136 resultados para Congost, Rosa
Resumo:
The design of concurrent software systems, in particular process-aware information systems, involves behavioral modeling at various stages. Recently, approaches to behavioral analysis of such systems have been based on declarative abstractions defined as sets of behavioral relations. However, these relations are typically defined in an ad-hoc manner. In this paper, we address the lack of a systematic exploration of the fundamental relations that can be used to capture the behavior of concurrent systems, i.e., co-occurrence, conflict, causality, and concurrency. Besides the definition of the spectrum of behavioral relations, which we refer to as the 4C spectrum, we also show that our relations give rise to implication lattices. We further provide operationalizations of the proposed relations, starting by proposing techniques for computing relations in unlabeled systems, which are then lifted to become applicable in the context of labeled systems, i.e., systems in which state transitions have semantic annotations. Finally, we report on experimental results on efficiency of the proposed computations.
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A progressive global increase in the burden of allergic diseases has affected the industrialized world over the last half century and has been reported in the literature. The clinical evidence reveals a general increase in both incidence and prevalence of respiratory diseases, such as allergic rhinitis (common hay fever) and asthma. Such phenomena may be related not only to air pollution and changes in lifestyle, but also to an actual increase in airborne quantities of allergenic pollen. Experimental enhancements of carbon dioxide (CO) have demonstrated changes in pollen amount and allergenicity, but this has rarely been shown in the wider environment. The present analysis of a continental-scale pollen data set reveals an increasing trend in the yearly amount of airborne pollen for many taxa in Europe, which is more pronounced in urban than semi-rural/rural areas. Climate change may contribute to these changes, however increased temperatures do not appear to be a major influencing factor. Instead, we suggest the anthropogenic rise of atmospheric CO levels may be influential.
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We have studied the mineral olmiite CaMn\[SiO3(OH)](OH) which forms a series with its calcium analogue poldevaartite CaCa\[SiO3(OH)](OH) using a range of techniques including scanning electron microscopy, thermogravimetric analysis , Raman and infrared spectroscopy. Chemical analysis shows the mineral is pure and contains only calcium and manganese in the formula. Thermogravimetric analysis proves the mineral decomposes at 502°C with a mass loss of 8.8% compared with the theoretical mass loss of 8.737%. A strong Raman band at 853 cm-1 is assigned to the SiO stretching vibration of the SiO3(OH) units. Two Raman bands at 914 and 953 cm-1 are attributed to the antisymmetric vibrations.Two intense Raman bands observed at 3511 and 3550 cm-1 are assigned to the OH stretching vibration of the SiO3(OH) units. The observation of multiple OH bands supports the concept of the non-equivalence of the OH units. Vibrational spectroscopy enables a detailed assessment of the molecular structure of olmiite.
Resumo:
Process-Aware Information Systems (PAISs) support executions of operational processes that involve people, resources, and software applications on the basis of process models. Process models describe vast, often infinite, amounts of process instances, i.e., workflows supported by the systems. With the increasing adoption of PAISs, large process model repositories emerged in companies and public organizations. These repositories constitute significant information resources. Accurate and efficient retrieval of process models and/or process instances from such repositories is interesting for multiple reasons, e.g., searching for similar models/instances, filtering, reuse, standardization, process compliance checking, verification of formal properties, etc. This paper proposes a technique for indexing process models that relies on their alternative representations, called untanglings. We show the use of untanglings for retrieval of process models based on process instances that they specify via a solution to the total executability problem. Experiments with industrial process models testify that the proposed retrieval approach is up to three orders of magnitude faster than the state of the art.
Resumo:
Buffeting response of a cable-stayed bridge under construction is investigated through wind tunnel tests and numerical simulations. Two configurations of the erection stage have been considered and compared in terms of dynamic response and internal forces using the results of the experimental aeroelastic models. Moreover the results of a numerical model able to simulate the simultaneous effects of vortex shedding from tower and aeroelastic response of the deck are compared to the wind tunnel ones.
Resumo:
Purpose: This is one of the first studies to report that the Achenbach internalising scales were much more effective at identifying those with current comorbid depression and anxiety, rather than individual mood disorder. Introduction: The Achenbach behaviour checklists (YSR,YASR) are widely used, low cost screening tools used to assess problem behaviour. Several studies report good association between the checklists and psychiatric diagnoses; although with varying degrees of agreement. Most are cross-sectional studies involving adolescents referred to mental health services; few are in large community-based studies. This study examined the usefulness of the Achenbach internalising scales in the primary screening (both predictive and concurrent)for depression and anxiety. Methods: The sample was 2400 young adults from an Australian population-based prospective birth cohort study. The association between the empirical anxiety and depression scales were individually assessed against DSM-IV depression and anxiety diagnoses. Odds ratios and diagnostic efficiency tests report the findings. Results: Adolescents with internalising symptoms were twice (OR 2.3, 95%CI 1.7 to 3.1) as likely to be diagnosed with later DSM-IV depression. YASR internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. The internalising scales were much more effective at identifying those with comorbid depression and anxiety. Conclusions: Adolescence and early adulthood are key risk periods for the onset of anxiety and depression. This study found that young people with internalising behaviour problems were more likely to have comorbid depression and anxiety DSM-IV disorder.
Resumo:
Surveying 1,700 journalists from seventeen countries, this study investigates perceived influences on news work. Analysis reveals a dimensional structure of six distinct domains—political, economic, organizational, professional, and procedural influences, as well as reference groups. Across countries, these six dimensions build up a hierarchical structure where organizational, professional, and procedural influences are perceived as more powerful limits to journalists' work than political and economic influences.
Resumo:
This article reports key findings from a comparative survey of the role perceptions, epistemological orientations and ethical views of 1800 journalists from 18 countries. The results show that detachment, non-involvement, providing political information and monitoring the government are considered essential journalistic functions around the globe. Impartiality, the reliability and factualness of information, as well as adherence to universal ethical principles are also valued worldwide, though their perceived importance varies across countries. Various aspects of interventionism, objectivism and the importance of separating facts from opinion, on the other hand, seem to play out differently around the globe. Western journalists are generally less supportive of any active promotion of particular values, ideas and social change, and they adhere more to universal principles in their ethical decisions. Journalists from non-western contexts, on the other hand, tend to be more interventionist in their role perceptions and more flexible in their ethical views.
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Automated process discovery techniques aim at extracting process models from information system logs. Existing techniques in this space are effective when applied to relatively small or regular logs, but generate spaghetti-like and sometimes inaccurate models when confronted to logs with high variability. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. This leads to a collection of process models – each one representing a variant of the business process – as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity and low fitness. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically using subprocess extraction. Splitting is performed in a controlled manner in order to achieve user-defined complexity or fitness thresholds. Experiments on real-life logs show that the technique produces collections of models substantially smaller than those extracted by applying existing trace clustering techniques, while allowing the user to control the fitness of the resulting models.
Resumo:
Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.
Resumo:
We initially described a rat chamber model with an inserted arteriovenous pedicle which spontaneously generates 3-dimensional vascularized connective tissue (Tanaka Y et al., Br J Plast Surg 2000; 53: 51-7). More recently we have developed a murine chamber model containing reconstituted basement membrane (Matrigel®) and FGF-2 that generates vascularized adipose tissue in vivo (Cronin K et al., Plast Reconstr Surg 2004; in press). We have extended this work to assess the cellular and matrix requirements for the Matrigel®- induced neo-adipogenesis. We found that chambers sealed to host fat were unable to grow new adipose tissue. In these chambers the Matrigel® became vascularized with maximal outgrowth of vessels extending to the periphery at 6 weeks. A small amount of adipose tissue was found adjacent to the vessels, most likely arising from periadventitial adipose tissue. In contrast, chambers open to interaction with endogenous adipose tissue showed abundant new fat, and partial exposure to adjacent adipose tissue clearly showed neo-adipogenesis only in this area. Addition of small amounts of free fat to the closed chamber containing Matrigel® was able to induce neo-adipogenesis. Addition of small pieces of human fat also caused neo-adipogenesis in immunocompromised (SCID) mice. Also, we found Matrigel® to induce adipogenesis of Lac-Z-tagged (Rosa-26) murine bone marrow-derived mesenchymal stem cells, and cells similar to these have been isolated from human adipose tissue. Given that Matrigel® is a mouse product and cannot be used in humans, we have started investigating alternative matrix scaffolds for adipogenesis such as the PDA-approved PLGA, collagen and purified components derived from Matrigel®, such as laminin-1. The optimal conditions for adipogenesis with these matrices are still being elucidated. In conclusion, we have demonstrated that a precursor cell source inside the chamber is essential for the generation of vascularized adipose tissue in vivo. This technique offers unique potential for the reconstruction of soft tissue defects and may enable the generation of site-specific tissue using the correct microenvironment.
Resumo:
This paper evaluates the suitability of sequence classification techniques for analyzing deviant business process executions based on event logs. Deviant process executions are those that deviate in a negative or positive way with respect to normative or desirable outcomes, such as non-compliant executions or executions that undershoot or exceed performance targets. We evaluate a range of feature types and classification methods in terms of their ability to accurately discriminate between normal and deviant executions both when deviances are infrequent (unbalanced) and when deviances are as frequent as normal executions (balanced). We also analyze the ability of the discovered rules to explain potential causes and contributing factors of observed deviances. The evaluation results show that feature types extracted using pattern mining techniques only slightly outperform those based on individual activity frequency. The results also suggest that more complex feature types ought to be explored to achieve higher levels of accuracy.
Resumo:
Empirical evidence shows that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication arises for example when the repository covers multiple variants of the same processes or due to copy-pasting. Previous work has addressed the problem of efficiently retrieving exact clones that can be refactored into shared subprocess models. This article studies the broader problem of approximate clone detection in process models. The article proposes techniques for detecting clusters of approximate clones based on two well-known clustering algorithms: DBSCAN and Hi- erarchical Agglomerative Clustering (HAC). The article also defines a measure of standardizability of an approximate clone cluster, meaning the potential benefit of replacing the approximate clones with a single standardized subprocess. Experiments show that both techniques, in conjunction with the proposed standardizability measure, accurately retrieve clusters of approximate clones that originate from copy-pasting followed by independent modifications to the copied fragments. Additional experiments show that both techniques produce clusters that match those produced by human subjects and that are perceived to be standardizable.