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Iteration Complexity of a Fixed-Stepsize SQP Method for Nonconvex Optimization with Convex Constraints 5th

Iteration Complexity of a Fixed-Stepsize SQP Method for Nonc...

5th International Conference on Numerical Analysis and Optimization: Theory, Methods, Applications and Technology Transfer, NAOV 2020

作者： Facchinei, Francisco Kungurtsev, Vyacheslav Lampariello, Lorenzo Scutari, Gesualdo Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Rome Italy Department of Computer Science Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic Department of Business Studies Roma Tre University Rome Italy School of Industrial Engineering Purdue University West-LafayetteIN United States

ISBN: (纸本)9783030720391

We consider an SQP method for solving nonconvex optimization problems whose feasible set is convex and with an objective function that is the sum of a smooth nonconvex term and a nonsmooth, convex one. In the proposed method, at each iteration, a direction is generated by solving a strongly convex approximation to the original problem and then a fixed-stepsize is taken in that direction. The complexity result we establish is, as far as we are aware, the best available for the rather general setting we consider. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fixed-stepsize Iteration complexity SQP methods

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Optimization of Methodology for Identifying Partial Discharges in Insulating Liquids Through Optical Radiation Analysis Using Machine Learning

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Michał Kozioł Tomasz Boczar Daniel Jancarczyk Marcin Bernaś Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computer Science and Automatics University of Bielsko-Biala Bielsko-Biala Poland

The emission of optical radiation is associated with electrical discharges in high-voltage power systems. Detecting, measuring, and analyzing this radiation can enable the identification of the type of electrical discharge and the determination of its source. This article presents the results of measurements and analysis of optical spectra in the context of their application for recognizing different forms of electrical discharges in selected insulating liquids. Optical radiation in the ultraviolet, visible light, and near-infrared range, emitted by electrical discharges in insulating liquids commonly used in electrical engineering, such as mineral oil, natural ester, and synthetic ester, was analyzed. As part of the research, an innovative methodology for measuring and analyzing optical radiation emitted by electrical discharges was proposed, utilizing machine learning (ML) tools for precise analysis and interpretation of measurement data. The research results enrich current knowledge with new parameters and measurement indicators, representing another stage in the development of diagnostic methods that can be used to build expert systems and new diagnostic techniques for high-voltage insulation systems.

关键词： Stimulated emission Optical variables measurement Optical fibers Optical sensors Optical fiber sensors Partial discharges Electrical engineering Signal processing algorithms Optical films Discharges (electric)

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Comparing concepts of quantum and classical neural network models for image classification task

arXiv

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arXiv 2021年

作者： Potempa, Rafal Porebski, Sebastian Department of Cybernetics Nanotechnology and Data Processing Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

While quantum architectures are still under development, when available, they will only be able to process quantum data when machine learning algorithms can only process numerical data. Therefore, in the issues of classification or regression, it is necessary to simulate and study quantum systems that will transfer the numerical input data to a quantum form and enable quantum computers to use the available methods of machine learning. This material includes the results of experiments on training and performance of a hybrid quantum-classical neural network developed for the problem of classification of handwritten digits from the MNIST data set. The comparative results of two models: classical and quantum neural networks of a similar number of training parameters, indicate that the quantum network, although its simulation is time-consuming, overcomes the classical network (it has better convergence and achieves higher training and testing accuracy). © 2021, CC BY.

关键词： Image recognition

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Automated Door to Prevent COVID-19 using Fuzzy Logic

Automated Door to Prevent COVID-19 using Fuzzy Logic

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International Conference on Electrical, Communication, and computer engineering (ICECCE)

作者： Salah-Ud-Din Khokhar Rana Sohaib Abdul Muneeb Irfana Bibi Muhammad Yasir Noor Muhammad Imran School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan P.R.China Department of Computer Science G.C. University Lahore Lahore Pakistan Department of Computer Science Faculty of Computing and Information Technology University of Punjab Lahore Pakistan Department of Electronics G.C. University Lahore Lahore Pakistan

Due to the vagueness and uncertainties due to the coronavirus, it is crucial to implement the standard operating procedures (SOPs) issued by the World Health Organization and the authorities. Therefore an effective control system is required that minimizes the vagueness and uncertainties of people who are on the front line during the period of this pandemic checking the entering persons in an indoor area where it is necessary to maintain a distance of six feet from one another to avoid the spread of coronavirus. In this research work, a robust and efficient system has been proposed that takes protective mask and feverishness values as input and applies them using the fuzzy logic algorithm. If these input values are according to the rules defined in the system, then the door will open as an output. Otherwise, the door will not open. It is, finally, analyzing the output values. This fuzzy model had been implemented using a microcontroller. The genuine difference in the duty cycle of the microcontroller’s output pulse was measured using a 100 MHz digital oscilloscope. Our proposed system was compared with different systems reported in the literature. This work reduces the human effort as well as the negligence of people and builds up the management system without the labor in a mint.

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Maximum Power Point Tracking Using Cross-Correlation Algorithm for Pv System

SSRN

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SSRN 2022年

作者： Abulanwar, Sayed Shahin, Ahmed Gad, Hesham H. Rizk, Mohammad E.M. Hu, Weihao Electrical Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Computer and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Engineering Horus University Egypt

This paper suggests an online, rapid, dynamic, and pragmatic cross-correlation (CC) technique to eﬀectively realize maximum power point tracking (MPPT) of the photovoltaic (PV) array. The PV voltage and current are extracted, averaged, and rate of change of the power and terminal voltage dynamics are integrally cross-correlated to regulate the duty ratio of the converter. According to this approach, the maximum power point (MPP) is defned in terms of the polarity of the CC coefcient (rcc). If the CC coefcient is positive, the operating point is at left of the MPP, while a negative CC coefcient indicates that the operating point is located at right of the MPP, otherwise the MPP is attained zero CC coefcient with lower steady-state ﬂuctuations. In this regard, a tracking optimization can be realized with confned drift either under gradual or step solar irradiance changes. The proposed CC technique quickly converges to the MPP without identifcation of PV array parameters. Besides, the proposed CC tracking algorithm tracks MPP with wide-range small step-size iterations since the search area is restricted to the vicinity of the MPP rather than the entire PV curve. Moreover, the proposed technique is featured by robustness against system parameters and load variations with simple hardware implementation as compared to several existing techniques. The eﬀectiveness of the proposed technique is thoroughly explored via time-domain, experimental, and hardware-in-loop investigations and meanwhile compared to the two most popular techniques: P&O INC methods, for both gradual and step irradiance changes and also shadow eﬀects. © 2022, The Authors. All rights reserved.

关键词： Time domain analysis

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MI3SE: A Multi-User Index-Based Searchable Symmetric Encryption Scheme for Improving Security of Data in Connected Electronic Devices

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IEEE Transactions on Consumer Electronics 2024年

作者： Soleymani, Seyed Ahmad Goudarzi, Shidrokh Anisi, Mohammad Hossein Xiao, Pei Mihaylova, Lyudmila Wang, Wenwu University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom University of West London School of Computing and Engineering LondonW5 5RF United Kingdom University of Essex School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom GuildfordGU2 7XH United Kingdom GuildfordGU2 7XH United Kingdom

In the Industrial Internet of Things (IIoT), outdoor electronic devices serve crucial roles across sectors, providing vital data for decision-making. However, their exposure to open outdoor environments makes them vulnerable to unauthorized access, physical theft, or compromise, endangering both the device and its data. Ensuring the security of outdoor devices and their data is thus critical. This study addresses data security in outdoor IIoT devices by supporting the encryption of all IIoT-related data in device memory. Accessing and retrieving this data requires operations on encrypted data. Hence, we introduce a Searchable Symmetric Encryption (SSE) scheme called MI3SE, which ensures each device's encryption key is unique and valid for a period based on the device's security sensitivity. Moreover, MI3SE meets key security requirements, including confidentiality, integrity, forward secrecy, and backward secrecy. It is specifically designed to mitigate physical compromise and query pattern analysis through a two-keyword query approach and withstand various attacks, as validated by rigorous security analysis. Comparative evaluations against benchmark schemes underscore the efficacy of MI3SE in terms of both security and performance. Moreover, comprehensive non-mathematical security analysis and simulation experiments affirm the enhanced accuracy and efficacy of MI3SE in securing sensitive data stored in outdoor IIoT devices. © 1975-2011 IEEE.

关键词： Data Security IIoT Outdoor Electronic Devices Searchable Symmetric Encryption (SSE)

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Real-time object detection and robotic manipulation for agriculture using a YOLO-based learning approach

arXiv

引用

arXiv 2024年

作者： Zhao, Hongyu Tang, Zezhi Li, Zhenhong Dong, Yi Si, Yuancheng Lu, Mingyang Panoutsos, George The Department of Physics Imperial College London United Kingdom The Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom The Department of Electrical and Electronic Engineering University of Manchester Manchester United Kingdom The Department of Electronics and Computer Science University of Southampton Southampton United Kingdom The Department of Economics Fudan University Shanghai200433 China Iowa State University AmesIA50011 United States

The optimisation of crop harvesting processes for commonly cultivated crops is of great importance in the aim of agricultural industrialisation. Nowadays, the utilisation of machine vision has enabled the automated identification of crops, leading to the enhancement of harvesting efficiency, but challenges still exist. This study presents a new framework that combines two separate architectures of convolutional neural networks (CNNs) in order to simultaneously accomplish the tasks of crop detection and harvesting (robotic manipulation) inside a simulated environment. Crop images in the simulated environment are subjected to random rotations, cropping, brightness, and contrast adjustments to create augmented images for dataset generation. The you only look once algorithmic framework is employed with traditional rectangular bounding boxes (R-Bbox) for crop localization. The proposed method subsequently utilises the acquired image data via a visual geometry group model in order to reveal the grasping positions for the robotic manipulation. Copyright © 2024, The Authors. All rights reserved.

关键词： Crops

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Enabling IoT Continuous Connectivity in Smart Spaces

Enabling IoT Continuous Connectivity in Smart Spaces

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International Symposium on Parallel and Distributed Computing

作者： Andreas Andreou Constandinos X. Mavromoustakis Jordi Mongay Batalla Ciprian Dobre Evangelos Markakis George Mastorakis Departement of Computer Science University of Nicosia and University of Nicosia Research Foundation Nicosia Cyprus Warsaw University of Technology Warsaw Poland Automatic Control and Computers University Politehnica of Bucharest National Institute for Research and Development in Informatics Bucharest Romania Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Greece Department of Management Science and Technology Hellenic Mediterranean University Agios Nikolaos Greece

Smart spaces are a rapidly emerging concept in technology. They result from the convergence of various novel technologies, such as the Internet of Things, Machine Learning and Artificial Intelligence, which allow for greater levels of automation and control within physical environments. The devices which are connected to the IoT network are equipped with sensors to acquire and exchange data. As a result, the IoT has transformed how we live, work, and play. However, the deployment in smart spaces is not always the best due to the issues arising from network node positioning. Therefore, we are investigating solutions to this problem with a novel approach which utilises Voronoi diagrams in conjunction with the algorithmic genetic technique. First, the initial positions of the IoT nodes will be determined by simulating a homogeneous Poisson point process in the smart space environment. Then, after dividing the area into the Voronoi cells, the genetic algorithm will optimise the position towards achieving full network coverage within the smart space. Experimental results prove the 100% network coverage within the specified area.

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Multi-method analysis of emotional and affective states

Multi-method analysis of emotional and affective states

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Progress in Applied Electrical engineering (PAEE)

作者： Adrian Luckiewicz Bogdan Ruszczak Mariusz Pelc Dariusz Mikołajewski Adam Sudoł Barbara Grochowicz Edward J. Gorzelanczyk Patryk Mendon Aleksandra Kawala-Sterniu Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science University of Opole Opole Poland School of Computing and Mathematical Sciences University of Greenwich London UK Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Neuropsychological Research Unit 2nd Clinic of the Psychiatry and Psychiatric Rehabilitation Medical University in Lublin Lublin Poland Faculty of Natural and Technical Sciences University of Opole Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland

ISBN: (数字)9798331527563

ISBN: (纸本)9798331527570

This study explores the neurological basis of emotions using a multi-method approach, analysing functional near-infrared spectroscopy (fNIRS) data obtained from a 26-channel device. Author’s primary objective was to examine the brain’s response to tasks that provoke emotional, imagery and affective reactions through the observation of hemodynamic changes in data. By applying data processing methods and techniques, cerebral activations corresponding to different emotional states were shown. This research enriches comprehension of how emotion and imagery tasks are processed by the brain and offers insights into aspects of brain activity during emotionally charged engagements.

关键词： Electrical engineering Brain Data processing Hemodynamics Functional near-infrared spectroscopy

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ML-Powered Biomedical Signals Processing using Hybrid Filters

ML-Powered Biomedical Signals Processing using Hybrid Filter...

引用

Progress in Applied Electrical engineering (PAEE)

作者： Mariusz Pelc Dariusz Mikołajewski Patryk Mendoń Adrian Luckiewicz Adam Sudoł Edward Jacek Gorzelańczyk Aleksandra Kawala-Sterniuk Institute of Computer Science University of Opole Opole Poland School of Computing and Mathematical Sciences University of Greenwich London UK Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Neuropsychological Research Unit 2nd Clinic of the Psychiatry and Psychiatric Rehabilitation Medical University in Lublin Lublin Poland Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Faculty of Natural and Technical Sciences University of Opole Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland

ISBN: (数字)9798331527563

ISBN: (纸本)9798331527570

This paper deals with the problem of signals filtering using hybrid filters. Such solutions may prove to be especially beneficial in the context of biomedical signals filtering where the signals’ amplitudes are typically not very high and they can be easily affected by different kinds of disturbances. Having a number of different types of filters tuned for some specific purposes we will show how the best filter choice is affected by selecting one ML model over another.

关键词： Electrical engineering Filters Biological system modeling Biomedical communication

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