Nonparametric Kernel Density Estimation and Its Computational Aspects
Nonparametric Kernel Density Estimation and Its Computational Aspects

Author: Artur Gramacki

Publisher: Springer

Published: 2017-12-21

Total Pages: 197

ISBN-13: 3319716883

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This book describes computational problems related to kernel density estimation (KDE) – one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-based algorithms for both KDE computations and bandwidth selection are presented. The theory of KDE appears to have matured and is now well developed and understood. However, there is not much progress observed in terms of performance improvements. This book is an attempt to remedy this. The book primarily addresses researchers and advanced graduate or postgraduate students who are interested in KDE and its computational aspects. The book contains both some background and much more sophisticated material, hence also more experienced researchers in the KDE area may find it interesting. The presented material is richly illustrated with many numerical examples using both artificial and real datasets. Also, a number of practical applications related to KDE are presented.

Advances in Artificial Intelligence – IBERAMIA 2022
Advances in Artificial Intelligence – IBERAMIA 2022

Author: Ana Cristina Bicharra Garcia

Publisher: Springer Nature

Published: 2023-01-03

Total Pages: 422

ISBN-13: 3031224191

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This book constitutes the refereed proceedings of the 17th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2022, held in Cartagena de Indias, Colombia, in November 2022. The 33 full and 4 short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in the following topical sections: applications of AI; ethics and smart city; green and sustainable AI; machine learning; natural language processing; robotics and computer vision; simulation and forecasting.

Image Processing and Machine Learning, Volume 2
Image Processing and Machine Learning, Volume 2

Author: Erik Cuevas

Publisher: CRC Press

Published: 2024-02-16

Total Pages: 239

ISBN-13: 1003829147

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Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important machine learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1. Written with instructors and students of image processing in mind, this book’s intuitive organization also contains appeal for app developers and engineers.

Automatic Control, Robotics, and Information Processing
Automatic Control, Robotics, and Information Processing

Author: Piotr Kulczycki

Publisher: Springer Nature

Published: 2020-09-03

Total Pages: 843

ISBN-13: 3030485870

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This book presents a wide and comprehensive range of issues and problems in various fields of science and engineering, from both theoretical and applied perspectives. The desire to develop more effective and efficient tools and techniques for dealing with complex processes and systems has been a natural inspiration for the emergence of numerous fields of science and technology, in particular control and automation and, more recently, robotics. The contributions gathered here concern the development of methods and algorithms to determine best practices regarding broadly perceived decisions or controls. From an engineering standpoint, many of them focus on how to automate a specific process or complex system. From a tools-based perspective, several contributions address the development of analytic and algorithmic methods and techniques, devices and systems that make it possible to develop and subsequently implement the automation and robotization of crucial areas of human activity. All topics discussed are illustrated with sample applications.

Computational Intelligence Methods for Bioinformatics and Biostatistics
Computational Intelligence Methods for Bioinformatics and Biostatistics

Author: Davide Chicco

Publisher: Springer Nature

Published: 2022-11-25

Total Pages: 269

ISBN-13: 3031208374

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This book constitutes revised selected papers from the 17th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2021, which was held virtually during November 15–17, 2021. The 19 papers included in these proceedings were carefully reviewed and selected from 26 submissions, and they focus on bioinformatics, computational biology, health informatics, cheminformatics, biotechnology, biostatistics, and biomedical imaging.

New Metaheuristic Schemes: Mechanisms and Applications
New Metaheuristic Schemes: Mechanisms and Applications

Author: Erik Cuevas

Publisher: Springer Nature

Published: 2023-12-08

Total Pages: 280

ISBN-13: 3031455614

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Recently, novel metaheuristic techniques have emerged in response to the limitations of conventional approaches, leading to enhanced outcomes. These new methods introduce interesting mechanisms and innovative collaborative strategies that facilitate the efficient exploration and exploitation of extensive search spaces characterized by numerous dimensions. The objective of this book is to present advancements that discuss novel alternative metaheuristic developments that have demonstrated their effectiveness in tackling various complex problems. This book encompasses a variety of emerging metaheuristic methods and their practical applications. The content is presented from a teaching perspective, making it particularly suitable for undergraduate and postgraduate students in fields such as science, electrical engineering, and computational mathematics. The book aligns well with courses in artificial intelligence, electrical engineering, and evolutionary computation. Furthermore, the material offers valuable insights to researchers within the metaheuristic and engineering communities. Similarly, engineering practitioners unfamiliar with metaheuristic computation concepts will recognize the pragmatic value of the discussed techniques. These methods transcend mere theoretical tools that have been adapted to effectively address the significant real-world problems commonly encountered in engineering domains.

Handbook of Research on Nurturing Industrial Economy for Africa’s Development
Handbook of Research on Nurturing Industrial Economy for Africa’s Development

Author: Nafukho, Frederick Muyia

Publisher: IGI Global

Published: 2021-03-19

Total Pages: 510

ISBN-13: 1799864723

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A robust manufacturing sector is a necessity and a sufficient condition for any country’s human and economic development as it creates employment and alleviates poverty. During this Fourth Industrial Revolution era, there is an urgent need in Africa to optimally utilize the existing resources to support manufacturing or else risk allowing the continent to fall behind in the industrial economy. Innovative strategies are needed that can unlock Africa’s manufacturing potential by exploring key areas that may help Africa mature and launch modernized economies that will benefit the developed world’s industrial economy. The Handbook of Research on Nurturing Industrial Economy for Africa’s Development examines various innovations necessary for Africa’s economic development including drivers of the manufacturing economy such as education, agriculture, human capital, science and technological innovations, language, politics, and business environments. The book explores strategies to increase Africa’s economic diversity, complexity, productivity, and ultimately competitiveness, and for the continent to realize its manufacturing/industrial potential. Further, chapters focus on African countries’ industrial economies in the African context and facilitating the fulfillment of the Sustainable Development Goals (SDGs) and the African Union’s Agenda 2063. This book is a valuable reference tool for government officials, economists, industrialists, practitioners, stakeholders, researchers, academicians, and students interested in the industrial economic development of Africa.

Introduction to Python in Earth Science Data Analysis
Introduction to Python in Earth Science Data Analysis

Author: Maurizio Petrelli

Publisher: Springer Nature

Published: 2021-09-16

Total Pages: 229

ISBN-13: 3030780554

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This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.

Mesh Generation and Adaptation
Mesh Generation and Adaptation

Author: Rubén Sevilla

Publisher: Springer Nature

Published: 2022-05-18

Total Pages: 328

ISBN-13: 3030925404

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The developments in mesh generation are usually driven by the needs of new applications and/or novel algorithms. The last decade has seen a renewed interest in mesh generation and adaptation by the computational engineering community, due to the challenges introduced by complex industrial problems.Another common challenge is the need to handle complex geometries. Nowadays, it is becoming obvious that geometry should be persistent throughout the whole simulation process. Several methodologies that can carry the geometric information throughout the simulation stage are available, but due to the novelty of these methods, the generation of suitable meshes for these techniques is still the main obstacle for the industrial uptake of this technology.This book will cover different aspects of mesh generation and adaptation, with particular emphasis on cutting-edge mesh generation techniques for advanced discretisation methods and complex geometries.