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Lecture Notes in computer science

作者： Xiao, Hang Zhang, Melvin Mosig, Axel Leong, Hon Wai Department of Biophysics CAS-MPG Partner Institute Key Laboratory for Computational Biology 320 Yue Yang Road 200031 Shanghai China Department of Computer Science National University of Singapore Computing 1 13 Computing Drive Singapore 117417 Singapore Bioinformatics Group Department of Biophysics Ruhr University Bochum Universitätsstraße 150 44801 Bochum Germany

ISBN: (纸本)9783642230370

Algorithms for comparing trees have recently been found relevant in the context of bioimage analysis. While previously proposed algorithms deal with problems that are computationally hard in general, we propose efficient algorithms for restricted versions that are able to handle significantly larger instances in practice. We propose two dynamic programming algorithms for the so-called tree assignment problem, which generalizes bipartite matchings to trees. We formulate restricted versions that are tractable by a dynamic programming algorithm. Furthermore, we describe a second dynamic programming algorithm that deals with the efficient computation of certain weights between so-called component trees that can be applied to obtain certain cosegmentations in bioimaging applications. Our investigations indicate that our algorithms are both efficient and effective, supported by evaluating the influence of the restrictions imposed by the dynamic programming formulation on a collection of image data. © 2011 Springer-Verlag.

关键词： Dynamic programming

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RAMC: A RSU-assisted multi-channel coordination MAC protocol for VANET

RAMC: A RSU-assisted multi-channel coordination MAC protocol...

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作者： Liu, Kai Guo, Jinhua Lu, Ning Liu, Fuqiang Wang, Xinhong Wang, Ping School of Electronics and Information Engineering Key Laboratory of Embedded System and Service Computing Tongji University 4800 Cao'an Road 201804 Shanghai China Department of Computer and Information Science University of Michigan-Dearborn 4901 Evergreen Rd Dearborn MI 48128 United States

Dedicated Short Range Communication (DSRC) employs one control channel for safety-oriented applications and six service channels for non-safety commercial applications. However, most existing multichannel schemes require all neighboring vehicles periodically (e.g. every 100 milliseconds) tune to the control channel for a full update of safety-oriented data before they can switch to the service channels for non-safety services. The safety exchange interval increases with the increase of traffic density. Consequently, under high traffic densities, the service channels are often completely idle while the control channel is congested. We propose a RSU Assisted Multi-channel Coordination MAC (RAMC) protocol that fully utilizes all channels to provide simultaneous safety and non-safety communications. Within the radio range of a roadside unit (RSU), vehicles are free to tune to any service channel. The RSU monitors all the safety messages being transmitted in both the control and service channels. Periodically, the RSU broadcasts a consolidated traffic view report to all neighboring vehicles in all channels. Therefore, a vehicle can operate in a service channel as long as it needs to achieve high throughput for non-safety applications, while maintaining adequate and timely safety awareness. Our simulation results show that the proposed RAMC protocol consistently achieves very high percentage of non-safety usage, while maintaining high safety message delivery ratios in various traffic density conditions. Copyright © 2011 The Institute of Electronics, Information and Communication Engineers.

关键词： Dedicated short range communications

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Reader Activation Scheduling in Multi-reader RFID systems: A Study of General Case

Reader Activation Scheduling in Multi-reader RFID Systems: A...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Shaojie Tang Cheng Wang Xiang-Yang Li Changjun Jiang Department of Computer Science Illinois Institute of Technology Chicago IL USA Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science University of Tongji Shanghai China

Radio frequency identification (RFID) is a technology where a reader device can "sense'' the presence of a close by object by reading a tag device attached to the object. To guarantee the coverage quality, multiple RFID readers can be deployed in the given region. In this paper, we consider the problem of activation schedule for readers in a multi-reader environment. In particular, we try to design a schedule for readers to maximize the number of served tags per time-slot while avoiding various interferences. We first develop a centralized algorithm under the assumption that different readers may have different interference and interrogation radius. Next, we propose a novel algorithm which does not need any location information of the readers. Finally, we extend the previous algorithm in distributed manner in order to suit the case where no central entity exists. We conduct extensive simulations to study the performances of our proposed algorithm. And our evaluation results corroborate our theoretical analysis.

关键词： Interference Radiofrequency identification Schedules Scheduling Processor scheduling Geometry Algorithm design and analysis

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A study of an irrelevant variability normalization based discriminative training approach for LVCSR

A study of an irrelevant variability normalization based dis...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yu Zhang Jian Xu Zhi-Jie Yan Qiang Huo Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems China Microsoft Research Asia Beijing China University of Science and Technology Hefei China

This paper presents a discriminative training (DT) approach to irrelevant variability normalization (IVN) based training of feature transforms and hidden Markov models for large vocabulary continuous speech recognition. A speaker-clustering based method is used for acoustic sniffing and maximum mutual information (MMI) is used as a training criterion. Combined with unsupervised adaptation of feature transforms, the IVN-based DT approach achieves a 14.5% relative word error rate reduction over an MMI-trained baseline system on a Switchboard-1 conversational telephone speech transcription task.

关键词： Training Hidden Markov models Acoustics Transforms Speech Speech recognition Feature extraction

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Protein interaction prediction for mouse PDZ domains using dipeptide composition features

Protein interaction prediction for mouse PDZ domains using d...

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5th IEEE International Conference on systems Biology, ISB 2011

作者： Nakariyakul, Songyot Liu, Zhi-Ping Chen, Luonan Key Laboratory of Systems Biology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Shanghai 200233 China Department of Electrical and Computer Engineering Thammasat University Khlong Luang Pathumthani 12120 Thailand Collaborative Research Center for Innovative Mathematical Modelling Institute of Industrial Science University of Tokyo Tokyo 153-8505 Japan

ISBN: (纸本)9781457716669

The PDZ domain is one of the largest families of protein domains that are involved in targeting and routing specific proteins in signaling pathways. PDZ domains mediate protein-protein interactions by binding the C-terminal peptides of their target proteins. Using the dipeptide feature encoding, we develop a PDZ domain interaction predictor using a support vector machine that achieves a high accuracy rate of 82.49%. Since most of the dipeptide compositions are redundant and irrelevant, we propose a new hybrid feature selection technique to select only a subset of these compositions that are useful for interaction prediction. Our experimental results show that only approximately 25% of dipeptide features are needed and that our method increases the accuracy by 3%. The selected dipeptide features are analyzed and shown to have important roles on specificity pattern of PDZ domains. © 2011 IEEE.

关键词： Feature Selection

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Adaptive social network construction using Gaussian mixture model

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Information Technology Journal 2011年第12期10卷 2252-2259页

作者： Guo, Xin Xiang, Yang Chen, Qian Wei, Wei Department of Computer Science and Technology School of Electronic and Information Engineering Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

A Social network graph shows social interactions and relationships between individuals in a specific social environment, which is very helpful for analyzing social relationships, activities, structures, etc. The author quantized the strengths of social objects' relationships in social environment using an improved vector space model. Gaussian mixture model was employed to set the threshold for identifying social relationships adaptively and divide social subgroups automatically. According to the threshold, social network graph would be constructed based on performance measures. It is concluded that hidden social relationships can be discovered effectively by using this approach which is very flexible and adaptive for dynamic information feedback mechanism. © 2011 Asian Network for Scientific Information.

关键词： Gaussian distribution

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On multicast throughput scaling of hybrid wireless networks with general node density

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computer Networks 2011年第15期55卷 3548-3561页

作者： Cheng Wang Changjun Jiang Xiang-Yang Li Yunhao Liu Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education China Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States TNLIST School of Software Tsinghua University China

In this paper, we consider hybrid wireless networks with a general node density λ ∈ [1, n ], where n ad hoc nodes are uniformly distributed and m base stations (BSs) are regularly placed in a square region A ( n , A ) = 1 , A × 1 , A with A ∈ [1, n ]. We focus on multicast sessions in which each ad hoc node as a user chooses randomly d ad hoc nodes as its destinations. Specifically, when d = 1 (or d = n − 1), a multicast session is essentially a unicast (or broadcast) session. We study the asymptotic multicast throughput for such a hybrid wireless network according to different cases in terms of m ∈ [1, n ] and d ∈ [1, n ], as n → ∞. To be specific, we design two types of multicast schemes, called hybrid scheme and BS - based scheme , respectively. For the hybrid scheme, there are two alternative routing backbones : sparse backbones and dense backbones . Particularly, according to different regimes of the node density λ = n A , we derive the thresholds in terms of m and d . Depending on these thresholds, we determine which scheme is preferred for the better performance of network throughput.

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Estimate-Piloted Regularization and Fast ALS Algorithm for Collaborative Filtering

Estimate-Piloted Regularization and Fast ALS Algorithm for C...

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2011 International Conference on Future computer science and Education（ICFCSE 2011）

作者： Zhenyue Zhang Keke Zhao Hongyuan Zha Guirong Xue Department of Mathematics State Key Laboratory of CAD&CGZhejiang University College of Computing Georgia Institute of Technology Department of Computer Science Shanghai Jiao Tong University

Regularized Low-rank approximation with missing data is an effective approach for Collaborative Filtering since it generates high quality rating predictions for recommender systems. Alternative LS(ALS) method is one of the commonly used algorithms for the CF problem. However, ALS did not work very well in some applications, due to the over-fitting to observations. This paper proposes a novel estimate-piloted regularization that uses a pre-estimate of the unobserved entries and uses the approximation errors to the pre-estimates as a regularize term. This new regularization can reduce the risk of over-fitting and improve the approximation accuracy of *** also proposed a fast implementation of the modified ALS method, which is also very suitable for parallel computing. The proposed algorithm PALS has higher accuracy than ALS for original model in three real-world data sets.

关键词： lowrank-matrix completion collaborative filtering regularization technique alternate least squares

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Knowledge Granulation in Interval-Valued Information systems

Knowledge Granulation in Interval-Valued Information Systems

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International Workshop on Intelligent systems and Applications, ISA

作者： Nan Zhang Duoqian Miao Can Gao Department of Computer Science and Technology University of Tongji Shanghai China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Key Laboratory of Embedded System and Service Computing of Ministry of Education University of Tongji Shanghai China

Rough set theory, proposed by Pawlak, has been proved to be a mathematical tool to deal with vagueness and uncertainty in intelligent information processing. In this paper, we propose the concept of knowledge granulation in interval-valued information systems, and discuss some important properties. From these properties, it can be shown that the proposed knowledge granulation provides important approaches to measuring the discernibility of different knowledge. It may be helpful for rule evaluation and knowledge discovery in interval-valued information systems.

关键词： Information systems Approximation methods Uncertainty Rough sets computers Entropy

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SelectCast: scalable data aggregation scheme in wireless sensor networks

SelectCast: Scalable data aggregation scheme in wireless sen...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Cheng Wang Shaojie Tang Xiang-Yang Li Changjun Jiang Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science University of Tongji Shanghai China Department of Computer Science Illinois Institute of Technology Chicago IL USA TNLIST School of Software Tsinghua University China

In this work, for a wireless sensor network (WSN) of n randomly placed sensors with node density λ ∈ [1, n], we study the tradeoffs between the aggregation throughput and gathering efficiency. The gathering efficiency refers to the ratio of the number of the sensors whose data have been gathered to the total number of sensors. Specifically, we design two efficient aggregation schemes, called single-hop-length (SLH) scheme and multiple-hop-length (MLH) scheme. By novelly integrating these two schemes, we theoretically prove that our protocol achieves the optimal tradeoffs, and derive the optimal aggregation throughput depending on a given threshold value (lower bound) on gathering efficiency. Particularly, we show that under the MLH scheme, for a practically important set of symmetric functions called perfectly compressible functions, including the mean, max, or various kinds of indicator functions, etc., the data from Θ(n) sensors can be aggregated to the sink at the throughput of a constant order Θ(1), implying that our MLH scheme is indeed scalable.

关键词： TV Wireless sensor networks Power capacitors Blogs Lattices

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