This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the big data era, large-scale datasets pose enormous challenges for the existing machine learning systems. As such, implementing machine learning algorithms in a distributed environment has become a key technology, and recent research has shown gradient-based iterative optimization to be an effective solution. Focusing on methods that can speed up large-sca...

Machinery Dynamics includes recent advancements in this quickly evolving area, while also analyzing real applications, analyzing integrated systems, and including further discussions on each mechanical component. The book treats mechanisms separately, with different methods depending on the level of accuracy required. The contents of this book is made to suit the needs of MsC and PhD students, researchers and engineers in the areas of design of high speed machinery, condition monitoring of...

This book explores the history of mechanical engineering since the Bronze Age. Focusing on machinery inventions and the development of mechanical technology, it also discusses the machinery industry and modern mechanical education. The evolution of machinery is divided into three stages: Ancient (before the European Renaissance), Modern (mainly including the two Industrial Revolutions) and Contemporary (since the Revolution in Physics, especially post Second World War). The book not only c...

This book constitutes the refereed post-conference proceedings of the 14th BenchCouncil International Symposium on Benchmarking, Measuring, and Optimization, Bench 2022, held virtually in November 2022.The 10 revised full papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in topical sections named: Architecture and System, Algorithm and Dataset, Network and Memory.