Laith Ali Abdulsahib Albaldawi

ABSTRACT Log in to post comments In this paper we consider the problem of storing sequences of symbols in a compressed format, while supporting random access to the symbols without decompression. Although this is a well-studied problem when the data is textual, the kind of sequences we look at are not textual, and we argue that traditional compression methods used in the text algorithms community (such as compressors targeting $k$-th order empirical entropy) do not perform as well on these sequential data, and simpler methods such as Huffman-coding the deltas between sequence elements give better compression performance. We discuss data structures that allow random access to sequence elements that target such measure

ABSTRACT Log in to post comments In this paper we consider the problem of storing sequences of symbols in a compressed format, while supporting random access to the symbols without decompression. Although this is a well-studied problem when the data is textual, the kind of sequences we look at are not textual, and we argue that traditional compression methods used in the text algorithms community (such as compressors targeting $k$-th order empirical entropy) do not perform as well on these sequential data, and simpler methods such as Huffman-coding the deltas between sequence elements give better compression performance. We discuss data structures that allow random access to sequence elements that target such measure

The goal of this workshop is to present the possibilities of how to mange the main memory with large amount of data and form the data to be succinct

Giving seminar about Binary decision diagram and how to represent the related data in term of speed and space. In addition, we will discuss the last used algorithms in this field. This seminar will take a place in CS department on 9th March 2020

In mean time, I am studying PhD in Full time study in Leicester university