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arXiv 2024年

作者： Chen, Xingdi Xiong, Yu Yang, Kai Department of Computer Science and Technology Tongji University China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University China Shanghai Research Institute for Intelligent Autonomous Systems China

Utilization of inter-base station cooperation for information processing has shown great potential in enhancing the overall quality of communication services (QoS) in wireless communication networks. Nevertheless, such cooperations require the knowledge of channel state information (CSI) at base stations (BSs), which is assumed to be perfectly known. However, CSI errors are inevitable in practice which necessitates beamforming techniques that can achieve robust performance in the presence of channel estimation errors. Existing approaches relax the robust beamforming design problems into semidefinite programming (SDP), which can only achieve a solution that is far from being optimal. To this end, this paper views robust beamforming design problems from a bilevel optimization perspective. In particular, we focus on maximizing the worst-case weighted sum-rate (WSR) in the downlink multi-cell multi-user multiple-input single-output (MISO) system considering bounded CSI errors. We first reformulate this problem into a bilevel optimization problem and then develop an efficient algorithm based on the cutting plane method. A distributed optimization algorithm has also been developed to facilitate the parallel processing in practical settings. Numerical results are provided to confirm the effectiveness of the proposed algorithm in terms of performance and complexity, particularly in the presence of CSI uncertainties. Copyright © 2024, The Authors. All rights reserved.

关键词： Channel state information

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LAMPT: LAbel Mask-Predicted Transformer for Extreme Multi-label Text Classification

LAMPT: LAbel Mask-Predicted Transformer for Extreme Multi-la...

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IEEE International Conference on Big Data

作者： Yifan Xu Minghao Zhu Junli Wang Chungang Yan Key Laboratory of Embedded System and Service Computing (Tongji University) Ministry of Education. National (Province-Ministry Joint) Collaborative Innovation Center for Financial Network Security Tongji University Shanghai China

ISBN: (纸本)9781665480468

Extreme Multi-label text Classification ( XMC) is a task of recalling the most relevant labels for each given text from an extremely large-scale label set. It is emphasized that XMC is a more complex classification task because there are two main problems: large space of labels and the labels in XMC tasks tend to be correlated. Existing methods attempt to model label correlations by viewing the XMC task as a sequence generation problem however they still suffer from (1) using the slow serial decoding strategy where labels are predicted one-by-one. (2) needing to compare a mass of label ordering strategies in the decoding stage to achieve satisfied accuracy. In this work, we propose LAbel Mask-Predicted Transformer (LAMPT) to address the both issues, which is a novel non-autoregressive generation model that (1) enriches the input raw text representation with the additional label features by fully exploiting the label dependencies, (2) allows for efficient parallel decoding thanks to its non-autoregressive decoding formulation and mask-prediced training strategy. Experimental results demonstrate that single model performance is substantially enhanced by LAMPT. On a Wiki dataset with thirty-one thousand labels, LAMPT-XLNet accuracy has gained 1.6% relative improvement on P@3 over the LightXML-XLNet. Also, the P@1 of ensemble LAMPT is 90.00%, a significant i mprovement over the state-of-the-art ensemble LightXML (transformer-based) and AttentionXML (LSTM-based), which achieve 89.45% and 87.47%, respectively.

关键词： Training Correlation Text categorization Information services Big Data Predictive models Transformers

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Two-Dimensional Reverse Time Migration for Multi-Input Multi-Output system by Shot Correlation Method with Noise Effect

Two-Dimensional Reverse Time Migration for Multi-Input Multi...

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IEEE International Conference on Microwaves, Communications, Antennas and Electronic systems, COMCAS

作者： Huan Wang Yuxian Zhang Mei Song Tong Zhixiang Huang Naixing Feng School of Electronic and Information Engineering Anhui University Hefei Anhui China The Key Laboratory of Embedded System and Service Computing of the Ministry of Education College of Electronics and Information Engineering Tongji University Shanghai China

ISBN: (数字)9798350348187

ISBN: (纸本)9798350348194

In this paper, we propose a shot correlation reverse time migration (SC-RTM) method for multiple-input-multiple-output (MIMO) ground penetrating radar (GPR) imaging to improve image contrast. In GPR applications, noise is unavoidable in radar echo signals and can cause artifacts in the subsurface reconstructed image. Since in general the correlation among noise signals is weaker than that in target signals, a shot correlation image operator is proposed to integrate all shot images and arrive at the final reconstructed image with artifacts suppression and resolution improvement. In numerical experiments, to test the performance of artifacts suppression, we add different noise levels in the synthetic GPR data. It is shown that the noise is effectively suppressed and the contrast between targets and artifacts is improved in reconstructed images of the SC-RTM method by more than 15 dB. The measured MIMO GPR echo signals with significant noises are successfully processed by the SC-RTM method to yield high contrast subsurface images.

关键词： Microwave antennas Correlation Ground penetrating radar Noise Radar imaging Radar antennas Noise measurement

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Trust-drive Minimize Cost Within Deadline Algorithm for Instance-intensive Workflows in Cloud computing Environment

Trust-drive Minimize Cost Within Deadline Algorithm for Inst...

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第十二届中国Rough集与软计算学术会议、第六届中国Web智能学术研讨会及第六届中国粒计算学术研讨会联合学术会议

作者： LI Dao-guo YANG Chen ZHAO Rong Hangzhou Dianzi University Hangzhou 310018 China The Key Laboratory of Embedded System and Service Hangzhou Dianzi University Hangzhou 310018 China

The workflow scheduling algorithms and strategies having been put forward by Wieczorek M,Rajakumar S,Simion B,Shi Zhiao,etc can be effectively applied to deal with instance-sparse workflows and single complex instance,but these computing techniques are inefficient to dispatch and process instance-intensive workflows which emerge largely in the electronic commerce,the online banking,the e-government,and the cloud computing *** cloud computing has many unique advantages of facilitating instance-intensive workflows execution except unreliable server resource.

关键词： Cloud computing Instance-intensive workflows Trust value Trust-drive minimize cost

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Automated web service composition supporting conditional branch structures

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Enterprise Information systems 2014年第1期8卷 121-146页

作者： Wang, Pengwei Ding, Zhijun zhijun_ding@*** Jiang, Changjun Zhou, Mengchu Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of “Embedded System and Service Computing” Ministry of Education Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 USA

The creation of value-added services by automatic composition of existing ones is gaining a significant momentum as the potential silver bullet in service-oriented architecture. However, service composition faces two aspects of difficulties. First, users' needs present such characteristics as diversity, uncertainty and personalisation; second, the existing services run in a real-world environment that is highly complex and dynamically changing. These difficulties may cause the emergence of nondeterministic choices in the process of service composition, which has gone beyond what the existing automated service composition techniques can handle. According to most of the existing methods, the process model of composite service includes sequence constructs only. This article presents a method to introduce conditional branch structures into the process model of composite service when needed, in order to satisfy users' diverse and personalised needs and adapt to the dynamic changes of real-world environment. UML activity diagrams are used to represent dependencies in composite service. Two types of user preferences are considered in this article, which have been ignored by the previous work and a simple programming language style expression is adopted to describe them. Two different algorithms are presented to deal with different situations. A real-life case is provided to illustrate the proposed concepts and methods. [ABSTRACT FROM AUTHOR]

关键词： conditional branch structure control construct service composition user preference web service

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Parameter Approximate Dynamic Optimization for PSO systems

Parameter Approximate Dynamic Optimization for PSO Systems

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Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference

作者： Qi Kang Lei Wang Derong Liu Qidi Wu College of Electronics and Information Engineering and the Key Laboratory of Embedded System and Computer-service of MOETongji University Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences

This paper presents a novel swarm approximate dynamic programming method(swarm-ADP) for parameter optimization of PSO systems,from the perspective of optimal *** on the stability results of a simplified PSO and the swarm-ADP algorithm,parameter dynamic optimization and computation is studied in detail for a deterministic PSO system and a stochastic PSO system,***,numerical simulations based on several benchmarks optimization are *** results show the validity of the proposed parameter optimization method for PSO systems.

关键词： swarm Parameter Approximate Dynamic Optimization for PSO systems

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A top-down algorithm for finding principal curves from complex patterns data

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ICIC Express Letters 2011年第3期5卷 797-802页

作者： Zhang, Hongyun Miao, Duoqian Xie, Chen Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University No. 1239 Siping Road Shanghai 201804 China School of Electronic and Information Engineering Tongji University No. 1239 Siping Road Shanghai 201804 China

Principal curves are a well established tool in data analysis and processing, but for complex pattern data with high curvature, high dispersion and self-intersecting, such as spiral-shaped curves, existing methods did not perform well. To solve the problem, a top-down strategy is introduced to extract principal curves from complex pattern data. Firstly, the thinning-based method is used to create rudimentary principal graph of data set, and then merging the contiguous vertices. Finally, the fitting-and-smoothing step introduced by Kégl is improved to optimize the principal graph, and Kégl's restructuring step is used to rectify imperfections of principal graph. This algorithm has been not only tested on simulated data sets but also applied to image skeletonization. Experimental results indicate the effectiveness of the proposed method on finding principal curves from complex pattern data sets. © 2011 ISSN 1881-803X.

关键词： Image enhancement

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$\varepsilon$-Constraint and Fuzzy Logic-Based Optimization of Hazardous Material Transportation via Lane Reservation

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IEEE Transactions on Intelligent Transportation systems 2013年第2期14卷 847-857页

作者： Zhen Zhou Feng Chu Ada Che MengChu Zhou Computing Integrative Biology and Complex Systems Laboratory University of Evry-Val dEssonne Evry France School of Management Northwestern Polytechnical University Xian China Key Laboratory of Embedded System and Service Computing of Ministry of Education Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

With economic development, a great amount of hazardous material is shipped in the transport network every day. Hazardous material transportation is well known for its high potential risk. An accident can cause very serious economic damage and will have a negative impact on public health and the environment over the long term. Transporting hazardous materials on special lanes can reduce the risk. However, a lane reservation strategy may worsen traffic conditions for other vehicles. This paper investigates a hazardous material transportation problem with lane reservation. The problem lies in how to choose lanes to be reserved in the network and select the path for each hazardous material shipment from the reserved lanes. The goal is to obtain the best compromise between the impact on normal traffic and the transportation risk. A multiobjective integer programming model is presented for the new problem. Then, an algorithm is developed based on the ε -constraint method and a fuzzy-logic-based approach. Pareto optimal solutions are obtained by the former, and a preferred solution is selected by the fuzzy-logic-based approach. Computational results demonstrate the efficiency of the proposed algorithm using an instance based on a real network topology and randomly generated instances.

关键词： Hazardous materials Accidents Roads Linear programming Vectors Optimization

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Solving the maximum planar subgraph problem using a two-part permutation encoding genetic approach

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ICIC Express Letters 2011年第11期5卷 4107-4113页

作者： Li, Sheng Chen, Huiqin Gao, Shangce Tang, Zheng Graduate School of Innovation Life Science University of Toyama Gofuku 930-8555 Toyama-shi Japan Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University No. 1239 Siping Road Shanghai 200092 China

Genetic algorithms (GAs) have been shown to be very useful in a variety of search and optimization problems. In this paper, we present a new genetic algorithm for the maximum planar subgraph problem (MPSP). Previous studies investigated solving the MPSP with genetic algorithms using standard bit string chromosomes. This paper proposes a new two-part permutation encoding with a greedy heuristic decoding to represent the chromosomes. The first part represents the ordering of the edges in the graph, while the second part deals with the starting vertex based on which a vertex sequence can be determined. Computational testing shows the new approach produces better solutions than previous techniques. © 2011 ICIC International.

关键词： Chromosomes

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A MapReduce-based parallel K-means clustering for large-scale CIM data verification

A MapReduce-based parallel K-means clustering for large-scal...

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作者： Deng, Chuang Liu, Yang Xu, Lixiong Yang, Jie Liu, Junyong Li, Siguang Li, Maozhen School of Electrical Engineering and Information Sichuan University Chengdu610065 China Department of Electronic and Computer Engineering Brunel University London UxbridgeUB8 3PH United Kingdom The Key Laboratory of Embedded Systems and Service Computing Tongji University Shanghai200092 China

The Common Information Model (CIM) has been heavily used in electric power grids for data exchange among a number of auxiliary systems such as communication systems, monitoring systems, and marketing systems. With a rapid deployment of digitalized devices in electric power networks, the volume of data continuously grows, which makes verification of CIM data a challenging issue. This paper presents a parallel K-means clustering algorithm for large-scale CIM data verification. The parallel K-means builds on the MapReduce computing model which has been widely taken up by the community in dealing with data-intensive applications. A genetic algorithm-based load-balancing scheme is designed to balance the workloads among the heterogeneous computing nodes for a further improvement in computation efficiency. The performance of the parallel K-means is initially evaluated in a small-scale in-house MapReduce cluster and subsequently evaluated in a commercial cloud computing platform. Finally, the parallel K-means is evaluated in large-scale simulated MapReduce environments. Both the experimental and simulation results show that the parallel K-means reduces the CIM data-verification time significantly compared with the sequential K-means clustering, while generating a high level of precision in data verification. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： MapReduce

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