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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Non-cooperative Model Predictive Control for Capturing a Remotely Piloted Target Drone 6th

Non-cooperative Model Predictive Control for Capturing a Rem...

引用

6th Iberian Robotics Conference (Robot)

作者： Rodrigues, Patricia Guerreiro, Bruno NOVA Univ Lisbon NOVA Sch Sci & Technol UNINOVA CTS LASI Caparica Portugal Univ Lisbon Inst Syst & Robot ISR Inst Super Tecn LARSYS Lisbon Portugal

ISBN: (纸本)9783031591662;9783031591679

This paper addresses the use of model predictive control (MPC) for pursuit-evasion games, where a shuttle drone aims at capturing a remotely piloted target drone. Several models for shuttle and target vehicles are developed, considering different degrees of complexity and reliance in inner-loop controllers. Based on these models MPC strategies are defined for each vehicle, for joint tracking operation, as well as for differential pursuit-evasion games between shuttle and target vehicles. Lastly the human-in-the-loop is added to the model and respective MPC algorithms of the fixed-wing target. Simulation results are provided, showing several scenarios where each vehicle has the advantage in terms of physical capabilities, or the disadvantage of being remotely-piloted.

关键词： Model Predictive Control Differential games Pursuit-Evasion Games Unmanned Aerial Vehicles Human-in-the-loop

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Enhanced Mental State Classification Using EEG-Based Brain-Computer Interface Through Deep Learning

Enhanced Mental State Classification Using EEG-Based Brain-C...

引用

Intelligent systems Conference

作者： Manoharan, Goutham Faria, Diego Resende Univ Hertfordshire Sch Phys Engn & Comp Sci Hatfield Herts England

ISBN: (纸本)9783031664304;9783031664311

This study is divided into two main components. Firstly, it involves the design and training of multiple Convolutional Neural networks (CNN) for the classification of brainwaves, predicting the mental state of an individual. Secondly, it encompasses the development of a Brain-Computer Interface (BCI) designed to record brainwaves, offering a user-friendly means to predict mental states using the recorded data and the trained neural network. The study utilizes a publicly available electroencephalographic (EEG) dataset collected with the Muse EEG headband. Various preprocessing techniques such as wavelet transform (WT), feature extraction, and feature selection are explored. The chosen temporal and statistical features are transformed into 2D grayscale images to facilitate the training of CNN models, classifying mental states into three categories: concentrated, neutral, and relaxed. The achieved highest accuracy is 91.72%, demonstrating competitiveness and improvement compared to previous works using the same dataset. The selected CNN model performs a fusion of the selected features and is integrated into the BCI, enabling users to predict mental states using EEG data. This BCI also holds the potential for enhancing model accuracy through continuous testing and incorporation of valuable data into the training dataset.

关键词： Deep learning Mental state classification Convolutional neural networks Wavelet transform Data fusion Brain-computer interfaces

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Modeling Blockchain System for Fashion Industry 11th

Modeling Blockchain System for Fashion Industry

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Labus, Aleksandra Barac, Dusan Lukovac, Petar Despotovic, Vukasin Simic, Milica Univ Belgrade Fac Org Sci Jove Ilica 154 Belgrade Serbia

ISBN: (纸本)9783031456473;9783031456480

The digitalization process affected the process of conducting supply chain management in the fashion industry. Innovative information technologies enabled improved communication between supply chain stakeholders, a more efficient and transparent way of conducting business transactions and protecting intellectual property rights. Blockchain technology has the potential to improve security and trust within fashion industry supply chains, reduce the placing of counterfeit products on the market, and provide customers insight into product authenticity. This paper focuses on the possibilities of using blockchain technologies in the supply chain of the fashion industry. The main goal of the paper is to propose a model of a blockchain system for the fashion industry. The proposed system should provide insight into the supply chain flow in the fashion industry based on using blockchain technology. Furthermore, the proposed model enables tracking all business transactions among stakeholders in the fashion industry in a transparent and immutable way, and for the customers enables insight into the product origin, authenticity and all relevant product data.

关键词： Blockchain Supply chain Fashion industry

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Health States Estimation and Prediction of Failure Occurrence Time of Rolling Element Bearing Using Hidden Markov Model 20th

Health States Estimation and Prediction of Failure Occurrenc...

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20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Gupta, Suraj Vasu, Katravath Maiti, Jhareswar Kumar, Akhilesh Indian Inst Technol Kharagpur Dept Ind & Syst Engn Kharagpur W Bengal India

ISBN: (纸本)9783031665936;9783031665943

The fourth industrial revolution and internet of things applications have led to significant advancements in sensor technology and cloud services. Modern systems can easily gather, transport, and store large amounts of data using the advanced powerful processing capabilities and cutting-edge GPU. Such massive data may be exploited extravagantly for a variety of purposes, including the development of intelligent maintenance strategies. To ensure the safe and reliable operations of any industrial assets, prognostics and health management plays a significant role. Among all the aspects in prognostics and health management (PHM) used for efficient deployment of predictive maintenance, machine health states estimation and remaining useful life prediction are the most pivotal tasks. This study thus proposes a novel technique based on hidden markov model (HMM) for the health states estimations and prediction of the failure occurrence time of a roller element bearing. Given the success of HMMs with its wide variety of applications in speech recognition, language processing, and image processing. This study proposes to use it in the domain of machine prognostics as well. The three prime benefits of HMM are (i) the number of clusters is not required to be pre-determined, (ii) HMM works best with sequential data (iii) it can extract hidden states of the system that are not directly observable in the concerned problem. Finally, the efficacy of the proposed model has been tested on the IEEE-PHM-2012 challenge data sets. The results obtained are much better when compared with the existing literatures.

关键词： Health States Estimation Predictive Maintenance Hidden Markov Model Remaining Useful Life

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Maximum Power Point Tracking and Field-Oriented Control Strategies Applied to PMSG-Based WECS 4th

Maximum Power Point Tracking and Field-Oriented Control Stra...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Dani, Abdelfattah Mekrini, Zineb El Mrabet, Mhamed Boulaala, Mohammed Abdelmalek Essaadi Univ FSTT Ind Syst Engn & Energy Convers Team Tetouan Morocco

ISBN: (纸本)9783031686498;9783031686504

In recent days, progress has been made in the development of power electronics and control strategies applied to permanent magnet synchronous generators (PMSG), enabling their large-scale use in wind energy conversion systems. This generator offers many benefits, such as low weight and high efficiency relative to cost. In addition, the low noise in direct drive wind turbine based on PMSG technology, thanks to absence of a gearbox. This study aims to present mathematical modeling and control strategies of the variable speed wind turbine based on a PMSG. Applying the field-oriented control strategy to the machine side converter leads to extracting the maximum of the available wind power via the maximum power point tracking (MPPT) approach. First, the MPPT technique without speed control is used to generate the optimum electromagnetic torque. This torque was then utilized to determine the reference stator quadrature current. The entire system was simulated using MATLAB/Simulink software environment. The simulation results reveal a good tracking performance.

关键词： Variable Speed Wind Turbine Wind Energy Conversion System Permanent Magnet synchronous Generator Field Oriented Control Maximum Power Point Tracking Machine Side Converter

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Industry 4.0 to Society 5.0: Change in Production and Management systems 10th

Industry 4.0 to Society 5.0: Change in Production and Manage...

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Bakator, Mihalj Cockalo, Dragan Stanisavljev, Sanja Ugrinov, Stefan Univ Novi Sad Tech Fac Mihajlo Pupin Zrenjanin Zrenjanin 23000 Serbia

ISBN: (纸本)9783031662676;9783031662683

This paper presents a comprehensive examination of the transition from Industry 4.0 to Society 5.0. It emphasizes the important role of AI, IoT, and Big Data in redefining production and management systems, fostering a shift towards more personalized, efficient, and sustainable practices. The integration of these advanced technologies while maintaining a human-centric approach is significant for ensuring that technological advancements work in harmony with human creativity and ethical considerations. The study also delves into the aspects of sustainable production, advocating for environmentally friendly practices and the development of collaborative ecosystems. The main goal of the paper is to analyze the importance acheiving competitiveness in the context of Industry 5.0, through AI application. The paper provides a solid basis for future reserach in this domain.

关键词： competitiveness Society 5.0 production and management systems

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Automated Verification of the Correctness of Transitions Between Elements of a Mobile Application Using Source Code Generation Tools 1

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4th Congress on Intelligent systems (CIS)

作者： Naumova, Nadezhda Barsukov, Ilya Mashina, Ekaterina Bostrikova, Darya ITMO Univ St Petersburg 197101 Russia

ISBN: (数字)9789819990436

ISBN: (纸本)9789819990429;9789819990436

The article is devoted to the issues of automation of software creation processes and the issue of creating universal testing tools for mobile device applications. The paper discusses in detail the process of creating a tool for automated testing that allows you to test applications created for Android and iOS and also provides the results of the research conducted to determine the completeness of the test coverage and reduce the time spent on testing procedures for mobile applications that arise when using the developed tool for all qualifying categories of specialists involved in testing applications. The novelty of the proposed method consists of automatic code generation of test scenarios based on the analysis of transitions between application pages, which provides the greatest coverage of transitions and methods associated with them. The modular method of constructing the solution proposed by the authors will allow the future to simply expand the functionality of the solution by adding new algorithms and testing modes, significantly increasing the "coverage area" of automated test scenarios.

关键词： Test automation User interface testing Code generation Mobile testing PageObject pattern Software testing Quality assurance Quality management Functional testing Time to market Delivery management

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WebXR-Driven Hand Gesture Data Capture: Designing a Web-Based Virtual Reality Application for Hand Tracking Data Recording 13th

WebXR-Driven Hand Gesture Data Capture: Designing a Web-Base...

引用

13th Computer Science Online Conference

作者： Tomes, Jakub Kohout, Jan Mares, Jan Univ Chem & Technol Dept Math Informat & Cybernet Tech 1905-5 Prague 6 Czech Republic

ISBN: (纸本)9783031702846;9783031702853

This paper focuses on the development of a web based Virtual Reality (VR) application, using WebXR and ***, to provide a portable and easy-to-use solution for recording of hand tracking data using the Oculus/Meta Quest platform. Modern technologies, like Vite, Github, Github Actions and Github Pages, were utilized for fast iteration and simplified development process.

关键词： Virtual Reality WebXR three.js Web Application Hand Tracking Hand Gestures Recorder Meta Quest Oculus Quest

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Impact of the Use of Social Media Among University Students Using Machine Learning 5th

Impact of the Use of Social Media Among University Students ...

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5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Al Mamun, Abdullah Akhy, Shabnur Anonna Mustofa, Sumaya Mia, Md Badol Sarkar, Partha Dip Chakraborty, Narayan Ranjan Khan, Md Abbas Ali Daffodil Int Univ Dhaka Bangladesh

ISBN: (纸本)9789819720811;9789819720828

This study explores innovative machine learning approaches to investigate how social media affects student behavior. In this study, we have collected a good number of dataset from different students of our university and cleaned, encoded as well as used feature engineering on our raw dataset through different scikit-learn classes for better training outcomes. We have trained our dataset using different types of classifiers like Gradient Boosting, Random Forest, Multi-Layer Perceptron, AdaBoost and Decision Trees Classifiers. We have used k-fold cross-validation for proper evaluation and obtained a high accuracy of 93% for the Gradient Boosting Classifier by analyzing the performance using confusion matrix, representing Area Under the ROC Curve (AUC) and Receiver Operating Characteristic curve (ROC). This study will play a vital role in controlling the upcoming youngster in using their social media.

关键词： Gradient boosting K-fold cross-validation Social media impact

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Pre-trained Deep Learning Models for Chest X-Rays' Classification: Views and Age-Groups 1

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Intelligent systems Conference (IntelliSys)

作者： Farhat, Hanan Jabbour, Joey Sakr, Georges E. Kilany, Rima Univ St Joseph Beirut Beirut Lebanon Lebanese Int Univ Beirut Lebanon Virgilsyst Inc Toronto ON Canada

ISBN: (数字)9783031477249

ISBN: (纸本)9783031477232;9783031477249

It is important for a generic diagnostic deep learning model in chest radiology to be independent of manual inputs such as patients' age-group and the view of Chest X-rays. Moreover, an accurate radiological diagnosis should take into consideration the patient age-group, as well as the Chest X-ray view. In this paper, we aim to find the optimal classification deep learning model to classify Chest X-rays by age-group and by view. We trained seven pre-trained deep learning models on customized Chest X-ray datasets, and we found that deep learning models based on residual blocks are the optimal models for the required classification. MobileNetV2 and ResNet50 were the best two models for classifying Chest X-rays into Adults or Pediatrics classes, and into AnteriorPosterior (AP) or Posterior-Anterior (PA) views. On the other hand, Xception was the least favored deep learning model for the two tasks. The drawn conclusions can help add an optimal preliminary classification head to a pulmonary diseases detection model, in order to optimize its performance.

关键词： Pre-trained models Chest X-Rays Deep learning

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