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共 245 条记录，以下是51-60 订阅

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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 Scalab.e 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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Robust dynamic skeleton extraction for blood vessels based on the level set method

Robust dynamic skeleton extraction for blood vessels based o...

引用

6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Cui, Zhiming Xu, Jing Feng, Daming Wu, Jian Institute Of Intelligent Information Processing and Application Soochow University Jiangsu 215006 China Department Of Computer S and T Soochow University Jiangsu Province Computer IT Key Lab. 215006 China

ISBN: (纸本)9780769537351

Skeleton has very important applications in objects expression, data compression, computer vision and animation. In the discrete space, the basic skeleton algorithms have two categories: one is thinning, the other is based on the distance transformation, in a high-dimensional space generatedfrom the suiface to form the ridge to create a skeleton. The skeleton which is based on the distance transform algorithm is accurate and smooth, but we must carefully check its continuity. Such a check of the continuity would be very difficult when the skeleton structure is complex. The biggest advantage ofthinning algorithm is that it can ensure that the skeleton is in a row and keeps the main topology of the initial target, but the general position is not accurate. In this paper, combining thinning algorithms and level set model, a dynamic robust vascular skeleton extraction algorithm is proposed. First using thinning technology to generate initial skeleton in a row, and then based on the level set model, it will guide the initial framework to the correct position. In this paper, the skeleton extracted from our algorithm not only maintains the exact location and the smooth appearance in a row at the same time curbs the noise of the border with a good robustness. © 2009 IEEE.

关键词： Blood vessels

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Robust centerline extraction for tree-like blood vessels based on the region growing algorithm and level-set method

Robust centerline extraction for tree-like blood vessels bas...

引用

6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Xu, Jing Feng, Darning Wu, Jian Cui, Zhirning Institute Ofintelligent Information Processing and Application Soochow University Jiangsu 215006 China Department of Computer S and T Soochow University Jiangsu Province Computer IT Key Lab. 215006 China

ISBN: (纸本)9780769537351

In this paper, we present a tree-like blood vessels based on the region growing algorithm and level sets methodfor computing centerlines for both 2D and 3D shape analysis. Consider the tree-like vascular structure, we first use region growing technology to generate the shortest distance from the given root to all the pixels, ground on the distance can detect all the extreme nodes of branches automatically. Propagate wave-front from a point of skeleton line with the level sets, track the points of the largest curvature on the suiface of the wave-front, through solute differential equations, the skeleton can be gained. The proposed method is computationally inexpensive, not only maintain the position exactly and the shape smoothly and connectedly, and less sensitive to boundary noise. © 2009 IEEE.

关键词： Blood vessels

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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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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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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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A privacy policy of P3P based on relational database

A privacy policy of P3P based on relational database

引用

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

作者： Jiang, Bin Zhang, Da-Fang Yang, Chao Yue, Guangxue Yu, Fei Software School Hunan University Changsha Hunan 410082 College of Computer and Communication Hunan University Changsha Hunan 410082 Provincial Key Laboratory of Computer Information Processing Technology Nanjing Jiangsu 215006

ISBN: (纸本)0769525814

P3P is an industry standard method that enables users to gain powerful control over their processing of personal information on Web sites being visited Traditional methods of database access control places great dependence on the use application of statically defined views. In this paper, we propose the procedure by which current RDBMS can be transformed into their privacy-preserving equivalents, In addition, architectural for implementing P3P based on RDBMS is dissected and a server-centric implementation that reuses database querying technology is suggested. © 2006 IEEE.

关键词： Relational database systems

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Reliable neighbors-based collab.rative filtering for recommendation systems 1

引用

1st International Conference on Neural Computing for Advanced Applications, NCAA 2020

作者： Zhang, Li Sun, Xiaohan Cheng, Jiangfei Li, Zepeng School of Computer Science and Technology Joint International Research Laboratory of Machine Learning and Neuromorphic Computing Soochow University SuzhouJiangsu215006 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University SuzhouJiangsu215006 China

ISBN: (数字)9789811576706

ISBN: (纸本)9789811576690

The sparsity of data and the diversity of ratings have a great effect on the performance of recommendation systems. To deal with these two issues, this paper proposes a reliable neighbors-based collab.rative filtering (RNCF) method for recommendation systems. RNCF first uses the item similarity to pre-estimated missing ratings to solve the issue of data sparsity, which enriches the sample data and reduces the impact of extremely sparse ratings on the recommendation effect. Then, RNCF finds a set of reliable users for each item by defining a reliable degree for each item. Next, RNCF adopts the K-means clustering algorithm to find the similar users for a target user. The set of reliable neighbors is the intersection of sets of reliable users and similar users. Finally, RNCF provides a predicted rating of a target user on some item using the pre-estimated ratings of corresponding reliable neighbors. Experimental analysis shows that RNCF can improve the performance at the extreme levels of sparsity and rating diversity in recommendation systems. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Collab.rative filtering

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Semi-supervised feature selection using sparse laplacian support vector machine 1

引用

1st International Conference on Neural Computing for Advanced Applications, NCAA 2020

作者： Zhang, Li Zheng, Xiaohan Xu, Zhiqiang School of Computer Science and Technology Joint International Research Laboratory of Machine Learning and Neuromorphic Computing Soochow University SuzhouJiangsu215006 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University SuzhouJiangsu215006 China

ISBN: (数字)9789811576706

ISBN: (纸本)9789811576690

Semi-supervised feature selection is an active topic in machine learning and data mining. Laplacian support vector machine (LapSVM) has been successfully applied to semi-supervised learning. However, LapSVM cannot be directly applied to feature selection. To remedy it, we propose a sparse Laplacian support vector machine (SLapSVM) and apply it to semi-supervised feature selection. On the basis of LapSVM, SLapSVM introduces the 1-norm regularization, which means the solution of SLapSVM has sparsity. In addition, the training procedure of SLapSVM can be formulated as solving a quadratic programming problem, which indicates that the solution of SLapSVM is unique and global. SLapSVM can perform feature selection and classification at the same time. Experimental results on semi-supervised classification problems show the feasibility and effectiveness of the proposed semi-supervised learning algorithms. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Support vector machines

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