Latest developments in data analysis tools for disruption prediction and for the exploration of multimachine operational spaces.

In the last years significant efforts have been devoted to the development of advanced data analysis tools to both predict the occurrence of disruptions and to investigate the operational spaces of devices, with the long term goal of advancing the understanding of the physics of these events and to prepare for ITER. On JET the latest generation of the disruption predictor called APODIS has been deployed in the real time network during the last campaigns with the new metallic wall. Even if it was trained only with discharges with the carbon wall, it has reached very good performance, with both missed alarms and false alarms in the order of a few percent (and strategies to improve the performance have already been identified). Since for the optimisation of the mitigation measures, predicting also the type of disruption is considered to be also very important, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been developed. This technique allows automatic classification of an incoming disruption with a success rate of better than 85%. Various other manifold learning tools, particularly Principal Component Analysis and Self Organised Maps, are also producing very interesting results in the comparative analysis of JET and ASDEX Upgrade (AUG) operational spaces, on the route to developing predictors capable of extrapolating from one device to another.

Procedures manual for the post-operational reporting and data extension countermeasure.

National Highway Traffic Safety Administration, Washington, D.C.

Geostationary operational environmental satellite (GOES) data collection system; task 3 & 4 final report.

"TER-157-0003."

An air-standard cycle and a thermodynamic perspective on operational limits of Ranque-Hilsh or vortex tubes

A Thermodynamic air-standard cycle was envisaged for Ranque-Hilsh (R-H) or Vortex Tubes to provide relevant Thermodynamic analysis and tools for setting operating limits according to the conservation laws of mass and energy, as well as the constraint of the Second Law of Thermodynamics. The study used an integral or control volume approach and resulted in establishing working equations for evaluating the performance of an R-H tube. The work proved that the coefficient of performance does not depend on the R-H tube operating mode, i.e., the same value is obtained independently if the R-H tube operates either as a heat pump or as a refrigeration device. It was also shown that the isentropic coefficient of performance displays optima values of cold and hot mass fractions for a given operating pressure ratio. Finally, the study was concluded by comparing the present analysis with some experimental data available in the literature for operating pressures ranging 2-11 atm. (C) 2010 Elsevier Ltd and IIR. All rights reserved.

Modelling life history strategies with capture-recapture data: Evolutionary demography of the water skink Eulamprus tympanum

Matrix population models, elasticity analysis and loop analysis can potentially provide powerful techniques for the analysis of life histories. Data from a capture-recapture study on a population of southern highland water skinks (Eulamprus tympanum) were used to construct a matrix population model. Errors in elasticities were calculated by using the parametric bootstrap technique. Elasticity and loop analyses were then conducted to identify the life history stages most important to fitness. The same techniques were used to investigate the relative importance of fast versus slow growth, and rapid versus delayed reproduction. Mature water skinks were long-lived, but there was high immature mortality. The most sensitive life history stage was the subadult stage. It is suggested that life history evolution in E. tympanum may be strongly affected by predation, particularly by birds. Because our population declined over the study, slow growth and delayed reproduction were the optimal life history strategies over this period. Although the techniques of evolutionary demography provide a powerful approach for the analysis of life histories, there are formidable logistical obstacles in gathering enough high-quality data for robust estimates of the critical parameters.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Relative importance of female-specific and non-female-specific effects on variation in iron stores between women

Women have lower iron stores than men because of iron loss during their reproductive years. However, variation between women could result from differences in iron loss, aspects of iron homeostasis common to men and women, or a combination of both. We compared the effects of age, menopause, menstrual blood loss and the number of pregnancies (sex-specific factors), and the effects of genetic variation, on markers of iron stores. We assessed how much the same genes or other familial factors influence iron status in both men and women. Data from 2039 female twins who participated in studies of reproductive health and iron status were used to estimate the proportions of variation that could be ascribed to genes, environment and measured factors. Significant effects of age, menopausal status and magnitude of menstrual blood loss were demonstrated, accounting for up to 18% of variance in serum ferritin in this sample, but number of children had no significant effect. Genetic effects were more than twice as great as sex-specific effects. The within-pair similarity of ferritin values in dizygotic female twin pairs was greater than for dizygotic opposite-sex pairs, but this difference was not quite significant, consistent with a minor role for sex-specific factors; and the opposite-sex within-pair differences did not diminish significantly with age. We conclude that the contribution of genetic differences between women to variation in iron stores outweighs the comparatively small effects of interindividual variation in iron loss through variation in menstruation and number of pregnancies.

Modelo de data mining para deteção de embolias pulmonares

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Assessment of data-driven modeling strategies for water delivery canals

The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.

A contabilidade de gestão e a data envelopment analysis : análise de desempenho organizacional

Mestrado em Contabilidade e Gestão das Instituições Financeiras

Operational modal monitoring of ancient structures using wireless technology

Operational Modal Analysis is currently applied in structural dynamic monitoring studies using conventional wired based sensors and data acquisition platforms. This approach, however, becomes inadequate in cases where the tests are performed in ancient structures with esthetic concerns or in others, where the use of wires greatly impacts the monitoring system cost and creates difficulties in the maintenance and deployment of data acquisition platforms. In these cases, the use of sensor platforms based on wireless and MEMS would clearly benefit these applications. This work presents a first attempt to apply this wireless technology to the structural monitoring of historical masonry constructions in the context of operational modal analysis. Commercial WSN platforms were used to study one laboratory specimen and one of the structural elements of a XV century building in Portugal. Results showed that in comparison to the conventional wired sensors, wireless platforms have poor performance in respect to the acceleration time series recorded and the detection of modal shapes. However, for frequency detection issues, reliable results were obtained, especially when random excitation was used as noise source.

Data mining languages for business intelligence

Doctoral Thesis in Information Systems and Technologies Area of Engineering and Manag ement Information Systems

Spatial data infrastructures model for developing countries: A case study of Nigeria

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies