A unified framework for the comprehension of software's time dimension

Les logiciels sont de plus en plus complexes et leur développement est souvent fait par des équipes dispersées et changeantes. Par ailleurs, de nos jours, la majorité des logiciels sont recyclés au lieu d’être développés à partir de zéro. La tâche de compréhension, inhérente aux tâches de maintenance, consiste à analyser plusieurs dimensions du logiciel en parallèle. La dimension temps intervient à deux niveaux dans le logiciel : il change durant son évolution et durant son exécution. Ces changements prennent un sens particulier quand ils sont analysés avec d’autres dimensions du logiciel. L’analyse de données multidimensionnelles est un problème difficile à résoudre. Cependant, certaines méthodes permettent de contourner cette difficulté. Ainsi, les approches semi-automatiques, comme la visualisation du logiciel, permettent à l’usager d’intervenir durant l’analyse pour explorer et guider la recherche d’informations. Dans une première étape de la thèse, nous appliquons des techniques de visualisation pour mieux comprendre la dynamique des logiciels pendant l’évolution et l’exécution. Les changements dans le temps sont représentés par des heat maps. Ainsi, nous utilisons la même représentation graphique pour visualiser les changements pendant l’évolution et ceux pendant l’exécution. Une autre catégorie d’approches, qui permettent de comprendre certains aspects dynamiques du logiciel, concerne l’utilisation d’heuristiques. Dans une seconde étape de la thèse, nous nous intéressons à l’identification des phases pendant l’évolution ou pendant l’exécution en utilisant la même approche. Dans ce contexte, la prémisse est qu’il existe une cohérence inhérente dans les évènements, qui permet d’isoler des sous-ensembles comme des phases. Cette hypothèse de cohérence est ensuite définie spécifiquement pour les évènements de changements de code (évolution) ou de changements d’état (exécution). L’objectif de la thèse est d’étudier l’unification de ces deux dimensions du temps que sont l’évolution et l’exécution. Ceci s’inscrit dans notre volonté de rapprocher les deux domaines de recherche qui s’intéressent à une même catégorie de problèmes, mais selon deux perspectives différentes.

The time dimension of neural network models

This review attempts to provide an insightful perspective on the role of time within neural network models and the use of neural networks for problems involving time. The most commonly used neural network models are defined and explained giving mention to important technical issues but avoiding great detail. The relationship between recurrent and feedforward networks is emphasised, along with the distinctions in their practical and theoretical abilities. Some practical examples are discussed to illustrate the major issues concerning the application of neural networks to data with various types of temporal structure, and finally some highlights of current research on the more difficult types of problems are presented.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.

Spatio-temporal modelling of environmental data

Programa Doutoral em Matemática e Aplicações.

Time of injury in the light of acute and hazardous usual alcohol consumption - A study among emergency department patients.

Purpose: To investigate how prior-to-injury and usual alcohol consumption relate to time of injury. Patients and methods: The associations between injury time of day and day of week and prior-to-injury (labeled as "acute") alcohol intake and hazardous usual alcohol consumption (considered from the point of view of both heavy episodic drinking [HED] and risky volumes of consumption) are assessed using interview data from a randomized sample of 486 injured patients treated in a Swiss emergency department (ED; Lausanne University Hospital). Results: Acute consumption was associated with both injury time of day and day of week, HED with day of week only, and risky volume with none. Conclusions: Acute consumption and HED, but not risky volume of consumption, show specific time distributions for injuries. These findings highlight the potential importance of considering the time dimension of an injury when providing emergency care and have additional implications for interventions aimed at influencing the alcohol consumption of injured patients presenting to the ED.

Problems in four-dimensional data assimilation

With the introduction of new observing systems based on asynoptic observations, the analysis problem has changed in character. In the near future we may expect that a considerable part of meteorological observations will be unevenly distributed in four dimensions, i.e. three dimensions in space and one in time. The term analysis, or objective analysis in meteorology, means the process of interpolating observed meteorological observations from unevenly distributed locations to a network of regularly spaced grid points. Necessitated by the requirement of numerical weather prediction models to solve the governing finite difference equations on such a grid lattice, the objective analysis is a three-dimensional (or mostly two-dimensional) interpolation technique. As a consequence of the structure of the conventional synoptic network with separated data-sparse and data-dense areas, four-dimensional analysis has in fact been intensively used for many years. Weather services have thus based their analysis not only on synoptic data at the time of the analysis and climatology, but also on the fields predicted from the previous observation hour and valid at the time of the analysis. The inclusion of the time dimension in objective analysis will be called four-dimensional data assimilation. From one point of view it seems possible to apply the conventional technique on the new data sources by simply reducing the time interval in the analysis-forecasting cycle. This could in fact be justified also for the conventional observations. We have a fairly good coverage of surface observations 8 times a day and several upper air stations are making radiosonde and radiowind observations 4 times a day. If we have a 3-hour step in the analysis-forecasting cycle instead of 12 hours, which is applied most often, we may without any difficulties treat all observations as synoptic. No observation would thus be more than 90 minutes off time and the observations even during strong transient motion would fall within a horizontal mesh of 500 km * 500 km.

Fluctuating dimension in a discrete model for quantum gravity based on the spectral principle

The spectral principle of Connes and Chamseddine is used as a starting point to define a discrete model for Euclidean quantum gravity. Instead of summing over ordinary geometries, we consider the sum over generalized geometries where topology, metric, and dimension can fluctuate. The model describes the geometry of spaces with a countable number n of points, and is related to the Gaussian unitary ensemble of Hermitian matrices. We show that this simple model has two phases. The expectation value , the average number of points in the Universe, is finite in one phase and diverges in the other. We compute the critical point as well as the critical exponent of . Moreover, the space-time dimension delta is a dynamical observable in our model, and plays the role of an order parameter. The computation of is discussed and an upper bound is found, < 2.

Reference list of 120 datasets from time series station Payerne used for exploratory search

The analysis of time-dependent data is an important problem in many application domains, and interactive visualization of time-series data can help in understanding patterns in large time series data. Many effective approaches already exist for visual analysis of univariate time series supporting tasks such as assessment of data quality, detection of outliers, or identification of periodically or frequently occurring patterns. However, much fewer approaches exist which support multivariate time series. The existence of multiple values per time stamp makes the analysis task per se harder, and existing visualization techniques often do not scale well. We introduce an approach for visual analysis of large multivariate time-dependent data, based on the idea of projecting multivariate measurements to a 2D display, visualizing the time dimension by trajectories. We use visual data aggregation metaphors based on grouping of similar data elements to scale with multivariate time series. Aggregation procedures can either be based on statistical properties of the data or on data clustering routines. Appropriately defined user controls allow to navigate and explore the data and interactively steer the parameters of the data aggregation to enhance data analysis. We present an implementation of our approach and apply it on a comprehensive data set from the field of earth bservation, demonstrating the applicability and usefulness of our approach.

Reflecting on time, timing and timeliness in public sector supply networks

Despite recent research on time (e.g. Hedaa & Törnroos, 2001), consideration of the time dimension in data collection, analysis and interpretation in research in supply networks is, to date, still limited. Drawing on a body of literature from organization studies, and empirical findings from a six-year action research programme and a related study of network learning, we reflect on time, timing and timeliness in interorganizational networks. The empirical setting is supply networks in the English health sector wherein we identify and elaborate various issues of time, within the case and in terms of research process. Our analysis is wide-ranging and multi-level, from the global (e.g. identifying the notion of life cycles) to the particular (e.g. different cycle times in supply, such as daily for deliveries and yearly for contracts). We discuss the ‘speeding up’ of inter-organizational ‘e’ time and tensions with other time demands. In closing the paper, we relate our conclusions to the future conduct of the research programme and supply research more generally, and to the practice of managing supply (in) networks.

Machine learning and data decompositions for complex networked dynamical systems

Thesis (Ph.D.)--University of Washington, 2016-08

Process oriented framework to support PLM implementation

Product lifecycle management (PLM) innovates as it defines both the product as a central element to aggregate enterprise information and the lifecycle as a new time dimension for information integration and analysis. Because of its potential benefits to shorten innovation lead-times and to reduce costs, PLM has attracted a lot of attention at industry and at research. However, the current PLM implementation stage at most organisations still does not apply the lifecycle management concepts thoroughly. In order to close the existing realisation gap, this article presents a process oriented framework to support effective PLM implementation. The framework central point consists of a set of lifecycle oriented business process reference models which links the necessary fundamental concepts, enterprise knowledge and software solutions to effectively deploy PLM. (c) 2007 Elsevier B.V. All rights reserved.

Regeneration of the Corneal Epithelium after Debridement of its Central Region: An Autoradiographic Study on Rabbits

Purpose: To investigate the proliferative behavior of the corneal and limbal epithelia after debridement on the central region of the rabbit cornea. Methods: After scraping a circular epithelial area, 5 mm in diameter, in the center of the cornea, (3)H-thymidine ((3)H-TdR) was injected intravitreally, and the rabbits killed from 1 to 49 days afterward. The cornea, together with the adjacent conjunctiva, was processed for autoradiography. Results: The regenerating epithelium at the center of the cornea exhibited high frequencies of labeled nuclei when compared to controls. The mitotic indexes for the limbus were comparable in experimental and control eyes. The unique basal stratum of the limbal epithelium exhibited quick proliferation and vertical migration in all eyes. Cells that remained labeled for four weeks or more were observed throughout the corneal epithelium, including its basal stratum, and this did not depend on epithelial damage. Conclusion: Corneal epithelium wounds are healed by sliding and proliferation of cells surrounding the epithelial gap without any evidence for the participation of the limbal epithelium. Daughter cells labeled with (3)H-TdR were visualized in all layers of the corneal epithelium up to 7 weeks after the DNA precursor injection. However, at this long interval, the only labeled cells in the limbus were in the suprabasal layers.

Morphological and autoradiographic studies on the corneal and limbal epithelium of rabbits

The investigation was centered on the morphological features of the conjunctiva-cornea transition (limbus) of the rabbit eye and the proliferative behavior of its epithelium. The eyes were processed for examination with light and electron microscopy, as well as for autoradiography after intravitreal injection of [H-3]thymidine ([H-3]TdR). At the sites of extraocular muscle insertion, the vascularization of the stroma extended to the peripheral cornea, and the limbal epithelium was thin with its basal stratum made up by clear cuboidal cells. In between the muscle insertions, the cuboidal clear cells, as well as the stroma blood vessels; were scarce. At the light microscope level, the basement membrane was distinct in the cornea but not in the limbus or the conjunctiva. Autoradiographs demonstrated that, at the limbus, the basal cells migrated very quickly to the suprabasal region and remained there up to the 28-day interval. Labeled cells were identified in all epithelial layers of the cornea, including the basal one, at 21 and 28 days but not in the limbal basal clear cells. The rate of renewal of conjunctival epithelium was similar to that observed for the transition with scarce clear cells. The high-resolution autoradiographs demonstrated that the basal cuboidal clear limbal cells exhibit a quick renewal and that they are not label-retaining cells. These latter ones were detected all over the corneal epithelium and in the suprabasal layers of the limbus up to 28 days, in physiological conditions, without the need of stimulation by damage to the corneal epithelium.

Sistema de apoio à aprendizagem na área da discalculia em menores

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Implementació en Geomedia PRO d'un exportador a KML per visualitzar dades 4D en Google Earth

Treball consistent en la construcció d'un exportador a format KML de mapes temàtics pel producte Geomedia PRO 6.1 possibilitant l'observació del component del temps sobre un globus virtual com és Google Earth. Mitjançant les dades de la xarxa XEMEC, es mostrarà un mapa temàtic d'exemple amb les dades d'intensitat i direcció del vent recollides en un període d'un any.