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2012 46th Annual Conference on Information Sciences and systems, CISS 2012

作者： Wei, Ermin Ozdaglar, Asuman Eryilmaz, Atilla Jadbabaie, Ali Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States Electrical and Computer Engineering Ohio State University United States Department of Electrical and Systems Engineering GRASP Laboratory University of Pennsylvania United States

ISBN: (纸本)9781467331401

The standard Network Utility Maximization (NUM) problem has a static formulation, which fails to capture the temporal dynamics in modern networks. This work considers a dynamic version of the NUM problem by introducing additional constraints, referred to as delivery contracts. Each delivery contract specifies the amount of information that needs to be delivered over a certain time interval for a particular source and is motivated by applications such as video streaming or webpage loading. The existing distributed algorithms for the Network Utility Maximization problems are either only applicable for the static version of the problem or rely on dual decomposition and first-order (gradient or subgradient) methods, which are slow in convergence. In this work, we develop a distributed Newton-type algorithm for the dynamic problem, which is implemented in the primal space and involves computing the dual variables at each primal step. We propose a novel distributed iterative approach for calculating the dual variables with finite termination based on matrix splitting techniques. It can be shown that if the error level in the Newton direction (resulting from finite termination of dual iterations) is below a certain threshold, then the algorithm achieves local quadratic convergence rate to an error neighborhood of the optimal solution in the primal space. Simulation results demonstrate significant convergence rate improvement of our algorithm, relative to the existing first-order methods based on dual decomposition. © 2012 IEEE.

关键词： Newton-Raphson method

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Graphic Processing Unit-Accelerated Neural Network Model for Biological Species Recognition

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Journal of Donghua University(English Edition) 2012年第1期29卷 5-8页

作者：温程璐潘伟陈晓熹祝青园 Department of Cognitive Science Xiamen University Fujian Provincial Key Laboratory of Brain-Like Intelligent Systems Department of Computer Science Xiamen University Department of Mechanical and Electrical Engineering Xiamen University

A graphic processing unit (GPU)-accelerated biological species recognition method using partially connected neural evolutionary network model is introduced in this paper. The partial connected neural evolutionary network adopted in the paper can overcome the disadvantage of traditional neural network with small inputs. The whole image is considered as the input of the neural network, so the maximal features can be kept for recognition. To speed up the recognition process of the neural network, a fast implementation of the partially connected neural network was conducted on NVIDIA Tesla C1060 using the NVIDIA compute unified device architecture (CUDA) framework. Image sets of eight biological species were obtained to test the GPU implementation and counterpart serial CPU implementation, and experiment results showed GPU implementation works effectively on both recognition rate and speed, and gained 343 speedup over its counterpart CPU implementation. Comparing to feature-based recognition method on the same recognition task, the method also achieved an acceptable correct rate of 84.6% when testing on eight biological species.

关键词： graphic processing unit(GPU) compute unified device architecture (CUDA) neural network species recognition

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Energy efficient allocation of virtual machines in cloud computing environments based on demand forecast

Energy efficient allocation of virtual machines in cloud com...

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7th International Conference on Advances in Grid and Pervasive computing, GPC 2012

作者： Cao, Jian Wu, Yihua Li, Minglu Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783642307669

In cloud computing environments, demands from different users are often handled on virtual machines (VMs) which are deployed over plenty of hosts. Huge amount of electrical power is consumed by these hosts and auxiliary infrastructures that support them. However, demands are usually time-variant and of some seasonal pattern. It is possible to reduce power consumption by forecasting varying demands periodically and allocating VMs accordingly. In this paper, we propose a power-saving approach based on demand forecast for allocation of VMs. First of all, we forecast demands of next period with Holt-Winters' exponential smoothing method. Second, a modified knapsack algorithm is used to find the appropriate allocation between VMs and hosts. Third, a self-optimizing module updates the values of parameters in Holt-Winters' model and determines the reasonable forecast frequency. We carried out a set of experiments whose results indicate that our approach can reduce the frequency of switching on/off hosts. In comparison with other approaches, this method leads to considerable power saving for cloud computing environments. © 2012 Springer-Verlag.

关键词： Electric power utilization

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Manhattan hashing for large-scale image retrieval 12

Manhattan hashing for large-scale image retrieval

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35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012

作者： Kong, Weihao Li, Wu-Jun Guo, Minyi Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781450316583

Hashing is used to learn binary-code representation for data with expectation of preserving the neighborhood structure in the original feature space. Due to its fast query speed and reduced storage cost, hashing has been widely used for efficient nearest neighbor search in a large variety of applications like text and image retrieval. Most existing hashing methods adopt Hamming distance to measure the similarity (neighborhood) between points in the hashcode space. However, one problem with Hamming distance is that it may destroy the neighborhood structure in the original feature space, which violates the essential goal of hashing. In this paper, Manhattan hashing (MH), which is based on Manhattan distance, is proposed to solve the problem of Hamming distance based hashing. The basic idea of MH is to encode each projected dimension with multiple bits of natural binary code (NBC), based on which the Manhattan distance between points in the hashcode space is calculated for nearest neighbor search. MH can effectively preserve the neighborhood structure in the data to achieve the goal of hashing. To the best of our knowledge, this is the first work to adopt Manhattan distance with NBC for hashing. Experiments on several large-scale image data sets containing up to one million points show that our MH method can significantly outperform other state-of-the-art methods. © 2012 ACM.

关键词： Hamming distance

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Performance Analysis of Multi-Hop AF Relaying systems with a Poisson Field of Interferers in Nakagami-m Fading Channels

Performance Analysis of Multi-Hop AF Relaying Systems with a...

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IEEE Vehicular Technology Conference

作者： Valentine A. Aalo Kostas P. Peppas George Efthymoglou Mohammed Alwakeel Sami Alwakeel Department of Computer & Electrical Engineering and Computer Science Florida Atlantic University Boca Raton FL 33431 USA. Laboratory of Mobile Communications Institute of Informatics and Telecommunications National Centre for Scientific Research "Demokritos" Patriarhou Grigoriou & Neapoleos Agia Paraskevi 15310 Athens Greece. Department of Digital Systems University of Piraeus 80 Karaoli & Dimitriou Street Piraeus 18534 Greece. Sensor Networks and Cellular Systems (SNCS) Research Center University of Tabuk Tabuk Saudi Arabia. Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia.

ISBN: (纸本)9781467361866

In this paper, we investigate the performance of multi-hop wireless networks with amplify-and-forward (AF) relaying operating in interference-limited environments. The analysis considers the presence of co-channel interferers that are scattered according to independent spatial Poisson point processes around the relays and the destination. Assuming that both the desired and the interfering signals experience Nakagami-m fading, exact expressions for the average bit error probability and the average channel capacity of the considered system are obtained as single integrals that can be reliably evaluated numerically. In addition, the diversity and coding gains per hop are obtained. The novel expressions can be used to show the impact of system and interference model parameters on the performance of multi-hop wireless systems. Simulation results are further provided to demonstrate the accuracy of the analytical expressions.

关键词： AF Possion Filed Nakagami-m Fading Channels air feed equipment ABER Spread spectrum communication relaying Channel capacity Sim'eon Denis Poisson coding gain Fading channels wireless multi-hop networks co-channel

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Performance analysis of planar inductor based snubbing circuit on EMI effects generated by switching action in DC/DC Boost converter

Performance analysis of planar inductor based snubbing circu...

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International Symposium on Electromagnetic Compatibility, EMC EUROPE 2012

作者： Nejadpak, Arash Mohammed, Osama A. Energy Systems Research Laboratory Electrical and Computer Engineering Department Florida International University Miami United States

ISBN: (纸本)9781467307185

In this paper, a planar inductor based snubber circuit is presented for power MOSFET devices used in a Boost power converters. The proposed snubber can control the EMI effects caused by the switching actions which can affect the drive circuit. Appropriate use of the snubber and considering the parasitic elements in the switching circuits can improve the conducted EMI of the converter, eliminating the need for the bulky EMI filters. To design an effective snubber circuit, a physics based model of the switch and the snubber circuit components are considered. Using impedance control method, the effects of various parasitic elements that can cause the common-mode noise can be controlled. This effort enables the evaluation of interference issues for EMC evaluation studies early in the design process. The numerical results were validated experimentally. © 2012 IEEE.

关键词： Electromagnetic compatibility

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Binary opinion dynamics with stubborn agents

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ACM Transactions on Economics and Computation 2013年第4期1卷 19-19页

作者： Yildiz, Ercan Ozdaglar, Asuman Acemoglu, Daron Saberi, Amin Scaglione, Anna Accenture Technology Labs Hong Kong Customer Research and Insights Group Google Inc. Mountain ViewCA United States Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA United States Department of Economics Massachusetts Institute of Technology CambridgeMA United States Engineering and Management Department Stanford University StanfordCA United States Electrical and Computer Engineering Department University of California Davis DavisCA United States

We study binary opinion dynamics in a social network with stubborn agents who influence others but do not change their opinions. We focus on a generalization of the classical voter model by introducing nodes (stubborn agents) that have a fixed state. We show that the presence of stubborn agents with opposing opinions precludes convergence to consensus;instead, opinions converge in distribution with disagreement and fluctuations. In addition to the first moment of this distribution typically studied in the literature, we study the behavior of the second moment in terms of network properties and the opinions and locations of stubborn agents. We also study the problem of optimal placement of stubborn agents where the location of a fixed number of stubborn agents is chosen to have the maximum impact on the long-run expected opinions of agents. © 2013 ACM.

关键词： Economics

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REAL-TIME SUPER-RESOLUTION FOR DIGITAL ZOOMING USING FINITE KERNEL-BASED EDGE ORIENTATION ESTIMATION AND TRUNCATED IMAGE RESTORATION

REAL-TIME SUPER-RESOLUTION FOR DIGITAL ZOOMING USING FINITE ...

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IEEE International Conference on Image Processing

作者： Wonseok Kang Jaehwan Jeon Eunsung Lee Changhun Cho Junghoon Jung Taechan Kim Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea System LSI Samsung Electronics Co. Ltd Suwon Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479923427

This paper presents a novel real-time super-resolution (SR) method using directionally adaptive image interpolation and image restoration. The proposed interpolation method estimates the edge orientation using steerable filters and performs edge refinement along the estimated edge orientation. Bi-linear and bi-cubic interpolation filters are then selectively used according to the estimated edge orientation for reducing jagging artifacts in slanting edge regions. The proposed restoration method can effectively remove image degradation caused by interpolation using the directionally adaptive truncated constrained least-squares (TCLS) filter. The proposed method provides high-quality magnified images which are similar to or better than the result of advanced interpolation or SR methods without high computational load. Experimental results indicate that the proposed system gives higher peak-to-peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) values than the state-of-the-art image interpolation methods.

关键词： Super-resolution image interpolation image restoration digital zooming

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Efficient updates for web-scale indexes over the cloud

Efficient updates for web-scale indexes over the cloud

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2012 IEEE 28th International Conference on Data engineering Workshops, ICDEW 2012

作者： Antonopoulos, Panagiotis Konstantinou, Ioannis Tsoumakos, Dimitrios Koziris, Nectarios Microsoft Corp Redmond WA United States Department of Informatics Ionian University Greece Computing Systems Laboratory School of Electrical and Computer Engineering National Technical University of Athens Greece

ISBN: (纸本)9780769547480

In this paper, we present a distributed system which enables fast and frequent updates on web-scale Inverted Indexes. The proposed update technique allows incremental processing of new or modified data and minimizes the changes required to the index, significantly reducing the update time which is now independent of the existing index size. By utilizing Hadoop MapReduce, for parallelizing the update operations, and HBase, for distributing the Inverted Index, we create a high-performance, fully distributed index creation and update system. To the best of our knowledge, this is the first open source system that creates, updates and serves large-scale indexes in a distributed fashion. Experiments with over 23 million Wikipedia documents demonstrate the speed and robustness of our implementation: It scales linearly with the size of the updates and the degree of change in the documents and demonstrates a constant update time regardless of the size of the underlying index. Moreover, our approach significantly increases its performance as more computational resources are acquired: It incorporates a 15.4GB update batch to a 64.2GB indexed dataset in about 21 minutes using just 12 commodity nodes, 3.3 times faster compared to using two nodes. © 2012 IEEE.

关键词： Open systems

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FREQUENCY-DOMAIN ANALYSIS OF DISCRETE WAVELET TRANSFORM COEFFICIENTS AND THEIR ADAPTIVE SHRINKAGE FOR ANTI-ALIASING

FREQUENCY-DOMAIN ANALYSIS OF DISCRETE WAVELET TRANSFORM COEF...

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IEEE International Conference on Image Processing

作者： Eunjung Chae Eunsung Lee Wonseok Kang Younghoon Lim Junghoon Jung Taechan Kim Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea System LSI Samsung Electronics Co. Ltd Suwon Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479923427

We present an antialiasing method using combined wavelet-Fourier transform and spatially adaptive shrinkage of the transform coefficients. Traditional antialiasing methods employ a simple low-pass filter onto the entire image, so the resulting image loses not only aliasing artifacts but also high-frequency components such as edges and ridges. The proposed algorithm analyzes the property of the LL subband of the discrete wavelet transform (DWT), and reduces aliasing artifacts using patch-adaptive shrinkage of the DWT coefficients. More specifically, an antialiased LL subband is obtained using adaptive patch-based aliasing reduction. To detect an aliased region, we subtract the discrete Fourier transform (DFT) coefficients of the LL subband from the DFT coefficients of antialiased LL subband. The detected aliasing artifacts in the LH, HL, and HH subbands are reduced by patch-wise adaptive shrinkage of the transform coefficients. The resulting antialiased image is obtained using the inverse DWT. The aliasing artifacts can be efficiently reduced by adaptively shrinking wavelet transform coefficients for preserving high-frequency image details. The proposed antialiasing algorithm is suitable for removing aliasing artifacts which frequently occur in imaging sensors with limited resolution.

关键词： Anti-aliasing wavelet-Fourier transform image enhancement patch-adaptive shrinkage antialiasing image enhancement Aliasing shrinkage Artifacts subband domain analysis Coefficients Sensors (image) Frequency-domain analysis discrete Fourier transform

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