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Tracking Nonstationary Streaming Data via Exponentially Weighted Moving Average Stochastic Gradient Descent

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Journal of Systems Science & Complexity 2024年

作者： QIAN Chengde JIANG Haiyan LIANG Decai School of Statistics and Data Science Nankai University department of machine learning Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)

In many applications involving data streams, the sequences of data arise from highly dynamic and often unstable real-life processes, rendering untenable the standard assumption that current and future data come from the same distribution. In response, new methodologies, such as dynamic online learning, have been proposed in order to account for the nonstationary features in the data-generating process. Motivated by the stability and statistical efficiency of the notable stochastic approximation method, average stochastic gradient descent(ASGD) in time-invariant systems, the authors propose an exponentially weighted moving average(EWMA)-based stochastic gradient descent(SGD) which accommodates the dynamic structure by introducing a forgetting factor and replacing the simple averaging step in ASGD with an EWMA step. Provided that the dynamic drift is Lipschitz continuous, the mean squared tracking error rate of the proposed method achieves the optimal rate in the nonparametric statistical paradigm. The proposed framework also allows us to derive the dynamic regret bound and asymptotic normality with a path variation constraint in a natural manner. Numerical analysis has been conducted to verify the performance of the proposed method. In particular, the proposed method is much more robust to the selection of learning rates compared with the ordinary SGD method.

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Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 37-57页

作者： Zhiqiang Pu Yi Pan Shijie Wang Boyin Liu Min Chen Hao Ma Yixiong Cui the School of artificial intelligence University of Chinese Academy of Sciences the Institute of Automation Chinese Academy of Sciences the Nanjing artificial intelligence Research of IA the School of Sports engineering Beijing Sport University

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) *** addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

关键词： artificial intelligence(AI) decision-making football review soccer sports analytics

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Design of Protograph LDPC-Coded MIMO-VLC Systems with Generalized Spatial Modulation

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China Communications 2024年第3期21卷 118-136页

作者： Dai Lin Fang Yi Guan Yongliang Mohsen Guizani School of Information engineering Guangdong University of TechnologyGuangzhou 51006China The State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710126China School of Electrical and Electronic engineering Nanyang Technological UniversitySingapore department of machine learning Mohamed Bin Zayed University of Artificial Intelligence(MBZUAI)Abu DhabiUnited Arab Emirates

This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC ***, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.

关键词： bit-interleaved coded modulation generalized spatial modulation multiple-input multipleoutput protograph LDPC codes visible light communication

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A Framework for Enhancing Privacy and Anonymity in Blockchain-Enabled IoT Devices

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Computers, Materials & Continua 2024年第3期78卷 4263-4282页

作者： Muhammad Saad Muhammad Raheel Bhutta Jongik Kim Tae-Sun Chung department of artificial intelligence Ajou UniversitySuwon443-749Korea department of Electrical and Computer engineering University of Utah Asia CampusIncheon21985Korea department of artificial intelligence Chungnam National UniversityDaejeon34134Korea

With the increase in IoT(Internet of Things)devices comes an inherent challenge of *** the world today,privacy is the prime concern of every *** one’s privacy and keeping anonymity throughout the system is a desired functionality that does not come without inevitable trade-offs like scalability and increased complexity and is always exceedingly difficult to *** challenge is keeping confidentiality and continuing to make the person innominate throughout the *** address this,we present our proposed architecture where we manage IoT devices using blockchain *** proposed architecture works on and off blockchain integrated with the closed-circuit television(CCTV)security camera fixed at the rental *** this framework,the CCTV security camera feed is redirected towards the owner and renter based on the smart contract *** entity(owner or renter)can see the CCTV security camera feed at one *** is no third-party dependence except for the CCTV security camera deployment *** contributions include the proposition of framework architecture,a novel smart contract algorithm,and the modification to the ring signatures leveraging an existing cryptographic *** are made based on different systems’security and key management *** an empirical study,our proposed algorithm performed better in key generation,proof generation,and verification *** comparing similar existing schemes,we have shown the proposed architectures’*** now,we have developed this system for a specific area in the real ***,this system is scalable and applicable to other areas like healthcare monitoring systems,which is part of our future work.

关键词： Privacy anonymity blockchain IoT smart contracts

No Reference Image Sharpness Assessment Based on Global Color Difference Variation

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Chinese Journal of Electronics 2024年第1期33卷 293-302页

作者： Chenyang SHI Yandan LIN School of artificial intelligence Anhui Polytechnic University School of Mechanical engineering Anhui Polytechnic University department of Light Sources and Illuminating engineering Fudan University Academy for engineering & Technology Fudan University

Image quality assessment(IQA) model is designed to measure the image quality in consistent with subjective ratings by computational models. In this research, a valid no reference IQA(NR-IQA) model for color image sharpness assessment is proposed based on local color difference map in a color space. In the proposed model, the absolute color difference variation and relative color difference variation are combined to evaluate sharpness in YIQ color space(a color coordinate system for the development of the United States color television system). The difference between sharpest and blurriest spot of an image is represented by the absolute color difference variation, and relative color difference variation expresses the variation in the image content. Extensive experiments are performed on five publicly available benchmark synthetic blur databases and two real blur databases, and the results prove that the proposed model work better than the other state-of-the-art and latest NR-IQA models for the prediction accuracy on blurry images. Besides, the model maintains the lowest computational complexity.

关键词： Image quality TV Image color analysis Databases Computational modeling Color Predictive models

Block Incremental Dense Tucker Decomposition with Application to Spatial and Temporal Analysis of Air Quality Data

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Computer Modeling in engineering & Sciences 2024年第4期139卷 319-336页

作者： SangSeok Lee HaeWon Moon Lee Sael department of artificial intelligence Ajou UniversitySuwon-si16499Korea department of Software and Computer engineering Ajou UniversitySuwon-si16499Korea

How can we efficiently store and mine dynamically generated dense tensors for modeling the behavior of multidimensional dynamic data?Much of the multidimensional dynamic data in the real world is generated in the form of time-growing *** example,air quality tensor data consists of multiple sensory values gathered from wide locations for a long *** data,accumulated over time,is redundant and consumes a lot ofmemory in its raw *** need a way to efficiently store dynamically generated tensor data that increase over time and to model their behavior on demand between arbitrary time *** this end,we propose a Block IncrementalDense Tucker Decomposition(BID-Tucker)method for efficient storage and on-demand modeling ofmultidimensional spatiotemporal *** that tensors come in unit blocks where only the time domain changes,our proposed BID-Tucker first slices the blocks into matrices and decomposes them via singular value decomposition(SVD).The SVDs of the time×space sliced matrices are stored instead of the raw tensor blocks to save *** modeling from data is required at particular time blocks,the SVDs of corresponding time blocks are retrieved and incremented to be used for Tucker *** factor matrices and core tensor of the decomposed results can then be used for further data *** compared our proposed BID-Tucker with D-Tucker,which our method extends,and vanilla Tucker *** show that our BID-Tucker is faster than both D-Tucker and vanilla Tucker decomposition and uses less memory for storage with a comparable reconstruction *** applied our proposed BID-Tucker to model the spatial and temporal trends of air quality data collected in South Korea from 2018 to *** were able to model the spatial and temporal air quality *** were also able to verify unusual events,such as chronic ozone alerts and large fire events.

关键词： Dynamic decomposition tucker tensor tensor factorization spatiotemporal data tensor analysis air quality

Grasp Detection with Hierarchical Multi-Scale Feature Fusion and Inverted Shuffle Residual

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Tsinghua Science and Technology 2024年第1期29卷 244-256页

作者： Wenjie Geng Zhiqiang Cao Peiyu Guan Fengshui Jing Min Tan Junzhi Yu State Key Laboratory of Multimodal artificial intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of artificial intelligence University of Chinese Academy of SciencesBeijing 100049China department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Grasp detection plays a critical role for robot *** pixel-wise grasp detection networks with encoder-decoder structure receive much attention due to good accuracy and ***,they usually transmit the high-level feature in the encoder to the decoder,and low-level features are *** is noted that low-level features contain abundant detail information,and how to fully exploit low-level features remains ***,the channel information in high-level feature is also not well ***,the performance of grasp detection is *** solve these problems,we propose a grasp detection network with hierarchical multi-scale feature fusion and inverted shuffle *** low-level and high-level features in the encoder are firstly fused by the designed skip connections with attention module,and the fused information is then propagated to corresponding layers of the decoder for in-depth feature *** a hierarchical fusion guarantees the quality of grasp ***,an inverted shuffle residual module is created,where the high-level feature from encoder is split in channel and the resultant split features are processed in their respective *** such differentiation processing,more high-dimensional channel information is kept,which enhances the representation ability of the ***,an information enhancement module is added before the encoder to reinforce input *** proposed method attains 98.9%and 97.8%in image-wise and object-wise accuracy on the Cornell grasping dataset,respectively,and the experimental results verify the effectiveness of the method.

关键词： grasp detection hierarchical multi-scale feature fusion skip connections with attention inverted shuffle residual

Lower limb suspension induces threshold-specific alterations of motor units properties that are reversed by active recovery

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Journal of Sport and Health Science 2024年第2期13卷 264-276页

作者： Giacomo Valli Fabio Sarto Andrea Casolo Alessandro Del Vecchio Martino V.Franchi Marco V.Narici Giuseppe De Vito department of Biomedical Sciences University of PadovaPadova 35131Italy department artificial intelligence in Biomedical engineering Friedrich-Alexander UniversityErlangen-Nurnberg 91052Germany

Purpose:This study aimed to non-invasively test the hypothesis that(a) short-term lower limb unloading would induce changes in the neural control of force production(based on motor units(MUs) properties) in the vastus lateralis muscle and(b) possible changes are reversed by active recovery(AR).Methods:Ten young males underwent 10 days of unilateral lower limb suspension(ULLS) followed by 21 days of *** ULLS,participants walked exclusively on crutches with the dominant leg suspended in a slightly flexed position(15°-20°) and with the contralateral foot raised by an elevated *** AR was based on resistance exercise(leg press and leg extension) and executed at 70% of each participant’s 1repetition maximum,3 times/*** voluntary isometric contraction(MVC) of knee extensors and MUs properties of the vastus lateralis muscle were measured at baseline,after ULLS,and after *** were identified using high-density electromyography during trapezoidal isometric contractions at 10%,25%,and 50% of the current MVC,and individual MUs were tracked across the 3 data collection ***:We identified 1428 unique MUs,and 270 of them(18.9%) were accurately *** ULLS,MVC decreased by 29.77%,MUs absolute recruitment/derecruitment thresholds were reduced at all contraction intensities(with changes between the 2 variables strongly correlated),while discharge rate was reduced at 10% and 25% but not at 50% *** MVC and MUs properties fully recovered to baseline levels after *** changes were observed in the pool of total as well as tracked ***:Our novel results demonstrate,non-invasively,that 10 days of ULLS affected neural control predominantly by altering the discharge rate of lower-threshold but not of higher-threshold MUs,suggesting a preferential impact of disuse on motoneurons with a lower depolarization ***,after 21 days of AR,the impaired MUs properties were fully restored to baseline levels,highlighting the plas

关键词： Disuse High-density EMG Muscle disuse Neural impairment Neuromuscular degeneration

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Scattering-based hybrid network for facial attribute classification

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Frontiers of Computer Science 2024年第3期18卷 105-116页

作者： Na LIU Fan ZHANG Liang CHANG Fuqing DUAN School of artificial intelligence Beijing Normal UniversityBeijing 100875China

Face attribute classification(FAC)is a high-profile problem in biometric verification and face *** recent research has been devoted to extracting more delicate image attribute features and exploiting the inter-attribute correlations,significant challenges still *** scattering transform(WST)is a promising non-learned feature *** has been shown to yield more discriminative representations and outperforms the learned representations in certain *** to the image classification task,WST can enhance subtle image texture information and create local deformation *** paper designs a scattering-based hybrid block,to incorporate frequency-domain(WST)and image-domain features in a channel attention manner(Squeezeand-Excitation,SE),termed WS-SE *** with CNN,WS-SE achieves a more efficient FAC performance and compensates for the model sensitivity of the small-scale affine *** addition,to further exploit the relationships among the attribute labels,we propose a learning strategy from a causal *** cause attributes defined using the causalityrelated information can be utilized to infer the effect attributes with a high confidence *** analysis experiments demonstrate the effectiveness of our model,and our hybrid model obtains state-of-the-art results in two public datasets.

关键词： wavelet scattering transform causality-related learning facial attribute classification