Stroke Based Painterly Rendering with Mass Data through Auto Warping Generation

Painting is done according to the artist’s style.The most representative of the style is the texture and shape of the brush stroke.Computer simulations allow the artist’s painting to be produced by taking this stroke and pasting it onto the image.This is called stroke-based rendering.The quality of the result depends on the number or quality of this stroke,since the stroke is taken to create the image.It is not easy to render using a large amount of information,as there is a limit to having a stroke scanned.In this work,we intend to produce rendering results using mass data that produces large amounts of strokes by expanding existing strokes through warping.Through this,we have produced results that have higher quality than conventional studies.Finally,we also compare the correlation between the amount of data and the results.

A Distributed In-Memory Database Solution for Mass Data Applications

In this paper, a Distributed In-Memory Database （DIMDB） system is proposed to improve processing efficiency in mass data applications. The system uses an enhanced language similar to Structured Query Language （SQL） with a key-value storage schema. The design goals of the DIMDB system is described and its system architecture is discussed. Operation flow and the enhanced SOL-like language are also discussed, and experimental results are used to test the validity of the system.

Mass Data—A Gold Mine to be Explored

Click on a shopping website and looking for the products you are interested in,then you will place the order and wait for home delivery.Or you may talk with your families living far away on the video conference,or share your video on the website.It will be interesting to know how does this happen and what is its significance.

Monthly gravity field solution from GRACE range measurements using modified short arc approach

In this paper we present a series of monthly gravity field solutions from Gravity Recovery and Climate Experiment（GRACE） range measurements using modified short arc approach,in which the ambiguity of range measurements is eliminated via differentiating two adjacent range measurements.The data used for developing our monthly gravity field model are same as Tongji-GRACEOl model except that the range measurements are used to replace the range rate measurements,and our model is truncated to degree and order 60,spanning Jan.2004 to Dec.2010 also same as Tongji-GRACE01 model.Based on the comparison results of the C_（2,0）,C_（2,1）,S_（2,1）,and C_（15,15）,S_（15,15）,time series and the global mass change signals as well as the mass change time series in Amazon area of our model with those of Tongji-GRACE01 model,we can conclude that our monthly gravity field model is comparable with Tongji-GRACE01 monthly model.

AB014. Metabolomics in retinal angiogenic diseases

Retinal angiogenic diseases,such as diabetic retinopathy(DR)and age-related macular degeneration(AMD)represent the leading causes of vision impairment in developed countries.There is strong evidence that dysregulated metabolic pathways contribute to DR as known risk factors do not explain all cases and the phenomenon of metabolic memory persists for decades or longer.Some early studies also showed that changes of plasma metabolic profiles are associated with AMD.Metabolic abnormalities can be explored using the techniques of the new science of metabolomics.In this presentation,several metabolomics workflows as well as the application of data independent acquisition mass spectrometry(DIA-MS)in metabolomics will be discussed.Our recent findings from metabolomics studies on DR and AMD will be presented.

Design of new format for mass data compression

In the field of lossless compression, most kinds of traditional software have some shortages when they face the mass data. Their compressing abilities are limited by the data window size and the compressing format design. This paper presents a new design of compressing format named ＇CZ format＇ which supports the data window size up to 4 GB and has some advantages in the mass data compression. Using this format, a compressing shareware named ＇ComZip＇ is designed. The experiment results support that ComZip has better compression ratio than WinZip, Bzip2 and are compressed. And ComZip has the potential to beat 7-zip in WinRAR in most cases, especially when GBs or TBs of mass data future as the data window size exceeds 128 MB.

Exploiting big earth data from space - first experiences with the timescan processing chain

The European Sentinel missions and the latest generation of the United States Landsat satellites provide new opportunities for global environmental monitoring.They acquire imagery at spatial resolutions between 10 and 60 m in a temporal and spatial coverage that could before only be realized on the basis of lower resolution Earth observation data(>250 m).However,images gathered by these modern missions rapidly add up to data volume that can no longer be handled with standard work stations and software solutions.Hence,this contribution introduces the TimeScan concept which combines pre-existing tools to an exemplary modular pipeline for the flexible and scalable processing of massive image data collections on a variety of(private or public)computing clusters.The TimeScan framework covers solutions for data access to arbitrary mission archives(with different data provisioning policies)and data ingestion into a processing environment(EO2Data module),mission specific pre-processing of multi-temporal data collections(Data2TimeS module),and the generation of a final TimeScan baseline product(TimeS2Stats module)providing a spectrally and temporally harmonized representation of the observed surfaces.Technically,a TimeScan layer aggregates the information content of hundreds or thousands of single images available for the area and time period of interest(i.e.up to hundreds of TBs or even PBs of data)into a higher level product with significantly reduced volume.In first test,the TimeScan pipeline has been used to process a global coverage of 452,799 multispectral Landsat–8 scenes acquired from 2013 to 2015,a global data-set of 25,550 Envisat ASAR radar images collected 2010–2012,and regional Sentinel–1 and Sentinel–2 collections of∼1500 images acquired from 2014 to 2016.The resulting TimeScan products have already been successfully used in various studies related to the large-scale monitoring of environmental processes and their temporal dynamics.