The city of Sao Paulo, the most populous municipality in Brazil, is characterized by an urban segregation responsible for numerous problems related to urban mobility. The current actions to solve problems of urban mob...
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ISBN:
(纸本)9781538676141
The city of Sao Paulo, the most populous municipality in Brazil, is characterized by an urban segregation responsible for numerous problems related to urban mobility. The current actions to solve problems of urban mobility have not exploited the potential of distributed computing to large data set visualization. This work aims to visualize and explore large AVL (Automatic Vehicles Location) data set of the buses of Sao Paulo city, to find hidden patterns. To achieve this goal, this work uses open source software to aggregate, visualize and explore large data sets.
Big data technology has experienced very rapid development over the last decade. This paper aims to trace the latest dynamic and trends in the hot classified fields of big data technology. Firstly, this paper builds t...
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ISBN:
(纸本)9781890843366
Big data technology has experienced very rapid development over the last decade. This paper aims to trace the latest dynamic and trends in the hot classified fields of big data technology. Firstly, this paper builds the classification system of big data technology. Based on the classification system, this paper uses patent counts to dig out the hot classified fields and finds out the representative hot classified fields. After that, we attempt to grasp the overall situation of big data technology at present through the dynamic collaborate analysis among scientists. Lastly, new directions for big data research and development are proposed.
The main goal in cluster analysis is finding groups that naturally exist in any given data. Conceptually, observations are generated from a Probability Density Function (PDF). The number of clusters, their shapes, siz...
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There are more and more users of the Internet, who actively make use of public techniques and programmatic tools. They often form social groups concentrated around various IT projects on a global scale. They just as o...
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There are more and more users of the Internet, who actively make use of public techniques and programmatic tools. They often form social groups concentrated around various IT projects on a global scale. They just as often work individually creating different applications and providing them free of charge. The aim of the paper is a comparative analysis of chosen components, which extend functionality of websites by the possibility to present data concentrated in the small area of a web map, the visibility of which depends on a degree of approximation of a map view. Chosen project tools that base on raster and vector maps were tested. In conclusion it was proved that the tested tools can be applied in projects from the trend called Volunteered Geographic Information (VGI) and in view of the attractive graphic form can also be used in commercial websites, for example, to present offered assortment.
The Mars Perseverance Rover represents a generational change in the scale of measurements that can be taken on Mars, however this increased resolution introduces new challenges for techniques in exploratory data analy...
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ISBN:
(纸本)9798400704901
The Mars Perseverance Rover represents a generational change in the scale of measurements that can be taken on Mars, however this increased resolution introduces new challenges for techniques in exploratory data analysis. The multiple different instruments on the rover each measures specific properties of interest to scientists, so analyzing how underlying phenomena affect multiple different instruments together is important to understand the full picture. However each instrument has a unique resolution, making the mapping between overlapping layers of data non-trivial. In this work, we introduce Nested Fusion, a method to combine arbitrarily layered datasets of different resolutions and produce a latent distribution at the highest possible resolution, encoding complex interrelationships between different measurements and scales. Our method is efficient for large datasets, can perform inference even on unseen data, and outperforms existing methods of dimensionality reduction and latent analysis on real-world Mars rover data. We have deployed our method Nested Fusion within a Mars science team at NASA Jet Propulsion Laboratory (JPL) and through multiple rounds of participatory design enabled greatly enhanced exploratory analysis workflows for real scientists. To ensure the reproducibility of our work we have open sourced our code on GitHub at https://***/pixlise/NestedFusion.
The Cramer-Rao error bound provides a fundamental limit on the expected performance of a statistical estimator. The error bound depends on the general properties of the system, but not on the specific properties of th...
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ISBN:
(纸本)0769519911
The Cramer-Rao error bound provides a fundamental limit on the expected performance of a statistical estimator. The error bound depends on the general properties of the system, but not on the specific properties of the estimator or the solution. The Cramer-Rao error bound has been applied to scalar- and vector-valued estimators and recently to parametric shape estimators. However, nonparametric, low-level surface representations are an important tool in 3D reconstruction, and are particularly useful for representing complex scenes with arbitrary shapes and topologies. This paper presents a generalization of the Cramer-Rao error bound to nonparametric shape estimators. Specifically, we derive the error bound for the full 3D reconstruction of scenes from multiple range images.
When conducting eye tracking studies, the benefits of collecting qualitative data are significant. In this paper, we propose to take qualitative data collection even further by exploring participants' emotions and...
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ISBN:
(纸本)9783030226480;9783030226497
When conducting eye tracking studies, the benefits of collecting qualitative data are significant. In this paper, we propose to take qualitative data collection even further by exploring participants' emotions and habitus during a semi-directive interview guided by the user himself. This method is part of a research on data visualization: how does the user make sense of data visualization and what is the influence of visualizations embellishment on this sense making? Since sense making can be stimulated as much by the human perceptual system as by personal experience and opinions, the methodological challenge of this research is to design an experimental protocol that considers these two dimensions. It is of great interest to combine an eye tracking study with qualitative data collection, which is intended to be both complementary and expanding. The challenge is to find the right method for collecting qualitative data when studying subjective elements. We then propose a semi-directive post-experimental interview method that will integrate all these aspects into the research.
The world wide web can be viewed as a repository of opinions from users spread across various websites and networks, and today's netizens look up reviews and opinions to judge commodities, visit forums to debate a...
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ISBN:
(纸本)9781479925711
The world wide web can be viewed as a repository of opinions from users spread across various websites and networks, and today's netizens look up reviews and opinions to judge commodities, visit forums to debate about events and policies. With this explosion in the volume of and reliance on user reviews and opinions, manufacturers and retailers face the challenge of automating the analysis of such big amounts of data (user reviews, opinions, sentiments). Armed with these results, sellers can enhance their product and tailor experience for the customer. Similarly, policy makers can analyse these posts to get instant and comprehensive feedback. Or use it for new ideas that democratize the policy making process. This paper is the outcome of our research in gathering opinion and review data from popular portals, e-commerce websites, forums or social networks;and processing the data using the rules of natural language and grammar to find out what exactly was being talked about in the user's review and the sentiments that people are expressing. Our approach diligently scans every line of data, and generates a cogent summary of every review (categorized by aspects) along with various graphical visualizations. A novel application of this approach is helping out product manufacturers or the government in gauging response. We aim to provide summarized positive and negative features about products, laws or policies by mining reviews, discussions,, forums etc.
Chart images are commonly used for data visualization. Automatically reading the chart values is a key step for chart content understanding. Charts have a lot of variations in style (e.g. bar chart, line chart, pie ch...
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ISBN:
(纸本)9780738142661
Chart images are commonly used for data visualization. Automatically reading the chart values is a key step for chart content understanding. Charts have a lot of variations in style (e.g. bar chart, line chart, pie chart and etc.), which makes pure rule-based data extraction methods difficult to handle. However, it is also improper to directly apply endto-end deep learning solutions since these methods usually deal with specific types of charts. In this paper, we propose an unified method ChartOCR to extract data from various types of charts. We show that by combing deep framework and rule-based methods, we can achieve a satisfying generalization ability and obtain accurate and semantic-rich intermediate results. Our method extracts the key points that define the chart components. By adjusting the prior rules, the framework can be applied to different chart types. Experiments show that our method achieves state-of-the-art performance with fast processing speed on two public datasets. Besides, we also introduce and evaluate on a large dataset ExcelChart400K for training deep models on chart images. The code and the dataset are publicly available at https://***/soap117/DeepRule.
This paper details the process we went through to visualize the output for our data learning algorithm. We have been developing a hierarchical self-structuring learning algorithm based around the general principles of...
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ISBN:
(纸本)9781510600676
This paper details the process we went through to visualize the output for our data learning algorithm. We have been developing a hierarchical self-structuring learning algorithm based around the general principles of the LaRue model. One example of a proposed application of this algorithm would be traffic analysis, chosen because it is conceptually easy to follow and there is a significant amount of already existing data and related research material with which to work with. While we choose the tracking of vehicles for our initial approach, it is by no means the only target of our algorithm. Flexibility is the end goal, however, we still need somewhere to start. To that end, this paper details our creation of the visualization GUI for our algorithm, the features we included and the initial results we obtained from our algorithm running a few of the traffic based scenarios we designed.
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