Creació de taules d'una base de dades relacional a partir del diagrama de classes d'anàlisi d'UML

És ben sabut que les úniques etapes del cicle de vida del programari que necessàriament s'han d'especificar són les de recollida de requisits i l'anàlisi o l'especificació del programari. La resta (disseny, implementació i prova) es pot generar d'una manera més o menys automàtica a partir de l'anàlisi. En aquest PFC hem volgut estudiar la viabilitat de la construcció automàtica de codi SQL a partir de diagrames de classes d'anàlisi UML. S'ha estès l'eina de modelatge UML Poseidon amb un connector, de manera que amb una interfície molt simple es pot obtenir molt ràpidament l'esquema bàsic d'una base de dades, incloent-hi les taules, les seves columnes, claus rimàries i foranes, i també els disparadors (i les claus úniques) necessaris per a garantir les restriccions de cardinalitat de les associacions.

The Holiness Code between D and P. Some Comments on the Function and Significance of Leviticus 17-26 in the Composition of the Torah.

(Résumé de l'ouvrage) Das Deuteronomium nimmt sowohl in der Literaturgeschichte der alttestamentlichen Geschichtsbücher Josua bis Könige eine Schlüsselstellung ein als auch für die Entstehung des Pentateuchs. Wie lassen sich diese beiden Funktionen vereinbaren? Mit der Verhältnisbestimmung haben sich namhafte Wissenschafter der Arbeitsgruppe »Biblical and Ancient Near Eastern Law« im Rahmen der Internationalen Treffen der Society of Biblical Literature in Berlin (2002) und Cambridge (2003) befasst. Der Band präsentiert die neuesten Forschungsergebnisse. Er enthält Vorträge von E. Otto, K. Schmid, H.-C. Schmitt, T. Römer, W.M. Schniedewind, G.N. Knoppers, R. Achenbach, M.M. Zahn und C. Nihan.

Estudi d'eines CASE que suporten OCLper a la generació automàtica de codi Java

Es tracta d'una recerca d'eines CASEque actualment suporten OCL en la generació automàtica de codi Java per estudiar-les ianalitzar-les a través d'un model de proves consistent en un diagrama de classes del modelestàtic de l'UML i una mostra variada d'instruccions OCL, amb l'objectiu de detectar lesseves mancances, analitzant el codi obtingut i determinar si controla o no cada tipus derestricció, i si s'han implementat bé en el codi.

Generació automàtica de codi Java amb ArgoUML

Aquesta memòria presenta un estudi de la generació automàtica de codi Java a partir de diagrames UML amb l'eina ArgoUML. El cicle de vida tradicional del programari presenta alguns problemes com la manca de sincronització entre codi i documentació, poca portabilitat i problemes de interoperabilidad. El paradigma MDA vol solucionar en part aquests problemes fent dels models el centre del desenvolupament del programari i apostant per la generació automàtica de models i codi.

J2EE : Generació automàtica de codi

Aquest projecte està enfocat a determinar l'estat actual de les principals eines de generació automàtica de codi que existeixen, analitzant les característiques principals de cada eina determinar-ne les funcionalitats.

Optimization of treatment with interferon beta in multiple sclerosis. Usefulness of automatic system application criteria

Background. A software based tool has been developed (Optem) to allow automatize the recommendations of the Canadian Multiple Sclerosis Working Group for optimizing MS treatment in order to avoid subjective interpretation. METHODS: Treatment Optimization Recommendations (TORs) were applied to our database of patients treated with IFN beta1a IM. Patient data were assessed during year 1 for disease activity, and patients were assigned to 2 groups according to TOR: "change treatment" (CH) and "no change treatment" (NCH). These assessments were then compared to observed clinical outcomes for disease activity over the following years. RESULTS: We have data on 55 patients. The "change treatment" status was assigned to 22 patients, and "no change treatment" to 33 patients. The estimated sensitivity and specificity according to last visit status were 73.9% and 84.4%. During the following years, the Relapse Rate was always higher in the "change treatment" group than in the "no change treatment" group (5 y; CH: 0.7, NCH: 0.07; p < 0.001, 12 m - last visit; CH: 0.536, NCH: 0.34). We obtained the same results with the EDSS (4 y; CH: 3.53, NCH: 2.55, annual progression rate in 12 m - last visit; CH: 0.29, NCH: 0.13). CONCLUSION: Applying TOR at the first year of therapy allowed accurate prediction of continued disease activity in relapses and disability progression.

Distinguishing general concepts from individuals: an automatic coarse-grained classifier

Named entity recognizers are unable to distinguish if a term is a general concept as "scientist" or an individual as "Einstein". In this paper we explore the possibility to reach this goal combining two basic approaches: (i) Super Sense Tagging (SST) and (ii) YAGO. Thanks to these two powerful tools we could automatically create a corpus set in order to train the SuperSense Tagger. The general F1 is over 76% and the model is publicly available.

Automatic self-configuration of the logical network using distributed software agents

We present a system for dynamic network resource configuration in environments with bandwidth reservation. The proposed system is completely distributed and automates the mechanisms for adapting the logical network to the offered load. The system is able to manage dynamically a logical network such as a virtual path network in ATM or a label switched path network in MPLS or GMPLS. The system design and implementation is based on a multi-agent system (MAS) which make the decisions of when and how to change a logical path. Despite the lack of a centralised global network view, results show that MAS manages the network resources effectively, reducing the connection blocking probability and, therefore, achieving better utilisation of network resources. We also include details of its architecture and implementation

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Overview of coded light projection techniques for automatic 3D profiling

Obtaining automatic 3D profile of objects is one of the most important issues in computer vision. With this information, a large number of applications become feasible: from visual inspection of industrial parts to 3D reconstruction of the environment for mobile robots. In order to achieve 3D data, range finders can be used. Coded structured light approach is one of the most widely used techniques to retrieve 3D information of an unknown surface. An overview of the existing techniques as well as a new classification of patterns for structured light sensors is presented. This kind of systems belong to the group of active triangulation method, which are based on projecting a light pattern and imaging the illuminated scene from one or more points of view. Since the patterns are coded, correspondences between points of the image(s) and points of the projected pattern can be easily found. Once correspondences are found, a classical triangulation strategy between camera(s) and projector device leads to the reconstruction of the surface. Advantages and constraints of the different patterns are discussed

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.