Artificial Intelligence and Robotics Commons^™

Research On Network Public Opinion Propagation Model Of Major Epidemics Under Cross-Infection Of Double Emotions, Yaming Zhang, Yanyuan Su, Guiru Zhao, Xiaoyu Guo

Journal of System Simulation

Abstract: Major epidemics provoke a variety of netizens' emotions. To some degree, the interaction of netizens' intense emotions determine the development direction of public opinion. Considering the complexity and dual emotional contagion, the impact of emotional factors in network public opinion is quantified to three dimensions indicators, emotional enhancement, differences and conversion rates. SIPINR public opinion propagation model is constructed. The equilibrium points and the transmission threshold are estimated and the stability is proved. The law of network public opinion propagation during major epidemics is revealed through numerical simulation. The results show that the dual emotional contagion would lead to …

Automatic Target Recognition Of Substation 3d Scene For Digital Twin, Qian Tu, Jun Li, Dongliang Fan, Qi Kong, Jie Shen

Journal of System Simulation

Abstract: In order to improve the accuracy of automatic target recognition and promote the effect on substation operation and maintenance, automatic target recognition of substation 3D scene for digital twin is proposed. The automatic target recognition model for the three dimensional scene of the substation is constructed. The perception module of the model is used to collect the real-time status data of substation, and the communication module is used to transmit the data to digital twin modules. This module, based on the received data information, realizes the deep fusion and panoramic mapping of substation information through the knowledge base constructed …

Simulation On High-Speed Train Carriage Evacuation Considering Passengers Moving To Adjacent Carriages, Zuoan Hu, Tian Zeng, Yidong Wei, Yi Ma

Journal of System Simulation

Abstract: To study the influence of passengers moving to adjacent carriages on high-speed train carriages' evacuation, a cellular automata model considering export selection is established. Taking the CR400BF second-class carriage as the research object, some analytical indexes such as evacuation efficiency, number of conflicts and the congestion degree are used to study the effect of passengers moving to adjacent carriages on carriage evacuation, and the passenger seat distribution, the number of passengers transferred from adjacent carriages and the opening door modes of adjacent carriages are discussed. The simulation results show that the discretized seat distribution reduces the times of conflicts …

Application Of Improved Path Tracking Algorithm In Robot Slam, Qian Li, Ye Tao, Hui Li

Journal of System Simulation

Abstract: Mapping is an important part of automated logistics. At present, SLAM is widely used. However, in large-scale scenes, errors are accumulated because robots often repeatedly measure and scan the region edge, which makes it impossible to quickly build a high-precision and complete map. An autonomous mapping method based on auxiliary path tracking is proposed, in which the given initial sketch is grid denoised and the auxiliary path is fitted and improved by multi segment cubic polynomial. The improved pure pursuit algorithm is used to guide the robot to build the map and improve the total distance and time of …

Modeling And Simulation On Production Logistics Of Intelligent Workshop Manufacturing System Based On Efsm, Liuzhen Li, Chao Jin, Tingyu Lin, Yaoqin Zhu

Journal of System Simulation

Abstract: The production logistics mode of manufacturing industry is developing rapidly, on which the modeling and simulation can provide the decision support for the design, analysis and transformation of manufacturing system. A description of the entity elements in intelligent workshop manufacturing system is given according to the classification of "human machine material environment rule". A production and logistics componentized EFSM model is created on the basis of EFSM and componentized modeling ideas. The modeling process for multi-job production in smart shop and the component model instantiation methodology are elaborated. The simulation running through the automatic conversion of EFSM-DEVS model and …

Research On 3d Object Detection Method With Cross-Module Attention, Renjie Xu, Xiaoming Zhang, Chen Wang, Peng Wu

Journal of System Simulation

Abstract: To address the issue of feature loss that occurs during the extraction and transmission of target features in 3D object detection tasks using point cloud data, this study proposes an object detection method based on cross-module attention. This method incorporates a channel attention module and a spatial attention module to enhance the crucial feature information. Through feature transformation, the features from different stages of the attention module are connected to mitigate the loss of features during the extraction and transmission process. To tackle the problem of inadequate detection performance in target detection networks for objects of different scales, a …

A Critical Computing Curriculum Design Case: Exploring Tribal Sovereignty For Middle School Students, Kristin A. Searle, Aubrey Rogowski, Colby Tofel-Grehl, Mengying Jiang

Journal of Computer Science Integration

We report on our efforts to design an integrated computing curriculum for middle school students in Montana that is in line with the Kapor Center’s focus on culturally sustaining-revitalizing pedagogies. Montana provides a unique context for doing this work because a state constitutional mandate requires all K-12 students to learn about tribal histories and cultures through Indian Education For All (IEFA). IEFA centers around seven essential understandings about Indigenous peoples in Montana that are integrated across content areas. In addition, implementation of Montana’s CS standards began in the 2021–2022 school year. In the curricular design, we sought to bring together …

Employing An Abolitionist, Critical Race Pedagogy In Cs: Centering The Voices, Experiences And Technological Innovations Of Black Youth, Tiera Tanksley

Journal of Computer Science Integration

This paper proposes a pedagogical extension of culturally responsive praxis called abolitionist, critical race pedagogy in CS. To showcase the power and potentiality of this pedagogy, this paper examines the experiences of 2 cohorts of Black high school students (n = 30) who participated in a critical race technology course that was taught during the dual pandemic of COVID-19 and anti-Black racism. The goal of this summer course was to employ an abolitionist, critical race pedagogy in CS to foster Black students’ ability to critically examine the ubiquity of anti-Black racism within the socio-technical architectures (e.g. code, data, algorithms and …

Culturally Responsive-Sustaining Computational Thinking: Enactment In Elementary Classrooms, Victoria Macann, Aman Yadav

Journal of Computer Science Integration

Technology has increasingly permeated many aspects of everyday life and this evolution raises the need for individuals to understand how the digital world works and what opportunities and risks it brings (Nouri, Zhang, Mannila & Norén, 2019). For this to be an experience for everyone, we need to rethink how we integrate computational thinking (CT) and provide teachers with tools to center their students’ identities, experiences, and cultures in the classroom. In this paper, we present two case studies of primary (elementary) teachers from a full primary (student ages 5–13) semi-rural school in the North Island of New Zealand that …

The Transformative Integration Of Artificial Intelligence With Cmmc And Nist 800-171 For Advanced Risk Management And Compliance, Mia Lunati

Cybersecurity Undergraduate Research Showcase

This paper explores the transformative potential of integrating Artificial Intelligence (AI) with established cybersecurity frameworks such as the Cybersecurity Maturity Model Certification (CMMC) and the National Institute of Standards and Technology (NIST) Special Publication 800-171. The thesis argues that the relationship between AI and these frameworks has the capacity to transform risk management in cybersecurity, where it could serve as a critical element in threat mitigation. In addition to addressing AI’s capabilities, this paper acknowledges the risks and limitations of these systems, highlighting the need for extensive research and monitoring when relying on AI. One must understand boundaries when integrating …

Brain-Inspired Spatio-Temporal Learning With Application To Robotics, Thiago André Ferreira Medeiros

USF Tampa Graduate Theses and Dissertations

The human brain still has many mysteries and one of them is how it encodes information. The following study intends to unravel at least one such mechanism. For this it will be demonstrated how a set of specialized neurons may use spatial and temporal information to encode information. These neurons, called Place Cells, become active when the animal enters a place in the environment, allowing it to build a cognitive map of the environment. In a recent paper by Scleidorovich et al. in 2022, it was demonstrated that it was possible to differentiate between two sequences of activations of a …

Decoding Usage And Adoption Behavior Of The Low-Carbon Transportation Market: An Ai-Driven Exploration, Vuban Chowdhury

Graduate Theses and Dissertations

The transportation sector stands as a significant contributor to greenhouse gas emissions in the United States, with its environmental impact steadily escalating over the past few decades. This has prompted government agencies to facilitate the adoption and usage of low-carbon transportation (LCT) options as alternatives to fossil-fuel-powered transportation. LCTs include modes of transportation that minimize the overall carbon footprint of the transportation sector by relying on energy sources that are environmentally sustainable. These sustainable transportation options have also garnered significant interest in the transportation research community. For government agencies and researchers alike, a comprehensive understanding of the adoption and usage …

Integrating Ai Into Uavs, Huong Quach

Cybersecurity Undergraduate Research Showcase

This research project explores the application of Deep Learning (DL) techniques, specifically Convolutional Neural Networks (CNNs), to develop a smoke detection algorithm for deployment on mobile platforms, such as drones and self-driving vehicles. The project focuses on enhancing the decision-making capabilities of these platforms in emergency response situations. The methodology involves three phases: algorithm development, algorithm implementation, and testing and optimization. The developed CNN model, based on ResNet50 architecture, is trained on a dataset of fire, smoke, and neutral images obtained from the web. The algorithm is implemented on the Jetson Nano platform to provide responsive support for first responders. …

Implementation Of Adas And Autonomy On Unlv Campus, Zillur Rahman

UNLV Theses, Dissertations, Professional Papers, and Capstones

The integration of Advanced Driving Assistance Systems (ADAS) and autonomous driving functionalities into contemporary vehicles has notably surged, driven by the remarkable progress in artificial intelligence (AI). These AI systems, capable of learning from real-world data, now exhibit the capability to perceive their surroundings via a suite of sensors, create optimal routes from source to destination, and execute vehicle control akin to a human driver.

Within the context of this thesis, we undertake a comprehensive exploration of three distinct yet interrelated ADAS and Autonomy projects. Our central objective is the implementation of autonomous driving(AD) technology at UNLV campus, culminating in …

Marss: Multi-Agent Reinforcement Learning For Satellite Swarms, Nicholas J. Yielding

Theses and Dissertations

Multi-agent systems and swarms in spacecraft formation flying are of ever-increasing importance in a contested space environment—use of multiple spacecraft to contribute to a cooperative mission potentially increases positive outcomes on orbit, while autonomy becomes an ever more important requirement to reduce reaction time in dynamic situations and lower the burden on space operators. This research explores difficult swarm Guidance Navigation and Control (GNC) scenarios using Deep Reinforcement Learning (DRL). DRL polices are trained to provide guidance inputs to agents in multi-agent swarm environments for completing complex, teamwork focused objectives in geosynchronous orbit. An example scenario is explored for a …

A Poisson-Based Distribution Learning Framework For Short-Term Prediction Of Food Delivery Demand Ranges, Jian Liang, Jintao Ke, Hai Wang, Hongbo Ye, Jinjun Tang

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has caused a dramatic change in the demand composition of restaurants and, at the same time, catalyzed on-demand food delivery (OFD) services—such as DoorDash, Grubhub, and Uber Eats—to a large extent. With massive amounts of data on customers, drivers, and merchants, OFD platforms can achieve higher efficiency with better strategic and operational decisions; these include dynamic pricing, order bundling and dispatching, and driver relocation. Some of these decisions, and especially proactive decisions in real time, rely on accurate and reliable short-term predictions of demand ranges or distributions. In this paper, we develop a Poisson-based distribution prediction (PDP) …

Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad

Theses and Dissertations

Running computer vision algorithms requires complex devices with lots of computing power, these types of devices are not well suited for space deployment. The harsh radiation environment and limited power budgets have hindered the ability of running advanced computer vision algorithms in space. This problem makes running an on-orbit servicing detection algorithm very difficult. This work proposes using a low powered FPGA to accelerate the computer vision algorithms that enable satellite component feature extraction. This work uses AMD/Xilinx’s Zynq SoC and DPU IP to run model inference. Experiments in this work centered around improving model post processing by creating implementations …

Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon

All Dissertations

The development of composite materials for structural components necessitates methods for evaluating and characterizing their damage states after encountering loading conditions. Laminates fabricated from carbon fiber reinforced polymers (CFRPs) are lightweight alternatives to metallic plates; thus, their usage has increased in performance industries such as aerospace and automotive. Additive manufacturing (AM) has experienced a similar growth as composite material inclusion because of its advantages over traditional manufacturing methods. Fabrication with composite laminates and additive manufacturing, specifically fused filament fabrication (fused deposition modeling), requires material to be placed layer-by-layer. If adjacent plies/layers lose adhesion during fabrication or operational usage, the strength …

Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu

Journal of System Simulation

Abstract: The definition and content of the virtual-real simulation are presented. According to different technical ideas, the development status and existing problems of virtual-real simulation are summarized from three aspects of digital twin, live-virtual-constructive (LVC) simulation, and parallel system. The similarities and differences, as well as the advantages and disadvantages of the three methods are analyzed and compared, and their main application fields are discussed. In order to deal with difficulties encountered in military training, operational tests, equipment development, and equipment maintenance, a solution based on virtual-real simulation is proposed by means of theoretical guidance, case comparison, and transfer and …

Knowing Just Enough To Be Dangerous: The Sociological Effects Of Censoring Public Ai, David Hopkins

Cybersecurity Undergraduate Research Showcase

This paper will present the capabilities and security concerns of public AI, also called generative AI, and look at the societal and sociological effects of implementing regulations of this technology.

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang

Journal of System Simulation

Abstract: Mainstream image semantic segmentation networks currently face problems such as incorrec segmentation, discontinuous segmentation, and high model complexity, which cannot be flexibly and efficiently deployed in practical scenarios. To this end, an image semantic segmentation network that optimizes the DeepLabv3+ model is designed by comprehensively considering the network parameters, prediction time, and accuracy. The lightweight EfficientNetv2 is adopted to extract backbone network features and improve parameter utilization. In the atrous spatial pyramid pooling module, the mixed strip pooling is utilized to replace the global average pooling, and a depthwise separable dilated convolution is introduced to reduce parameters and improve …

Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning, Jing Ni, Mengke Ma

Journal of System Simulation

Abstract: In order to solve the intercell scheduling problem of dynamic arrival of machining tasks and realize adaptive scheduling in the complex and changeable environment of the intelligent factory, a scheduling method based on a deep Q network is proposed. A complex network with cells as nodes and workpiece intercell machining path as directed edges is constructed, and the degree value is introduced to define the state space with intercell scheduling characteristics. A compound scheduling rule composed of a workpiece layer, unit layer, and machine layer is designed, and hierarchical optimization makes the scheduling scheme more global. Since double deep …

Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao

Journal of System Simulation

Abstract: From the perspective of flight tests, how to evaluate the autonomous aerial refueling (AAR) capability and select key indicators for evaluation is a key problem to be solved for AAR trials. The standards requirements of aerial refueling and manned aircraft aerial refueling experience in China and abroad are analyzed. The total capability of AAR is studied, and key evaluation indicators in the AAR whole process including rendezvous, formation, docking, refueling, and disengagement are proposed. The evaluation method is demonstrated in both numerical simulation and hardware-in-loop test environments. Finally, the key indicators affecting the docking success of AAR are analyzed, …

Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning, Zhengxuan Jia, Tingyu Lin, Yingying Xiao, Guoqiang Shi, Hao Wang, Bi Zeng, Yiming Ou, Pengpeng Zhao

Journal of System Simulation

Abstract: Under the background of high-speed maneuvering target interception, an optimal guidance law generation method for head-on interception independent of target acceleration estimation is proposed based on deep reinforcement learning. In addition, its effectiveness is verified through simulation experiments. As the simulation results suggest, the proposed method successfully achieves head-on interception of high-speed maneuvering targets in 3D space and largely reduces the requirement for target estimation with strong uncertainty, and it is more applicable than the optimal control method.

Charging Facility Layouts Based On Charging Selection Behavior, Lixiao Wang, Zhonghui Wang

Journal of System Simulation

Abstract: A charging facility layout method based on charging selection behavior is proposed for the current uncoordinated development of electric vehicles and charging infrastructure and the low utilization of public charging facilities. The influence of the charging selection behavior of electric vehicle users' trips on the charging facility layout is considered, and a charging selection behavior model is built and applied to the charging demand prediction. Based on the study of charging selection behavior and charging demands, a charging facility layout model with the minimization of total travel time as the objective function is built, and the reciprocal feedback between …

Uav-Enabled Task Offloading Strategy For Vehicular Edge Computing Networks, Feng Hu, Haiyang Gu, Jun Lin

Journal of System Simulation

Abstract: As intelligent vehicles are equipped with more and more sensors, the explosive growth of sensor data is generated, which brings severe challenges to vehicular communication and computing. In addition, the modern road presents a three-dimensional structure, and the system architecture of traditional vehicular networks cannot guarantee full coverage and seamless computing. A task offloading strategy for UAV-assisted and 6G-enabled (Sixth Generation) vehicular edge computing networks is proposed. Furthermore, a flexible and intelligent vehicular edge computing mode is composed by vehicles and UAVs, which provide three-dimensional edge computing services for delay-sensitive and computation-intensive vehicular tasks, and ensure timely processing and …

Development Of Combat Concept Of Intelligent Land Assault System Based On Dodaf, Can Wang, Haoran Ji, Qisheng Guo, Zhiming Dong, Yaxin Tan, Ge Mu

Journal of System Simulation

Abstract: In view of military demand traction in the development of land assault equipment, a combat concept of land assault systems for future intelligent combat is developed. Basedon the definition of relevant concepts and research boundaries, the combat concept model framework and modeling steps are proposed based on DoDAF, and the combat effect, combat process, combat nodes, resource interaction, system composition, and capability characteristics are analyzed in combination with the model description. The combat concept verification is carried out from the aspects of system combat efficiency and communication load by simulation experiments. The results show that the intelligent assault system …

Research On Operational Effectiveness Evaluation Method Of Space-Based Information Support Equipment System, Xiaolan Yu, Wei Xiong, Chi Han, Zhenwei Wu

Journal of System Simulation

Abstract: The operational effectiveness evaluation of space-based information support equipment systems has become a research hotspot in the military field. How to effectively deal with the nonlinear and confrontational problems of the operational effectiveness of the space-based information support equipment system has become a crucial issue in the development of the space-based information support equipment system. In this paper, a method for evaluating the operational effectiveness of the space-based information support equipment system based on the system dynamics (SD) model is presented. The SD flow rate basic tree entry modeling method is used to establish the basic tree entry model …

Requirements Of Parallel Combat System Based On Gqfd-Coupling Coordination Degree, Zhiming Dong, Bingshan Si, Liang Li

Journal of System Simulation

Abstract: In view of future intelligent unmanned combat characteristics, the concept of parallel combat is proposed and the model of parallel combat system is built based on OODA ring theory. Meanwhile, this paper builds a demand analysis model based on GQFD-coupling coordination degree to solve the low reliability, lack of objectivity, and single description perspective of the traditional quality function deployment (QFD) method and coupling coordination degree analysis during demand analysis. Additionally, the importance ranking of ability requirements in the parallel combat system is obtained by the house of quality of ability requirement analysis in the combat system based on …