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2021 World Automation Congress, WAC 2021

作者： Keivanimehr, Mehran Chamorro, Harold R. Zareian-Jahromi, Mehdi Segundo-Sevilla, Felix Rafael Guerrero, Josep M. Konstantinou, Charalambos University of Kashan Department of Electrical Engineering Kashan Iran Royal Institute of Technology KTH Stockholm Sweden Shiraz University School of Electrical and Computer Engineering Shiraz Iran Zurich University of Applied Sciences Power Systems and Smart Grid Lab Zurich Switzerland Aalborg University Aalborg Denmark Division of Computer Electrical and Mathematical Sciences and Engineering Thuwal23955 Saudi Arabia

ISBN: (纸本)9781685241117

Frequency control is one important issue in autonomous operating mode of Microgrids (MGs). In stand-alone microgrids, when generation power is not enough, it is inevitable to shed some parts of the load. This paper presents a decentralized fuzzy controller for optimal load shedding in MGs. The proposed controller which is separately installed for each load center uses a hierarchical fuzzy controller approach to make the optimal decision. Three inputs of the hierarchical fuzzy controller are the power of non-critical load, the load energy not supplied and its interruption frequency. From a specific time of the past, these inputs are calculated for all load centers, and updated periodically. The non-critical part of the loads which can be shed to survive network. Each decentralized controller of the loads has a bilateral communication with the microgrid central controller to transact some information, periodically. Simulation results on a typical microgrid with several load buses showing the effectiveness of the proposed method. © 2021 TSI Enterprises.

关键词： Controllers

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A Breast Cancer Image Classification Algorithm with 2c Multiclass Support Vector Machine

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Journal of Healthcare engineering 2023年第1期2023卷 3875525页

作者： Wajeed, Mohammed Abdul Tiwari, Shivam Gupta, Rajat Ahmad, Aamir Junaid Agarwal, Seema Jamal, Sajjad Shaukat Hinga, Simon Karanja Department of Computer Science and Engineering Swami Vivekananda Institute of Technology Telangana Secunderabad India Department of Computer Science and Engineering G L Bajaj Institute of Technology and Management Uttar Pradesh Greater Noida India Engineering and Technology Career Point University Rajasthan Kota India Department of Computer Science and Engineering Maulana Azad College of Engineering and Technology Patna India SRM institute of Science and Technology Delhi-NCR Campus Ghaziabad India Department of Mathematics College of Science King Khalid University Abha Saudi Arabia Department of Electrical and Electronic Engineering Technical University of Mombasa Mombasa Kenya

Breast cancer is the most frequent type of cancer in women;however, early identification has reduced the mortality rate associated with the condition. Studies have demonstrated that the earlier this sickness is detected by mammography, the lower the death rate. Breast mammography is a critical technique in the early identification of breast cancer since it can detect abnormalities in the breast months or years before a patient is aware of the presence of such abnormalities. Mammography is a type of breast scanning used in medical imaging that involves using x-rays to image the breasts. It is a method that produces high-resolution digital pictures of the breasts known as mammography. Immediately following the capture of digital images and transmission of those images to a piece of high-tech digital mammography equipment, our radiologists evaluate the photos to establish the specific position and degree of the sickness in the breast. When compared to the many classifiers typically used in the literature, the suggested Multiclass Support Vector Machine (MSVM) approach produces promising results, according to the authors. This method may pave the way for developing more advanced statistical characteristics based on most cancer prognostic models shortly. It is demonstrated in this paper that the suggested 2C algorithm with MSVM outperforms a decision tree model in terms of accuracy, which follows prior findings. According to our findings, new screening mammography technologies can increase the accuracy and accessibility of screening mammography around the world. Copyright © 2023 Mohammed Abdul Wajeed et al.

关键词： Diseases

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Analysis of Some Parameters of Synthesized Anodized Aluminum Oxide Matrices 17

Analysis of Some Parameters of Synthesized Anodized Aluminum...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Bukliv, Roxoliana Adamiv, Volodymyr Bordun, Ihor Andrushchak, Nazariy Teslyuk, Ihor Andrushchak, Anatoliy Institute of Chemistry and Chemical Technologies Lviv Polytechnic National University Department of Chemistry and Technology of Inorganic Substances Lviv Ukraine O. G. Vlokh Institute of Physical Opics Ivan Franko National University of Lviv Lviv Ukraine Czestochowa University of Technology Department of Electrical Power Engineering Czestochowa Poland Lviv Polytechnic National University Department of Ecology and Sustainable Environmental Management Lviv Ukraine Lviv Politechnic National University Computer-Aided Design Systems Lviv Ukraine Lviv Polytechnic National University Department of Applied Physics and Nanomaterials Science Lviv Ukraine

ISBN: (纸本)9798331520564

Studies have been conducted on anodized aluminum oxide (AAO) nanomatrices manufactured by SmartMembranes (SM) (Germany) and InRedox (USA). An X-ray fluorescence analyzer determined the quantitative and qualitative composition of AAO matrices. It is shown that the AAO matrices have a large transparency window (250 - 2750 nm) and the dependence of the second harmonic generation (SHG) signal on the pore size. The parameters of the porous structure of the samples were estimated by isothermal processes of nitrogen adsorption/desorption at its boiling point (T = 77 K). © 2024 IEEE.

关键词： Harmonic generation

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Reduced KPCA based Ensemble Learning Approach for Fault Diagnosis of Grid-Connected PV Systems 19

Reduced KPCA based Ensemble Learning Approach for Fault Diag...

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19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

作者： Dhibi, Khaled Mansouri, Majdi Bouzrara, Kais Nounou, Hazem Nounou, Mohamed Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir 5019 Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha23874 Qatar Department of Mathematics and Sciences Prince Sultan University Riyadh11586 Saudi Arabia Chemical Engineering Program Texas A&M University at Qatar Doha23874 Qatar

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

The main objective of this work is to develop novel fault diagnosis techniques using ensemble learning and multivariate statistical techniques. The proposed methods are capable of identifying and classifying PV faults. First, an ensemble learning (EL) method that combines several base models is proposed. Next, kernel principal components analysis (KPCA) and reduced KPCA are proposed to extract and select the pertinent characteristics from raw data. Then, the extracted significant characteristics are transmitted to the EL model for classification purposes. The main idea behind these proposals is to provide the best accuracy and also improve the results in terms of computation time. The diagno-sis results demonstrated the efficiency of the proposed frameworks. © 2022 IEEE.

关键词： Multivariant analysis

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Online Learning Quantum States with the Logarithmic Loss via VB-FTRL

arXiv

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arXiv 2023年

作者： Tseng, Wei-Fu Chen, Kai-Chun Xiao, Zi-Hong Li, Yen-Huan Department of Mathematics National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taiwan School of Medicine National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan Center for Quantum Science and Engineering National Taiwan University Taiwan

Online learning quantum states with the logarithmic loss (LL-OLQS) is a quantum generalization of online portfolio selection, a classic open problem in the field of online learning for over three decades. The problem also emerges in designing randomized optimization algorithms for maximum-likelihood quantum state tomography. Recently, Jézéquel et al. [9, arXiv:2209.13932] proposed the VB-FTRL algorithm, the first nearly regret-optimal algorithm for OPS with moderate computational complexity. In this note, we generalize VB-FTRL for LL-OLQS. Let d denote the dimension and T the number of rounds. The generalized algorithm achieves a regret rate of O(d2 log(d +T)) for LL-OLQS. Each iteration of the algorithm consists of solving a semidefinite program that can be implemented in polynomial time by, e.g., cutting-plane methods. For comparison, the best-known regret rate for LL-OLQS is currently O(d2 logT), achieved by the exponential weight method. However, there is no explicit implementation available for the exponential weight method for LL-OLQS. To facilitate the generalization, we introduce the notion of VB-convexity. VB-convexity is a sufficient condition for the logarithmic barrier associated with any function to be convex and is of independent interest. Copyright © 2023, The Authors. All rights reserved.

关键词： Maximum likelihood

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Cyber Warfare Threat Categorization on CPS by Dark Web Terrorist 4

Cyber Warfare Threat Categorization on CPS by Dark Web Terro...

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4th IEEE International Conference on Computing, Power and Communication Technologies, GUCON 2021

作者： Mahor, Vinod Rawat, Romil Kumar, Anil Chouhan, Mukesh Shaw, Rabindra Nath Ghosh, Ankush SVVV IPS College of Technology and Management Computer Science Gwalior India SVIIT Shri Vaishnav Vidyapeeth Vishwavidyalaya Computer Science Indore India Government Engineering College Department of Computer Science and Engineering Rajasthan Bharatpur India Government Polytechnic College Department of Computer Science and Engineering SheopurMP India Galgotias University Department of Electrical Electronics and Communication Engineering India School of Engineering and Applied Sciences The Neotia University West Bengal India

ISBN: (纸本)9781728199511

The Industrial Internet of Things (IIoT) also referred as Cyber Physical Systems (CPS) as critical elements, expected to play a key role in Industry 4.0 and always been vulnerable to cyber-attacks and vulnerabilities. Terrorists use cyber vulnerability as weapons for mass destruction. The dark web's strong transparency and hard-to-track systems offer a safe haven for criminal activity. On the dark web (DW), there is a wide variety of illicit material that is posted regularly. For supervised training, large-scale web pages are used in traditional DW categorization. However, new study is being hampered by the impossibility of gathering sufficiently illicit DW material and the time spent manually tagging web pages. We suggest a system for accurately classifying criminal activity on the DW in this article. Rather than depending on the vast DW training package, we used authorized regulatory to various types of illicit activity for training Machine Learning (ML) classifiers and get appreciable categorization results. Espionage, Sabotage, electrical power grid, Propaganda and Economic disruption are the cyber warfare motivations and We choose appropriate data from the open source links for supervised Learning and run a categorization experiment on the illicit material obtained from the actual DW. The results shows that in the experimental setting, using TF-IDF function extraction and a AdaBoost classifier, we were able to achieve an accuracy of 0.942. Our method enables the researchers and System authoritarian agency to verify if their DW corpus includes such illicit activity depending on the applicable rules of the illicit categories they are interested in, allowing them to identify and track possible illicit websites in real time. Because broad training set and expert-supplied seed keywords are not required, this categorization approach offers another option for defining illicit activities on the DW. © 2021 IEEE.

关键词： Terrorism

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Fault detection in closed-loop systems using a double residual generator

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IFAC-PapersOnLine 2022年第6期55卷 298-303页

作者： Henrik Niemann Niels Kjølstad Poulsen Dept. of Electrical Engineering Technical University of Denmark DK-2800 Kgs. Lyngby Denmark Dept. of Applied Mathematics and Computer Science Technical University of Denmark DK-2800 Kgs. Lyngby Denmark

A double residual generator for fault detection in closed-loop systems is presented in this paper. The residual generator gives the standard residual vector and a dual residual vector as outputs. The standard residual vector can be applied directly for fault detection. The dual residual vector depends on known inputs to the system e.g. reference inputs and auxiliary inputs but decoupled from the disturbance in the system. It is also an input vector that can be applied for active fault detection (AFD). The dual residual vector can be considered as a generalized input vector in connection with AFD in closed-loop systems. This gives the possibility to use all known inputs for detection. The dual residual vector gives a link between passive and AFD in closed-loop systems. The double residual generator is given directly as the left Bezout matrix from the Bezout equation.

关键词： Fault detection residual generators parametric faults closed-loop systems coprime factorization

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Real-Time Task Scheduling for Digital Twin Edge Network

Real-Time Task Scheduling for Digital Twin Edge Network

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IEEE Conference on Global Communications (GLOBECOM)

作者： Cheonyong Kim Mahdi Chehimi Minchae Jung Walid Saad Department of Electronics and Information Engineering Sejong University Seoul Republic of Korea Bradley Department of Electrical and Computer Engineering Wireless@VT Virginia Tech VA USA Cyber Security Systems and Applied AI Research Center Lebanese American University Lebanon

The deployment of digital twins (DTs) at the edge of a wireless network can facilitate low-latency and high-throughput DT autonomous and real-time Internet of everything (IoE) applications. In such DT edge networks (DTENs), each DT has two types of real-time tasks that require timely processing: DT update tasks and DT inference tasks. However, the joint scheduling of these two types of tasks has been overlooked in prior works. In this paper, the first joint real-time scheduling scheme for DT update and inference tasks in a DTEN is proposed. Moreover, a novel performance metric called freshness is introduced to capture the effectiveness and synchronization performance of scheduling. Also, a new scheduling scheme is proposed to efficiently solve a freshness maximization problem for DTENs. Simulation results show that the performance of the proposed scheme is within 4% of the upper bound for DTENs with 20 physical objects, and within 12% of the upper bound in worst cases for DTENs with more than 30 physical objects. The results also show that the proposed approach reduces the maximum de-synchronization time by 63% compared to existing real-time scheduling algorithms.

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Improving the speed of variational quantum algorithms for quantum error correction

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Physical Review A 2023年第2期108卷 022611-022611页

作者： Fabio Zoratti Giacomo De Palma Bobak Kiani Quynh T. Nguyen Milad Marvian Seth Lloyd Vittorio Giovannetti Scuola Normale Superiore I-56126 Pisa Italy Department of Mathematics University of Bologna 40126 Bologna Italy Department of Electrical Engineering and Computer Science MIT 77 Massachusetts Avenue Cambridge Massachusetts 02139 USA Department of Electrical and Computer Engineering and Center for Quantum Information and Control University of New Mexico Albuquerque New Mexico 87131 USA Department of Mechanical Engineering MIT 77 Massachusetts Avenue Cambridge Massachusetts 02139 USA Turing Inc. Cambridge Massachusetts 02139 USA NEST Scuola Normale Superiore and Istituto Nanoscienze-CNR I-56126 Pisa Italy

We consider the problem of devising suitable quantum error correction (QEC) procedures for a generic quantum noise acting on a quantum circuit. In general, there is no analytic universal procedure to obtain the encoding and correction unitary gates, and the problem is even harder if the noise is unknown and has to be reconstructed. The existing procedures rely on variational quantum algorithms (VQAs) and are very difficult to train since the size of the gradient of the cost function decays exponentially with the number of qubits. We address this problem using a cost function based on the quantum Wasserstein distance of order 1 (QW1). At variance with other quantum distances typically adopted in quantum information processing, QW1 lacks the unitary invariance property which makes it a suitable tool to avoid getting trapped in local minima. Focusing on a simple noise model for which an exact QEC solution is known and can be used as a theoretical benchmark, we run a series of numerical tests that show how, guiding the VQA search through the QW1, can indeed significantly increase both the probability of a successful training and the fidelity of the recovered state, with respect to the results one obtains when using conventional approaches.

关键词： Quantum computation Quantum error correction

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On Trivalent Logics, Compound Conditionals, and Probabilistic Deduction Theorems

arXiv

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arXiv 2023年

作者： Gilio, Angelo Over, David E. Pfeifer, Niki Sanfilippo, Giuseppe Department of Basic and Applied Sciences for Engineering University of Rome "La Sapienza" Italy Department of Psychology Durham University United Kingdom Department of Philosophy University of Regensburg Germany Department of Mathematics and Computer Science University of Palermo Italy INdAM-GNAMPA Italy

In this paper we recall some results for conditional events, compound conditionals, conditional random quantities, p-consistency, and p-entailment. Then, we show the equivalence between bets on conditionals and conditional bets, by reviewing de Finetti’s trivalent analysis of conditionals. But our approach goes beyond de Finetti’s early trivalent logical analysis and is based on his later ideas, aiming to take his proposals to a higher level. We examine two recent articles that explore trivalent logics for conditionals and their definitions of logical validity and compare them with our approach to compound conditionals. We prove a Probabilistic Deduction Theorem for conditional events. After that, we study some probabilistic deduction theorems, by presenting several examples. We focus on iterated conditionals and the invalidity of the Import-Export principle in the light of our Probabilistic Deduction Theorem. We use the inference from a disjunction, A or B, to the conditional, if not-A then B, as an example to show the invalidity of the Import-Export principle. We also introduce a General Import-Export principle and we illustrate it by examining some p-valid inference rules of System P. Finally, we briefly discuss some related work relevant to AI. Copyright © 2023, The Authors. All rights reserved.

关键词： Artificial intelligence

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