scholarly journals Hiding Any Data File Format into Wave Cover

2019 ◽  
Vol 16 (69) ◽  
pp. 1-10
Author(s):  
Narjis Mezaal Shati ◽  
Ali Jassim Mohamed Ali
Keyword(s):  
Data File ◽  
Markup Language ◽  
File Format ◽  
Test Results

In the current study a steganography approach utilized to hide various data file format in wave files cover. Lest significant bit insertion (LSB) used to embedding a regular computer files (such as graphic, execution file (exe), sound, text, hyper text markup language (HTML) …etc) in a wave file with 2-bits hiding rates. The test results achieved good performance to hide any data file in wave file.

scholarly journals cd2sbgnml: bidirectional conversion between CellDesigner and SBGN formats

2020 ◽  
Vol 36 (8) ◽  
pp. 2620-2622 ◽  
Author(s):  
Irina Balaur ◽  
Ludovic Roy ◽  
Alexander Mazein ◽  
S Gökberk Karaca ◽  
Ugur Dogrusoz ◽  
...  
Keyword(s):  
Systems Biology ◽  
Web Service ◽  
Large Scale ◽  
Supplementary Information ◽  
Markup Language ◽  
File Format ◽  
Signalling Network ◽  
Lesser General Public License ◽  
Systems Biology Markup Language ◽  
General Public License

Abstract Motivation CellDesigner is a well-established biological map editor used in many large-scale scientific efforts. However, the interoperability between the Systems Biology Graphical Notation (SBGN) Markup Language (SBGN-ML) and the CellDesigner’s proprietary Systems Biology Markup Language (SBML) extension formats remains a challenge due to the proprietary extensions used in CellDesigner files. Results We introduce a library named cd2sbgnml and an associated web service for bidirectional conversion between CellDesigner’s proprietary SBML extension and SBGN-ML formats. We discuss the functionality of the cd2sbgnml converter, which was successfully used for the translation of comprehensive large-scale diagrams such as the RECON Human Metabolic network and the complete Atlas of Cancer Signalling Network, from the CellDesigner file format into SBGN-ML. Availability and implementation The cd2sbgnml conversion library and the web service were developed in Java, and distributed under the GNU Lesser General Public License v3.0. The sources along with a set of examples are available on GitHub (https://github.com/sbgn/cd2sbgnml and https://github.com/sbgn/cd2sbgnml-webservice, respectively). Supplementary information Supplementary data are available at Bioinformatics online.

Shape Similarity Matching With Octree Representations

2009 ◽  
Vol 9 (3) ◽  
Author(s):  
Jingsheng Zhang ◽  
Shana Smith
Keyword(s):  
Shape Matching ◽  
Data File ◽  
Markup Language ◽  
3D Shape Retrieval ◽  
3D Shape ◽  
Space Efficiency ◽  
Extensible Markup ◽  
Octree Representation ◽  
3D Shape Matching ◽  
Mesh Models

To achieve effective 3D shape retrieval, there is a crucial need for efficient shape matching methods. This paper introduces a new method for 3D shape matching, which uses a simplified octree representation of 3D mesh models. The simplified octree representation was developed to improve time and space efficiency over prior representations. The proposed method also stores octree information in extensible markup language format, rather than in a new proprietary data file type, to facilitate comparing models over the Internet.

A Multi-Dimensional Data Storage Using Quad-Tree and Z-Ordering

2013 ◽  
Vol 347-350 ◽  
pp. 2436-2441
Author(s):  
Fang Hou ◽  
Cheng Hui Huang ◽  
Ji Yuan Lu
Keyword(s):  
Data Storage ◽  
Performance Test ◽  
Tree Structure ◽  
File Format ◽  
Test Results ◽  
Space Filling ◽  
Space Filling Curves ◽  
Quad Tree

Multi-dimensional applications use tree structure to store data and space filling curves to traverse data. Most frequently used Quad-tree and Z-ordering curve are analyzed. By importing these to a HDF5 file format, a multi-dimensional data storage subsystem is constructed. Performance test results show in a sequential reading application environment, this method is feasible and efficient.

scholarly journals File Formats for Big Data Storage Systems

2019 ◽  
Vol 9 (1) ◽  
pp. 2906-2912
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data File ◽  
Data System ◽  
Heterogeneous Environments ◽  
File Format ◽  
Data Systems ◽  
File Formats ◽  
Big Data Systems ◽  
Big Data Storage

Big data is one of the most influential technologies of the modern era. However, in order to support maturity of big data systems, development and sustenance of heterogeneous environments is requires. This, in turn, requires integration of technologies as well as concepts. Computing and storage are the two core components of any big data system. With that said, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings the facet of big data file formats into picture. This paper classifies available big data file formats into five categories namely text-based, row-based, column-based, in-memory and data storage services. It also compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Lastly, it provides a discussion on tradeoffs that must be considered while choosing a file format for a big data system, providing a framework for creation for file format selection criteria.

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