Biomechanical engineering is involved with creating and producing a variety of products in everyday use, from environmentally safe plastics to various foods, fabrics, and medicines. A combination of engineering and biology, it is a fast-growing field with many new and exciting opportunities in genetic engineering and biotechnology. However, research surrounding biomechanical applications is scattered and often restricted, leading to the need for a comprehensive publication of the recent advances and developments in this emerging field. Design, Development, and Optimization of Bio-Mechatronic Engineering Products provides pivotal research on the application of combining mechanical engineering with human biological systems in order to develop bio-mechatronic products like pacemakers, artificial kidney replacements, artificial hearts, and new joints or limbs to better and more accurately monitor and advance human health. While highlighting topics such as orthotic devices, inter-electrode gap, and biomaterial applications, this publication explores producing artificial material to work in sync with the human body. This book is ideally designed for engineers, health professionals, technology developers, researchers, academicians, and students.

Includes supplements.

Hydraulic Structure, Equipment and Water Data Acquisition Systems is a component of Encyclopedia of Water Sciences, Engineering and Technology Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Hydraulic structures occupied a vital role in the development of civilization from the earliest recorded history up to the present, and undoubtedly will do so in the future. Humanity in ancient times settled mostly near perennial rivers, nomadic people frequented oases and springs, and to augment these natural ephemeral supplies, established societies built primitive dams and dug wells. This 4-volume set contains several chapters, each of size 5000-30000 words, with perspectives, applications and extensive illustrations. It carries state-of-the-art knowledge in the fields of Hydraulic Structure, Equipment and Water Data Acquisition Systems. In these volumes the historical origins, modern developments, and future perspectives in the field of water supply engineering are discussed. Various types of hydraulic structures, their associated equipment, and the various systems for collecting data are described. These four volumes are aimed at the following five major target audiences: University and College Students Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers, NGOs and GOs.

The field of polymer nanocomposites has become essential for engineering and military industries over the last few decades as it applies to computing, sensors, biomedical microelectronics, hard coating, and many other domains. Due to their outstanding mechanical and thermal features, polymer nanocomposite materials have recently been developed and now have a wide range of applications. Polymer Nanocomposites for Advanced Engineering and Military Applications provides emerging research on recent advances in the fabrication methods, properties, and applications of various nano-fillers including surface-modification methods and chemical functionalization. Featuring coverage on a broad range of topics such as barrier properties, biomedical microelectronics, and matrix processing, this book is ideally designed for engineers, industrialists, chemists, government officials, military professionals, practitioners, academicians, researchers, and students.

Deep Learning and Missing Data in Engineering Systems uses deep learning and swarm intelligence methods to cover missing data estimation in engineering systems. The missing data estimation processes proposed in the book can be applied in image recognition and reconstruction. To facilitate the imputation of missing data, several artificial intelligence approaches are presented, including: deep autoencoder neural networks; deep denoising autoencoder networks; the bat algorithm; the cuckoo search algorithm; and the firefly algorithm. The hybrid models proposed are used to estimate the missing data in high-dimensional data settings more accurately. Swarm intelligence algorithms are applied to address critical questions such as model selection and model parameter estimation. The authors address feature extraction for the purpose of reconstructing the input data from reduced dimensions by the use of deep autoencoder neural networks. They illustrate new models diagrammatically, report their findings in tables, so as to put their methods on a sound statistical basis. The methods proposed speed up the process of data estimation while preserving known features of the data matrix. This book is a valuable source of information for researchers and practitioners in data science. Advanced undergraduate and postgraduate students studying topics in computational intelligence and big data, can also use the book as a reference for identifying and introducing new research thrusts in missing data estimation.