Matching Items (7)

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Web-Scale Multidimensional Visualization of Big Spatial Data to Support Earth Sciences—A Case Study with Visualizing Climate Simulation Data

Description

The world is undergoing rapid changes in its climate, environment, and ecosystems due to increasing population growth, urbanization, and industrialization. Numerical simulation is becoming an important vehicle to enhance the

The world is undergoing rapid changes in its climate, environment, and ecosystems due to increasing population growth, urbanization, and industrialization. Numerical simulation is becoming an important vehicle to enhance the understanding of these changes and their impacts, with regional and global simulation models producing vast amounts of data. Comprehending these multidimensional data and fostering collaborative scientific discovery requires the development of new visualization techniques. In this paper, we present a cyberinfrastructure solution—PolarGlobe—that enables comprehensive analysis and collaboration. PolarGlobe is implemented upon an emerging web graphics library, WebGL, and an open source virtual globe system Cesium, which has the ability to map spatial data onto a virtual Earth. We have also integrated volume rendering techniques, value and spatial filters, and vertical profile visualization to improve rendered images and support a comprehensive exploration of multi-dimensional spatial data. In this study, the climate simulation dataset produced by the extended polar version of the well-known Weather Research and Forecasting Model (WRF) is used to test the proposed techniques. PolarGlobe is also easily extendable to enable data visualization for other Earth Science domains, such as oceanography, weather, or geology.

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Created

Date Created
  • 2017-06-26

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Observation of ultralong valley lifetime in WSe2/MoS2 heterostructures

Description

The valley degree of freedom in two-dimensional (2D) crystals recently emerged as a novel information carrier in addition to spin and charge. The intrinsic valley lifetime in 2D transition metal

The valley degree of freedom in two-dimensional (2D) crystals recently emerged as a novel information carrier in addition to spin and charge. The intrinsic valley lifetime in 2D transition metal dichalcogenides (TMD) is expected to be markedly long due to the unique spin-valley locking behavior, where the intervalley scattering of the electron simultaneously requires a large momentum transfer to the opposite valley and a flip of the electron spin. However, the experimentally observed valley lifetime in 2D TMDs has been limited to tens of nanoseconds thus far. We report efficient generation of microsecond-long-lived valley polarization in WSe[subscript 2]/MoS[subscript 2] heterostructures by exploiting the ultrafast charge transfer processes in the heterostructure that efficiently creates resident holes in the WSe[subscript 2] layer. These valley-polarized holes exhibit near-unity valley polarization and ultralong valley lifetime: We observe a valley-polarized hole population lifetime of more than 1 μs and a valley depolarization lifetime (that is, intervalley scattering lifetime) of more than 40 μs at 10 K. The near-perfect generation of valley-polarized holes in TMD heterostructures, combined with ultralong valley lifetime, which is orders of magnitude longer than previous results, opens up new opportunities for novel valleytronics and spintronics applications.

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Created

Date Created
  • 2017-07-26

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Polar Cyclone Identification from 4D Climate Data in a Knowledge-Driven Visualization System

Description

Arctic cyclone activity has a significant association with Arctic warming and Arctic ice decline. Cyclones in the North Pole are more complex and less developed than those in tropical regions.

Arctic cyclone activity has a significant association with Arctic warming and Arctic ice decline. Cyclones in the North Pole are more complex and less developed than those in tropical regions. Identifying polar cyclones proves to be a task of greater complexity. To tackle this challenge, a new method which utilizes pressure level data and velocity field is proposed to improve the identification accuracy. In addition, the dynamic, simulative cyclone visualized with a 4D (four-dimensional) wind field further validated the identification result. A knowledge-driven system is eventually constructed for visualizing and analyzing an atmospheric phenomenon (cyclone) in the North Pole. The cyclone is simulated with WebGL on in a web environment using particle tracing. To achieve interactive frame rates, the graphics processing unit (GPU) is used to accelerate the process of particle advection. It is concluded with the experimental results that: (1) the cyclone identification accuracy of the proposed method is 95.6% when compared with the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data; (2) the integrated knowledge-driven visualization system allows for streaming and rendering of millions of particles with an interactive frame rate to support knowledge discovery in the complex climate system of the Arctic region.

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Created

Date Created
  • 2016-09-05

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The population genomics of rhesus macaques (Macaca mulatta) based on whole genome sequences

Description

Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primate in biomedical research, have the largest natural geographic distribution of any nonhuman primate, and have been the focus of

Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primate in biomedical research, have the largest natural geographic distribution of any nonhuman primate, and have been the focus of much evolutionary and behavioral investigation. Consequently, rhesus macaques are one of the most thoroughly studied nonhuman primate species. However, little is known about genome-wide genetic variation in this species. A detailed understanding of extant genomic variation among rhesus macaques has implications for the use of this species as a model for studies of human health and disease, as well as for evolutionary population genomics. Whole genome sequencing analysis of 133 rhesus macaques revealed >43.7 million single nucleotide variants, including thousands predicted to alter protein sequences, transcript splicing and transcription factor binding sites. Rhesus macaques exhibit 2.5-fold higher overall nucleotide diversity and slightly elevated putative functional variation compared with humans. This functional variation in macaques provides opportunities for analyses of coding and non-coding variation, and its cellular consequences. Despite modestly higher levels of non-synonymous variation in the macaques, the estimated distribution of fitness effects and the ratio of non-synonymous to synonymous variants suggest that purifying selection has had stronger effects in rhesus macaques than in humans. Demographic reconstructions indicate this species has experienced a consistently large but fluctuating population size. Overall, the results presented here provide new insights into the population genomics of nonhuman primates and expand genomic information directly relevant to primate models of human disease.

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Created

Date Created
  • 2016-10-17

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Business Intelligence from Social Media A Study from the VAST Box Office Challenge

Description

With over 16 million tweets per hour, 600 new blog posts per minute, and 400 million active users on Facebook, businesses have begun searching for ways to turn real-time consumer-based

With over 16 million tweets per hour, 600 new blog posts per minute, and 400 million active users on Facebook, businesses have begun searching for ways to turn real-time consumer-based posts into actionable intelligence. The goal is to extract information from this noisy, unstructured data and use it for trend analysis and prediction. Current practices support the idea that visual analytics (VA) can help enable the effective analysis of such data. However, empirical evidence demonstrating the effectiveness of a VA solution is still lacking. A proposed VA toolkit extracts data from Bitly and Twitter to predict movie revenue and ratings. Results from the 2013 VAST Box Office Challenge demonstrate the benefit of an interactive environment for predictive analysis, compared to a purely statistical modeling approach. The VA approach used by the toolkit is generalizable to other domains involving social media data, such as sales forecasting and advertisement analysis.

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Created

Date Created
  • 2014-09-01

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Coding for insertion/deletion channels

Description

Insertion and deletion errors represent an important category of channel impairments. Despite their importance and much work over the years, channels with such impairments are far from being fully understood

Insertion and deletion errors represent an important category of channel impairments. Despite their importance and much work over the years, channels with such impairments are far from being fully understood as they proved to be difficult to analyze. In this dissertation, a promising coding scheme is investigated over independent and identically distributed (i.i.d.) insertion/deletion channels, i.e., interleaved concatenation of an outer low-density parity-check (LDPC) code with error-correction capabilities and an inner marker code for synchronization purposes. Marker code structures which offer the highest achievable rates are found with standard bit-level synchronization is performed. Then, to exploit the correlations in the likelihoods corresponding to different transmitted bits, a novel symbol-level synchronization algorithm that works on groups of consecutive bits is introduced. Extrinsic information transfer (EXIT) charts are also utilized to analyze the convergence behavior of the receiver, and to design LDPC codes with degree distributions matched to these channels. The next focus is on segmented deletion channels. It is first shown that such channels are information stable, and hence their channel capacity exists. Several upper and lower bounds are then introduced in an attempt to understand the channel capacity behavior. The asymptotic behavior of the channel capacity is also quantified when the average bit deletion rate is small. Further, maximum-a-posteriori (MAP) based synchronization algorithms are developed and specific LDPC codes are designed to match the channel characteristics. Finally, in addition to binary substitution errors, coding schemes and the corresponding detection algorithms are also studied for several other models with synchronization errors, including inter-symbol interference (ISI) channels, channels with multiple transmit/receive elements and multi-user communication systems.

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Created

Date Created
  • 2012

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Visual Analytics Methods for Exploring Geographically Networked Phenomena

Description

The connections between different entities define different kinds of networks, and many such networked phenomena are influenced by their underlying geographical relationships. By integrating network and geospatial analysis, the goal

The connections between different entities define different kinds of networks, and many such networked phenomena are influenced by their underlying geographical relationships. By integrating network and geospatial analysis, the goal is to extract information about interaction topologies and the relationships to related geographical constructs. In the recent decades, much work has been done analyzing the dynamics of spatial networks; however, many challenges still remain in this field. First, the development of social media and transportation technologies has greatly reshaped the typologies of communications between different geographical regions. Second, the distance metrics used in spatial analysis should also be enriched with the underlying network information to develop accurate models.

Visual analytics provides methods for data exploration, pattern recognition, and knowledge discovery. However, despite the long history of geovisualizations and network visual analytics, little work has been done to develop visual analytics tools that focus specifically on geographically networked phenomena. This thesis develops a variety of visualization methods to present data values and geospatial network relationships, which enables users to interactively explore the data. Users can investigate the connections in both virtual networks and geospatial networks and the underlying geographical context can be used to improve knowledge discovery. The focus of this thesis is on social media analysis and geographical hotspots optimization. A framework is proposed for social network analysis to unveil the links between social media interactions and their underlying networked geospatial phenomena. This will be combined with a novel hotspot approach to improve hotspot identification and boundary detection with the networks extracted from urban infrastructure. Several real world problems have been analyzed using the proposed visual analytics frameworks. The primary studies and experiments show that visual analytics methods can help analysts explore such data from multiple perspectives and help the knowledge discovery process.

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Created

Date Created
  • 2017