Entropy

We develop and apply several novel methods quantifying dynamic multi-agent team interactions. These interactions are detected information-theoretically and captured in two ways: via (i) directed networks (interaction diagrams) representing significant coupled dynamics between pairs of agents, and (ii) state-space plots (coherence diagrams) showing coherent structures in Shannon information dynamics. This model-free analysis relates, on the one hand, the information transfer to responsiveness of the agents and the team, and, on the other hand, the information storage within the team to the teamʼs rigidity and lack of tactical flexibility. The resultant interaction and coherence diagrams reveal implicit interactions, across teams, that may be spatially long-range. The analysis was verified with a statistically significant number of experiments (using simulated football games, produced during RoboCup 2D Simulation League matches), identifying the zones of the most intense competition, the extent and types of interactions, and the correlation between the strength of specific interactions and the results of the matches.

Ce texte a été publié en français en juin 2021 dans le quatrième numéro des Cahiers COSTECH : http://www.costech.utc.fr/CahiersCOSTECH/spip.php?article117.
Il constitue un travail préparatoire en vue de la publication d'un article en polonais dans la revue Er(r)go. Theory, Literature, Culture, N°44 1/2022 (https://journals.us.edu.pl/index.php/ERRGO).

Résumé : Cet article propose de considérer la crise écologique contemporaine comme un triple problème d'écologie environnementale, d'écologie mentale et d'écologie sociale : alors que les écosystèmes naturels se voient menacés par les infrastructures industrielles, qui exploitent les ressources minérales au service d'une économie consumériste globalisée, les écosystèmes psychiques et sociaux se voient menacés par les appareils connectés, qui exploitent les ressources libidinales, au service de l'économie de l'attention et des données. Nous proposons de penser cette triple crise écologique comme un processus d'augmentation de l'entropie à différents niveaux (thermodynamique, biologique et informationnel ou psycho-social), qui requiert une double transition énergétique, fondée sur l'économie et le soin des énergies physiques et minérales, et sur l'économie et le soin des énergies psychiques et libidinales. Nous nous appuyons sur les travaux de Nicholas Georgescu-Roegen et de Bernard Stiegler, qui envisagent cette transition comme une lutte contre l'augmentation de l'entropie, sur le plan physique et environnemental d'une part, et sur le plan psychique, technique et social d'autre part.

A total of 32 MCDM methods are included in the book. 10 of which are the methods used in determining the criteria weights and the rest are the MCDM methods used for the ranking of alternatives. The book also acts as a bridge from past to present. Kitapta toplam 32 ÇKKV yöntemine yer verilmiştir. Bunların 10’u kriter önem ağırlıklarının belirlenmesinde kullanılan yöntemler olup geriye kalanlar ise alternatiflerin sıralamaları amacıyla yararlanılan ÇKKV yöntemleridir. Kitap ayrıca geçmişten günümüze bir köprü görevi de görmektedir.

Contextuality and entanglement are valuable resources for quantum computing and quantum information. Bell inequalities are used to certify entanglement; thus, it is important to understand why and how they are violated. Quantum mechanics and behavioral sciences teach us that random variables measuring the same content (the answer to the same Yes or No question) may vary, if measured jointly with other random variables. Alice and Bob raw data confirm Einsteinian non-signaling, but setting dependent experimental protocols are used to create samples of coupled pairs of distant outcomes and to estimate correlations. Marginal expectations, estimated using these final samples, depend on distant settings. Therefore, a system of random variables measured in Bell tests is inconsistently connected and it should be analyzed using a Contextuality-by-Default approach, what is done for the first time in this paper. The violation of Bell inequalities and inconsistent connectedness may be explained...

This paper presents a numerical analysis of entropy generation in a two-dimensional rectangular channel where the inlet flow undergoes thermal decomposition resulting from a chemical reaction. The model considered viscosity and thermal conductivity to be dependent of temperature. Irreversibility due to mass transport was included in the entropy generation analysis. Relevant applications of this study are possible for the design of power generation systems and reactors. The effects of the Reynolds number, Schmidt number, and length of the heat source on thermal fluid dynamics, mass transfer, and irreversibility were also investigated. It was found that thermal decomposition increases at: a) low Reynolds numbers, b) low Schmidt numbers, and c) increased length of heat source. Additionally, overall entropy generation increased when Reynolds number and length of heat source were increased, although in all cases, overall irreversibility attains a minimum value at a specific Schmidt number.

Customer Relationship Management (CRM) is a fundamental tool in the hospitality industry nowadays, which can be seen as a big-data scenario due to the large amount of recordings which are annually handled by managers. Data quality is crucial for the success of these systems, and one of the main issues to be solved by businesses in general and by hospitality businesses in particular in this setting is the identification of duplicated customers, which has not received much attention in recent literature, probably and partly because it is not an easy-to-state problem in statistical terms. In the present work, we address the problem statement of duplicated customer identification as a large-scale data analysis, and we propose and benchmark a general-purpose solution for it. Our system consists of four basic elements: (a) A generic feature representation for the customer fields in a simple table-shape database; (b) An efficient distance for comparison among feature values, in terms of th...

In this chapter we present Excess Entropy Production for human aging system as the sum of their respective subsystems and electrophysiological status. Additionally, we support the hypothesis of human brain and central neural system quantumness and we strongly suggest the theoretical and philosophical status of human brain as one of the unknown natural Dirac magnetic monopoles placed in the center of a Riemann sphere.

The fundamental holographic principle is first proposed, then demonstrated in its validity and viability through a thought experiment and then finally derived. The Heisenberg uncertainty relations are shown to follow from this fundamental relation. The quantum blackhole entropy is then demonstrated using this holographic uncertainty relation along with the application of the Landauer’s principle for the thermodynamic erasure of a bit yielding a formula with a logarithmic correction. The blackhole entropy is found to be half the value normally delivered by any other method. So, it is proposed that there is a real relevant physical horizon at the twice the Schwarzschild radius dubbed the holographic information geometric horizon.

Determining the strength of nonlinear, statistical dependencies between two variables is a crucial matter in many research fields. The established measure for quantifying such relations is the mutual information. However, estimating mutual information from limited samples is a challenging task. Since the mutual information is the difference of two entropies, the existing Bayesian estimators of entropy may be used to estimate information. This procedure, however, is still biased in the severely under-sampled regime. Here, we propose an alternative estimator that is applicable to those cases in which the marginal distribution of one of the two variables—the one with minimal entropy—is well sampled. The other variable, as well as the joint and conditional distributions, can be severely undersampled. We obtain a consistent estimator that presents very low bias, outperforming previous methods even when the sampled data contain few coincidences. As with other Bayesian estimators, our prop...

Image analysis is playing a very essential role in numerous research areas in the fields of science and technology, ranging from medical imaging to the computer science of automatic vision. Being involved in several applications, which are mainly based on a constant innovation of technologies, image analysis always requires different approaches and new algorithms, including continual upgrades and improvements of existing methods. Accordingly, the range of the analyses in which it is engaged can be considered as wide as the prospective future technologies. A challenge of image analysis is obtaining meaningful information by extracting specific features from images contained in large databases or during real-time acquisition. Among the problems requiring feature extraction are, to name a few, face detection and recognition, character recognition, and parametric determinations for augmented reality and other technologies. Another challenge is the secure encryption and decryption of multimedia data. These tasks demand highly sophisticated numerical and analytical methods. The contributions to this Special Issue provide a good overview of the most important demands and solutions concerning the abovementioned extraction, encryption, and decryption of data. In all the contributions, entropy plays a pivotal role. In the following, the reader can find subjects and problems according to the order of their publication.

The concentration of people in densely populated urban areas, especially in developing countries, calls for the use of monitoring systems like remote sensing. Such systems along with spatial analysis techniques like digital image processing and geographical information system (GIS) can be used for the monitoring and planning purposes as these enable the reporting of overall sprawl at a detailed level.In the present work, urban sprawl of the Ajmer city (situated in Rajasthan State of India) has been studied at a mid scale level, over a period of 25 years (1977–2002), to extract the information related to sprawl, area of impervious surfaces and their spatial and temporal variability. Statistical classification approaches have been used for the classification of the remotely sensed images obtained from various sensors viz. Landsat MSS, TM, ETM+ and IRS LISS-III. Urban sprawl and its spatial and temporal characteristics have been derived from the classified satellite images. The Shannon's entropy and landscape metrics (patchiness and map density) have been computed in terms of spatial phenomenon, in order to quantify the urban form (impervious area). Further, multivariate statistical techniques have been used to establish the relationship between the urban sprawl and its causative factors. Results reveal that land development (160.8%) in Ajmer is more than three times the population growth (50.1%). Shannon's entropy and landscape metrics has revealed the spatial distribution of the urban sprawl over a period of last 25 years.