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Companion Proceedings of the ACM on Web Conference 2025

作者： Shaojie Min Shaobin Wang Yaxiao Luo Min Gao Qingyuan Gong Yu Xiao Yang Chen Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai China Research Institute of Intelligent Complex Systems Fudan University Shanghai China Department of Information and Communications Engineering Aalto University Espoo Finland

ISBN: (纸本)9798400713316

Decentralized online social networks such as Mastodon have emerged quickly during the past years, and offer unique opportunities to investigate user behavior, moderation strategies, and community evolution. However, their decentralized nature imposes challenges for data collection and preprocessing, particularly for obtaining a real-time snapshot in a timely manner. This paper introduces FediLive, a framework designed to rapidly collect and preprocess the live feeds from Mastodon, generate a comprehensive snapshot in real-time, including user-generated contents, interaction networks, and users' demographic attributes. Such a snapshot could further be leveraged for data analysis from different angles, leading to a deeper understanding of user activities on Mastodon. Using FediLive, we collected a 13-day snapshot of Mastodon, covering the publicly-visible activities of all Mastodon users. Our study demonstrates the usefulness of FediLive, and reveals its potential in facilitating data-driven analysis for decentralized online social networks.

关键词： decentralized online social networks

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Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps 38

Binding in hippocampal-entorhinal circuits enables compositi...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Kymn, Christopher J. Mazelet, Sonia Thomas, Anthony Kleyko, Denis Frady, E. Paxon Sommer, Friedrich T. Olshausen, Bruno A. Redwood Center for Theoretical Neuroscience Helen Wills Neuroscience Institute UC Berkeley Berkeley United States Université Paris-Saclay ENS Paris-Saclay Gif-sur-Yvette France Department of Electrical and Computer Engineering UC Davis Davis United States Centre for Applied Autonomous Sensor Systems Örebro University Örebro Sweden Intelligent Systems Lab Research Institutes of Sweden Kista Sweden Intel Labs Santa Clara United States Herbert Wertheim School of Optometry & Vision Science UC Berkeley Berkeley United States

We propose a normative model for spatial representation in the hippocampal formation that combines optimality principles, such as maximizing coding range and spatial information per neuron, with an algebraic framework for computing in distributed representation. Spatial position is encoded in a residue number system, with individual residues represented by high-dimensional, complex-valued vectors. These are composed into a single vector representing position by a similarity-preserving, conjunctive vector-binding operation. Self-consistency between the representations of the overall position and of the individual residues is enforced by a modular attractor network whose modules correspond to the grid cell modules in entorhinal cortex. The vector binding operation can also associate different contexts to spatial representations, yielding a model for entorhinal cortex and hippocampus. We show that the model achieves normative desiderata including superlinear scaling of patterns with dimension, robust error correction, and hexagonal, carry-free encoding of spatial position. These properties in turn enable robust path integration and association with sensory inputs. More generally, the model formalizes how compositional computations could occur in the hippocampal formation and leads to testable experimental predictions. © 2024 Neural information processing systems foundation. All rights reserved.

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Online Canonical Correlation Analysis via Rayleigh-Ritz Projections

Online Canonical Correlation Analysis via Rayleigh-Ritz Proj...

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Asilomar Conference on Signals, systems & computers

作者： Vassilis Kalantzis Panagiotis A. Traganitis Charilaos I. Kanatsoulis IBM Research MIT-IBM Watson AI Lab Yorktown Heights NY USA Dept. of Electrical and Computer Engineering Michigan State University East Lansing MI USA Dept. of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354065

Canonical correlation analysis (CCA) is a classical statistical tool that enables processing of multiview data in a plethora signal processing, machine learning and data mining applications, by identifying a common linear subspace from the available data views. Most algorithms tackling the CCA task require all the data per view to be available. Nevertheless, in many cases, data are not available in batch form and may arrive in streaming fashion. This work puts forth a novel, computationally efficient, projection based method for identifying and updating the common subspace on-the-fly, as new data arrive, while retaining its' fidelity. Preliminary numerical tests, on synthetic and real data benchmarks, showcase the potential of the proposed method.

关键词： computers Correlation Machine learning algorithms Signal processing algorithms Machine learning Signal processing Approximation algorithms Performance analysis Computational efficiency Data mining

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Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks

arXiv

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arXiv 2023年

作者： Chowdhury, Mohammed Nowaz Rabbani Zhang, Shuai Wang, Meng Liu, Sijia Chen, Pin-Yu Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute NY United States Department of Computer Science and Engineering Michigan State University MI United States MIT-IBM Watson Ai Lab Ibm Research MA United States Ibm Research Yorktown HeightsNY United States

In deep learning, mixture-of-experts (MoE) activates one or few experts (sub-networks) on a per-sample or per-token basis, resulting in significant computation reduction. The recently proposed patch-level routing in MoE (pMoE) divides each input into n patches (or tokens) and sends l patches (l n) to each expert through prioritized routing. pMoE has demonstrated great empirical success in reducing training and inference costs while maintaining test accuracy. However, the theoretical explanation of pMoE and the general MoE remains elusive. Focusing on a supervised classification task using a mixture of two-layer convolutional neural networks (CNNs), we show for the first time that pMoE provably reduces the required number of training samples to achieve desirable generalization (referred to as the sample complexity) by a factor in the polynomial order of n/l, and outperforms its single-expert counterpart of the same or even larger capacity. The advantage results from the discriminative routing property, which is justified in both theory and practice that pMoE routers can filter label-irrelevant patches and route similar class-discriminative patches to the same expert. Our experimental results on MNIST, CIFAR-10, and CelebA support our theoretical findings on pMoE's generalization and show that pMoE can avoid learning spurious correlations. Copyright © 2023, The Authors. All rights reserved.

关键词： Convolution

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Comparative Study of Alternative-Pole Flux Switching and Inter-Modular Biased-Flux Permanent Magnet Motors

Comparative Study of Alternative-Pole Flux Switching and Int...

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Electrical Machines and Drives (ICEMD), International Conference on

作者： Mohammad Afrank Alireza Eikani Ehsan Farmahini Farahani Mojtaba Mirsalim Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Advanced Motion Systems Research Lab School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electrical Power Research Group School of Engineering Newcastle University Newcastle upon Tyne U.K

This paper executes a comparative analysis between alternative-pole flux-switching and inter-modular biased-flux permanent magnet (PM) motors. Despite their close structural similarities, the former puts magnets not only between stator modules, but also close to the armature windings. However, the inter-modular PM (IMPM) motor only occupies spaces between stator modules. This type of occupation allows this structure to provide a safe operation point for PMs. Not considering the PM’s recoil-phenomenon, the torque density of the IMPM motor is not as significant as the alternative-pole flux-switching PM (AP-FSPM) motor. This is because of the four-operating mode of the AP-FSPM structure which enables it to increase the torque density by utilizing the PMs in every moment of the operation. But, when the demagnetization of the AP-FSPM’s PMs is taken into account, the torque density and torque per PM values of the AP-FSPM structure plummets. A complete full-load demagnetization analysis is done in order to get a better understanding of how the performance of the IMPM structure supersedes the AP-FSPM structure. 2D finite element analysis is used to extract the most important indexes of both topologies.

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Dioxins and plastic waste: A scientometric analysis and systematic literature review of the detection methods

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Environmental Advances 2023年 13卷

作者： Baca, David Monroy, Roberto Castillo, Miguel Elkhazraji, Ali Farooq, Aamir Ahmad, Rafiq Smart & Sustainable Manufacturing Systems Laboratory (SMART LAB) Department of Mechanical Engineering University of Alberta 116 Street NW AB Edmonton 9211 Canada Clean Combustion Research Center Physical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955 Saudi Arabia

Dioxins are highly toxic compounds that pose significant risks to human health and the environment. Burning plastics is a major source of dioxin emissions, contributing to their presence in the environment. This review paper presents a scientometric analysis of publications spanning four decades (1987-2023) aiming to investigate the relationship between plastics and dioxin emissions. Relevant scientific articles were retrieved from the Scopus database, and quantitative analyses were carried out using the VOSviewer tool. Data on literature coupling, keyword co-occurrence, authorship, and countries/regions activities were extracted, mapped, interpreted, and validated. Additionally, a systematic literature review was conducted to provide comprehensive insights into the existing research on smart sensing technologies and strategies employed to mitigate dioxin emissions from plastic waste incineration. The findings showed that the number of articles and publications on dioxin emissions from plastic waste has rapidly increased since 2005, indicating growing research interest. The main keywords used for the analysis included “air pollutants”, “waste management”, “mass spectrometry”, and “toxicity”. The results of this paper contribute to a broader understanding of the complex relationship between plastics and environmental degradation, facilitating informed decision-making and smart technology integration for a more sustainable future. © 2023 The Authors

关键词： Detection Dioxin Plastic Scientometric analysis Waste

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Counting on AR: EEG responses to incongruent information with real-world context

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computers in Biology and Medicine 2025年 185卷 109483-109483页

作者： Wimmer, Michael Pepicelli, Alex Volmer, Ben ElSayed, Neven Cunningham, Andrew Thomas, Bruce H. Müller-Putz, Gernot R. Veas, Eduardo E. Know Center Research GmbH Graz Austria Institute of Neural Engineering Graz University of Technology Graz Austria Wearable Computer Lab University of South Australia AdelaideSA Australia BioTechMed Graz Austria Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria

Augmented Reality (AR) technologies enhance the real world by integrating contextual digital information about physical entities. However, inconsistencies between physical reality and digital augmentations, which may arise from errors in the visualized information or the user's mental context, can considerably impact user experience. This work characterizes the brain dynamics associated with processing incongruent information within an AR environment. To study these effects, we designed an interactive paradigm featuring the manipulation of a Rubik's cube serving as a physical referent. Congruent and incongruent information regarding the cube's current status was presented via symbolic (digits) and non-symbolic (graphs) stimuli, thus examining the impact of different means of data representation. The analysis of electroencephalographic signals from 19 participants revealed the presence of centro-parietal N400 and P600 components following the processing of incongruent information, with significantly increased latencies for non-symbolic stimuli. Additionally, we explored the feasibility of exploiting incongruency effects for brain-computer interfaces. Hence, we implemented decoders using linear discriminant analysis, support vector machines, and EEGNet, achieving comparable performances with all methods. Therefore, this work contributes to the design of adaptive AR systems by demonstrating that above-chance detection of incongruent information based on physiological signals is feasible. The successful decoding of incongruency-induced modulations can inform systems about the current mental state of users without making it explicit, aiming for more coherent and contextually appropriate AR interactions. © 2024

关键词： Interfaces (computer)

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Tracking-Differentiator-Based Sliding-Mode Control for Tracking Control

Tracking-Differentiator-Based Sliding-Mode Control for Track...

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Chinese Automation Congress (CAC)

作者： Wenfei Li Boyuan Li Wei Hua Chao Huang Haiping Du Haitao Xing Research center for intelligent transportation Zhejiang lab Hangzhou China Department of Industrial & Systems Engineering The Hong Kong Polytechnic University Hong Kong China School of Electrical Computer and Telecommunications Engineering University of Wollongong Wollongong Australia

Tracking control has attracted significant attention because of its close link with industrial applications. Tracking control requires that a control algorithm can ensure that an actuator follows control commands, with a fast response anti-disturbance abilities and small chattering. A tracking-differentiator-based sliding-mode control approach for tracking control is proposed in this paper. A tracking differentiator has the ability to obtain the desired signal's differential signal, even when there is noise in the desired signal. A differential signal is often required in the design of sliding-mode controllers. When tracking differentiator is applied to a sliding-mode controller, the chattering of the control commands (caused by noise disturbance) can be reduced while the fast response of the sliding-mode controller can be maintained. The simulation results show that the proposed controller is effective.

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Screening cognitive impairment in patients with atrial fibrillation: A deep learning model based on retinal fundus photographs

Heart Rhythm O2

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Heart Rhythm O2 2025年第5期6卷 678-686页

作者： Wang, Zhen Li, Mingxiao Xia, Peng Jiang, Chao Shen, Ting Ma, Jiaming Bai, Yu Zhang, Suhui Lai, Yiwei Li, Sitong Xu, Hui Xu, Yang Ma, Tong Ju, Lie He, Liu Dong, Li Sang, Caihua Long, Deyong Chen, Yuzhong Du, Xin Ge, Zongyuan Dong, Jianzeng Wei, Wen-Bin Ma, Changsheng Department of Cardiology Beijing Anzhen Hospital Capital Medical University Beijing China Engineering Research Center of Medical Devices for Cardiovascular Diseases Ministry of Education Capital Medical University Beijing China National Clinical Research Center for Cardiovascular Diseases Beijing China Beijing Airdoc Technology Co. Ltd. Beijing China Department of Electrical and Computer Systems Engineering Faculty of Engineering Monash University Clayton Australia Yale School of Medicine New Haven Connecticut United States School of Clinical Medicine Peking Union Medical College and Chinese Academy of Medical Science Beijing China Beijing Tongren Eye Center Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment Beijing Ophthalmology & Visual Sciences Key Lab Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology Beijing Tongren Hospital Capital Medical University Beijing China Monash e-Research Center Monash University Clayton Australia

Background: Patients with atrial fibrillation (AF) have a higher risk of cognitive impairment (CI). However, complexity of CI diagnosis and lack of simple screening approaches limited early screening and intervention of CI in AF patients. Objective: Our study aimed to develop deep learning models based on fundus photographs for easy screening of CI in AF patients. Methods: From May 2021 to April 2023, patients who completed fundus examination and cognitive function evaluation in the Chinese Atrial Fibrillation Registry Study were included. The training and validation sets were randomly split at an 8:2 ratio. Participants from the Beijing Eye Study served as the external validation set. Different deep learning models were trained, and their CI detection ability was validated. Results: A total of 899 patients in the Chinese Atrial Fibrillation Registry Study were included. In the validation set, the vision-ensemble model based on fundus images alone had an area under the receiver-operating characteristic curve (AUROC) of 0.855 (95% confidence interval 0.816–0.894) for CI screening. The multimodal model (AUROC 0.861, 95% confidence interval 0.823–0.898), based on fundus photographs and 4 clinical variables, performed comparably to the vision-ensemble model. The AUROC of the vision-ensemble model for CI screening achieved 0.773 (95% confidence interval 0.709–0.837) in the external test set. In the saliency map, the vision-ensemble model focused on areas around retinal vessels and the optic disc. Conclusion: A vision-ensemble model based on fundus images might be practical for preliminary screening of CI in AF patients. © 2025 Heart Rhythm Society

关键词： Artificial intelligence Atrial fibrillation Cognitive impairment Deep learning Fundus photography

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ZnS nanolayer coated hollow carbon spheres with enhanced rate and cycling performance for Li-S batteries

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Science China(Technological Sciences) 2022年第2期65卷 272-281页

作者： MENG FanCheng XU Bin LONG Tao CHENG Sheng LI Yong ZHANG YongYi LIU JieHua School of Materials Science and Engineering Engineering Research Centre of High-Performance Copper Alloy Materials and ProcessingMinistry of EducationHefei University of TechnologyHefei 230009China Division of Nanomaterials and Jiangxi Key Lab of Carbonene Materials Suzhou Institute of Nano-Tech and Nano-BionicsNanchangChinese Academy of SciencesNanchang 330200China Instrumental Analysis Centre Hefei University of TechnologyHefei 230009China School of Instrument Science and Opto-electronics Engineering Hefei University of TechnologyHefei 230009China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Advanced Materials DivisionSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China School of Nano-Tech and Nano-Bionics University of Science and Technology of ChinaHefei 230026China

Conductive carbon structure has been considered as a promising sulfur-hosting material as the cathode of lithium-sulfur ***, the issue of polysulfide shuttling requires an additional component to help restrict and convert sulfur ***, in this work, hollow and porous carbon nanospheres(HCS) are synthesized by a template method and a high-temperature carbonization treatment. A thin layer of ZnS coating is then deposited on the HCS-based sulfur(ZnS@HCS/S) cathode with controlled thickness, and the overall electrochemical properties are systematically evaluated. Results show that with 30 nm-thick ZnS coating, the cathode reveals an improved capacity of 1411 m A h g^(-1), and higher capacities from 0.2 to 3 C rate compared with bare HCS/S cathode. Moreover, the ZnS coating also enhances the cycling stability of ZnS@HCS/S cathode over 280 cycles at 0.5 C, with only 0.2% capacity decay per cycle. This work demonstrates potential applications for high-performance lithiumsulfur batteries.

关键词： lithium-sulfur battery ZnS nanolayer hollow carbon sphere rate performance cycling stability

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