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Gesture interpretation control system using convolutional neural networks

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Gesture interpretation control system using convolutional ne...

2019 International Conference on Biomedical Innovations and Applications, BIA 2019

作者： Baldursson, Benedikt Rasti, Behnood Gudmundsson, Karl Cojocaru, Dorian Andersen, Kristinn Thorsteinsson, Saemundur E. University of Iceland Faculty of Electrical and Computer Engineering Hafnarfjordur Iceland University of Craiova Faculty of Automation Computers and Electronics Craiova Romania

ISBN: (纸本)9781728147543

This paper proposes a non-invasive control system for electrical wheelchairs utilizing facial gestures of individuals captured by real-Time monocular camera. The images are interpreted with a convolutional neural network that achieves up to ~99.5% overall accuracy. The control system uses an embedded system with a graphics processing unit for predicting real-Time throughput with fast inference time. This solution offers great versatility, where the user can make a gesture to depict a command of his choice. © 2019 IEEE.

关键词： Control systems

DECOMPOSITION OF INDUSTRIAL SYSTEMS FOR ENERGY EFFICIENCY OPTIMIZATION WITH OPTTOPO

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arXiv 2022年

作者： Thiele, Gregor Johanni, Theresa Sommer, David Krüger, Jörg Department for Process Automation and Robotics Fraunhofer Institute for Production Systems and Design Technology IPK Germany Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany Weierstrass Institute for Applied Analysis and Stochastics Berlin Germany Institute for Machine Tools and Factory Management Technical University of Berlin Berlin Germany

The operation of industrial facilities is a broad field for optimization. Industrial plants are often a) composed of several components, b) linked using network technology, c) physically interconnected and d) complex regarding the effect of set-points and operating points in every entity. This leads to the possibility of overall optimization but also to a high complexity of the emerging optimization problems. The decomposition of complex systems allows the modeling of individual models which can be structured according to the physical topology. A method for energy performance indicators (EnPI) helps to formulate an optimization problem. The optimization algorithm OptTopo achieves efficient set-points by traversing a graph representation of the overall system. © 2022, CC BY.

关键词： Optimization

A Top-Down Deep Learning Model for Predicting Spatiotemporal Dynamics of Groundwater Recharge

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SSRN

SSRN 2023年

作者： Gao, Lei Huang, Xin Zhang, Nan Crosbie, Russell S. Ye, Long Liu, Jian Guo, Zhaoxia Meng, Qinghua Fu, Guobin Bryan, Brett A. College of Computer and Information Engineering Tianjin Normal University Tianjin300387 China Waite Campus UrrbraeSA5064 Australia Faculty of Education Tianjin Normal University Tianjin300387 China School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China Faculty of Business Information Shanghai Business School Shanghai201400 China HeFei University of Technology Hefei230009 China Business School Sichuan University Chengdu610065 China Private Bag 5 WembleyWA6913 Australia Centre for Integrative Ecology Deakin University Melbourne Burwood Campus BurwoodVIC3125 Australia

Efficient models are needed to portray the spatiotemporal dynamics of groundwater recharge, which is difficult to measure directly. This paper proposes a top-down deep learning model called s-LSTM for modelling and predicting the spatiotemporal dynamics of groundwater recharge. The effectiveness of the proposed model was evaluated and compared with three bottom-up machine learning models using a case study of 246 bores in South *** results demonstrate that s-LSTM outperformed the three bottom-up models in terms of prediction performance, generalization/interpolation ability, training time, and the ability of identifying influential factors to recharge prediction at the regional scale. Groundwater extraction, mean number of wet days per year, seasonal minimum temperature, seasonal rainfall, and seasonal actual evaporation were identified by s-LSTM as the top five influential factors for the prediction of groundwater recharge in the study region. Practitioners are encouraged to consider s-LSTM when dealing with spatiotemporal data modelling and prediction problems. © 2023, The Authors. All rights reserved.

关键词： Forecasting

MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability

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Genomics, Proteomics & Bioinformatics 2020年第1期18卷 65-71页

作者： Peng Jia Xiaofei Yang Li Guo Bowen Liu Jiadong Lin Hao Liang Jianyong Sun Chengsheng Zhang Kai Ye School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China MOE Key Laboratory for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Life Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Leiden Institute of Advanced Computer Science Leiden UniversityLeiden 2311 ZENetherlands School of Mathematics and Statistics Xi’an Jiaotong UniversityXi’an 710049China Precision Medicine Center the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China Jackson Laboratory for Genomic Medicine FarmingtonCT 06032USA Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China

Microsatellite instability(MSI)is a key biomarker for cancer therapy and *** experimental assays are laborious and time-consuming,and next-generation sequencingbased computational methods do not work on leukemia samples,paraffin-embedded samples,or patient-derived xenografts/organoids,due to the requirement of matched normal ***,we developed MSIsensor-pro,an open-source single sample MSI scoring method for research and clinical ***-pro introduces a multinomial distribution model to quantify polymerase slippages for each tumor sample and a discriminative site selection method to enable MSI detection without matched normal *** demonstrate that MSIsensor-pro is an ultrafast,accurate,and robust MSI calling *** samples with various sequencing depths and tumor purities,MSIsensor-pro significantly outperformed the current leading methods in both accuracy and computational ***-pro is available at https://***/xjtu-omics/msisensor-pro and free for non-commercial use,while a commercial license is provided upon request.

关键词： Microsatellite Polymerase slippage Multinomial distribution Microsatellite instability Tumor

Influence of electric field orientation on the effect of ocular current stimulation using full field electroretinogram

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Current Directions in Biomedical engineering 2021年第2期7卷

作者： Blum, Maren-Christina Leydolph, Lilly Klee, Sascha Institute of Biomedical Engineering and Informatics Faculty of Computer Sciences and Automation Technische Universität Ilmenau Ilmenau Germany Department of General Health Studies Division Biostatistics and Data Science Karl Landsteiner University of Health Sciences Krems an der Donau Austria

Ocular current stimulation (CS) exhibits potential for the treatment of neurodegenerative ocular diseases. For a full field electroretinogram (ffERG) we found no CS effect on the characteristic waves (a-wave, b'-wave, and b-wave). To investigate whether the orientation of the generated electric field has an influence on the CS effect, this study repeated the previous ffERG study with changing one CS electrode position and compared the results of both studies. In the first study 15 (8 m, 27.5 ± 4.5 years) and in the second study 17 (7 m, 22.0 ± 1.9 years) healthy volunteers were stimulated with an anodal, cathodal, and sham direct CS of 800 μA for 5 min in three sessions (randomized, different days). For both studies, a cut-sized ring rubber electrode was placed around the eye. A square rubber electrode was placed for the first study at the ipsilateral temple and for the second study at the visual cortex. Before (ERG 1) and during (ERG 2) the CS, the ffERG was measured. For both studies, the difference between the ERG 1 and ERG 2 measurement (CS effect) for the three characteristic waves was analyzed and compared between the studies. For statistical analysis, the Mann-Whitney U test with Bonferroni correction was applied (α = 0.05). The comparison of the data distribution showed only slight differences between the studies. The Mann-Whitney U test found no significant difference of the CS effect between the studies for all amplitudes and CS groups (p ≥ 0.0055). In the mean, the latency differences were smaller than the time resolution, therefore no statements for latency effects were possible. It can be concluded that the retinal cells generating the ffERG are not affected by ocular CS in either electrode montages tested. © 2021 by Walter de Gruyter Berlin/Boston.

关键词： Rubber

Learning Dictionaries from Physical-Based Interpolation for Water Network Leak Localization

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arXiv 2023年

作者： Irofti, Paul Romero-Ben, Luis Stoican, Florin Puig, Vicenç Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest 010014 Romania The Institute for Logic and Data Science Popa Tatu 18 Bucharest010805 Romania The Institut de Robòtica i Informàtica Industrial CSIC-UPC Llorens i Artigas 4-6 Barcelona08028 Spain The Universitat Politècnica de Catalunya Campus de Terrassa Gaia Building Rambla Sant Nebridi 22 Terrassa Barcelona08222 Spain The Deptartment of Automation Control and Systems Engineering Politehnica University of Bucharest 060042 Romania

This article presents a leak localization methodology based on state estimation and learning. The first is handled by an interpolation scheme, whereas dictionary learning is considered for the second stage. The novel proposed interpolation technique exploits the physics of the interconnections between hydraulic heads of neighboring nodes in water distribution networks. Additionally, residuals are directly interpolated instead of hydraulic head values. The results of applying the proposed method to a well-known case study (Modena) demonstrated the improvements of the new interpolation method with respect to a state-of-the-art approach, both in terms of interpolation error (considering state and residual estimation) and posterior localization. Copyright © 2023, The Authors. All rights reserved.

关键词： Interpolation

Label Cluster Chains for Multi-Label Classification

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arXiv 2024年

作者： Gatto, Elaine Cecília Nakano, Felipe Kenji Read, Jesse Ferrandin, Mauri Cerri, Ricardo Vens, Celine Department of Computer Science Federal University of São Carlos SP São Carlos13565-905 Brazil Faculty of Medicine Katholieke Universiteit Leuven West Flanders Kortrijk8500 Belgium École Polytechnique Polytechnic Institute of Paris Palaiseau Paris91120 France Department of Control Automation and Computing Engineering Federal University of Santa Catarina SC Blumenau89036-002 Brazil Institute of Mathematical and Computing Sciences University of São Paulo SP São Carlos13566-590 Brazil

Multi-label classification is a type of supervised machine learning that can simultaneously assign multiple labels to an instance. To solve this task, some methods divide the original problem into several sub-problems (local approach), others learn all labels at once (global approach), and others combine several classifiers (ensemble approach). Regardless of the approach used, exploring and learning label correlations is important to improve the classifier predictions. Ensemble of Classifier Chains (ECC) is a well-known multi-label method that considers label correlations and can achieve good overall performance on several multi-label datasets and evaluation measures. However, one of the challenges when working with ECC is the high dimensionality of the label space, which can impose limitations for fully-cascaded chains as the complexity increases regarding feature space expansion. To improve classifier chains, we propose a method to chain disjoint correlated label clusters obtained by applying a partition method in the label space. During the training phase, the ground truth labels of each cluster are used as new features for all of the following clusters. During the test phase, the predicted labels of clusters are used as new features for all the following clusters. Our proposal, called Label Cluster Chains for Multi-Label Classification (LCC-ML), uses multi-label Random Forests as base classifiers in each cluster, combining their predictions to obtain a final multi-label classification. Our proposal obtained better results compared to the original ECC. This shows that learning and chaining disjoint correlated label clusters can better explore and learn label correlations. © 2024, CC BY.

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Data-Driven Distributed Algorithms for Estimating Eigenvalues and Eigenvectors of Interconnected Dynamical Systems

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IFAC-PapersOnLine 2020年第2期53卷 52-57页

作者： Azwirman Gusrialdi Zhihua Qu Automation Technology and Mechanical Engineering Unit Faculty of Engineering and Natural Sciences Tampere University Tampere 33014 Finland Department of Electrical and Computer Engineering University of Central Florida Orlando 32816 USA

The paper presents data-driven algorithms to estimate in a distributed manner the eigenvalues, right and left eigenvectors of an unknown linear (or linearized) interconnected dynamic system. In particular, the proposed algorithms do not require the identification of the system model in advance before performing the estimation. As a first step, we consider interconnected dynamical system with distinct eigenvalues. The proposed strategy first estimates the eigenvalues using the well-known Prony method. The right and left eigenvectors are then estimated by solving distributively a set of linear equations. One important feature of the proposed algorithms is that the topology of communication network used to perform the distributed estimation can be chosen arbitrarily, given that it is connected, and is also independent of the structure or sparsity of the system (state) matrix. The proposed distributed algorithms are demonstrated via a numerical example.

关键词： distributed estimation data-driven algorithm eigenvalues eigenvectors

Optical super-resonances in dielectric microsphere particles

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arXiv 2022年

作者： Wang, Zengbo Luk’yanchuk, Boris Wu, Baidong Yan, Bing Assel, Ahmetova Yaminsky, Igor Yu, Haibo Liu, Lianqing School of Computer Science and Electronic Engineering Bangor University Dean Street Gwynedd BangorLL57 1UT United Kingdom Faculty of Physics Lomonosov Moscow State University Moscow119991 Russia State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

Extreme field localization and giant field enhancement are often achieved by using plasmonic nanostructures and metamaterials such as strongly coupled silver nanoparticles. Dielectric particles and structures can focus light beyond the diffraction limit (photonic nanojet effect), but with much weaker strengths. Recently, we showed that dielectric microspheres could support high-order Mie resonance modes (‘super-resonance modes’), that can generate similar level of electric field intensity enhancement as plasmonic structures on the order of 104- 107. In this work, we aim to further advance our understanding of the super-resonance modes. New results on the effects of size parameter and refractive index on optical super-resonances across a wide parameter range and with improved numerical accuracies is presented. The results suggest that the electric field intensity enhancement could reach a record high level of 109-1011 at specific conditions that surpass plasmonic enhancements. Moreover, super-resonance-enabled focusing by microsphere lens under different lighting sources (e.g., different color LEDs or lasers, halogen lamps) is investigated and compared for the first time. These results are important in understanding the super-resolution mechanism for microsphere nanoscopy and will find numerous potential applications in photonics. © 2022, CC BY.

关键词： Microspheres