Computer Engineering Commons^™

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 …

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 …

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, …

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 …

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 …

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 …

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 …

Advancing Social Media Analytics And Personalized Generation Via Transfer Learning, Discourse-Aware Modeling, And Collaborative Modeling, Gibson Nkhata

Graduate Theses and Dissertations

Social media platforms have become central to information exchange, shaping public opinion across social, political, and economic domains. However, the massive volume of user-generated content, combined with its informal, nuanced, and often noisy nature, presents significant challenges for automated analysis and generation. Tasks such as stance detection, rumor verification, and personalized content generation are further complicated by sarcasm, evolving discourse structures, and diverse user preferences. Addressing these challenges requires models that can effectively leverage linguistic nuance, conversational dynamics, and collaborative user signals. Transfer learning has emerged as a powerful paradigm for improving performance in low-resource and complex language understanding tasks. …

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 …

Design And Modeling Of A Robotic Manipulator For Agricultural Explorations, Trent Thomas Powell

Graduate Theses and Dissertations

This thesis focuses on the modeling, design, and early testing of a spherical revolute revolute prismatic (RRP) robotic manipulator for probe based applications. The system is motivated by agricultural grain probing, where a probe is positioned over a truck bed and inserted into the grain to collect samples as trucks enter storage facilities, ports, hubs, or transfer points. A spherical RRP configuration is useful for this type of task because it provides a large accessible workspace while maintaining a relatively simple mechanical structure. A model based design approach is used to develop the system, beginning with forward and inverse kinematics …

Monitoring And Short-Term Forecasting Of Atmospheric Air Pollutants Using Deep Neural Networks, Prasanjit Dey

Dissertations

Accurate forecasting of near-surface atmospheric air pollutants such as PM2.5, NO2, SO2, CO, and O3 remains a critical scientific and societal challenge. This difficulty arises from several factors, including nonlinear pollutant dynamics, sparse ground monitoring net works, heterogeneous satellite observations, and strong cross-pollutant interdependencies. Substantial advances have been achieved in temporal deep learning, probabilistic modeling, satellite-based estimation, physics-informed methods, and foundation models. However, these paradigms have largely evolved in isolation. As a result, existing systems are often station-dependent or pollutant-specific and optimized for a single forecasting task. This limits their robustness and generalizability across regions and heterogeneous data regimes.

This …

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 …

Advancing Imbalanced Classification Through Representation Learning, Morteza Mohammady Gharasuie

Computer Science Theses & Dissertations

Real-world datasets frequently exhibit severe class imbalance, where certain categories are significantly underrepresented relative to others, leading standard empirical risk minimization to bias learning toward majority classes and degrade performance on minority categories. This dissertation addresses imbalanced classification across both structured tabular data and long-tailed visual recognition by developing methods that improve representation learning and decision reliability under skewed distributions. For tabular data, it introduces Conditional Probability Representation (CPR), a target-based encoding framework that embeds feature–label relationships directly into the representation space, enhanced by a progressive feature upgrading mechanism for semi-supervised settings and a class-frequency–aware extension that improves robustness to …

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

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 …

Compound Role Of Using Advanced Materials And Design Procedures On Improving The Performance Of Baghdad Buildings Facades, Abeer Qasim Jbur

Al-Esraa University College Journal for Engineering Sciences

The research idea addresses improving the thermal performance of buildings in Baghdad by selecting and employing facade materials to reduce heat gain and energy consumption associated with cooling in a hot-dry climate. The study discusses the pivotal role of facade materials in interacting with solar radiation, heat transfer, and inward thermal transmittance, as well as their capacity to store and release heat in ways that maintain thermal comfort within architectural spaces and reduce reliance on mechanical cooling systems. A range of traditional materials such as stone, earth, and concrete is presented alongside modern materials like high-performance glass and thermal storage …