scholarly journals Filtering Statistics on Networks

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1149
Author(s):  
G. J. Baxter ◽  
R. A. da Costa ◽  
S. N. Dorogovtsev ◽  
J. F. F. Mendes
Keyword(s):  
Exact Solution ◽  
Information Processing ◽  
Complex Systems ◽  
Random Graphs ◽  
Strong Dependence ◽  
Initial Configuration ◽  
Final States ◽  
Two Factors ◽  
Processing Information ◽  
Simple Filter

Compression, filtering, and cryptography, as well as the sampling of complex systems, can be seen as processing information. A large initial configuration or input space is nontrivially mapped to a smaller set of output or final states. We explored the statistics of filtering of simple patterns on a number of deterministic and random graphs as a tractable example of such information processing in complex systems. In this problem, multiple inputs map to the same output, and the statistics of filtering is represented by the distribution of this degeneracy. For a few simple filter patterns on a ring, we obtained an exact solution of the problem and numerically described more difficult filter setups. For each of the filter patterns and networks, we found three key numbers that essentially describe the statistics of filtering and compared them for different networks. Our results for networks with diverse architectures are essentially determined by two factors: whether the graphs structure is deterministic or random and the vertex degree. We find that filtering in random graphs produces much richer statistics than in deterministic graphs, reflecting the greater complexity of such graphs. Increasing the graph’s degree reduces this statistical richness, while being at its maximum at the smallest degree not equal to two. A filter pattern with a strong dependence on the neighbourhood of a node is much more sensitive to these effects.

ON THE CLASSIFICATION OF DIGITAL TECHNOLOGIES IN CIVIL PROCESS

2019 ◽  
pp. 27-35
Author(s):  
Alexandr Neznamov
Keyword(s):  
Information Processing ◽  
Scientific Community ◽  
Digital Technologies ◽  
Significant Feature ◽  
Legal Proceedings ◽  
Civil Process ◽  
Civil Proceedings ◽  
Processing Information ◽  
The Impact

Digital technologies are no longer the future but are the present of civil proceedings. That is why any research in this direction seems to be relevant. At the same time, some of the fundamental problems remain unattended by the scientific community. One of these problems is the problem of classification of digital technologies in civil proceedings. On the basis of instrumental and genetic approaches to the understanding of digital technologies, it is concluded that their most significant feature is the ability to mediate the interaction of participants in legal proceedings with information; their differentiating feature is the function performed by a particular technology in the interaction with information. On this basis, it is proposed to distinguish the following groups of digital technologies in civil proceedings: a) technologies of recording, storing and displaying (reproducing) information, b) technologies of transferring information, c) technologies of processing information. A brief description is given to each of the groups. Presented classification could serve as a basis for a more systematic discussion of the impact of digital technologies on the essence of civil proceedings. Particularly, it is pointed out that issues of recording, storing, reproducing and transferring information are traditionally more «technological» for civil process, while issues of information processing are more conceptual.

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).

scholarly journals EXACT SOLUTION OF AN IRREVERSIBLE ONE-DIMENSIONAL MODEL WITH FULLY BIASED SPIN EXCHANGES

1996 ◽  
Vol 10 (25) ◽  
pp. 3451-3459 ◽  
Author(s):  
ANTÓNIO M.R. CADILHE ◽  
VLADIMIR PRIVMAN
Keyword(s):  
Exact Solution ◽  
Domain Wall ◽  
Nearest Neighbor ◽  
Spin Exchange ◽  
Initial Conditions ◽  
Strong Dependence ◽  
Zero Temperature ◽  
Dimensional Model ◽  
One Dimensional ◽  
Temperature Dynamics

We introduce a model with conserved dynamics, where nearest neighbor pairs of spins ↑↓ (↓↑) can exchange to assume the configuration ↓↑ (↑↓), with rate β(α), through energy decreasing moves only. We report exact solution for the case when one of the rates, α or β, is zero. The irreversibility of such zero-temperature dynamics results in strong dependence on the initial conditions. Domain wall arguments suggest that for more general, finite-temperature models with steady states the dynamical critical exponent for the anisotropic spin exchange is different from the isotropic value.

scholarly journals ENGINEERING SUSTAINABLE COMPLEX SYSTEMS

2013 ◽  
Vol 4 (4) ◽  
pp. 4-14 ◽  
Author(s):  
Tareq Z. Ahram
Keyword(s):  
Complex Systems ◽  
Systems Engineering ◽  
New Technologies ◽  
Business Environment ◽  
Sustainable Business ◽  
Global Business ◽  
Two Factors ◽  
Critical Requirement ◽  
And Performance ◽  
Industrial Solutions

Abstract Given the most competitive nature of global business environment, effective engineering innovation is a critical requirement for all levels of system lifecycle development. The society and community expectations have increased beyond environmental short term impacts to global long term sustainability approach. Sustainability and engineering competence skills are extremely important due to a general shortage of engineering talent and the need for mobility of highly trained professionals [1]. Engineering sustainable complex systems is extremely important in view of the general shortage of resources and talents. Engineers implement new technologies and processes to avoid the negative environmental, societal and economic impacts. Systems thinking help engineers and designers address sustainable development issues with a global focus using leadership and excellence. This paper introduces the Systems Engineering (SE) methodology for designing complex and more sustainable business and industrial solutions, with emphasis on engineering excellence and leadership as key drivers for business sustainability. The considerable advancements achieved in complex systems engineering indicate that the adaptation of sustainable SE to business needs can lead to highly sophisticated yet widely useable collaborative applications, which will ensure the sustainability of limited resources such as energy and clean water. The SE design approach proves critical in maintaining skills needed in future capable workforce. Two factors emerged to have the greatest impact on the competitiveness and sustainability of complex systems and these were: improving skills and performance in engineering and design, and adopting SE and human systems integration (HSI) methodology to support sustainability in systems development. Additionally, this paper provides a case study for the application of SE and HSI methodology for engineering sustainable and complex systems.

Lost in the Woods

2016 ◽  
Author(s):  
Arthur Lupia
Keyword(s):  
Information Processing ◽  
Deliberative Democracy ◽  
Source Credibility ◽  
Logical Necessity ◽  
Educational Strategies ◽  
Two Factors ◽  
Important Challenge ◽  
Degree Of Control ◽  
Basic Facts ◽  
Almost All

Chapter 5 offered a logic that clarifies the kinds of information that can increase knowledge and competence. In the coming chapters, I explain how educators can more effectively communicate this kind of information to others. From this point forward in part I, I focus on the time after an educator has identified information that can increase desired knowledge and competences. An educator in this situation faces an important challenge: Just because information can increase knowledge and competence does not mean that it will do so. For information to have these effects, prospective learners must think about the information in certain ways. For example, if a piece of information is to increase another person’s competence, that person must pay attention to the information. If the prospective learner ignores the information or processes it in ways that an educator did not anticipate, then the information may not have the educator’s desired effect. In chapters 6 to 8, I use insights from research on information processing to describe two necessary conditions for persuading an audience to think about information in ways that increase knowledge and competence. These conditions are gaining an audience’s attention and having sufficient source credibility. I focus on these conditions not only because of their logical necessity, but also because they are two factors over which educators often have some degree of control. “Not so fast!” This is a reaction that I sometimes get when suggesting that we base educational strategies on basic facts about attention and credibility, rather than continuing to rely on often-faulty intuitions about how others learn. Indeed, I have met many educators who initially argue that: “Being an expert in (say, deliberative democracy) makes me persuasive. Citizens and policymakers should respect me and be interested in what I have to say.” This is an attractive notion. It is also an illusion in many cases. Learning is a process that has knowable biological and psychological properties. A fundamental implication of these properties is that people ignore almost all of the information to which they could attend and people forget about almost all of the information to which they pay attention.

Knowledge Geometry

2015 ◽  
Vol 14 (04) ◽  
pp. 1550028 ◽  
Author(s):  
Flávio Luis de Mello ◽  
Roberto Lins de Carvalho
Keyword(s):  
Knowledge Management ◽  
Information Processing ◽  
Knowledge Acquisition ◽  
Information Management ◽  
Spatial Representation ◽  
Geometric Approach ◽  
Alternative Theory ◽  
Acquisition Process ◽  
Evaluation Systems ◽  
Processing Information

This paper aims to present what we call knowledge geometry, an alternative theory for spatial representation of features related to information processing, information management, and knowledge management. It is a unique geometric approach for representing intuition, reification, interpretation, and deduction processes, as well as their relations. We employ the concept of cultural filter and use what we call real, conceptual, and symbolic planes in order to support transformations which occur along the perception of a phenomenon. After that, we discuss the use of evaluation systems to judge concepts and also the use of semantic systems as a communication language. Finally, a framework of the knowledge acquisition process in the field of the proposed theory is offered, proving the feasibility of its automation.

Delusion

2013 ◽  
Author(s):  
Martin Davies ◽  
Andy Egan
Keyword(s):  
Information Processing ◽  
Cognitive Approach ◽  
Explanatory Framework ◽  
Two Factors ◽  
Personal Level ◽  
Cognitive Approaches

Cognitive approaches contribute to our understanding of delusions by providing an explanatory framework that extends beyond the personal level to the sub personal level of information-processing systems. According to one influential cognitive approach, two factors are required to account for the content of a delusion, its initial adoption as a belief, and its persistence. This chapter reviews Bayesian developments of the two-factor framework.

scholarly journals A Teaching Resource for a Computational Framework of the Value of Information in Origin of Life

2018 ◽  
Author(s):  
soumya banerjee ◽  
joyeeta ghose
Keyword(s):  
Complex Systems ◽  
Origin Of Life ◽  
Value Of Information ◽  
Critical Role ◽  
Computational Framework ◽  
Teaching Resource ◽  
Processing Information ◽  
The Origin Of Life ◽  
Role Of Information

Information plays a critical role in complex biological systems. Complex systems like immune systems andant colonies co-ordinate heterogeneous components in a decentralized fashion. How do these distributeddecentralized systems function? One key component is how these complex systems efficiently processinformation. These complex systems have an architecture for integrating and processing information comingin from various sources and points to the value of information in the functioning of different complexbiological systems. This paper is a teaching resource that explains the role of information processing inquestions around the origin of life and suggests how computational simulations may yield insights intoquestions related to the origin of life.

Information Structure Parsing for Chinese Legal Texts

2019 ◽  
Vol 15 (1) ◽  
pp. 46-64 ◽  
Author(s):  
Bo Sun
Keyword(s):  
Information Processing ◽  
Discourse Analysis ◽  
Information Structure ◽  
Viterbi Algorithm ◽  
Support Vector ◽  
Linguistic Features ◽  
Discourse Parsing ◽  
Legal Texts ◽  
Processing Information ◽  
Rule Based Approach

Information processing is one of the main concerns in the field of artificial intelligence, because it can benefit many related downstream tasks. To facilitate information processing, information structure parsing is assumed to be of great significance. This article proposes a discourse analysis based approach so that information structure of Chinese legal texts can be recognized automatically. This article employs Discourse Information Theory to explore information features of Chinese legal texts. The texts used in this study include 6 types, each type containing 60 training texts and 30 testing texts. After that, a set of rules is formulated to classify legal texts and identify the categories of information units. Finally, to examine the performance of the rules, a comparison is made by designing a Support Vector Machine classifier and a Viterbi algorithm decoder. The experiment demonstrates that the rule based approach outperforms the statistics based approaches. This research suggests that discourse analysis may provide some linguistic features conducive to discourse parsing.

Measuring Features of Complex Systems

2020 ◽  
pp. 87-116
Author(s):  
J. Ladyman ◽  
K. Wiesner
Keyword(s):  
Information Processing ◽  
Complex Systems ◽  
Complexity Science ◽  
Effective Measure ◽  
Statistical Complexity ◽  
Universal Behaviour

This chapter offers a guide to quantifying complexity based on the fruits of the analysis of the previous chapters. Many measures of complexity have been proposed since scientists first began to study complex systems, and the list is still growing. If complexity is a collection of features rather than a single phenomenon, then all quantitative measures of complexity can quantify only aspects of complexity rather than complexity as such. The chapter demonstrates the truism of complexity science that it is computational and probabilistic. It also further explains some of the new kinds of invariance and forms of universal behaviour that emerge when complex systems are modelled as networks and information-processing systems. The chapter then looks at a few, by now classic, measures of complexity from the 1980s and 1990s, including effective complexity, effective measure complexity, statistical complexity, and logical depth.

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