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

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

Data Mining Practical Machine Learning Tools and Techniques

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

Bidirectional handshaking LSTM for remaining useful life prediction

Condition based maintenance (CBM) is based on collecting observations over time, in order to assess equipment's state, to prevent its failure and to determine the optimal maintenance strategies. In this paper, we derive an optimal CBM replacement policy when the state of equipment is unknown but can be estimated based on observed condition. We use a proportional hazards model (PHM) to represent the system's degradation. Since equipment's state is unknown, the optimization of the optimal maintenance policy is formulated as a partially observed Markov decision process (POMDP), and the problem is solved using dynamic programming. Practical advantages of combining the PHM with the POMDP are shown.

Optimal condition based maintenance with imperfect information and the proportional hazards model

This article proposes a model to calculate the reliability function, and the mean residual (remaining) life of a piece of equipment, when its degradation state is not directly observable. At each observation moment, an indicator of the underlying unobservable degradation state is observed, and the monitoring information is collected. The observation process is due to a condition monitoring system where the obtained information is not perfect. For that reason, the observation process doesn't directly reveal the exact degradation state. To match an indicator's value to the unobservable degradation state, a stochastic relation between them is given by an observation probability matrix. It is assumed that the equipment's unobservable degradation state transition follows a Markov chain, and we model it using a hidden Markov model. The Bayes' rule is used to determine the probability of being in a certain degradation state at each observation moment. Cox's time-dependent proportional hazards model is considered to model the equipment's failure rate. This paper addresses two main problems: the problem of imperfect observations, and the problem of taking into account the whole history of observations. Two numerical examples are presented.

Evaluating the Reliability Function and the Mean Residual Life for Equipment With Unobservable States

With the rise of the Internet of Things (IoT) technology, the number of IoT devices/sensors has increased significantly. It is anticipated that large-scale sensor-based systems will prevail in our societies, calling for novel methodologies to design and operate those new systems. To support the computational demand of real-time delay-sensitive applications of largely distributed IoT devices/sensors, the Cloud is migrating to the edge of the network where resources such as routers, switches, and gateways are being virtualized. The open structural design of IoT architecture and the extensive usage of the paradigm itself cause to encounter conventional security issues for the existing networking technologies. Moreover, cooperation generates challenges as new security challenges can disrupt the systems’ regular functionalities and operations. Furthermore, the commercialization of the IoT has led to several public security concerns including threats of cyber-attacks, privacy issues, and organized crimes. In this paper, we aim to provide guidelines for researchers and practitioners interested in understanding IoT security issues. More specifically, an extensive description of security threats and challenges across the different layers of the architecture of IoT systems is presented. Also, the light will be shed on the solutions and countermeasures proposed in the literature to address such security issues. Finally, an emerging security challenge which has yet to be explained in-depth in previous studies is introduced.

Enforcing security in Internet of Things frameworks: A Systematic Literature Review

This article proposes methods to estimate the parameters of condition monitored equipment whose failure rate follows the Cox's time-dependent Proportional Hazards Model. Due to errors of measurement, of interpretation, or due to limited accuracy of measurement instruments, the observation process is not perfect, and does not directly reveal the exact degradation state. At each observation moment, we observe and collect information about an indicator of the underlying unobservable degradation state. To match the indicator's value to the unobservable degradation state, the stochastic relation between them is given by an observation probability matrix. In this study, we consider the case of imperfect observations, and we assume that the equipment's unobservable degradation state transition follows a Hidden Markov Model. We determine the Probability Density Function of the time to failure, and use the Maximum Likelihood Estimation to estimate the model's parameters. These are the Proportional Hazards', and the Hidden Markov Models' parameters. We study the cases of censored, and uncensored data; and carry out simulation studies to test the accuracy, and the convergence of the estimation methods.

Soumaya Yacout

Papers

Bidirectional handshaking LSTM for remaining useful life prediction

Optimal condition based maintenance with imperfect information and the proportional hazards model

Evaluating the Reliability Function and the Mean Residual Life for Equipment With Unobservable States

Enforcing security in Internet of Things frameworks: A Systematic Literature Review

Parameter Estimation Methods for Condition-Based Maintenance With Indirect Observations