Approximate entropy normalized measures for analyzing social neurobiological systems

When considering time series data of variables describing agent interactions in social neurobiological systems, measures of regularity can provide a global understanding of such system behaviors. Approximate entropy (ApEn) was introduced as a nonlinear measure to assess the complexity of a system behavior by quantifying the regularity of the generated time series. However, ApEn is not reliable when assessing and comparing the regularity of data series with short or inconsistent lengths, which often occur in studies of social neurobiological systems, particularly in dyadic human movement systems. Here, the authors present two normalized, nonmodified measures of regularity derived from the original ApEn, which are less dependent on time series length. The validity of the suggested measures was tested in well-established series (random and sine) prior to their empirical application, describing the dyadic behavior of athletes in team games. The authors consider one of the ApEn normalized measures to generate the 95th percentile envelopes that can be used to test whether a particular social neurobiological system is highly complex (i.e., generates highly unpredictable time series). Results demonstrated that suggested measures may be considered as valid instruments for measuring and comparing complexity in systems that produce time series with inconsistent lengths.

Modeling of a solid-state bipolar blumlein generator for N stages

This paper models an n-stage stacked Blumlein generator for bipolar pulses for various load conditions. Calculation of the voltage amplitudes in time domain at the load and between stages is described for an n-stage generator. For this, the reflection and transmission coefficients are mathematically modeled where impedance discontinuity occurs (i.e., at the junctions between two transmission lines). The mathematical model developed is assessed by comparing simulation results to experimental data from a two-stage Blumlein solid-state prototype.

The contribution of multitemporal information from multispectral satellite images for automatic land cover classification at the national scale

Thesis submitted to the Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Information Management – Geographic Information Systems

Optimization of multi-stage amplifiers in deep-submicron CMOS using a distributed/parallel genetic algorithm

IEEE International Symposium on Circuits and Systems, pp. 724 – 727, Seattle, EUA

Software languages engineering: experimental evaluation

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Distributed controllers modeling through Petri nets with multi-asynchronous-channels

This paper proposes the concept of multi-asynchronous-channel for Petri nets. Petri nets extended with multi-asynchronous-channels and time-domains support the specification of distributed controllers, where each controller has a synchronous execution but the global system is asynchronous (globally-asynchronous locally-synchronous systems). Each multi-asynchronous-channel specify the interaction between two or more distributed controllers. These channels, together with the time-domain concept, ensure the creation of network-independent models to support implementations using heterogeneous communication networks. The created models support not only the systems documentation but also their validation and implementation through simulation tools, verification tools, and automatic code generators. An application example illustrates the use of a Petri net class extended with the proposed channels. © 2015 IEEE.

RESTAVEC – from haitian slave child to middle-class american

Trabalho de Projeto apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Tradução e Interpretação Especializadas, sob orientação da Doutora Clara Sarmento

Generalized convolution

The paper revisits the convolution operator and addresses its generalization in the perspective of fractional calculus. Two examples demonstrate the feasibility of the concept using analytical expressions and the inverse Fourier transform, for real and complex orders. Two approximate calculation schemes in the time domain are also tested.

Efficiency of strengthening techniques assessed for existing masonry buildings

The Azores archipelago is a zone with a vast cultural heritage, presenting a building stock mainly constructed in traditional stone masonry. It is known that this type of construction exhibits poor behaviour under seismic excitations; however it is extensively used in seismic prone areas, such as this case. The 9th of July of 1998 earthquake was the last seismic event in the islands, leaving many traditional stone constructions severely damaged or totally destroyed. This scenario led to an effort by the local government of improving the seismic resistance of these constructions, with the application of several reinforcement techniques. This work aims to study some of the most used reinforcement schemes after the 1998 earthquake, and to assess their effectiveness in the mitigation of the construction’s seismic vulnerability. A brief evaluation of the cost versus benefit of these retrofitting techniques is also made, seeking to identify those that are most suitable for each building typology. Thus, it was sought to analyze the case of real structures with different geometrical and physical characteristics, by establishing a comparison between the seismic performance of reinforced and non-reinforced structures. The first section contains the analysis of a total of six reinforcement scenarios for each building chosen. Using the recorded 1998 earthquake accelerograms, a linear time-history analysis was performed for each reinforcement scenario. A comparison was then established between the maximum displacements, inter-storey drift and maximum stress obtained, in order to evaluate the global seismic response of each reinforced structure. In the second part of the work, the examination of the performance obtained in the previous section, in relation to the cost of implementing each reinforcement technique, allowed to draw conclusions concerning the viability of implementing each reinforcement method, based on the book value of the buildings in study.

Quantification of the TMS-EEG response in epilepsy

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Transimpedance amplifier for integrated SpO2 optic sensor

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Using GIS to map the spatial and temporal occurrence of cholera epidemic in Camaroon

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

Kinetics of IFN-gamma, TNF-alpha, IL-10 and IL-4 production by mononuclear cells stimulated with gp43 peptides, in patients cured of paracoccidioidomycosis

We analyzed the kinetics of cytokine production by mononuclear cells from 17 patients who had been treated for paracoccidioidomycosis, using the stimulus of gp43 peptide groups (43kDa glycoprotein of Paracoccidioides brasiliensis) at 0.1 and 1µM, gp43 (1µg/ml) and crude Paracoccidioides brasiliensis antigen (PbAg; 75µg/ml). IFN-gamma production was a maximum at 144 hours in relation to the G2 and G8 peptide groups at 1µM and was greatest at 144 hours when stimulated by gp43 and by PbAg. The maximum TNF-alpha production was at 144 hours for the G2 group (0.1µM) and for gp43. IL-10 production was highest after 48 and 72 hours for G7 and G6 at 1µM, respectively. We also suggest the best time for analysis of IL4 production. These results may contribute towards future studies with gp43 peptides and encourage further investigations with the aim of understanding the influence of these peptides on the production of inflammatory and regulatory cytokines.

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil

INTRODUCTION: Forecasting dengue cases in a population by using time-series models can provide useful information that can be used to facilitate the planning of public health interventions. The objective of this article was to develop a forecasting model for dengue incidence in Campinas, southeast Brazil, considering the Box-Jenkins modeling approach. METHODS: The forecasting model for dengue incidence was performed with R software using the seasonal autoregressive integrated moving average (SARIMA) model. We fitted a model based on the reported monthly incidence of dengue from 1998 to 2008, and we validated the model using the data collected between January and December of 2009. RESULTS: SARIMA (2,1,2) (1,1,1)12 was the model with the best fit for data. This model indicated that the number of dengue cases in a given month can be estimated by the number of dengue cases occurring one, two and twelve months prior. The predicted values for 2009 are relatively close to the observed values. CONCLUSIONS: The results of this article indicate that SARIMA models are useful tools for monitoring dengue incidence. We also observe that the SARIMA model is capable of representing with relative precision the number of cases in a next year.