[PDF] Frontiers In Neurorobotics Editors Pick 2021 eBook

Author : Kostas J. Kyriakopoulos
Publisher : Frontiers Media SA
Page : 124 pages
File Size : 24,66 MB
Release : 2024-02-13
Category : Technology & Engineering
ISBN : 2832543472

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For the second year in a row, we are very happy to offer our readership an ebook of 10 articles that have achieved widespread acceptance within our core audience and beyond. This time it concerns articles published in 2023, a landmark year for this journal, as it was officially awarded its first impact factor. These papers are among the large number that attained significant interest last year, but we selected just 10, which we consider to be the “best”. These articles have already made an impact in the form of original research or comprehensive reviews. As the Field Chief Editor, I would like to stand alongside our journal staff to honor all authors who contributed very high-level papers to the journal last year and are contributing to our success. We also thank the editors and reviewers of these papers, and of all papers this past year, for their invaluable contribution.

Author : Nima Rezaei
Publisher : Academic Press
Page : 284 pages
File Size : 16,45 MB
Release : 2022-04-19
Category : Medical
ISBN : 0128224304

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Immunoinformatics of Cancers: Practical Machine Learning Approaches Using R takes a bioinformatics approach to understanding and researching the immunological aspects of malignancies. It details biological and computational principles and the current applications of bioinformatic approaches in the study of human malignancies. Three sections cover the role of immunology in cancers and bioinformatics, including databases and tools, R programming and useful packages, and present the foundations of machine learning. The book then gives practical examples to illuminate the application of immunoinformatics to cancer, along with practical details on how computational and biological approaches can best be integrated.This book provides readers with practical computational knowledge and techniques, including programming, and machine learning, enabling them to understand and pursue the immunological aspects of malignancies. Presents the knowledge researchers need to apply computational techniques to immunodeficiencies Provides the most practical material for bioinformatics approaches to the immunology of cancers Gives straightforward and efficient explanations of programming and machine learning approaches in R Includes details of the most useful databases, tools, programming packages and algorithms for immunoinformatics Illuminates clear explanations with practical examples of immunoinformatic approaches to cancer

Author : Adam Safron
Publisher : Frontiers Media SA
Page : 392 pages
File Size : 17,27 MB
Release : 2023-12-08
Category : Science
ISBN : 2832536166

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Even before the deep learning revolution, the landscape of artificial intelligence (AI) was already changing drastically in the 90s. Embodied intelligence, it was proposed, must play a crucial role in the design of intelligent machines. This new wave was inspired by what is today known as Embodied and Enactive Cognitive Science or E-Cognition, which considers that cognitive activity does not reduce to the intellectual capacities of agents being able to represent their environments. E-cognition set AI and robotics in a new direction, in which intelligent machines are required to interact with the environment, and where this interaction does not reduce to explicit representations or prespecified algorithms. These ideas revolutionized the way we think about intelligent machines and cognition, but these theoretical advances are only partially reflected in modern approaches to AI and machine learning (ML). Despite deeply impressive achievements, AI/ML still struggles to recapitulate the kinds of intelligence we find in natural systems, whether we are considering individual insects (e.g. simultaneous localization and mapping), or swarm behaviour (e.g. forum sensing and ensemble inferences), and especially the kinds of flexibility and high-level reasoning characteristic of human cognition.