This book collects high-quality research papers presented at the International Conference on Computing Applications in Electrical & Electronics Engineering, held at Rajkiya Engineering College, Sonbhadra, India, on August 30-31, 2019. It provides novel contributions in computational intelligence, together with valuable reference material for future research. The topics covered include: big data analytics, IoT and smart infrastructures, machine learning, artificial intelligence and deep learning, crowd sourcing and social intelligence, natural language processing, business intelligence, high-performance computing, wireless, mobile and green communications, ad-hoc, sensor and mesh networks, SDN and network virtualization, cognitive systems, swarm intelligence, human-computer interaction, network and information security, intelligent control, soft computing, networked control systems, renewable energy sources and technologies, biomedical signal processing, pattern recognition and object tracking, and sensor devices and applications.

This book constitutes the thoroughly refereed proceedings of the 11th International Symposium on Intelligence Computation and Applications, ISICA 2019, held in Guangzhou, China, in November 2019. The 65 papers presented were carefully reviewed and selected from the total of 112 submissions. This volume features the most up-to-date research in evolutionary algorithms, parallel computing and quantum computing, evolutionary multi-objective and dynamic optimization, intelligent multimedia systems, virtualization and AI applications, smart scheduling, intelligent control, big data and cloud computing, deep learning, and hybrid machine learning systems.The papers are organized according to the following topical sections: new frontier in evolutionary algorithms; evolutionary multi-objective and dynamic optimization; intelligent multimedia systems; virtualization and AI applications; smart scheduling; intelligent control; big data and cloud computing; statistical learning.

The book discusses advantages of the firefly algorithm over other well-known metaheuristic algorithms in various engineering studies. The book provides a brief outline of various application-oriented problem solving methods, like economic emission load dispatch problem, designing a fully digital controlled reconfigurable switched beam nonconcentric ring array antenna, image segmentation, span minimization in permutation flow shop scheduling, multi-objective load dispatch problems, image compression, etc., using FA and its variants. It also covers the use of the firefly algorithm to select features, as research has shown that the firefly algorithm generates precise and optimal results in terms of time and optimality. In addition, the book also explores the potential of the firefly algorithm to provide a solution to traveling salesman problem, graph coloring problem, etc

Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab's default install of the most current TensorFlow 2.x along with Colab's easy access to on-demand GPU hardware acceleration in the cloud for fast execution of deep learning models. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. Everything else-Python, TensorFlow 2.x, GPU support, and Jupyter Notebooks-is provided and ready to go from Colab. The book begins with an introduction to TensorFlow 2.x and the Google Colab cloud service. You will learn how to provision a workspace on Google Colab and build a simple neural network application. From there you will progress into TensorFlow datasets and building input pipelines in support of modeling and testing. You will find coverage of deep learning classification and regression, with clear code examples showing how to perform each of those functions. Advanced topics covered in the book include convolutional neural networks and recurrent neural networks. This book contains all the applied math and programming you need to master the content. Examples range from simple to relatively complex when necessary to ensure acquisition of appropriate deep learning concepts and constructs. Examples are carefully explained, concise, accurate, and complete to perfectly complement deep learning skill development. Care is taken to walk you through the foundational principles of deep learning through clear examples written in Python that you can try out and experiment with using Google Colab from the comfort of your own home or office. What You Will Learn Be familiar with the basic concepts and constructs of applied deep learning Create machine learning models with clean and reliable Python code Work with datasets common to deep learning applications Prepare data for TensorFlow consumption Take advantage of Google Colab's built-in support for deep learning Execute deep learning experiments using a variety of neural network models Be able to mount Google Colab directly to your Google Drive account Visualize training versus test performance to see model fit Who This Book Is For Readers who want to learn the highly popular TensorFlow 2.x deep learning platform, those who wish to master deep learning fundamentals that are sometimes skipped over in the rush to be productive, and those looking to build competency with a modern cloud service tool such as Google Colab

This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.

Implement practical data structures and algorithms for text search and discover how it is used inside other larger applications. This unique in-depth guide explains string algorithms using the C programming language. String Algorithms in C teaches you the following algorithms and how to use them: classical exact search algorithms; tries and compact tries; suffix trees and arrays; approximative pattern searches; and more. In this book, author Thomas Mailund provides a library with all the algorithms and applicable source code that you can use in your own programs. There are implementations of all the algorithms presented in this book so there are plenty of examples. You'll understand that string algorithms are used in various applications such as image processing, computer vision, text analytics processing from data science to web applications, information retrieval from databases, network security, and much more. What You Will Learn Use classical exact search algorithms including naive search, borders/border search, Knuth-Morris-Pratt, and Boyer-Moor with or without Horspool Search in trees, use tries and compact tries, and work with the Aho-Carasick algorithm Process suffix trees including the use and development of McCreight's algorithm Work with suffix arrays including binary searches; sorting naive constructions; suffix tree construction; skew algorithms; and the Borrows-Wheeler transform (BWT) Deal with enhanced suffix arrays including longest common prefix (LCP) Carry out approximative pattern searches among suffix trees and approximative BWT searches Who This Book Is For Those with at least some prior programming experience with C or Assembly and have at least prior experience with programming algorithms.

This two-volume set (CCIS 1159 and CCIS 1160) constitutes the proceedings of the 14th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2019, held in Zhengzhou, China, in November 2019. The 121 full papers presented in both volumes were selected from 197 submissions. The papers are organized according to the topical headings: evolutionary computation and swarm intelligence; bioinformatics and systems biology; complex networks; DNA and molecular computing; neural networks and articial intelligence.

Data structures is a key course for computer science and related majors. This book presents a variety of practical or engineering cases and derives abstract concepts from concrete problems. Besides basic concepts and analysis methods, it introduces basic data types such as sequential list, tree as well as graph. This book can be used as an undergraduate textbook, as a training textbook or a self-study textbook for engineers.

This book constitutes the refereed proceedings of the First International Conference on Security and Privacy in Digital Economy, SPDE 2020, held in Quzhou, China, in October 2020*. The 49 revised full papers and 2 short papers were carefully reviewed and selected from 132 submissions. The papers are organized in topical sections: cyberspace security, privacy protection, anomaly and intrusion detection, trust computation and forensics, attacks and countermeasures, covert communication, security protocol, anonymous communication, security and privacy from social science. *The conference was held virtually due to the COVID-19 pandemic.

Realism and Complexity in Social Science is an argument for a new approach to investigating the social world, that of complex realism. Complex realism brings together a number of strands of thought, in scientific realism, complexity science, probability theory and social research methodology. It proposes that the reality of the social world is that it is probabilistic, yet there exists enough invariance to make the discovery and explanation of social objects and causal mechanisms possible. This forms the basis for the development of a complex realist foundation for social research, that utilises a number of new and novel approaches to investigation, alongside the more traditional corpus of quantitative and qualitative methods. Research examples are drawn from research in sociology, epidemiology, criminology, social policy and human geography. The book assumes no prior knowledge of realism, probability or complexity and in the early chapters, the reader is introduced to these concepts and the arguments against them. Although the book is grounded in philosophical reasoning, this is in a direct and accessible style that will appeal both to social researchers with a methodological interest and philosophers with an interest in social investigation.

This book describes the uses of different mathematical modeling and soft computing techniques used in epidemiology for experiential research in projects such as how infectious diseases progress to show the likely outcome of an epidemic, and to contribute to public health interventions. This book covers mathematical modeling and soft computing techniques used to study the spread of diseases, predict the future course of an outbreak, and evaluate epidemic control strategies. This book explores the applications covering numerical and analytical solutions, presents basic and advanced concepts for beginners and industry professionals, and incorporates the latest methodologies and challenges using mathematical modeling and soft computing techniques in epidemiology. Primary users of this book include researchers, academicians, postgraduate students, and specialists.

This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language. What You Will Learn Optimize core operations based on N-dimensional arrays Design and implement an industry-level algorithmic differentiation module Implement mathematical optimization, regression, and deep neural network functionalities based on algorithmic differentiation Design and optimize a computation graph module, and understand the benefits it brings to the numerical computing library Accommodate the growing number of hardware accelerators (e.g. GPU, TPU) and execution backends (e.g. web browser, unikernel) of numerical computation Use the Zoo system for efficient scripting, code sharing, service deployment, and composition Design and implement a distributed computing engine to work with a numerical computing library, providing convenient APIs and high performance Who This Book Is For Those with prior programming experience, especially with the OCaml programming language, or with scientific computing experience who may be new to OCaml. Most importantly, it is for those who are eager to understand not only how to use something, but also how it is built up.

ALGORITHMS IN BIOINFORMATICS Explore a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields Algorithms in Bioinformatics: Theory and Implementation delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. The text incorporates graphical illustrations to highlight and emphasize the technical details of computational algorithms found within, to further the reader's understanding and retention of the material. Throughout, the book is written in an accessible and practical manner, showing how algorithms can be implemented and used in JavaScript on Internet Browsers. The author has included more than 120 open-source implementations of the material, as well as 33 ready-to-use presentations. The book contains original material that has been class-tested by the author and numerous cases are examined in a biological and medical context. Readers will also benefit from the inclusion of: A thorough introduction to biological evolution, including the emergence of life, classifications and some known theories and molecular mechanisms A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields An examination of information and entropy, including sequence logos and explanations related to their meaning An exploration of the current state of bioinformatics, including what is known and what issues are usually avoided in the field A chapter on philosophical transactions that allows the reader a broader view of the prediction process Native computer implementations in the context of the field of Bioinformatics Extensive worked examples with detailed case studies that point out the meaning of different results Perfect for professionals and researchers in biology, medicine, engineering, and information technology, as well as upper level undergraduate students in these fields, Algorithms in Bioinformatics: Theory and Implementation will also earn a place in the libraries of software engineers who wish to understand how to implement bioinformatic algorithms in their products.

When it comes to artificial intelligence, we either hear of a paradise on earth or of our imminent extinction. It's time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we'll be discussing these issues long after the last page is turned.

The book highlights three types of technologies being developed for autonomous solution of navigation problems. These technologies are based on the polarization structure, ultra-broadband and the fluctuation characteristics (slow and fast) of the radiolocation signals. The book presents the problems of intrinsic thermal radio emission polarization and change in radio waves polarization when they are reflected from objects with non-linear properties. The purpose of this book is to develop the foundations for creating autonomous radionavigation systems to provide aviation with navigation systems that will substantially increase its capabilities, specifically acting where satellite technologies do not work. The book is intended for specialists involved in the development and operation of aviation-technical complexes, as well as for specialists of national aviation regulators and ICAO experts dealing with the problems of improving flight safety.

The Design and Analysis of Computer Algorithms introduces the basic data structures and programming techniques often used in efficient algorithms. It covers the use of lists, push-down stacks, queues, trees, and graphs.

Handbook of IoT and Blockchain: Methods, solutions, and Recent Advancements includes contributions from around the globe on recent advances and findings in the domain of Internet of Things (IoT) and Blockchain. Chapters include theoretical analysis, practical implications, and extensive surveys with analysis on methods, algorithms, and processes for new product development. IoT and Blockchain are the emerging topics in the current manufacturing scenario.This handbook includes recent advances; showcases the work of research around the globe; offers theoretical analysis and practical implications; presents extensive surveys with analysis, new contributions, and proposals on methods, algorithms, and processes; and also covers recent advances from quantitative and qualitative articles, case studies, conceptual works, and theoretical backing. This handbook will be of interest to graduate students, researchers, academicians, institutions, and professionals that are interested in exploring the areas of IoT and Blockchain.

Provides complete update and organization of the previous books, with some material moving online; Includes new problems, projects, and exercises; Includes interactive coding resources to accompany the book, including examples in the text, exercises, projects, and refection questions.

The two volumes LNAI 11649 and 11650 constitute the refereed proceedings of the 20th Annual Conference "Towards Autonomous Robotics", TAROS 2019, held in London, UK, in July 2019. The 87 full papers and 12 short papers presented were carefully reviewed and selected from 101 submissions. The papers present and discuss significant findings and advances in autonomous robotics research and applications. They are organized in the following topical sections: robotic grippers and manipulation; soft robotics, sensing and mobile robots; robotic learning, mapping and planning; human-robot interaction; and robotic systems and applications.

Networks powered by algorithms are pervasive. Major contemporary technology trends - Internet of Things, Big Data, Digital Platform Power, Blockchain, and the Algorithmic Society - are manifestations of this phenomenon. The internet, which once seemed an unambiguous benefit to society, is now the basis for invasions of privacy, massive concentrations of power, and wide-scale manipulation. The algorithmic networked world poses deep questions about power, freedom, fairness, and human agency. The influential 1997 Federal Communications Commission whitepaper "Digital Tornado" hailed the "endless spiral of connectivity" that would transform society, and today, little remains untouched by digital connectivity. Yet fundamental questions remain unresolved, and even more serious challenges have emerged. This important collection, which offers a reckoning and a foretelling, features leading technology scholars who explain the legal, business, ethical, technical, and public policy challenges of building pervasive networks and algorithms for the benefit of humanity. This title is also available as Open Access on Cambridge Core.

This book constitutes the refereed post-conference proceedings of the 30th International Workshop on Combinatorial Algorithms, IWOCA 2019, held in Pisa, Italy, in July 2019. The 36 regular papers presented in this volume were carefully reviewed and selected from 73 submissions. They cover diverse areas of combinatorical algorithms, complexity theory, graph theory and combinatorics, combinatorial optimization, cryptography and information security, algorithms on strings and graphs, graph drawing and labelling, computational algebra and geometry, computational biology, probabilistic and randomized algorithms, algorithms for big data analytics, and new paradigms of computation.

This book constitutes the proceedings of the 22nd International Symposium on Fundamentals of Computation Theory, FCT 2019, held in Copenhagen, Denmark, in August 2019.The 21 full papers included in this volume were carefully reviewed and selected from 45 submissions. In addition, the book contains 3 invited talks in full-paper length. The papers were organized in topical sections named: formal methods, complexity, and algorithms.

A remarkable look at how the growth, technology, and politics of high-frequency trading have altered global financial markets In today's financial markets, trading floors on which brokers buy and sell shares face-to-face have increasingly been replaced by lightning-fast electronic systems that use algorithms to execute astounding volumes of transactions. Trading at the Speed of Light tells the story of this epic transformation. Donald MacKenzie shows how in the 1990s, in what were then the disreputable margins of the US financial system, a new approach to trading-automated high-frequency trading or HFT-began and then spread throughout the world. HFT has brought new efficiency to global trading, but has also created an unrelenting race for speed, leading to a systematic, subterranean battle among HFT algorithms. In HFT, time is measured in nanoseconds (billionths of a second), and in a nanosecond the fastest possible signal-light in a vacuum-can travel only thirty centimeters, or roughly a foot. That makes HFT exquisitely sensitive to the length and transmission capacity of the cables connecting computer servers to the exchanges' systems and to the location of the microwave towers that carry signals between computer datacenters. Drawing from more than 300 interviews with high-frequency traders, the people who supply them with technological and communication capabilities, exchange staff, regulators, and many others, MacKenzie reveals the extraordinary efforts expended to speed up every aspect of trading. He looks at how in some markets big banks have fought off the challenge from HFT firms, and how exchanges sometimes engineer technical systems to favor certain types of algorithms over others. Focusing on the material, political, and economic characteristics of high-frequency trading, Trading at the Speed of Light offers a unique glimpse into its influence on global finance and where it could lead us in the future.

This book constitutes the proceedings of the 17th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2019, held in Avila, Spain, in June 2019. The 19 regular and 14 demo papers presented in this volume were carefully reviewed and selected from 55 submissions. They deal with the application and validation of agent-based models, methods, and technologies in a number of key applications areas, including: Agronomy and Internet of Things, coordination and structure, finance and energy, function and autonomy, humans and societies, reasoning and optimization, traffic and routing.