Author: Anders Malthe-Sørenssen
Publisher: Springer Nature
ISBN: 3031599004
Category :
Languages : en
Pages : 221
Book Description
Percolation Theory Using Python
Author: Anders Malthe-Sørenssen
Publisher: Springer Nature
ISBN: 3031599004
Category :
Languages : en
Pages : 221
Book Description
Publisher: Springer Nature
ISBN: 3031599004
Category :
Languages : en
Pages : 221
Book Description
Quantitative Biosciences Companion in Python
Author: Joshua S. Weitz
Publisher: Princeton University Press
ISBN: 0691259615
Category : Science
Languages : en
Pages : 273
Book Description
A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scales This lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organized around central questions in the life sciences, introducing landmark advances in the field while teaching students—whether from the life sciences, physics, computational sciences, engineering, or mathematics—how to reason quantitatively in the face of uncertainty. Draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communities Encourages good coding practices, clear and understandable modeling, and accessible presentation of results Helps students to develop a diverse repertoire of simulation approaches, enabling them to model at the appropriate scale Builds practical expertise in a range of methods, including sampling from probability distributions, stochastic branching processes, continuous time modeling, Markov chains, bifurcation analysis, partial differential equations, and agent-based simulations Bridges the gap between the classroom and research discovery, helping students to think independently, troubleshoot and resolve problems, and embark on research of their own Stand-alone computational lab guides for Quantitative Biosciences also available in R and MATLAB
Publisher: Princeton University Press
ISBN: 0691259615
Category : Science
Languages : en
Pages : 273
Book Description
A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scales This lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organized around central questions in the life sciences, introducing landmark advances in the field while teaching students—whether from the life sciences, physics, computational sciences, engineering, or mathematics—how to reason quantitatively in the face of uncertainty. Draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communities Encourages good coding practices, clear and understandable modeling, and accessible presentation of results Helps students to develop a diverse repertoire of simulation approaches, enabling them to model at the appropriate scale Builds practical expertise in a range of methods, including sampling from probability distributions, stochastic branching processes, continuous time modeling, Markov chains, bifurcation analysis, partial differential equations, and agent-based simulations Bridges the gap between the classroom and research discovery, helping students to think independently, troubleshoot and resolve problems, and embark on research of their own Stand-alone computational lab guides for Quantitative Biosciences also available in R and MATLAB
Practical Social Network Analysis with Python
Author: Krishna Raj P.M.
Publisher: Springer
ISBN: 3319967460
Category : Computers
Languages : en
Pages : 355
Book Description
This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis. With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks. This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.
Publisher: Springer
ISBN: 3319967460
Category : Computers
Languages : en
Pages : 355
Book Description
This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis. With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks. This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.
Topological Methods in Data Analysis and Visualization VI
Author: Ingrid Hotz
Publisher: Springer Nature
ISBN: 3030835006
Category : Mathematics
Languages : en
Pages : 372
Book Description
This book is a result of a workshop, the 8th of the successful TopoInVis workshop series, held in 2019 in Nyköping, Sweden. The workshop regularly gathers some of the world’s leading experts in this field. Thereby, it provides a forum for discussions on the latest advances in the field with a focus on finding practical solutions to open problems in topological data analysis for visualization. The contributions provide introductory and novel research articles including new concepts for the analysis of multivariate and time-dependent data, robust computational approaches for the extraction and approximations of topological structures with theoretical guarantees, and applications of topological scalar and vector field analysis for visualization. The applications span a wide range of scientific areas comprising climate science, material sciences, fluid dynamics, and astronomy. In addition, community efforts with respect to joint software development are reported and discussed.
Publisher: Springer Nature
ISBN: 3030835006
Category : Mathematics
Languages : en
Pages : 372
Book Description
This book is a result of a workshop, the 8th of the successful TopoInVis workshop series, held in 2019 in Nyköping, Sweden. The workshop regularly gathers some of the world’s leading experts in this field. Thereby, it provides a forum for discussions on the latest advances in the field with a focus on finding practical solutions to open problems in topological data analysis for visualization. The contributions provide introductory and novel research articles including new concepts for the analysis of multivariate and time-dependent data, robust computational approaches for the extraction and approximations of topological structures with theoretical guarantees, and applications of topological scalar and vector field analysis for visualization. The applications span a wide range of scientific areas comprising climate science, material sciences, fluid dynamics, and astronomy. In addition, community efforts with respect to joint software development are reported and discussed.
Computational Design of Battery Materials
Author: Dorian A. H. Hanaor
Publisher: Springer Nature
ISBN: 3031473035
Category :
Languages : en
Pages : 589
Book Description
Publisher: Springer Nature
ISBN: 3031473035
Category :
Languages : en
Pages : 589
Book Description
Introduction to Mathematical Modeling and Computer Simulations
Author: Vladimir Mityushev
Publisher: CRC Press
ISBN: 1040271316
Category : Mathematics
Languages : en
Pages : 349
Book Description
Introduction to Mathematical Modeling and Computer Simulations, Second Edition continues to serve as an engaging and accessible textbook for undergraduates studying mathematical modeling and computer simulations. The book is heavily focussed on applications, and so may have a particular appeal to applied mathematicians, engineers, and others working in applied quantitative disciplines. The book may also be useful as a reference text for reference text for early-career stage practitioners. New to this Edition: A new chapter on Machine Learning and Data Analysis in order to account for recent developments in the field. Chapter 9, ‘Asymptotic Methods in Composites’, has been entirely re-written to make it more consistent with industry and scientific standards. Includes an elementary introduction to programming in Python language. The Jupyter notebooks with examples for Chapter 10 and Appendix A are available for a download from www.Routledge.com/9781032661513.
Publisher: CRC Press
ISBN: 1040271316
Category : Mathematics
Languages : en
Pages : 349
Book Description
Introduction to Mathematical Modeling and Computer Simulations, Second Edition continues to serve as an engaging and accessible textbook for undergraduates studying mathematical modeling and computer simulations. The book is heavily focussed on applications, and so may have a particular appeal to applied mathematicians, engineers, and others working in applied quantitative disciplines. The book may also be useful as a reference text for reference text for early-career stage practitioners. New to this Edition: A new chapter on Machine Learning and Data Analysis in order to account for recent developments in the field. Chapter 9, ‘Asymptotic Methods in Composites’, has been entirely re-written to make it more consistent with industry and scientific standards. Includes an elementary introduction to programming in Python language. The Jupyter notebooks with examples for Chapter 10 and Appendix A are available for a download from www.Routledge.com/9781032661513.
The Routledge Handbook of Landscape Ecology
Author: Robert A. Francis
Publisher: Routledge
ISBN: 042967967X
Category : Nature
Languages : en
Pages : 453
Book Description
The Handbook provides a supporting guide to key aspects and applications of landscape ecology to underpin its research and teaching. A wide range of contributions written by expert researchers in the field summarize the latest knowledge on landscape ecology theory and concepts, landscape processes, methods and tools, and emerging frontiers. Landscape ecology is an interdisciplinary and holistic discipline, and this is reflected in the chapters contained in this Handbook. Authors from varying disciplinary backgrounds tackle key concepts such as landscape structure and function, scale and connectivity; landscape processes such as disturbance, flows, and fragmentation; methods such as remote sensing and mapping, fieldwork, pattern analysis, modelling, and participation and engagement in landscape planning; and emerging frontiers such as ecosystem services, landscape approaches to biodiversity conservation, and climate change. Each chapter provides a blend of the latest scientific understanding of its focal topics along with considerations and examples of their application from around the world. An invaluable guide to the concepts, methods, and applications of landscape ecology, this book will be an important reference text for a wide range of students and academics in ecology, geography, biology, and interdisciplinary environmental studies.
Publisher: Routledge
ISBN: 042967967X
Category : Nature
Languages : en
Pages : 453
Book Description
The Handbook provides a supporting guide to key aspects and applications of landscape ecology to underpin its research and teaching. A wide range of contributions written by expert researchers in the field summarize the latest knowledge on landscape ecology theory and concepts, landscape processes, methods and tools, and emerging frontiers. Landscape ecology is an interdisciplinary and holistic discipline, and this is reflected in the chapters contained in this Handbook. Authors from varying disciplinary backgrounds tackle key concepts such as landscape structure and function, scale and connectivity; landscape processes such as disturbance, flows, and fragmentation; methods such as remote sensing and mapping, fieldwork, pattern analysis, modelling, and participation and engagement in landscape planning; and emerging frontiers such as ecosystem services, landscape approaches to biodiversity conservation, and climate change. Each chapter provides a blend of the latest scientific understanding of its focal topics along with considerations and examples of their application from around the world. An invaluable guide to the concepts, methods, and applications of landscape ecology, this book will be an important reference text for a wide range of students and academics in ecology, geography, biology, and interdisciplinary environmental studies.
Data Science and Complex Networks
Author: Guido Caldarelli
Publisher: Oxford University Press
ISBN: 0199639604
Category : Business & Economics
Languages : en
Pages : 139
Book Description
This book guides the reader in the analysis of big-data by providing theoretical and practical instruments to tame the complexity of such systems. Together with support provided by the companion website, it constitutes a simple and useful handbook for data analysts.
Publisher: Oxford University Press
ISBN: 0199639604
Category : Business & Economics
Languages : en
Pages : 139
Book Description
This book guides the reader in the analysis of big-data by providing theoretical and practical instruments to tame the complexity of such systems. Together with support provided by the companion website, it constitutes a simple and useful handbook for data analysts.
Cyber-Physical Energy and Power Systems
Author: Yijia Cao
Publisher: Springer Nature
ISBN: 9811500622
Category : Technology & Engineering
Languages : en
Pages : 224
Book Description
This book discusses recent advances in cyber-physical power systems (CPPS) in the modeling, analysis and applications of smart grid. It introduces a series of models, such as an analysis of interaction between the power grid and the communication network, differential protection in smart distribution systems, data flow for VLAN-based communication in substations, a co-simulation model for investigating the impacts of cyber-contingency and distributed control systems as well as the analytical techniques used in different parts of cyber physical energy systems. It also discusses methods of cyber-attack on power systems, particularly false data injection. The results presented are a comprehensive summary of the authors’ original research conducted over a period of 5 years. The book is of interest to university researchers, R&D engineers and graduate students in power and energy systems.
Publisher: Springer Nature
ISBN: 9811500622
Category : Technology & Engineering
Languages : en
Pages : 224
Book Description
This book discusses recent advances in cyber-physical power systems (CPPS) in the modeling, analysis and applications of smart grid. It introduces a series of models, such as an analysis of interaction between the power grid and the communication network, differential protection in smart distribution systems, data flow for VLAN-based communication in substations, a co-simulation model for investigating the impacts of cyber-contingency and distributed control systems as well as the analytical techniques used in different parts of cyber physical energy systems. It also discusses methods of cyber-attack on power systems, particularly false data injection. The results presented are a comprehensive summary of the authors’ original research conducted over a period of 5 years. The book is of interest to university researchers, R&D engineers and graduate students in power and energy systems.
Introduction to Programming in Python
Author: Robert Sedgewick
Publisher: Addison-Wesley Professional
ISBN: 0134076524
Category : Computers
Languages : en
Pages : 1487
Book Description
Today, anyone in a scientific or technical discipline needs programming skills. Python is an ideal first programming language, and Introduction to Programming in Python is the best guide to learning it. Princeton University’s Robert Sedgewick, Kevin Wayne, and Robert Dondero have crafted an accessible, interdisciplinary introduction to programming in Python that emphasizes important and engaging applications, not toy problems. The authors supply the tools needed for students to learn that programming is a natural, satisfying, and creative experience. This example-driven guide focuses on Python’s most useful features and brings programming to life for every student in the sciences, engineering, and computer science. Coverage includes Basic elements of programming: variables, assignment statements, built-in data types, conditionals, loops, arrays, and I/O, including graphics and sound Functions, modules, and libraries: organizing programs into components that can be independently debugged, maintained, and reused Object-oriented programming and data abstraction: objects, modularity, encapsulation, and more Algorithms and data structures: sort/search algorithms, stacks, queues, and symbol tables Examples from applied math, physics, chemistry, biology, and computer science—all compatible with Python 2 and 3 Drawing on their extensive classroom experience, the authors provide Q&As, exercises, and opportunities for creative practice throughout. An extensive amount of supplementary information is available at introcs.cs.princeton.edu/python. With source code, I/O libraries, solutions to selected exercises, and much more, this companion website empowers people to use their own computers to teach and learn the material.
Publisher: Addison-Wesley Professional
ISBN: 0134076524
Category : Computers
Languages : en
Pages : 1487
Book Description
Today, anyone in a scientific or technical discipline needs programming skills. Python is an ideal first programming language, and Introduction to Programming in Python is the best guide to learning it. Princeton University’s Robert Sedgewick, Kevin Wayne, and Robert Dondero have crafted an accessible, interdisciplinary introduction to programming in Python that emphasizes important and engaging applications, not toy problems. The authors supply the tools needed for students to learn that programming is a natural, satisfying, and creative experience. This example-driven guide focuses on Python’s most useful features and brings programming to life for every student in the sciences, engineering, and computer science. Coverage includes Basic elements of programming: variables, assignment statements, built-in data types, conditionals, loops, arrays, and I/O, including graphics and sound Functions, modules, and libraries: organizing programs into components that can be independently debugged, maintained, and reused Object-oriented programming and data abstraction: objects, modularity, encapsulation, and more Algorithms and data structures: sort/search algorithms, stacks, queues, and symbol tables Examples from applied math, physics, chemistry, biology, and computer science—all compatible with Python 2 and 3 Drawing on their extensive classroom experience, the authors provide Q&As, exercises, and opportunities for creative practice throughout. An extensive amount of supplementary information is available at introcs.cs.princeton.edu/python. With source code, I/O libraries, solutions to selected exercises, and much more, this companion website empowers people to use their own computers to teach and learn the material.