Fractal and Trans-scale Nature of Entropy: Towards a Geometrization of Thermodynamics develops a new vision for entropy in thermodynamics by proposing a new method to geometrize. It investigates how this approach can accommodate a large number of very different physical systems, going from combustion and turbulence towards cosmology. As an example, a simple interpretation of the Hawking entropy in black-hole physics is provided. In the life sciences, entropy appears as the driving element for the organization of systems. This book demonstrates this fact using simple pedagogical tools, thus showing that entropy cannot be interpreted as a basic measure of disorder. Develop a new vision of entropy in thermodynamics Study the concept of entropy Propose a simple interpretation the entropy of Hawking Demonstrate entropy as a measure of energy dispersal

The epistemological synthesis of the various theories of evolution, since the first formulation in 1802 with the transmission of the inherited characters by J.B. Lamarck, shows the need for an alternative synthesis to that of Princeton (1947). This new synthesis integrates the scientific models of self-organization developed during the second half of the 20th century based on the laws of physics, thermodynamics, and mathematics with the emergent evolutionary problematics such as self-organized memory. This book shows, how self-organization is integrated in modern evolutionary biology. It is divided in two parts: The first part pays attention to the modern observations in paleontology and biology, which include major theoreticians of the self-organization (d’Arcy Thompson, Henri Bergson, René Thom, Ilya Prigogine). The second part presents different emergent evolutionary models including the sciences of complexity, the non-linear dynamical systems, fractals, attractors, epigenesis, systemics, and mesology with different examples of the sciences of complexity and self-organization as observed in the human lineage, from both internal (embryogenesis-morphogenesis) and external (mesology) viewpoints.

This book provides theoretical concepts and applications of fractals and multifractals to a broad range of audiences from various scientific communities, such as petroleum, chemical, civil and environmental engineering, atmospheric research, and hydrology. In the first chapter, we introduce fractals and multifractals from physics and math viewpoints. We then discuss theory and practical applications in detail. In what follows, in chapter 2, fragmentation process is modeled using fractals. Fragmentation is the breaking of aggregates into smaller pieces or fragments, a typical phenomenon in nature. In chapter 3, the advantages and disadvantages of two- and three-phase fractal models are discussed in detail. These two kinds of approach have been widely applied in the literature to model different characteristics of natural phenomena. In chapter 4, two- and three-phase fractal techniques are used to develop capillary pressure curve models, which characterize pore-size distribution of porous media. Percolation theory provides a theoretical framework to model flow and transport in disordered networks and systems. Therefore, following chapter 4, in chapter 5 the fractal basis of percolation theory and its applications in surface and subsurface hydrology are discussed. In chapter 6, fracture networks are shown to be modeled using fractal approaches. Chapter 7 provides different applications of fractals and multifractals to petrophysics and relevant area in petroleum engineering. In chapter 8, we introduce the practical advantages of fractals and multifractals in geostatistics at large scales, which have broad applications in stochastic hydrology and hydrogeology. Multifractals have been also widely applied to model atmospheric characteristics, such as precipitation, temperature, and cloud shape. In chapter 9, these kinds of properties are addressed using multifractals. At watershed scales, river networks have been shown to follow fractal behavior. Therefore, the applications of fractals are addressed in chapter 10. Time series analysis has been under investigations for several decades in physics, hydrology, atmospheric research, civil engineering, and water resources. In chapter 11, we therefore, provide fractal, multifractal, multifractal detrended fluctuation analyses, which can be used to study temporal characterization of a phenomenon, such as flow discharge at a specific location of a river. Chapter 12 addresses signals and again time series using a novel fractal Fourier analysis. In chapter 13, we discuss constructal theory, which has a perspective opposite to fractal theories, and is based on optimizationof diffusive exchange. In the case of river drainages, for example, the constructal approach begins at the divide and generates headwater streams first, rather than starting from the fundamental drainage pattern.

Gathering the proceedings of the 12th CHAOS2019 International Conference, this book highlights recent developments in nonlinear, dynamical and complex systems. The conference was intended to provide an essential forum for Scientists and Engineers to exchange ideas, methods, and techniques in the field of Nonlinear Dynamics, Chaos, Fractals and their applications in General Science and the Engineering Sciences. The respective chapters address key methods, empirical data and computer techniques, as well as major theoretical advances in the applied nonlinear field. Beyond showcasing the state of the art, the book will help academic and industrial researchers alike apply chaotic theory in their studies.

Current interest in fractal dimensions of networks is the result of more than a century of previous research on dimensions. Fractal Dimensions of Networks ties the theory and methods for computing fractal dimensions of networks to the “classic” theory of dimensions of geometric objects. The goal of the book is to provide a unified treatment of fractal dimensions of sets and networks. Since almost all of the major concepts in fractal dimensions originated in the study of sets, the book achieves this goal by first clearly presenting, with an abundance of examples and illustrations, the theory and algorithms for sets, and then showing how the theory and algorithms have been applied to networks. Thus, the book presents the classical theory and algorithms for the box counting dimension for sets, and then presents the box counting dimension for networks. All the major fractal dimensions are studied, e.g., the correlation dimension, the information dimension, the Hausdorff dimension, the multifractal spectrum, as well as many lesser known dimensions. Algorithm descriptions are accompanied by worked examples, many applications of the methods are presented, and many exercises, ranging in difficulty from easy to research level, are included.

This volume constitutes the refereed post-conference proceedings of the 6th International Conference on Machine Learning and Intelligent Communications, MLICOM 2021, held in November 2021. Due to COVID-19 pandemic the conference was held virtually. The 28 revised full papers were carefully selected from 58 submissions. The papers are organized thematically in tracks as follows: internet of vehicle communication system; applications of neural network and deep learning; intelligent massive MIMO communications; intelligent positioning and navigation systems; intelligent space and terrestrial integrated networks; machine learning algorithms and intelligent networks; image information processing.

This volume constitutes the refereed proceedings of the Second International Conference on Scale-Space Theories in Computer Vision, Scale-Space'99, held in Corfu, Greece, in September 1999. The 36 revised full papers and the 18 revised posters presented in the book were carefully reviewed and selected from 66 high-quality submissions. The book addresses all current aspects of this young and active field, in particular geometric Image flows, nonlinear diffusion, functional minimization, linear scale-space, etc.