Information systems for you.

Cumple con los requisitos exigidos en la materia de Tecnologías de la Información y Comunicación (TIC) para la preparación del General Certificate Secondary Education (GCSE) en el Reino Unido. El objetivo de este libro es el conocimiento de los sistemas de información y el desarrollo de las habilidades en este área. Se divide en dos secciones: la primera parte, del capítulo uno al veintiséis abarca la parte teórica del programa: definición, características y componentes de los sistemas de información, hardware, software, sistemas de seguridad, bases de datos, transferencia de datos y sus aplicaciones en distintos sectores (educación, salud, oficinas), internet. En la segunda parte, de los capítulos veintisiete al treinta y cuatro, hay tareas prácticas con ejercicios sobre programas de procesamiento de textos, hojas de cálculo, paquetes gráficos, autoedición. Va acompañado del libro del profesor.

Information systems for you. Teacher support pack.

Este recurso para el profesor ayuda en la preparación de clases, ofrece ideas para lecciones y actividades basadas en el libro del alumno, así como, material diseñado para maximizar la utilidad del libro del alumno y que, además, puede ser fotocopiado. Cumple con los requisitos exigidos en la materia de Tecnologías de la Información y Comunicación (TIC) para la preparación del General Certificate Secondary Education (GCSE) en el Reino Unido.

Database Engines for Geographical Information Systems

Our ability to identify, acquire, store, enquire on and analyse data is increasing as never before, especially in the GIS field. Technologies are becoming available to manage a wider variety of data and to make intelligent inferences on that data. The mainstream arrival of large-scale database engines is not far away. The experience of using the first such products tells us that they will radically change data management in the GIS field.

Parallel genetic algorithms for the tuning of a fuzzy AQM controller

This paper presents the results of the application of a parallel Genetic Algorithm (GA) in order to design a Fuzzy Proportional Integral (FPI) controller for active queue management on Internet routers. The Active Queue Management (AQM) policies are those policies of router queue management that allow the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. Two different parallel implementations of the genetic algorithm are adopted to determine an optimal configuration of the FPI controller parameters. Finally, the results of several experiments carried out on a forty nodes cluster of workstations are presented.

Implementing a generic systolic array for genetic algorithms

We have designed a highly parallel design for a simple genetic algorithm using a pipeline of systolic arrays. The systolic design provides high throughput and unidirectional pipelining by exploiting the implicit parallelism in the genetic operators. The design is significant because, unlike other hardware genetic algorithms, it is independent of both the fitness function and the particular chromosome length used in a problem. We have designed and simulated a version of the mutation array using Xilinix FPGA tools to investigate the feasibility of hardware implementation. A simple 5-chromosome mutation array occupies 195 CLBs and is capable of performing more than one million mutations per second. I. Introduction Genetic algorithms (GAs) are established search and optimization techniques which have been applied to a range of engineering and applied problems with considerable success [1]. They operate by maintaining a population of trial solutions encoded, using a suitable encoding scheme.

Systolic random number generation for genetic algorithms

A parallel hardware random number generator for use with a VLSI genetic algorithm processing device is proposed. The design uses an systolic array of mixed congruential random number generators. The generators are constantly reseeded with the outputs of the proceeding generators to avoid significant biasing of the randomness of the array which would result in longer times for the algorithm to converge to a solution. 1 Introduction In recent years there has been a growing interest in developing hardware genetic algorithm devices [1, 2, 3]. A genetic algorithm (GA) is a stochastic search and optimization technique which attempts to capture the power of natural selection by evolving a population of candidate solutions by a process of selection and reproduction [4]. In keeping with the evolutionary analogy, the solutions are called chromosomes with each chromosome containing a number of genes. Chromosomes are commonly simple binary strings, the bits being the genes.

Singular vector ensemble forecasting systems and the prediction of flow dependent uncertainty

The ECMWF ensemble weather forecasts are generated by perturbing the initial conditions of the forecast using a subset of the singular vectors of the linearised propagator. Previous results show that when creating probabilistic forecasts from this ensemble better forecasts are obtained if the mean of the spread and the variability of the spread are calibrated separately. We show results from a simple linear model that suggest that this may be a generic property for all singular vector based ensemble forecasting systems based on only a subset of the full set of singular vectors.