Diseño y cálculo de una nave industrial para instalación de cogeneración

Diseño y cálculo de una nave industrial para la posterior instalación de una planta de cogeneración.

Nave industrial para troquelería

Diseño y cálculo de una nave industrial destinada a ser una troquelería.

Learning and using taxonomies for visual and olfactory classification

Humans are able of distinguishing more than 5000 visual categories even in complex environments using a variety of different visual systems all working in tandem. We seem to be capable of distinguishing thousands of different odors as well. In the machine learning community, many commonly used multi-class classifiers do not scale well to such large numbers of categories. This thesis demonstrates a method of automatically creating application-specific taxonomies to aid in scaling classification algorithms to more than 100 cate- gories using both visual and olfactory data. The visual data consists of images collected online and pollen slides scanned under a microscope. The olfactory data was acquired by constructing a small portable sniffing apparatus which draws air over 10 carbon black polymer composite sensors. We investigate performance when classifying 256 visual categories, 8 or more species of pollen and 130 olfactory categories sampled from common household items and a standardized scratch-and-sniff test. Taxonomies are employed in a divide-and-conquer classification framework which improves classification time while allowing the end user to trade performance for specificity as needed. Before classification can even take place, the pollen counter and electronic nose must filter out a high volume of background “clutter” to detect the categories of interest. In the case of pollen this is done with an efficient cascade of classifiers that rule out most non-pollen before invoking slower multi-class classifiers. In the case of the electronic nose, much of the extraneous noise encountered in outdoor environments can be filtered using a sniffing strategy which preferentially samples the visensor response at frequencies that are relatively immune to background contributions from ambient water vapor. This combination of efficient background rejection with scalable classification algorithms is tested in detail for three separate projects: 1) the Caltech-256 Image Dataset, 2) the Caltech Automated Pollen Identification and Counting System (CAPICS) and 3) a portable electronic nose specially constructed for outdoor use.

Carbon leakage and the future of Old Industrial Regions

4 p.

Economic Valuation of Ecosystem Services: Conflicts in Classification

4 p.

Carbon leakage and the future of Old Industrial Regions after Copenhagen

35 p.

Análisis y estudio técnico de una instalación industrial para la fabricación de tubos de acero sin costura

[ES]En este trabajo se analiza el proceso de fabricación de tubos de acero sin soldadura en la planta de Tubos Reunido Industrial (en lo sucesivo TRI) en la localidad alavesa de Amurrio. Además, se acompaña el análisis con puntualizaciones sobre las alternativas aplicables en cada paso del proceso y la conveniencia de aplicarlas en la planta estudiada. De esta manera se realiza un estudio de los procesos y equipos requeridos para los distintos pasos que se dan para fabricar tubos de acero sin soldadura de gran calidad a partir de chatarra de acero. Así mismo, dada la importancia de la calidad y el medio ambiente en la estrategia de TRI, se aporta también en este trabajo un resumen de los métodos utilizados en estas áreas.

Monitoring and classification of lakes in Finland

In Finland, as in other member countries of the European Union, preparations for implementing the EC Water Framework Directive (WFD) have begun. The article describes the current monitoring and classification strategies for Finnish Lakes.