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Enhancing Immunity of Full-Cycle Discrete Fourier Transform Against Decaying DC Components: A Comparative Analysis 19

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Enhancing Immunity of Full-Cycle Discrete Fourier Transform ...

19th IEEE International Conference on Environment and Electrical engineering and 2019 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2019

作者： Tajdinian, Mohsen Samet, Haidar Hamedi, Alireza Hadaeghi, Arsalan Bagheri, Alireza Allahbakhshi, Mehdi Seifi, Alireza School of Electrical and Computer Engineering Shiraz University Dept. of Power and Control Engineering Shiraz Iran

ISBN: (纸本)9781728106526

Decaying DC terms of the fault current signal indisputably affect the accuracy of the discrete Fourier transform (DFT) based fundamental phasor estimators of digital relays. This effects will lead to delay in the best case and mal operation in the worst case of the protective relays and it may threat the reliability and security of the power system. This paper aims to conduct a comparative analysis between some decaying DC removal filters for enhancing the immunity if full-cycle DFT against decaying DC components. This paper mainly discusses the effects of DC offsets in the fault current and CT transient responses, harmonics and off-nominal frequency on the performance of DFT. Applying different test signals and also simulated fault current, the effectiveness of the different DC removal filters in combination with DFT is investigated. Analyzing simulation results, it is observed that the DFT phasor estimator should be provided with an algorithm that removes DC offsets due to fault current and CT transient responses under harmonic, noisy and off-nominal frequency conditions. © 2019 IEEE.

关键词： Discrete Fourier transforms

Resource-Efficient Real-Time Polarization Compensation for MDI-QKD with Rejected Data

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arXiv 2022年

作者： Bedroya, Olinka Li, Chenyang Wang, Wenyuan Hu, Jianyong Lo, Hoi-Kwong Qian, Li Centre for Quantum Information and Quantum Control Dept. of Physics University of Toronto TorontoONM5S 1A7 Canada Centre for Quantum Information and Quantum Control Dept. of Electrical & Computer Engineering University of Toronto TorontoONM5S 3G4 Canada Department of Physics University of Hong Kong Pokfulam Hong Kong 100 College St TorontoONM5G 1L5 Canada

Measurement-device-independent quantum key distribution (MDI-QKD) closes all the security loopholes in the detection system and is a promising solution for secret key sharing. Polarization encoding is the most common QKD encoding scheme, as it is straightforward to prepare and measure. However, implementing polarization encoding in MDI QKD imposes extra challenges, as polarization alignment must be maintained over both mutually unbiased bases and be maintained for both paths (Alice-Charlie and Bob-Charlie). Polarization alignment is usually done by interrupting the QKD process (reducing overall key generation rates) or using additional classical laser sources multiplexed with quantum channels for polarization alignment. Since low key rates and cost are the two most pressing challenges preventing wide adoption of QKD systems, using additional resources or reducing key rates runs contrary to making QKD commercially viable. Therefore, we propose and implement a novel polarization compensation scheme in the MDI-QKD system that avoids the aforementioned drawbacks by recycling part of discarded detection events. Our scheme evaluates the polarization drift in real-time based on single measurements corresponding to decoy intensities. Our fully automated experimental demonstration maintains the average polarization drift below 0.13 rad over 40 km of spooled fibre (without an insulating jacket) for at least four hours. The average quantum bit error rate is 3.8%, and we achieved an average key rate of 7.45 × 10−6 bits per pulse. © 2022, CC BY.

关键词： Polarization

Live Demo: E2P–Events to Polarization Reconstruction from PDAVIS Events

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Live Demo: E2P–Events to Polarization Reconstruction from P...

IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Tobi Delbruck Zuowen Wang Haiyang Mei Germain Haessig Damien Joubert Justin Haque Yingkai Chen Moritz B. Milde Viktor Gruev Sensors Group Institute of Neuroinformatics Univ. of Zurich and ETH Zurich Switzerland AIT Austrian Institute of Technology Center for Vision Automation & Control High-Performance Vision Systems Vienna Austria Intl. Centre for Neuromorphic Systems The MARCS Institute Western Sydney University Sydney Australia Dept. of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL USA

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [...

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Automated segmentation of microtomography imaging of Egyptian mummies

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arXiv 2021年

作者： Tanti, Marc Berruyer, Camille Tafforeau, Paul Muscat, Adrian Farrugia, Reuben Scerri, Kenneth Valentino, Gianluca Solé, V. Armando Briffa, Johann A. Dept. of Comm. & Computer Engineering University of Malta Msida MSD 2080 Malta European Synchrotron Radiation Facility 71 Avenue des Martyrs CS-40220 Cedex 09 Grenoble38043 France Dept. of Systems & Control Engineering University of Malta Msida MSD 2080 Malta

Propagation Phase Contrast Synchrotron Microtomography (PPC-SRµCT) is the gold standard for non-invasive and non-destructive access to internal structures of archaeological remains. In this analysis, the virtual specimen needs to be segmented to separate different parts or materials, a process that normally requires considerable human effort. In the Automated SEgmentation of Microtomography Imaging (ASEMI) project, we developed a tool to automatically segment these volumetric images, using manually segmented samples to tune and train a machine learning model. For a set of four specimens of ancient Egyptian animal mummies we achieve an overall accuracy of 94-98% when compared with manually segmented slices, approaching the results of off-the-shelf commercial software using deep learning (97-99%) at much lower complexity. A qualitative analysis of the segmented output shows that our results are close in terms of usability to those from deep learning, justifying the use of these techniques. Copyright © 2021, The Authors. All rights reserved.

关键词： Tomography

V-Edge: Virtual edge computing as an enabler for novel microservices and cooperative computing

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arXiv 2021年

作者： Dressler, Falko Chiasserini, Carla Fabiana Fitzek, Frank H.P. Karl, Holger Cigno, Renato Lo Capone, Antonio Casetti, Claudio Malandrino, Francesco Mancuso, Vincenzo Klingler, Florian Rizzo, Gianluca The School of Electrical Engineering and Computer Science TU Berlin Berlin Germany The Dept. of Electronics and Telecommunications Politecnico di Torino Torino Italy The School of Engineering Sciences as well as the Excellence Cluster CeTI TU Dresden Dresden Germany The Hasso-Plattner-Institute Potsdam Germany The Dept. of Information Engineering University of Brescia Brescia Italy The Dept. of Electronics Information and Bioengineering Politecnico di Milano Milano Italy The Dept. of Control and Computer Engineering Politecnico di Torino Torino Italy The Institute of Electronics Computer and Communication Engineering of the National Research Council of Italy Torino Italy IMDEA Networks Madrid Spain The Dept. of Computer Science Paderborn University Paderborn Germany The Research Institute of Information Systems HES-SO Valais-Wallis Switzerland University of Foggia Italy

As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: instead of sending all data and tasks from an end user's device to the cloud, possibly covering thousands of kilometers and introducing delays that are just owed to limited propagation speed, edge servers deployed in close proximity to the user, e.g., at some 5G gNB, serve as proxy for the cloud. Yet this promising idea is hampered by the limited availability of such edge servers. In this paper, we discuss a way forward, namely the virtual edge computing (V-Edge) concept. V-Edge bridges the gap between cloud, edge, and fog by virtualizing all available resources including the end users' devices and making these resources widely available using well-defined interfaces. V-Edge also acts as an enabler for novel microservices as well as cooperative computing solutions. We introduce the general V-Edge architecture and we characterize some of the key research challenges to overcome, in order to enable wide-spread and even more powerful edge services. Copyright © 2021, The Authors. All rights reserved.

关键词： Edge computing

On the Role of Models in Learning control: Actor-Critic Iterative Learning control

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IFAC-PapersOnLine 2020年第2期53卷 1450-1455页

作者： Maurice Poot Jim Portegies Tom Oomen Control Systems Technology Group Dept. of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands CASA Dept. of Mathematics and Computer Science Eindhoven University of Technology Eindhoven The Netherlands

Learning from data of past tasks can substantially improve the accuracy of mechatronic systems. Often, for fast and safe learning a model of the system is required. The aim of this paper is to develop a model-free approach for fast and safe learning for mechatronic systems. The developed actor-critic iterative learning control (ACILC) framework uses a feedforward parameterization with basis functions. These basis functions encode implicit model knowledge and the actor-critic algorithm learns the feedforward parameters without explicitly using a model. Experimental results on a printer setup demonstrate that the developed ACILC framework is capable of achieving the same feedforward signal as preexisting model-based methods without using explicit model knowledge.

关键词： Feedforward control iterative learning control learning algorithms reinforcement learning Markov decision problems function-approximation model-free control model-based control

Improving P300 Speller performance by means of optimization and machine learning

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arXiv 2020年

作者： Bianchi, Luigi Liti, Chiara Liuzzi, Giampaolo Piccialli, Veronica Salvatore, Cecilia Dept. of Civil Engineering and Computer Science University of Rome Tor Vergata Department of Computer Control and Management Engineering Sapienza University of Rome

Brain-computer Interfaces (BCIs) are systems allowing people to interact with the environment bypassing the natural neuromuscular and hormonal outputs of the peripheral nervous system (PNS). These interfaces record a user’s brain activity and translate it into control commands for external devices, thus providing the PNS with additional artificial outputs. In this framework, the BCIs based on the P300 Event-Related Potentials (ERP), which represent the electrical responses recorded from the brain after specific events or stimuli, have proven to be particularly successful and robust. The presence or the absence of a P300 evoked potential within the EEG features is determined through a classification algorithm. Linear classifiers such as stepwise linear discriminant analysis (SWLDA) and support vector machine (SVM) are the most used discriminant algorithms for ERPs’ classification. Due to the low signal-to-noise ratio of the EEG signals, multiple stimulation sequences (a.k.a. iterations) are carried out and then averaged before the signals being classified. However, while augmenting the number of iterations improves the Signal-to-Noise Ratio (SNR), it also slows down the process. In the early studies, the number of iterations was fixed (no stopping), but recently, several early stopping strategies have been proposed in the literature to dynamically interrupt the stimulation sequence when a certain criterion is met to enhance the communication rate. In. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain computer interface

An Experimental Study on Classification of Drivers Based on Confidence and Command of Driving

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An Experimental Study on Classification of Drivers Based on ...

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Daghan Dogan Tankut Acarman Seta Bogosyan Mechatronics Engineering Dept. Istanbul Technical University Istanbul Turkey Computer Engineering Dept. Galatasaray University Istanbul Turkey Control and Automation Engineering Dept. Istanbul Technical University Istanbul Turkey

ISBN: (数字)9781728156354

ISBN: (纸本)9781728156361

This study proposes a simple classification method for drivers based on their driving confidence and authority using feedback from steering wheel angle and traction motor current measurement data. Data is collected from 38 drivers on a prototype electric vehicle. For the classification process, the driving performance of each driver is assessed with respect to an expert driver. The data is time-stamped and geo-referenced. The experimental driving data is comprised of the two command inputs that the driver generates to regulate handling and lane-level tracking. Deviations from the expert's performance data are considered to be a measure of potential failure of the driver's confidence and authority leading to a possible accident. The dataset of the participating drivers is processed by extracting the mean, standard deviation, skewness and kurtosis values. Extracted features are evaluated with different classification methods, including KNN.

关键词： Vehicles Feature extraction Hidden Markov models Torque Data collection Euclidean distance Task analysis

Spectroscopic detection of pigments in tissues: correlation with tissue aging and cancer development

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Spectroscopic detection of pigments in tissues: correlation ...

2022 International Conference Laser Optics, ICLO 2022

作者： Oliveira, L.M. Goncalves, T.M. Botelho, A.R. Martins, I.S. Silva, H.F. Carneiro, I. Carvalho, S. Henrique, R. Tuchin, V.V. Porto Portugal Center of Innovation in Engineering and Industrial Technology Isep Porto Portugal Department of Electrical and Computer Engineering Porto University-School of Engineering Porto Portugal Department of Pathology and Cancer Biology and Epigenetics Group Portuguese Oncology Institute of Porto Porto Portugal Porto Portugal Viana do Castelo Portugal Dept. of Pathol. and Molecular Immunology Porto University-Institute of Biomedical Sciences Abel Salazar Porto Portugal Science Medical Center Saratov State University Saratov Russia Laboratory of Laser Molecular Imaging and Machine Learning National Research Tomsk State University Tomsk Russia Laboratory of Laser Diagnostics of Technical and Living Systems Institute of Precision Mechanics and Control Frc-Saratov Scientific Centre-of the Russian Academy of Sciences Saratov Russia

ISBN: (纸本)9781665466646

The direct calculation of the absorption coefficient spectra of various tissues from spectral measurements allowed to retrieve the contents of melanin and lipofuscin. In the rabbit brain cortex, 1.8 times higher melanin content is explained by the neuron degeneration process. Similar melanin and lipofuscin contents were found in the rabbit pancreas as a result of the tissue aging process. The conversion of 83 % of the melanin in the human normal kidney into lipofuscin in the cancer kidney indicates that lipofuscin can be considered a kidney cancer marker in humans. © 2022 IEEE.

关键词： Tissue