Engineering Commons^™

Noise-Optimized Routes For Air Taxi, Waleed Raza

Doctoral Dissertations and Master's Theses

Community noise is a primary barrier to the public acceptance and deployment of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) air taxi operations. This dissertation develops a coupled siting, routing, and noise optimization framework that links vertiport placement to its downstream acoustic consequences, demonstrated through a Daytona Beach case study. Candidate vertiports are screened and selected using accessibility, safety, demand, and feasibility criteria, and the selected sites form a directed network of 20 routes. Each trajectory is evaluated with a physics-based acoustic pipeline reporting Lmax, SEL, and EPNL at school, hospital, and residential receptors, showing that received exposure …

Online Ppo-Based Multi-Hop Task Offloading Strategy For Vehicular Edge Computing, Wenzhu Zhang, Yuewei Bian, Fuli Xiong, Siqi Cai

Journal of System Simulation

Abstract: To address the problems of frequent communication link interruptions caused by dynamic network topologies and the sharp increase in computational complexity triggered by high-dimensional decision spaces in the vehicular edge computing (VEC) environment, a multi-hop task offloading strategy for VEC based on an online PPO algorithm was proposed. A multi-hop task offloading optimization model simultaneously considering link effective time, transmission rate, and computing resource constraints was constructed; a multi-hop A* path search algorithm integrating link stability and end-to-end delay was designed; an online offloading decision framework based on PPO was proposed, which transformed the 0-1 mixed integer nonlinear programming …

Improved Pbs Algorithm For Multi-Agent Path Planning Based On Conflict Guidance And Punishment Mechanism, Jinbao Zhang, Jianlin Mao, Chengze Qian, Guimi Sun, Kaixin Tong

Journal of System Simulation

Abstract: To address the bottleneck in which the priority-based search (priority-based search, PBS) algorithm for multi-agent path planning easily falls into conflict loops and generates invalid node expansions in complex scenarios, an improved algorithm based on conflict guidance and a punishment mechanism (improved PBS multi-agent path finding algorithm based on conflict guidance and punishment mechanism, CGP-PBS) was proposed. A conflict-guided node expansion mechanism was constructed; in high-level search, it comprehensively evaluated path cost and the number of conflicts, preferentially expanded child nodes with high potential for conflict resolution, and delayed the expansion of high-conflict nodes, thereby effectively compressing the search …

Research On Temporal Action Localization Methods For Cross-Modal Understanding, Jinwei Li, Xiaoyang Liu, Rusheng Ju

Journal of System Simulation

Abstract: To address the problems of insufficient localization accuracy and high model complexity in the temporal action localization (TAL) task for video-text cross-modal understanding, an anchor-free action transformer (AFAT) model was proposed. Based on the anchor-free framework, the local self-attention mechanism of Transformer was introduced to enhance the global modeling capability of temporal features. A multi-scale feature pyramid structure was combined to strengthen the representation of actions with different durations, and a lightweight predictor was adopted to reduce computational redundancy. Experimental results show that the average precision of this model on the THUMOS14 dataset is significantly improved compared with the …

Robot Remote Control Utility, Jeremy Cantu, Paul Uhlig

Systems Manuals - 2026

The purpose of this document is to describe the Robot Control Management Utility developed in the course of this graduate project. Information included in this document will include the background of the developed product, as well as the functional requirements, data structures, software modules, interface design, installation guide, and sample and troubleshooting guides.

Dataset To Analyzing Energy Use In 2 & 3d Imaging Systems And Workflows, Michael J. Bennett

Published Works

Analyzing Energy Use in 2D & 3D Imaging Systems and Workflows Dataset

CONTENTS: Z-WaveReportingProfiles; SessionInput; DroneFlights; SessionsComputed; Types; ByType; GrossSummaryUnweighted; WeightingSummary; Raw Sampling History Data

Resilience Modeling Method For Combat System-Of-Systems Based On Hypernetwork And Game Theory, Yuxian Duan, Hanqiang Deng, Jiarui Zhang, Jian Huang, Shijia Zhang

Journal of System Simulation

Abstract: In view of the difficulties in dynamic reconfiguration and resilience evaluation faced by modern combat system-of-systems in a highly adversarial environment, and the deficiencies of existing studies in depicting high-order interaction relationships and cluster evolution mechanisms, this paper proposed a resilience modeling method for combat system-of-systems integrating hypernetwork and game theory, aiming to analyze the resilience mechanism of the system-of-systems in all dimensions from micro, mesoscopic, to macro levels. At the micro level, a high-order motif structure was introduced to represent the complex interaction modes among combat units, which overcame the information loss of traditional binary relationships in depicting …

Simulation Study Of Elevator Group Control Scheduling Based On Real-Time Occupancy Perception, Yiyong Han, Shiyu Wang, Yang Ye, Zhen Zhang, Fengque Pei, Minghai Yuan

Journal of System Simulation

Abstract: To address the conflict between car space allocation and peak passenger flow response efficiency in elevator group control scheduling, a multi-objective scheduling method based on proximal policy optimization (PPO) with real-time occupancy perception was proposed. A simulation environment considering car capacity constraints was constructed, and a reward-penalty mechanism with average passenger waiting time, system energy consumption, and car congestion as optimization objectives was designed. Based on this, state and action spaces were defined to form a PPO-based scheduling framework; a simulation platform integrating traffic flow visualization, policy scheduling, and performance evaluation was developed. Simulation results show that this method …

Adaptive Spatiotemporal Graph Neural Network-Based Net Load Forecasting For Residential Areas, Yongqi Yang, Cong Wang, Hongli Zhang, Ping Ma, Yue Meng, Tianhao Zhou

Journal of System Simulation

Abstract: To address the issue that traditional residential overall power load forecasting methods fail to fully consider the differences in users' electricity consumption habits, making it difficult to improve prediction accuracy, a residential net load forecasting method combining representation learning clustering and an AGCN-Transformer was proposed. The representation learning method was utilized to fully extract the latent features of users' net load data, and users were divided into different groups based on the similarity of electricity consumption behaviors; the net load data of the same group were aggregated, and a graph structure suitable for this task was constructed by comprehensively …

Evolution And Prospects Of Polarization Image Simulation Technology, Gengpeng Li, Wei Cai, Zhiyong Yang, Zhili Zhang, Xiaowei Wang

Journal of System Simulation

Abstract: Polarization image simulation technology is a key means to break through the bottleneck of polarization data acquisition and promote the development of polarization vision. This study systematically reviewed three evolutionary paradigms of this technology: Physical mechanism simulation, based on the polarization bidirectional reflectance distribution function and polarization ray tracing, strictly solves polarization light transmission, which has high interpretability and credibility, but it is computationally complex and lacks visual realism. Data-driven simulation, using models like neural radiance fields to learn polarization appearance from data, has high generation efficiency and visual fidelity but weaker physical consistency and interpretability. Physics-data fusion simulation …

Mbse Design And Approach-Phase Operational Simulation Of Bdsbas Airborne Receiver, Ruihua Liu, Tongwei Wang, Zan Ma

Journal of System Simulation

Abstract: In view of the problem that traditional document-based design methods are difficult to effectively capture the dynamic characteristics and internal interactions in navigation accuracy and integrity assurance required by BeiDou satellite-based augmentation system (BDSBAS) airborne receivers during the approach phase, which easily leads to designs deviating from actual requirements and affects system performance, a model-based systems engineering(MBSE) method was introduced. A multi-dimensional system architecture model encompassing system requirement analysis, behavior description, structure design, and parameter constraints was established. Taking BDSBAS as the object, a co-simulation method of system modeling language and MATLAB for required navigation performance (RNP) was proposed, …

Simulation Study On The Vulnerability Of Belt And Road Composite Transportation Network Based On Cascading Failure, Mingjun Qian, Chao Yin, Zhiwen Huang, Quanneng Wang

Journal of System Simulation

Abstract: To address the issues of unclear cascading failure propagation mechanisms and difficult-to-quantify vulnerability evolution laws caused by the structural complexity and node heterogeneity of the "Belt and Road" multimodal transport network, a vulnerability assessment method for composite transportation networks integrating physical analogy and improved cascading failure model was proposed. Sub-networks were constructed based on main transportation modes of the Belt and Road, and nodes in the same city were coupled to build a composite transportation network model. An information entropy-Joule's law model was constructed to identify key nodes of the composite network and its subnetworks. A load-capacity cascading failure …

Distributed Cooperative Control Of Swarm Unmanned Aerial Vehicles Based On Multi-Route Clustering, Yuyang Xiong, Chuntao Li, Wenhao Qiu

Journal of System Simulation

Abstract: To address the collaborative control and formation maintenance problems of large-scale swarm unmanned aerial vehicles, a distributed cooperative control method for unmanned aerial vehicles based on multi-route clustering was proposed. Leveraging the characteristics of multiple routes, the overall cooperative control problem of the swarm was decoupled into the cooperative control within the same route and the consensus control between multiple routes. Within the same route, a forward-neighbor information interaction mechanism was designed to determine the neighbor relationships, and a velocity-guided cooperative algorithm was utilized to achieve the desired velocity matching and spacing maintenance of unmanned aerial vehicles; between multiple …

Multi-Scale Modeling Method For Intelligent Unmanned Aerial Vehicle Swarm Combat, Yelei Zhu, Shoulin Shen, Jiang Zhu, Chuanhua Wen

Journal of System Simulation

Abstract: Intelligent unmanned aerial vehicle swarm combat exhibits multi-scale characteristics of microlevel tactical autonomy, meso-level resource constraints, and macro-level network collaboration. In view of the problem that a single-scale modeling method is difficult to simultaneously characterize individual decision-making details, resource flow process, and system collaboration mechanism, a multi-scale modeling method integrating multi-agent modeling, system dynamics, and complex network theory was proposed. By designing six formal coupling operators to achieve cross-layer information mapping, a time progression mechanism based on a master-slave clock and hybrid synchronization was established, and a proof of error boundedness was provided. A prototype system was implemented on …

Modeling And Simulation Of Efficient State Information Diffusion In Wireless Ad Hoc Networks, Mengyao Jia, Shaozhu Gu, Junhan Wang, Denghao Wang, Du Xu, Xiaoning Zhang

Journal of System Simulation

Abstract: To solve the problems of significant communication overhead and limited real-time response capability in the traditional flooding-based state diffusion mechanism, an efficient diffusion algorithm based on regional partitioning and information compression was proposed. A multi-dimensional feature clustering method integrating geographic distance and link quality was used to achieve high-cohesion network partitioning through weighted Euclidean distance and the K-means algorithm; a dynamic selection mechanism for representative nodes was designed to conduct comprehensive scoring by combining the link quality and geographic centrality of nodes, realizing the efficient compression and aggregated transmission of regional information. Simulation results indicate that the algorithm significantly …

Research On Safety Monitoring System For Digital Twin Fully Mechanized Mining Face In Thin Coal Seams, Ya Liu, Zhaoyun Zhang, Cheng An, Canguang Zheng

Journal of System Simulation

Abstract: To solve the problems of opaque production processes, difficult expression of production information, and high difficulty in real-time model driving and safety monitoring in fully mechanized mining faces of thin coal seams, studying the use of digital twin technology and risk early warning models to solve beyond-visual-range visual production operations and safety monitoring control of the working face has important theoretical and practical value. This paper studied the construction methods of the digital twin system for fully mechanized mining faces in thin coal seams and discussed the construction of high-precision three-dimensional models, the real-time collection and processing conversion of …

Trajectory-Aware Dynamic Offloading For High-Mobility Vehicular Edge Systems, Haoran Xu, Zhiqin Huang, Youwu Hu, Zheyi Chen

Journal of System Simulation

Abstract: To address the problems of service interruptions, task failures, and resource waste caused by high mobility of intelligent vehicles (IVs) in vehicular edge computing (VEC), this paper proposes a trajectory-aware dynamic offloading (TADO) framework for high-mobility vehicular edge systems. A lightweight T-pattern trajectory-aware algorithm is designed to efficiently predict the next-hop road side unit (RSU) by mining spatio-temporal patterns from historical trajectories of vehicles, offering a forward-looking reference for offloading decisions. A joint optimization model is constructed, and a service interruption risk factor driven by trajectory prediction is introduced. An improved DRL method is developed. It takes the predicted …

Multi-Auv Pursuit Algorithm With Phased Guidance Based On Maddpg, Sen Zhang, Sihang Shen, Xiaojie Sun, Jingping Shao, Shuaiqiang Guo, Yingjie Deng

Journal of System Simulation

Abstract: To address the problems such as low exploration and sampling efficiency and sparse rewards in the early training stage under the complex target pursuit environment of multiple AUVs based on MADDPG, a phased-guidance curriculum MADDPG (PGC-MADDPG) algorithm was proposed. The pursuit task was divided into two phases, i.e., target tracking and encircling, through curriculum learning. In the target tracking phase, an experience strategy based on the APF method was introduced as a guidance item to provide prior knowledge of the target direction and accelerate the AUV training speed. After entering the encircling phase, the APF guidance item was removed, …

Study On Trajectory Optimization Of Spray Painting Robot Based On Improved Sparrow Search Algorithm, Jie Yang, Zhenkai Xiong, Longyan Wang

Journal of System Simulation

Abstract: To address the challenges posed by the complex working environment to the trajectory planning of the spray painting robot, a multi-strategy integrated sparrow search algorithm (MISSA) was proposed with the dual optimization objectives of time efficiency and motion smoothness. The 3-5-3 polynomial interpolation method was adopted to design the trajectory curve, aiming to ensure continuous angular displacement, angular velocity, and angular acceleration throughout the process. A multidimensional optimization problem with joint constraints was constructed using the total trajectory duration as the performance index. MISSA, which integrates refraction reverse learning, sine-cosine adaptive adjustment, and Cauchy mutation, was utilized to optimize …

Research On Multi-Objective Hybrid Flow-Shop Scheduling With Order Splitting, Junjie Yu, Weixi Ji, Chen Chen, Jingyu Lu, Chaoyang Zhang

Journal of System Simulation

Abstract: To address the order splitting multi-objective hybrid flow-shop scheduling problem (OSMOHFSP), a dual-objective optimization model was formulated with the objectives of minimizing makespan and total order tardiness. Fixed sub-batch specification constraints were incorporated to reflect common splitting limitations in actual production. A sub-batch generation strategy based on a candidate set of sub-batch specifications was designed to efficiently filter feasible splitting combinations, effectively reducing the search space dimensionality and computational complexity. A hybrid multi-objective metaheuristic algorithm integrating NSGA-II and SA was proposed. The global search capability was enhanced by constructing two crossover and four mutation operators. An improved SA embedding …

Ultra-Short-Term Photovoltaic Power Prediction Method Based On Spatio-Temporal Feature Enhancement Of Ground-Based Cloud Images, Zhiwei Kou, Fengyue Xin, Xiaoming Cui, Yu Yin, Feifan Li, Yongsheng Qi

Journal of System Simulation

Abstract: In view of the time lag in ground-based cloud image acquisition and the insufficient accuracy of existing photovoltaic power prediction models, an ultra-short-term photovoltaic power prediction method named spatial-temporal feature enhancement-ground-based cloud image-improved LSTM (STFE-GCI-ILSTM), which is based on spatio-temporal feature enhancement-ground-based cloud images-improved long short-term memory (LSTM) network was proposed. A ground-based cloud image prediction model with multi-scale spatio-temporal feature enhancement (STFE-GCI) was constructed. By spatial feature enhancement, temporal feature enhancement, and multi-scale feature fusion technologies, the deep spatio-temporal features of historical cloud image sequences were extracted to generate future predicted cloud image sequences, thereby eliminating the time …

Simulation Platform Based On Soc-Fpga Clusters For Cxl-Ethernet Heterogeneous Interconnection, Xu Zhang, Ke Liu, Mingyu Chen

Journal of System Simulation

Abstract: To address the difficulty of balancing simulation speed and topology flexibility when simulating large-scale, CXL-Ethernet heterogeneous interconnect datacenter scenarios with existing CXL simulation platforms, this paper presents CNetSim, a semi-physical simulation platform based on an SoC-FPGA cluster. The platform employs SoC-FPGA hardware to emulate endpoint nodes, leveraging their real processors and memory devices as well as FPGA-implemented CXL. mem protocol to support high-speed execution of standard Linux systems and real distributed applications. Meanwhile, it utilizes the flexible topology configuration capability of software simulation to implement CXL switched networks and inter-rack Ethernet interconnects based on DPDK on simulation servers. Simulation …

Optimization Of Convective Heat Transfer Parameters For Spindles Based On Finite Element Thermal Analysis, Jiali Zhang, Haiping Liu, Qinsheng Jiang, Sina Dang

Journal of System Simulation

Abstract: In view of the low simulation accuracy of existing finite element models for thermal characteristics of spindles caused by ignoring the influences of geometric characteristics of convective surfaces and fluid flow patterns and often adopting constant temperature loading in the setting of convective heat transfer boundary conditions, this paper proposed an optimization method for convective heat transfer parameters of spindles based on finite element thermal analysis. Combined with the geometric shapes and spatial positions of various convective surfaces of the spindle system, the calculation criterion of the convective heat transfer coefficient was determined through dimensional analysis according to the …

Simulation And Optimization Of Task Offloading In Mine Edge Computing For Low-Concurrency Devices, Zhaolu Guo, Qianhui Liu

Journal of System Simulation

Abstract: With the advancement of mine intelligence, task offloading technology has become a core technology of mine edge computing (MEC). For edge computing systems deployed with mine low-concurrency devices (MLCD), a discrete-event simulation model for MEC task offloading oriented to MLCD was constructed to solve the collaborative optimization problem of task processing latency and load balancing of mine edge servers (MES). By dynamically simulating the queuing, transmission, and computation processes of tasks, the objective of minimizing task processing latency was achieved. An improved evolutionary algorithm, ISBT-EA, was proposed, which integrated a task-characteristic-driven initialization strategy and local search operators, enhancing the …

Prediction Of Industrial Concentration Parameters Based On Caudformer Model, Kaipeng Xu, Yan Wang, Xin Zhang, Yang Liu, Zhenzhong Wang, Xiang Liu, Zhicheng Ji

Journal of System Simulation

Abstract: To solve the problems in the industrial concentration process of traditional Chinese medicine that traditional prediction methods are difficult to deal with complex characteristics such as nonlinearity, high-dimensional coupling, and highly skewed distribution and that existing deep learning models insufficiently consider causal relationships among variables, ignore frequency-domain periodic characteristics, and lack long-range dependency modeling capabilities, an improved multivariate time series prediction model CauDformer was proposed in this paper. Based on the iTransformer architecture, a causal multi-head self-attention mechanism (C-MHSA) was introduced to compulsorily constrain the dependency direction among variables by utilizing a lower triangular causal mask, guiding the model …

Veribrief: A Multi-Agent Retrieval-Augmented Generation System For Policy Decision Support, Imane Bahji

Electrical and Computer Engineering ETDs

VeriBrief is a multi-agent retrieval-augmented generation (RAG) system for evidence-grounded economic policy analysis. The system orchestrates a five-stage LangGraph pipeline, retrieval, research, analysis, synthesis, and critique, to produce cited, structured responses while detecting out-of-scope queries. An empirical evaluation on eight questions drawn from official U.S. macroeconomic releases compared VeriBrief against a single-pass RAG baseline. The multi-agent system achieved 100% refusal precision on unanswerable analytical queries versus 0% for the baseline. Unsupported claims fell substantially on answerable factual questions. A context-propagation defect discovered during evaluation was diagnosed and corrected. Limitations include failure of the evidence gate on policy-counterfactual queries and a …

Neural Network Technologies In The Automatical Control Systems Of Absorption Process For Pureficating Natural Gas, Abdishukurov Maqsudovich Shavkat Mr, Xuecheng Li Li Xuecheng Mr

Technical science and innovation

Analysis of methods and algorithms for synthesizing adaptive control systems for technological processes based on the neural network approach is carried out in this search. The stages of mathematical modeling of complex technological processes using neural network technology were considered. Additionally, an algorithm for solving the interpolation and extrapolation problem that arises in the training process a neural network to control system was proposed. At the final stage of this article, algorithms based on neural network technology are synthesized for the control system for the parameters of the technological process of natural gas purification by absorption

Hsv-1 Us3 Hijacks Conserved Actin Regulatory Complexes To Drive F-Actin Remodeling, Md Imran Hossain, Md Arifuzzaman, Md Mehedi Hasan, Seung Jong Park, Leila Rahimian, Ojasvi Dutta, Vladimir Chouljenko, Harikrishnan Mohan, Reza Ghavimi, Konstantin G. Kousoulas

Computer Science Faculty Research & Creative Works

The herpes simplex virus 1 (HSV-1) US3 is a multifunctional serine/threonine kinase that promotes HSV-1 replication and spread. But its role and the mechanisms by which US3 regulates actin cytoskeletal remodeling remain poorly defined. We combined flow cytometry, confocal microscopy, immunoprecipitation-mass spectrometry (IP-MS), protein complex mapping, and machine learning to characterize US3-mediated F-actin dynamics. Flow cytometry and confocal microscopy showed that wild-type HSV-1 induces significant F-actin remodeling, while the ΔUS3 mutant displays F-actin levels comparable to uninfected cells, identifying US3 as a key regulator. IP-MS identified 47 high-confidence US3 interactors enriched in conserved actin regulatory complexes, including Arp2/3 nucleation machinery, …

Design And Evaluation Of A Distributed Ticket Booking System Using Cqrs And Hybrid Consistency Models, Tai Nguyen Vo, Sangwhan Cha

Harrisburg University Other Works

This paper presents the design and evaluation of a Distributed Ticket Booking System (DTBS) built to handle extreme concurrency in high-traffic digital environments. Motivated by real-world failures such as the 2022 Taylor Swift Eras Tour sale—where 14 million simultaneous requests overwhelmed Ticketmaster—the system addresses the fundamental conflict between strong consistency and high availability under massive demand. The proposed solution adopts the Command Query Responsibility Segregation (CQRS) pattern to decouple read and write operations, and applies a hybrid consistency model grounded in the CAP theorem: a CP-oriented booking subsystem with Redis-based distributed locking, and an AP-oriented search subsystem using Elasticsearch for …

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …