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EEG channel reconstruction using convolutional neural networks in limited BCIs: A proposed method for neuromarketing applications

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Applied Soft Computing 2025年 181卷

作者： Mario Quiles Pérez Sergio López Bernal Eduardo Horna Prat Luis Montesano Del Campo Lorenzo Fernández Maimó Alberto Huertas Celdrán Department of Information and Communications Engineering University of Murcia 30100 Murcia Spain Bit&Brain Technologies S.L Zaragoza 50006 Spain Department of Computer Architecture and Technology University of Murcia 30100 Murcia Spain Communication Systems Group CSG Department of Informatics IfI University of Zurich UZH CH–8050 Zürich Switzerland

Neuromarketing is a discipline that combines insights from neuroscience with marketing strategies to gain a profound understanding of consumer behavior through the analysis of physiological data. Electroencephalography (EEG), which provides real-time and direct measurements of brain activity, is increasingly utilized to assess cognitive and emotional responses, offering vital insights for optimizing marketing campaigns. However, the application of EEG via Brain–computer Interfaces (BCIs) in neuromarketing scenarios encounters specific challenges, particularly with low-cost BCIs. These devices, while expanding the accessibility of EEG technology for mass data collection, typically suffer from limited channel numbers and static electrode configurations, constraining the depth and amplitude of data that can be gathered. This study introduces a novel, a lightweight convolutional neural network model that has demonstrated good performance in reconstructing EEG signals for neuromarketing applications, particularly when employed with limited-channel, low-cost BCIs. The integration of advanced deep learning techniques directly into the EEG device firmware enables the virtual generation of additional EEG channels, effectively overcoming traditional device limitations. Furthermore, this research presents a custom loss function that combines mean squared error and Pearson’s correlation coefficient, ensuring high fidelity in signal reconstruction and alignment with the intricate temporal dynamics of brain activity. This enhancement is crucial for capturing accurate consumer responses. Validation against public EEG datasets demonstrated the superiority of the model in reconstructing EEG channels over traditional signal processing methods. Additionally, rigorous testing of over 1,820 channel configurations has proven the adaptability and precision of the model, making it ideal for diverse neuromarketing scenarios.

关键词： EEG Neuromarketing Brain–computer Interfaces Deep learning Artificial Intelligence

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Non-convex potential games for finding global solutions to sensor network localization

arXiv

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arXiv 2023年

作者： Xu, Gehui Chen, Guanpu Hong, Yiguang Fidan, Baris Parisini, Thomas Johansson, Karl H. Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Department of Engineering and Architecture University of Trieste Trieste34127 Italy

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results. Copyright © 2023, The Authors. All rights reserved.

关键词： Sensor networks

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Cloud-Magnetic Resonance Imaging System: In the Era of 6G and Artificial Intelligence

arXiv

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arXiv 2023年

作者： Zhou, Yirong Wu, Yanhuang Su, Yuhan Li, Jing Cai, Jianyun You, Yongfu Guo, Di Qu, Xiaobo The Department of Electronic Science Biomedical Intelligent Cloud R&D Center Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance National Institute for Data Science in Health and Medicine Institute of Artificial Intelligence Xiamen University Xiamen361104 China The Department of Electronic Science Key Laboratory of Digital Fujian on IoT Communication Architecture and Safety Technology Xiamen University Xiamen361104 China Shanghai Electric Group CO. LTD Shanghai200001 China China Telecom Group Quanzhou362000 China China Mobile Group Xiamen361005 China School of Computer and Information Engineering Fujian Engineering Research Center for Medical Data Mining and Application Xiamen University of Technology Xiamen361024 China

Magnetic Resonance Imaging (MRI) plays an important role in medical diagnosis, generating petabytes of image data annually in large hospitals. This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure. Additionally, local data processing demands substantial manpower and hardware investments. Data isolation across different healthcare institutions hinders cross-institutional collaboration in clinics and research. In this work, we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing, 6G bandwidth, edge computing, federated learning, and blockchain technology. This system is called Cloud-MRI, aiming at solving the problems of MRI data storage security, transmission speed, AI algorithm maintenance, hardware upgrading, and collaborative work. The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data (ISMRMRD) format. Then, the data are uploaded to the cloud or edge nodes for fast image reconstruction, neural network training, and automatic analysis. Then, the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services. The Cloud-MRI system will save the raw imaging data, reduce the risk of data loss, facilitate inter-institutional medical collaboration, and finally improve diagnostic accuracy and work efficiency. Copyright © 2023, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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iLGaCo: Incremental learning of gait covariate factors

arXiv

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arXiv 2020年

作者： Mu, Zihao Castro, Francisco M. Marín-Jiménez, Manuel J. Guil, Nicolás Li, Yan-Ran Yu, Shiqi College of Computer Science and Software Engineering Shenzhen University China Department of Computer Architecture University of Málaga Spain Department of Computing and Numerical Analysis University of Córdoba Spain China Department of Computer Science and Engineering Southern University of Science and Technology China

Gait is a popular biometric pattern used for identifying people based on their way of walking. Traditionally, gait recognition approaches based on deep learning are trained using the whole training dataset. In fact, if new data (classes, view-points, walking conditions, etc.) need to be included, it is necessary to re-train again the model with old and new data samples. In this paper, we propose iLGaCo, the first incremental learning approach of covariate factors for gait recognition, where the deep model can be updated with new information without re-training it from scratch by using the whole dataset. Instead, our approach performs a shorter training process with the new data and a small subset of previous samples. This way, our model learns new information while retaining previous knowledge. We evaluate iLGaCo on CASIA-B dataset in two incremental ways: adding new view-points and adding new walking conditions. In both cases, our results are close to the classical ‘training-from-scratch’ approach, obtaining a marginal drop in accuracy ranging from 0.2% to 1.2%, what shows the efficacy of our approach. In addition, the comparison of iLGaCo with other incremental learning methods, such as LwF and iCarl, shows a significant improvement in accuracy, between 6% and 15% depending on the experiment. Copyright © 2020, The Authors. All rights reserved.

关键词： Gait analysis

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Mode-dependent seamless transfer control strategy of a microgrid via a small-signal stability approach

Mode-dependent seamless transfer control strategy of a micro...

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作者： Wu, Ying Guerrero, Josep M. Wu, Yanpeng School of Computer Science Xi'an Shiyou University China Department of Energy Technology Aalborg University Denmark School of Information and Control Engineering Xi'an University of Architecture and Technology China

A microgrid is an effective solution to enhance the integration of distributed renewable energy resources, which can operate both in grid connected mode and islanded mode. In order to reduce the jumps of the system variables within acceptable limits to ensure the system has good transient performance and power quality in multiple operating modes, seamless transfer is the key problem to be considered. In this paper, due to the different multiple equilibrium points for the two operating modes, the dynamics of every operating mode re modeled as a subsystem with all the variables that are needed to be synchronized. Linearization is carried out respectively for the two operation modes on the different equilibriums in a state-space form based on the small-signal stability method. To reduce the conservatism of the unified controller, the concept of the relative Lyapunov function is introduced to derive a multiple segmental Lyapunov method and a robust feedback mode-dependent switching controller is designed to achieve smooth transfer by making the deviation energy of the two modes both converge to the zero point. To rapidly detect the switching signal, a sparse communication network is introduced by the use of low bandwidth communication links to broadcast the switching signal to each distributed controller. Finally, two microgrid test systems were built in SIMULINK to show the feasibility and effectiveness of the proposed seamless transfer control strategies. © 2019 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd

关键词： Controllers

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A Highly Efficient Dynamical Core of Atmospheric General Circulation Model based on Leap-Format

A Highly Efficient Dynamical Core of Atmospheric General Cir...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Hang Cao Liang Yuan He Zhang Baodong Wu Shigang Li Pengqi Lu Yunquan Zhang Yongjun Xu Minghua Zhang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Institute of Atmospheric Physics Chinese Academy of Sciences Department of Computer Science ETH Zurich Institute of Computing Technology Chinese Academy of Sciences

ISBN: (数字)9781728168760

ISBN: (纸本)9781728168777

The finite-difference dynamical core based on the equal-interval latitude-longitude mesh has been widely used for numerical simulations of the Atmospheric General Circulation Model (AGCM). Previous work utilizes different filtering schemes to alleviate the instability problem incurred by the unequal physical spacing at different latitudes, but they all incur high communication and computation overhead and become a scaling bottleneck. This paper proposes a new leap-format finite-difference computing scheme. It generalizes the usual finite-difference format with adaptive wider intervals and is able to maintain the computational stability in the grid updating. Therefore, the costly filtering scheme is eliminated. The new scheme is parallelized with a shifting communication method and implemented with fine communication optimizations based on a 3D decomposition. With the proposed leap-format computation scheme, the communication overhead of the AGCM is significantly reduced and good load balance is exhibited. The simulation results verify the correctness of the new leap-format scheme. The new scheme achieves the speed of 16.6 simulation-year-per-day (SYPD) and up to 3.3x speedup over the latest implementation.

关键词： Atmospheric modeling Computational modeling Mathematical model Three-dimensional displays Power system stability Stability analysis Two dimensional displays

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Muon identification in a compact single-layered water Cherenkov detector and gamma/hadron discrimination using Machine Learning techniques

arXiv

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arXiv 2021年

作者： Conceição, R. González, Borja Serrano Guillén, A. Pimenta, M. Tomé, B. LIP Av. Prof. Gama Pinto 2 LisbonP-1649-003 Portugal Universidade de Lisboa Av. Rovisco Pais 1 Lisbon1049-001 Portugal Computer Architecture and Technology Department University of Granada Granada Spain

The muon tagging is an essential tool to distinguish between gamma and hadron-induced showers in wide field-of-view gamma-ray observatories. In this work, it is shown that an efficient muon tagging (and counting) can be achieved using a water Cherenkov detector with a reduced water volume and 4 PMTs, provided that the PMT signal spatial and time patterns are interpreted by an analysis based on Machine Learning (ML). The developed analysis has been tested for different shower and array configurations. The output of the ML analysis, the probability of having a muon in the WCD station, has been used to notably discriminate between gamma and hadron induced showers with S/√B ∼ 4 for shower with energies E0 ∼ 1 TeV. Finally, for proton-induced showers, an estimator of the number of muons was built by means of the sum of the probabilities of having a muon in the stations. Resolutions about 20% and a negligible bias are obtained for vertical showers with Nµ > 10. Copyright © 2021, The Authors. All rights reserved.

关键词： Observatories

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Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors

arXiv

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arXiv 2023年

作者： Neun, Moritz Eichenberger, Christian Martin, Henry Spanring, Markus Siripurapu, Rahul Springer, Daniel Deng, Leyan Wu, Chenwang Lian, Defu Zhou, Min Lumiste, Martin Ilie, Andrei Wu, Xinhua Lyu, Cheng Lu, Qing-Long Mahajan, Vishal Lu, Yichao Li, Jiezhang Li, Junjun Gong, Yue-Jiao Grötschla, Florian Mathys, Joël Wei, Ye Haitao, He Fang, Hui Malm, Kevin Tang, Fei Kopp, Michael Kreil, David Hochreiter, Sepp Vienna Austria Institute of Cartography and Geoinformation ETH Zurich Switzerland School of Data Science University of Science and Technology of China China Huawei Noah’s Ark Lab Bolt Technology Tallinn Estonia University of Bucharest Bucharest Romania Department of Civil and Environmental Engineering Northeastern University BostonMA United States Transportation Systems Engineering Technical University of Munich Germany Layer 6 AI Toronto Canada School of Coumpute Science and Engineering South China University of Technology Guangzhou China ETH Zurich Switzerland Department of Computer Science Loughborough University Loughborough United Kingdom School of Architecture Building and Civil Engineering Loughborough University Loughborough United Kingdom HERE Technologies ChicagoIL United States Kaiko Zurich Switzerland Machine Learning Institute Johannes Kepler University Linz Austria

The global trends of urbanization and increased personal mobility force us to rethink the way we live and use urban space. The Traffic4cast competition series tackles this problem in a data-driven way, advancing the latest methods in machine learning for modeling complex spatial systems over time. In this edition, our dynamic road graph data combine information from road maps, 1012 probe data points, and stationary vehicle detectors in three cities over the span of two years. While stationary vehicle detectors are the most accurate way to capture traffic volume, they are only available in few locations. Traffic4cast 2022 explores models that have the ability to generalize loosely related temporal vertex data on just a few nodes to predict dynamic future traffic states on the edges of the entire road graph. In the core challenge, participants are invited to predict the likelihoods of three congestion classes derived from the speed levels in the GPS data for the entire road graph in three cities 15 min into the future. We only provide vehicle count data from spatially sparse stationary vehicle detectors in these three cities as model input for this task. The data are aggregated in 15 min time bins for one hour prior to the prediction time. For the extended challenge, participants are tasked to predict the average travel times on super-segments 15 min into the future – super-segments are longer sequences of road segments in the graph. The competition results provide an important advance in the prediction of complex city-wide traffic states just from publicly available sparse vehicle data and without the need for large amounts of real-time floating vehicle data. © 2023, CC BY-NC-SA.

关键词： Travel time

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Thermodynamic Analysis of a Jet Engine Using a Liquid Propellant

Research Square

引用

Research Square 2022年

作者： Alliche, Mounir Rebhi, Redha Inc, Mustafa Kidar, Ali Menni, Younes Ameur, Houari Lorenzini, Giulio Alsharif, Sameer Althobaiti, Ahmed Aly, Ayman A. Department of Mechanical Engineering Faculty of Technology University Yahia Fares of Medea Medea26000 Algeria Department of Computer Engineering Biruni University Istanbul Turkey Department of Mathematics Science Faculty Firat University Elazig23119 Turkey Department of Medical Research China Medical University Hospital China Medical University Taichung40402 Taiwan Faculty of Exact Sciences and Informatics Ziane Achour University of Djelfa Algeria Faculty of Technology Ziane Achour University of Djelfa Algeria Unit of Research on Materials and Renewable Energies Department of Physics Faculty of Sciences Abou Bekr Belkaid University P.O. Box 119 Tlemcen13000 Algeria Department of Technology University Centre of Naama - Salhi Ahmed P.O. Box 66 Naama 45000 Algeria Department of Engineering and Architecture University of Parma Parco Area Delle Scienze 181/A Parma43124 Italy Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia Department of Mechanical Engineering College of Engineering Taif University Taif21944 Saudi Arabia

Combustion-chamber is a critical component of the propulsion engine, which is widely used in the space industry and aeronautics. The goal of this article is to perform a numerical-analysis on the combustion process using a liquid-type propellant. The steps that must be followed until total combustion is achieved are emphasized. It concerns the fuel feeding phase, its injection and the combustion operation. The amount of combustion products and the energy generated are evaluated. It has been shown that the liquid propellant may present an efficient alternative fuel than the kerosene. In addition, the temperature of combustion does not exceed a certain limit to avoid structural problems in the chamber. The parametric survey allowed determining the range of the most influence factors, including the pressure, mixture richness, velocity and flow rates of injection for the fuel and oxidizer. The number and type of injectors revealed a considerable influence on the velocity and flow rates of injection. To maximize thrust force and system propulsion, a careful selection of chamber material and ignition methods is required. A thorough inspection on the issues of walls cooling showed the necessary survey of maximum temperatures that may be reached during the combustion. Finally, an investigation of the thermal exchange through the walls will be very interesting. © 2022, CC BY.

关键词： Surveys

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Corrigendum to "Electrical coupling regulated by GABAergic nucleo-olivary afferent fibres facilitates cerebellar sensory-motor adaptation" [Neural Netw. 155 (2022) 422-438]

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Neural networks : the official journal of the International Neural Network Society 2023年 165卷 676页

作者： Niceto R Luque Francisco Naveros Ignacio Abadía Eduardo Ros Angelo Arleo Sorbonne Université INSERM CNRS Institut de la Vision 17 rue Moreau F-75012 Paris France Department of Computer Architecture and Technology CITIC-University of Granada 2 Calle Periodista Rafael Gómez Montero ES 18014 Granada Spain. Electronic address: nluque@ugr.es. Department of Computer Architecture and Technology CITIC-University of Granada 2 Calle Periodista Rafael Gómez Montero ES 18014 Granada Spain Department of Neuroscience Baylor College of Medicine Houston TX USA. Department of Computer Architecture and Technology CITIC-University of Granada 2 Calle Periodista Rafael Gómez Montero ES 18014 Granada Spain. Sorbonne Université INSERM CNRS Institut de la Vision 17 rue Moreau F-75012 Paris France.

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