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arXiv 2023年

作者： Trummel, Tabea Liu, Zonglin Stursberg, Olaf Control and System Theory Dept. of Electrical Engineering and Computer Science University of Kassel Germany

This paper proposes a novel method to achieve and preserve synchronization for a set of connected heterogeneous Van der Pol oscillators. Unlike the state-of-the-art synchronization methods, in which a large coupling gain is applied to couple any pair of connected oscillators, the proposed method first casts the whole synchronization process into two phases. The first one considers the period from the beginning to the first instant of synchronization, while the second phase covers the following time in which synchronization must be preserved. It is shown that a large coupling gain is adopted for the first phase, while the averaged coupling gain to preserve the synchronization in the second phase can be reduced significantly by using an offline optimized coupling law. Efficiency and performance of this method are confirmed by a set of numerical tests with different graphs and system dynamics. © 2023, CC BY-NC-ND.

关键词： Synchronization

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Benchmarking Different Strategies for Offloading ROS2 Computation to the Edge

Benchmarking Different Strategies for Offloading ROS2 Comput...

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IEEE Conference on Network Softwarization (NetSoft)

作者： Daniele Cacciabue Jacopo Marino Francesco Aglieco Marco Levorato Domenico Perroni Fulvio Risso Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy Dept. of Computer Science University of California Irvine CA USA Links Foundation Torino Italy Italdesign Torino Italy

ISBN: (数字)9798350369588

ISBN: (纸本)9798350369595

Mobile robots suffer from inherent limitations due to the tradeoff in the amount of energy consumed by their on-board processing components, and the need to increase their operational time. On the communication side, the volatility of communication links severely hinders the ability of a mobile device to rely on computation offloading. The challenge addressed by this paper is the development of a methodology and framework to effectively migrate the location of a service from a system to another, minimizing downtime and striving to reduce any side-effects that may be perceived by the system. Solving this challenge will pave the way for more effective computation offloading solutions that can cope with the unpredictability of the edge systems. Four different approaches are compared, analyzing their performance via an empirical approach. The insights gathered from data allow the identification of the most promising solution to address the aforementioned challenge.

关键词： Switches computer architecture Benchmark testing Mobile handsets Mobile robots Business continuity

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Effectiveness of computer-based e-Learning and Virtual Reality Training System for the Preparatory Phase of a Training on Maintenance Procedure

Effectiveness of Computer-based e-Learning and Virtual Reali...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Filippo Gabriele Pratticò Debora Di Cosmo Matteo Piviotti Giuseppe La Rosa Fabrizio Lamberti Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy Leonardo S.p.a Turin Italy

This work investigates the effectiveness of two training systems based on consumer hardware technologies, a first one using computer-Based Learning (CBL) and the other exploiting Virtual Reality (VR). A user study was executed in order to compare the two training and analyze the most suitable approach for the learning of preparatory material in the context of an industrial assembly and maintenance (IMA) procedure. The results highlighted that, although trainees using VR experienced higher levels of cognitive processing and attention, the knowledge gain of CBL was comparable to that of VR for the preliminary phase training. Nonetheless, VR was still able to provide better learning gains in terms of procedural skills compared to CBL.

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Properties of singular solutions in optimal control problems under input dynamic extension

Properties of singular solutions in optimal control problems...

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IEEE Conference on Decision and control

作者： Paolo Di Giamberardino Daniela Iacoviello Dept. of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome via Ariosto 25 Rome Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The paper addresses the problem of optimal control design in presence of singular solutions for single input dynamics. The dynamical extension for systems obtained adding an integrator on the input is addressed and analyzed. The possibility of computing the optimal control for dynamically extended systems from the solution of the initial ones is investigated, as well as the inverse procedure. These relationships are well evidenced for the singular solutions, showing the possibility of simplifying the optimal control computation. An example is introduced to better highlight the presented results.

关键词： Optimal control Cost function

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Adaptive control Using a Quaternion Wavelet Neural Network

Adaptive Control Using a Quaternion Wavelet Neural Network

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International Workshop on Robot Motion and control (RoMoCo)

作者： Gerardo Martínez-Terán Eduardo Bayro-Corrochano Dept. Electrical Engineering and Computer Science CINVESTAV Guadalajara Mexico Institute of Automatic Control and Robotics Poznan University of Technology

ISBN: (数字)9798350393965

ISBN: (纸本)9798350393972

Robotics and haptic systems have allowed new and diverse applications in the field of medicine, such as assisted surgery and teleoperation which have increasingly stringent requirements for accuracy, convergence, and low computational consumption. In this paper an adaptive PID control law (Proportional Integral Derivative controller, PID), of indirect architecture is presented for movement paths in a haptic system of open chain, where the identification of the plant is through a quaternionic wavelet neural network (Quaternion Wavelet Neural Network, QWNN) for tune the PID values, this allows the optimal movement into the regions of the workspace.

关键词： Uncertainty Quaternions Neural networks Surgery Robustness Haptic interfaces Topology

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Newton-Euler Modeling of Robot Dynamics Using Geometric Algebra

Newton-Euler Modeling of Robot Dynamics Using Geometric Alge...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Eduardo Bayro-Corrochano Daniel Alvarado-Mejia Institute of Automatic Control and Robotics Poznan University of Technology Dept. Electrical Engineering and Computer Science CINVESTAV Guadalajara Mexico

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

In this work, we present the modeling of the dynamics of a robot manipulator using the Newton-Euler algorithm in the conformal algebra framework. The modeling of the dynamics of robot manipulators is currently done using the Euler-Lagrange formulation which is a batch type of computation. In contrast, in this paper, we propose a recursive algorithm for the modeling of the dynamics of robot manipulators using the Newton-Euler algorithm in the conformal geometric algebra framework.

关键词： Algebra Heuristic algorithms Computational modeling Optimal control Motors Real-time systems Mathematical models

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Optical Data Center Implementation within Data Center Networks Context Based on Mininet 2

Optical Data Center Implementation within Data Center Networ...

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2nd International engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Abdulmahdi, Esraa Ali Ali, Adnan Hussein Ibrahim, Raed Khalid Al-Askery, Ali Alhamdane, Hayder Jasim Mahmood, Amal Ibrahim Electrical Engineering College Middle Technical University Student at Dept. of Computer Engineering Techniques Baghdad Iraq Institute of Technology Middle Technical University Electrical Techniques Department Baghdad Iraq Al-Farahidi University Department of Medical Instruments Engineering Techniques Baghdad Iraq Electrical Engineering College Middle Technical University Department of Control and Automation Technical Engineering Baghdad Iraq College of Applied Arts Middle Technical University Baghdad Iraq Electrical Engineering College Middle Technical University Dept. of Computer Engineering Techniques Baghdad Iraq

ISBN: (纸本)9798350373363

The technology of reconfigurable optical networks (RONs) is growing to be a promising solution to effectively cater to the rapidly increasing traffic generated by the digital society. Optical technology emerges as a viable alternative because to its capacity to offer a substantial bandwidth, little latency, and enhanced overall performance. Nevertheless, it is imperative to effectively manage the physical resources comprising a data center. This study provides an experimental demonstration of the RONs, which is enhanced by a control plane. The implementation relies on the monitoring of real-time network statistics. This enables the execution of various activities, including as network slice provisioning and reconfiguration, assignment of packet priority classes, and dynamic operations. These actions are performed to ensure the attainment of the desired Quality of Service level. The experimental results show the successfully implementation of RONs using Mininet Emulator and sFlow traffic monitoring technology. The results approve that optical datacenter has minimum delay with low OSNR even with long distance and fast switching time. © 2023 IEEE.

关键词： Optical switches

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Deep Image Inpainting to Support Endoscopic Procedures

Deep Image Inpainting to Support Endoscopic Procedures

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Mediterranean Conference on control and Automation (MED)

作者： Danilo Menegatti Filippo Betello Francesco Delli Priscoli Alessandro Giuseppi Dept. of Computer Control and Management Engineering (DIAG) University of Rome “La Sapienza” Rome Italy

Deep image inpainting is a computer vision task that uses Deep Neural Networks to generate plausible content to complete an image, for example for the restoration of a damaged image or the removal of unwanted elements captured in the picture. This paper uses deep image inpainting to restore endoscopic images that are affected by various types of artifacts. To this end, we developed a transfer learning-based procedure that uses the CSA inpainting model, which was originally proposed for unrelated tasks including the restoration of images from the Paris StreetView Dataset. The proposed system is trained and validated on the EndoCV2020 dataset, consisting of images from real endoscopies, highlighting how deep image inpainting may be a promising technology for frame restoration during medical procedures.

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Vertically-Advised Federated Learning for Multi-Strategic Stock Predictions through Stochastic Attention-based LSTM

Vertically-Advised Federated Learning for Multi-Strategic St...

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Mediterranean Conference on control and Automation (MED)

作者： Danilo Menegatti Emanuele Ciccarelli Michele Viscione Alessandro Giuseppi Dept. of Computer Control and Management Engineering (DIAG) University of Rome ”La Sapienza” Rome Italy

In recent years, stock price forecasting has become a challenging task commonly used to evaluate the performance of various machine learning solutions. This work explores a Federated Learning (FL) framework within a competitive collaboration scenario with the aim of training a centralised model advised by non-recoverable decentralised strategies so that no exchange of private data is required. The proposed Vertically-Advised Federated Learning (VAFL) framework combines elements from both horizontal and vertical FL, as each client trains two independent models. Furthermore, a novel forecasting architecture, based on a stochastic variant of an Attention-based Long Short Term Memory (LSTM) network, is proposed and validated on a simulated scenario based on real data from the stock market.

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A Feature Fusion based Custom Deep Learning Model for Vehicle Make and Model Recognition

A Feature Fusion based Custom Deep Learning Model for Vehicl...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Triyas Ghosh Soumyajit Gayen Sourajit Maity Daria Valenkova Ram Sarkar Dept. of Computer Sc. and Engineering Jadavpur University Kolkata India Dept. of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (数字)9798350387568

ISBN: (纸本)9798350387575

Vehicle Make and Model Recognition (VMMR) is a pivotal task in various domains including surveillance, traffic management, and the automotive industry. Despite significant progress in deep learning approaches, existing VMMR systems still struggle to attain robust accuracy, particularly across diverse environments and viewing angles. In this paper, we propose a novel approach based on the fusion of two feature maps extracted from DenseNet201 and ResNet50V2 baseline models, respectively. Additionally, we employ a modified Convolutional Block Attention Module (CBAM) to enhance the resilience and precision of VMMR systems. By incorporating attention mechanisms in the feature extraction process, our modified CBAM model effectively captures both spatial and channel-wise dependencies, facilitating more potent discriminative feature representations. We assess our proposed approach through extensive experiments on two benchmark datasets namely Stanford Cars and CompCarsSV. Achieved accuracies are 93.51% and 99.03%, on Stanford Cars and CompCarsSV, respectively that are better than past methods. The code of our proposed model can be found at: https://***/JUVCSE/featurefusion.

关键词： Deep learning Industries Accuracy Surveillance Traffic control Feature extraction Robustness

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