This volume presents several machine intelligence technologies, developed over recent decades, and illustrates how they can be combined in application. One application, the detection of dementia from patterns in speech, is used throughout to illustrate these combinations. This application is a classic stationary pattern detection task, so readers may easily see how these combinations can be applied to other similar tasks. The expositions of the methods are supported by the basic theory they rest upon, and their application is clearly illustrated. The book's goal is to allow readers to select one or more of these methods to quickly apply to their own tasks. Includes a variety of machine intelligent technologies and illustrates how they can work together Shows evolutionary feature subset selection combined with support vector machines and multiple classifiers combined Includes a running case study on intelligent processing relating to Alzheimer's / dementia detection, in addition to several applications of the machine hybrid algorithms

While the potential of stem cells is recognized, their proliferation and differentiation must be more precisely controlled to maximize the production of therapeutically relevant cells and for cell replacement therapies to minimize contamination with residual cells that can give rise to side effects. How can engineers make contributions to address these challenges? With contributions from pioneers and experts, Stem Cell Engineering: Principles and Practices highlights recent advances in the understanding of the cellular and molecular composition of the stem cell niche, as well as approaches to build upon this basic information to direct stem cell differentiation into therapeutically valuable lineages. The growing recognition of stem cells as an important and exciting field will continue to draw investigators with diverse backgrounds-from biology, engineering, and the physical sciences-and thereby enable further progress in these and other new directions. This book discusses advances made during the last decade that have led to increasingly defined culture systems for growing stem cells, starting from co-culture with feeder cells in the presence of serum to growth on synthetic substrates in defined medium. In addition to highlighting many recent advances, it underscores the need for future work.

While the potential of stem cells is recognized, their proliferation and differentiation must be more precisely controlled to maximize the production of therapeutically relevant cells and for cell replacement therapies to minimize contamination with residual cells that can give rise to side effects. How can engineers make contributions to address these challenges? With contributions from pioneers and experts, Stem Cell Engineering: Principles and Practices highlights recent advances in the understanding of the cellular and molecular composition of the stem cell niche, as well as approaches to build upon this basic information to direct stem cell differentiation into therapeutically valuable lineages. The growing recognition of stem cells as an important and exciting field will continue to draw investigators with diverse backgrounds-from biology, engineering, and the physical sciences-and thereby enable further progress in these and other new directions. This book discusses advances made during the last decade that have led to increasingly defined culture systems for growing stem cells, starting from co-culture with feeder cells in the presence of serum to growth on synthetic substrates in defined medium. In addition to highlighting many recent advances, it underscores the need for future work.

This volume presents several machine intelligence technologies, developed over recent decades, and illustrates how they can be combined in application. One application, the detection of dementia from patterns in speech, is used throughout to illustrate these combinations. This application is a classic stationary pattern detection task, so readers may easily see how these combinations can be applied to other similar tasks. The expositions of the methods are supported by the basic theory they rest upon, and their application is clearly illustrated. The book's goal is to allow readers to select one or more of these methods to quickly apply to their own tasks. Includes a variety of machine intelligent technologies and illustrates how they can work together Shows evolutionary feature subset selection combined with support vector machines and multiple classifiers combined Includes a running case study on intelligent processing relating to Alzheimer's / dementia detection, in addition to several applications of the machine hybrid algorithms