dissertation presents a cohesive set of novel frameworks developed to address critical challenges in oncology data integration, representation learning, and clinical information extraction. The work encompasses four interconnected projects: MINDS (Multimodal Integration of Oncology Data System), HoneyBee (Harmonized ONcologY Biomedical Embedding Encoder), LLM Extraction (Large Language Model-based Extraction from Pathology Reports), and EAGLE (Embedding Analysis for Generalized Learning in Oncology). Together, these systems enable the unification of diverse cancer data modalities—from genomics and clinical records to histopathology images and radiological scans—creating a robust foundation for advanced machine learning applications in precision oncology. By addressing key barriers in data accessibility, …

Examining Green And Chemical Methods For Zero-Valent Iron Nanoparticle Synthesis In Heavy Metal Adsorption, Juan Ferro-Falla, Lewis Stetson Rowles, Farith Diaz Arriaga, Jaime Plazas-Tuttle

Civil Engineering & Construction: Faculty Publications

The increasing concern over heavy metal contamination in water has necessitated the development of sustainable and efficient treatment methods. This study compares two synthesis approaches for zero-valent iron nanoparticles (nZVI) for cadmium, chromium, and arsenic removal: chemical reduction using sodium borohydride and green synthesis utilizing cocoa husk extracts combined with hydrothermal carbonization (HTC). Chemically synthesized nZVI exhibited high initial removal efficiencies (>98%), though desorption effects occurred over time due to particle aging. In contrast, green-synthesized nZVI, stabilized by a carbon matrix, maintained consistent removal efficiencies above 98% for 120 h under acidic conditions, showcasing superior stability and reactivity. Characterization …

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofrendly Systems, Noora Al Mansoori

Thesis/ Dissertation Defenses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

Engineering Bio-Based Poly (Ethylene Furanoate) Blends And Nanocomposites, Safa Fadl Eldin Mohamed

Thesis/ Dissertation Defenses

The growing demand for sustainable materials has directed attention toward bio-based polymers such as poly(ethylene furanoate) (PEF), a 100% bio-derived alternative to PET. While PEF offers excellent gas barrier and thermal properties, its limited mechanical strength restricts its use. This study explores polymer blending and nanocomposite strategies to enhance PEF’s mechanical and electrical performance.
Blending PEF with linear low-density polyethylene (PE) using reactive compatibilizers (SEBS-g-MA, PE-g-MA) significantly improved ductility and tensile toughness. Interfacial reactions between PEF and compatibilizers transformed the blend morphology, resulting in improved flexibility suitable for packaging applications.
Electrically conductive composites were developed by localizing graphene nanoplatelets (GNP) …

Knee-Thigh-Hip Impact In Children: Effects Of Age And Impact Velocity, Mohammad Ziad Turki

Thesis/ Dissertation Defenses

Brief introduction: This thesis examined the crash impact injury outcomes of the knee-thigh-hip complex (KTH) in children based on age and impact velocity using computational modelling. Child occupant (3YO, 6YO, 10YO) Total Human Body Model for Safety (THUMS) models developed by Toyota were used to evaluate the effects of age and impact velocity on pediatric KTH crash impact response. Aims: The main objectives of this thesis are to analyze the effect of child age and impact velocity on KTH crash impact response. Methods: The knee impact simulations were performed based on different impact velocities (1.2, 3.5, 7.2, …

An Integrated Geophysical Approach For Estimating The Depth Of Mineral Potential In Some Part Of Basement Complex Terrain Southwestern Nigeria, Hamid Titilope Oladunjoye, Joseph Coker, Niyi-Ola Adebisi, Omolara Abosede Adenuga, Sofiat Adetomilola Adekoya, Aderemi Alabi, Abisola Akinmoladun

Al-Bahir

Effective mineral exploration in a basement complex necessitates precise delineation of overburden thickness and mineral potential within the Basement Complex terrain. This study examined the subsurface geology and assesses the abundance of prospective mineral deposits within the study area The objective of the study was to outline the overburden thickness and infer mineral potential using integrated ground magnetic and electrical resistivity geophysical methods. The electrical resistivity method unraveled the litho-stratigraphic sequence as surmised from geo-electric layers. Consequently, the mineralization of the basement delineated was characterized by the magnetic method. The acquired data were processed using WINRESIST and Oasis Montaj respectively. …

Cross-Cultural Inspiration Coach, Romeo Nickel, Veronica Flores, Rahul Rani, Andrew Yang

Computer Science and Engineering Senior Theses

Personal inspiration and motivation are fundamental drivers of well-being and growth, yet current digital wellness solutions predominantly reflect Western perspectives, failing to address the diverse cultural contexts through which inspiration manifests globally. This thesis presents the development of an Inspirational Coach platform that leverages artificial intelligence to deliver culturally-adaptive personal development content. The system employs a fine-tuned Llama 3.1 8B model using Low-Rank Adaptation (LoRA) techniques to generate personalized motivational content that incorporates users’ cultural backgrounds, personal themes, and individual preferences.

The platform integrates four core features within a comprehensive React-based web application: guided journaling with mood tracking, goal setting …

Teaching Computer Science Through An Educational Game, Aidan Walker, Matthew Leonard, Grant Goldman

Computer Science and Engineering Senior Theses

In our ever-evolving technological landscape, it is becoming more and more important for students of all ages to have at least a basic concept of coding fundamentals. It’s not just the basic knowledge of how to code; knowing important coding concepts is just as important. To help introduce these concepts to young students, we developed an educational game in the Roblox platform aimed at teaching foundational programming concepts—specifically recursion—to young learners through interactive and engaging gameplay. Leveraging Roblox’s accessibility and popularity among younger audiences, the game introduces players to recursive thinking in a visual and intuitive manner. Players control a …

Self Driving Robot Car, Eric Hicks, Ruby Huynh

Computer Science and Engineering Senior Theses

In the real world, vehicular crashes are the result of human error and inadequate reaction time and are often deadly. Due to the issue of accidents being frequent occurrences, using machine learning to drive vehicles has quickly become a relevant topic as it could potentially become a way to minimize fatalities and damages. Thus, the project aims to approach self-automation with the focus on maximizing the vehicle’s performance and the machine’s ability to make the best decisions within that time.

Today’s self-driving cars use radar or cameras as well as digital signal processing algorithms to sense the environment while using …

Tcras: Traffic Control Risk Analysis System, Owen Matejka

Computer Science and Engineering Senior Theses

Traffic intersections represent critical points of conflict in urban transportation networks, with over 40,000 traffic-related fatalities occurring annually in the United States alone. Traditional intersection monitoring systems, based on timer controls and inductive loop detectors, lack the sophisticated detection capabilities needed to address modern traffic safety challenges. This thesis presents the Traffic Control Risk Analysis System (TCRAS), a low-cost, computer vision-based solution that democratizes access to advanced intersection monitoring capabilities. TCRAS leverages edge AI processing through Hailo neural network accelerators combined with open-source computer vision algorithms to provide comprehensive intersection analysis. The system performs real-time multi-class object detection and tracking …

A Universal Lstm Stock Price Predictor Utilizing News Sentiment Analysis And Technical Indicators, Kelly Zhou, Zhirong Wang

Computer Science and Engineering Senior Theses

The stock market is influenced by a complex interplay of factors, including historical price trends, technical indicators, news sentiment, and macroeconomic conditions. Traditional stock prediction models typically focus on a single stock, limiting their ability to capture broader market relationships. Investors require a model that can accurately forecast price movements across multiple stocks to optimize trading decisions.

We propose a universal stock prediction model that leverages relationships across all S&P 500 stocks. Unlike traditional single-stock models, our approach utilizes a multi-stock LSTM architecture trained on a combination of historical stock prices, technical indicators, and news sentiment. The model is designed …

Preserving Yucatán’S Agricultural Heritage: A Mobile App For Agricultural Sustainability, Fernando Rojas, Jason Serrano, Kavya Sharma

Computer Science and Engineering Senior Theses

We developed a mobile application that preserves Yucatán’s agricultural heritage and supports local farmers, while addressing the urgent need for the technology-driven integration of Mayan agricultural knowledge, specifically the Milpa system, into an accessible mobile platform. Our objective was to create an intuitive, culturally appropriate, and low-technology resource to support farmers in making informed, sustainable agricultural decisions, regardless of their internet connection. We saw this as critical for enhancing agricultural practices in Yucatán and beyond. We accomplished this by creating a trilingual (Spanish, English, and Yucatec Maya) mobile app with features such as agrarian cycle information, mapping and location services, …