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e-Journal of Nondestructive Testing 2024年第8期29卷

作者： Hena, Bata Wei, Ziang Perron, Luc Castanedo, Clemente Ibarra Maldague, Xavier Department of Electrical and Computer Engineering Université Laval 1065 Ave de la Médecine Quebec CityQCG1V 0A6 Canada Computer Vision and Systems Laboratory Department of Electrical and Computer Engineering Université Laval 1065 Ave de la Médecine Quebec CityQCG1V 0A6 Canada GI Lab Solutions 475 Pruneau Ave Québec CityQCG1M 2J8 Canada

Industrial radiography is a pivotal non-destructive testing (NDT) method that ensures quality and safety in a wide range of industrial sectors. Nevertheless, the conventional human-based approaches to carrying out industrial radiography are prone to challenges that negatively impact the accuracy and efficiency of defect detection. To solve this challenge, numerous computer-based alternatives have been developed, including Automated Defect Recognition (ADR) using deep learning algorithms. At the core of training, these ADR algorithms demand large volumes of qualitative data that should be representative of real-world cases to be expected during deployment. However, the availability of digital X-ray radiography data, especially for open research, is limited by non-disclosure contractual terms in the industry. In this study, we present a pipeline that is capable of modelling synthetic images based on real digital X-ray radiography images. This is achieved through a systematic analysis of the intensity distribution, considering grey value (GV) statistical uniqueness related to exposure conditions used during image acquisition, type of imaged component, material thickness variations, X-ray beam divergence, anode heel effect, scatter radiation, edge delineation, etc. The generated synthetic images were exclusively utilized to train a deep learning model, yielding an impressive model performance with mean intersection over union (IoU) of 0.93, and mean dice coefficient of 0.96 when tested on real unseen digital X-ray radiography images. The presented methodology is scalable and adaptable, making it suitable for diverse industrial applications. © 2024 The Authors.

关键词： X ray radiography

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NMPC-based Unified Posture Manipulation and Thrust Vectoring for Fault Recovery

arXiv

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arXiv 2025年

作者： Salagame, Adarsh Pandya, Shashwat Mandralis, Ioannis Sihite, Eric Ramezani, Alireza Gharib, Morteza SiliconSynapse Laboratory Department of Electrical and Computer Engineering Northeastern University BostonMA02119 United States Department of Aerospace California Institute of Technology PasadenaCA91125 United States

Multi-rotors face significant risks, as actuator failures at high altitudes can easily result in a crash and the robot’s destruction. Therefore, rapid fault recovery in the event of an actuator failure is necessary for the fault-tolerant and safe operation of unmanned aerial robots. In this work, we present a fault recovery approach based on the unification of posture manipulation and thrust vectoring. The key contributions of this work are: 1) Derivation of two flight dynamics models (high-fidelity and reduced-order) that capture posture control and thrust vectoring. 2) Design of a controller based on Nonlinear Model Predictive Control (NMPC) and demonstration of fault recovery in simulation using a high-fidelity model of the Multi-Modal Mobility Morphobot (M4) in Simscape. Copyright © 2025, The Authors. All rights reserved.

关键词： Predictive control systems

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Granular Spintronics-based Reservoir Computing for Temporal Applications

Granular Spintronics-based Reservoir Computing for Temporal ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Oliver Fridorf Lasse Møller Ryan Bjørnskov Alex Jenkins Luana Benetti Sonal Shreya Yasser Rezaeiyan Tim Böhnert Ricardo Ferreira Farshad Moradi Hooman Farkhani Dep. of Electrical and Computer Engineering Aarhus University Aarhus Denmark INL Av. Mestre José Veiga s/n International Iberian Nanotechnology Laboratory Braga Portugal

ISBN: (数字)9798350356830

ISBN: (纸本)9798350356847

This paper presents a novel approach to reservoir computing (RC) using Granular Vortex-Based Magnetic Tunnel Junctions (GV-MTJs) for temporal applications. GV-MTJs, with their unique magnetic domain configurations and granular structures, provide the necessary fading memory and non-linear dynamics essential for RC. The vortex core’s oscillatory motion within the device allows for temporal correlation of inputs, giving fading memory, while grain-induced non-linear resistance and frequency variations enhance data dimensionality. Our findings indicate that varying device parameters can affect the relaxation time and gyrotropic frequency in both simulation and experiments. Relaxation times range from 100-140 ns and frequencies from 250-100 MHz. Through experiments, the classification error was reduced by 27% for the best sample, others showed limited potential. Due to signal application speed constraints, the fading memory is not fully utilized. However, the inherent RC capabilities of GV-MTJs are validated. This paper highlights the promise of GV-MTJs in neuromorphic computing and suggests avenues for future research to optimise their use in practical applications.

关键词： Fading channels Resistance Time-frequency analysis Neuromorphic engineering Noise Memory management Pipelines Reservoir computing Speech recognition Spintronics

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Work-in-Progress: A Hybrid Collaborative Multi Agent Decision Making Algorithm With Factored-Value Max-Plus

Work-in-Progress: A Hybrid Collaborative Multi Agent Decisio...

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International Black Sea Conference on Communications and Networking (BlackSeaCom)

作者： Paul Cotae Nii Emil Alexander Reindorf Myong Kang Alexander Velazquez Department of Electrical and Computer Engineering The University of the District of Columbia Washington DC USA U. S. Naval Research Laboratory Center for High Assurance Computer Systems Washington DC USA

We focus on a real-time multi agent decision-making algorithm that combines a centralized algorithm and a distributed algorithm. A network segmentation is unavoidable in a dynamic environment. In such cases, it is necessary for each agent to continually make the most urgent real-time decisions in both centralized and decentralized ways. In this paper, we present a Hybrid Factored-Value Max-Plus algorithm with cost which has online, anytime, and scalable properties despite network segmentation. We also study the performance of centralized and distributed algorithms to understand the performance characteristics of a hybrid algorithm.

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MCMC-Based Sparse Bayesian Learning for Channel Estimation Using Gaussian Mixture Models

MCMC-Based Sparse Bayesian Learning for Channel Estimation U...

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IEEE Conference on Wireless Communications and Networking

作者： Xiaotian Fan Xingyu Zhou Hao Ye Le Liang Shi Jin National Mobile Communications Research Laboratory Southeast University Nanjing China Department of Electrical and Computer Engineering University of California Santa Cruz CA Purple Mountain Laboratories Nanjing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

This paper investigates the downlink channel estimation problem for frequency division duplex (FDD) multi-user massive multiple-input multiple-output (MIMO) systems. We model this problem within the sparse Bayesian learning (SBL) framework, where all unknowns are treated as random variables. Due to limited scattering at the base station, the channel exhibits sparsity in the angular domain. By introducing Gaussian mixture priors to characterize the user equipment internal sparsity and partially shared sparsity, we develop a Markov chain Monte Carlo (MCMC) method to implement Bayesian inference and accurately estimate all random variables in the model, including the channel matrix. Experimental results demonstrate that the MCMC-based SBL channel estimation algorithm outperforms existing approaches by over 5 dB in multi-user scenarios while reducing pilot overhead.

关键词： Monte Carlo methods Simulation Channel estimation Scattering Massive MIMO Downlink Inference algorithms Bayes methods Random variables Sparse matrices

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Experimental investigation on lightning impulse flashover of a 24 kv silicone line pin insulator

Experimental investigation on lightning impulse flashover of...

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23rd International Symposium on High Voltage engineering (ISH 2023)

作者： Pantelis N. Mikropoulos Petros P. Tsouris Michalis K. Angeli Fotini C. Knai High Voltage Laboratory School of Electrical and Computer Engineering Faculty of Engineering Aristotle University of Thessaloniki Building D Egnatia Str. 54124 Thessaloniki Greece

ISBN: (数字)9781839539923

An experimental investigation is presented on the flashover characteristics of a typical 24 kV silicone line pin insulator under lightning impulses 0.34/47 μs, by considering the amplitude and polarity of the applied voltage as influencing parameters. Based on the oscillographic records of the applied voltage and discharge current different phases of discharge growth could be discerned. Thus, inception, growth and flashover discharge characteristics are assessed and discussed. Increasing amplitude of the applied voltage causes more intense streamer corona activity, which, associated with greater charge, exerts a hindering effect on leader inception, the latter occurring at higher voltages. This is more pronounced for negative impulse voltages under which corona initiates at higher voltage and with higher current, thus also charge. At a given leader inception voltage the charge related to the streamer corona activity preceding leader inception is lower under negative impulses, possibly due to negative surface discharges and charge deposition on the insulator surface, suppressing the growth of streamer corona in air. The average potential gradient required for leader inception at 2.5% flashover probability was estimated approximately 690 and 1050 kV/m under positive and negative polarity impulses, respectively. At a given steepness of the applied voltage at leader inception the charge associated with leader growth is approximately two times larger for negative than positive impulses. The charge at flashover increases linearly with the steepness of the applied voltage at leader inception.

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Digital Twin-Assisted Collaborative Transcoding for Better User Satisfaction in Live Streaming

arXiv

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arXiv 2022年

作者： Huang, Xinyu Li, Mushu Wu, Wen Zhou, Conghao Shen, Xuemin Department of Electrical & Computer Engineering University of Waterloo Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Canada Frontier Research Center Peng Cheng Laboratory China

In this paper, we propose a digital twin (DT)-assisted cloud-edge collaborative transcoding scheme to enhance user satisfaction in live streaming. We first present a DT-assisted transcoding workload estimation (TWE) model for the cloud-edge collaborative transcoding. Particularly, two DTs are constructed for emulating the cloud-edge collaborative transcoding process by analyzing spatial-temporal information of individual videos and transcoding configurations of transcoding queues, respectively. Two light-weight Bayesian neural networks are adopted to fit the TWE models in DTs, respectively. We then formulate a transcoding-path selection problem to maximize long-term user satisfaction within an average service delay threshold, taking into account the dynamics of video arrivals and video requests. The problem is transformed into a standard Markov decision process by using the Lyapunov optimization and solved by a deep reinforcement learning algorithm. Simulation results based on the real-world dataset demonstrate that the proposed scheme can effectively enhance user satisfaction compared with benchmark schemes. © 2022, CC BY.

关键词： Markov processes

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Origin of Pinning Disorder in Magnetic-Field-Induced Wigner Solids

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Physical Review Letters 2024年第17期132卷 176301-176301页

作者： Matthew L. Freeman P. T. Madathil L. N. Pfeiffer K. W. Baldwin Y. J. Chung R. Winkler M. Shayegan L. W. Engel National High Magnetic Field Laboratory Florida State University Tallahassee Florida 32310 USA Department of Electrical and Computer Engineering Princeton University Princeton New Jersey 08544 USA Northern Illinois University DeKalb Illinois 60115 USA

At low Landau level filling factors (ν), Wigner solid phases of two-dimensional electron systems in GaAs are pinned by disorder and exhibit a pinning mode, whose frequency is a measure of the disorder that pins the Wigner solid. Despite numerous studies spanning the past three decades, the origin of the disorder that causes the pinning and determines the pinning mode frequency remains unknown. Here, we present a study of the pinning mode resonance in the low-ν Wigner solid phases of a series of ultralow-disorder GaAs quantum wells which are similar except for their varying well widths d. The pinning mode frequencies fp decrease strongly as d increases, with the widest well exhibiting fp as low as ≃35 MHz. The amount of reduction of fp with increasing d can be explained remarkably well by tails of the wave function impinging into the alloy-disordered AlxGa1−xAs barriers that contain the electrons. However, it is imperative that the model for the confinement and wave function includes the Coulomb repulsion in the growth direction between the electrons as they occupy the quantum well.

关键词： Charge density waves electrical conductivity electrical properties Plasmons Two-dimensional electron system

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An on-chip platform for multi-degree-of-freedom control of two-dimensional quantum and nonlinear materials

An on-chip platform for multi-degree-of-freedom control of t...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Tang, Haoning Wang, Yiting Ni, Xueqi Watanabe, Kenji Taniguchi, Takashi Fan, Shanhui Mazur, Eric Yacoby, Amir Cao, Yuan School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States National Institute for Materials Science Namiki 1-1 Ibaraki Tsukuba305-0044 Japan Department of Applied Physics Ginzton Laboratory Stanford University StanfordCA94305 United States

ISBN: (纸本)9781957171395

We introduce the first on-chip, microelectromechanical system for the in situ tuning of twisted 2D materials, enabling tunable interfacial properties, synthetic topological singularities, and adjustable-polarization light sources for advanced quantum material manipulation in 2D-3D devices. © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Degrees of freedom (mechanics)

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Dynamic Interval-Valued PCA for Enhanced Fault Detection

Dynamic Interval-Valued PCA for Enhanced Fault Detection

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Lahcene Rouani Mohamed Faouzi Harkat Abdelmalek Kouadri Abderazak Bensmail Majdi Mansouri Mohamed Nounou Signals and Systems Laboratory Institute of Electrical and Electronics Engineering University M’Hamed Bougara of Boumerdes Boumerdes Algeria Systems and Advanced Material Laboratory Badji Mokhtar - Annaba University Annaba Algeria Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This study introduces three novel dynamic interval-valued principal component analysis (DIPCA) methods: dynamic centers PCA (D-CPCA), dynamic vertices PCA (D-VPCA), and dynamic complete information PCA (D-CIPCA). These methods advance traditional interval-valued PCA (IPCA) by integrating dynamic aspects of industrial processes, thus addressing both data uncertainties and temporal correlations. The DIPCA methods were validated using real-world data from the Ain El Kebira cement plant. Results indicate significant improvements in fault detection accuracy, achieving lower false alarm rates and higher reliability compared to classical IPCA methods. Furthermore, an enhanced combined index for interval-valued data was developed, providing a single, comprehensive statistical measure for streamlined process monitoring.

关键词： Process monitoring Uncertainty Accuracy Fault detection Cement industry Aerodynamics Robustness Real-time systems Indexes Principal component analysis

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