Datavis : a research work in data management toolkit

With increasing popularity of interactive data analysis, simulations and visualization, there is a need for flexibility in the development and use of data management toolkits. Although some work has done by the researchers, a solid foundation is not yet established. This thesis introduces Datavis, a flexible, extensible data management toolkit that integrates simulation systems into data visualization systems. Datavis links together standard numerical simulation tools such as EASY5 [Bl] with visualization packages like GGobi making the data flow among these different tools transparent to the user. Datavis allows users to perform data analysis interactively independent of the data format or the packages needed in the process. Datavis has three main components: The core that handles the user requests, the data handler which takes care of the organization and storage of the data, and the visualization handler which takes care of the instantiation and manipulation of the visualization system. The proposed toolkit has been successfully implemented and transferred to use as part of routine data analysis activities at a company. At the same time, the work on Datavis has laid the foundation for more sophisticated approaches on integrating simulation and visualization for data analysis

CBIR by Using Features of Shape and Color

Geometrical Feature is a key issue in content based image retrieval (CBIR). In the prior work, various surface highlights have been proposed in writing, including literature, including statistic ethos and spectral methods. But in many cases most of them are not precisely captured. The most critical texture feature in an image called edge information. As of late, a portion of the authors on multi-scale analysis, particularly the curve-let research about, gave great chance to remove more accurate texture features for image recovery. Curve-let has indicated promising execution, anyway it was initially proposed for image de-noising. In this paper, another image include in view of curve-let transform has been proposed. We apply discrete curve-let transform on surface image and transformed images; we process the low order statistics. Images are then represented using the extracted texture features. We discuss design, implementation, and performance analysis of Tamara’s new statistical feature based image retrieval system. One of our major contributions is to propose a new scalable image retrieval scheme using shape and color based features, which is shown to be scalable to high dimensional of image data

Assessment of Work Pedestal on RSA in Text Cryptographic System

Cryptography is a Greek word, crypto signifies ‘hidden or covered up’ and graphy means ‘study’. The conversion of plain text to cipher text is called as encryption and changing the cipher text to plain text is called as decryption. Cryptographic algorithm further divides in symmetric cryptography and asymmetric cryptography. Symmetric cryptography has only one key for both encryption and decryption, this key is called as secret key or private key. Asymmetric cryptography has two keys, one key is used for encryption this key is called public key and other key is used for decryption this key is called as private key. In this paper, we survey on the customized advance of RSA by using manifold of public keys and prime numbers. This algorithm is providing more secure communication over the network of text files

Building Near-Real-Time Processing Pipelines with the Spark-MPI Platform

Advances in detectors and computational technologies provide new opportunities for applied research and the fundamental sciences. Concurrently, dramatic increases in the three Vs (Volume, Velocity, and Variety) of experimental data and the scale of computational tasks produced the demand for new real-time processing systems at experimental facilities. Recently, this demand was addressed by the Spark-MPI approach connecting the Spark data-intensive platform with the MPI high-performance framework. In contrast with existing data management and analytics systems, Spark introduced a new middleware based on resilient distributed datasets (RDDs), which decoupled various data sources from high-level processing algorithms. The RDD middleware significantly advanced the scope of data-intensive applications, spreading from SQL queries to machine learning to graph processing. Spark-MPI further extended the Spark ecosystem with the MPI applications using the Process Management Interface. The paper explores this integrated platform within the context of online ptychographic and tomographic reconstruction pipelines.Comment: New York Scientific Data Summit, August 6-9, 201

Datavis: a research work in data management toolkit

With increasing popularity of interactive data analysis, simulations and visualization, there is a need for flexibility in the development and use of data management toolkits. Although some work has done by the researchers, a solid foundation is not yet established. This thesis introduces Datavis, a flexible, extensible data management toolkit that integrates simulation systems into data visualization systems. Datavis links together standard numerical simulation tools such as EASY5 [Bl] with visualization packages like GGobi making the data flow among these different tools transparent to the user. Datavis allows users to perform data analysis interactively independent of the data format or the packages needed in the process. Datavis has three main components: The core that handles the user requests, the data handler which takes care of the organization and storage of the data, and the visualization handler which takes care of the instantiation and manipulation of the visualization system. The proposed toolkit has been successfully implemented and transferred to use as part of routine data analysis activities at a company. At the same time, the work on Datavis has laid the foundation for more sophisticated approaches on integrating simulation and visualization for data analysis.</p

Datavis : a research work in data management toolkit

With increasing popularity of interactive data analysis, simulations and visualization, there is a need for flexibility in the development and use of data management toolkits. Although some work has done by the researchers, a solid foundation is not yet established. This thesis introduces Datavis, a flexible, extensible data management toolkit that integrates simulation systems into data visualization systems. Datavis links together standard numerical simulation tools such as EASY5 [Bl] with visualization packages like GGobi making the data flow among these different tools transparent to the user. Datavis allows users to perform data analysis interactively independent of the data format or the packages needed in the process. Datavis has three main components: The core that handles the user requests, the data handler which takes care of the organization and storage of the data, and the visualization handler which takes care of the instantiation and manipulation of the visualization system. The proposed toolkit has been successfully implemented and transferred to use as part of routine data analysis activities at a company. At the same time, the work on Datavis has laid the foundation for more sophisticated approaches on integrating simulation and visualization for data analysis.</p

geojson_test_dataset

<p>Test geojson data</p