scholarly journals Complex systems are always correlated but rarely information processing

2021 ◽  
Author(s):  
Karoline Wiesner ◽  
James Ladyman
Keyword(s):  
Information Theory ◽  
Information Processing ◽  
Data Analysis ◽  
Pattern Formation ◽  
Complex Systems ◽  
Symbolic Representation ◽  
Versus Data ◽  
Open Questions ◽  
First Case ◽  
Case Versus

Abstract `Complex systems are information processors' is a statement that is frequently made. Here we argue for the distinction between information processing -- in the sense of encoding and transmitting a symbolic representation -- and the formation of correlations (pattern formation / self-organisation). The study of both uses tools from information theory, but the purpose is very different in each case: explaining the mechanisms and understanding the purpose or function in the first case, versus data analysis and correlation extraction in the latter. We give examples of both and discuss some open questions. The distinction helps focus research efforts on the relevant questions in each case.

Data Analysis of Complex Systems

2011 ◽  
Author(s):  
Misty K. Blowers
Keyword(s):  
Data Analysis ◽  
Complex Systems

Covid-19 Cases in India: A Visual Exploratory Data Analysis Model (Preprint)

2020 ◽  
Author(s):  
Jayesh S
Keyword(s):  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Case Fatality ◽  
Public Health Emergency ◽  
Virus Spread ◽  
Analysis Model ◽  
Case Fatality Ratio ◽  
First Case ◽  
Exploratory Data ◽  
The Government

UNSTRUCTURED Covid-19 outbreak was first reported in Wuhan, China. The deadly virus spread not just the disease, but fear around the globe. On January 2020, WHO declared COVID-19 as a Public Health Emergency of International Concern (PHEIC). First case of Covid-19 in India was reported on January 30, 2020. By the time, India was prepared in fighting against the virus. India has taken various measures to tackle the situation. In this paper, an exploratory data analysis of Covid-19 cases in India is carried out. Data namely number of cases, testing done, Case Fatality ratio, Number of deaths, change in visits stringency index and measures taken by the government is used for modelling and visual exploratory data analysis.

scholarly journals New Inequalities between Information Measures of Network Information Content

2013 ◽  
Vol 2013 ◽  
pp. 1-3 ◽  
Author(s):  
Pantelimon-George Popescu ◽  
Florin Pop ◽  
Alexandru Herişanu ◽  
Nicolae Ţăpuş
Keyword(s):  
Information Processing ◽  
Complex Systems ◽  
Complex Networks ◽  
Information Content ◽  
Discrete Case ◽  
Network Information ◽  
Information Inequalities ◽  
Information Measures ◽  
New Inequalities

We refine a classical logarithmic inequality using a discrete case of Bernoulli inequality, and then we refine furthermore two information inequalities between information measures for graphs, based on information functionals, presented by Dehmer and Mowshowitz in (2010) as Theorems 4.7 and 4.8. The inequalities refer to entropy-based measures of network information content and have a great impact for information processing in complex networks (a subarea of research in modeling of complex systems).

Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments

2003 ◽  
Vol 01 (03) ◽  
pp. 541-586 ◽  
Author(s):  
Tero Aittokallio ◽  
Markus Kurki ◽  
Olli Nevalainen ◽  
Tuomas Nikula ◽  
Anne West ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Microarray Data ◽  
Microarray Data Analysis ◽  
Biological Research ◽  
Microarray Experiments ◽  
Dna Microarray Data ◽  
Open Questions ◽  
Analysis Technique ◽  
Wide Range

Microarray analysis has become a widely used method for generating gene expression data on a genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the analysis of such data. A wide range of approaches are available for computational analysis, but no general consensus exists as to standard for microarray data analysis protocol. Consequently, the choice of data analysis technique is a crucial element depending both on the data and on the goals of the experiment. Therefore, basic understanding of bioinformatics is required for optimal experimental design and meaningful interpretation of the results. This review summarizes some of the common themes in DNA microarray data analysis, including data normalization and detection of differential expression. Algorithms are demonstrated by analyzing cDNA microarray data from an experiment monitoring gene expression in T helper cells. Several computational biology strategies, along with their relative merits, are overviewed and potential areas for additional research discussed. The goal of the review is to provide a computational framework for applying and evaluating such bioinformatics strategies. Solid knowledge of microarray informatics contributes to the implementation of more efficient computational protocols for the given data obtained through microarray experiments.

scholarly journals Detection of the homotopy type of an object using differential invariants of an approximating map

2019 ◽  
Vol 43 (4) ◽  
pp. 611-617
Author(s):  
S.V. Kurochkin
Keyword(s):  
Neural Network ◽  
Data Analysis ◽  
Homotopy Type ◽  
Morse Theory ◽  
Object Representation ◽  
Differential Invariants ◽  
Topological Data Analysis ◽  
Higher Dimension ◽  
Differential Topology ◽  
Open Questions

A method of topological data analysis is proposed that allows one to find out the homotopy type of the object under study. Unlike mature and widely used methods based on persistent homologies, our method is based on computing differential invariants of some map associated with an approximating map. Differential topology tools and the analogy with the main result in Morse theory are used. The approximating map can be constructed in the usual way using a neural network or otherwise. The method allows one to identify the homotopy type of an object in the plane because the number of circles in the homotopy equivalent object representation as a wedge is expressed through the degree of some map associated with the approximating map. The performance of the algorithm is illustrated by examples from the MNIST database and transforms thereof. Generalizations and open questions relating to a higher-dimension case are discussed.

Development of a new approach to data analysis of complex systems: study of synchronization in the dynamics of solar activity parameters

2021 ◽  
Author(s):  
Valentin A. Yunusov ◽  
Sergey A. Demin ◽  
Sergey F. Timashev ◽  
Natalya Y. Demina
Keyword(s):  
Data Analysis ◽  
Solar Activity ◽  
Complex Systems ◽  
New Approach

Ankle Bones, Rogues, and Sexual Freedom for Women

2011 ◽  
pp. 461-468
Author(s):  
Nigel K.L. Pope ◽  
Kevin E. Voges
Keyword(s):  
Information Processing ◽  
Data Analysis ◽  
Problem Solving ◽  
Computational Intelligence ◽  
History Of Mathematics ◽  
Volume Form ◽  
Paper Briefly ◽  
Sexual Freedom ◽  
History Of ◽  
And Control

In this chapter we review the history of mathematics-based approaches to problem solving. The authors suggest that while the ability of analysts to deal with the extremes of data now available is leading to a new leap in the handling of data analysis, information processing, and control systems, that ability remains grounded in the work of early pioneers of statistical thought. Beginning with pre-history, the paper briefly traces developments in analytical thought to the present day, identifying milestones in this development. The techniques developed in studies of computational intelligence, the applications of which are presented in this volume, form the basis for the next great development in analytical thought.

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