THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

System Identification I

Applications of machine learning to machine fault diagnosis: A review and roadmap

A strain sensor has been fabricated from a polymer nanocomposite with multiwalled carbon nanotube (MWNT) fillers. The piezoresistivity
of this nanocomposite strain sensor has been investigated based on an improved three-dimensional (3D) statistical resistor network
model incorporating the tunneling effect between the neighboring carbon nanotubes (CNTs), and a fiber reorientation model. The
numerical results agree very well with the experimental measurements. As compared with traditional strain gauges, much higher sensitivity
can be obtained in the nanocomposite sensors when the volume fraction of CNT is close to the percolation threshold. For a small
CNT volume fraction, weak nonlinear piezoresistivity is observed both experimentally and from numerical simulation. The tunneling
effect is considered to be the principal mechanism of the sensor under small strains.

Tunneling effect in a polymer/carbon nanotube nanocompositestrain sensor

Magnetic resonance imaging-based brain tumor grades classification and grading via convolutional neural networks and genetic algorithms

Disturbance-observer-based fuzzy terminal sliding mode control for MIMO uncertain nonlinear systems

Wind turbine technology is pursuing the maturation using advanced multi-megawatt machinery equipped by powerful monitoring systems. In this work, a multichannel convolutional neural network is employed to develop an autonomous databased fault diagnosis algorithm. This algorithm has been evaluated in a 5MW wind turbine benchmark model. Several faults for various wind speeds are simulated in the benchmark model, and output data are recorded. A multichannel convolutional neural network with multiple parallel local heads is utilized in order to consider changes in every measured variable separately to identify subsystem faults. Time-domain signals obtained from the wind turbine are portrayed as images and fed independently to the proposed network. Results show that the multivariable fault diagnosis scheme diagnoses the most common wind turbine faults and achieves high accuracy.

Simultaneous fault diagnosis of wind turbine using multichannel convolutional neural networks.

Second-order sliding mode fault-tolerant control of heat recovery steam generator boiler in combined cycle power plants

This article is concerned with suppression of nonlinear forced vibration of a single-wall carbon nanotube conveying fluid based on the nonlocal elasticity theory and Euler–Bernoulli beam theory. El...

Moosa Ayati

Papers

Magnetic resonance imaging-based brain tumor grades classification and grading via convolutional neural networks and genetic algorithms

Disturbance-observer-based fuzzy terminal sliding mode control for MIMO uncertain nonlinear systems

Simultaneous fault diagnosis of wind turbine using multichannel convolutional neural networks.

Second-order sliding mode fault-tolerant control of heat recovery steam generator boiler in combined cycle power plants

Stabilization of nonlinear vibrations of carbon nanotubes using observer-based terminal sliding mode control: