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检索条件"机构=Automatic Control and Informatics"

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FedAcc and FedAccSize: Aggregation Methods for Federated Learning Applications

FedAcc and FedAccSize: Aggregation Methods for Federated Lea...

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Mediterranean Conference on control and Automation (MED)

作者： Iuliana Bejenar Lavinia Ferariu Carlos Pascal Constantin F. Caruntu Department of Automatic Control and Applied Informatics “Gheorghe Asachi” Technical University of Iasi Iasi Romania

This paper presents the ability of the federated learning concept to create a collaboration between multiple devices using a shared global model, while still keeping data privacy to meet the General Data Protection Regulation (GDPR). In real-world application scenarios, this concept faces problems related to the defense of the global model from possible attacks and the compatibility with non-independent and identically distributed data (non-IID). This paper presents two aggregation algorithms compatible with non-IID data, which use a refined aggregation of the local model, based on their accuracy. Thus, the proposed algorithms can refine the confidence in each client, eliminate intruders and allow a safe aggregation of the global model. Testing scenarios performed for IID and non-IID data illustrate that the proposed algorithms are able to provide faster training and improved robustness against intruders, w.r.t. the well-known federated average algorithm.

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Real-time testing of vision-based systems for AGVs with ArUco markers

Real-time testing of vision-based systems for AGVs with ArUc...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Filus, Katarzyna Sobczak, Lukasz Domanska, Joanna Domanski, Adam Cupek, Rafal Institute of Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland

ISBN: (纸本)9781665480451

Automated Ground Vehicles (AGVs) use deep-learning-based vision systems to perceive the surrounding environment and extract relevant information about it. Although deep learning models offer high capabilities, they require large amounts of data to be properly trained and tested. Testing is especially important when off-the-shelf models are used by the AGVs - to examine whether they can meet the demands of complex environments such as the production halls of automated factories. One area of such perception algorithms is object recognition. To test such systems, we propose a solution based on ArUco fiducial markers used for automatic labeling of objects. Our solution can be used to test deep learning systems in real time directly on a robot. Our solution requires minimal interference with the environment and additional infrastructure - the desired objects only need to be marked with a marker printed on a home printer. Therefore, the presented testing procedure can be used for testing of AGVs in real-life environments during a real ride from an actual robot perspective. Data gathered during the online testing can be used for the offline comparison of the accuracy of different deep learning models. Although we focus on the online and offline testing in our study, we also incorporated a marker masking procedure. Therefore, the resulting datasets may also be used for training. © 2022 IEEE.

关键词： Object recognition

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Solving Multimodal Problems Using Genetic Algorithms - A Case Study in Electromagnetics 11

Solving Multimodal Problems Using Genetic Algorithms - A Cas...

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11th International Conference on Electromechanical and Energy Systems, SIELMEN 2021

作者： Ferariu, Lavinia Petrescu, Camelia Technical University of Iai Dept. of Automatic Control and Applied Informatics Iai Romania

ISBN: (纸本)9781665400787

In multimodal optimization, it is important to obtain all the optima in a single run, for an insightful description of the potential design configurations. Genetic algorithms, as population-based approaches, are very suitable for this purpose. In this paper, the genetic algorithm is designed to work on subpopulations, which use special mechanisms for the insertion of offspring and immigrants. Mainly, the subpopulations are designed to allow speciation, each species being potentially formed around a global optimum. To this end, the insertion mechanism uses a combination of fitness-based and similarity-based insertion techniques, which can help both for preserving the exploration in diverse areas and for improving the accuracy of the solutions. A highly nonlinear problem is considered as a case study - that of finding the propagation constants of a planar dielectric microwave guide. The experimental investigations carried out for different waveguide setups show that using migration with similitude-based insertion of migrants helps achieve accurate locations of all optima, with reasonable computational costs. © 2021 IEEE.

关键词： Genetic algorithms

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The concept of an expert system for partial discharge assessment in power transformers 6

The concept of an expert system for partial discharge assess...

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6th International Conference on Nanotechnology for Instrumentation and Measurement, NanofIM 2021

作者： Kunicki, Michal Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Opole Poland

ISBN: (纸本)9781665407007

This paper describes the idea of novel approach to creating an expert system for partial discharge (PD) assessment in power transformers. The proposed system is intended to support the decision-making process regarding technical condition assessment of power transformers. The primal objective of this study is to share the idea with the academia and industry in order to find potential partners interested in practical realization of such a solution. Moreover, this paper analyzes state of the art in the field of expert systems for PD, introduces experience and competences of the research team involved in this project, and presents the results of surveys among industrial entities representing the point of view and needs of the transformer market in this matter. Results show that in most cases, contemporary PD analysis systems do not meet all the needs of their end users, and proposed expert system is sought by the industry, and would be willingly used in their practice. © 2021 IEEE.

关键词： Partial discharges

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Data- And model-driven digital twins for design and logistics control of product distribution 23

Data- And model-driven digital twins for design and logistic...

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23rd International Conference on control Systems and Computer Science Technologies, CSCS 2021

作者： Stan, Mihai Borangiu, Theodor Raileanu, Silviu University Politehnica of Bucharest Dept. of Automatic Control and Industrial Informatics Bucharest Romania

ISBN: (纸本)9781665439398

Digital control of product-on-pallet distribution is organized on two layers in logistics systems: the low-level local process automation and the supervision and coordination dual logistic execution system. The paper's scientific contribution consists in a holonic control system for multiple robot palletizing cells for product-on-pallet distribution. In this holonic control approach, data-driven digital twins (DT) are created to optimize palletizing schedules, controlled with situation awareness and resource health monitoring. A model-driven DT configuration with embedded simulation faster than real-time is combined with the data-driven DT in a meta-level control scheme offering predictive situation awareness. The paper also presents a pure model-driven DT mock-up of a robot palletizing cell - simulation with software in the loop - in which the actual holonic control system including digital twins and decision making is used in the simulation as it will be deployed in reality. This configuration is used to design the robot palletizing cells, to experiment in limit conditions, to fine tune and validate the robot control solution. © 2021 IEEE.

关键词： Supply chains

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Analysis of selected dielectric parameters of insulating liquids

Analysis of selected dielectric parameters of insulating liq...

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International Scientific Conference on Electric Power Engineering (EPE)

作者： Aleksandra Płużek Łukasz Nagi Michał Kozioł Małgorzata Zygarlicka Department of Electrical Power and Renewable Energy Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength.

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Usability of Industrial HMI Testing Method

Usability of Industrial HMI Testing Method

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International Conference on Process control (PC)

作者： Jakub Jura Cyril Oswald dept. of Automatic Control and Engineering Informatics Czech Technical University in Prague Prague Czech republic

The article deals with methods of usability testing of industrial SCADA/HMI interfaces such as graphical operator panels or control room visualization screens. Analysis of the designed HMI screens and quantitative and qualitative testing methods are used. Usability is estimated by measuring the reaction times of the defined test tasks and by the Eye Tracking methods. The proposed method for testing and evaluating the industrial HMI is presented as a case study. The method allows for to improvement the quality of industrial HMI. Especially its usability, reliability, and efficiency.

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Mixed Reality Framework for Eye-in-Hand Collaborative Robot-Human Interaction

Mixed Reality Framework for Eye-in-Hand Collaborative Robot-...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Ionut Sopon Cristina Tincu Aura Ganciu Adrian Burlacu Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Iasi Romania

In recent years, the manufacturing sector has undergone a significant transition from a paradigm of robotic autonomy to human-robot collaboration. This approach allows operators from different domains to rapidly adapt to a new way of working and reduces redundant learning costs, while also enabling intuitive robot control. To further enhance this paradigm, integrating Mixed Reality (MR) technology has emerged as a promising approach to creating and working in a virtual workspace while having a safe environment for training. This work develops a framework, based on digital twin representation, to integrate the MR with real-life equipment and humans. This allows for the control of a collaborative robot in an environment with objects or humans perceived by the eye-in-hand visual sensor. The efficiency of the proposed framework is emphasized by a comparison of Unity simulations versus the real-time behavior of the collaborative robot.

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Legal Named Entity Recognition with Multi-Task Domain Adaptation 4

Legal Named Entity Recognition with Multi-Task Domain Adapta...

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4th Natural Legal Language Processing Workshop, NLLP 2022, co-located with the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Smădu, Răzvan-Alexandru Dinică, Ion-Robert Avram, Andrei-Marius Cercel, Dumitru-Clementin Pop, Florin Cercel, Mihaela-Claudia University Politehnica of Bucharest Faculty of Automatic Control and Computers Romania National Institute for Research & Development in Informatics - ICI Bucharest Romania First District Court of Buftea Romania

ISBN: (纸本)9781959429180

Named Entity Recognition (NER) is a well-explored area from Information Retrieval and Natural Language Processing with an extensive research community. Despite that, few languages, such as English and German, are well-resourced, whereas many other languages, such as Romanian, have scarce resources, especially in domain-specific applications. In this work, we address the NER problem in the legal domain from both Romanian and German languages and evaluate the performance of our proposed method based on domain adaptation. We employ multi-task learning to jointly train a neural network on two legal and general domains and perform adaptation among them. The results show that domain adaptation increase performances by a small amount, under 1%, while considerable improvements are in the recall metric. © 2022 Association for Computational Linguistics.

关键词： Natural language processing systems

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A Novel Architecture - Switching Echo State Networks

A Novel Architecture - Switching Echo State Networks

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IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR

作者： Codrin A. Lupascu Daniel Coca Octavian C. Pastravanu Department of Automatic Control and Applied Informatics Technical University “Gheorghe Asachi” Iasi Romania School of Engineering Newcastle University Newcastle UK

ISBN: (数字)9798350361933

ISBN: (纸本)9798350361940

This paper presents a novel approach to Echo State Networks (ESNs) by integrating state-feedback with switching systems theory and the computational efficiency of Reservoir Computing architectures. We introduce an innovative architecture for ESNs, featuring a switching input weight and state-feedback gain, applicable to both linear and non-linear reservoirs. The stability of this architecture is rigorously analysed using the standard Lyapunov function construction method. Additionally, we explore the dynamical properties of a state-feedback ESN architecture used in the literature. The advantages of the proposed switching ESN is demonstrated using electrophysiological recordings in fruitfly photoreceptors.

关键词： Symmetric matrices Computer architecture Switches Voltage Reservoirs Photoreceptors Stability analysis

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