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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Xiaohai Dai Bin Xiao Jiang Xiao Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computing The Hong Kong Polytechnic University Hong Kong

It has been recognized that one of the bottlenecks in the UTXO-based blockchain systems is the slow block validation - the process of validating a newly-received block by a node before locally storing it and further broadcasting it. As a block contains multiple inputs, the block validation mainly involves checking the inputs against the status data, which is also known as the Unspent Transaction Outputs (UTXO) set. As time goes by, the UTXO set becomes more and more expansive, most of which can only be stored on disks. This considerably slows down the input checking and thus block validation, which can potentially compromise system security. To deal with the above problem, we disassemble the function of input checking into three parts: existence validation (EV), unspent validation (UV), and script validation (SV). Based on the disassembly, we propose EBV, an efficient block validation mechanism to speed up EV, UV, and SV individually. First, EBV changes the representation of status data, from UTXO set to a bit-vector set, which drastically reduces its size. The smaller status data can be entirely maintained in memory, thereby accelerating UV and also block validation. Second, EBV requires each transaction to carry the proof data, which enables EV and SV without accessing the disks. Furthermore, we also cope with two challenges in the design of EBV, namely transaction inflation and fake positions. To evaluate the EBV mechanism, we implement a prototype on top of Bitcoin, the most widely known UTXO-based blockchain, and conduct extensive experiments to compare EBV and Bitcoin. The experimental results demonstrate that EBV successfully reduces the memory requirement by 93.1 % and the block validation time by up to 93.5%.

关键词： Distributed processing Memory management Prototypes Bitcoin Broadcasting Blockchains Delays

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NeuroHeed: Neuro-Steered Speaker Extraction using EEG Signals

arXiv

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arXiv 2023年

作者： Pan, Zexu Borsdorf, Marvin Cai, Siqi Schultz, Tanja Li, Haizhou The Integrative Sciences and Engineering Programme the Institute of Data Science National University of Singapore 119077 Singapore The Machine Listening Lab the University of Bremen Bremen28359 Germany The Department of Electrical and Computer Engineering National University of Singapore 119077 Singapore The Cognitive System Lab the University of Bremen Bremen28359 Germany The School of Data Science The Chinese University of Hong Kong Shenzhen518172 China The Machine Listening Lab University of Bremen Bremen28359 Germany

Humans possess the remarkable ability to selectively attend to a single speaker amidst competing voices and background noise, known as selective auditory attention. Recent studies in auditory neuroscience indicate a strong correlation between the attended speech signal and the corresponding brain’s elicited neuronal activities, which the latter can be measured using affordable and non-intrusive electroencephalography (EEG) devices. In this study, we present NeuroHeed, a speaker extraction model that leverages EEG signals to establish a neuronal attractor which is temporally associated with the speech stimulus, facilitating the extraction of the attended speech signal in a cocktail party scenario. We propose both an offline and an online NeuroHeed, with the latter designed for real-time inference. In the online NeuroHeed, we additionally propose an autoregressive speaker encoder, which accumulates past extracted speech signals for self-enrollment of the attended speaker information into an auditory attractor, that retains the attentional momentum over time. Online NeuroHeed extracts the current window of the speech signals with guidance from both attractors. Experimental results demonstrate that NeuroHeed effectively extracts brain-attended speech signals, achieving high signal quality, excellent perceptual quality, and intelligibility in a two-speaker scenario. Copyright © 2023, The Authors. All rights reserved.

关键词： Extraction

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Visible Light Positioning Based on a Single Luminaire: A Novel Visual Odometry Assisted Algorithm

Visible Light Positioning Based on a Single Luminaire: A Nov...

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IEEE International Conference on Communications (ICC)

作者： Zhiyu Zhu Yang Yang Mingzhe Chen Caili Guo Yipeng Bai Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Visible light positioning (VLP) is a promising positioning technique, which, however, typically requires multiple luminaires to achieve accurate positioning. This paper proposes a novel visual odometry (VO) assisted visible light positioning algorithm (VO-VLP) in achieving positioning with only a single luminaire. In the considered model, a user equipped with a camera jointly uses geometric features in the captured images and coordinates information obtained via visible light communication (VLC) for positioning. The proposed VLP algorithm does not rely on any extra inertial measurement unit and relaxes the tilted angle limitation at the user. In particular, VO-VLP first uses the circle feature of a luminaire to obtain dual normal vectors of the luminaire. Then, the basic principle of VO is used to eliminate the wrong normal vector by exploiting the geometric features in two consecutive images captured when the user moves. Finally, the pose and location of the user are obtained by using an artificially marked point on the luminaire's contour. VO-VLP can achieve accurate positioning with only a single luminaire and a camera. Simulation results show that the proposed indoor positioning algorithm can achieve a 97th-percentile positioning accuracy of around 10 cm.

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Online News Extraction and Multiclass Classification Using Linear Support Vector Machines

Online News Extraction and Multiclass Classification Using L...

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International Conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Apoorva Gupta Smriti Arora Niyati Baliyan Data Science Team Barclays UK Knutsford England Computer Science and Infromation System Birla Institute of Technology and Science Pilani India Computer Engineering Department National Institute of Technology Kurukshetra Kurukshetra India

Online news articles, blogs, sites are a rich source of diverse text-based data. However, the data contained in these sources cannot be manually extricated, recorded, and listed because it comes in colossal size. Accurate mapping of precise news into their corresponding category is challenging in these times. Several methods have been proposed over time for news classification when training documents for each predefined class are present readily, however such methods were tried and tested upon a small dataset. With the underlying research, the aim is to propose a method that can be used when lakhs and lakhs of instances are present. This research analysis involves the task of news classification using multiclass classifiers - OneVsRest and OneVsOne classifiers over the Linear Support Vector Classification to learn the performance of multiclass news categorization. The proposed methodology “Keyword Based Classification Technique (KBCT)” in this study was executed and concluded using Python and deployed using Google Colaboratory. The result was expressed using four distinguished news classes over a multivariate dataset of 422419 instances from the uci-news-aggregator dataset. The OneVsRestClassifier's accuracy was computed to be 95.76% that was 0.09% more than the OneVsOneClassifier's accuracy of 95.67%. The proposed prototype was compared with some of the related studies and algorithms, and the outcomes produced by the OneVsRest model were the most optimum in terms of accuracy.

关键词： Training Prototypes Support vector machine classification Organizations Search engines Real-time systems Internet

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Improving Routing Decision Algorithm for RPL Networks

Improving Routing Decision Algorithm for RPL Networks

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International Conference on Information Technology (ICIT)

作者： Abdullah Al Zaqebah Omar Almomani Malek Almomani Adeeb Alsaaidah Ahmad Adel Abu-Shareha Ahmad Althunibat Department of Computer Science The World IslamicSciences and Education University Amman Jordan Department of Information System and Networks The World Islamic Sciences and Education University Amman Jordan Software Engineering The World Islamic Sciences and Education University Amman Jordan Department of Networks and Information Security Al-Ahliyya Amman University Amman Jordan Department of Data Science and Artificial Intelligence Al-Ahliyya Amman University Amman Jordan Department of Software Engineering Al-Zaytoonah University of Jordan Amman Jordan

Low Power Networks are spreading worldwide, seeking to enable small devices to join wireless networks. This requires a routing mechanism that makes it possible and seamless. This research aims to create a Low Power and Lossy Networks (RPL) routing protocol that balances power usage and node dependability. The main emphasis of the algorithm presented here is the choice made by network nodes (Zigbees) regarding which path to deliver the message along. Results for this routing technique seem promising. Utilizing it increased packet transfer reliability while enforcing power conservation. Furthermore, a 10% reduction in the network's overall power consumption was made.

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Enhanced surface water-energy coupling on the Tibetan Plateau over the past six decades (1960–2020)

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Fundamental Research 2024年

作者： Yang, Kun Sun, Jing Lu, Hui McColl, Kaighin A. Jiang, Yaozhi He, Qing Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University Beijing 100084 China National Tibetan Plateau Data Center State Key Laboratory of Tibetan Plateau Earth System Science Environment and Resources Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing 100101 China Department of Earth and Planetary Sciences Harvard University Cambridge 02138 MA United States School of Engineering and Applied Sciences Harvard University Cambridge 02138 MA United States River and Environmental Engineering Laboratory The University of Tokyo Tokyo 113 8656 Japan

Long-term changes in surface water and energy budgets on the Tibetan Plateau (TP) are essential for understanding the variability of the Asian summer monsoon and water resources. The water budget and energy budget are inherently coupled, and in this study evaporative fraction (EF, the proportion of the surface available energy used for evapotranspiration) is used to quantify their coupling strength and simultaneously study its response to climate change in the TP. A so-called ‘surface flux equilibrium’ (SFE) method that uses only air temperature and humidity as inputs to estimate EF is evaluated and adopted for understanding EF variability in the TP during the warm season of the past six decades (1960–2020). The results show an overall increase in EF of the TP, but this increase is not uniform, instead comprising three distinct stages of change, i.e., little change until the 1980s, a significant increase in the next two decades, and a slight but insignificant decrease in the last two decades. Accordingly, evapotranspiration has undergone similar decadal changes over this period. More importantly, there is a spatial pattern of the response to climate change, showing a stronger enhancement of EF in the west TP than in the east TP during 1979–2020. This response pattern shows a weakened contrast in the surface water cycle between the dry west and the wet east TP. The enhanced coupling and diminished spatial contrast may provide a perspective for understanding spatiotemporal changes in environment and ecology. Finally, it is worth pointing out that given the simplicity of the SFE method, it is expected that it can be applied in climate-sensitive regions outside the TP. © 2024

关键词： Climate change Evaporative fraction Spatial pattern Surface flux equilibrium Tibetan Plateau Water-energy coupling

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Continual Reinforcement Learning for Digital Twin Synchronization Optimization

arXiv

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arXiv 2025年

作者： Tong, Haonan Chen, Mingzhe Zhao, Jun Hu, Ye Yang, Zhaohui Liu, Yuchen Yin, Changchuan The Beijing Key Laboratory of Network System Architecture and Convergence The Beijing Advanced Information Network Laboratory Beijing University of Posts and Telecommunications Beijing China Singapore The Department of Electrical and Computer Engineering Frost Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Department of Industrial and Systems Engineering University of Miami Coral GablesFL33146 United States The College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China The Department of Computer Science North Carolina State University RaleighNC27695 United States The Beijing Key Laboratory of Network System Architecture and Convergence China The Beijing Advanced Information Network Laboratory Beijing University of Posts and Telecommunications Beijing100876 China

This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base station (BS) continuously collects factory physical object state data from wireless devices to build a real-time virtual DT system for factory event analysis. Due to continuous data transmission, maintaining DT synchronization must use extensive wireless resources. To address this issue, a subset of devices is selected to transmit their sensing data, and resource block (RB) allocation is optimized. This problem is formulated as a constrained Markov process (CMDP) problem that minimizes the long-term mismatch between the physical and virtual systems. To solve this CMDP, we first transform the problem into a dual problem that refines RB constraint impacts on device scheduling strategies. We then propose a continual reinforcement learning (CRL) algorithm to solve the dual problem. The CRL algorithm learns a stable policy across historical experiences for quick adaptation to dynamics in physical states and network capacity. Simulation results show that the CRL can adapt quickly to network capacity changes and reduce normalized root mean square error (NRMSE) between physical and virtual states by up to 55.2%, using the same RB number as traditional methods. © 2025, CC BY-NC-SA.

关键词： Markov processes

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Dynamic Searchable Scheme with Forward Privacy for Encrypted Document Similarity

Dynamic Searchable Scheme with Forward Privacy for Encrypted...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Mustafa A. Al Sibahee Chengwen Luo Jin Zhang Yijing Huang Zaid Ameen Abduljabbar National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen PR China College of Computer Science and Software Engineering Shenzhen University Shenzhen PR China Computer Technology Engineering Department Iraq University College Basrah Iraq Department of Computer Science College of Education for Pure Sciences University of Basrah Basrah Iraq Shenzhen Institute Huazhong University of Science and Technology Shenzhen PR China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Document retrieval plays an essential role in many real-world applications especially when the data storage is outsourced. Due to the great advantages offered by cloud computing, clients tend to outsource their personal data to remote servers maintained by external service providers. This raises serious privacy concerns about outsourced data because such providers are usually considered untrusted entities. The majority of previous schemes of document similarity search share the same limitation: they focus mainly on static collections. Dynamic searchable schemes (DSE) allow adding or removing documents at the expense of more leakage than static schemes. To thwart certain attacks, DSE schemes should support forward privacy property, which ensures that newly added documents cannot be related to previously issued search queries. We design and implement dynamic secure similarity search schemes with forward privacy for textual documents utilizing simhash method for hamming similarity. Our scheme provides an efficient search time and a sufficient level of privacy. To show the practicality of our proposed scheme, we performed excremental results with large document collections.

关键词： Privacy data privacy Cloud computing Memory Search problems Cryptography Servers

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High-resolution mapping of CH4/N2O emissions from industrialization-related anthropogenic sources in China

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National Science Review 2025年第4期 13-15页

作者： Ziyang Lou Haoyu Zhang Xu Zhao Qiang Liu Minqi Liang Hui Wang Huiwen Yang Bofeng Cai Jingyi Lu Ying Cui Jingyi Wu Fei Teng Xiao Lu Wenping Yuan Mengyao Liu Shanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery School of Environmental Science & Engineering Shanghai Jiao Tong University China-UK Low Carbon College Shanghai Jiao Tong University China Institute for Urban Governance Shanghai Jiao Tong University Institute of Blue and Green Development Shandong University Institute of Energy Environment and Economy Tsinghua University School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Center for Climate Change and Environmental Policy Chinese Academy for Environmental Planning School of College of Environmental and Chemical Engineering Shanghai University of Electric Power Institute of Carbon Neutrality Sino-French Institute for Earth System Science College of Urban and Environmental Sciences Peking University Satellite Observation Department Royal Netherlands Meteorological Institute

CH4and N2O are critical non-CO2greenhouse gases（GHGs） that collectively contribute to more than one-quarter of anthropogenic global warming, accounting for ～35%–45% of the total climate forcing [1]. China is the world's largest emitter of CH4and N2O,accounting for 17.88% and 16.67% of global emissions, respectively [2]. As the largest developing and industrial country, China has the most comprehensive industrial supply chain globally, resulting in huge energy consumption,

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Fusing Bluetooth with Pedestrian Dead Reckoning: A Floor Plan-Assisted Positioning Approach

arXiv

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arXiv 2025年

作者： Pan, Wenxuan Yang, Yang Chen, Mingzhe Wei, Dong Guo, Caili Mao, Shiwen Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering the Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Wireless Engineering Research and Education Center Auburn University AuburnAL36849 United States

Floor plans can provide valuable prior information that helps enhance the accuracy of indoor positioning systems. However, existing research typically faces challenges in efficiently leveraging floor plan information and applying it to complex indoor layouts. To fully exploit information from floor plans for positioning, we propose a floor plan-assisted fusion positioning algorithm (FP-BP) using Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). In the considered system, a user holding a smartphone walks through a positioning area with BLE beacons installed on the ceiling, and can locate himself in real time. In particular, FP-BP consists of two phases. In the offline phase, FP-BP programmatically extracts map features from a stylized floor plan based on their binary masks, and constructs a mapping function to identify the corresponding map feature of any given position on the map. In the online phase, FP-BP continuously computes BLE positions and PDR results from BLE signals and smartphone sensors, where a novel grid-based maximum likelihood estimation (GML) algorithm is introduced to enhance BLE positioning. Then, a particle filter is used to fuse them and obtain an initial estimate. Finally, FP-BP performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a real-time mean positioning accuracy of 1.19 m, representing an improvement of over 28% compared to existing floor plan-fused baseline algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Photomapping

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