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Mobile Model Predictive Control for the Évora irrigation test canal

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IFAC-PapersOnLine 2017年第1期50卷 6570-6575页

作者： López Rodríguez F. Horváth K. García Martín J. Maestre J.M. Department of Systems and Automation University of Seville Avenida de los descubrimientos s/n 41092 Seville Spain Department of Mechanical Engineering Eindhoven University of Technology Building Gemini Zuid Groene Loper Eindhoven MB 5600 United States Department of Systems and Automation University of Seville Department of Computer Science School of Computing Tokyo Institute of Technology Avenida de los Descubrimientos s/n 41092 4259-J2-54 Nagatsuta-cho Midori-ku Seville Yokohama 226-8502 Spain

Mobile Model Predictive control is a novel control technique for irrigation canals that optimizes the actions carried out by human operators. In this paper it is assessed preliminary by means of the numerical model of a reduced scale laboratory irrigation canal located in the facilities of the University of Évora (Portugal). Other control algorithms have also been tested by using a numerical model of the canal and compared with the novel control method: proportional integral control, linear quadratic regulator and centralized model predictive control. The results show that mobile model predictive control offers a performance comparable to that of fully automatic control despite being based exclusively on human operation. © 2017

关键词： automatic control control applications Predictive control

Pansharpening via detail injection based convolutional neural networks

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arXiv 2018年

作者： He, Lin Rao, Yizhou Li, Jun Plaza, Antonio Zhu, Jiawei School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation School of Geography and Planning Sun Yat-sen University Guangzhou510275 Hyperspectral Computing Laboratory Department of Technology of Computers and Communications Escuela Politécnica University of Extremadura CaceresE-10071

Pansharpening aims to fuse a multispectral (MS) image with an associated panchromatic (PAN) image, producing a composite image with the spectral resolution of the former and the spatial resolution of the latter. Traditional pansharpening methods can be ascribed to a unified detail injection context, which views the injected MS details as the integration of PAN details and band-wise injection gains. In this work, we design a detail injection based CNN (DiCNN) framework for pansharpening, with the MS details being directly formulated in end-to-end manners, where the first detail injection based CNN (DiCNN1) mines MS details through the PAN image and the MS image, and the second one (DiCNN2) utilizes only the PAN image. The main advantage of the proposed DiCNNs is that they provide explicit physical interpretations and can achieve fast convergence while achieving high pansharpening quality. Furthermore, the effectiveness of the proposed approaches is also analyzed from a relatively theoretical point of view. Our methods are evaluated via experiments on real-world MS image datasets, achieving excellent performance when compared to other state-of-the-art methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Neural networks

Sequential Solution Polymerization of Poly(3,4-Ethylenedioxythiophene) Using V2O5 as Oxidant for Flexible Touch Sensors

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SSRN

SSRN 2018年

作者： Chen, Rui Sun, Kuan Zhang, Qi Zhou, Yongli Li, Meng Sun, Yuyang Wu, Zhou Wu, Yuyang Li, Xinlu Xi, Jialei Ma, Chi Zhang, Yiyang Ouyang, Jianyong MOE Key Laboratory of Low-grade Energy Utilization Technologies and Systems School of Energy & Power Engineering Chongqing University Chongqing400044 China MOE Key Laboratory of Dependable Service Computing in Cyber Physical Society School of Automation Chongqing University Chongqing400044 China School of Materials Science and Engineering Chongqing University Chongqing400044 China Chengdu Mobius Technology Sichuan610015 China Department of Materials Science and Engineering National University of Singapore Singapore117574 Singapore

Various in-situ synthesis methods have been developed for the polymerization of 3,4-ethylenedioxythiophene (EDOT) monomers, such as electro-polymerization (EP), oxidative chemical vapor deposition (OCVD) and vapor phase polymerization (VPP). Additional to these existing techniques, here a novel and facile method is introduced to fabricate highly conductive poly(3,4-ethylenedioxythiophene) (PEDOT) films in-situ by solution means. The process contains sequential deposition of oxidants and monomers. V2O5 is introduced as the oxidant in this synthetic route. Excess reactants and by-products can be completely removed from the PEDOT film by MeOH-rinsing. The obtained PEDOT films possess good crystallinity and high doping level, with carrier concentration three orders of magnitude higher than the commercial product (PH1000, Heraeus GmbH). The electrical conductivity of the as-cast PEDOT film reaches up to 1420 S/cm. In addition, this method is fully compatible with large-scale printing techniques. A 15 cm × 12 cm PEDOT film is printed on polyethylene terephthalate (PET) substrate by bar coating. These PEDOT conducting films enable the realization of flexible touch sensors, which demonstrate superior flexibility and sensitivity. The low-cost and highly efficient synthetic method shows great potential for large-scale production of PEDOT films that have wide applications in electromagnetic shielding, antistatic coating, sensor, etc. © 2018, The Authors. All rights reserved.

关键词： Monomers

Design of an embedded control system based on the quasi-time optimal control law when limiting the control signal for the ball and beam system

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AIP Conference Proceedings 2019年第1期2188卷

作者： C. X. Nguyen H. N. Phan A. D. Lukianov T. D. Pham T. T. Nguyen H. T. Nguyen 1Department of Automation and Computing Techniques Le Quy Don Technical University Hanoi Vietnam 2Department of Software Engineering Le Quy Don Technical University Hanoi Vietnam 3Don State Technical University Rostov on Don Russia 4Department of Technology equipment and aerospace Le Quy Don Technical University Hanoi Vietnam

In the paper, it is presented about the design of the quasi-time optimal control law for Ball and Beam system when the control signal is limited. Impact signal limits are characteristic of real physical systems, so when designing embedded control systems this is an important factor to consider. In this design method, the transformation from the equations of object system to equations with limited control signals is made using extra variables. Proceed to synthesize the new control laws on the new system by the quasi-time optimal control. By the proposed synthesizing method, the control law ensures that the embedded control system works stably and the system works quickly in terms of time. Simulation and experimental results show the effectiveness of the proposed design.

关键词：

Study of tau neutrinos and non-unitary neutrino mixing with the first six detection units of KM3NeT/ORCA

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arXiv 2025年

作者： Aiello, S. Albert, A. Alhebsi, A.R. Alshamsi, M. Garre, S. Alves Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Aublin, J. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Gualandi, F. Benfenati Benhassi, M. Bennani, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Bouasla, A.B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J.A.B. Coyle, P. Creusot, A. Wasseige, G. De Decoene, V. Rosso, I. Del Mauro, L.S. Di Palma, I. Di Díaz, A.F. Diego-Tortosa, D. Distefano, C. Donzaud, C. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Duverne, P. Eberl, T. Eckerová, E. Eddymaoui, A. Eff, M. Bojaddaini, I. El Hedri, S. El Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gagliardini, S. Gal, T. Méndez, J. García Soto, A. Garcia Oliver, C. Gatius Geißelbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J.J. Idrissi, A. Ibnsalih, W. Idrissi Illuminati, G. Joly, D. de Jong, M. de Jong, P. Jung, B.J. Kalaczynski, P. Kikvadze, V. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y.Y. Krupa, L. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Lamoureux, M. Larosa, G. Lastoria, C. Lazar, J. Lazo, A. Le Stum, S. Lehaut, G. Lemaître, V. Leonora, E. Lessing, N. Levi, G. Clark, M. Lindsey Magnani, F. Majumdar, J. Malerba, L. Mamedov, F. Manfreda, A. Manousakis, A. Marconi, M. Margiotta, A. Marinelli, A. Markou, C. Martin, L. Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France Khalifa University of Science and Technology Department of Physics PO Box 127788 Abu Dhabi United Arab Emirates Aix Marseille Univ CNRS IN2P3 CPPM Marseille France c/Catedrático José Beltrán 2 Valencia Paterna46980 Spain INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain Subatech IMT Atlantique IN2P3-CNRS Nantes Université 4 rue Alfred Kastler - La Chantrerie BP Nantes20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France Università di Genova Via Dodecaneso 33 Genova16146 Italy INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna40127 Italy Università di Bologna Dipartimento di Fisica e Astronomia v.le C. Berti-Pichat 6/2 Bologna40127 Italy Università degli Studi della Campania"Luigi Vanvitelli" Dipartimento di Matematica e Fisica viale Lincoln 5 Caserta81100 Italy LPC Campus des Cézeaux 24 av

Oscillations of atmospheric muon and electron neutrinos produce tau neutrinos with energies in the GeV range, which can be observed by the ORCA detector of the KM3NeT neutrino telescope in the Mediterranean Sea. First measurements with ORCA6, an early subarray corresponding to about 5% of the final detector, are presented. A sample of 5828 neutrino candidates has been selected from the analysed exposure of 433 kton-years. The ντ normalisation, defined as the ratio between the number of observed and expected tau neutrino events, is measured to be Sτ = 0.48+0−0.335 . This translates into a ντ charged-current cross section measurement of στmeas = (2.5+2−1.68) × 10−38 cm2 nucleon−1 at the median ντ energy of 20.3 GeV. The result is consistent with the measurements of other experiments. In addition, the current limit on the non-unitarity parameter affecting the τ-row of the neutrino mixing matrix was improved, with α33 > 0.95 at the 95% confidence level. Copyright © 2025, The Authors. All rights reserved.

关键词： Neutrons

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the heichole benchmark

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arXiv 2021年

作者： Wagner, Martin Müller-Stich, Beat-Peter Kisilenko, Anna Tran, Duc Heger, Patrick Mündermann, Lars Lubotsky, David M. Müller, Benjamin Davitashvili, Tornike Capek, Manuela Reinke, Annika Yu, Tong Vardazaryan, Armine Innocent Nwoye, Chinedu Padoy, Nicolas Liu, Xinyang Lee, Eung-Joo Disch, Constantin Meine, Hans Xia, Tong Jia, Fucang Kondo, Satoshi Reiter, Wolfgang Jin, Yueming Long, Yonghao Jiang, Meirui Dou, Qi Heng, Pheng Ann Twick, Isabell Kirtac, Kadir Hosgor, Enes Bolmgren, Jon Lindström Stenzel, Michael von Siemens, Björn Kenngott, Hannes G. Nickel, Felix von Frankenberg, Moritz Mathis-Ullrich, Franziska Maier-Hein, Lena Speidel, Stefanie Bodenstedt, Sebastian Department for General Visceral and Transplantation Surgery Heidelberg University Hospital Im Neuenheimer Feld 420 Heidelberg69120 Germany Heidelberg Im Neuenheimer Feld 460 Heidelberg69120 Germany Data Assisted Solutions Corporate Research & Technology KARL STORZ SE & Co. KG Dr. Karl-Storz-Str. 34 Tuttlingen78332 Germany Im Neuenheimer Feld 223 Heidelberg69120 Germany Im Neuenheimer Feld 223 Heidelberg69120 Germany Faculty of Mathematics and Computer Science Heidelberg University Im Neuenheimer Feld 205 Heidelberg69120 Germany ICube University of Strasbourg CNRS France 300 bd Sébastien Brant - CS 10413 Illkirch CedexF-67412 France IHU Strasbourg France 1 Place de l'hôpital Strasbourg67000 France Sheikh Zayed Institute for Pediatric Surgical Innovation Children's National Hospital 111 Michigan Ave NW WashingtonDC20010 United States University of Maryland College Park 2405 A V Williams Building College ParkMD20742 United States Fraunhofer Institute for Digital Medicine MEVIS Max-von-Laue-Str. 2 Bremen28359 Germany University of Bremen FB3 Medical Image Computing Group ℅ Fraunhofer MEVIS Am Fallturm 1 Bremen28359 Germany Lab for Medical Imaging and Digital Surgery Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Konika Minolta Inc. JP TOWER 2-7-2 Marunouchi Chiyoda-ku Tokyo100-7015 Japan Wintegral GmbH Ehrenbreitsteiner Str. 36 München80993 Germany Department of Computer Science and Engineering Ho Sin-Hang Engineering Building The Chinese University of Hong Kong Sha Tin NT Hong Kong Caresyntax GmbH Komturstr. 18A Berlin12099 Germany Department of Surgery Salem Hospital of the Evangelische Stadtmission Heidelberg Zeppelinstrasse 11-33 Heidelberg69121 Germany Health Robotics and Automation Laboratory Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Geb. 40.28 KIT Campus Süd Engler-Bunte-Ring 8 Karlsruhe76131 Germany Medical Faculty Heidelberg Uni

PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the operation through context-sensitive warnings and semi-autonomous robotic assistance or improve training of surgeons via data-driven feedback. In surgical workflow analysis up to 91% average precision has been reported for phase recognition on an open data single-center video dataset. In this work we investigated the generalizability of phase recognition algorithms in a multi-center setting including more difficult recognition tasks such as surgical action and surgical skill. METHODS: To achieve this goal, a dataset with 33 laparoscopic cholecystectomy videos from three surgical centers with a total operation time of 22 hours was created. Labels included framewise annotation of seven surgical phases with 250 phase transitions, 5514 occurences of four surgical actions, 6980 occurences of 21 surgical instruments from seven instrument categories and 495 skill classifications in five skill dimensions. The dataset was used in the 2019 international Endoscopic Vision challenge, sub-challenge for surgical workflow and skill analysis. Here, 12 research teams trained and submitted their machine learning algorithms for recognition of phase, action, instrument and/or skill assessment. RESULTS: F1-scores were achieved for phase recognition between 23.9% and 67.7% (n=9 teams), for instrument presence detection between 38.5% and 63.8% (n=8 teams), but for action recognition only between 21.8% and 23.3% (n=5 teams). The average absolute error for skill assessment was 0.78 (n=1 team). CONCLUSION: Surgical workflow and skill analysis are promising technologies to support the surgical team, but are not solved yet, as shown by our comparison of machine learning algorithms. This novel HeiChole benchmark can be used for comparable evaluation and validation of future work. In future studies, it is of utmost impo

关键词： Learning algorithms

Quantum key distribution with distinguishable decoy states

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Physical Review A 2018年第1期98卷 012330-012330页

作者： Anqi Huang Shi-Hai Sun Zhihong Liu Vadim Makarov Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 People's Republic of China Institute for Quantum Computing University of Waterloo Waterloo Ontario N2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo Ontario N2L 3G1 Canada College of Science National University of Defense Technology Changsha 410073 People's Republic of China College of Mechatronic Engineering and Automation National University of Defense Technology Changsha 410073 People's Republic of China Russian Quantum Center and MISIS University Moscow Department of Physics and Astronomy University of Waterloo Waterloo Ontario N2L 3G1 Canada

The decoy-state protocol has been considered to be one of the most important methods to protect the security of quantum key distribution (QKD) with a weak coherent source. Here we test two experimental approaches to generating the decoy states with different intensities: modulation of the pump current of a semiconductor laser diode, and external modulation by an optical intensity modulator. The former approach shows a side channel in the time domain that allows an attacker to distinguish s signal state from a decoy state, breaking a basic assumption in the protocol. We model a photon-number-splitting attack based on our experimental data, and show that it compromises the system's security. Then, based on the work of Tamaki et al. [New J. Phys. 18, 065008 (2016)], we obtain two analytical formulas to estimate the yield and error rate of single-photon pulses when the signal and decoy states are distinguishable. The distinguishability reduces the secure key rate below that of a perfect decoy-state protocol. To mitigate this reduction, we propose to calibrate the transmittance of the receiver (Bob's) unit. We apply our method to three QKD systems and estimate their secure key rates.

关键词： Quantum communication Quantum cryptography

Influence of gama prime changes on the heat transport phenomena of a nickel super alloy

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Defect and Diffusion Forum 2017年 379卷 1-11页

作者： Koštial, Pavel Jonšta, Petr Kopal, Ivan Jančíková, Zora Koštialová Špička, Ivo Kulová, Tatána Vlčková, Irena Department of Material Engineering Faculty of Metallurgy and Materials Engineering VŠB-Technical University of Ostrava Czech Republic Faculty of Mining and Geology VŠB Institute of Physics Technical University of Ostrava Czech Republic VÍtkovice Heavy Machinery a.s. Czech Republic Department of Automation and Computing in Metallurgy Faculty of Metallurgy and Materials Engineering VŠB-Technical University of Ostrava Czech Republic Faculty of Industrial Technologies in Puchov University of Alexander Dubček in Trenčín Slovakia RMTSC MATERIAL METALLURGICAL RESEARCH Ltd. Remote site Ostrava VÚHŽ a.s. Czech Republic

The paper deals with the influence of microstructural changes of the nickel superalloy (NiS) on heat transport changes in MAR-M247. The dissolving annealing within the temperature interval of 900 - 1240°C and cooling in water has been applied to enhance structural changes. It has been shown that the narrow connection between the γ' phase morphology changes, as well as values of density, thermal conductivity and specific heat capacity. In the dissolving annealing process, the γ' particles change in certain cycles from fine to rough and back to fine one. Obtained results of changes of thermal conductivity, density and specific heat capacity correlate with image analysis and electron microscopy observation. © 2017 Trans Tech Publications, Switzerland.

关键词： Thermal conductivity

Memory attention networks for skeleton-based action recognition

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arXiv 2018年

作者： Xie, Chunyu Li, Ce Zhang, Baochang Chen, Chen Han, Jungong Zou, Changqing Liu, Jianzhuang School of Automation Science and Electrical Engineering Beihang University Beijing China Department of Computer Science and Technology China University of Mining & Technology Beijing China Department of Electrical and Computer Engineering University of North Carolina at Charlotte School of Computing & Communications Lancaster University LA1 4YW United Kingdom University of Maryland Institute for Advanced Computer Studies College ParkMD20742 United States Noah's Ark Lab Huawei Technologies Co. Ltd. China

Skeleton-based action recognition task is entangled with complex spatio-temporal variations of skeleton joints, and remains challenging for Recurrent Neural Networks (RNNs). In this work, we propose a temporal-then-spatial recalibration scheme to alleviate such complex variations, resulting in an end-to-end Memory Attention Networks (MANs) which consist of a Temporal Attention Recalibration Module (TARM) and a Spatio-Temporal Convolution Module (STCM). Specifically, the TARM is deployed in a residual learning module that employs a novel attention learning network to recalibrate the temporal attention of frames in a skeleton sequence. The STCM treats the attention calibrated skeleton joint sequences as images and leverages the Convolution Neural Networks (CNNs) to further model the spatial and temporal information of skeleton data. These two modules (TARM and STCM) seamlessly form a single network architecture that can be trained in an end-to-end fashion. MANs significantly boost the performance of skeleton-based action recognition and achieve the best results on four challenging benchmark datasets: NTU RGB+D, HDM05, SYSU-3D and UT-Kinect. Copyright © 2018, The Authors. All rights reserved.

关键词： Convolution