Author: Paul M. Rea
Publisher: Springer Nature
ISBN: 3030877795
Category : Medical
Languages : en
Pages : 351
Book Description
This edited book explores the use of technology to enable us to visualise the life sciences in a more meaningful and engaging way. It will enable those interested in visualisation techniques to gain a better understanding of the applications that can be used in visualisation, imaging and analysis, education, engagement and training. The reader will also be able to learn about the use of visualisation techniques and technologies for the historical and forensic settings. The chapters presented in this volume cover such a diverse range of topics, with something for everyone. We present here chapters on 3D visualising novel stent grafts to aid treatment of aortic aneuryms; confocal microscopy constructed vascular models in patient education; 3D patient specific virtual reconstructions in surgery; virtual reality in upper limb rehabilitation in patients with multiple sclerosis and virtual clinical wards. In addition, we present chapters in artificial intelligence in ultrasound guided regional anaesthesia; carpal tunnel release visualisation techniques; visualising for embryology education and artificial intelligence data on bone mechanics. Finally we conclude with chapters on visualising patient communication in a general practice setting; digital facial depictions of people from the past; instructor made cadaveric videos, novel cadaveric techniques for enhancing visualisation of the human body and finally interactive educational videos and screencasts. This book explores the use of technologies from a range of fields to provide engaging and meaningful visual representations of the biomedical sciences. It is therefore an interesting read for researchers, developers and educators who want to learn how visualisation techniques can be used successfully for a variety of purposes, such as educating students or training staff, interacting with patients and biomedical procedures in general.
Biomedical Visualisation
Author: Paul M. Rea
Publisher: Springer Nature
ISBN: 3030877795
Category : Medical
Languages : en
Pages : 351
Book Description
This edited book explores the use of technology to enable us to visualise the life sciences in a more meaningful and engaging way. It will enable those interested in visualisation techniques to gain a better understanding of the applications that can be used in visualisation, imaging and analysis, education, engagement and training. The reader will also be able to learn about the use of visualisation techniques and technologies for the historical and forensic settings. The chapters presented in this volume cover such a diverse range of topics, with something for everyone. We present here chapters on 3D visualising novel stent grafts to aid treatment of aortic aneuryms; confocal microscopy constructed vascular models in patient education; 3D patient specific virtual reconstructions in surgery; virtual reality in upper limb rehabilitation in patients with multiple sclerosis and virtual clinical wards. In addition, we present chapters in artificial intelligence in ultrasound guided regional anaesthesia; carpal tunnel release visualisation techniques; visualising for embryology education and artificial intelligence data on bone mechanics. Finally we conclude with chapters on visualising patient communication in a general practice setting; digital facial depictions of people from the past; instructor made cadaveric videos, novel cadaveric techniques for enhancing visualisation of the human body and finally interactive educational videos and screencasts. This book explores the use of technologies from a range of fields to provide engaging and meaningful visual representations of the biomedical sciences. It is therefore an interesting read for researchers, developers and educators who want to learn how visualisation techniques can be used successfully for a variety of purposes, such as educating students or training staff, interacting with patients and biomedical procedures in general.
Publisher: Springer Nature
ISBN: 3030877795
Category : Medical
Languages : en
Pages : 351
Book Description
This edited book explores the use of technology to enable us to visualise the life sciences in a more meaningful and engaging way. It will enable those interested in visualisation techniques to gain a better understanding of the applications that can be used in visualisation, imaging and analysis, education, engagement and training. The reader will also be able to learn about the use of visualisation techniques and technologies for the historical and forensic settings. The chapters presented in this volume cover such a diverse range of topics, with something for everyone. We present here chapters on 3D visualising novel stent grafts to aid treatment of aortic aneuryms; confocal microscopy constructed vascular models in patient education; 3D patient specific virtual reconstructions in surgery; virtual reality in upper limb rehabilitation in patients with multiple sclerosis and virtual clinical wards. In addition, we present chapters in artificial intelligence in ultrasound guided regional anaesthesia; carpal tunnel release visualisation techniques; visualising for embryology education and artificial intelligence data on bone mechanics. Finally we conclude with chapters on visualising patient communication in a general practice setting; digital facial depictions of people from the past; instructor made cadaveric videos, novel cadaveric techniques for enhancing visualisation of the human body and finally interactive educational videos and screencasts. This book explores the use of technologies from a range of fields to provide engaging and meaningful visual representations of the biomedical sciences. It is therefore an interesting read for researchers, developers and educators who want to learn how visualisation techniques can be used successfully for a variety of purposes, such as educating students or training staff, interacting with patients and biomedical procedures in general.
Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems
Author: Yinpeng Wang
Publisher: CRC Press
ISBN: 100089665X
Category : Computers
Languages : en
Pages : 200
Book Description
This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems. Pursuing a holistic perspective, the book includes the following areas. The first chapter discusses the basic DL frameworks. Then, the steady heat conduction problem is solved by the classical U-net in Chapter 2, involving both the passive and active cases. Afterwards, the sophisticated heat flux on a curved surface is reconstructed by the presented Conv-LSTM, exhibiting high accuracy and efficiency. Additionally, a physics-informed DL structure along with a nonlinear mapping module are employed to obtain the space/temperature/time-related thermal conductivity via the transient temperature in Chapter 4. Finally, in Chapter 5, a series of the latest advanced frameworks and the corresponding physics applications are introduced. As deep learning techniques are experiencing vigorous development in computational physics, more people desire related reading materials. This book is intended for graduate students, professional practitioners, and researchers who are interested in DL for computational physics.
Publisher: CRC Press
ISBN: 100089665X
Category : Computers
Languages : en
Pages : 200
Book Description
This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems. Pursuing a holistic perspective, the book includes the following areas. The first chapter discusses the basic DL frameworks. Then, the steady heat conduction problem is solved by the classical U-net in Chapter 2, involving both the passive and active cases. Afterwards, the sophisticated heat flux on a curved surface is reconstructed by the presented Conv-LSTM, exhibiting high accuracy and efficiency. Additionally, a physics-informed DL structure along with a nonlinear mapping module are employed to obtain the space/temperature/time-related thermal conductivity via the transient temperature in Chapter 4. Finally, in Chapter 5, a series of the latest advanced frameworks and the corresponding physics applications are introduced. As deep learning techniques are experiencing vigorous development in computational physics, more people desire related reading materials. This book is intended for graduate students, professional practitioners, and researchers who are interested in DL for computational physics.
Data-driven Modelling and Scientific Machine Learning in Continuum Physics
Author: Krishna Garikipati
Publisher: Springer Nature
ISBN: 3031620291
Category :
Languages : en
Pages : 233
Book Description
Publisher: Springer Nature
ISBN: 3031620291
Category :
Languages : en
Pages : 233
Book Description
Deep Learning and Computational Physics
Author: Deep Ray
Publisher: Springer Nature
ISBN: 3031593456
Category :
Languages : en
Pages : 160
Book Description
Publisher: Springer Nature
ISBN: 3031593456
Category :
Languages : en
Pages : 160
Book Description
Deep Learning in Computational Mechanics
Author: Stefan Kollmannsberger
Publisher: Springer Nature
ISBN: 3030765873
Category : Technology & Engineering
Languages : en
Pages : 108
Book Description
This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine learning’s fundamental concepts before neural networks are explained thoroughly. It then provides an overview of current topics in physics and engineering, setting the stage for the book’s main topics: physics-informed neural networks and the deep energy method. The idea of the book is to provide the basic concepts in a mathematically sound manner and yet to stay as simple as possible. To achieve this goal, mostly one-dimensional examples are investigated, such as approximating functions by neural networks or the simulation of the temperature’s evolution in a one-dimensional bar. Each chapter contains examples and exercises which are either solved analytically or in PyTorch, an open-source machine learning framework for python.
Publisher: Springer Nature
ISBN: 3030765873
Category : Technology & Engineering
Languages : en
Pages : 108
Book Description
This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine learning’s fundamental concepts before neural networks are explained thoroughly. It then provides an overview of current topics in physics and engineering, setting the stage for the book’s main topics: physics-informed neural networks and the deep energy method. The idea of the book is to provide the basic concepts in a mathematically sound manner and yet to stay as simple as possible. To achieve this goal, mostly one-dimensional examples are investigated, such as approximating functions by neural networks or the simulation of the temperature’s evolution in a one-dimensional bar. Each chapter contains examples and exercises which are either solved analytically or in PyTorch, an open-source machine learning framework for python.
Numerical Algorithms
Author: Justin Solomon
Publisher: CRC Press
ISBN: 1482251892
Category : Computers
Languages : en
Pages : 400
Book Description
Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic desig
Publisher: CRC Press
ISBN: 1482251892
Category : Computers
Languages : en
Pages : 400
Book Description
Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic desig
Model Reduction and Approximation
Author: Peter Benner
Publisher: SIAM
ISBN: 161197481X
Category : Science
Languages : en
Pages : 421
Book Description
Many physical, chemical, biomedical, and technical processes can be described by partial differential equations or dynamical systems. In spite of increasing computational capacities, many problems are of such high complexity that they are solvable only with severe simplifications, and the design of efficient numerical schemes remains a central research challenge. This book presents a tutorial introduction to recent developments in mathematical methods for model reduction and approximation of complex systems. Model Reduction and Approximation: Theory and Algorithms contains three parts that cover (I) sampling-based methods, such as the reduced basis method and proper orthogonal decomposition, (II) approximation of high-dimensional problems by low-rank tensor techniques, and (III) system-theoretic methods, such as balanced truncation, interpolatory methods, and the Loewner framework. It is tutorial in nature, giving an accessible introduction to state-of-the-art model reduction and approximation methods. It also covers a wide range of methods drawn from typically distinct communities (sampling based, tensor based, system-theoretic).?? This book is intended for researchers interested in model reduction and approximation, particularly graduate students and young researchers.
Publisher: SIAM
ISBN: 161197481X
Category : Science
Languages : en
Pages : 421
Book Description
Many physical, chemical, biomedical, and technical processes can be described by partial differential equations or dynamical systems. In spite of increasing computational capacities, many problems are of such high complexity that they are solvable only with severe simplifications, and the design of efficient numerical schemes remains a central research challenge. This book presents a tutorial introduction to recent developments in mathematical methods for model reduction and approximation of complex systems. Model Reduction and Approximation: Theory and Algorithms contains three parts that cover (I) sampling-based methods, such as the reduced basis method and proper orthogonal decomposition, (II) approximation of high-dimensional problems by low-rank tensor techniques, and (III) system-theoretic methods, such as balanced truncation, interpolatory methods, and the Loewner framework. It is tutorial in nature, giving an accessible introduction to state-of-the-art model reduction and approximation methods. It also covers a wide range of methods drawn from typically distinct communities (sampling based, tensor based, system-theoretic).?? This book is intended for researchers interested in model reduction and approximation, particularly graduate students and young researchers.
Genetic Programming
Author: John R. Koza
Publisher: MIT Press
ISBN: 9780262111706
Category : Computers
Languages : en
Pages : 856
Book Description
In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.
Publisher: MIT Press
ISBN: 9780262111706
Category : Computers
Languages : en
Pages : 856
Book Description
In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.
Advances in Theory and Practice of Computational Mechanics
Author: Lakhmi C. Jain
Publisher: Springer Nature
ISBN: 9811526001
Category : Technology & Engineering
Languages : en
Pages : 386
Book Description
This book discusses physical and mathematical models, numerical methods, computational algorithms and software complexes, which allow high-precision mathematical modeling in fluid, gas, and plasma mechanics; general mechanics; deformable solid mechanics; and strength, destruction and safety of structures. These proceedings focus on smart technologies and software systems that provide effective solutions to real-world problems in applied mechanics at various multi-scale levels. Highlighting the training of specialists for the aviation and space industry, it is a valuable resource for experts in the field of applied mathematics and mechanics, mathematical modeling and information technologies, as well as developers of smart applied software systems.
Publisher: Springer Nature
ISBN: 9811526001
Category : Technology & Engineering
Languages : en
Pages : 386
Book Description
This book discusses physical and mathematical models, numerical methods, computational algorithms and software complexes, which allow high-precision mathematical modeling in fluid, gas, and plasma mechanics; general mechanics; deformable solid mechanics; and strength, destruction and safety of structures. These proceedings focus on smart technologies and software systems that provide effective solutions to real-world problems in applied mechanics at various multi-scale levels. Highlighting the training of specialists for the aviation and space industry, it is a valuable resource for experts in the field of applied mathematics and mechanics, mathematical modeling and information technologies, as well as developers of smart applied software systems.
Computational Geometry
Author: Mark de Berg
Publisher: Springer Science & Business Media
ISBN: 3662042452
Category : Computers
Languages : en
Pages : 370
Book Description
This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.
Publisher: Springer Science & Business Media
ISBN: 3662042452
Category : Computers
Languages : en
Pages : 370
Book Description
This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.