Ultrasonic Material Characterization and Imaging by Unsupervised Learning PDF Download

Author: Jeng Tzong Sheu
Publisher:
ISBN:
Category : Diagnostic ultrasonic imaging
Languages : en
Pages : 240

View

Book Description

Author: Chi-hau Chen
Publisher: World Scientific
ISBN: 9812704094
Category : Medical
Languages : en
Pages : 682

View

Book Description
Ultrasonic methods have been very popular in nondestructive testing and characterization of materials. This book deals with both industrial ultrasound and medical ultrasound. The advantages of ultrasound include flexibility, low cost, in-line operation, and providing data in both signal and image formats for further analysis. The book devotes 11 chapters to ultrasonic methods. However, ultrasonic methods can be much less effective with some applications. So the book also has 14 chapters catering to other or advanced methods for nondestructive testing or material characterization. Topics like structural health monitoring, Terahertz methods, X-ray and thermography methods are presented. Besides different sensors for nondestructive testing, the book places much emphasis on signal/image processing and pattern recognition of the signals acquired.

Author: Francesca Lionetto
Publisher: Mdpi AG
ISBN: 9783036517100
Category : Technology & Engineering
Languages : en
Pages : 188

View

Book Description
Ultrasonic waves are nowadays used for multiple purposes including both low-intensity/high frequency and high-intensity/low-frequency ultrasound. Low-intensity ultrasound transmits energy through the medium in order to obtain information about the medium or to convey information through the medium. It is successfully used in non-destructive inspection, ultrasonic dynamic analysis, ultrasonic rheology, ultrasonic spectroscopy of materials, process monitoring, applications in civil engineering, aerospace and geological materials and structures, and in the characterization of biological media. Nowadays, it is an essential tool for assessing metals, plastics, aerospace composites, wood, concrete, and cement. High-intensity ultrasound deliberately affects the propagation medium through the high local temperatures and pressures generated. It is used in industrial processes such as welding, cleaning, emulsification, atomization, etc.; chemical reactions and reactor induced by ultrasonic waves; synthesis of organic and inorganic materials; microstructural effects; heat generation; accelerated material characterization by ultrasonic fatigue testing; food processing; and environmental protection. This book collects eleven papers, one review, and ten research papers with the aim to present recent advances in ultrasonic wave propagation applied for the characterization or the processing of materials. Both fundamental science and applications of ultrasound in the field of material characterization and material processing have been gathered.

Author: Siddharth Misra
Publisher: Gulf Professional Publishing
ISBN: 0128177373
Category : Technology & Engineering
Languages : en
Pages : 442

View

Book Description
Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine learning (ML) focusses on developing computational methods/algorithms that learn to recognize patterns and quantify functional relationships by processing large data sets, also referred to as the "big data." Deep learning (DL) is a subset of machine learning that processes "big data" to construct numerous layers of abstraction to accomplish the learning task. DL methods do not require the manual step of extracting/engineering features; however, it requires us to provide large amounts of data along with high-performance computing to obtain reliable results in a timely manner. This reference helps the engineers, geophysicists, and geoscientists get familiar with data science and analytics terminology relevant to subsurface characterization and demonstrates the use of data-driven methods for outlier detection, geomechanical/electromagnetic characterization, image analysis, fluid saturation estimation, and pore-scale characterization in the subsurface. - Learn from 13 practical case studies using field, laboratory, and simulation data - Become knowledgeable with data science and analytics terminology relevant to subsurface characterization - Learn frameworks, concepts, and methods important for the engineer's and geoscientist's toolbox needed to support

Author: Harold Berger
Publisher:
ISBN:
Category : Ultrasonic testing
Languages : en
Pages : 680

View

Book Description

Author: Amadou Belal Gueye
Publisher: Elsevier
ISBN: 0323914217
Category : Technology & Engineering
Languages : en
Pages : 715

View

Book Description
Nanostructured Materials Engineering and Characterization for Battery Applications is designed to help solve fundamental and applied problems in the field of energy storage. Broken up into four separate sections, the book begins with a discussion of the fundamental electrochemical concepts in the field of energy storage. Other sections look at battery materials engineering such as cathodes, electrolytes, separators and anodes and review various battery characterization methods and their applications. The book concludes with a review of the practical considerations and applications of batteries.This will be a valuable reference source for university professors, researchers, undergraduate and postgraduate students, as well as scientists working primarily in the field of materials science, applied chemistry, applied physics and nanotechnology. - Presents practical consideration for battery usage such as LCA, recycling and green batteries - Covers battery characterization techniques including electrochemical methods, microscopy, spectroscopy and X-ray methods - Explores battery models and computational materials design theories

Author: Amit Kumar
Publisher: Springer Nature
ISBN: 9811636907
Category : Technology & Engineering
Languages : en
Pages : 1600

View

Book Description
This book gathers selected high-impact articles from the 2nd International Conference on Data Science, Machine Learning & Applications 2020. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.

Author: Leonard A. Ferrari
Publisher:
ISBN:
Category : Psychology
Languages : en
Pages : 380

View

Book Description

Author: ASM International
Publisher: ASM International
ISBN: 1627082735
Category : Technology & Engineering
Languages : en
Pages : 540

View

Book Description
The theme for the 2019 conference is Novel Computing Architectures. Papers will include discussions on the advent of Artificial Intelligence and the promise of quantum computing that are driving disruptive computing architectures; Neuromorphic chip designs on one hand, and Quantum Bits on the other, still in R&D, will introduce new computing circuitry and memory elements, novel materials, and different test methodologies. These novel computing architectures will require further innovation which is best achieved through a collaborative Failure Analysis community composed of chip manufacturers, tool vendors, and universities.

Author: Vinit Kumar Gunjan
Publisher: Springer Nature
ISBN: 9811664072
Category : Technology & Engineering
Languages : en
Pages : 821

View

Book Description
This book contains original, peer-reviewed research articles from the Second International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, held in March 28-29th 2021 at CMR Institute of Technology, Hyderabad, Telangana India. It covers the latest research trends and developments in areas of machine learning, artificial intelligence, neural networks, cyber-physical systems, cybernetics, with emphasis on applications in smart cities, Internet of Things, practical data science and cognition. The book focuses on the comprehensive tenets of artificial intelligence, machine learning and deep learning to emphasize its use in modelling, identification, optimization, prediction, forecasting and control of future intelligent systems. Submissions were solicited of unpublished material, and present in-depth fundamental research contributions from a methodological/application perspective in understanding artificial intelligence and machine learning approaches and their capabilities in solving a diverse range of problems in industries and its real-world applications.