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检索条件"任意字段=14th Symposium on Large Data Analysis and Visualization"

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An Adaptive and Composite Spatio-Temporal data Compression Approach for Wireless Sensor Networks 11

An Adaptive and Composite Spatio-Temporal Data Compression A...

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14th ACM International Conference on Modeling, analysis and Simulation of Wireless and Mobile Systems (MSWiM)

作者： Ali, Azad Khelil, Abdelmajid Szczytowski, Piotr Suri, Neeraj Tech Univ Darmstadt Dept CS Darmstadt Germany

ISBN: (纸本)9781450308984

Wireless Sensor Networks (WSN) are often deployed to sample the desired environmental attributes and deliver the acquired samples to the sink for processing, analysis or simulations as per the application needs. Many applications stipulate high granularity and data accuracy that results in high data volumes. Sensor nodes are battery powered and sending the requested large amount of data rapidly depletes their energy. Fortunately, the environmental attributes (e.g., temperature, pressure) often exhibit spatial and temporal correlations. Moreover, a large class of applications such as scientific measurement and forensics tolerate high latencies for sensor data collection. Accordingly, we develop a fully distributed adaptive technique for spatial and temporal in-network data compression with accuracy guarantees. We exploit the spatio-temporal correlation of sensor readings while benefiting from possible data delivery latency tolerance to further minimize the amount of data to be transported to the sink. Using real data, we demonstrate that our proposed scheme can provide significant communication/energy savings without sacrificing the accuracy of collected data. In our simulations, we achieved data compression of up to 95% on the raw data requiring around 5% of the original data to be transported to the sink.

关键词： spatial and temporal correlations hierarchical clustering energy efficiency modeling approximation accuracy

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A Classification Scheme for Characterizing Visual Mining

A Classification Scheme for Characterizing Visual Mining

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symposium on Human Interface/14th International Conference on Human-Computer Interaction (HCI)

作者： Mozaffari, Elaheh Mudur, Sudhir Concordia Univ Montreal PQ Canada

ISBN: (纸本)9783642216688;9783642216695

Visual mining refers to the cognitive process which integrates the human in analysis of information when using interactive visualization systems. this paper presents a classification scheme which provides user-centered representation of goals and actions that a user performs during the visual mining process. the classification scheme has been developed using content-analysis of published literature containing precise descriptions of different visual mining tasks in multiple fields of study. there were two stages in the development. First, we defined all the sub-processes of visual mining process. then we used these sub-processes as a template to develop the initial coding scheme prior to utilizing specific data from each of the publications. As analysis proceeded, additional codes were developed and the initial coding scheme was refined. the results of the analysis were represented in the form of a classification scheme of the visual mining process. the naturalistic methods recommended by Lincoln and Guba have been applied to ensure that the content analysis is credible, transferable, dependable and confirmable.

关键词： Visual mining large dataset analysis human information behaviour

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Intelligent classification methods of grain kernels using computer vision analysis

Intelligent classification methods of grain kernels using co...

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14th International symposium on Flow visualization (ISFV14)

作者： Lee, Choon Young Yan, Lei Wang, Tianfeng Lee, Sang Ryong Park, Cheol Woo Kyungpook Natl Univ Sch Mech Engn Taegu 702701 South Korea Beijing Forestry Univ Sch Technol Beijing 100083 Peoples R China

In this paper, a digital image analysis method was developed to classify seven kinds of individual grain kernels (common rice, glutinous rice, rough rice, brown rice, buckwheat, common barley and glutinous barley) widely planted in Korea. A total of 2800 color images of individual grain kernels were acquired as a data set. Seven color and ten morphological features were extracted and processed by linear discriminant analysis to improve the efficiency of the identification process. the output features from linear discriminant analysis were used as input to the four-layer back-propagation network to classify different grain kernel varieties. the data set was divided into three groups: 70% for training, 20% for validation, and 10% for testing the network. the classification experimental results show that the proposed method is able to classify the grain kernel varieties efficiently.

关键词： digital image analysis individual grain kernels feature extraction linear discriminant analysis

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Multidimensional Modeling and analysis of Wireless Users Online Activity and Mobility: A Neural-networks Map Approach 11

Multidimensional Modeling and Analysis of Wireless Users Onl...

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14th ACM International Conference on Modeling, analysis and Simulation of Wireless and Mobile Systems (MSWiM)

作者： Moghaddam, Saeed Helmy, Ahmed Univ Florida CISE Dept Gainesville FL 32611 USA

ISBN: (纸本)9781450308984

User online behavior and interests will play a central role in future mobile networks. We introduce a systematic method for large-scale multi-dimensional modeling and analysis of online activity and mobility for thousands of mobile users across 79 buildings over a variety of web domains. We propose a modeling approach based on kind of neural-networks, called self-organizing maps (SOM), for discovering, organizing and visualizing different mobile users' trends from billions of WLAN records. We find surprisingly that users' trends based on domains and locations can be accurately modeled using a self-organizing map with clearly distinct characteristics. We also find many non-trivial correlations between different types of web domains and locations.

关键词： Self-organizing map data-driven trend wireless

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Close-to-optimal Energy Balanced data Propagation via Limited, Local Network Density Information 11

Close-to-optimal Energy Balanced Data Propagation via Limite...

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14th ACM International Conference on Modeling, analysis and Simulation of Wireless and Mobile Systems (MSWiM)

作者： Boukerche, Azzedine Efstathiou, Dionysios Nikoletseas, Sotiris Raptopoulos, Christoforos Univ Ottawa PARADISE Res Lab Ottawa ON K1N 6N5 Canada

ISBN: (纸本)9781450308984

We study the problem of energy-balanced data propagation in wireless sensor networks. the energy balance property is crucial for maximizing the time the network is functional, by avoiding early energy depletion of a large portion of sensors. We propose a distributed, adaptive data propagation algorithm that exploits limited, local network density information for achieving energy-balance while at the same time minimizing energy dissipation. We investigate both uniform and heterogeneous sensor placement distributions. By a detailed experimental evaluation and comparison with well-known energy-balanced protocols, we show that our density-based protocol improves energy efficiency significantly while also having better energy balance properties. Furthermore, we compare the performance of our protocol with a centralized, off-line optimum solution derived by a linear program which maximizes the network lifetime and show that it achieves near-optimal performance for uniform sensor deployments.

关键词： Wireless Sensor Networks Algorithms data Propagation Energy Balance Routing Performance Evaluation

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A Variation-Aware Adaptive Voltage Scaling Technique based on In-Situ Delay Monitoring

A Variation-Aware Adaptive Voltage Scaling Technique based o...

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14th IEEE International symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Wirnshofer, Martin Heiss, Leonhard Georgakos, Georg Schmitt-Landsiedel, Doris Tech Univ Munich Inst Tech Elect D-80290 Munich Germany Infineon Technol AG Neubiberg Germany

ISBN: (纸本)9781424497560

In this paper, we present an adaptive voltage scaling (AVS) scheme to tune the supply voltage of digital circuits according to variations. Compared to worst-case designs, which produce fixed and excessively large safety margins, a considerable amount of energy can be saved by this approach. the AVS technique is based on in-situ delay monitoring, i.e. observing the timing in critical paths. For this task, we propose a Pre-Error flip-flop, that is capable of detecting late data transitions - so-called pre-errors. We provide an in-depth analysis, that is based on a Markov model, to describe the closed loop voltage regulation. We simulated the power saving potential compared to the worst-case design and obtained a reduction of 13.5% in active energy for a negligible error rate of 1E-15. Moreover, we illustrate the opportunity to further reduce the power consumption when tolerating higher error rates. this way, our approach can gain the optimal power saving for a given allowed failure probability.

关键词： AVS scheme AVS technique Clocks Delay Markov model Markov processes Monitoring Temperature measurement Temperature sensors Voltage control active energy closed loop systems closed loop voltage regulation computerised monitoring digital circuits digital circuits error statistics failure probability flip-flops in-depth analysis in-situ delay monitoring late data transitions negligible error rate power aware computing power consumption power consumption power saving potential pre-error flip-flop probability safety margins supply voltage variation-aware adaptive voltage scaling technique voltage control worst-case designs

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the analysis of load balance for wireless sensor network using compressive sensing

The analysis of load balance for wireless sensor network usi...

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14th IEEE Int. Conf. on Computational Science and Engineering, CSE 2011, the 11th International symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2011, and the 10th IEEE Int. Conf. on Ubiquitous Computing and Communications, IUCC 2011

作者： Cao, Guangming Yu, Fengqi Department of Integrated Electronics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong Province 518055 China Chinese University of Hong Kong Hong Kong Hong Kong Graduate University Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9780769544779

One of the most important issues in large-scale Wireless Sensor Networks (WSNs) is how to balance the energy consumption of sensor nodes. In this paper, we propose a novel approach for load balance using compressive sensing. Our approach offers accurate recovery of sampled data from a small number compressed data. Its performance is evaluated in TinyOS. Simulation results show that it achieves a good performance in terms of energy balancing among all nodes in a network. It outperforms the tree collection protocol stack. © 2011 IEEE.

关键词： Compressed sensing

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Hierarchical fusion using vector quantization for visualization of hyperspectral images

Hierarchical fusion using vector quantization for visualizat...

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作者： Shah, Parul Jayalakshmi, M. Merchant, Shabbir N. Desai, Uday B. Department of Electrical Engineering IIT Bombay India IIT Hyderabad India

ISBN: (纸本)9781457702679

visualization of hyperspectral images that combines the data from multiple sensors is a major challenge due to huge data set. An efficient image fusion could be a primary key step for this task. To make the approach computationally efficient and to accommodate a large number of image bands, we propose a hierarchical fusion based on vector quantization and bilateral filtering. the consecutive image bands in the hyperspectral data cube exhibit a high degree of feature similarity among them due to the contiguous and narrow nature of the hyperspectral sensors. Exploiting this redundancy in the data, we fuse neighboring images at every level of hierarchy. As at the first level, the redundancy between the images is very high we use a powerful compression tool, vector quantization, to fuse each group. From second level onwards, each group is fused using bilateral filtering. While vector quantization removes redundancy, bilateral filter retains even the minor details that exist in individual image. the hierarchical fusion scheme helps in accommodating a large number of hyperspectral image bands. It also facilitates the midband visualization of a subset of the hyperspectral image cube. Quantitative performance analysis shows the effectiveness of the proposed method. © 2011 IEEE.

关键词： visualization

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EGPGV 2011 - 11th Eurographics symposium on Parallel Graphics and visualization

EGPGV 2011 - 11th Eurographics Symposium on Parallel Graphic...

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11th Eurographics symposium on Parallel Graphics and visualization, EGPGV 2011

ISBN: (纸本)9783905674323

the proceedings contain 14 papers. the topics discussed include: optimal multi-image processing streaming framework on parallel heterogeneous systems;parallel gradient domain processing of massive images;distributed OpenGL rendering in network bandwidth constrained environments;revisiting parallel rendering for shared memory machines;cross-segment load balancing in parallel rendering;load balancing utilizing data redundancy in distributed volume rendering;real-time ray tracer for visualizing massive models on a cluster;interactive particle tracing in time-varying tetrahedral grids;efficient I/O for parallel visualization;parallel computational steering and analysis for HPC applications using a ParaView interface and the HDF5 DSM virtual file driver;parallel in situ coupling of simulation with a fully featured visualization system;and a preview and exploratory technique for large-scale scientific simulations.

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Comparison analysis for Text data by Using FACT-Graph

Comparison Analysis for Text Data by Using FACT-Graph

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symposium on Human Interface/14th International Conference on Human-Computer Interaction (HCI)

作者： Saga, Ryosuke Takamizawa, Seiko Kitami, Kodai Tsuji, Hiroshi Matsumoto, Kazunori Kanagawa Inst Technol Facuty Informat & Comp Sci 1030 Shimo Ogino Atsugi Kanagawa 2430292 Japan Kanagawa Inst Technol Grad Sch Engn Atsugi Kanagawa 2430292 Japan Osaka Prefecture Univ Grad Sch Engn Naka Ku Sakai Osaka 5598531 Japan

ISBN: (纸本)9783642216688;9783642216695

this paper describes a method to apply the Frequency and Co-occurrence Trend (FACT)-Graph to comparison analysis. FACT-Graph is the method to visualize the changes in keyword trends and relationships between terms over two time periods. the usefulness of FACT-Graph has been shown in tracking trends in politics and crime. To apply FACT-Graph to compare information, we use class transition analysis and separate analysis periods into categories that are the target of comparisons, and collate the features in each comparison target. For the comparison analysis by using 138 articles from two newspapers, we compare topics such as politics and events in them by using the relationships between terms found in the FACT-Graph results.

关键词： Comparison analysis visualization FACT-Graph Text Mining Knowledge Management

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