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2005 International Conference on Communications, Circuits and Systems

作者： Xu, Li-Bo Wu, Guo-Xin Li, Jian-Fei Key Laboratory of Computer Network and Information Integration Southeast University Nanjing 210096 China

ISBN: (纸本)0780390156

In high-speed Internet links, effective and efficient packet sampling technology in traffic measurement becomes more and more indispensable for its benefits of reducing data quantity and saving various resources. We address the Issue of how to keep or improve sampling accuracy during burst or fluctuation periods. In the paper, an adaptive packet-level sampling method on different traffic fluctuation and burst scales is proposed. The method can dynamically adjust each packet sampling probability dependent on the magnitude of traffic fluctuation. The adjustment granularity is fine because it reaches single packet. By contrast to static random sampling method in experiments using real traffic trace, we show that the proposed adaptive sampling has great capability to trace traffic fluctuations and Improve sampling accuracy through capturing more fluctuation or burst details. © 2005 IEEE.

关键词： Telecommunication traffic

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MSPL: Multi-modal Statistical Prompt Learning for New Energy Equipment Defect Recognition

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IEEE Internet of Things Journal 2025年

作者： Wang, Zhenwei Wang, Pengfei Han, Guangjie Zhou, Chengjie Lin, Qing Zhang, Jianxin Fan, Guangjie Zhang, Qiang Dalian University of Technology School of Computer Science and Technology Dalian116024 China Dalian116024 China Shenyang Huayan Electric Technology Co Ltd Shenyang110180 China Hohai University Key Laboratory of Maritime Intelligent Network Information Technology Ministry of Education China Deputy Director of the Yantai Big Data Center and Senior Engineer Yantai264003 China Dalian Minzu University School of Computer Science and Engineering Dalian116600 China

Monitoring renewable energy devices is crucial for the timely detection of faults and the improvement of system stability, making it a key component of the Internet of Things (IoT) ecosystem. However, existing intelligent algorithms and IoT methods rely on edge devices with limited computational capacity, which requires balancing real-time performance and accuracy. Additionally, most methods require initial training on large-scale data using cloud platforms or high-performance servers, leading to high initial costs. To address these challenges, we propose Multi-modal Statistical Prompt Learning (MSPL) for new energy equipment defect recognition on IoT edge devices. This method enables rapid learning with only a few samples, avoiding the need for large-scale centralized training. Specifically, MSPL uses the pre-trained Contrastive Language-Image Pre-training model as its backbone, leveraging text-based conceptual information to enhance the understanding of visual inputs. A Statistical Query (SQ) module is implemented at the end of the backbone to extract distinctive features from the outputs, integrating these features with soft prompts to customize them for the defect recognition task. Since the learnable parameters are limited to soft prompts added at the end of the backbone, MSPL restricts gradient backpropagation to this point. This improves parameter and memory efficiency, making it more suitable for scenarios with limited computational capacity on IoT edge devices. Experimental results of MSPL on two renewable energy equipment defect datasets and edge devices indicate that it meets real-time processing requirements while maintaining high accuracy, outperforming other methods. © 2025 IEEE.

关键词： Zero-shot learning

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PBNA: An Improved Probabilistic Biological network Alignment Method

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Tsinghua Science and Technology 2014年第6期19卷 658-667页

作者： Muwei Zhao Wei Zhong Jieyue He School of Computer Science and Engineering and also with MOE Key Laboratory of Computer Network and Information IntegrationSoutheast University Division of Math and Computer Science University of South Carolina Upstate Spartanburg SC 29303USA

Biological network alignment is an important research topic in the field of bioinformatics. Nowadays almost every existing alignment method is designed to solve the deterministic biological network alignment ***, it is worth noting that interactions in biological networks, like many other processes in the biological realm,are probabilistic events. Therefore, more accurate and better results can be obtained if biological networks are characterized by probabilistic graphs. This probabilistic information, however, increases difficulties in analyzing networks and only few methods can handle the probabilistic information. Therefore, in this paper, an improved Probabilistic Biological network Alignment（PBNA） is proposed. Based on Iso Rank, PBNA is able to use the probabilistic information. Furthermore, PBNA takes advantages of Contributor and Probability Generating Function（PGF） to improve the accuracy of node similarity value and reduce the computational complexity of random variables in similarity matrix. Experimental results on dataset of the Protein-Protein Interaction（PPI） networks provided by Todor demonstrate that PBNA can produce some alignment results that ignored by the deterministic methods, and produce more biologically meaningful alignment results than Iso Rank does in most of the cases based on the Gene Ontology Consistency（GOC） measure. Compared with Prob method, which is designed exactly to solve the probabilistic alignment problem, PBNA can obtain more biologically meaningful mappings in less time.

关键词： probabilistic biological network network alignment protein interaction network

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Wireless sensor network-enabled intravenous infusion monitoring

Wireless sensor network-enabled intravenous infusion monitor...

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作者： Zhang, Y. Zhang, S.F. Ji, Y. Wu, G.X. Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China

Considering that intravenous in blood infusion, usually applied without a proper control of the progress and velocity under unreliable manual monitoring practice, is the most popular and frequent clinical activity throughout the world, which can potentially endanger a patient's life, leads to a huge burden as patients, relatives and nursing staff can cause serious cases of medical negligence. In order to resolve this problem and provide a networkable solution the authors propose a novel radio frequency identification-based wireless sensor networkable intravenous infusion monitoring system. The proposed system is a wireless sensor system based on taking a fork-type light barrier as a sensor, a micro-control unit (MCU) as a ZigBee-based radio frequency device. The system's performance is evaluated through some laboratory experiments using tuning algorithm to demonstrate that the results show the required accuracy of the system to meet practical needs. © 2011 The Institution of Engineering and Technology.

关键词： Zigbee

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Efficient Asynchronous Uplink Sensing in Perceptive Mobile networks via Accurate Delay Estimation

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IEEE Transactions on Cognitive Communications and networking 2025年

作者： Li, Hang Teng, Fuxian Guo, Qinghua Zhang, J. Andrew Huang, Xiaojing Cheng, Zhiqun Hangzhou Dianzi University School of Electronics and Information Hangzhou310018 China Academy of Network and Communications of CETC National Key Laboratory of Advanced Communication Networks Hebei Shijiazhuang050081 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia University of Technology Sydney Global Big Data Technologies Centre UltimoNSW2007 Australia

In perceptive mobile networks (PMNs) with integrated sensing and communication (ISAC), sensing ambiguity in ranging and velocity measurements can be caused by timing offsets (TOs) and carrier frequency offsets (CFOs) between asynchronous sensing transmitter and receiver. In this paper, we propose an efficient method for uplink sensing with asynchronous transceivers, via accurately estimating path delays including TOs. Firstly, we develop a sparse signal recovery model to decouple multiple sensing parameters, i.e., delay, angle of arrival (AoA) and Doppler for multipath, facilitating efficient and low-complexity sensing parameter estimation. Then, leveraging unitary approximate message passing (UAMP) and sparse Bayesian learning (SBL), we obtain initial delay and signal estimates, which are then refined through Gauss-Seidel iteration. Finally, we conduct estimation and association of the remaining sensing parameters by coherently processing cross-correlation of received signals across the spatial and temporal domains. This effectively removes the sensing ambiguity incurred by time-varying TOs and CFOs, enabling accurate estimation of range and velocity for multiple targets. Simulation results verify the effectiveness of the proposed method, demonstrating its superior sensing performance, compared to existing methods such as cross-antenna cross correlation (CACC). © 2015 IEEE.

关键词： Frequency allocation

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A structured P2P system with match path and probability balance tree

A structured P2P system with match path and probability bala...

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First International Multi- Symposiums on computer and Computational Sciences, IMSCCS'06

作者： Xu, L.B. Wu, G.X. You, F.Q. Key Laboratory of Computer Network and Information Integration Southeast University Nanjing 210096 China

ISBN: (纸本)0769525814

Excellent P2P network infrastructure should support scalability and efficient search simultaneity. The intelligent routing mechanisms have flexible query expression but hold low scalability and recall rate. Contrastively, DHTs are scalable but either difficult to organize or too expensive for maintenance. A new structured P2P model is proposed in which resource storages are organized by match path and random access method. When an approximately balance distributed character is obtained, nodes will keep high search efficiency and low maintenance cost. The system supports various query models, has load balancing capability and high scalability, and ensures search range of each node can cover entire network. The system runs without any center service while all nodes simultaneously take index storage, data storage and routing task to drive network by only maintaining a little local information. © 2006 IEEE.

关键词： Distributed computer systems

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Label distribution learning for scene text detection

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Frontiers of computer Science 2023年第6期17卷 5-12页

作者： Haoyu MA Ningning LU Junjun MEI Tao GUAN Yu ZHANG Xin GENG School of Computer Science and Engineering and the Key Lab of Computer Network and Information Integration(Ministry of Education)Southeast UniversityNanjing 211189China ZTE Corporation Nanjing 210012China

Recently,segmentation-based scene text detection has drawn a wide research interest due to its flexibility in describing scene text instance of arbitrary shapes such as curved ***,existing methods usually need complex post-processing stages to process ambiguous labels,i.e.,the labels of the pixels near the text boundary,which may belong to the text or *** this paper,we present a framework for segmentation-based scene text detection by learning from ambiguous *** use the label distribution learning method to process the label ambiguity of text annotation,which achieves a good performance without using additional post-processing *** on benchmark datasets demonstrate that our method produces better results than state-of-the-art methods for segmentation-based scene text detection.

关键词： scene text detection multi-task learning label distribution learning

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Design and Analysis of a Multiscale Active Queue Management Scheme

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Journal of computer Science & Technology 2006年第6期21卷 1022-1030页

作者：纪其进董永强 School of Computer Science and Engineering Southeast University Nanjing 210096 P.R. China Key Laboratory of Computer Network and Information Integration of Ministry of Education Southeast University Nanjing 210096 P.R China

Since Internet is dominated by TCP-based applications, active queue management （AQM） is considered as an effective way for congestion control. However, most AQM schemes suffer obvious performance degradation with dynamic traffic. Extensive measurements found that Internet traffic is extremely bursty and possibly self-similar. We propose in this paper a new AQM scheme called multiscale controller （MSC） based on the understanding of traffic burstiness in multiple time scale. Different from most of other AQM schemes, MSC combines rate-based and queue-based control in two time scales. While the rate-based dropping on burst level （large time scales） determines the packet drop aggressiveness and is responsible for low and stable queuing delay, good robustness and responsiveness, the queue-based modulation of the packet drop probability on packet level （small time scales） will bring low loss and high throughput. Stability analysis is performed based on a fluid-flow model of the TCP/MSC congestion control system and simulation results show that MSC outperforms many of the current AQM schemes.

关键词： active queue management multiscale traffic burstiness fluid-flow model stability analysis

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An Efficient Direct Downlink Sensing Method Using 5G NR SSB Signals in Perceptive Mobile networks

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IEEE Internet of Things Journal 2025年

作者： Li, Hang Xiang, Yang Guo, Qinghua Liu, Lizhe Huang, Xiaojing Cheng, Zhiqun Pang, Yashan Hangzhou Dianzi University School of Electronics and Information Hangzhou310018 China Academy of Network and Communications of CETC National Key Laboratory of Advanced Communication Networks Hebei Shijiazhuang050081 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia University of Technology Sydney Global Big Data Technologies Centre UltimoNSW2007 Australia

In perceptive mobile networks (PMNs), using 5G New Radio (NR) signals for direct sensing poses a significant challenge to practical implementation due to the high computational complexity involved in estimating sensing parameters. In this paper, an efficient sensing method is proposed to incorporate both downlink active sensing and passive sensing to estimate multiple sensing parameters, including delays, angle of arrival (AoA), angle of departure (AoD) and Doppler. In particular, it exploits the synchronization signal blocks (SSBs) to facilitate sensing with multiple remote radio units (RRUs). To reduce the computational complexity of direct sensing, a sparse model is developed to decouple multiple sensing parameter estimation, enabling efficient sensing method design. Then, leveraging unitary approximate message passing (UAMP) and sparse Bayesian learning (SBL), we propose an efficient method to achieve parameter estimation and association with corresponding RRUs. This method is further extended to general scenarios involving multiple path components with the same delay. Extensive simulations demonstrate the effectiveness of the proposed method, showing that it outperforms existing ones in terms of sensing accuracy and complexity. © 2014 IEEE.

关键词： 5G mobile communication systems

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A New and Efficient IT Knowledge Exchange Platform 2nd

A New and Efficient IT Knowledge Exchange Platform

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2nd International Conference on Applied Intelligence, ICAI 2024

作者： Sha, Jinting Yu, Wendong Wei, Hongwei Yuan, Lin Li, Zhujun Shandong Jinan250353 China Shandong Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Shandong Jinan250353 China Shandong Tianyi Information Technology Co. Ltd. Shandong Jinan250101 China Jinan Springs Patent and Trademark Office Shandong Jinan250014 China

ISBN: (纸本)9789819619061

As information technology continues to advance, an increasing number of technicians are joining the IT field. However, the technology in this field is changing very rapidly, requiring many technicians to constantly learn new knowledge to keep pace with developments. Therefore, in this context, the creation of a user-friendly IT technology exchange platform is highly valuable, so that technicians can easily learn and interact with each other. This platform adopts Vue 2 as the front-end framework, utilizes Spring Boot for the back-end development, Elasticsearch for full-text search capabilities, MySQL for data storage, Spring Security for authentication and security, and MyBatis for data persistence. Users can register accounts, create and publish articles and resources, and also like or bookmark articles and resources. In addition, the platform also supports features such as full-text search, article categorization, resource classification and so on. Testing has demonstrated that this IT knowledge exchange platform meets the basic needs of its users. At the same time, the platform offers robust security measures to protect user privacy and ensure data security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： IT knowledge exchange platform Spring Boot Vue 2

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