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Aspects of autonomous drive control using NVIDIA Jetson Nano microcomputer 17

Aspects of autonomous drive control using NVIDIA Jetson Nano...

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17th conference on Computer Science and Intelligence Systems (FedCSIS)

作者： Podbucki, Kacper Marciniak, Tomasz Poznan Univ Tech Ul Jana Pawla II 24 PL-60965 Poznan Poland

ISBN: (数字)9788396242396

ISBN: (纸本)9788396242396

The article describes the training process and experiments regarding autonomous movement by the autonomous car Waveshare JetRacer AI. The central unit responsible for controlling the vehicle's systems, i.e. the steering servo and the DC motors used for the drive, is the NVIDIA Jetson Nano embedded device. The application of the IMX219 camera module for data acquisition and training of a neural network models on microcomputer and their use for the implementation of autonomous driving are described.

关键词： Training Computational modeling Neural networks process control Microcomputers data models Trajectory

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18th International KES conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2024

18th International KES Conference on Agents and Multi-Agent ...

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18th International KES conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2024

ISBN: (纸本)9789819764686

The proceedings contain 34 papers. The special focus in this conference is on Agents and Multi-Agent Systems: Technologies and Applications. The topics include: Fair Path Generation for Formation control Combining Ant Colony and Particle Swarm Optimizations;preference Definition in a Multi-agent System Approach for User-Centric Internet of Things Smart Environments;AI-Driven Nitrogen Stress Management in Cereal Crops via Drone Technology;agent-Based Simulation for Withdrawal of Energy-Inefficient Housing;resource Limitations of Business process Simulations: Literature Study;data Augmentation for Business process Alignment: Proof of Concept and Experimental Design;smart Scheduling in Urban Traffic: A Multi-Agent System for Dynamic Vanpooling;analysis of the Impact on Area Prices Using Propensity Score Matching, Considering the Proportions of Photovoltaic and Thermal Power Generation Simultaneously;consideration of Building a Simulator to Evaluate Methods to Maximize the Effectiveness of Advertising to Households;Human-AI-Collaboration SECI Model: The Knowledge Management Model of the Experts’ Tacit Knowledges with Augmented LLM-Based AI;modeling Agent Awareness After Hierarchical Managerial Training;development of An Application for Extracting Needs Related to Actual Gas Use Using Text Mining;Impact of Intelligent Systems in the Home Office on Employee Satisfaction—Lessons Learned from the COVID-19 Pandemic;agile Methodologies in Software Development: A Study of Effective Management Strategies for Companies in the Digital Era;predictive analysis of Cyclical Sales data;EMG Signal Classification Using Machine Learning for Augmentative Assistance in Cerebral Palsy;wellnessWave—Platform for the Digitization of the Romanian Public Medical System;TRIAGE Predictive Model Based on Artificial Neural Networks and Deep Learning;platform for Automated Assessment of Obstetric Ultrasounds, Using Machine Learning;identification of Fonts in Unstructured Environments Through Deep Lea

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Research on Digital modeling Technology for Commercial Aerospace Launch data

Research on Digital Modeling Technology for Commercial Aeros...

引用

control, Electronics and Computer Technology (ICCECT), IEEE International conference on

作者： Yubo Tang Jia Wang Zheshuai Zhou Yating Pan Xiuluo Liu Han Zhang Institute of Tracking and Communication Technology Beijing China

ISBN: (数字)9798350380958

ISBN: (纸本)9798350380965

Aiming at overcoming the difficulties of actual test and demonstration in commercial space launch missions and the lack of visualized analysis tools, this paper studies the digital modeling technology for commercial space launch, and proposes solutions to problems such as multi-module parallel assembly testing with short intervals, spatiotemporal coordination for comprehensive process and technical interface matching etc. Models for the analysis and calculation of explosion range, noise impact, and geological environment are created, which has achieved quick customization and flexible assembly of simulation and modeling for complex process, as well as a data evaluation model for digitalized collaboration under multiple problem domain situations, optimizing the process of space launch activities in commercial field.

关键词： Analytical models Space missions Computational modeling Space technology process control Aerospace electronics data models

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Design of intelligent control system of cold water for horizontal continuous casting of TP2 copper tube billet

Design of intelligent control system of cold water for horiz...

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2023 International conference on Computer, Artificial Intelligence, and control Engineering, CAICE 2023

作者： Yue, Fengli Wang, Shouquan Li, Qingwen School of Automotive and Transportation Shenyang Ligong University Shenyang110159 China Changzhou Runlai Technology Co. Ltd. Changzhou213100 China

ISBN: (纸本)9781510665040

The existing cold water control system for horizontal continuous casting of TP2 copper billet and the water cooling data under this control system are analyzed. In order to improve the existing water control system, through 3D modeling software, programming software and the analysis of the field situation of enterprises, the intelligent control system of cold water for horizontal continuous casting of TP2 copper pipe billet based on PLC is proposed. The visualization and online intelligent precise control of water flow process parameters are realized. Physical experiments on the open loop control strategy and closed loop control strategy are carried out. The results show that the closed loop control meets the requirements better than the open loop control. © 2023 SPIE.

关键词： Closed loop control systems

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Contextual Mathematical modeling Using the Formation of a Capital Size control Algorithm in the Music Industry 7

Contextual Mathematical Modeling Using the Formation of a Ca...

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7th International conference on Future Networks and Distributed Systems, ICFNDS 2023

作者： Rodionov, Dmitriy Eshov, Mansur Smirnova, Irina Isroilov, Bokhodir Kryzhko, Darya Konnikov, Evgenii Peter The Great St.Petersburg Polytechnic University Polytechnicheskaya 29 St.Petersburg195251 Russia Tashkent State University Of Economics Islam Karimov street 49 Tashkent100066 Uzbekistan

ISBN: (纸本)9798400709036

Today's volumes of information streams allow to mathematize a wide spectrum of processes and regularities, which qualitatively improves the possibilities of data analysis, prediction and planning. A mathematical model of an object of study, which has reached a satisfactory level of confidence in a particular situation, is a flexible tool in the hands of a knowledgeable analyst, providing, first and foremost, information about the relationships in the considered system. The understanding of situational relationships - within the framework of a limited model and system - is an effective means of control. Thus, a person possessing information can not only evaluate their expectations - making the most productive choices - but also transform influencing factors, exerting an appropriate influence on them, in order to achieve a targeted change in an specific index that requires adjustments. The algorithms for such modeling, descriptive analysis, and the process of forming conclusions are considered in this study on the example of the change in the volume of private capital in the music industry. The personal capital of popular musical artists is described in the context of its existence in the socio-economic environment of the music industry, which is mathematically estimated by the genre, quantitative composition of musical works, musical activity duration, number of streaming (estimated by a well-known entertainment-information edition that is relevant to the described environment), the number of Grammys awarded, and the number of nominations for this prestigious award, as well as the fact that the artist is included in the number of living or deceased. © 2023 ACM.

关键词： Music

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Efficiency analysis of Tandem Substring Search Methods 24

Efficiency Analysis of Tandem Substring Search Methods

引用

24th International Carpathian control conference, ICCC 2023

作者： Kovacs, Laszlo Polonkai, David University of Miskolc Department of Information Technology Miskolc Hungary

ISBN: (纸本)9798350310221

Strings and lists play a fundamental role in data structures. Considering string operations, one of the key functions is the search for matching parts within a given host string. The location of repeating substring pattern is a special type of general substring search. This task is of outstanding importance, among other in biology (examining genes problem) or in process modeling (searching for cycles). This article presents a specific alternative method for tandem substring search which unlike the traditional, direct pattern search methods presents, is based on the application of neural networks. The performed comparative analyzes carried out show that a neural network-based methods is a good alternative, especially in the case of approximate searches. © 2023 IEEE.

关键词： Pattern matching

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Analyzing Machining Cycle Time Anomalies via CNC and Operational data 20

Analyzing Machining Cycle Time Anomalies via CNC and Operati...

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20th CIRP conference on modeling of Machining Operations in Mons, CIRP CMMO 2025

作者： Vlaminck, Noémie Nicolas, Michel Benamara, Tariq Raddoux, Hervé Cenaero Rue des Frères Wright 29 Gosselies6041 Belgium Sonaca Route Nationale 5 Gosselies6041 Belgium

As manufacturers are transitioning to Industry 4.0, real-Time monitoring of manufacturing processes has become more prevalent. This paper presents an intuitive anomaly analysis tool designed to support data-driven decision-making for multiple Computer Numerical control (CNC) machines in a production environment. By leveraging internal Programmable Logic controller (PLC) signals enriched with tool information from G-code, and operational scheduling data, the proposed tool identifies anomalies in machining process durations without relying on theoretical cycle time estimates from G-code or CNC interpolation strategies. Instead, it computes actual program duration distributions after applying rigorous filtering to address operational disruptions such as server issues, maintenance, or shift changes. Results reveal a near-linear correlation between these computed statistics and theoretical machining durations predicted by a machining simulator, validating the pipeline's reliability. The developed decision-support application integrates cycle time statistics into comprehensive tables and visualizations, allowing users to analyse data at program, tooling, and G-code levels. This approach facilitates the detection of specific anomalies or bottlenecks in the process, including significant cycle time variance in tools or G-code sections, tool sequencing issues, recurrent anomalies in subprograms or G-code ranges linked with axes and table movements, unoptimized machining parameters or other causes. By focusing on robust data preparation, this work highlights the critical role of preprocessing in achieving actionable insights for production optimization. © 2025 The Author(s).

关键词： Machining centers

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Advanced Signal processing Techniques for Plasma-MAG Welding process 27

Advanced Signal Processing Techniques for Plasma-MAG Welding...

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27th IEEE Signal processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Tessema, Solomon Habtamu Bismor, Daruisz Wyzgolik, Roman Silesian University of Technology Department of Measurements and Control Systems Gliwice Poland

ISBN: (纸本)9788362065486

The Plasma-MAG (Metal Active Gas) welding process represents an advanced hybrid welding technique that combines the precision of plasma arc welding with the robust shielding capabilities of MAG welding. This integration is pivotal for applications requiring high-quality, defect-free welds. As the demand for superior welding performance and efficiency increases in various industrial sectors, the role of advanced signal processing techniques becomes ever more *** paper explores the application of sophisticated signal processing methods such as wavelet transforms, Fourier transforms, discrete wavelet transforms (DWT), and time-frequency analysis in the Plasma-MAG welding process. It specifically focuses on the role of the microphone within the monitoring and data acquisition setup depicted in the hybrid welding process, highlighting how these signal processing techniques are utilized to enhance monitoring and analysis capabilities during welding operations. By analyzing the welding signals, these methods facilitate the early detection of defects, ensure consistent weld quality, and optimize welding parameters for enhanced performance. The integration of advanced signal processing not only improves weld integrity but also contributes to process efficiency and reliability, addressing the stringent requirements of modern manufacturing and industrial applications. This study underscores the transformative impact of signal processing technologies on the Plasma-MAG welding process, highlighting their potential to advance welding practices and outcomes. © 2024 Division of Signal processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Discrete wavelet transforms

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Towards a Fault Management analysis Tool for Model Centric Systems 16

Towards a Fault Management Analysis Tool for Model Centric S...

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16th Annual conference of the Prognostics and Health Management Society, PHM 2024

作者： Kolcio, Ksenia Prather, Maurice Wagner, David Elaasar, Maged Shougarian, Narek Okean Solutions Inc SeattleWA98122 United States Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States

ISBN: (纸本)9781936263059

In an effort to effectively develop more complex spacecraft fault management (FM) systems new technologies are sought to enable rapid diagnostic model generation and validation, and provide tools to perform FM analyses Model-based Systems Engineering approaches to FM system development are uniquely suited to be combined with model-based tools currently utilized in the design of other parts of flight systems. Combined tools utilizing information from a common system model can reduce design inconsistencies and gaps in analyses. Tighter integration of FM with other system-level and subsystem-level hardware/software development activities allows crucial redundancy and sensor placement trades to be performed earlier and throughout the mission lifecycle. Our work has been towards the integration of a model-based fault management tool suite called MONSID®, with JPL’s Computer Aided Engineering for Systems ARchitecture (CAESAR) platform as a way to improve FM system modeling and analysis. MONSID relies on application-specific models of the system being monitored. MONSID models consist of interconnected elements representing system hardware and measurement/command input points, called the topology. Model topology design is currently a manual process and often relies heavily on paper documentation such as hardware/software specs, engineering drawings, and interface control documents. CAESAR is a semantically- driven toolchain for model-based system engineering. At the core is a system model expressed in the Ontological modeling Language (OML). It is intended to support semantic modeling, consistency validation, and continuous integration. A goal of the combined toolset is to automate FM model development by directly extracting models from CAESAR and then analyzing them in MONSID. Analyses currently available in MONSID include model topology inspection and validation and fault isolation capability based on sensor placement. While we have focused on two specific tools, the inte

关键词： Application programs

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Battery State of Health Estimation for Real-world Vehicles Based on Ensemble Learning 16

Battery State of Health Estimation for Real-world Vehicles B...

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16th IEEE PES Asia-Pacific Power and Energy Engineering conference, APPEEC 2024

作者： Wang, Haoyu He, Hongwen Wang, Pei Geng, Yiteng Guo, Xuncheng National Engineering Laboratory for Electric Vehicles Beijing China National Key Laboratory of Advanced Vehicle Integration and Control Beijing Institute of Technology Beijing China

ISBN: (纸本)9798350386127

Lithium-ion batteries (LIBs) are important energy storage components for new energy vehicles. Accurately estimating the State of Health (SOH) of LIBs ensures the safe and reliable operation of the power battery. Addressing the challenges of poor data quality, intricate sampling information, and incomplete battery cycles in real-world vehicle data, this paper proposes a pioneering SOH estimation method based on Light Gradient Boost Machine (LGBM) ensemble learning during charging process. A data preprocessing and operating condition reconstruction method is designed to streamline battery operating conditions and enhance overall data quality. The charging segments are extracted, and an aging features extraction method suitable for real-world vehicle data is proposed as well as high-value health indicators are selected using correlation analysis. The Bayesian optimization algorithm is employed to efficiently search for the optimal hyperparameters of the model, and comparisons and validations with other modeling algorithms and optimization methods and the estimation results on different vehicles are also carried out. The results show that LGBM method with Bayesian optimization algorithm achieves an overall superior estimation performance with the mean absolute percentage error limited within 2.71 % and exceptional computational efficiency. © 2024 IEEE.

关键词： State of charge

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