Modeling Information Diffusion In Online Social Networks With Partial Differential Equations

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Modeling Information Diffusion in Online Social Networks with Partial Differential Equations

Author : Haiyan Wang
Publisher : Springer Nature
ISBN 13 : 3030388522
Total Pages : 153 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Modeling Information Diffusion in Online Social Networks with Partial Differential Equations by : Haiyan Wang

Download or read book Modeling Information Diffusion in Online Social Networks with Partial Differential Equations written by Haiyan Wang and published by Springer Nature. This book was released on 2020-03-16 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book lies at the interface of mathematics, social media analysis, and data science. Its authors aim to introduce a new dynamic modeling approach to the use of partial differential equations for describing information diffusion over online social networks. The eigenvalues and eigenvectors of the Laplacian matrix for the underlying social network are used to find communities (clusters) of online users. Once these clusters are embedded in a Euclidean space, the mathematical models, which are reaction-diffusion equations, are developed based on intuitive social distances between clusters within the Euclidean space. The models are validated with data from major social media such as Twitter. In addition, mathematical analysis of these models is applied, revealing insights into information flow on social media. Two applications with geocoded Twitter data are included in the book: one describing the social movement in Twitter during the Egyptian revolution in 2011 and another predicting influenza prevalence. The new approach advocates a paradigm shift for modeling information diffusion in online social networks and lays the theoretical groundwork for many spatio-temporal modeling problems in the big-data era.

Information Diffusion Management and Knowledge Sharing: Breakthroughs in Research and Practice

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799804186
Total Pages : 920 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Information Diffusion Management and Knowledge Sharing: Breakthroughs in Research and Practice by : Management Association, Information Resources

Download or read book Information Diffusion Management and Knowledge Sharing: Breakthroughs in Research and Practice written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-10-11 with total page 920 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within the past 10 years, tremendous innovations have been brought forth in information diffusion and management. Such technologies as social media have transformed the way that information is disseminated and used, making it critical to understand its distribution through these mediums. With the consistent creation and wide availability of information, it has become imperative to remain updated on the latest trends and applications in this field. Information Diffusion Management and Knowledge Sharing: Breakthroughs in Research and Practice examines the trends, models, challenges, issues, and strategies of information diffusion and management from a global context. Highlighting a range of topics such as influence maximization, information spread control, and social influence, this publication is an ideal reference source for managers, librarians, information systems specialists, professionals, researchers, and administrators seeking current research on the theories and applications of global information management.

Intelligent Information and Database Systems

Author : Ngoc Thanh Nguyen
Publisher : Springer
ISBN 13 : 3319754173
Total Pages : 749 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Intelligent Information and Database Systems by : Ngoc Thanh Nguyen

Download or read book Intelligent Information and Database Systems written by Ngoc Thanh Nguyen and published by Springer. This book was released on 2018-03-03 with total page 749 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 10751 and 10752 constitutes the refereed proceedings of the 10th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2018, held in Dong Hoi City, Vietnam, in March 2018. The total of 133 full papers accepted for publication in these proceedings was carefully reviewed and selected from 423 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Machine Learning and Data Mining; Decision Support and Control Systems; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Multiple Model Approach to Machine Learning; Sensor Networks and Internet of Things; Intelligent Information Systems; Data Structures Modeling for Knowledge Representation; Modeling, Storing, and Querying of Graph Data; Data Science and Computational Intelligence; Design Thinking Based R&D, Development Technique, and Project Based Learning; Intelligent and Contextual Systems; Intelligent Systems and Algorithms in Information Sciences; Intelligent Applications of Internet of Thing and Data Analysis Technologies; Intelligent Systems and Methods in Biomedicine; Intelligent Biomarkers of Neurodegenerative Processes in Brain; Analysis of Image, Video and Motion Data in Life Sciences; Computational Imaging and Vision; Computer Vision and Robotics; Intelligent Computer Vision Systems and Applications; Intelligent Systems for Optimization of Logistics and Industrial Applications.

Mathematical Methods in Data Science

Author : Jingli Ren
Publisher : Elsevier
ISBN 13 : 0443186804
Total Pages : 260 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Mathematical Methods in Data Science by : Jingli Ren

Download or read book Mathematical Methods in Data Science written by Jingli Ren and published by Elsevier. This book was released on 2023-01-06 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Methods in Data Science covers a broad range of mathematical tools used in data science, including calculus, linear algebra, optimization, network analysis, probability and differential equations. Based on the authors’ recently published and previously unpublished results, this book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for dataanalysis and prediction. With data science being used in virtually every aspect of our society, the book includes examples and problems arising in data science and the clear explanation of advanced mathematical concepts, especially data-driven differential equations, making it accessible to researchers and graduate students in mathematics and data science. Combines a broad spectrum of mathematics, including linear algebra, optimization, network analysis and ordinary and partial differential equations for data science Written by two researchers who are actively applying mathematical and statistical methods as well as ODE and PDE for data analysis and prediction Highly interdisciplinary, with content spanning mathematics, data science, social media analysis, network science, financial markets, and more Presents a wide spectrum of topics in a logical order, including probability, linear algebra, calculus and optimization, networks, ordinary differential and partial differential equations

Materials Phase Change PDE Control & Estimation

Author : Shumon Koga
Publisher : Springer Nature
ISBN 13 : 3030584909
Total Pages : 352 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Materials Phase Change PDE Control & Estimation by : Shumon Koga

Download or read book Materials Phase Change PDE Control & Estimation written by Shumon Koga and published by Springer Nature. This book was released on 2020-11-01 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph introduces breakthrough control algorithms for partial differential equation models with moving boundaries, the study of which is known as the Stefan problem. The algorithms can be used to improve the performance of various processes with phase changes, such as additive manufacturing. Using the authors' innovative design solutions, readers will also be equipped to apply estimation algorithms for real-world phase change dynamics, from polar ice to lithium-ion batteries. A historical treatment of the Stefan problem opens the book, situating readers in the larger context of the area. Following this, the chapters are organized into two parts. The first presents the design method and analysis of the boundary control and estimation algorithms. Part two then explores a number of applications, such as 3D printing via screw extrusion and laser sintering, and also discusses the experimental verifications conducted. A number of open problems and provided as well, offering readers multiple paths to explore in future research. Materials Phase Change PDE Control & Estimation is ideal for researchers and graduate students working on control and dynamical systems, and particularly those studying partial differential equations and moving boundaries. It will also appeal to industrial engineers and graduate students in engineering who are interested in this area.

Information Spread in a Social Media Age

Author : Michael Muhlmeyer
Publisher : CRC Press
ISBN 13 : 0429558872
Total Pages : 252 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Information Spread in a Social Media Age by : Michael Muhlmeyer

Download or read book Information Spread in a Social Media Age written by Michael Muhlmeyer and published by CRC Press. This book was released on 2021-03-29 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rise of social networks and social media has led to a massive shift in the ways information is dispersed. Platforms like Twitter and Facebook allow people to more easily connect as a community, but they can also be avenues for misinformation, fake news, and polarization. The need to examine, model, and analyze the trajectory of information spread within this new paradigm has never been greater. This text expands upon the authors’ combined teaching experience, engineering knowledge, and multiple academic journal publications on these topics to present an intuitive and easy to understand exploration of social media information spread alongside the technical and mathematical concepts. By design, this book uses simple language and accessible and modern case studies (including those centered around United States mass shootings, the #MeToo social movement, and more) to ensure it is accessible to the casual reader. At the same time, readers with prior knowledge of the topics will benefit from the mathematical model and control elements and accompanying sample simulation code for each main topic. By reading this book and working through the included exercises, readers will gain a general understanding of modern social media systems, network fundamentals, model development techniques, and social marketing. The mathematical modeling of information spread over social media is heavily emphasized through a review of existing epidemiology and marketing based models. The book then presents novel models developed by the authors to account for modern social media concerns such as community filter bubbles, strongly polarized groups, and contentious information spread. Readers will learn how to build and execute simple case studies using Twitter data to help verify the text’s proposed models. Once the reader is armed with a fundamental understanding of mathematical modeling and social media-based system considerations, the book introduces more complex engineering control concepts, including controller design, PID control, and optimal control. Examples of control methods for social campaigns and misinformation mitigation applications are covered in a step-by-step format from problem formulation to solution simulation and results discussions. While many of the examples and methods are framed in the context of controlling social media information spread, the material is also directly applicable to many different types of controllable systems. With the essential background, models, and tools presented within, any interested reader can take the first steps toward exploring and taming the growing complexity of the modern social media age.

Information and Influence Propagation in Social Networks

Author : Wei Chen
Publisher : Springer Nature
ISBN 13 : 3031018508
Total Pages : 161 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Information and Influence Propagation in Social Networks by : Wei Chen

Download or read book Information and Influence Propagation in Social Networks written by Wei Chen and published by Springer Nature. This book was released on 2022-05-31 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models against any available real datasets consisting of a social network and propagation traces that occurred in the past? These are just some questions studied by researchers in this area. Information propagation models find applications in viral marketing, outbreak detection, finding key blog posts to read in order to catch important stories, finding leaders or trendsetters, information feed ranking, etc. A number of algorithmic problems arising in these applications have been abstracted and studied extensively by researchers under the garb of influence maximization. This book starts with a detailed description of well-established diffusion models, including the independent cascade model and the linear threshold model, that have been successful at explaining propagation phenomena. We describe their properties as well as numerous extensions to them, introducing aspects such as competition, budget, and time-criticality, among many others. We delve deep into the key problem of influence maximization, which selects key individuals to activate in order to influence a large fraction of a network. Influence maximization in classic diffusion models including both the independent cascade and the linear threshold models is computationally intractable, more precisely #P-hard, and we describe several approximation algorithms and scalable heuristics that have been proposed in the literature. Finally, we also deal with key issues that need to be tackled in order to turn this research into practice, such as learning the strength with which individuals in a network influence each other, as well as the practical aspects of this research including the availability of datasets and software tools for facilitating research. We conclude with a discussion of various research problems that remain open, both from a technical perspective and from the viewpoint of transferring the results of research into industry strength applications.

Mathematical Optimization Theory and Operations Research: Recent Trends

Author : Alexander Strekalovsky
Publisher : Springer Nature
ISBN 13 : 3030864332
Total Pages : 515 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Mathematical Optimization Theory and Operations Research: Recent Trends by : Alexander Strekalovsky

Download or read book Mathematical Optimization Theory and Operations Research: Recent Trends written by Alexander Strekalovsky and published by Springer Nature. This book was released on 2021-09-20 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the 20th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2021, held in Irkutsk, Russia, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 31 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 102 submissions. The papers in the volume are organised according to the following topical headings: continuous optimization; integer programming and combinatorial optimization; operational research applications; optimal control.

Online Social Networks

Author : Valerio Arnaboldi
Publisher : Elsevier
ISBN 13 : 0128030429
Total Pages : 116 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Online Social Networks by : Valerio Arnaboldi

Download or read book Online Social Networks written by Valerio Arnaboldi and published by Elsevier. This book was released on 2015-09-25 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online Social Networks: Human Cognitive Constraints in Facebook and Twitter provides new insights into the structural properties of personal online social networks and the mechanisms underpinning human online social behavior. As the availability of digital communication data generated by social media is revolutionizing the field of social networks analysis, the text discusses the use of large- scale datasets to study the structural properties of online ego networks, to compare them with the properties of general human social networks, and to highlight additional properties. Users will find the data collected and conclusions drawn useful during design or research service initiatives that involve online and mobile social network environments. Provides an analysis of the structural properties of ego networks in online social networks Presents quantitative evidence of the Dunbar’s number in online environments Discusses original structural and dynamic properties of human social network through OSN analysis

Computational Data and Social Networks

Author : Sriram Chellappan
Publisher : Springer Nature
ISBN 13 : 303066046X
Total Pages : 551 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Computational Data and Social Networks by : Sriram Chellappan

Download or read book Computational Data and Social Networks written by Sriram Chellappan and published by Springer Nature. This book was released on 2021-01-03 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Computational Data and Social Networks, CSoNet 2020, held in Dallas, TX, USA, in December 2020. The 20 full papers were carefully reviewed and selected from 83 submissions. Additionally the book includes 22 special track papers and 3 extended abstracts. The selected papers are devoted to topics such as Combinatorial Optimization and Learning; Computational Methods for Social Good Applications; NLP and Affective Computing; Privacy and Security; Blockchain; Fact-Checking, Fake News and Malware Detection in Online Social Networks; and Information Spread in Social and Data Networks.

Diffusion in Social Networks

Author : Paulo Shakarian
Publisher : Springer
ISBN 13 : 3319231057
Total Pages : 101 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Diffusion in Social Networks by : Paulo Shakarian

Download or read book Diffusion in Social Networks written by Paulo Shakarian and published by Springer. This book was released on 2015-09-16 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the leading models of social network diffusion that are used to demonstrate the spread of disease, ideas, and behavior. It introduces diffusion models from the fields of computer science (independent cascade and linear threshold), sociology (tipping models), physics (voter models), biology (evolutionary models), and epidemiology (SIR/SIS and related models). A variety of properties and problems related to these models are discussed including identifying seeds sets to initiate diffusion, game theoretic problems, predicting diffusion events, and more. The book explores numerous connections between social network diffusion research and artificial intelligence through topics such as agent-based modeling, logic programming, game theory, learning, and data mining. The book also surveys key empirical results in social network diffusion, and reviews the classic and cutting-edge research with a focus on open problems.

Intelligent Information and Database Systems

Author : Ngoc Thanh Nguyen
Publisher : Springer
ISBN 13 : 9783319754161
Total Pages : 0 pages
Book Rating : 4.7/5 (541 download)

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Book Synopsis Intelligent Information and Database Systems by : Ngoc Thanh Nguyen

Download or read book Intelligent Information and Database Systems written by Ngoc Thanh Nguyen and published by Springer. This book was released on 2018-02-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 10751 and 10752 constitutes the refereed proceedings of the 10th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2018, held in Dong Hoi City, Vietnam, in March 2018. The total of 133 full papers accepted for publication in these proceedings was carefully reviewed and selected from 423 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Machine Learning and Data Mining; Decision Support and Control Systems; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Multiple Model Approach to Machine Learning; Sensor Networks and Internet of Things; Intelligent Information Systems; Data Structures Modeling for Knowledge Representation; Modeling, Storing, and Querying of Graph Data; Data Science and Computational Intelligence; Design Thinking Based R&D, Development Technique,and Project Based Learning; Intelligent and Contextual Systems; Intelligent Systems and Algorithms in Information Sciences; Intelligent Applications of Internet of Thing and Data Analysis Technologies; Intelligent Systems and Methods in Biomedicine; Intelligent Biomarkers of Neurodegenerative Processes in Brain; Analysis of Image, Video and Motion Data in Life Sciences; Computational Imaging and Vision; Computer Vision and Robotics; Intelligent Computer Vision Systems and Applications; Intelligent Systems for Optimization of Logistics and Industrial Applications.

Mathematical Methods in Data Science

Author : Jingli Ren
Publisher : Elsevier
ISBN 13 : 0443186790
Total Pages : 258 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Mathematical Methods in Data Science by : Jingli Ren

Download or read book Mathematical Methods in Data Science written by Jingli Ren and published by Elsevier. This book was released on 2023-01-16 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Methods in Data Science introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data analysis and prediction. The mathematics is accompanied with examples and problems arising in data science to demonstrate advanced mathematics, in particular, data-driven differential equations used. Chapters also cover network analysis, ordinary and partial differential equations based on recent published and unpublished results. Finally, the book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data analysis and prediction. There are a number of books on mathematical methods in data science. Currently, all these related books primarily focus on linear algebra, optimization and statistical methods. However, network analysis, ordinary and partial differential equation models play an increasingly important role in data science. With the availability of unprecedented amount of clinical, epidemiological and social COVID-19 data, data-driven differential equation models have become more useful for infection prediction and analysis. Combines a broad spectrum of mathematics, including linear algebra, optimization, network analysis and ordinary and partial differential equations for data science Written by two researchers who are actively applying mathematical and statistical methods as well as ODE and PDE for data analysis and prediction Highly interdisciplinary, with content spanning mathematics, data science, social media analysis, network science, financial markets, and more Presents a wide spectrum of topics in a logical order, including probability, linear algebra, calculus and optimization, networks, ordinary differential and partial differential equations

Social Networks: Models of Information Influence, Control and Confrontation

Author : Alexander G. Chkhartishvili
Publisher : Springer
ISBN 13 : 3030054292
Total Pages : 158 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Social Networks: Models of Information Influence, Control and Confrontation by : Alexander G. Chkhartishvili

Download or read book Social Networks: Models of Information Influence, Control and Confrontation written by Alexander G. Chkhartishvili and published by Springer. This book was released on 2018-12-30 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys the well-known results and also presents a series of original results on the mathematical modeling of social networks, focusing on models of informational influence, control and confrontation. Online social networks are intended for communication, opinion exchange and information acquisition for their members, but recently, online social networks have been intensively used as the objects and means of informational control and an arena of informational confrontation. They have become a powerful informational influence tool, particularly for the manipulation of individuals, social groups and society as a whole, as well as a battlefield of information warfare (cyberwars). This book aimed at under- and postgraduate university students as well as experts in information technology and modeling of social systems and processes.

A Compendium of Partial Differential Equation Models

Author : William E. Schiesser
Publisher : Cambridge University Press
ISBN 13 : 0521519861
Total Pages : 491 pages
Book Rating : 4.5/5 (215 download)

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Book Synopsis A Compendium of Partial Differential Equation Models by : William E. Schiesser

Download or read book A Compendium of Partial Differential Equation Models written by William E. Schiesser and published by Cambridge University Press. This book was released on 2009-03-16 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents numerical methods and computer code in Matlab for the solution of ODEs and PDEs with detailed line-by-line discussion.

Partial Differential Equations in Action

Author : Sandro Salsa
Publisher : Springer
ISBN 13 : 3319150936
Total Pages : 701 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Partial Differential Equations in Action by : Sandro Salsa

Download or read book Partial Differential Equations in Action written by Sandro Salsa and published by Springer. This book was released on 2015-04-24 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is intended as an advanced undergraduate or first-year graduate course for students from various disciplines, including applied mathematics, physics and engineering. It has evolved from courses offered on partial differential equations (PDEs) over the last several years at the Politecnico di Milano. These courses had a twofold purpose: on the one hand, to teach students to appreciate the interplay between theory and modeling in problems arising in the applied sciences, and on the other to provide them with a solid theoretical background in numerical methods, such as finite elements. Accordingly, this textbook is divided into two parts. The first part, chapters 2 to 5, is more elementary in nature and focuses on developing and studying basic problems from the macro-areas of diffusion, propagation and transport, waves and vibrations. In turn the second part, chapters 6 to 11, concentrates on the development of Hilbert spaces methods for the variational formulation and the analysis of (mainly) linear boundary and initial-boundary value problems.

Non-Local Partial Differential Equations for Engineering and Biology

Author : Nikos I. Kavallaris
Publisher : Springer
ISBN 13 : 3319679449
Total Pages : 300 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Non-Local Partial Differential Equations for Engineering and Biology by : Nikos I. Kavallaris

Download or read book Non-Local Partial Differential Equations for Engineering and Biology written by Nikos I. Kavallaris and published by Springer. This book was released on 2017-11-28 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new developments in non-local mathematical modeling and mathematical analysis on the behavior of solutions with novel technical tools. Theoretical backgrounds in mechanics, thermo-dynamics, game theory, and theoretical biology are examined in details. It starts off with a review and summary of the basic ideas of mathematical modeling frequently used in the sciences and engineering. The authors then employ a number of models in bio-science and material science to demonstrate applications, and provide recent advanced studies, both on deterministic non-local partial differential equations and on some of their stochastic counterparts used in engineering. Mathematical models applied in engineering, chemistry, and biology are subject to conservation laws. For instance, decrease or increase in thermodynamic quantities and non-local partial differential equations, associated with the conserved physical quantities as parameters. These present novel mathematical objects are engaged with rich mathematical structures, in accordance with the interactions between species or individuals, self-organization, pattern formation, hysteresis. These models are based on various laws of physics, such as mechanics of continuum, electro-magnetic theory, and thermodynamics. This is why many areas of mathematics, calculus of variation, dynamical systems, integrable systems, blow-up analysis, and energy methods are indispensable in understanding and analyzing these phenomena. This book aims for researchers and upper grade students in mathematics, engineering, physics, economics, and biology.