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A new method for accurate detection of movement intention from single channel EEG for online BCI

Computer Methods and programs in Biomedicine Update 2021年 1卷

作者： Mahmoodi, Maryam Makkiabadi, Bahador Mahmoudi, Mehran Sanei, Saeid Department of Medical Physics and Biomedical Engineering School of Medicine Tehran University of Medical Sciences (TUMS) Tehran Iran Research Center for Biomedical Technology and Robotics (RCBTR) of Advanced Medical Technologies and Equipment Institute (AMTEI) Tehran University of Medical Sciences Tehran Iran Department of Mechanical Engineering University of Tehran Tehran Iran School of Science and Technology Nottingham Trent University Nottingham United Kingdom

Low frequency readiness potential (RP) is elicited in electroencephalograms (EEGs) as one intends to perform an imagery (IMI) or real movement (RMI). While in most brain-computer-interface (BCI) applications the challenge is to classify RPs of different limbs from the given EEG trials, the objective of this study is fast and automatic detection of RPs from the entire single channel EEG signal. The proposed algorithm has two threshold blocks based on the nonlinear Teager-Kaiser energy operator (TEO) in the first block and the morphological properties of the RP waveform as constraints in the second block. The performance is strongly influenced by the abrupt energy changes due to transients and artefacts. As the major contribution, the proposed nonlinear convex optimization algorithm enables separation of transients from low frequency components by providing a fast thresholding mechanism. Application of the proposed method to Physionet RMI dataset, BCI competitionIV-1 IMI dataset and our own left hand movement datasets of healthy subjects led to true positive rates (TPRs) of 76.5±8.27%, 83.85±11.4%, and 81.1±5.23%, number of FPs/min of 2.4±1.07, 1.4±0.7, and 1.6±0.69 and accuracy rates of 85.4±3.83%, 90±3.56%, and 91.2±2.04%. Movement onset detection latency from our automatic RP detector was -384.9±296.5 ms. As a conclusion, the proposed method outperforms state-of-the-art techniques using as low as single channel EEG making it suitable for real-time neuro-rehabilitation of paralyzed subjects suffering from stroke. © 2021

关键词： BCI Convex optimization EEG Nonlinear Readiness potential (RP) Teager-Kaiser energy operator (TEO)

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Crack Catcher AI — Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI — Enabling Smart Fracture Mechanics Approa...

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Annual International Symposium on Reliability Physics

作者： Gabriel Preston Greer Gonzolez Andrea S. Karnyoto Fitya S. Mozar Matthew M. Henry Mahmud Isnan Kuncahyo S. Nugroho Henry Candra Muhamad Doris Dianing N. N. Putri Tyas K Sari Bens Pardamean Endang Djuana Derrric Speaks Arief S. Budiman Oregon Renewable Energy Center (OREC) Oregon Institute of Technology (Oregon Tech) Klamath Falls OR USA Dept. of Manufacturing & Mechanical Eng. & Tech. (MMET) Oregon Institute of Technology Klamath Falls OR USA Bioinformatics & Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia Computer Sci. Dept. BINUS Grad. Program - Master of Computer Sci. Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Center for Artificial Intelligence and Advanced Technology (CAPTIVATE) Universitas TRISAKTI Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas TRISAKTI Jakarta Indonesia Industrial Eng. Dept. BINUS Grad. Program – Master of Industrial Eng. Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability.

关键词： Semiconductor device measurement Three-dimensional displays Accuracy Semiconductor device reliability Silicon Artificial intelligence Bonding Stress Three-dimensional integrated circuits Stress measurement

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Corporate Venture Capital and Sustainability

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Journal of Open Innovation: Technology, Market, and Complexity 2022年第3期8卷

作者： Döll, Luciano Mathias Ulloa, Micaela Ines Castillo Zammar, Alexandre Prado, Guilherme Francisco do Piekarski, Cassiano Moro Post-Graduation Program of Production Engineering Federal University Technology (UTFPR) Ponta Grossa 84016-210 Brazil Department of Informatics Universidade Estadual de Ponta Grossa (UEPG) Ponta Grossa 84030-900 Brazil Coordination of Technology in Mechanical Manufacturing Instituto Federal de Santa Catarina (IFPR) Florianópolis 88020-300 Brazil

Corporate Venture Capital (CVC) has been receiving increasingly more attention all over the world as a special way for accessing new ideas and innovative opportunities through minor-share investing in established companies. The purpose of CVC investments may either be purely financial or to pursue strategic goals. Organisations often seek to take actions that impact positively on sustainability by assembling related knowledge and technologies. These resources may come from invested startups through the use of a CVC programme. This research aims to measure and analyse the Corporate Venture Capital programmes of companies listed in the ISE B3 Corporate Sustainability Index. To this end, a three-step methodology was conducted. First, a systematic review of the literature took place, followed by a review of companies based on secondary sources such as their websites. Finally, a survey was developed and was opted to survey companies through their Investor Relationship (IR) public channels. Results show that 27 of the companies listed in the ISE B3 Index have CVC programmes that contemplate organizational initiatives besides investment. In this sense, one can claim that at least 70% of the ISE B3 Index companies are somehow involved in CVC operations. The results contribute to the literature on corporate venture capital and sustainability by showing that companies spend from 10% to 15% of their capital in sustainable businesses in order to remain competitive. © 2022 by the authors.

关键词： corporate venture capital open innovation startups sustainability

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An Immersed Peridynamics Model of Fluid-Structure Interaction Accounting for Material Damage and Failure

SSRN

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SSRN 2022年

作者： Kim, Keon Ho Bhalla, Amneet Pal Singh Griffith, Boyce E. Department of Mathematics University of North Carolina Chapel HillNC United States Department of Mechanical Engineering San Diego State University San DiegoCA United States Departments of Mathematics Applied Physical Sciences and Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina Chapel HillNC United States McAllister Heart Institute University of North Carolina Chapel HillNC United States

This paper develops and benchmarks an immersed peridynamics method to simulate the deformation, damage, and failure of hyperelastic materials within a fluid-structure interaction framework. The immersed peridynamics method describes an incompressible structure immersed in a viscous incompressible fluid. It expresses the momentum equation and incompressibility constraint in Eulerian form, and it describes the structural motion and resultant forces in Lagrangian form. Coupling between Eulerian and Lagrangian variables is achieved by integral transforms with Dirac delta function kernels, as in standard immersed boundary (IB) methods. The major difference between our approach and conventional IB methods is that we use peridynamics, instead of classical continuum mechanics, to determine the structural forces. We focus on non-ordinary state-based peridynamic material descriptions that allow us to use a constitutive correspondence framework that can leverage well characterized nonlinear constitutive models of soft materials. The convergence and accuracy of our approach are compared to both conventional and immersed finite element methods using widely used benchmark problems of nonlinear incompressible elasticity. We demonstrate that the immersed peridynamics method yields comparable accuracy with similar numbers of structural degrees of freedom for several choices of the size of the peridynamic horizon. We also demonstrate that the method can generate grid-converged simulations of fluid-driven material damage growth, crack formation and propagation, and rupture under large deformations. © 2022, The Authors. All rights reserved.

关键词： Fluid structure interaction

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Use your smartphone to observe sound phenomenon and understand the concepts

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AIP Conference Proceedings 2023年第1期2572卷

作者： Ade Yeti Nuryantini Rizki Zakwandi Muhamad Ari Ariayuda 11Department of Physics Education State Islamic University Sunan Gunung Djati Bandung Bandung Indonesia 2Master Program of Physics Education Faculty of Mathematics and Natural Sciences Universitas Negeri Yogyakarta Yogyakarta Indonesia 3Mechanical Engineering Department Faculty of Engineering Universitas Diponegoro Semarang Indonesia

Smartphone sensors have been widely researched and published in literature by experts to be used in physics learning. This paper presents the use of smartphone sensors and applications as a measuring instrument in the classical sound wave experiment adapted from physics textbooks at school or university. Tone generator, sound meter, and audio autocorrelation were used in the experiment to visualize sound as a propagating vibration, sound waves as mechanical waves, characteristics of sound waves (loud and soft or high-pitched or low-pitched), sound range, and sound power. The experimental results presented are expected to help students understand the concept of sound waves.

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Adaptive Traffic Signal Control for Developing Countries Using Fused Parameters Derived from Crowd-Source Data

arXiv

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arXiv 2022年

作者： Mishra, Sumit Singh, Vishal Gupta, Ankit Bhattacharya, Devanjan Mudgal, Abhisek The Robotics Program Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Member of Technical Staff VMware Inc Palo AltoCA United States Department of Civil Engineering Indian Institute of Technology Banaras Hindu University Varanasi India Marie Sklodowska-Curie Actions TRAIN@ED School of Law School of Informatics University of Edinburgh United Kingdom Universidade Nova de Lisboa Campus de Campolide Lisboa1070-312 Portugal

Advancement of mobile technologies has enabled economical collection, storage, processing, and sharing of traffic data. These data are made accessible to intended users through various application program interfaces (API) and can be used to recognize and mitigate congestion in real time. In this paper, quantitative (time of arrival) and qualitative (color-coded congestion levels) data were acquired from the Google traffic APIs. New parameters that reflect heterogeneous traffic conditions were defined and utilized for real-time control of traffic signals while maintaining the green-to-red time ratio. The proposed method utilizes a congestion-avoiding principle commonly used in computer networking. Adaptive congestion levels were observed on three different intersections of Delhi (India), in peak hours. It showed good variation, hence sensitive for the control algorithm to act efficiently. Also, simulation study establishes that proposed control algorithm decreases waiting time and congestion. The proposed method provides an inexpensive alternative for traffic sensing and tracking technologies. © 2022, CC BY.

关键词： Crowdsourcing

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Motion Intensity Extraction Scheme for Simultaneous Recognition of Wrist/Hand Motions

Motion Intensity Extraction Scheme for Simultaneous Recognit...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Minjae Kim Wan Kyun Chung Keehoon Kim Interaction and Robotics Research Center Korea Institute of Science and Technology (KIST) Seoul South Korea Department of Mechanical Engineering Pohang University of Science and Technology (POSTECH) Pohang South Korea

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Surface electromyography contains muscular information representing gestures and corresponding forces. However, conventional sEMG-based motion recognition methods, such as pattern classification and regression, have intrinsic limitations due to the complex characteristics of sEMG signals. In this paper, motion intensity, a highly selective sEMG feature proportional to the level of muscle contraction, is proposed. The motion intensity feature allows proportional and simultaneous recognition of multiple degrees of freedom. The proposed method was demonstrated in terms of simultaneous recognition of wrist/hand motions. The result shows that the proposed method can successfully decompose sEMG signals into highly selective signals to target motions. In future works, the proposed method will be adapted for more subjects and to sEMG applications for practical evaluation considering various grasping motions.

关键词： Muscles Crosstalk Feature extraction Wrist Pattern recognition Microsoft Windows Electrodes

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Coordination-driven mixing behavior of corrosion and fission products in NaCl-UCl₃ molten salt

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Journal of Nuclear Materials 2025年 615卷

作者： Gaoxue Wang Bo Li Ping Yang Theodore M. Besmann David A. Andersson Theoretical Division Los Alamos National Laboratory P.O. Box 1663 Los Alamos NM 87545 USA Nuclear Engineering Program Department of Mechanical Engineering University of South Carolina Columbia SC 29208 USA Materials Science and Technology Division Los Alamos National Laboratory P.O. Box 1663 Los Alamos NM 87545 USA

Molten salts play a crucial role in Generation IV nuclear energy technology, with chloride salts like NaCl-UCl 3 garnering significant attention due to their distinctive properties and potential applications in fast-spectrum molten salt reactors (MSRs). The corrosive nature of molten salts can cause the dissolution of structural materials, leading to the formation of new species in molten chlorides. In addition, the radioactive decay of nuclear fuels results in the accumulation of fission products in the salts. Understanding the behavior of these corrosion and fission products and their impacts on the properties of molten salts is critical for the design of MSRs. This paper presents a systematic study on the properties of eutectic NaCl-UCl 3 molten salt in the presence of corrosion products (CrCl 2 and CrCl 3 ) and fission products (CsCl and SrCl 2 ) utilizing ab initio molecular dynamics (AIMD) simulations. We focus on essential structural and thermophysical properties such as density, mixing energy, coordination numbers (CN), and Radial Distribution Functions (RDF) with varying compositions of these corrosion and fission products from 0 % to 15.8 %. It is found that the mixing behavior of these corrosion and fission products is strongly driven by their coordination chemistry in eutectic NaCl-UCl 3 . Both CrCl 2 and SrCl 2 have identical coordination to eutectic NaCl-UCl 3 , thus exhibit negative mixing energies at a lower concentration. In contrast, CsCl exhibits significant different coordination compared to NaCl-UCl 3 , resulting to positive mixing energies. Our results offer valuable insights into the coordination chemistry and mixing behavior of corrosion and fission products in chloride molten salts and provide essential data that can be used as input to property databases to supplement experimental data.

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Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition

arXiv

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arXiv 2023年

作者： de Franca, F.O. Virgolin, M. Kommenda, M. Majumder, M.S. Cranmer, M. Espada, G. Ingelse, L. Fonseca, A. Landajuela, M. Petersen, B. Glatt, R. Mundhenk, N. Lee, C.S. Hochhalter, J.D. Randall, D.L. Kamienny, P. Zhang, H. Dick, G. Simon, A. Burlacu, B. Kasak, Jaan Machado, Meera Wilstrup, Casper La Cava, W.G. Federal University of ABC Santo Andre Brazil Evolutionary Intelligence Group Centrum Wiskunde & Informatica Science Park 123 Amsterdam Netherlands Computational Health Informatics Program Boston Children's Hospital Harvard Medical School Boston United States University of Applied Sciences Upper Austria Hagenberg Austria Center for Computational Astrophysics Flatiron Institute Department of Astrophysical Sciences Princeton University United States LASIGE Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Computational Engineering Division Lawrence Livermore National Laboratory Livermore United States University of Utah Department of Mechanical Engineering Utah United States Meta FAIR France Victoria University of Wellington School of Engineering and Computer Science New Zealand University of otago Department of Information Science New Zealand Institut für Angewandte Physik Universität Tübingen Max Planck Institute for Intelligent Systems Tübingen Germany Abzu AI Orient Plads 1 Nordhavn 2150 Denmark

Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main attraction of this approach is that it returns an interpretable model that can be insightful to users. Historically, the majority of algorithms for symbolic regression have been based on evolutionary algorithms. However, there has been a recent surge of new proposals that instead utilize approaches such as enumeration algorithms, mixed linear integer programming, neural networks, and Bayesian optimization. In order to assess how well these new approaches behave on a set of common challenges often faced in real-world data, we hosted a competition at the 2022 Genetic and Evolutionary Computation Conference consisting of different synthetic and real-world datasets which were blind to entrants. For the real-world track, we assessed interpretability in a realistic way by using a domain expert to judge the trustworthiness of candidate models. We present an in-depth analysis of the results obtained in this competition, discuss current challenges of symbolic regression algorithms and highlight possible improvements for future competitions. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Deepclaw: A robotic hardware benchmarking platform for learning object manipulation

arXiv

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arXiv 2020年

作者： Wan, Fang Wang, Haokun Liu, Xiaobo Yang, Linhan Song, Chaoyang SUSTech Institute of Robotics Southern University of Science and Technology Shenzhen Guangdong518055 China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen Guangdong518055 China

We present DeepClaw as a reconfigurable benchmark of robotic hardware and task hierarchy for robot learning. The DeepClaw benchmark aims at a mechatronics perspective of the robot learning problem, which features a minimum design of robot cell that can be easily reconfigured to host robot hardware from various vendors, including manipulators, grippers, cameras, desks, and objects, aiming at a streamlined collection of physical manipulation data and evaluation of the learned skills for hardware benchmarking. We provide a detailed design of the robot cell with readily available parts to build the experiment environment that can host a wide range of robotic hardware commonly adopted for robot learning. We also propose a hierarchical pipeline of software integration, including localization, recognition, grasp planning, and motion planning, to streamline learning-based robot control, data collection, and experiment validation towards shareability and reproducibility. We present benchmarking results of the DeepClaw system for a baseline Tic-Tac-Toe task, a bin-clearing task, and an jigsaw puzzle task using three sets of standard robotic hardware. Our results show that tasks defined in DeepClaw can be easily reproduced on three robot cells. Under the same task setup, the differences in robotic hardware used will present a non-negligible impact on the performance metrics of robot learning. All design layouts and codes are hosted on Github for open access. Copyright © 2020, The Authors. All rights reserved.

关键词： Benchmarking

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