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

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Learning and evolution are two fundamental forms of adaptation. There has been a great interest in combining learning and evolution with artificial neural networks (ANNs) in recent years. This paper: 1) reviews different combinations between ANNs and evolutionary algorithms (EAs), including using EAs to evolve ANN connection weights, architectures, learning rules, and input features; 2) discusses different search operators which have been used in various EAs; and 3) points out possible future research directions. It is shown, through a considerably large literature review, that combinations between ANNs and EAs can lead to significantly better intelligent systems than relying on ANNs or EAs alone.

/pdf/evolving-artificial-neural-networks-4kzrbu7pkn.pdf

Evolving artificial neural networks

List of Figures. List of Tables. Preface. Contributing Authors. Series Foreword. Part I: Foundations. 1. An Introduction to Evolutionary Algorithms J.A. Lozano. 2. An Introduction to Probabilistic Graphical Models P. Larranaga. 3. A Review on Estimation of Distribution Algorithms P. Larranaga. 4. Benefits of Data Clustering in Multimodal Function Optimization via EDAs J.M. Pena, et al. 5. Parallel Estimation of Distribution Algorithms J.A. Lozano, et al. 6. Mathematical Modeling of Discrete Estimation of Distribution Algorithms C. Gonzalez, et al. Part II: Optimization. 7. An Empiricial Comparison of Discrete Estimation of Distribution Algorithms R. Blanco., J.A. Lozano. 8. Results in Function Optimization with EDAs in Continuous Domain E. Bengoetxea, et al. 9. Solving the 0-1 Knapsack Problem with EDAs R. Sagarna, P. Larranaga. 10. Solving the Traveling Salesman Problem with EDAs V. Robles, et al. 11. EDAs Applied to the Job Shop Scheduling Problem J.A. Lozano, A. Mendiburu. 12. Solving Graph Matching with EDAs Using a Permutation-Based Representation E. Bengoetxea, et al. Part III: Machine Learning. 13. Feature Subset Selection by Estimation of Distribution Algorithms I. Inza, et al. 14. Feature Weighting for Nearest Neighbor by EDAs I. Inza, et al. 15. Rule Induction by Estimation of Distribution Algorithms B. Sierra, et al. 16. Partial Abductive Inference in Bayesian Networks: An Empirical Comparison Between GAs and EDAs L.M. de Campos, et al.17. Comparing K-Means, GAs and EDAs in Partitional Clustering J. Roure, et al. 18. Adjusting Weights in Artificial Neural Networks using Evolutionary Algorithms C. Cotta, et al. Index.

Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation

A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

http://ieeexplore.ieee.org/iel2/815/3148/00100651.pdf

Robot vision

This document defines capabilities and operations for subscribing to
content and providing asynchronous notification message delivery on
that content. Notification delivery can occur over a variety of
protocols used commonly in conjunction with YANG, such as NETCONF and
RESTCONF. The capabilities and operations defined in this document
when using in conjunction with draft-ietf-netconf-netconf-event-
notifications are intended to replace RFC 5277.

Subscribing to Event Notifications

Computational intelligence and bioinspired systems : 8th International Work-Conference on Artificial Neural Networks, IWANN 2005, Vilanova i la Geltrú, Barcelona, Spain, June 8-10, 2005 : proceedings

A communication layer is proposed that, besides improving communication performance on clusters of PCs, by reducing the latencies and increasing the bandwidth figures even for short messages, also meets other requirements such as multiprogramming, portability, protection against corrupted programs, reliable message delivery, direct access to the network for all applications, etc. Instead of removing the operating system kernel from the critical path and creating a user-level network interface, our aim was to optimize the operating system support to provide reliable and efficient network software, avoiding the TCP/IP protocol stack. The communication system was tested in a cluster of PCs with Linux OS and interconnected with Fast Ethernet. The performance figures obtained define the best situation that can be attained without modifying the device drivers or using a user-level network interface approach.

An efficient OS support for communication on Linux clusters

Due to the network technology advances, an order-of-magnitude jump has been produced in the network bandwidth. This fact has returned to wake up the interest on protocol offloading, since network communication is a key factor for system performance. Thus, much research work on offloading is been done, particularly on TCP offloading as it has been the main transport protocol for many years, and in fact, it is the most used protocol in the networks. Nevertheless, some recent studies on protocol offloading have produced some controversy about its benefits. This paper describes a model to simulate the protocol offloading by using the simulator Simics. It can be used for a functional system simulation, including the application program, the operating system, the protocol stack and the device drivers, since network-oriented applications require this kind of full-system simulation. Nevertheless, as Simics does not provide a detailed network I/O model, in this paper we describe the way we have overcome this problem.

Modeling Network Behaviour By Full-System Simulation

In this paper, a learning algorithm that leads to an efficient self-organization in a Kohonen Neural Network (KNN) with fixed neighbourhood is presented. This algorithm may be faster than the originally proposed for KNNs, produces in general better covering of the input stimulus space, and can be more easily implemented in hardware due to the fixed neighbourhood it manages.

Alberto Prieto

Papers

Subscribing to Event Notifications

Computational intelligence and bioinspired systems : 8th International Work-Conference on Artificial Neural Networks, IWANN 2005, Vilanova i la Geltrú, Barcelona, Spain, June 8-10, 2005 : proceedings

An efficient OS support for communication on Linux clusters

Modeling Network Behaviour By Full-System Simulation

A Learning Algorithm to Obtain Self-Organizing Maps Using Fixed Neighbourhood Kohonen Networks