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检索条件"任意字段=Conference on Visual Data Exploration and Analysis IV"

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Applicability evaluation of SRV concept in tight and shale reservoirs via large-scale rock block experiments

Applicability evaluation of SRV concept in tight and shale r...

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SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology conference 2019, APUR 2019

作者： Li, Shuai Wang, Xin He, Chunming Liang, Tiancheng Fu, Haifeng Research Institute of Petroleum Exploration and Development PetroChina China

ISBN: (纸本)9781613996737

The concept of stimulated reservoir volume (SRV) has conquered the whole oil and gas industry after it was firstly put forward by Fisher et al. in 2004. This concept was used to provide a visual display of hydraulic fracturing performance based on the monitored microseismic data, and had played very important roles in evaluating the stimulation effectiveness, while at the same time, accompanied with numerous queries and criticisms. In this paper, we firstly carried out large-scale rock block experiments (the rock block size is 1m×1m×1m) under the in-situ stress condition to simulate the whole process of hydraulic fracturing, and during the period, we use acoustic emission (AE) monitoring method to obtain the fracture propagation events. Via the indoor experiment, we want to show the corresponding relationship between SRV events (obtained via AE monitoring) and artificial fracture propagation (obtained via fluorescence irradiate of cut rocks after experiment). Secondly, we carried out series of numerical reservoir simulation, fracture propagation simulation and well testing analysis to history match the experimental data and field production data, aiming to reveal the applicability of SRV concept in tight or shale reservoirs. Results showed that fracture propagation is a competition controlled by stresses and rock fabric. The propagation of the hydraulic fracture is generally perpendicular to the minimum principal stress while is locally controlled by the rock fabric. Rock fabric will directly affect the fracture propagation including the bedding development, the interface bonding strength, the bedding fracture toughness and the bedding longitudinal stress difference. A large amount of acoustic emission events were obtained on rock sample's horizontal bedding position, not only along the vertical artificial cracks, and this may result in low correlation of the actual SRV events with the later well production. After the experiments, we cut the large rock block into th

关键词： Hydraulic fracturing

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Recovering 6D Object Pose: A Review and Multi-modal analysis 15th

Recovering 6D Object Pose: A Review and Multi-modal Analysis

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15th European conference on Computer Vision (ECCV)

作者： Sahin, Caner Kim, Tae-Kyun Imperial Coll London ICVL London England

ISBN: (纸本)9783030110246;9783030110239

A large number of studies analyse object detection and pose estimation at visual level in 2D, discussing the effects of challenges such as occlusion, clutter, texture, etc., on the performances of the methods, which work in the context of RGB modality. Interpreting the depth data, the study in this paper presents thorough multi-modal analyses. It discusses the above-mentioned challenges for full 6D object pose estimation in RGB-D images comparing the performances of several 6D detectors in order to answer the following questions: What is the current position of the computer vision community for maintaining "automation" in robotic manipulation? What next steps should the community take for improving "autonomy" in robotics while handling objects? Our findings include: (i) reasonably accurate results are obtained on textured-objects at varying viewpoints with cluttered backgrounds. (ii) Heavy existence of occlusion and clutter severely affects the detectors, and similar-looking distractors is the biggest challenge in recovering instances' 6D. (iii) Template-based methods and random forest-based learning algorithms underlie object detection and 6D pose estimation. Recent paradigm is to learn deep discriminative feature representations and to adopt CNNs taking RGB images as input. (iv) Depending on the availability of large-scale 6D annotated depth datasets, feature representations can be learnt on these datasets, and then the learnt representations can be customized for the 6D problem.

关键词： Object detection

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Proposal and Evaluation of Textual Description Templates for Bar Charts Vocalization

Proposal and Evaluation of Textual Description Templates for...

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International conference on Information visualisation (iv)

作者： Cynthya Letícia Teles De Oliveira Alan Trindade De Almeida Silva Erick Modesto Campos Tiago Davi Oliveira Araújo Marcelle Pereira Mota Bianchi Serique Meiguins Jefferson Magalhães De Morais Laboratory of Visualization Interaction and Intelligent Systems Federal University of Pará Belém Brazil

The textual description of data charts is a complex task. A chart presents different visual characteristics for the information represented, which can be influenced by the technique selected and the combination of visual elements. There are crowdsourcing initiatives to create descriptions for charts available on the Web, but the descriptions can have failures, considering that they arise from the understanding of the person. In this context, methods to automatically extract data from chart images allow producing descriptions for use in these scenarios. However, there is no standard way of vocalizing the chart content. For this, the textual description must be based on a template, so that the chart can be completely understood. Thus, this paper presents templates that allow verbalizing the data extracted from vertical and grouped bar charts in an intelligible way. Evaluations were performed with users to verify the ease of understanding textual descriptions. The results showed that the proposed templates were suitable for vocalization the contents of bar charts.

关键词： Bars data visualization Task analysis data mining visualization Crowdsourcing Standards

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Medical Computing visual Synchronization Using WebSocket Protocol and Web Rendering

Medical Computing Visual Synchronization Using WebSocket Pro...

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Canadian conference on Electrical and Computer Engineering (CCECE)

作者： Qi Zhang Illinois State University Normal Normal IL USA

ISBN: (数字)9781728103198

ISBN: (纸本)9781728103204

Web based 3D medical data computing and visual synchronization can provide clinical users with critical information for distributed diagnosis and treatment. However, due to the limited internet bandwidth, high computational cost and increasing data size, real-time medical data exploration and information sharing on internet is still a challenging task. Therefore, we developed a new internet based medical data computing and information visual distribution system, in which graphics processing units were utilized for parallel medical data computing and visualization, cloud was used for data storage, Apache HTTP Server and MySQL were employed for medical image management and analysis, and WebSocket Protocol was used for medical information visual synchronization. The major contributions include algorithms developed for high performance medical computing, and medical information sharing and visual synchronization on distributed web browsers. The developed system can provide medical users with intuitive feedback for collaborative diagnosis and remote therapy.

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VizCertify: A Framework for Secure visual data exploration

VizCertify: A Framework for Secure Visual Data Exploration

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International conference on data Science and Advanced Analytics (DSAA)

作者： Lorenzo De Stefani Leonhard F. Spiegelberg Eli Upfal Tim Kraska Department of Computer Science Brown University Providence United States of America CSAIL Massachusetts Institute of Technology Cambridge United States of America

Recently, there have been several proposals to develop visual recommendation systems. The most advanced systems aim to recommend visualizations, which help users to find new correlations or identify an interesting deviation based on the current context of the user's analysis. However, when recommending a visualization to a user, there is an inherent risk to visualize random fluctuations rather than solely true patterns: a problem largely ignored by current techniques. In this paper, we present VizCertify, a novel framework to improve the performance of visual recommendation systems by quantifying the statistical significance of recommended visualizations. The proposed methodology allows to control the probability of misleading visual recommendations using both classical statistical testing procedures and a novel application of the Vapnik Chervonenkis (VC) dimension towards visualization recommendation which results in an effective criterion to decide whether a recommendation corresponds to a true phenomenon or not.

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TranSeVis: A visual Analytics System for Transportation data Sensing and exploration 1

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15th International conference on Cooperative Design, visualization, and Engineering (CDVE)

作者： Gong, Rui Teng, Zhiyao Han, Mei Wei, Lirui Zhang, Yuwei Pu, Jiansu Univ Elect Sci & Technol China Big Data Res Ctr Web Sci Ctr CompleX Lab Chengdu 611731 Sichuan Peoples R China

ISBN: (数字)9783030005603

ISBN: (纸本)9783030005603;9783030005597

With increasing availability of location-acquisition technologies, huge volumes of data tracking transportation system have been collected. These data are highly valuable for unveiling human mobility patterns, transportation system utilization, and urban planning. However, it is still highly challenging to visualize and explore transportation data. In this paper, an interactive visual analytic system, TranSeVis has been proposed. It has two visualization modules, one named region view provides geographical information and effective temporal information comparison, the other named road view provides detailed visual analysis of mobility factors along routes or congestions spots. Besides, two case studies have been used to evaluate the visualization techniques and real-world taxi data sets have been used to demonstrate TranSeVis. Based on the results, TranSeVis offers transportation researchers an easy-to-use, efficient, and scalable platform to visualize and explore transportation data.

关键词： visual analysis Urban traffic Congestion analysis Spatio-temporal data

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Interactive visual data exploration with Subjective Feedback: An Information-Theoretic Approach 34

Interactive Visual Data Exploration with Subjective Feedback...

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34th IEEE International conference on data Engineering Workshops (ICDEW)

作者： Puolamaki, Kai Oikarinen, Emilia Kang, Bo Lijffijt, Jefrey De Bie, Tijl Aalto Univ Dept Comp Sci Espoo Finland Finnish Inst Occupat Hlth Helsinki Finland Univ Ghent IDLab Dept Elect & Informat Syst Ghent Belgium

ISBN: (纸本)9781538655207

The exploration of high-dimensional real-valued data is one of the fundamental exploratory data analysis (EDA) tasks. Existing methods use predefined criteria for the representation of data. There is a lack of methods eliciting the user's knowledge from the data and showing patterns the user does not know yet. We provide a theoretical model where the user can input the patterns she has learned as knowledge. The background knowledge is used to find a MaxEnt distribution of the data, and the user is shown maximally informative projections in which the MaxEnt distribution and the data differ the most. We provide an interactive open source EDA system, study its performance, and present use cases on real data.

关键词： Principal component analysis data visualization Task analysis Computational modeling Matrix decomposition data analysis data models

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19th International conference on Web Engineering, ICWE 2019

19th International Conference on Web Engineering, ICWE 2019

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19th International conference on Web Engineering, ICWE 2019

ISBN: (纸本)9783030192730

The proceedings contain 50 papers. The special focus in this conference is on Web Engineering. The topics include: Supervised group embedding for rumor detection in social media;fast incremental pagerank on dynamic networks;crowdsourced time-sync video recommendation via semantic-aware neural collaborative filtering;on Twitter bots behaving badly: Empirical study of code patterns on GitHub;CrowDIY: How to design and adapt collaborative crowdsourcing workflows under budget constraints;finding baby mothers on Twitter;an end-user pipeline for scraping and visualizing semi-structured data over the web;DotCHA: A 3D text-based scatter-type CAPTCHA;entropy and compression based analysis of web user interfaces;Augmenting LOD-based recommender systems using graph centrality measures;domain classifier: Compromised machines versus malicious registrations;the “game hack” scam;decentralized service registry and discovery in P2P networks using blockchain technology;amalgam: Hardware hacking for web developers with style (sheets);Jekyll RDF: Template-based linked data publication with minimized effort and maximum scalability;on the web platform cornucopia;Linked USDL extension for cloud services description;an automatic data service generation approach for cross-origin datasets;Merging intelligent API responses using a proportional representation approach;analyzing the evolution of linked vocabularies;ST-sem: A multimodal method for points-of-interest classification using street-level imagery;Comparison matrices of semantic RESTful APIs technologies;dragon: Decision tree learning for link discovery;catch & release: An approach to debugging distributed full-stack javascript applications;multi-device adaptation with liquid media queries;conversational data exploration;distributed intelligent client-centric personalisation;webifying heterogenous internet of things devices;VR-powered scenario-based testing for visual and acoustic web of things services.

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Region of interest generation algorithms for eye tracking data 3

Region of interest generation algorithms for eye tracking da...

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conference on Eye Tracking and visualization (ETVIS)

作者： Fuhl, Wolfgang Kuebler, Thomas Brinkmann, Hanna Rosenberg, Raphael Rosenstiel, Wolfgang Kasneci, Enkelejda Univ Tubingen Tubingen Baden Wuerttemb Germany Univ Vienna Vienna Austria

ISBN: (纸本)9781450357876

Using human fixation behavior, we can interfere regions that require to be processed at high resolution and where stronger compression can be favored. Analyzing the visual scan path solely based on a predefined set of regions of interest (ROIs) limits the exploration room of the analysis. Insights can only be gained for those regions that the data analyst considered worthy of labeling. Furthermore, visual exploration is naturally time-dependent: A short initial overview phase may be followed by an in-depth analysis of regions that attracted the most attention. Therefore, the shape and size of regions of interest may change over time. Automatic ROI generation can help in automatically reshaping the ROIs to the data of a time slice. We developed three novel methods for automatic ROI generation and show their applicability to different eye tracking data sets. The methods are publicly available as part of the EyeTrace software at http://***/***

关键词： ROI generation AOI generation Eye tracking analysis visualization Expertise classification Abstract art

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Big data Landscapes: Improving the visualization of Machine Learning-based Clustering Algorithms 18

Big Data Landscapes: Improving the Visualization of Machine ...

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14th International conference on Advanced visual Interfaces (AVI)

作者： Kammer, Dietrich Keck, Mandy Gruender, Thomas Groh, Rainer Tech Univ Dresden D-01187 Dresden Germany

ISBN: (纸本)9781450356169

With the internet, massively heterogeneous data sources need to be understood and classified to provide suitable services to users such as content observation, data exploration, e-commerce, or adaptive learning environments. The key to providing these services is applying machine learning (ML) in order to generate structures via clustering and classification. Due to the intricate processes involved in ML, visual tools are needed to support designing and evaluating the ML pipelines. In this contribution, we propose a comprehensive tool that facilitates the analysis and design of ML-based clustering algorithms using multiple visualization features such as semantic zoom, glyphs, and histograms.

关键词： Big data Landscapes Machine Learning visualization Glyphs Clustering

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