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

共 540 条记录，以下是191-200 订阅

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MLV-Viewer: Multi-level visualization in Decision Support Systems Prototype

MLV-Viewer: Multi-level Visualization in Decision Support Sy...

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Iberian Conference on Information Systems and Technologies (CISTI)

作者： Carlos Manuel Oliveira Alves Manuel Pérez Cota María Díaz Rodríguez Miguel Ramón González Castro Instituto Politecnico de Castelo Branco Castelo Branco Castelo Branco PT Universidade de Vigo Vigo Galicia ES

Information visualization (InfoVis) is defined as ”the use of visual, interactive and visual representations supported by computer, to increase cognition”. InfoVis tools and methods help us accelerate our understanding of a large amount of data. datavisualization improves understanding, especially with multidimensional data sets. Visual analysis methods allow decision makers to combine their human flexibility, creativity and knowledgewith the huge storage and processing capabilities of today's computers for information about complex problems. Using advanced visual interfaces, humans can interact directly with the data analysis, adding more to their liking and need. the MLV-Viewer prototype will be described in this article.

关键词： data visualization Decision support systems visualization Tools Computational modeling three-dimensional displays Adaptation models

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Collection and Sentiment analysis of Twitter data on the Political Atmosphere 14

Collection and Sentiment Analysis of Twitter Data on the Pol...

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14th symposium on Neural Networks and Applications (NEUREL)

作者： Cisija, Merima Zunic, Emir Donko, Dzenana Univ Sarajevo Fac Elect Engn Sarajevo Bosnia & Herceg Univ Sarajevo Info Studio Doo Sarajevo Sarajevo Bosnia & Herceg

ISBN: (纸本)9781538669747

the past decade was marked, among other things, by the rapid growth of social networks. these networks collect personal data about their users - their photographs, interests, friends, locations, website visits, clicks, status updates and much more. A large number of users and a big collection of various data collected about the users make social media networks an abundant source of data that can be analyzed and used for targeted marketing, social phenomena analysis, generating different statistics and so on. In this paper we will use the potential of the tool RapidMiner in order to collect data from the social media network Twitter using the AYLIEN extension, preparing the data and applying sentiment analysis, which will give insight into the general atmosphere surrounding the actions of the current USA president Donald Trump

关键词： sentiment analysis data mining RapidMiner Twitter Donald Trump

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DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using data-Parallel Primitives 8

DPP-PMRF: Rethinking Optimization for a Probabilistic Graphi...

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8th IEEE symposium on large-Scale data analysis and visualization (LDAV)

作者： Lessley, Brenton Perciano, Talita Heinemann, Colleen Camp, David Childs, Hank Bethel, E. Wes Univ Oregon Eugene OR 97403 USA Lawrence Berkeley Natl Lab Berkeley CA USA

ISBN: (纸本)9781538668733

We present a new parallel algorithm for probabilistic graphical model optimization. the algorithm relies on data-parallel primitives (DPPs), which provide portable performance over hardware architecture. We evaluate results on CPUs and GPUs for an image segmentation problem. Compared to a serial baseline, we observe runtime speedups of up to 13X (CPU) and 44X (GPU). We also compare our performance to a reference, OpenMP-based algorithm, and find speedups of up to 7X (CPU).

关键词： Mathematics of computing-Graph algorithms Markov networks Expectation maximization Computing methodologies-Image processing Shared memory

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Distributed Feature Extraction on Apache Spark for Human Action Recognition

Distributed Feature Extraction on Apache Spark for Human Act...

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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Nguyen Anh Tu thien Huynh-the Kok-Seng Wong Dinh-Mao Bui Young-Koo Lee Dept. Computer Science Nazarbayev University Nur-Sultan Republic of Kazakhstan ICT Convergence Research Center Kumoh National Institute of Technology Gumi South Korea Dept. Computer Science & Engineering Kyung Hee University Yongin South Korea

ISBN: (数字)9781728154534

ISBN: (纸本)9781728154541

Local feature extraction is one of the most important tasks to build robust video representation in human action recognition. Recent advances in computing visual features, especially deep-learned features, have achieved excellent performance on a variety of action datasets. However, the extraction process is computing-intensive and extremely time-consuming when conducting it on large-scale video data. Consequently, to extract video features over big data, most of the existing methods that run on single machine become inefficient due to the limit of computation power and memory capacity. In this paper, we propose the elastic solutions for feature extraction based on the Spark framework. Particularly, exploiting the in-memory computing capability of Spark, the process of computing features are parallelized by partitioning video data into videos or frames and place them into resilient distributed datasets (RDDs) for the subsequent processing. then, we present the parallel algorithms to extract the state-of-the-art deep-learned features on the Spark cluster. Subsequently, using the distributed encoding, the extracted features are aggregated into the global representation which is fed into the learned classifier to recognize actions in videos. Experimental results on a benchmark dataset demonstrate that our proposed methods can significantly speed up the extraction process and achieve the promising scalability performance.

关键词： Feature extraction Sparks Trajectory Task analysis Liquid crystal displays visualization Streaming media

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Cluster of IoT Sensors for Smart Cities: Impact of the Communication Infrastructure over Computational Performance 14

Cluster of IoT Sensors for Smart Cities: Impact of the Commu...

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14th IEEE Sensors Applications symposium (SAS)

作者： Bonafini, Federico Rinaldi, Stefano Depari, Alessandro Flammini, Alessandra Ferrari, Paolo Sisinni, Emiliano Univ Brescia Dept Informat Engn Via Branze 38 I-25123 Brescia Italy

ISBN: (纸本)9781538677131

the Smart City (SC) paradigm is based on the integration of Information and Communication Technology (ICT) into the urban asset, for the optimal management of the energies and resources. the Internet of thing (IoT) technology seems the proper solution to achieve this target, thanks to its capability to abstract the object in the real world. the deployment of IoT devices at different level in urban infrastructures is causing the presence of thousands of intelligent devices, large part of them with unused computational capabilities. Such devices could be integrated in a cluster in order to share the unused resources with other devices with limited computational resources. the use of a cluster of IoT Sensors has several benefits, including, but not limited to: high availability, sharing of computational resources, reduced response time with the respect of centralized cloud computing solution. the main bottleneck of this approach is represented by the communication infrastructure, typically based on wireless connection and, thus with a limited available bandwidth. the aim of the work related to this paper is to analyze the impact the communication infrastructure has on computational performance of a cluster of IoT sensors. An experimental set-up for the characterization of the performance of a cluster of low-cost off-the-shelf devices has been described. the experimental validation highlighted as the network infrastructure is loaded only during the data transfer and the maximum network load, with a cluster of ten IoT nodes is approximately 2 Mb/s with the considered benchmark.

关键词： Smart City Edge Computing Internet of thing Distributed computing Wireless Sensor Network Cluster of Sensors Computing performance analysis Software Defined Networking

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A framework for constructing open data map visualizations 18

A framework for constructing open data map visualizations

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14th Brazilian symposium on Information Systems (SBSI)

作者： Santos, Victor Camara, Pedro Bernardini, Flavia Viterbo, Jose Jorge, Douglas Univ Fed Fluminense Inst Ciencia & Tecnol Rio Das Ostras RJ Brazil Univ Fed Fluminense Inst Comp Niteroi RJ Brazil

ISBN: (纸本)9781450365598

Open Government data has been made available by public institutions in Brazil and the world, and can add value to various sectors of society. Open data is also linked to smart cities, and hence important in this context, as it is the first step towards public transparency. Despite the wide range of Open Government data, interpreting such data sets is a non-trivial task, due to the massive amount of raw data. this stimulates the search for techniques and methodologies that allow the interpretation of implicit information and deduction of new knowledge. One of the approaches used for these tasks involves the use of data visualizations. In addition to data visualizations classically used in descriptive statistics for data analysis, such as line or bar charts, many web sites have been used map visualization techniques. this type of visualization is important, since visualization of georeferenced data combined with other types of information can aid its interpretation. However, for data visualization construction on maps, it is necessary that the objects to be visualized are georeferenced. there are standards for turning such data available, however they are diverse, which may make it difficult for a single tool to display views from different sources. this work aims to present a framework that defines data standards for constructing data visualizations on maps of various types. Based on this framework, a tool was implemented to facilitate the creation of different map views, both by developers of open data portals and by users who analyze such data.

关键词： Open Government data Transparency Information visualization in Maps

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Image descriptors analysis supported by Information visualization with application in automatic classification 18

Image descriptors analysis supported by Information Visualiz...

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14th Brazilian symposium on Information Systems (SBSI)

作者： Mendes, Gilson Paiva, Jose Gustavo S. Univ Fed Uberlandia Fac Comp Uberlandia MG Brazil

ISBN: (纸本)9781450365598

Automatic image classification strongly depends on image representation, commonly made using visual descriptors. Several works compare the variety of the available ones, aiming to guide analysts in which one to choose for each scenario, but they consider only numerical accuracy results, which may limit the understanding of reasons for these performance differences. this paper employs Neighbor Joining similarity trees to visually analyze three image descriptors, focusing on their application in an automatic classification scenario. the results demonstrated that these trees provide means to comprehend important information about the descriptors, such as how they describe images characteristics, which image aspects they focus in the representation, and which criteria they consider to distinguish images into different classes, revealing their strengths and limitations regarding the representation of a specific categorization scheme. We believe such analysis may help specialists to better choose which descriptor is adequate to be used in this data mining task.

关键词： Information visualization Similarity Trees Visual Classification Image Descriptor analysis

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Multimodal Interaction for data visualization 18

Multimodal Interaction for Data Visualization

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14th International Conference on Advanced Visual Interfaces (AVI)

作者： Lee, Bongshin Srinivasan, Arjun Stasko, John Tory, Melanie Setlur, Vidya Microsoft Res Redmond WA 98052 USA Georgia Inst Technol Atlanta GA 30332 USA Tableau Software Palo Alto CA USA

ISBN: (纸本)9781450356169

Multimodal interaction offers many potential benefits for data visualization. It can help people stay in the flow of their visual analysis and presentation, with the strengths of one interaction modality offsetting the weaknesses of others. Furthermore, multimodal interaction offers strong promise for leveraging data visualization on diverse display hardware including mobile, AR/VR, and large displays. However, prior research on visualization and interaction techniques has mostly explored a single input modality such as mouse, touch, pen, or more recently, natural language. the unique challenges and opportunities of synergistic multimodal interaction for data visualization have yet to be investigated. this workshop will bring together researchers with expertise in visualization, interaction design, and natural user interfaces. We aim to build a community of researchers focusing on multimodal interaction for data visualization, explore opportunities and challenges in our research, and establish an agenda for multimodal interaction research specifically for data visualization.

关键词： data Visuallization Multimodal Interaction Interaction Design

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NoC Symbiosis (Special Session Paper)

NoC Symbiosis (Special Session Paper)

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International symposium on Networks-on-Chip (NOCS)

作者： Daniel Petrisko Chun Zhao Scott Davidson Paul Gao Dustin Richmond Michael Bedford Taylor Bespoke Silicon Group University of Washington

ISBN: (数字)9781728188478

ISBN: (纸本)9781728188485

Conventional wisdom states that Network-on-Chip router area grows quadratically with the channel width, and this perception has fundamentally shaped the assumptions of thousands of NoC papers that have been written to date, and many chip designs. However, this assumption is not entirely true. Simple analysis and empirical data from this paper shows that, in modern standard cell technology, a router's standard cell logic area actually grows only linearly; it is solely the wire routing area that grows *** we think of a NoC as a standalone block as is done in standard hierarchical VLSI design, then the overall area growth is indeed quadratic. But this approach either vastly under-utilizes logic area, or, in designs that match wire and logic area, leads to small network links. At the same time, many standard non-NoC logic blocks like processors or accelerator blocks typically use the standard cell logic area but need only a fraction of available wiring *** propose an alternative approach, NoC Symbiosis, in which router logic and the node logic it services are jointly placed together. the router absorbs excess wiring resources from the node logic, and the node logic absorbs excess standard cell area from the router. Current-day automatic place and route (APR) tools already automatically distribute the router logic across the node logic, in order to provide enough space for the wiring resources. With this approach, future SoC's can leverage vastly larger amounts of wiring bandwidth than ever before, or alternatively, reduce the area overhead of existing *** describe how we first encountered this phenomena, perform experiments to demonstrate its behavior, and provide design tips to help teams realize the potential of NoC Symbiosis.

关键词： Symbiosis Wiring Wires Network-on-chip Very large scale integration Tools Standards

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Visual Marker Guided Point Cloud Registration in a large Multi-Sensor Industrial Robot Cell 14

Visual Marker Guided Point Cloud Registration in a Large Mul...

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14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)

作者： Ujkani, Erind Dybedal, Joacim Aalerud, Atle Kaldestad, Knut Berg Hovland, Geir Univ Agder Dept Engn Sci Mechatron Grp Kristiansand Norway

ISBN: (纸本)9781538646434

this paper presents a benchmark and accuracy analysis of 3D sensor calibration in a large industrial robot cell. the sensors used were the Kinect v2 which contains both an RGB and an IR camera measuring depth based on the time-of-flight principle. the approach taken was based on a novel procedure combining Aruco visual markers, methods using region of interest and iterative closest point. the calibration of sensors is performed pairwise, exploiting the fact that time-of-flight sensors can have some overlap in the generated point cloud data. For a volume measuring 10m x 14m x 5m a typical accuracy of the generated point cloud data of 5-10cm was achieved using six sensor nodes.

关键词： Cameras three-dimensional displays Calibration Robot sensing systems Cloud computing Iterative closest point algorithm visualization"

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