Variables efectives de l'empowerment

Aquest treball que porta per títol variables efectives de l’empowerment es el treball investigació del programa de doctorat Interuniversitari en Organització i Administració d’Empreses. El treball està composat per tres parts diferenciades. La primera part del treball consisteix amb el comentari de vint articles relacionats amb la motivació, el downsizing i l’empowerment. Els resums exposats han servit per establir els fonaments teòrics previs al model proposat de variables efectives d’empowerment. La segona part consisteix amb l’elaboració d’un article que resumeix les principals fonts consultades i proposa un model de classificació de les variables que poden contribuir a aconseguir amb èxit un procés d’empowerment. Les variables efectives es poden dividir en variables recíproques, variables unidireccionals, variables compartides i variables reflexives. La tercera part i amb l’objectiu de comprovar la validesa de model s’ha desenvolupat un qüestionari per mesurar l’estat de les variables anomenades efectives d’empowerment i la seva contribució amb l’èxit del procés. Es descriu l’eina desenvolupada, el tractament i la representació de les dades obtingudes. Finalment es pot trobar els primers resultats de la prova pilot realitzada per provar el model conceptual proposat.

Nous perfils professionals de l'actual panorama informatiu audiovisual i multimèdia de Catalunya

Aquest treball forma part de una recerca –finançada pel Consell de l’Audiovisual de Catalunya- dedicada a l’anàlisi de les conseqüències dels processos de digitalització en els mitjans de comunicació de Catalunya (Espanya). El document presenta les transformacions que han afectat al periodista, especialment les noves tasques i funcions. Després d’una introducció dedicada al marc teòric i a la metodologia de la recerca, el document explica les tendències principals observades en les ràdios, emissores de televisió, agències de noticies i mitjans en línia de Catalunya. El document també presenta una sèrie de reflexions sobre la polivalència, la re-qualificació i altres processos que afecten als professionals de la informació. Finalment, es proposa una classificació de les formes que assumeix la polivalència en els mitjans.

Generic object classification for autonomous robots

Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.

A classification, up to hyperbolicity, of groups given by 2 generators and one relator of length 8

"Vegeu el resum a l'inici del document del fitxer adjunt."

Combining classification techniques to define topo-climatic landscapes

Landscape classification tackles issues related to the representation and analysis of continuous and variable ecological data. In this study, a methodology is created in order to define topo-climatic landscapes (TCL) in the north-west of Catalonia (north-east of the Iberian Peninsula). TCLs relate the ecological behaviour of a landscape in terms of topography, physiognomy and climate, which compound the main drivers of an ecosystem. Selected variables are derived from different sources such as remote sensing and climatic atlas. The proposed methodology combines unsupervised interative cluster classification with a supervised fuzzy classification. As a result, 28 TCLs have been found for the study area which may be differentiated in terms of vegetation physiognomy and vegetation altitudinal range type. Furthermore a hierarchy among TCLs is set, enabling the merging of clusters and allowing for changes of scale. Through the topo-climatic landscape map, managers may identify patches with similar environmental conditions and asses at the same time the uncertainty involved.

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

Genetic diversity and differentiation processes in the ploidy series of Olea europaea L.: a multiscale approach from subspecies to insular populations.

Geographical isolation and polyploidization are central concepts in plant evolution. The hierarchical organization of archipelagos in this study provides a framework for testing the evolutionary consequences for polyploid taxa and populations occurring in isolation. Using amplified fragment length polymorphism and simple sequence repeat markers, we determined the genetic diversity and differentiation patterns at three levels of geographical isolation in Olea europaea: mainland-archipelagos, islands within an archipelago, and populations within an island. At the subspecies scale, the hexaploid ssp. maroccana (southwest Morocco) exhibited higher genetic diversity than the insular counterparts. In contrast, the tetraploid ssp. cerasiformis (Madeira) displayed values similar to those obtained for the diploid ssp. guanchica (Canary Islands). Geographical isolation was associated with a high genetic differentiation at this scale. In the Canarian archipelago, the stepping-stone model of differentiation suggested in a previous study was partially supported. Within the western lineage, an east-to-west differentiation pattern was confirmed. Conversely, the easternmost populations were more related to the mainland ssp. europaea than to the western guanchica lineage. Genetic diversity across the Canarian archipelago was significantly correlated with the date of the last volcanic activity in the area/island where each population occurs. At the island scale, this pattern was not confirmed in older islands (Tenerife and Madeira), where populations were genetically homogeneous. In contrast, founder effects resulted in low genetic diversity and marked genetic differentiation among populations of the youngest island, La Palma.

Classificação de fêmeas de Stomoxys calcitrans (L. ) (Diptera: Muscidae), de acordo com a idade fisiológica

With the purpose of maiking easier the determination of the physiological age of Stomosys calcitrans population, a classification based on the oocitary developtment and number of ovipositions was proposed. Female were reared under laboratory conditions, in individual cages and maintained in the presence of male for copulation. On the proper time, ovary and oviduct were removed and the stage of development was observed. Adult female were classified as: 1-New emerged female, 2 - Young nuliparous female, 3 - Old nuliparous female, 4 - Uniparousfemale, 5 - Two or three ovipositions times female, and 6 - Multiparous female.

Actualités diagnostiques et thérapeutiques dans le domaine de l'encéphalopathie hépatique [Hepatic encephalopathy: recent developments].

Hepatic encephalopathy is a neurological syndrome occurring in patients with liver failure or in those with a large porto-systemic shunt. In cirrhotic patients, the current classification comprises covert and overt encephalopathy. Diagnosis of covert encephalopathy requires sensitive tests. Lactulose and rifaximin are the two leading therapeutic options. Rifaximin is efficacious for maintaining remission from hepatic encephalopathy. Liver transplantation should be discussed in cirrhotic patients with encephalopathy.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

II Workshop on the use of Computed Tomography (CT) in pig carcass classification. Other CT applications: live animals and meat technology, 16-17th April 2009, Monells (Girona), Spain

Es va realitzar el II Workshop en Tomografia Computeritzada (TC) a Monells. El primer dia es va dedicar íntegrament a la utilització del TC en temes de classificació de canals porcines, i el segon dia es va obrir a altres aplicacions del TC, ja sigui en animals vius o en diferents aspectes de qualitat de la carn o els productes carnis. Al workshop hi van assistir 45 persones de 12 països de la UE. The II workshop on the use of Computed Tomography (CT) in pig carcass classification. Other CT applications: live animals and meat technology was held in Monells. The first day it was dedicated to the use of CT in pig carcass classification. The segond day it was open to otehr CT applications, in live animals or in meat and meat products quality. There were 45 assistants of 12 EU countries.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.