MIRACLE at GeoCLEF Query Parsing 2007: Extraction and Classification of Geographical Information

This paper describes the participation of MIRACLE research consortium at the Query Parsing task of GeoCLEF 2007. Our system is composed of three main modules. First, the Named Geo-entity Identifier, whose objective is to perform the geo-entity identification and tagging, i.e., to extract the “where” component of the geographical query, should there be any. This module is based on a gazetteer built up from the Geonames geographical database and carries out a sequential process in three steps that consist on geo-entity recognition, geo-entity selection and query tagging. Then, the Query Analyzer parses this tagged query to identify the “what” and “geo-relation” components by means of a rule-based grammar. Finally, a two-level multiclassifier first decides whether the query is indeed a geographical query and, should it be positive, then determines the query type according to the type of information that the user is supposed to be looking for: map, yellow page or information. According to a strict evaluation criterion where a match should have all fields correct, our system reaches a precision value of 42.8% and a recall of 56.6% and our submission is ranked 1st out of 6 participants in the task. A detailed evaluation of the confusion matrixes reveal that some extra effort must be invested in “user-oriented” disambiguation techniques to improve the first level binary classifier for detecting geographical queries, as it is a key component to eliminate many false-positives

Report of MIRACLE team for Geographical IR in CLEF 2006

The main objective of the designed experiments is testing the effects of geographical information retrieval from documents that contain geographical tags. In the designed experiments we try to isolate geographical retrieval from textual retrieval replacing all geo-entity textual references from topics with associated tags and splitting the retrieval process in two phases: textual retrieval from the textual part of the topic without geo-entity references and geographical retrieval from the tagged text generated by the topic tagger. Textual and geographical results are combined applying different techniques: union, intersection, difference, and external join based. Our geographic information retrieval system consists of a set of basics components organized in two categories: (i) linguistic tools oriented to textual analysis and retrieval and (ii) resources and tools oriented to geographical analysis. These tools are combined to carry out the different phases of the system: (i) documents and topics analysis, (ii) relevant documents retrieval and (iii) result combination. If we compare the results achieved to the last campaign’s results, we can assert that mean average precision gets worse when the textual geo-entity references are replaced with geographical tags. Part of this worsening is due to our experiments return cero pertinent documents if no documents satisfy de geographical sub-query. But if we only analyze the results of queries that satisfied both textual and geographical terms, we observe that the designed experiments recover pertinent documents quickly, improving R-Precision values. We conclude that the developed geographical information retrieval system is very sensible to textual georeference and therefore it is necessary to improve the name entity recognition module

MIRACLE at ImageCLEFanot 2007: Machine Learning Experiments on Medical Image Annotation

This paper describes the participation of MIRACLE research consortium at the ImageCLEF Medical Image Annotation task of ImageCLEF 2007. Our areas of expertise do not include image analysis, thus we approach this task as a machine-learning problem, regardless of the domain. FIRE is used as a black-box algorithm to extract different groups of image features that are later used for training different classifiers in order to predict the IRMA code. Three types of classifiers are built. The first type is a single classifier that predicts the complete IRMA code. The second type is a two level classifier composed of four classifiers that individually predict each axis of the IRMA code. The third type is similar to the second one but predicts a combined pair of axes. The main idea behind the definition of our experiments is to evaluate whether an axis-by-axis prediction is better than a prediction by pairs of axes or the complete code, or vice versa. We submitted 30 experiments to be evaluated and results are disappointing compared to other groups. However, the main conclusion that can be drawn from the experiments is that, irrespective of the selected image features, the axis-by-axis prediction achieves more accurate results not only than the prediction of a combined pair of axes but also, in turn, than the prediction of the complete IRMA code. In addition, data normalization seems to improve the predictions and vector-based features are preferred over histogram-based ones

Study of alkaline hydrothermal activation of belite cements by thermal analysis

The effect of alkaline hydrothermal activation of class-C fly ash belite cement was studied using thermal analysis (TG/DTG) by determining the increase in the combined water during a period of hydration of 180 days. The results were compared with those obtained for a belite cement hydrothermally activated in water. The two belite cements were fabricated via the hydrothermal-calcination route of class-C fly ash in 1 M NaOH solution (FABC-2-N) or demineralised water (FABC-2-W). From the results, the effect of the alkaline hydrothermal activation of belite cement (FABC-2-N) was clearly differentiated, mainly at early ages of hydration, for which the increase in the combined water was markedly higher than that of the belite cement that was hydrothermally activated in water. Important direct quantitative correlations were obtained among physicochemical parameters, such as the combined water, the BET surface area, the volume of nano-pores, and macro structural engineering properties such as the compressive mechanical strength

MIRACLE at ImageCLEFannot 2008: Classification of Image Features for Medical Image Annotation

This paper describes the participation of MIRACLE research consortium at the ImageCLEF Medical Image Annotation task of ImageCLEF 2008. A lot of effort was invested this year to develop our own image analysis system, based on MATLAB, to be used in our experiments. This system extracts a variety of global and local features including histogram, image statistics, Gabor features, fractal dimension, DCT and DWT coefficients, Tamura features and coocurrency matrix statistics. Then a k-Nearest Neighbour algorithm analyzes the extracted image feature vectors to determine the IRMA code associated to a given image. The focus of our experiments is mainly to test and evaluate this system in-depth and to make a comparison among diverse configuration parameters such as number of images for the relevance feedback to use in the classification module

Report of MIRACLE team for the Ad-Hoc track in CLEF 2007

This paper presents the 2007 MIRACLE’s team approach to the AdHoc Information Retrieval track. The work carried out for this campaign has been reduced to monolingual experiments, in the standard and in the robust tracks. No new approaches have been attempted in this campaign, following the procedures established in our participation in previous campaigns. For this campaign, runs were submitted for the following languages and tracks: - Monolingual: Bulgarian, Hungarian, and Czech. - Robust monolingual: French, English and Portuguese. There is still some room for improvement around multilingual named entities recognition

Síntesis hidrotermal de zeolita a partir de ceniza volante tipo F: influencia de la temperatura = Influence of temperature of alkaline hydrothermal treatment on the zeolite conversion of spanish coal class F fly ash

En este trabajo se presenta el papel que juega la temperatura durante el tratamiento hidrotermal en medio alcalino para convertir una ceniza volante de bajo contenido en cal (clase F, según la norma ASTM) en zeolita. Durante este tratamiento a la temperatura de 100 ºC se forma zeolita Na-P1 tipo gismondina (Na6Al6Si10O32.12H2O); al elevar la temperatura a 200 ºC, dicha zeolita se transforma en zeolita analcima C (Na(Si2Al)O6H2O) y en fase sodalita (1.08 Na2O.Al2O3.1.68SiO2.1.8H2O) junto con trazas de tobermorita-11Å (Ca5(OH)2Si6O16.4H2O). A esta temperatura y en estas condiciones se ha conseguido un 100% de reacción. Un estudio equivalente se ha llevado a cabo empleando agua como medio de referencia. La conversión de ceniza volante en zeolita se ha caracterizado mediante técnicas, como difracción de Rayos X (DRX), espectroscopia infrarroja por transformada de Fourier (FTIR) y análisis térmico (TG/ATD); asimismo los cambios en el área superficial se han llevado a cabo mediante la técnica BET-N

Estudio termoanalítico y caracterización de los precipitados obtenidos a partir de soluciones FE (III) por alcalinización en medio homogeneo

Tesis - Universidad Complutense de Madrid, 1981.Depto. de Química AnalíticaFac. de Ciencias QuímicasTRUEProQuestpu

Effect of temperature on the durability of class C fly ash belite cement in simulated radioactive liquid waste: Synergy of chloride and sulphate ions

The durability of class C fly ash belite cement (FABC-2-W) in simulated radioactive liquid waste (SRLW) rich in a mixed sodium chloride and sulphate solution is presented here. The effect of the temperature and potential synergic effect of chloride and sulfate ions are discussed. This study has been carried out according to theKoch–Steinegger test, at the temperature of 20 ◦Cand 40 ◦Cduring a period of 180days. The durability has been evaluated by the changes of the flexural strength of mortar, fabricatedwith this cement, immersed in a simulated radioactive liquid waste rich in sulfate (0.5 M), chloride (0.5M) and sodium (1.5M) ions – catalogued like severely aggressive for the traditional Portland cement – and demineralised water, which was used as reference. The reaction mechanism of sulphate, chloride and sodium ions with the mortar was evaluated by scanning electron microscopy (SEM), porosity and pore-size distribution, and X-ray diffraction (XRD). The results showed that the chloride binding and formation of Friedel’s salt was inhibited by the presence of sulphate. Sulphate ion reacts preferentially with the calcium aluminate hydrates forming non-expansive ettringite which precipitated inside the pores; the microstructure was refined and the mechanical properties enhanced. This process was faster and more marked at 40 ◦C