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2012 2nd International Conference on Advanced Materials and Information technology Processing(AMITP 2012)

作者： Li Tu Ling Chen Department of Computer Science Yangzhou UniversityJiangyin Polytechnic College Department of Computer Science National Key Lab of Novel Software TechYangzhou UniversityNanjing University

An algorithm named F Stream for mining frequent items in a stream based on sliding window is *** algorithm can detect ε approximate frequent items in a data stream using O(ε-1) memory space and the processing time for each data item is O(ε-1).Extensive experimental results show that F Stream outperforms other methods in terms of accuracy,memory requirement,and processing speed.

关键词： Data mining Data stream Frequent items Sliding window

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Top rank optimization in linear time 14

Top rank optimization in linear time

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Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 1

作者： Nan Li Rong Jin Zhi-Hua Zhou National Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science and Engineering Michigan State University East Lansing MI

Bipartite ranking aims to learn a real-valued ranking function that orders positive instances before negative instances. Recent efforts of bipartite ranking are focused on optimizing ranking accuracy at the top of the ranked list. Most existing approaches are either to optimize task specific metrics or to extend the rank loss by emphasizing more on the error associated with the top ranked instances, leading to a high computational cost that is super-linear in the number of training instances. We propose a highly efficient approach, titled TopPush, for optimizing accuracy at the top that has computational complexity linear in the number of training instances. We present a novel analysis that bounds the generalization error for the top ranked instances for the proposed approach. Empirical study shows that the proposed approach is highly competitive to the state-of-the-art approaches and is 10-100 times faster.

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Hidden Markov Models Based Dynamic Hand Gesture Recognition with Incremental Learning Method

Hidden Markov Models Based Dynamic Hand Gesture Recognition ...

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International Joint Conference on Neural Networks

作者： Meng Hu Furao Shen Jinxi Zhao Robotic Intelligence and Neural Computing Laboratory (RINC.Lab) the State Key Laboratory for Novel Software Technology at School of Computer Science and Technology Nanjing University

ISBN: (纸本)9781479914821

This paper proposes a real-time dynamic hand gesture recognition system based on Hidden Markov Models with incremental learning method (IL-HMMs) to provide natural human-computer interaction. The system is divided into four parts: hand detecting and tracking, feature extraction and vector quantization, HMMs training and hand gesture recognition, incremental learning. After quantized hand gesture vector being recognized by HMMs, incremental learning method is adopted to modify the parameters of corresponding recognized model to make itself more adaptable to the coming new gestures. Experiment results show that comparing with traditional one, the proposed system can obtain better recognition rates.

关键词： Hidden Markov models Vectors Training Gesture recognition Data models Image color analysis Face

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Using Self-organizing Incremental Neural Network (SOINN) For Radial Basis Function Networks

Using Self-organizing Incremental Neural Network (SOINN) For...

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International Joint Conference on Neural Networks

作者： Jie Lu Furao Shen Jinxi Zhao Robotic Intelligence and Neural Computing Laboratory (RINC.Lab) the State Key Laboratory for Novel Software Technology at School of Computer Science and Technology Nanjing University

ISBN: (纸本)9781479914821

This paper presents a batch learning algorithm and an online learning algorithm for radial basis function networks based on the self-organizing incremental neural network (SOINN), together referred to as SOINN-RBF. The batch SOINN-RBF is a combination of SOINN and least square algorithm. It achieves a comparable performance with SVM for regression. The online SOINN-RBF is based on the self-adaption procedure of SOINN and adopts the growing and pruning strategy of the minimal resource allocation network (MRAN). The growing and pruning criteria use the redefined significance, which is originally introduced by the growing and pruning algorithm for RBF (GGAP-RBF). Simulation results for both artificial and real-world data sets show that, comparing with other online algorithms, the online SOINN-RBF has comparable approximation accuracy, network compactness and better learning efficiency.

关键词： Radial basis function networks Radio access networks Moon Support vector machines Approximation algorithms Accuracy Least squares approximations

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Toward a seamless adaptation platform for Internetware

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science China(Information sciences) 2013年第8期56卷 41-53页

作者： CAO Chun YU Ping HU Hao LV Jian State Key Laboratory for Novel Software Technology Nanjing University Department of Computer Science and Technology Nanjing University

Internetware applications must adapt themselves to keep their satisfaction with sufficient functionality,performance and *** this paper,we introduce a comprehensive technical platform to support such *** and low disruptive software updating techniques for multi-grained abstractions,namely objects,processes/workflows,components and coordinated systems,are proposed toward a seamless adaptation *** platform integrates all the techniques organically to support the practical adaptation scenarios that need the synergy of multiple *** implement the platform in accordance with industrial standards with its feasibility and efficiency demonstrated and hope the platform can be a stepping stone for future technical research for the Internetware paradigm.

关键词： Internetware seamless adaptation dynamic software update process migration component reconfiguration

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An approximately strategy-proof mechanism for radio spectrum allocation

An approximately strategy-proof mechanism for radio spectrum...

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IEEE Conference on Wireless Communications and Networking

作者： Qinhui Wang Baoliu Ye Bolei Zhang Sanglu Lu Song Guo Department of Military Management Army Command College China National Key Lab. for Novel Software and Technology Nanjing Univesity China School of Computer Science and Engineering University of Aizu Japan

ISBN: (纸本)9781479930845

In wireless networks, a recent trend is to make spectrum access dynamic for the sake of efficient utilization of spectrum. In this case, one promising approach is using auction-based market mechanism where available channels are periodically allocated to users. Two of the key objectives in designing an auction mechanism are strategy-proofness and social welfare maximization. It is hard to design a practical auction achieving both objectives. Prior work either do not consider strategy-proofness or do not guarantee performance ratio. In this paper, we achieve a tradeoff between supporting strong strategy-proofness and maximizing social welfare. We design a polynomial-time spectrum auction mechanism that is approximately strategy-proof which bounds the profit gain of a bidder from a lying bid, and yields an allocation with approximate social welfare. Through simulations, we show that our mechanism improves performance by about 30% in terms of social welfare and spectrum utilization, compared to the state-of-art mechanisms.

关键词： Resource management Approximation algorithms Algorithm design and analysis Pricing Interference constraints Cost accounting

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Dynamic Slicing of Python Programs

Dynamic Slicing of Python Programs

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IEEE Annual International computer software and Applications Conference (COMPSAC)

作者： Zhifei Chen Lin Chen Yuming Zhou Zhaogui Xu William C. Chu Baowen Xu State key Laboratory of Novel Software Technology Nanjing University Naniing China Department of Computer Science Tunghai University Taichung Taiwan

ISBN: (纸本)9781479935765

Python is widely used for web programming and GUI development. Due to the dynamic features of Python, Python programs may contain various unlimited errors. Dynamic slicing extracts those statements from a program which affect the variables in a slicing criterion with a particular input. Dynamic slicing of Python programs is essential for program debugging and fault location. In this paper, we propose an approach of dynamic slicing for Python programs which combines static analysis and dynamic tracing of the Python byte code. It precisely handles the dynamic features of Python, such as dynamic typing of variables, heavy usage of first-class objects, and dynamic modifications of classes and instances. Finally, we evaluate our approach on several Python programs. Experimental results show that the whole dynamic slicing for each subject program spends at most about 13 seconds on the average and costs at most 7.58 mb memory space overhead. Furthermore, the average slice ratio of Python source code ranges from 9.26% to 59.42%. According to it, our dynamic slicing approach can be effectively and efficiently performed. To the best of our knowledge, it is the first one of dynamic slicing for Python programs.

关键词： Educational institutions Debugging Performance analysis Runtime Heuristic algorithms Monitoring software

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Privacy Preserving Calculation of Fisher Criterion Score for Informative Gene Selection

Privacy Preserving Calculation of Fisher Criterion Score for...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Suxin Guo Sheng Zhong Aidong Zhang Department of Computer Science and Engineering State University of New York at Buffalo State Key Laboratory for Novel Software Technology Nanjing University

ISBN: (纸本)9781479975037

Informative gene selection is an important topic in the field of bioinformatics which has attracted intensive interest in recent years. It aims to identify the genes which are differentially expressed in different groups, and thus are informative for the classification between the groups. For this purpose, many micro array experiments have been conducted by various medical institutes on their own sets of patients and test subjects. For those institutes who have conducted experiments regarding the same type of disease, it would be beneficial to all of them if they learn on the union of their data to find the informative genes instead of learn just on their own datasets, since the amount of data each institute holds is very limited. However, in many cases, the institutes are not allowed to share their data with others because micro array datasets contain private information about the patients and test subjects. In this paper, we focus on this problem and propose a privacy preserving algorithm that allows multiple parties to perform the widely used informative gene selection method, the Fisher criterion, on the union of their data, without revealing each party's data to others. Basically, we utilize the homomorphic cryptographic system to protect the data during the calculations. Experimental results on real world datasets show the effectiveness of the proposed method.

关键词： Data privacy Encryption Protocols Distributed databases Accuracy Privacy

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SEA: Stable Resource Allocation in Geographically Distributed Clouds

SEA: Stable Resource Allocation in Geographically Distribute...

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IEEE International Conference on Communications

作者： Sheng Zhang Zhuzhong Qian Jie Wu Sanglu Lu State Key Lab. for Novel Software Technology Nanjing University China Department of Computer and Information Sciences Temple University USA

Today's public cloud providers typically deploy their small sized data centers in multiple geographically different locations, so as to improve data center power usage effectiveness and locate resources closer to users. A major challenge is resource allocation. Many results have been reported regarding this issue from the perspectives of virtual machine consolidation, network-aware virtual machine placement, traffic engineering, dynamic capacity provisioning, and so on. However, there has not been any focus on stable resource allocations, where no resource request or data center has any migration incentives. To the best of our knowledge, this paper is the first attempt at gaining a better understanding of the structure of the Stable rEsource Allocation (SEA) problem. We introduce a formal problem statement and develop two algorithms for the 1-dimensional (1-D) and 2-D cases, respectively. Simulation results show that the proposed algorithms have good scalability and convergence.

关键词： Resource management Cloud computing Virtual machining Bandwidth Algorithm design and analysis Proposals Next generation networking

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Leveraging tenant flexibility in resource allocation for virtual networks

Leveraging tenant flexibility in resource allocation for vir...

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International Conference on computer Communications and Networks (ICCCN)

作者： Sheng Zhang Zhuzhong Qian Jie Wu Sanglu Lu State Key Lab. for Novel Software Technology Nanjing University China Department of Computer and Information Sciences Temple University USA

Virtual networks that allow tenants to explicitly specify their computing as well as networking resources are recently proposed to be better interfaces between cloud providers and tenants. Many virtual networks have time-varying resource demands, as evidenced in prior studies [1-3]. New opportunities emerge when such variation is exploited. In this paper, we design a novel resource demand model for tenants to flexibly trade off between application performance and cost, and propose a work-conserving allocation algorithm, WCA, for deploying virtual networks with time-varying resource demands. WCA places virtual nodes in a first-fit fashion, and places virtual links through path-splitting. In each physical node or link, by opportunistically sharing physical resources among multiple variable parts of resource demands, physical utilization can be improved, and more virtual networks can be deployed concurrently. Our evaluation results show that WCA achieves a 4% higher physical resource utilization and rejects 18% less virtual network requests than a state-of-the-art algorithm [4].

关键词： Resource management Computational modeling Algorithm design and analysis Data models Substrates Capacity planning Virtual machining

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