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Selected, peer reviewed papers from the 2013 3rd International Conference on Mechanical Engineering, Materials and Energy (ICMEME 2013), November 9-10, 2013, Changsha, China
The surgical treatment of the aortic valve and root disease, organic and ischemic mitral regurgitation, and endocarditis has made great strides. This book focuses on surgical approaches to and various trends in aortic valve repair, aortic root and valve replacement with pulmonary autograft, aortic allograft, stentless and stented bioprostheses.
The book is intended for all those who are interested in application problems related to dynamical systems. It provides an overview of recent findings on dynamical systems in the broadest sense. Divided into 46 contributed chapters, it addresses a diverse range of problems. The issues discussed include: Finite Element Analysis of optomechatronic choppers with rotational shafts; computational based constrained dynamics generation for a model of a crane with compliant support; model of a kinetic energy recuperation system for city buses; energy accumulation in mechanical resonance; hysteretic properties of shell dampers; modeling a water hammer with quasi-steady and unsteady friction in viscoelastic conduits; application of time-frequency methods for the assessment of gas metal arc welding conditions; non-linear modeling of the human body’s dynamic load; experimental evaluation of mathematical and artificial neural network modeling for energy storage systems; interaction of bridge cables and wake in vortex-induced vibrations; and the Sommerfeld effect in a single DOF spring-mass-damper system with non-ideal excitation.
Selected peer-reviewed extended articles based on abstracts presented at the 7th International Conference on Material Engineering and Application (ICMEA-2022) Aggregated Book
Smart Electrical and Mechanical Systems: An Application of Artificial Intelligence and Machine Learning is an international contributed work with the most up-to-date fundamentals and conventional methods used in smart electrical and mechanical systems. Detailing methods and procedures for the application of ML and AI, it is supported with illustrations of the systems, process diagrams visuals of the systems and/or their components, and supportive data and results leading to the benefits and challenges of the relevant applications. The multidisciplinary theme of the book will help researchers build a synergy between electrical and mechanical engineering systems. The book guides readers on not only how to effectively solve problems but also provide high accuracy needed for successful implementation. Interdisciplinary in nature, the book caters to the needs of the electrical and mechanical engineering industry by offering details on the application of AI and ML in robotics, design and manufacturing, image processing, power system operation and forecasting with suitable examples. - Includes significant case studies related to application of Artificial Intelligence and Machine Learning in Energy and Power, Mechanical Design and Manufacturing - Contains supporting illustrations and tables, along with a valuable set of references at the end of each chapter - Provides original, state-of-the-art research material written by international and national respected contributors
Selected, peer reviewed papers from the 2013 International Conference on Civil, Materials and Environmental Sciences (CMES 2013), April 17-18, 2013, Vancouver, Canada
This unique text presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques. Features: provides a complete framework for the modeling and analysis of noise in MRI, considering different modalities and acquisition techniques; describes noise and signal estimation for MRI from a statistical signal processing perspective; surveys the different methods to remove noise in MRI acquisitions from a practical point of view; reviews different techniques for estimating noise from MRI data in single- and multiple-coil systems for fully sampled acquisitions; examines the issue of noise estimation when accelerated acquisitions are considered, and parallel imaging methods are used to reconstruct the signal; includes appendices covering probability density functions, combinations of random variables used to derive estimators, and useful MRI datasets.
2016 International Conference on Electrical Engineering and Automation (EEA2016) was held in Hong Kong, China from June 24th-26th, 2016. EEA2016 has provided a platform for leading academic scientists, researchers, scholars and students around the world, to get together to compare notes, and share their results and findings, in areas of Electronics Engineering and Electrical Engineering, Materials and Mechanical Engineering, Control and Automation Modeling and Simulation, Testing and Imaging, Robotics, Actuating and Sensoring.The conference had received a total of 445 submissions. However, after peer review by the Technical Program Committee only 129 were selected to be included in this conference proceedings; based on their originality, ability to test ideas, and contribution to the understanding and advancement in Electronics and Electrical Engineering.
This book gathers selected contributions presented at the Enzo Levi and XX Annual Meeting of the Fluid Dynamic Division of the Mexican Physical Society in 2014. The individual papers explore recent advances in experimental and theoretical fluid dynamics and are suitable for use in both teaching and research. The fluid dynamics applications covered include multiphase flows, convection, diffusion, heat transfer, rheology, granular materials, viscous flows, porous media flows, geophysics and astrophysics. The contributions, some of which are introductory and avoid the use of complicated mathematics, are suitable for fourth-year undergraduate and graduate students. Accordingly, the book is of immense benefit to these students, as well as to scientists in the fields of physics, chemistry and engineering with an interest in fluid dynamics from experimental and theoretical points of view.