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.

scholarly journals Comparative Study of Generalized Quantitative-Qualitative Inaccuracy Fuzzy Measures for Noiseless Coding Theorem and 1:1 Codes

2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
H. D. Arora ◽  
Anjali Dhiman
Keyword(s):  
Information Theory ◽  
Data Compression ◽  
Error Correction ◽  
Coding Theory ◽  
Fuzzy Information ◽  
Fuzzy Measures ◽  
Information Measures ◽  
Codeword Length ◽  
Engineering Mathematics ◽  
The Relationship

In coding theory, we study various properties of codes for application in data compression, cryptography, error correction, and network coding. The study of codes is introduced in Information Theory, electrical engineering, mathematics, and computer sciences for the transmission of data through reliable and efficient methods. We have to consider how coding of messages can be done efficiently so that the maximum number of messages can be sent over a noiseless channel in a given time. Thus, the minimum value of mean codeword length subject to a given constraint on codeword lengths has to be founded. In this paper, we have introduced mean codeword length of orderαand typeβfor 1:1 codes and analyzed the relationship between average codeword length and fuzzy information measures for binary 1:1 codes. Further, noiseless coding theorem associated with fuzzy information measure has been established.

Quantum Information Science Vis-à-Vis Information Schools

2019 ◽  
pp. 199-211
Author(s):  
P. K. Paul ◽  
D. Chatterjee ◽  
A. Bhuimali
Keyword(s):  
Information Theory ◽  
Quantum Information ◽  
Computer Science ◽  
Quantum Physics ◽  
Information Science ◽  
New Paradigm ◽  
Quantum Information Science ◽  
Information Studies ◽  
Quantum Science ◽  
Science Information

Quantum information science (QIS) is a combination of quantum science (which combines radio physics, condensed physics, and electronics) and information science (which combines computer science, information technology, mathematics, information studies, and documentation studies). Quantum information science (QIS) is actually an extension of quantum computing. Quantum information science (QIS) is mistakenly taken as quantum information theory, but it has several differences with this. Quantum information science (QIS) is mainly responsible for improved and faster acquisition, transmission, and processing of information. The 20th century is marked by three monumental achievements, namely, computer science, quantum physics, and information theory, which have not only stunned the civilized world but also ushered into a new world – a new paradigm of science and technology.

scholarly journals On Some New Trapezoidal Type Inequalities for Twice (p,q) Differentiable Convex Functions in Post-Quantum Calculus

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1605
Author(s):  
Thanin Sitthiwirattham ◽  
Ghulam Murtaza ◽  
Muhammad Aamir Ali ◽  
Sotiris K. Ntouyas ◽  
Muhammad Adeel ◽  
...  
Keyword(s):  
Information Theory ◽  
Quantum Information ◽  
Computer Science ◽  
Convex Functions ◽  
Strong Association ◽  
Quantum Information Theory ◽  
Symmetric Convex ◽  
Quantum Calculus ◽  
Interdisciplinary Field ◽  
Science Information

Quantum information theory, an interdisciplinary field that includes computer science, information theory, philosophy, cryptography, and symmetry, has various applications for quantum calculus. Inequalities has a strong association with convex and symmetric convex functions. In this study, first we establish a p,q-integral identity involving the second p,q-derivative and then we used this result to prove some new trapezoidal type inequalities for twice p,q-differentiable convex functions. It is also shown that the newly established results are the refinements of some existing results in the field of integral inequalities. Analytic inequalities of this nature and especially the techniques involved have applications in various areas in which symmetry plays a prominent role.

scholarly journals Average Redundancy for Known Sources: Ubiquitous Trees in Source Coding

2008 ◽  
Vol DMTCS Proceedings vol. AI,... (Proceedings) ◽  
Author(s):  
Wojciech Szpankowski
Keyword(s):  
Information Theory ◽  
Data Compression ◽  
Computer Science ◽  
Complex Analysis ◽  
Source Coding ◽  
Singularity Analysis ◽  
Saddle Point Method ◽  
Code Length ◽  
International Audience ◽  
Lossless Data Compression

International audience Analytic information theory aims at studying problems of information theory using analytic techniques of computer science and combinatorics. Following Hadamard's precept, these problems are tackled by complex analysis methods such as generating functions, Mellin transform, Fourier series, saddle point method, analytic poissonization and depoissonization, and singularity analysis. This approach lies at the crossroad of computer science and information theory. In this survey we concentrate on one facet of information theory (i.e., source coding better known as data compression), namely the $\textit{redundancy rate}$ problem. The redundancy rate problem determines by how much the actual code length exceeds the optimal code length. We further restrict our interest to the $\textit{average}$ redundancy for $\textit{known}$ sources, that is, when statistics of information sources are known. We present precise analyses of three types of lossless data compression schemes, namely fixed-to-variable (FV) length codes, variable-to-fixed (VF) length codes, and variable-to-variable (VV) length codes. In particular, we investigate average redundancy of Huffman, Tunstall, and Khodak codes. These codes have succinct representations as $\textit{trees}$, either as coding or parsing trees, and we analyze here some of their parameters (e.g., the average path from the root to a leaf).

scholarly journals A logical and structural thinking development tool (LST) to enhance fundamental problem-solving skills of learners of information technology

2005 ◽  
Vol 1 (1) ◽  
pp. 18
Author(s):  
Annelie Jordaan ◽  
Dawid Jordaan
Keyword(s):  
Information Technology ◽  
Problem Solving ◽  
Computer Science ◽  
Fundamental Problem ◽  
Object Oriented Programming ◽  
Interactive Software ◽  
Functional Skills ◽  
Problem Solving Skills ◽  
And Mathematics ◽  
Science Information

The role of information technology in modern education has increased significantly over the past two decades [14]. The opportunity to develop an interactive software system with the aim of enhancing fundamental problem-solving skills of learners enrolled for the Computer Science, Information Technology and Mathematics programs at tertiary institutions is possible with object-oriented programming techniques and multi-dimensional graphic design. The definition of fundamental problem-solving skills includes cognitive functional skills such as logical thinking, conceptualism with prior knowledge, relationship forming and objective analysis. Experiments done for this research indicate that given the right educational tools, cognitive functional skills of learners can be stimulated, developed and enhanced. This, in turn, may lead to an increase in the graduation rates of learners enrolled for the Computer Science, Information Technology and Mathematics program and ultimately contribute to the reshaping of the educational experience.

Student' own discoveries in information theory curriculum

2021 ◽  
pp. 50-51
Author(s):  
Yevgeny Gayev
Keyword(s):  
Information Theory ◽  
Computer Science ◽  
Coding Theory ◽  
Science Students ◽  
Approach To Learning ◽  
Modern Computer ◽  
Recent Approach

A recent approach to learning Information and Coding Theory is suggested basing on power of modern computer science. Students willingly try to rediscover known and famous technologies by means of programming them. In order not to distract their attention, an ‘easy programming’ is suggested for what MATLAB seems to be the best tool. Collection of programs developed mutually by author and his students forms an ‘Information Theory Digital Laboratory’.

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