scholarly journals Textual data compression in computational biology: a synopsis

2009 ◽  
Vol 25 (13) ◽  
pp. 1575-1586 ◽  
Author(s):  
R. Giancarlo ◽  
D. Scaturro ◽  
F. Utro
Keyword(s):  
Computational Biology ◽  
Data Compression ◽  
Textual Data

Textual data compression in computational biology: Algorithmic techniques

2012 ◽  
Vol 6 (1) ◽  
pp. 1-25 ◽  
Author(s):  
R. Giancarlo ◽  
D. Scaturro ◽  
F. Utro
Keyword(s):  
Computational Biology ◽  
Data Compression ◽  
Textual Data ◽  
Algorithmic Techniques

scholarly journals A Novel Encoding Algorithm for Textual Data Compression

2020 ◽  
Author(s):  
Anas Al-okaily ◽  
Abdelghani Tbakhi
Keyword(s):  
Information Theory ◽  
Data Compression ◽  
Computer Science ◽  
Coding Theory ◽  
Fundamental Problem ◽  
Novel Approach ◽  
Textual Data ◽  
Science Information

ABSTRACTData compression is a fundamental problem in the fields of computer science, information theory, and coding theory. The need for compressing data is to reduce the size of the data so that the storage and the transmission of them become more efficient. Motivated from resolving the compression of DNA data, we introduce a novel encoding algorithm that works for any textual data including DNA data. Moreover, the design of this algorithm paves a novel approach so that researchers can build up on and resolve better the compression problem of DNA or textual data.

Data Compression Techniques and Standards

2011 ◽  
pp. 61-86
Author(s):  
Phillip K.C. Tse
Keyword(s):  
Image Compression ◽  
Data Compression ◽  
Video Compression ◽  
Storage System ◽  
Multimedia Data ◽  
Jpeg2000 Compression ◽  
Compression Model ◽  
Textual Data ◽  
Mpeg2 Video

In the previous chapter, we see that the performance of a storage system depends on the amount of data being retrieved. The size of multimedia objects are however very large in size. Thus, the performance of the storage system can be enhanced if the object sizes are reduced. Therefore, multimedia objects are always compressed when they are stored. In addition, the performance of most subsystems depends on the amount of data being processed. Since multimedia objects are large in size, their accessing times are long. Thus, multimedia objects are always kept in their compressed form when they are being stored, retrieved, and processed. We shall describe the commonly used compression techniques and compression standards in this chapter. We first describe the general compression model in the next section. Then, we explain the techniques in compressing textual data. This is followed by the image compression techniques. In particular, we shall explain the JPEG2000 compression with details. Lastly, we explain the MPEG2 video compression standard. These compression techniques are helpful to understand the multimedia data being stored and retrieved.

scholarly journals Lossless Image Compression Schemes: A Review

2021 ◽  
pp. 14-22
Author(s):  
I. Manga ◽  
E. J. Garba ◽  
A. S. Ahmadu
Keyword(s):  
Image Compression ◽  
Data Compression ◽  
Image Data ◽  
Original Data ◽  
Lossy Compression ◽  
Video Content ◽  
Textual Data ◽  
Audio Data ◽  
Lossless Data Compression ◽  
Compressed Data

Data compression refers to the process of representation of data using fewer number of bits. Data compression can be lossless or lossy. There are many schemes developed and used to perform either lossless or lossy compression. Lossless data compression allows the original data be conveniently reconstructed from the compressed data while lossy compression allow only an approximate of the original data to be constructed. The type of data to compressed can be classified as image data, textual data, audio data or even video content. Various researches are being carried out in the area of image compression. This paper presents various literatures in field of data compression and the techniques used to compress image using lossless type of compression. In conclusion, the paper reviewed some schemes used to compress an image using a single schemes or combination of two or more schemes methods.

Modeling longitudinal dynamics in textual data

2003 ◽  
Author(s):  
Kevin Dooley ◽  
Steven Corman
Keyword(s):  
Longitudinal Dynamics ◽  
Textual Data
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