Nilesh Kulkarni - Böcker
678 kr
Skickas inom 7-10 vardagar
This book will summarize research work carried out so far on dissimilar metallic material welding using friction stir welding (FSW). Joining of dissimilar alloys and materials are needed in many engineering systems and is considered quite challenging. Research in this area has shown significant benefit in terms of ease of processing, material mixing, and superior mechanical properties such as joint efficiencies. A summary of these results will be discussed along with potential guidelines for designers.
Explains solid phase process and distortion of work piece Addresses dimensional stability and repeatability Addresses joint strength Covers metallurgical properties in the joint area Covers fine microstructure Introduces improved materials use (e.g., joining different thicknesses) Covers decreased fuel consumption in light weight aircraft Addresses automotive and ship applications
EEG-Based Diagnosis of Alzheimer Disease
A Review and Novel Approaches for Feature Extraction and Classification Techniques
1 162 kr
Skickas inom 7-10 vardagar
EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer's disease, and dementia diagnostics. The book examines different features of EEG signals used to properly diagnose Alzheimer's Disease early, presenting new and innovative results in the extraction and classification of Alzheimer's Disease using EEG signals. This book brings together the use of different EEG features, such as linear and nonlinear features, which play a significant role in diagnosing Alzheimer's Disease.
Includes the mathematical models and rigorous analysis of various classifiers and machine learning algorithms from a perspective of clinical deployment Covers the history of EEG signals and their measurement and recording, along with their uses in clinical diagnostics Analyzes spectral, wavelet, complexity and other features of early and efficient Alzheimer's Disease diagnostics Explores support vector machine-based classification to increase accuracy