Explore the multidisciplinary nature of complex networks through machine learning techniques
Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for...
Sound is an integral part of every user experience but a neglected medium in design disciplines. Design of an artifact's sonic qualities is often limited to the shaping of functional, representational, and signaling roles of sound. The interdisciplinary field of sonic interaction design (SID) challenges these prevalent approaches by...
Wireless ad hoc sensor networks have recently become a very active research subject
as well as a topic of rapid technological progress and large-scale practical development
and application activities. However, a solid foundational and theoretical
background seems still necessary for sensor networking to achieve its full potential....
Healthcare professionals and patients hold fundamentally different views with respect to the content of quality in healthcare as related to the reliability of systems and services.
E-Health Systems Quality and Reliability: Models and Standards addresses the reason, principles and functionality of health and health care...
"Despite spending more than $600 billion on information technology over the past decade, the Federal Government has achieved little of the productivity improvements that private industry has realized from IT" according to the 25 Point Implementation Plan to Reform Federal Information Technology Management published by the...
Snake Robots is a novel treatment of theoretical and practical topics related to snake robots: robotic mechanisms designed to move like biological snakes and able to operate in challenging environments in which human presence is either undesirable or impossible. Future applications of such robots include search and rescue, inspection and...
No organization can survive without iconoclasts -- innovators who single-handedly upturn conventional wisdom and manage to achieve what so many others deem impossible.
Though indispensable, true iconoclasts are few and far between. In Iconoclast, neuroscientist Gregory Berns explains why. He explores the constraints...
There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of...
What is the secret of talent? How do we unlock it? In this groundbreaking work, journalist and New York Times bestselling author Daniel Coyle provides parents, teachers, coaches, businesspeople—and everyone else—with tools they can use to maximize potential in themselves and others.
This graduate-level textbook introduces fundamental concepts and methods in machine learning. It describes several important modern algorithms, provides the theoretical underpinnings of these algorithms, and illustrates key aspects for their application. The authors aim to present novel theoretical tools and concepts while giving concise...
Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and discriminant analysis. It is currently mainly the domain of computer scientists, and is already commonly used in social sciences, marketing...
The book is written for students as well as for teachers and researchers in the field of High Voltage and Insulation Engineering. It is based on the advance level courses conducted at TU Dresden, Germany and Indian Institute of Technology Kanpur, India. The book has a novel approach describing the fundamental concept of field dependent...
