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检索条件"机构=Jiangsu Provincial Key Lab for Computer Information Processing Technology"

共 224 条记录，以下是41-50 订阅

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A mobility-aware zone-based routing protocol for mobile grid computing

A mobility-aware zone-based routing protocol for mobile grid...

引用

2nd International Conference on Semantics, Knowledge, and Grid, SKG 2006

作者： Li, Rui Li, Renfa Yu, Fei Wen, Jigang School of Computer and Communication Hunan University Changsha 410082 China Provincial Key Laboratory of Computer Information Processing Technology Jiangsu Province Suzhou University Suzhou 150063 China

ISBN: (纸本)076952673X

Mobile grid computing is a new computing paradigm which joins classic grid computing and mobile computing paradigm to provide dependable, seamless, pervasive access to mobile resources and services. It can use the underlying connectivity and routing protocols defined by MANET in order to perform resource discovery and access. This paper proposes a mobility-aware zoned routing protocol for MANET-MAFZP, which create zones in terms of the distance between each node to the Minimum ID node. Resort to the information provided by neighborhood nodes, our proposed protocol's request delay and control overhead is descend to O(2R). In addition, this protocol classifies the mobility pattern with neighbor node and reduces routing control overhead. Simulation results show that the protocol greatly decreased routing time and control overhead. © 2006 IEEE.

关键词： Routing protocols

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Ranking based activity trajectory search

Ranking based activity trajectory search

引用

15th International Conference on Web information Systems Engineering, WISE 2014

作者： Chen, Wei Zhao, Lei Jiajie, Xu Zheng, Kai Zhou, Xiaofang School of Computer Science and Technology Soochow University China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University China School of ITEE The University of Queensland Brisbane Australia

ISBN: (纸本)9783319117485

With the proliferation of the GPS-enabled devices and mobile techniques, there has been a lot of work on trajectory search in the last decade. Previous trajectory search has focused on spatio-temporal features and text descriptions. Different from them, we study a novel problem of searching trajectories with activities and corresponding ranking information. Given a query q, which is attached with a set of activities and a threshold of distance, the results of ranking based activity trajectory search (RTS) are k trajectories such that the given activities are performed with the highest ranking within the threshold of distance. In addition, we also extend the query with an order, i.e., order-sensitive ranking based activity trajectory search (ORTS), which takes both the order of activities in a query q and the order of trajectories into account. It is challenging to answer RTS and ORTS efficiently due to the structural complexity of trajectory data with ranking information. In this paper, a hybrid index AC-tree and its optimized variant RAC-tree are proposed to achieve higher efficiency. Extensive experiments verify the high efficiency and scalability of the proposed algorithms. © Springer International Publishing Switzerland 2014.

关键词： Trajectories

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Answer set optimization with dependence based priority propagation

Answer set optimization with dependence based priority propa...

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作者： Zhang, Zhizheng School of Computer Science and Engineering Southeast University Nanjing China Jiangsu Provincial Key Laboratory of Computer Information Processing Technology Suzhou University China

ISBN: (纸本)9781577355014

We propose a new interpretation for a certain kind of ASO preference rules to handling prioritized symptoms. Our interpretation is based on the idea of dependence based priority propagation. Then, we present a fixpoint based answer set optimization method under such an interpretation. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Artificial intelligence

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ADJSA: An adaptable dynamic job scheduling approach based on historical information 2

ADJSA: An adaptable dynamic job scheduling approach based on...

引用

2nd International Conference on Scalable information Systems, InfoScale 2007

作者： Xu, Lan Zhu, Qiao-Ming Gong, Zhengxian Li, Pei-Feng School of Computer Science and Technology Soochow University Suzhou215006 China Key Lab of Computer Information Processing Technology of Jiangsu Province Suzhou215006 China

ISBN: (纸本)9781595937575

Currently, there are many researches focusing on grid scheduling and more and more scheduling algorithms were proposed. However, those algorithms are not satisfied with the requirement of the grid for ignoring its characteristics of dynamics, autonomy, distributing, etc. Therefore, this paper proposes an adaptable dynamic job scheduling approach based on historical information (ADJSA). This approach adjusts the predicting model automatically by using the recent jobs execution historical information and then selects the appropriate resource to execute the job considering dynamic and real-time factors of the Grid.

关键词： Grid computing

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Unsupervised ensemble learning based on graph embedding for image clustering 25th

Unsupervised ensemble learning based on graph embedding for ...

引用

25th International Conference on Neural information processing, ICONIP 2018

作者： Luo, Xiaohui Zhang, Li Li, Fanzhang Hu, Chengxiang School of Computer Science and Technology and Joint International Research Laboratory of Machine Learning and Neuromorphic Computing Provincial Key Laboratory for Computer Information Processing Technology Soochow University SuzhouJiangsu215006 China

ISBN: (纸本)9783030041816

Manifold learning has attracted more and more attention in machine learning for past decades. Unsupervised Large Graph Embedding (ULGE), which performs well on the large-scale data, has been proposed for manifold learning. To improve the clustering performance, a novel Unsupervised Ensemble Learning based on Graph Embedding (UEL-GE) is explored, which takes ULGE to get low-dimensional embeddings of the given data and uses the K-means method to obtain the clustering results. Furthermore, the multiple clusterings are corrected by using the bestMap method. Finally, the corrected clusterings are combined to generate the final clustering. Extensive experiments on several data sets are conducted to show the efficiency and effectiveness of the proposed ensemble learning method. © Springer Nature Switzerland AG 2018.

关键词： K-means clustering

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Improving nominal SRL in Chinese language with verbal SRL information and automatic predicate recognition

Improving nominal SRL in Chinese language with verbal SRL in...

引用

2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Li, Junhui Zhou, Guodong Zhao, Hai Zhu, Qiaoming Qian, Peide Jiangsu Provincial Key Lab. for Computer Information Processing Technologies School of Computer Science and Technology Soochow University Suzhou 215006 China Department of Chinese Translation and Linguistics City University of HongKong Hong Kong

This paper explores Chinese semantic role labeling (SRL) for nominal predicates. Besides those widely used features in verbal SRL, various nominal SRL-specific features are first included. Then, we improve the performance of nominal SRL by integrating useful features derived from a state-of-the-art verbal SRL system. Finally, we address the issue of automatic predicate recognition, which is essential for a nominal SRL system. Evaluation on Chinese NomBank shows that our research in integrating various features derived from verbal SRL significantly improves the performance. It also shows that our nominal SRL system much outperforms the state-of-the-art ones. © 2009 ACL and AFNLP.

关键词： Natural language processing systems

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Fuzzy inference mechanism based automatic elastic registration of two-dimensional gel electrophoresis images

Fuzzy inference mechanism based automatic elastic registrati...

引用

2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Deng, Zhaohong Shitong Wang Qun Gao Yonghui Pan School of Digital Media Jiangnan University Jiangsu Wuxi China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Jiangsu Suzhou China Jiangsu Engineering R and D Center for Information Fusion Software Jiangsu Jiangyin China

ISBN: (纸本)9781612841816

A key technique for protein analysis is the geometric alignment of two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), i.e. 2-D PAGE image registration. In this study, according to the characteristics of 2-D gel image registration, a fuzzy-inference-rule based flexible model (FIM-FM) is proposed to model the complex geometric transformation and intensity variation between 2-D gel image pairs. Then, by introducing the concept of motion estimation and the corresponding sum-of-squared-difference (SSD) objective function, the parameter learning rules of the proposed model are derived for registration. Accordingly, an adaptive FIR-FM-based automatic elastic image registration algorithm is presented for 2-D gel image registration here. It is distinguished by its strong ability in approximating complex nonlinear transformation inherited from fuzzy inference and its efficiency and adaptability in obtaining precise model parameters through effective parameter learning rules. Our experiments show that the proposed algorithm is highly effective for registration of 2-D gel images. © 2011 IEEE.

关键词： Fuzzy inference

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An unsupervised discriminative random vector functional link network for efficient data clustering 4

An unsupervised discriminative random vector functional link...

引用

4th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2021

作者： Zhang, Yikai Zhu, Qi Peng, Yong Kong, Wanzeng School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Provincial Key Lab. for Computer Information Processing Technology Soochow University Suzhou215123 China

ISBN: (纸本)9781665413220

Random Vector Functional Link (RVFL) is a single hidden layer feed forward network which can be trained with non-iterative learning methods. Concretely, the input weights and hidden biases in RVFL can be randomly generated and then the calculation of the output weights can be reduced to solve a regularized least squares regression formula. Though RVFL network obtained promising performance in diverse applications, most of its current variants work mainly for supervised tasks such as classification and regression while less effort was made to utilize the unlabeled data. In this paper, we propose an unsupervised RVFL model by simultaneously considering the local manifold structure and the global discriminative information of data. The newly formulated unsupervised discriminative RVFL (UDRVFL) model can be efficiently solved by handling an eigen-value decomposition operation. We conduct experiments by comparing UDRVFL with several state-of-the-arts on representative benchmark data sets and the results demonstrate that it has very competitive performance in data clustering. © 2021 IEEE.

关键词： Iterative methods

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The application of flash into M-learning in 3G initial stage

The application of flash into M-learning in 3G initial stage

引用

2010 3rd International Symposium on Knowledge Acquisition and Modeling, KAM 2010

作者： Tang, Yue-Ming Liu, Quan Wang, Ling-Ling Department of Educational Technology Henan Normal University Xinxiang Henan Province China Institute of Computer Science and Technology Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou Jiangsu Province China

ISBN: (纸本)9781424480050

With the development of the 3G technology, M-learning enters a period of rapid development. But meanwhile 3G also restrains the development of M-Iearning due to several drawbacks in its early days. According to the application analysis, it comes out Flash has its unique features: small capacity, easy to develop high-quality and etc, which can make up for 3G initial stage's disadvantages. Through case design, this paper proves that Flash can be a new effective approach and way for M-Iearning in the 3G network. In the end, from the aspects of technical and artistic, this paper makes a further research on how to improve the flash animation to serve the M-Iearning better. © 2010 IEEE.

关键词： E-learning

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Multi-target localization using distributed MIMO radar based on spatial sparsity

Multi-target localization using distributed MIMO radar based...

引用

2021 IEEE International Conference on Artificial Intelligence and computer Applications, ICAICA 2021

作者： Zhao, Chenyang Ke, Wei Wang, Tingting Nanjing Normal University Jiangsu Key Laboratory on Optoelectronic Technology in School of Computer and Electronic Information School of Artificial Intelligence Nanjing China Nanjing University of Information Science Technology Jiangsu Key Lab of Meteorological Observation and Information Processing Nanjing China

ISBN: (纸本)9781665418676

This paper presents a sparsity-based multi-target localization method for multiple-input multiple-output (MIMO) radar systems using distributed antennas. Since targets usually lie at some points within the localization domain, we are able to exploit this sparsity to convert the radar localization problem into a distributed recovery solution. Based on this natural sparsity, in this paper we introduce a block-sparse illustration model for distributed MIMO radar and propose a completely unique block-sparse recovery algorithmic rule supported approximate l0 norm diminution. The novelty of this technique is using l0 norm to push inter-block sparsity within the signals and also the optimisation problem is resolved by an ordered procedure in conjunction with a conjugate-gradient technique for quick reconstruction. Moreover, the amount of targets doesn't be well-known in advance. The effectiveness of this technique is incontestable by simulation results that obtain better localization performance and reduce computation complexness for giant sized data. © 2021 IEEE.

关键词： MIMO radar

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