Strategies for teaching students with special needs : methods and techniques for classroom instruction.

El objetivo de este manual es que orientar a los maestros de primaria en centros de integración que tienen en su clase niños con necesidades especiales. Las estrategias presentadas intencionadamente borran la distinción entre y dentro de las categorías de niños con necesidades especiales y hacen hincapié en el acto de aprender de todos los niños. Tanto las estrategias como las prácticas educativas son reales, con énfasis sobre las orientaciones de lo que se debe hacer para satisfacer las necesidades de veinticinco estudiantes muy distintos. La atención se centra en la evaluación de lectura y métodos de lectura, el lenguaje, las matemáticas y las ideas de los aspectos sociales de integración.

Planning a system of regions: methods and techniques of interregional planning

Includes bibliography

Plant food supplement (PFS) market structure in EC Member States, methods and techniques for the assessment of individual PFS intake

The popularity of herbal products, especially plant food supplements (PFS) and herbal medicine is on the rise in Europe and other parts of the world, with increased use in the general population as well as among specific subgroups encompassing children, women or those suffering from diseases such as cancer. The aim of this paper is to examine the PFS market structures in European Community (EC) Member States as well as to examine issues addressing methodologies and consumption data relating to PFS use in Europe. A revision of recent reports on market data, trends and main distribution channels, in addition an example of the consumption of PFS in Spain, is presented. An overview of the methods and administration techniques used...

Methods and Techniques for the Generation and Eficient Exploitation of RDB2RDF Mappings

RDB to RDF Mapping Language (R2RML) es una recomendación del W3C que permite especificar reglas para transformar bases de datos relacionales a RDF. Estos datos en RDF se pueden materializar y almacenar en un sistema gestor de tripletas RDF (normalmente conocidos con el nombre triple store), en el cual se pueden evaluar consultas SPARQL. Sin embargo, hay casos en los cuales la materialización no es adecuada o posible, por ejemplo, cuando la base de datos se actualiza frecuentemente. En estos casos, lo mejor es considerar los datos en RDF como datos virtuales, de tal manera que las consultas SPARQL anteriormente mencionadas se traduzcan a consultas SQL que se pueden evaluar sobre los sistemas gestores de bases de datos relacionales (SGBD) originales. Para esta traducción se tienen en cuenta los mapeos R2RML. La primera parte de esta tesis se centra en la traducción de consultas. Se propone una formalización de la traducción de SPARQL a SQL utilizando mapeos R2RML. Además se proponen varias técnicas de optimización para generar consultas SQL que son más eficientes cuando son evaluadas en sistemas gestores de bases de datos relacionales. Este enfoque se evalúa mediante un benchmark sintético y varios casos reales. Otra recomendación relacionada con R2RML es la conocida como Direct Mapping (DM), que establece reglas fijas para la transformación de datos relacionales a RDF. A pesar de que ambas recomendaciones se publicaron al mismo tiempo, en septiembre de 2012, todavía no se ha realizado un estudio formal sobre la relación entre ellas. Por tanto, la segunda parte de esta tesis se centra en el estudio de la relación entre R2RML y DM. Se divide este estudio en dos partes: de R2RML a DM, y de DM a R2RML. En el primer caso, se estudia un fragmento de R2RML que tiene la misma expresividad que DM. En el segundo caso, se representan las reglas de DM como mapeos R2RML, y también se añade la semántica implícita (relaciones de subclase, 1-N y M-N) que se puede encontrar codificada en la base de datos. Esta tesis muestra que es posible usar R2RML en casos reales, sin necesidad de realizar materializaciones de los datos, puesto que las consultas SQL generadas son suficientemente eficientes cuando son evaluadas en el sistema gestor de base de datos relacional. Asimismo, esta tesis profundiza en el entendimiento de la relación existente entre las dos recomendaciones del W3C, algo que no había sido estudiado con anterioridad. ABSTRACT. RDB to RDF Mapping Language (R2RML) is a W3C recommendation that allows specifying rules for transforming relational databases into RDF. This RDF data can be materialized and stored in a triple store, so that SPARQL queries can be evaluated by the triple store. However, there are several cases where materialization is not adequate or possible, for example, if the underlying relational database is updated frequently. In those cases, RDF data is better kept virtual, and hence SPARQL queries over it have to be translated into SQL queries to the underlying relational database system considering that the translation process has to take into account the specified R2RML mappings. The first part of this thesis focuses on query translation. We discuss the formalization of the translation from SPARQL to SQL queries that takes into account R2RML mappings. Furthermore, we propose several optimization techniques so that the translation procedure generates SQL queries that can be evaluated more efficiently over the underlying databases. We evaluate our approach using a synthetic benchmark and several real cases, and show positive results that we obtained. Direct Mapping (DM) is another W3C recommendation for the generation of RDF data from relational databases. While R2RML allows users to specify their own transformation rules, DM establishes fixed transformation rules. Although both recommendations were published at the same time, September 2012, there has not been any study regarding the relationship between them. The second part of this thesis focuses on the study of the relationship between R2RML and DM. We divide this study into two directions: from R2RML to DM, and from DM to R2RML. From R2RML to DM, we study a fragment of R2RML having the same expressive power than DM. From DM to R2RML, we represent DM transformation rules as R2RML mappings, and also add the implicit semantics encoded in databases, such as subclass, 1-N and N-N relationships. This thesis shows that by formalizing and optimizing R2RML-based SPARQL to SQL query translation, it is possible to use R2RML engines in real cases as the resulting SQL is efficient enough to be evaluated by the underlying relational databases. In addition to that, this thesis facilitates the understanding of bidirectional relationship between the two W3C recommendations, something that had not been studied before.

Methods and Techniques for Segmentation of Consumers in Social Media

Los medios sociales han revolucionado la manera en la que los consumidores se relacionan entre sí y con las marcas. Las opiniones publicadas en dichos medios tienen un poder de influencia en las decisiones de compra tan importante como las campañas de publicidad. En consecuencia, los profesionales del marketing cada vez dedican mayores esfuerzos e inversión a la obtención de indicadores que permitan medir el estado de salud de las marcas a partir de los contenidos digitales generados por sus consumidores. Dada la naturaleza no estructurada de los contenidos publicados en los medios sociales, la tecnología usada para procesar dichos contenidos ha menudo implementa técnicas de Inteligencia Artificial, tales como algoritmos de procesamiento de lenguaje natural, aprendizaje automático y análisis semántico. Esta tesis, contribuye al estado de la cuestión, con un modelo que permite estructurar e integrar la información publicada en medios sociales, y una serie de técnicas cuyos objetivos son la identificación de consumidores, así como la segmentación psicográfica y sociodemográfica de los mismos. La técnica de identificación de consumidores se basa en la huella digital de los dispositivos que utilizan para navegar por la Web y es tolerante a los cambios que se producen con frecuencia en dicha huella digital. Las técnicas de segmentación psicográfica descritas obtienen la posición en el embudo de compra de los consumidores y permiten clasificar las opiniones en función de una serie de atributos de marketing. Finalmente, las técnicas de segmentación sociodemográfica permiten obtener el lugar de residencia y el género de los consumidores. ABSTRACT Social media has revolutionised the way in which consumers relate to each other and with brands. The opinions published in social media have a power of influencing purchase decisions as important as advertising campaigns. Consequently, marketers are increasing efforts and investments for obtaining indicators to measure brand health from the digital content generated by consumers. Given the unstructured nature of social media contents, the technology used for processing such contents often implements Artificial Intelligence techniques, such as natural language processing, machine learning and semantic analysis algorithms. This thesis contributes to the State of the Art, with a model for structuring and integrating the information posted on social media, and a number of techniques whose objectives are the identification of consumers, as well as their socio-demographic and psychographic segmentation. The consumer identification technique is based on the fingerprint of the devices they use to surf the Web and is tolerant to the changes that occur frequently in such fingerprint. The psychographic profiling techniques described infer the position of consumer in the purchase funnel, and allow to classify the opinions based on a series of marketing attributes. Finally, the socio-demographic profiling techniques allow to obtain the residence and gender of consumers.

Development of methods and techniques for final treatment of combined municipal and textile wastewater, including sludge utilization and disposal /

Issued Dec. 1979.

Methods and techniques for gouache painting.

Mode of access: Internet.

DEVELOPMENT OF CURRENT-BASED MICROSCOPIC DEFECT ANALYSIS-METHODS AND ASSOCIATED OPTICAL FILLING TECHNIQUES FOR THE INVESTIGATION ON HIGHLY IRRADIATED HIGH-RESISTIVITY SILICON DETECTORS

Current based microscopic defect analysis methods such as current deep level transient spectroscopy (I-DLTS) and thermally stimulated current (TSC) have been further developed in accordance with the need for the defect analysis of highly irradiated (Phi(n) > 10(13) n/cm(2)) high resistivity silicon detectors. The new I-DLTS/TSC system has a temperature range of 8 K less than or equal to T less than or equal to 450 K and a high sensitivity that can detect a defect concentration of less than 10(10)/cm(3) (background noise as low as 10 fA). A new filling method using different wavelength laser illumination has been applied, which is more efficient and suitable than the traditional voltage pulse filling. It has been found that the filling of a defect level depends on such factors as the total concentration of free carriers generated or injected, the penetration length of the laser (laser wavelength), the temperature at which the filling is taking place, as well as the decay time after the filling (but before the measurement). The mechanism of the defect filling can be explained by the competition between trapping and detrapping of defect levels, possible capture cross section temperature dependence, and interaction among various defect levels in terms of charge transferring. Optimum defect filling conditions have been suggested for highly irradiated high resistivity silicon detectors.

Bibliographic analysis of persuasive systems: techniques, methods and domains of application

This paper presents findings of our study on peer-reviewed papers published in the International Conference on Persuasive Technology from 2006 to 2010. The study indicated that out of 44 systems reviewed, 23 were reported to be successful, 2 to be unsuccessful and 19 did not specify whether or not it was successful. 56 different techniques were mentioned and it was observed that most designers use ad hoc definitions for techniques or methods used in design. Hence we propose the need for research to establish unambiguous definitions of techniques and methods in the field.

A Study of XML models for data mining : representations, methods, and issues

With the increasing number of XML documents in varied domains, it has become essential to identify ways of finding interesting information from these documents. Data mining techniques were used to derive this interesting information. Mining on XML documents is impacted by its model due to the semi-structured nature of these documents. Hence, in this chapter we present an overview of the various models of XML documents, how these models were used for mining and some of the issues and challenges in these models. In addition, this chapter also provides some insights into the future models of XML documents for effectively capturing the two important features namely structure and content of XML documents for mining.

Quantitative evaluation of matching methods and validity measures for stereo vision

The authors present a qualitative and quantitative comparison of various similarity measures that form the kernel of common area-based stereo-matching systems. The authors compare classical difference and correlation measures as well as nonparametric measures based on the rank and census transforms for a number of outdoor images. For robotic applications, important considerations include robustness to image defects such as intensity variation and noise, the number of false matches, and computational complexity. In the absence of ground truth data, the authors compare the matching techniques based on the percentage of matches that pass the left-right consistency test. The authors also evaluate the discriminatory power of several match validity measures that are reported in the literature for eliminating false matches and for estimating match confidence. For guidance applications, it is essential to have and estimate of confidence in the three-dimensional points generated by stereo vision. Finally, a new validity measure, the rank constraint, is introduced that is capable of resolving ambiguous matches for rank transform-based matching.

Nanostructured copper oxide semiconductors : a perspective on materials, synthesis methods and applications

The oxides of copper (CuxO) are fascinating materials due to their remarkable optical, electrical, thermal and magnetic properties. Nanostructuring of CuxO can further enhance the performance of this important functional material and provide it with unique properties that do not exist in its bulk form. Three distinctly different phases of CuxO, mainly CuO, Cu2O and Cu4O3, can be prepared by numerous synthesis techniques including, vapour deposition and liquid phase chemical methods. In this article, we present a review of nanostructured CuxO focusing on their material properties, methods of synthesis and an overview of various applications that have been associated with nanostructured CuxO.