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arXiv 2019年

作者： Özdenizci, Ozan Meyer, Timm Wichmann, Felix Peters, Jan Schölkopf, Bernhard Çetin, Müjdat Grosse-Wentrup, Moritz Department of Electrical and Computer Engineering Northeastern University BostonMA United States Signal Processing and Information Systems Laboratory Faculty of Engineering and Natural Sciences Sabancı University Istanbul Turkey Max Planck Institute for Intelligent Systems Tübingen Germany Faculty of Science University of Tübingen Bernstein Center for Computational Neuroscience Tübingen Tübingen Germany FG Intelligente Autonome Systeme Technische Universität Darmstadt Darmstadt Germany Department of Electrical and Computer Engineering University of Rochester RochesterNY United States Research Group Neuroinformatics Faculty of Computer Science University of Vienna Vienna Austria

Stroke-induced disturbances of large-scale cortical networks are known to be associated with the extent of motor deficits. We argue that identifying brain networks representative of motor behavior in the resting brain would provide significant insights for current neurorehabilitation approaches. Particularly, we aim to investigate the global configuration of brain rhythms and their relation to motor skill, instead of learning performance as broadly studied. We empirically approach this problem by conducting a three-dimensional physical space visuomotor learning experiment during electroencephalographic (EEG) data recordings with thirty-seven healthy participants. We demonstrate that across-subjects variations in average movement smoothness as the quantified measure of subjects' motor skills can be predicted from the global configuration of resting-state EEG alpha-rhythms (8-14 Hz) recorded prior to the experiment. Importantly, this neural signature of motor skill was found to be orthogonal to (independent of) task- as well as to learning-related changes in alpha-rhythms, which we interpret as an organizing principle of the brain. We argue that disturbances of such configurations in the brain may contribute to motor deficits in stroke, and that reconfiguring stroke patients' brain rhythms by neurofeedback may enhance post-stroke neurorehabilitation. Copyright © 2019, The Authors. All rights reserved.

关键词： Electroencephalography

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A Scalable Deep Attention Mechanism of Instance Segmentation for the Investigation of Chromosome

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SLAS technology 2025年 33卷 100306页

作者： Neelam Umbreen Sara Ali Hasan Sajid Yasar Ayaz Shrooq Alsenan Yunyoung Nam So Yeon Kim Muhammad Baber Sial National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: neelamumbreen.phd@smme.edu.pk. National University of Sciences and Technology (NUST) Islamabad Pakistan Suzhou Industrial Park (SIP) Monash Research Institute of Science and Technology Monash University 8Q9C+R6W Suzhou Jiangsu China. School of Mechanical and Manufacturing Engineering (SMME) National University of Sciences and Technology (NUST) Islamabad NUST-COVENTRY Human-Robot Interaction (NC-HRI) Laboratory Pakistan Intelligent Field Robotics Laboratory (IFRL) National Center for Artificial Intelligence (NCAI) National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: sarababer@smme.nust.edu.pk. National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: hasan.sajid@smme.nust.edu.pk. Intelligent Field Robotics Laboratory (IFRL) National Center for Artificial Intelligence (NCAI) National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: yasar@smme.nust.edu.pk. Information Systems Department College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia. Electronic address: shalsenan@pnu.edu.sa. Emotional and Intelligent Child Care Convergence Research Center Soonchunhyang University Asan 31538 Korea. Electronic address: ynam@sch.ac.kr. Department of Artificial Intelligence Department of Software and Computer Engineering Ajou University. Electronic address: jebi1771@ajou.ac.kr. School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China. Electronic address: babersial@***.

Chromosome segmentation in metaphase images is a critical yet challenging task in cytogenetics and genomics due to the inherent complexity, variability in chromosome shapes, and the scarcity of high-quality annotated datasets. This study proposes a robust instance segmentation framework that integrates an automated annotation pipeline with an enhanced deep learning architecture to address these challenges. A novel dataset is introduced, comprising metaphase images and corresponding karyograms, annotated with precise instance segmentation information across 24 chromosome classes in COCO format. To overcome the labor-intensive manual annotation process, a feature-based image registration technique leveraging SIFT and homography is employed, enabling the accurate mapping of chromosomes from karyograms to metaphase images and significantly improving annotation quality and segmentation performance. The proposed framework includes a custom Mask R-CNN model enhanced with an Attention-based Feature Pyramid Network (AttFPN), spatial attention mechanisms, and a LastLevelMaxPool block for superior multi-scale feature extraction and focused attention on critical regions of the image. Experimental evaluations demonstrate the model's efficacy, achieving a mean average precision (mAP) of 0.579 at IoU = 0.50:0.95, surpassing the baseline Mask R-CNN and Mask R-CNN with AttFPN by 3.94% and 5.97% improvements in mAP and AP50, respectively. Notably, the proposed architecture excels in segmenting small and medium-sized chromosomes, addressing key limitations of existing methods. This research not only introduces a state-of-the-art segmentation framework but also provides a benchmark dataset, setting a new standard for chromosome instance segmentation in biomedical imaging. The integration of automated dataset creation with advanced model design offers a scalable and transferable solution, paving the way for tackling similar challenges in other domains of biomedical and cytogenetic imagi

关键词： Chromosome segmentation Instance segmentation, cytogenetics Mask R-CNN attention mechanism biomedical imaging multi-scale feature fusion

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Design of Experiments for Battery Aging Estimation

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IFAC-PapersOnLine 2018年第28期51卷 386-391页

作者： Pózna, Anna I. Hangos, Katalin M. Magyar, Attila Department of Electrical Engineering and Information Systems Faculty of Information Technology University of Pannonia Egyetem str. 10. VeszprémH-8200 Hungary Process Control Research Group HAS Research Institute for Computer Science and Control Kende str. 13-17. BudapestH-1111 Hungary

Li-ion batteries are widely used in EV applications and are imposed to several aging effects during their lifetime. Since battery health cannot be measured directly, information about its health can be obtained by iteratively re-estimating the parameters of the model describing its dynamical behavior. The optimal design of experiments is investigated in this paper. The proposed method applies families of input signals (PRBS current and constant current-constant voltage (CC-CV) signals) to the batteries to estimate the key aging factors. Simulation experiments have been used to analyze the statistical properties of the estimators as a function of the design parameters of the input signal families. The results show that the CC-CV charging-discharging cycle has the possibility to gain the most information out of the battery model parameter estimation. © 2018

关键词： Parameter estimation Battery management systems Design of experiments Electric excitation Iterative methods Lithium ion batteries Planning Electric Experiment design Input Model formulation Storage operations

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A Study of Feature Extraction and Classifier Methods for Tropical Wood Recognition System

A Study of Feature Extraction and Classifier Methods for Tro...

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2018 IEEE Region 10 Conference, TENCON 2018

作者： Yusof, Rubiyah Khairuddin, Uswah Rosli, Nenny Ruthfalydia Abdul Ghafar, Hafizza Aizuddin Nik Azmi, Nik Mohamad Ahmad, Azlin Khairuddin, Anis Salwa Centre of Artificial Intelligence and Robotics Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Shah Alam Malaysia Department of Electrical Engineering Universiti Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781538654576

Tropical wood recognition is a very challenging task due to the lack of discriminative features among some species of the wood, and also some very discriminative features among inter class species. Moreover, noises due to illuminations, or the uncontrolled environment as well as the wood features such as the size of pores, the density of pores, etc., which depend very much on the age, weather and other factors, contributing to the irregularities of the features. In this paper, we explore the use of feature extraction techniques, classification techniques for better accuracy of the system. In particular, we explore the use of one of the deep learning method residual network based CNN (Res-Net), noting the capability of the network to learn the features of images and its ability of generalization. Results have shown that good feature extraction methods can give a much better accuracy for all the datasets tested, and Res-Net performed badly due to lack of data, which cause the problem of overfitting. © 2018 IEEE.

关键词： Classification (of information)

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K-core structure of real multiplex networks

arXiv

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arXiv 2019年

作者： Osat, Saeed Radicchi, Filippo Papadopoulos, Fragkiskos Deep Quantum Labs Skolkovo Institute of Science and Technology Moscow43026 Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology 33 Saripolou Street Limassol3036

Multiplex networks are convenient mathematical representations for many real-world - biological, social, and technological - systems of interacting elements, where pairwise interactions among elements have different flavors. Previous studies pointed out that real-world multiplex networks display significant inter-layer correlations - degree-degree correlation, edge overlap, node similarities - able to make them robust against random and targeted failures of their individual components. Here, we show that inter-layer correlations are important also in the characterization of their k-core structure, namely the organization in shells of nodes with increasingly high degree. Understanding k-core structures is important in the study of spreading processes taking place on networks, as for example in the identification of influential spreaders and the emergence of localization phenomena. We find that, if the degree distribution of the network is heterogeneous, then a strong k-core structure is well predicted by significantly positive degree-degree correlations. However, if the network degree distribution is homogeneous, then strong k-core structure is due to positive correlations at the level of node similarities. We reach our conclusions by analyzing different real-world multiplex networks, introducing novel techniques for controlling inter-layer correlations of networks without changing their structure, and taking advantage of synthetic network models with tunable levels of inter-layer correlations. Copyright © 2019, The Authors. All rights reserved.

关键词： Network layers

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The master stability function for synchronization in simplicial complexes

arXiv

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arXiv 2020年

作者： Gambuzza, L.V. Di Patti, F. Gallo, L. Lepri, S. Romance, M. Criado, R. Frasca, Mattia Latora, V. Boccaletti, S. Department of Electrical Electronics and Computer Science Engineering University of Catania Catania95125 Italy CNR-Institute of Complex Systems Via Madonna del Piano Sesto Fiorentino Florence50019 Italy Department of Physics and Astronomy University of Catania Catania95125 Italy Department of Applied Math. and Data Complex Networks and Cybersecurity Research Institute University Rey Juan Carlos C/Tulipn s/n Mstoles Madrid28933 Spain Department of Physics and Astronomy University of Catania INFN Catania95125 Italy School of Mathematical Sciences Queen Mary University of London LondonE1 4NS United Kingdom The Alan Turing Institute The British Library LondonNW1 2DB United Kingdom Unmanned Systems Research Institute Northwestern Polytechnical University Xi'an710072 China Moscow Institute of Physics and Technology Dolgoprudny Moscow Region141701 Russia

All interesting and fascinating collective properties of a complex system arise from the intricate way in which its components interact. Various systems in physics, biology, social sciences and engineering have been successfully modelled as networks of coupled dynamical systems, where the graph links describe pairwise interactions. This is, however, too strong a limitation, as recent studies have revealed that higher-order many-body interactions are present in social groups, ecosystems and in the human brain, and they actually affect the emergent dynamics of all these systems. Here, we introduce a general framework that allows to study coupled dynamical systems accounting for the precise microscopic structure of their interactions at any possible order. We consider the most general ensemble of identical dynamical systems, organized on the nodes of a simplicial complex, and interacting through synchronization-non-invasive coupling function. The simplicial complex can be of any dimension, meaning that it can account, at the same time, for pairwise interactions, three-body interactions and so on. In such a broad context, we show that complete synchronization, a circumstance where all the dynamical units arrange their evolution in unison, exists as an invariant solution, and we give the necessary condition for it to be observed as a stable state in terms of a Master Stability Function. This generalizes the existing results valid for pairwise interactions (i.e. graphs) to the case of complex systems with the most general possible architecture. Moreover, we show how the approach can be simplified for specific, yet frequently occurring, instances, and we verify all our theoretical predictions in synthetic and real-world systems. Given the completely general character of the method proposed, our results contribute to the theory of dynamical systems with many-body interactions and can find applications in an extremely wide range of practical cases. Copyright © 2020, The Auth

关键词： Dynamical systems

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Pain-Free Blood Glucose Monitoring Using Wearable Sensors: Recent Advancements and Future Prospects

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IEEE Reviews in Biomedical engineering 2018年 11卷 21-35页

作者： Siddiqui, Sarah Ali Zhang, Yuan Lloret, Jaime Song, Houbing Obradovic, Zoran Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan250022 China Integrated Management Coastal Research Institute Universidad Politecnica de Valencia Valencia46022 Spain Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Department of Computer and Information Sciences Temple University PhiladelphiaPA19122 United States

Keeping track of blood glucose levels non-invasively is now possible due to diverse breakthroughs in wearable sensors technology coupled with advanced biomedical signal processing. However, each user might have different requirements and priorities when it comes to selecting a self-monitoring solution. After extensive research and careful selection, we have presented a comprehensive survey on noninvasive/pain-free blood glucose monitoring methods from the recent five years (2012-2016). Several techniques, from bioinformatics, computer science, chemical engineering, microwave technology, etc., are discussed in order to cover a wide variety of solutions available for different scales and preferences. We categorize the noninvasive techniques into nonsample- and sample-based techniques, which we further grouped into optical, nonoptical, intermittent, and continuous. The devices manufactured or being manufactured for noninvasive monitoring are also compared in this paper. These techniques are then analyzed based on certain constraints, which include time efficiency, comfort, cost, portability, power consumption, etc., a user might experience. Recalibration, time, and power efficiency are the biggest challenges that require further research in order to satisfy a large number of users. In order to solve these challenges, artificial intelligence (AI) has been employed by many researchers. AI-based estimation and decision models hold the future of noninvasive glucose monitoring in terms of accuracy, cost effectiveness, portability, efficiency, etc. The significance of this paper is twofold: first, to bridge the gap between IT and medical field;and second, to bridge the gap between end users and the solutions (hardware and software). © 2008-2011 IEEE.

关键词： Cost effectiveness

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Robust gesture-based communication for underwater human-robot interaction in the context of search and rescue diver missions

arXiv

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arXiv 2018年

作者： Chavez, Arturo Gomez Mueller, Christian A. Doernbach, Tobias Chiarella, Davide Birk, Andreas Robotics Group Computer Science & Electrical Engineering Jacobs University Bremen Germany Institute of Intelligent Systems for AutomationNational Research Council of Italy Genova Italy

We propose a robust gesture-based communication pipeline for divers to instruct an Autonomous Underwater Vehicle (AUV) to assist them in performing high-risk tasks and helping in case of emergency. A gesture communication language (CADDIAN) is developed, based on consolidated and standardized diver gestures, including an alphabet, syntax and semantics, ensuring a logical consistency. A hierarchical classification approach is introduced for hand gesture recognition based on stereo imagery and multi-descriptor aggregation to specifically cope with underwater image artifacts, e.g. light backscatter or color attenuation. Once the classification task is finished, a syntax check is performed to filter out invalid command sequences sent by the diver or generated by errors in the classifier. Throughout this process, the diver receives constant feedback from an underwater tablet to acknowledge or abort the mission at any time. The objective is to prevent the AUV from executing unnecessary, infeasible or potentially harmful motions. Experimental results under different environmental conditions in archaeological exploration and bridge inspection applications show that the system performs well in the field. Copyright © 2018, The Authors. All rights reserved.

关键词： Syntactics

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Real-time detection, tracking, and classification of moving and stationary objects using multiple fisheye images

arXiv

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arXiv 2018年

作者： Baek, Iljoo Davies, Albert Yan, Geng Rajkumar, Ragunathan Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States Robotics Institute Carnegie Mellon University PittsburghPA15213 United States Department of Electrical and Computer Engineering and Robotics Institute Carnegie Mellon University PittsburghPA15213 United States

The ability to detect pedestrians and other moving objects is crucial for an autonomous vehicle. This must be done in real-time with minimum system overhead. This paper discusses the implementation of a surround view system to identify moving as well as static objects that are close to the ego vehicle. The algorithm works on 4 views captured by fisheye cameras which are merged into a single frame. The moving object detection and tracking solution uses minimal system overhead to isolate regions of interest (ROIs) containing moving objects. These ROIs are then analyzed using a deep neural network (DNN) to categorize the moving object. With deployment and testing on a real car in urban environments, we have demonstrated the practical feasibility of the solution1. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep neural networks

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TOI-2015b: A Warm Neptune with Transit Timing Variations Orbiting an Active mid M Dwarf

arXiv

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arXiv 2023年

作者： Jones, Sinclaire E. Stefánsson, Gu mundur Masuda, Kento Libby-Roberts, Jessica E. Gardner, Cristilyn N. Holcomb, Rae Beard, Corey Robertson, Paul Cañas, Caleb I. Mahadevan, Suvrath Kanodia, Shubham Lin, Andrea S.J. Kobulnicky, Henry A. Parker, Brock A. Bender, Chad F. Cochran, William D. Diddams, Scott A. Fernandes, Rachel B. Gupta, Arvind F. Halverson, Samuel Hawley, Suzanne L. Hearty, Fred R. Hebb, Leslie Kowalski, Adam Lubin, Jack Monson, Andrew Ninan, Joe P. Ramsey, Lawrence Roy, Arpita Schwab, Christian Terrien, Ryan C. Wisniewski, John Department of Astronomy The Ohio State University 4055 McPherson Laboratory ColumbusOH43210 United States Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08540 United States Anton Pannekoek Institute for Astronomy University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Department of Earth and Space Science Graduate School of Science Osaka University 1-1 Machikaneyama Toyonaka Osaka560-0043 Japan Department of Astronomy & Astrophysics The Pennsylvania State University 525 Davey Laboratory University ParkPA16802 United States Department of Physics & Astronomy University of Wyoming LaramieWY82070 United States Department of Physics & Astronomy The University of California Irvine IrvineCA92697 United States NASA Goddard Space Flight Center 8800 Greenbelt Road GreenbeltMD20771 United States Center for Exoplanets and Habitable Worlds The Pennsylvania State University 525 Davey Laboratory University ParkPA16802 United States Earth and Planets Laboratory Carnegie Institution for Science 5241 Broad Branch Road NW WashingtonDC20015 United States Steward Observatory The University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States McDonald Observatory and Department of Astronomy The University of Texas at Austin 2515 Speedway AustinTX78712 United States Center for Planetary Systems Habitability The University of Texas at Austin 2515 Speedway AustinTX78712 United States Electrical Computer & Energy Engineering University of Colorado 425 UCB BoulderCO80309 United States Department of Physics University of Colorado 2000 Colorado Avenue BoulderCO80309 United States National Institute of Standards and Technology 325 Broadway BoulderCO80305 United States Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States Astronomy Department University of Washington SeattleWA98195 United States Department of Physics Hobart and Wil

We report the discovery of a close-in (Porb = 3.349 days) warm Neptune with clear transit timing variations (TTVs) orbiting the nearby (d = 47.3 pc) active M4 star, TOI-2015. We characterize the planet's properties using TESS photometry, precise near-infrared radial velocities (RV) with the Habitable-zone Planet Finder (HP) Spectrograph, ground-based photometry, and high-contrast imaging. A joint photometry and RV fit yields a radius Rp = 3.37+0.15 -0.20 R⊕, mass mp = 16.4+4.1 -4.1 M⊕, and density ρp = 2.32+0.38 -0.37 gcm-3 for TOI-2015b, suggesting a likely volatile-rich planet. The young, active host star has a rotation period of Prot = 8.7 ± 0.9 days and associated rotation-based age estimate of 1.1 ± 0.1 Gyr. Though no other transiting planets are seen in the TESS data, the system shows clear TTVs of super period Psup ≈ 430 days and amplitude ∼100 minutes. After considering multiple likely period ratio models, we show an outer planet candidate near a 2:1 resonance can explain the observed TTVs while offering a dynamically stable solution. However, other possible two-planet solutions-including 3:2 and 4:3 resonance-cannot be conclusively excluded without further observations. Assuming a 2:1 resonance in the joint TTV-RV modeling suggests a mass of mb = 13.3+4.7 -4.5M⊕ for TOI-2015b and mc = 6.8+3.5 -2.3M⊕ for the outer candidate. Additional transit and RV observations will be beneficial to explicitly identify the resonance and further characterize the properties of the system. Copyright © 2023, The Authors. All rights reserved.

关键词： Photometry

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