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International Symposium on parallel and distributed processing with Applications, ISPA

作者： Wen-Pinn Fang Department of Computer Science and Information Engineering Yuanpei University Hsinchu Taiwan

Secret image sharing is a method to transmit and store an image safely. The security of secret image sharing is based on the fact that the values are operated in the finite field and the number of pixels is high enough to ensure security. However, the time complexity to encode and decode a secret image is not acceptable in real-time application. There are some papers discussing how to upgrade the efficiency of encoding phase while few papers exploring how to decrease the decoding phase time. This paper proposes a method to achieve to speed up decoding phase by parallel processing.

关键词： Decoding Cryptography Complexity theory parallel processing Pixel Finite element methods Conferences

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Size-fractionated characterization and quantification of nanoparticle release rates from a consumer spray product containing engineered nanoparticles

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JOURNAL OF NANOPARTICLE RESEARCH 2010年第7期12卷 2481-2494页

作者： Hagendorfer, Harald Lorenz, Christiane Kaegi, Ralf Sinnet, Brian Gehrig, Robert Goetz, Natalie V. Scheringer, Martin Ludwig, Christian Ulrich, Andrea EMPA Swiss Fed Labs Mat Testing & Res CH-8600 Dubendorf Switzerland ETHZ Swiss Fed Inst Technol Zurich CH-8093 Zurich Switzerland EAWAG Swiss Fed Inst Aquat Sci & Technol CH-8600 Dubendorf Switzerland Paul Scherrer Inst CH-5232 Villigen Switzerland Ecole Polytech Fed Lausanne Swiss Fed Inst Technol Lausanne CH-1015 Lausanne Switzerland

This study describes methods developed for reliable quantification of size- and element-specific release of engineered nanoparticles (ENP) from consumer spray products. A modified glove box setup was designed to allow controlled spray experiments in a particle-minimized environment. Time dependence of the particle size distribution in a size range of 10-500 nm and ENP release rates were studied using a scanning mobility particle sizer (SMPS). In parallel, the aerosol was transferred to a size-calibrated electrostatic TEM sampler. The deposited particles were investigated using electron microscopy techniques in combination with image processing software. This approach enables the chemical and morphological characterization as well as quantification of released nanoparticles from a spray product. The differentiation of solid ENP from the released nano-sized droplets was achieved by applying a thermo-desorbing unit. After optimization, the setup was applied to investigate different spray situations using both pump and gas propellant spray dispensers for a commercially available water-based nano-silver spray. The pump spray situation showed no measurable nanoparticle release, whereas in the case of the gas spray, a significant release was observed. From the results it can be assumed that the homogeneously distributed ENP from the original dispersion grow in size and change morphology during and after the spray process but still exist as nanometer particles of size < 100 nm. Furthermore, it seems that the release of ENP correlates with the generated aerosol droplet size distribution produced by the spray vessel type used. This is the first study presenting results concerning the release of ENP from spray products.

关键词： Nanoparticle release Nano-silver Engineered nanoparticles Propellant gas spray Pump spray Consumer products SMPS Electrostatic TEM sampler Electron microscopy image analysis Environment, health and safety (EHS)

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On the parallelisation of MCMC-based image processing

On the parallelisation of MCMC-based image processing

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IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Jonathan M. R. Byrd Stephen A. Jarvis Abhir H. Bhalerao Department of Computer Science University of Warwick Coventry UK

ISBN: (纸本)9781424465330

The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As such MCMC has found a wide variety of applications in fields including computational biology and physics, financial econometrics, machine learning and image processing. Whilst divide and conquer is an obvious means to simplify image processing tasks, "naively" dividing an image into smaller images to be processed separately results in anomalies and breaks the statistical validity of the MCMC algorithm. We present a method of grouping the spatially local moves and temporarily partitioning the image to allow those moves to be processed in parallel, reducing the runtime whilst conserving the properties of the MCMC method. We calculate the theoretical reduction in runtime achievable by this method, and test its effectiveness on a number of different architectures. Experiments are presented that show reductions in runtime of 38% using a dual-core dual-processor machine. In circumstances where absolute statistical validity are not required, an algorithm based upon, but not strictly adhering to, MCMC may suffice. For such situation two additional algorithms are presented for partitioning of images to which MCMC will be applied. Assuming preconditions are met, these methods may be applied with minimal risk of anomalous results. Although the extent of the runtime reduction will be data dependent, the experiments performed showed the runtime reduced to 27% of its original value.

关键词： image processing Runtime Partitioning algorithms Availability Computer architecture Computer simulation Monte Carlo methods Biological system modeling Computational modeling Bayesian methods

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processing of the information by the complex of neural networks in the distributed fiber-optical measuring systems

Computer Optics

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Computer Optics 2010年第3期34卷 360-366页

作者： Kulchin, Yuri Nikolaevich Zakasovskaya, Elena Vladimirovna Institute of Automation and Control Processes FEB RAS Russia Far Eastern National University Russia

The paper discusses tomography reconstruction of distributed physical fields by means of distributed fiber optical measuring systems (FOMN) for incomplete parallel schemes of measuring lines (ML) stacking. The approach is presented, consists in optimization of geometry of a measuring network for the purpose of the further application neural network methods of restoration of a full-image of investigated functions. Possibility of a choice and use of a suitable neural network from set of the several, in advance trained, neural networks of RBF-type is investigated. © 2010, Institution of Russian Academy of Sciences. All rights reserved.

关键词： Tomography

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Scalability in Privacy-Preserving Data Aggregation for Wireless Sensor Networks

Scalability in Privacy-Preserving Data Aggregation for Wirel...

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International Symposium on parallel and distributed processing with Applications, ISPA

作者： Rabindra Bista Young-Sung Shin Jae-Woo Chang Department of Computer Engineering and Center of Advanced Image and Information Technology Chonbuk National University of Korea Cheongju Chungbuk South Korea

In this paper, we propose a new privacy preserving data aggregation scheme for WSNs. Our scheme applies additive property of complex numbers in order to combine sensor data and preserve data privacy during transmission to the sink node. In addition, for supporting scalability, we propose a novel mechanism in which a special set of real numbers are assigned to sensor nodes as their IDs so that a single bit is sufficient to hold ID of a sensor node during transmission of aggregated data to the sink node. For this, we, first, generate fixed size signatures for the IDs of all sensor nodes and then superimpose the signatures during data aggregation phase. By analytical evaluations, we show that our scheme is more scalable and energy efficient than the existing methods to achieve data privacy and transmit IDs of sensor nodes along with the aggregated data to the sink node.

关键词： Wireless sensor networks Data privacy Payloads Technical Activities Guide - TAG Encryption Tin Aggregates

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On the parallelisation of MCMC by speculative chain execution

On the parallelisation of MCMC by speculative chain executio...

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IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Jonathan M. R. Byrd Stephen A. Jarvis Abhir H. Bhalerao Department of Computer Science University of Warwick Coventry UK

ISBN: (纸本)9781424465330

The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As such MCMC has had a wide variety of applications in fields including computational biology and physics, financial econometrics, machine learning and image processing. One method for improving the performance of Markov Chain Monte Carlo simulations is to use SMP machines to perform 'speculative moves', reducing the runtime whilst producing statistically identical results to conventional sequential implementations. In this paper we examine the circumstances under which the original speculative moves method performs poorly, and consider how some of the situations can be addressed by refining the implementation. We extend the technique to perform Markov Chains speculatively, expanding the range of algorithms that maybe be accelerated by speculative execution to those with non-uniform move processing times. By simulating program runs we can predict the theoretical reduction in runtime that may be achieved by this technique. We compare how efficiently different architectures perform in using this method, and present experiments that demonstrate a runtime reduction of up to 35-42% where using conventional speculative moves would result in execution as slow, if not slower, than sequential processing.

关键词： Runtime Availability Computer architecture Computer simulation Monte Carlo methods Biological system modeling Computational modeling Bayesian methods Application software Computational biology

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A distributed and Energy Efficient Algorithm for Data Collection in Sensor Networks

A Distributed and Energy Efficient Algorithm for Data Collec...

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International Conference on parallel processing Workshops (ICPPW)

作者： Sarah Sharafkandi David H. C. Du Alireza Razavi Department of Computer Science and Engineering University of Minnesota Twin city MN USA

In wireless sensor networks, collection of raw sensor data at a base station provides the flexibility to perform offline detailed analysis on the data which may not be possible with innetwork data aggregation. However, lossless data collection consumes considerable amount of energy for communication while sensors usually have limited energy. In this paper, we propose a distributed and Energy efficient algorithm for Collection of Raw data in sensor networks called DECOR. DECOR exploits spatial correlation to reduce the communication energy in sensor networks with highly correlated data. In our approach, at each neighborhood, one sensor shares its raw data as a reference with the rest of sensors without any suppression or compression. Other sensors use this reference data to compress their observations by representing them in the forms of mutual differences. In a highly correlated network, transmission of reference data consumes significantly more energy than transmission of compressed data. Thus, we first attempt to minimize the number of reference transmissions. Then, we try to minimize the size of mutual differences. We derive analytical lower bounds for both these phases and based on our theoretical results, we propose a two-step distributed data collection algorithm which reduces the communication energy significantly compared to existing methods. In addition, we modify our algorithm for lossy communication channels and we evaluate its performance through simulation.

关键词： Base stations distributed databases image color analysis Correlation Approximation methods Bridges Propagation losses

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Using the GPU and Multi-core CPU to Generate a 3D Oviduct through Feature Extraction from Histology Slides

Using the GPU and Multi-core CPU to Generate a 3D Oviduct th...

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International Workshop on High Performance Computational Systems Biology, HIBI

作者： Mark Burkitt Dawn Walker Daniela M. Romano Alireza Fazeli Department of Computer Science University of Sheffield Sheffield UK Academic Unit of Reproductive and Developmental Medicine University of Sheffield Sheffield UK

Extracting information about the structure of biological tissue from static image data is a complex task which requires a series of computationally intensive operations. Here we present how the power of multi-core CPUs and massively parallel GPUs have been utilised to extract information about the shape, size and path followed by the mammalian oviduct, called the fallopian tube in humans, from histology images, to create a realistic 3D virtual organ for use in predictive computational models. Histology images from a mouse oviduct were processed, using a combination of GPU and multi-core CPU techniques, to identify the individual cross-sections and determine the 3D path that the tube follows through the tissue. This information was then related back to the histology images, linking the 2D cross-sections with their corresponding 3D position along the oviduct. Measurements were then taken from the images and used to computationally generate a series of linear 2D spline cross-sections for the length of the oviduct, which were bound to the 3D path of the tube using a novel particle system based technique that provides smooth resolution of self intersections and crossovers from adjacent sections. This results in a unique 3D model of the oviduct, which is based on measurements of histology slides and therefore grounded in reality. The GPU is used for the processor intensive operations of image processing and particle physics based simulations, significantly reducing the time required to generate a complete model. A set of models created using this technique is being used to investigate the influence that the 3D structure of the oviductal environment has on sperm transport and navigation.

关键词： Three dimensional displays Electron tubes Graphics processing unit Pixel Solid modeling Computational modeling Biological system modeling

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Low cost VLSI discrete wavelet transform and FIR filters architectures for very high-speed signal and image processing

Low cost VLSI discrete wavelet transform and FIR filters arc...

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IEEE International Conference on Cybernetic Intelligent Systems, CIS

作者： Mountassar Maamoun Rafik Bradai Abdelhamid Meraghni Rachid Beguenane Department of Electronics University of Blida Burgas Algeria LSIC Laboratory Ecole Normale Supérieure Kouba Algiers Algeria Department of Electrical and Computer Engineering Royal Military College of Canada Kingston Canada

This paper presents new VLSI architectures for finite impulse response (FIR) filters and discrete wavelet transform, intended for very high-speed signal and image processing. The proposed architectures, based on combining pipeline and parallel arithmetic methods, provide a new and very fast convolution approach with a reduced critical path. The key to this is a clever use of D-latches and multipliers which are efficiently distributed. Furthermore, an advanced discrete wavelet transform (DWT) approach, with an area-efficient architecture, is designed to produce one output in every clock cycle. As a result, a very high-speed is attained. The proposed structure can increase the work frequency (85%) at a low cost of additional hardware elements (55%). The systems are verified, using JPEG2000 coefficients filters, on Xilinx Field Programmable Gate Array (FPGA) devices.

关键词： Finite impulse response filter Computer architecture Adders Discrete wavelet transforms Low pass filters Convolution

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3D Wave field phase retrieval from multi-plane observations

3D Wave field phase retrieval from multi-plane observations

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3DTV Conference

作者： Artem Migukin Vladimir Katkovnik Jaakko Astola Department of Signal Processing Tampere University of Technology Tampere Finland

We reconstruct a spatially distributed three-dimensional (3D) wave field from a number of intensity observations, obtained in different sensor planes, parallel to the object plane. The proposed algorithm can be treated as a multiple plane iterative Gerchberg-Saxton algorithm [1]. It is obtained from the best linear estimate of the complex-valued object distribution derived for the complex-valued observations. This estimator is modified for the intensity measurements in the sensor planes. The algorithm is studied by numerical experiments performed for amplitude and phase object distributions. It is shown that the proposed method allows reconstructing the whole 3D wave fields for different setup parameters. This technique can be applied for 3D imaging. The comparison versus the successive iterative method [2] shows an accuracy advantage of the proposed algorithm provided that the type of modulation in the object plane is known.

关键词： Signal processing algorithms image reconstruction Iterative algorithms Phase measurement Optical imaging Optical interferometry Iterative methods Holography Reconstruction algorithms Optical scattering

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