Destination image of Girona: an online text-mining approach

The main objective of this Master Thesis is to discover more about Girona’s image as a tourism destination from different agents’ perspective and to study its differences on promotion or opinions. In order to meet this objective, three components of Girona’s destination image will be studied: attribute-based component, the holistic component, and the affective component. It is true that a lot of research has been done about tourism destination image, but it is less when we are talking about the destination of Girona. Some studies have already focused on Girona as a tourist destination, but they used a different type of sample and different methodological steps. This study is new among destination studies in the sense that it is based only on textual online data and it follows a methodology based on text-miming. Text-mining is a kind of methodology that allows people extract relevant information from texts. Also, after this information is extracted by this methodology, some statistical multivariate analyses are done with the aim of discovering more about Girona’s tourism image

Nasopalatine duct cyst: report of 22 cases and review of the literature

Objectives: Nasopalatine duct cysts (NPDCs) are the most common developmental, epithelial and non-odontogenic cysts of the maxillae. The present study describes the clinicopathological characteristics of 22 NPDCs and discusses their etiology, incidence, treatment and prognosis, with a review of the literature on the subject. Study design: A retrospective observational study was made comprising a period of 36 years (1970-2006), and yielding a series of 22 patients with histopathological confirmation of NPDC. Surgical treatment was carried out under local anesthesia and comprised the dissection and removal of the cyst adopting a usually palatine approach, with the preparation of an enveloping flap from 1.4 to 2.4. Results: No statistically significant correlation was observed between the size of the lesion and patient age, although the size of the cyst differed according to patient gender, with a mean NPDC diameter of 16 mm in males and 12 mm in females. In no case did we observe root reabsorption or loss of vitality of the upper incisors following surgery. The X-ray image was rounded in 15 cases and heart-shaped in the remaining 7 cases. In the majority of cases panoramic X-rays and periapical and occlusal X-rays sufficed to identify the lesion, though computed tomography was used in cases of doubt. Conclusions: The etiology of NPDC is unclear. Simple surgical resection is recommended, followed by clinical and radiological control to ensure correct resolution of the case.

Corruption in building the image of politics in television news broadcasts

This work analyses the political news of eight Spanish television channels in order to see what image is built of politics, and particularly how the news of corruption affects the image of politics in Spanish news broadcasts. Different cases of corruption such as Gürtel, Palma Arena and those associated with judge Baltasar Garzón in his final stage in office, occupy part of the study. A new methodology is therefore proposed that enables the quality of the political information emitted from inside and outside the political content of the news programmes to be observed. Particular attention is paid to the news broadcasts of Televisión Española and Cuatro as those which offer a more balanced view of politics, and channels such as La Sexta, which give priority to a narrative construction of politics in the news programmes around causes of corruption.

Hepatitis G virus infection in primary Sjögren's syndrome: analysis in a series of 100 patients.

OBJECTIVE To determine the prevalence and clinical significance of hepatitis G virus (HGV) infection in a large cohort of patients with primary Sjögren¿s syndrome (SS). PATIENTS AND METHODS The study included 100 consecutive patients (92 female and eight male), with a mean age of 62 years (range 31¿80) that were prospectively visited in our unit. All patients fulfilled the European Community criteria for SS and underwent a complete history, physical examination, as well as biochemical and immunological evaluation for liver disease. Two hundred volunteer blood donors were also studied. The presence of HGV-RNA was investigated in the serum of all patients and donors. Aditionally, HBsAg and antibodies to hepatitis C virus were determined. RESULTS Four patients (4%) and six volunteer blood donors (3%) presented HGV-RNA sequences in serum. HGV infection was associated with biochemical signs of liver involvement in two (50%) patients. When compared with primary SS patients without HGV infection, no significant differences were found in terms of clinical or immunological features. HCV coinfection occurs in one (25%) of the four patients with HGV infection. CONCLUSION The prevalence of HGV infection in patients with primary SS is low in the geographical area of the study and HCV coinfection is very uncommon. HGV infection alone does not seen to be an important cause of chronic liver injury in the patients with primary SS in this area.

Recruitment advertising and corporate image : The HRM-marketing interface

Extended abstract.

Subjectively adapted high capacity lossless image data hiding based on prediction errors

This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.

Lossless Image Data Embedding in Plain Areas

This letter presents a lossless data hiding scheme for digital images which uses an edge detector to locate plain areas for embedding. The proposed method takes advantage of the well-known gradient adjacent prediction utilized in image coding. In the suggested scheme, prediction errors and edge values are first computed and then, excluding the edge pixels, prediction error values are slightly modified through shifting the prediction errors to embed data. The aim of proposed scheme is to decrease the amount of modified pixels to improve transparency by keeping edge pixel values of the image. The experimental results have demonstrated that the proposed method is capable of hiding more secret data than the known techniques at the same PSNR, thus proving that using edge detector to locate plain areas for lossless data embedding can enhance the performance in terms of data embedding rate versus the PSNR of marked images with respect to original image.

Threading libraries performance when applied to image acquisition and processing in a forensic application

Peer-reviewed

InserQual: una eina per a la millora de la qualitat en l'acompanyament a la inserció laboral

InserQual és un protocol nascut al tercer sector que garanteix a les entitats la quali tat del procés d'acompanyament a la inserció laboral. Les enlitats ques' hi dediquen acostumen a treballara partir de l' ilinerari lineal class ic,queconsidera la inserciócom un procés lineal i ordenat que va de I' atur a I'ocupació. InserQual reformula aquest itinerari aportant la imatge de la rotonda. Aquesta aporta a I' itinerari un valor afegitde fl ex ibilitat i adequació a les necessitats de cada usuari/aria. LnserQual és, perlant, unaeina útil i propera, específica per a entitats dedicades a la inserció laboral de persones amb dificultats i que aporta un seguit d' actuacions molt concretes, pero flexibles, que permeten als professionals millorar en la seva intervenció del dia a dia.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

Transketolase-like 1 expression is modulated during Colorectal cancer progression and metastasis formation

Background Transketolase-like 1 (TKTL1) induces glucose degradation through anaerobic pathways, even in presence of oxygen, favoring the malignant aerobic glycolytic phenotype characteristic of tumor cells. As TKTL1 appears to be a valid biomarker for cancer prognosis, the aim of the current study was to correlate its expression with tumor stage, probability of tumor recurrence and survival, in a series of colorectal cancer patients. Methodolody/Principal Findings Tumor tissues from 63 patients diagnosed with colorectal cancer at different stages of progression were analyzed for TKTL1 by immunohistochemistry. Staining was quantified by computational image analysis, and correlations between enzyme expression, local growth, lymph-node involvement and metastasis were assessed. The highest values for TKTL1 expression were detected in the group of stage III tumors, which showed significant differences from the other groups (Kruskal-Wallis test, P = 0.000008). Deeper analyses of T, N and M classifications revealed a weak correlation between local tumor growth and enzyme expression (Mann-Whitney test, P = 0.029), a significant association of the enzyme expression with lymph-node involvement (Mann-Whitney test, P = 0.0014) and a significant decrease in TKTL1 expression associated with metastasis (Mann-Whitney test, P = 0.0004). Conclusions/Significance To our knowledge, few studies have explored the association between variations in TKTL1 expression in the primary tumor and metastasis formation. Here we report downregulation of enzyme expression when metastasis appears, and a correlation between enzyme expression and regional lymph-node involvement in colon cancer. This finding may improve our understanding of metastasis and lead to new and more efficient therapies against cancer.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Variabilidad espacial del arroz como cultivo indicador de salinidad en regadíos del valle del Ebro a partir de series temporales en imágenes Landsat TM

El presente trabajo pretende la caracterización de la distribución espacial típica del cultivo de arroz en regadíos del valle del Ebro, donde la presencia del cultivo está ligada a la existencia de suelos salino-sódicos. Esta caracterización ha de permitir identificar las áreas donde es típica la presencia del cultivo año tras año y las áreas donde es frecuente su fluctuación debido tanto a condiciones variables de salinidad del suelo como a variabilidad en las condiciones de mercado. Para ello se ha recurrido al análisis de una serie temporal de mapas de cultivos (7 años) derivados de la clasificación supervisada de imágenes Landsat TM. La determinación de las áreas típicas y de fluctuación del cultivo de arroz se hace entonces a partir del análisis estadístico de clases, y mediante superposición espacial de coberturas en un entorno SIG-Raster.