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Prospects for the use of wireless reading of prosthetic control signals and methods for generating commands

IOP Conference Series: Materials Science and engineering 2021年第1期1019卷

作者： D Malakhov V Zhmud V Avrmachuk D Gryaznov J Nosek L Dimitrov Department of Automation Novosibirsk State Technical University Novosibirsk Russia Department of Complex Information Security of Computer Systems Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Department of Mechatronics and Computer Engineering (MTI) Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Liberec Czech Republic Vice rector Technical University of Sofia Sofia Bulgaria

The paper provides a rationale for the use of low-power wireless communication to create non-invasive bionic limb prostheses. The need for such a connection is dictated, on the one hand, by the expediency of using sensors located in various parts of the body, often very remote from each other, on the other hand, by the desire to free the disabled person's body from the wires that would envelop it like a spider web. For each of these positions, arguments are given.

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Prospects for the development of functional expansion of individual low-cost prosthetic limbs for people with disabilities with intelligent sensors

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IOP Conference Series: Materials Science and engineering 2021年第1期1019卷

作者： D Gryaznov V Zhmud V Avrmachuk D Malakhov J Nosek L Dimitrov Department of Automation Novosibirsk State Technical University Novosibirsk Russia Department of Complex Information Security of Computer Systems Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Department of Mechatronics and Computer Engineering (MTI) Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Liberec Czech Republic Vice rector of Technical University of Sofia Sofia Bulgaria

Despite the development of medicine, as well as robotics aimed at helping people with disabilities, most disabled people with missing limbs cannot hope for a full life with the help of bionic prostheses, since these products are made strictly individually, and their control requires expensive surgeries to implant sensors. In addition, such prostheses themselves are very expensive. An alternative solution is to reduce the cost of such prostheses as much as possible and abandon the implantable sensors of signals of the human nervous system. The paper proposes a method for solving such a problem using a variety of sensors that remove signals from the skin surface without invasive surgery.

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A bibliometric analysis of the uses of the cocoa pod shell

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IOP Conference Series: Materials Science and engineering 2021年第1期1154卷

作者： A D Rincón-Quintero L A Del Portillo-Valdés C G Cárdenas-Arias B E Tarazona-Romero W L Rondón-Romero M A Durán-Sarmiento Design and materials research group (DIMAT) Automation and Control Energy Systems Research Group (GISEAC) Electromechanical engineering Faculty of Natural Sciences and Engineering Technological Units of Santander (UTS) Calle de los estudiantes No 9-82 680005 Bucaramanga Colombia Energy in Building research group (ENEDI) Doctoral Program in Energy Efficiency and Sustainability in Engineering and Architecture Department of Machines and Thermal Engines University of the Basque Country UPV/EHU Engineer Torres Quevedo Plaza 1 48013 Bilbao Spain Doctoral Program in Electronic and Communications Department of Communications Engineering University of the Basque Country UPV/EHU 48013 Bilbao Spain Doctoral Program in Engineering of Materials and Sustainable Processes University of the Basque Country UPV/EHU 48013 Bilbao Spain

The research explores the use of cocoa pod shell (CPS) in rural areas and accessible to the cocoa farmer, applying VOSviewer software. The results show that the production of ethanol or biochar with CPS is not feasible, the first due to its low sugar content and the second, due to the requirement of processes with high temperatures for the extraction of different chemical compounds (i.e activated carbon). On the other hand, obtaining pellets represents a viable energy potential, since the calorific value is competitive with other biomass; Also, through anaerobic digestion under the ideal conditions, it can generate 55% in biogas of the solid matter used. Additionally, the ashes produced in direct combustion or pellets rep-resent an excellent catalyst, which can be used in transesterification, for the generation of biodiesel, used with other residual oils, giving a plus in the efficient use of resources.

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New Grid for Particle Filtering of Multivariable Nonlinear Objects

New Grid for Particle Filtering of Multivariable Nonlinear O...

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Federated Conference on Computer Science and Information Systems

作者： Piotr Kozierski Jacek Michalski Talar Sadalla Wojciech Giernacki Joanna Zietkiewicz Szymon Drgas Faculty of Computing Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan University of Technology Faculty of Electrical Engineering Institute of Control Robotics and Information Engineering Division of Control and Robotics Poznan University of Technology

ISBN: (纸本)9781538623718

In the paper a new grid (potentially linear, nonlinear and even semi-Markovian jump system) was presented. All transition and measurement functions were proposed. Moreover, the transition functions of two types were considered - dependent on one and many different state variables. Also 10 types of measurements were proposed for both nodal and branch cases. Based on the obtained results one can see, which measurement functions are "easy", and which are "hard" for state estimation task.

关键词： Measuring Function Particle filters grids Grid State variable Multivariable nonlinearity

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Sparse Least Square Support Vector Machines based on Random Entropy 36

Sparse Least Square Support Vector Machines based on Random ...

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第36届中国控制会议

作者： Wenlu Ma Han Liu Faculty of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Lab. of Complex System Control and Intelligent Information Processing Faculty of Automation and Information EngineeringXi’an University of Technology

ISBN: (纸本)9781538629185

Least squares support vector machines(LSSVM) has a good performance in small data samples, but can't solve the large-scale sample problems. In this paper, large data set sparse least squares support vector machines model based on stochastic entropy is proposed, and it can be applied to large-scale data samples. Firstly, the large-scale data set is divided into several subsets. Then the entropy method is used to the sparse samples in each subset. Finally, we use sparse samples sets as training samples, and use least squares support vector machine algorithm to train. The results show that the sparse least squares support vector machine model based on entropy can effectively solve the problem of large-scale data.

关键词： Sparsity LSSVM Large-scale data Random Entropy

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Study on an Adaptive Algorithm for Time-varying System 36

Study on an Adaptive Algorithm for Time-varying System

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第36届中国控制会议

作者： KIM KwangHo GENG Yanfeng Yue Yaobin College of Information & Control Engineering China University of Petroleum(East China) Automation Engineering Faculty Kimchaek University of TechnologyCAS College of Automation & Electronic Engineering Qingdao University of Science & Technology

ISBN: (数字)9789881563934

ISBN: (纸本)9781538629185

In this paper,we presented the derivation of an adaptive algorithm for time-varying system and verified that it satisfied convergence *** on the concept of distance in parameter space,we proposed a robust identification method which identified the smallest set of discrete transfer functions under the assumption that its parameters were time-varying and described derivation of an adaptive law based on verification and update algorithm of the identified model *** also described that the proposed algorithm satisfied the convergence properties through numerical simulation.

关键词： adaptive algorithm time-varying system parameter estimation robust identification

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A consensus protocol for functional connectivity analysis in the rat brain (vol 26, pg 673, 2023)

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NATURE NEUROSCIENCE 2023年第6期26卷 1127-1128页

作者： Grandjean, Joanes Desrosiers-Gregoire, Gabriel Anckaerts, Cynthia Angeles-Valdez, Diego Ayad, Fadi Barriere, David A. Blockx, Ines Bortel, Aleksandra Broadwater, Margaret Cardoso, Beatriz M. Celestine, Marina Chavez-Negrete, Jorge E. Choi, Sangcheon Christiaen, Emma Clavijo, Perrin Colon-Perez, Luis Cramer, Samuel Daniele, Tolomeo Dempsey, Elaine Diao, Yujian Doelemeyer, Arno Dopfel, David Dvorakova, Lenka Falfan-Melgoza, Claudia Fernandes, Francisca F. Fowler, Caitlin F. Fuentes-Ibanez, Antonio Garin, Clement M. Gelderman, Eveline Golden, Carla E. M. Guo, Chao C. G. Henckens, Marloes J. A. G. Hennessy, Lauren A. Herman, Peter Hofwijks, Nita Horien, Corey Ionescu, Tudor M. Jones, Jolyon Kaesser, Johannes Kim, Eugene Lambers, Henriette Lazari, Alberto Lee, Sung-Ho Lillywhite, Amanda Liu, Yikang Liu, Yanyan Y. Lopez-Castro, Alejandra Lopez-Gil, Xavier Ma, Zilu MacNicol, Eilidh Madularu, Dan Mandino, Francesca Marciano, Sabina McAuslan, Matthew J. McCunn, Patrick McIntosh, Alison Meng, Xianzong Meyer-Baese, Lisa Missault, Stephan Moro, Federico Naessens, Daphne M. P. Nava-Gomez, Laura J. Nonaka, Hiroi Ortiz, Juan J. Paasonen, Jaakko Peeters, Lore M. Pereira, Mickael Perez, Pablo D. Pompilus, Marjory Prior, Malcolm Rakhmatullin, Rustam Reimann, Henning M. Reinwald, Jonathan Del Rio, Rodrigo Triana Rivera-Olvera, Alejandro Ruiz-Perez, Daniel Russo, Gabriele Rutten, Tobias J. Ryoke, Rie Sack, Markus Salvan, Piergiorgio Sanganahalli, Basavaraju G. Schroeter, Aileen Seewoo, Bhedita J. Selingue, Erwan Seuwen, Aline Shi, Bowen Sirmpilatze, Nikoloz Smith, Joanna A. B. Smith, Corrie Sobczak, Filip Stenroos, Petteri J. Straathof, Milou Strobelt, Sandra Sumiyoshi, Akira Takahashi, Kengo Torres-Garcia, Maria E. Tudela, Raul van den Berg, Monica van der Marel, Kajo van Hout, Aran T. B. Vertullo, Roberta Vidal, Benjamin Vrooman, Roel M. Wang, Victora X. Wank, Isabel Watson, David J. G. Yin, Ting Zhang, Yongzhi Zurbruegg, Stefan Achard, Sophie Alcauter, Sarael Auer, Dorothee P. Barbier, Emmanuel L. Baudewig, Juergen Beckmann, Chri Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada Integrated Program in Neuroscience McGill University Montreal QC Canada Bio-imaging Lab University of Antwerp Antwerp Belgium µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico Biological and Biomedical Engineering McGill University Montreal QC Canada McConnell Brain Imaging Centre McGill University Montreal QC Canada Montreal Neurological Institute McGill University Montreal QC Canada UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France Department of Neurology and Neurosurgery McGill University Montreal QC Canada Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l’Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cybernetics Tuebingen Germany Graduate Training Centre of Neuroscience International Max

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.

关键词： Databases Neural circuits

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Soft-Sensing Estimation of Optical Density for PHA Production Using Multilayer Perceptron Neural Network

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Journal of Physics: Conference Series 2020年第1期1532卷

作者： Nor Hana Mamat Samsul Bahari Mohd Noor Azura Che Soh Farah Saleena Taip Ahmad Hazri Ab. Rashid Nur Liyana Jufika Ahmad Ishak Mohd Yusof Adida Zuraida Mohamad Control System and Signal Processing Research Centre Department of Electrical & Electronic Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor. Faculty of Electrical and Automation Engineering Technology TATI University College Teluk Kalong 24000 Kemaman Terengganu. Food and Process Department Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor. Industrial Biotechnology Research Centre SIRIM Berhad Persiaran Dato' Menteri Seksyen 2 40700 Shah Alam Selangor.

Biomass concentration is an important indicator of production rate in polyhydroxyalkanoates (PHA) fermentation process. In current practice, measurement of biomass concentration is done off-line by laboratory analysis that is unsuitable for online process monitoring and control. Soft-sensor is often used as an alternative that provides an estimate of hard to measure parameters from easy to measure process data. However, most of these studies use simulated data or data generated from mathematical model that was developed without full consideration of process and measurement uncertainty. In this study, a soft-sensor is developed from real production data for PHA fermentation in pilot-scale bioreactor with the appropriate data pre-processing techniques applied to process data that was obtained from this system. Multilayer perceptron (MLP) neural network is used to estimate biomass concentration using secondary process parameters such as dissolved oxygen (DO), temperature, pH and agitation speed as inputs. Different models are developed based on different batches of production data and various network architecture in order to study the appropriate integration of process data and network topology that gives the best model accuracy. Results indicate that the biomass soft-sensor developed using MLP-ANN provides a better estimate of biomass in comparison to radial basis function (RBF) neural network and support vector regression (SVR) methods. The developed soft-sensor can be further used in monitoring and control of production output.

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Modelling and Hierarchical control of CBTC

Modelling and Hierarchical Control of CBTC

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International Conference on control, engineering & Information Technology (CEIT)

作者： Cem ATILGAN Özgür Turay KAYMAKÇI Technology Faculty Mechatronics Engineering Kırklareli University Kırklareli TURKEY Faculty of Electric Electronic Control and Automation Engineering Yıldız Technical University Istanbul TURKEY

ISBN: (纸本)9781538676424

Over the last decade, the railway industry has a great evolution about signaling system and there is more orientation from the standard railway signaling system to the communicationbased signaling system day to day. Communications-based train control (CBTC) is a very flexible and useful approach to check train activity and track operation. This system basically build upon radio communication to transfer in time and correct train control information. In this paper, we focus on model the all necessary CBTC elements with finite state automata and build CBTC control architecture with decentralized DES and support the existing control architecture with a three-level hierarchy. For the overall system, we show hierarchical consistency and that the closed-loop behavior is non-blocking. This paper gives an overview of the modelling a discrete event system about CBTC and gives control of CBTC.

关键词： Automata Supervisory control Computer architecture Decentralized control Discrete-event systems control engineering

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Short term electric load forecast with artificial neural networks

arXiv

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arXiv 2018年

作者： Cristian, Vasar Iosif, Szeidert Ioan, Filip Gabriela, Prostean Department of Control System Engineering Politehnica' University from Timisoara Faculty of Automation and Computer Science Timisoara300223 Romania

This paper presents issues regarding short term electric load forecasting using feedforward and Elman recurrent neural networks. The study cases were developed using measured data representing electrical energy consume from Banat area. There were considered 35 different types of structure for both feedforward and recurrent network cases. For each type of neural network structure were performed many trainings and best solution was selected. The issue of forecasting the load on short term is essential in the effective energetic consume management in an open market environment. Copyright © 2007 IFAC Copyright © 2018, The Authors. All rights reserved.

关键词： Electric load forecasting

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