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Record Nr. |
UNISA996418197603316 |
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Autore |
Giraldo Francis X. |
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Titolo |
An introduction to element-based Galerkin methods on tensor-product bases : analysis, algorithms, and applications / / Francis X. Giraldo |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2020] |
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©2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XXVI, 559 p. 171 illus., 168 illus. in color.) |
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Collana |
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Texts in Computational Science and Engineering, , 1611-0994 ; ; 24 |
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Disciplina |
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Soggetti |
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Differential equations, Partial - Numerical solutions |
Computer science - Mathematics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Introduction -- Motivation and Background -- Overview of Existing Methods -- One-Dimensional Problems -- Interpolation in One Dimension -- Numerical Integration in One Dimension -- 1D Continuous Galerkin Method for Hyperbolic Equations -- 1D Discontinuous Galerkin Methods for Hyperbolic Equations -- 1D Unified Continuous and Discontinuous Galerkin Methods for Systems of Hyperbolic Equations -- 1D Continuous Galerkin Methods for Elliptic Equations -- 1D Discontinuous Galerkin Methods for Elliptic Equations -- Two-Dimensional Problems -- Interpolation in Multiple Dimensions -- Numerical Integration in Multiple Dimensions -- 2D Continuous Galerkin Methods for Elliptic Equations -- 2D Discontinuous Galerkin Methods for Elliptic Equations -- 2D Unified Continuous and Discontinuous Galerkin Methods for Elliptic Equations -- 2D Continuous Galerkin Methods for Hyperbolic Equations -- 2D Discontinuous Galerkin Methods for Hyperbolic Equations -- 2D Continuous/Discontinuous Galerkin Methods for Hyperbolic Equations -- Advanced Topics -- Stabilization of High-Order Methods -- Adaptive Mesh Refinement -- Time Integration -- 1D Hybridizable Discontinuous Galerkin Method -- Classification of Partial Differential Equations and Vector Notation -- Jacobi Polynomials -- Data Structures. |
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Sommario/riassunto |
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This book introduces the reader to solving partial differential equations (PDEs) numerically using element-based Galerkin methods. Although it draws on a solid theoretical foundation (e.g. the theory of interpolation, numerical integration, and function spaces), the book’s main focus is on how to build the method, what the resulting matrices look like, and how to write algorithms for coding Galerkin methods. In addition, the spotlight is on tensor-product bases, which means that only line elements (in one dimension), quadrilateral elements (in two dimensions), and cubes (in three dimensions) are considered. The types of Galerkin methods covered are: continuous Galerkin methods (i.e., finite/spectral elements), discontinuous Galerkin methods, and hybridized discontinuous Galerkin methods using both nodal and modal basis functions. In addition, examples are included (which can also serve as student projects) for solving hyperbolic and elliptic partial differential equations, including both scalar PDEs and systems of equations. |
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2. |
Record Nr. |
UNINA9910731481703321 |
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Autore |
Sarveshwaran Velliangiri |
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Titolo |
Artificial Intelligence and Cyber Security in Industry 4.0 / / edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (374 pages) |
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Collana |
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Advanced Technologies and Societal Change, , 2191-6861 |
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Altri autori (Persone) |
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ChenJoy Iong-zong |
PelusiDanilo |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Internet of things |
Big data |
Machine learning |
Computational intelligence |
Wireless communication systems |
Mobile communication systems |
Artificial Intelligence |
Internet of Things |
Big Data |
Machine Learning |
Computational Intelligence |
Wireless and Mobile Communication |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction to Artificial Intelligence and Cyber Security for Industry -- Role of AI and its impact on the development of cyber security applications -- AI and IoT in Manufacturing and related Security Perspectives for Industry 4.0 -- IoT Security Vulnerabilities and Defensive Measures in Industry 4.0 -- Adopting Artificial Intelligence in ITIL for Information Security Management - Way forward in Industry 4.0 -- Intelligent Autonomous Drones in Industry 4.0 -- A review on automatic generation of attack trees and its application to automotive cybersecurity -- Malware Analysis using Machine Learning Tools and Techniques in IT Industry -- USE OF MACHINE LEARNING IN FORENSICS AND COMPUTER SECURITY -- Control of feed drives in CNC machine tools using artificial immune adaptive strategy -- Efficient Anomaly Detection for Empowering Cyber Security by Using Adaptive Deep Learning Model -- Intrusion Detection in IoT based Healthcare Using ML and DL approaches: A Case Study -- War Strategy Algorithm based GAN model for Detecting the Malware Attacks in Modern Digital Age -- ML algorithms for providing financial security in banking sectors with the prediction of loan risks -- Machine Learning based DDoS Attack Detection using Support Vector Machine -- Artificial Intelligence based Cyber Security Applications. |
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Sommario/riassunto |
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This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications. |
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