A module for Data Centric Storage in ns-3

Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.

Using data mining with time series data in short-term stocks prediction

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

Planeamento de um Data Market Place

Relatório de Estágio apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Novos Media e Práticas Web

Detection of EBV-DNA in serum samples of an immunosuppressed child during a three years follow-up: association of clinical and PCR data with active infection

Twenty-four whole blood and serum samples were drawn from an eight year-old heart transplant child during a 36 months follow-up. EBV serology was positive for VCA-IgM and IgG, and negative for EBNA-IgG at the age of five years old when the child presented with signs and symptoms suggestive of acute infectious mononucleosis. After 14 months, serological parameters were: positive VCA-IgG, EBNA-IgG and negative VCA-IgM. This serological pattern has been maintained since then even during episodes suggestive of EBV reactivation. PCR amplified a specific DNA fragment from the EBV gp220 (detection limit of 100 viral copies). All twenty-four whole blood samples yielded positive results by PCR, while 12 out of 24 serum samples were positive. We aimed at analyzing whether detection of EBV-DNA in serum samples by PCR was associated with overt disease as stated by the need of antiviral treatment and hospitalization. Statistical analysis showed agreement between the two parameters evidenced by the Kappa test (value 0.750; p < 0.001). We concluded that detection of EBV-DNA in serum samples of immunosuppressed patients might be used as a laboratory marker of active EBV disease when a Real-Time PCR or another quantitative method is not available.

Planning, operations and data handling of planetary science missions

Dissertação para obtenção do Grau de Mestre em Engenharia Física

New data on Echinococcus spp. in Southern Brazil

40 Echinococcus isolates from sheep and cattle in Southern Brazil were genetically analysed in order to obtain further data on the presence of different taxa of the Echinococcus granulosus complex. Differentiation was done using a PCR technique and sequencing of mitochondrial cytochrome c oxidase subunit 1 (CO1). Most samples (38) could be allocated to the sheep strain (G1) of E. granulosus, while two samples belonged to E. ortleppi, previously known as cattle strain (G5) of E. granulosus. Due to the shorter prepatent period in dogs of the latter taxon, this records have important implications for the design of control measures in this endemic region.

Implementação de um modelo de Data Warehouse para o Serviço Nacional de Avisos Agrícolas

Trabalho de Projecto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.

Training and discovering corpus-based data driven exercices in english teaching (L2/FL) to native speakers of portuguese (L1)

Project submitted as part requirement for the degree of Masters in English teaching,

Candida bloodstream infection: data from a teaching hospital in Mato Grosso do Sul, Brazil

The incidence of Candida bloodstream infection has increased over the past years. In the Center-West region of Brazil, data on candidemia are scarce. This paper reports a retrospective analysis of 96 cases of Candida bloodstream infection at a Brazilian tertiary-care teaching hospital in the state of Mato Grosso do Sul, from January 1998 to December 2006. Demographic, clinical and laboratory data were collected from medical records and from the hospital's laboratory database. Patients' ages ranged from three days to 92 years, with 53 (55.2%) adults and 43 (44.8%) children. Of the latter, 25 (58.1%) were newborns. The risk conditions most often found were: long period of hospitalization, utilization of venous central catheter, and previous use of antibiotics. Fifty-eight (60.4%) patients died during the hospitalization period and eight (13.7%) of them died 30 days after the diagnosis of candidemia. Candida albicans (45.8%) was the most prevalent species, followed by C. parapsilosis (34.4%), C. tropicalis (14.6%) and C. glabrata (5.2%). This is the first report of Candida bloodstream infection in the state of Mato Grosso do Sul and it highlights the importance of considering the possibility of invasive Candida infection in patients exposed to risk factors, particularly among neonates and the elderly.

Single operation multiple data - paralelismo de dados ao nível da sub-rotina

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

On the analysis of data emerging in non-linear and complex systemscomparison of two X-Ray prony spectra

New arguments proving that successive (repeated) measurements have a memory and actually remember each other are presented. The recognition of this peculiarity can change essentially the existing paradigm associated with conventional observation in behavior of different complex systems and lead towards the application of an intermediate model (IM). This IM can provide a very accurate fit of the measured data in terms of the Prony's decomposition. This decomposition, in turn, contains a small set of the fitting parameters relatively to the number of initial data points and allows comparing the measured data in cases where the “best fit” model based on some specific physical principles is absent. As an example, we consider two X-ray diffractometers (defined in paper as A- (“cheap”) and B- (“expensive”) that are used after their proper calibration for the measuring of the same substance (corundum a-Al2O3). The amplitude-frequency response (AFR) obtained in the frame of the Prony's decomposition can be used for comparison of the spectra recorded from (A) and (B) - X-ray diffractometers (XRDs) for calibration and other practical purposes. We prove also that the Fourier decomposition can be adapted to “ideal” experiment without memory while the Prony's decomposition corresponds to real measurement and can be fitted in the frame of the IM in this case. New statistical parameters describing the properties of experimental equipment (irrespective to their internal “filling”) are found. The suggested approach is rather general and can be used for calibration and comparison of different complex dynamical systems in practical purposes.

Measuring data transfer in heterogeneous IoT environments

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

E.D.I.: electronic data interchange

O presente trabalho tem como tema a Troca Electrónica de Dados (Electronic Data Interchange – EDI) transferência de dados estruturados, respeitando mensagens normalizadas estabelecidas, computador a computador, por meios electrónicos. Trocas entre computadores refere-se a trocas entre aplicações informáticas: por exemplo o sistema de encomendas envia ordens ao sistema central de controlo da produção, o qual então fará o envio da respectiva factura. O EDI aberto faz a troca electrónica de dados entre parceiros autónomos que se associaram para fazerem trocas de dados estruturados que são destinados a serem processados por programas de aplicações.

A score test for non-nested hypotheses with applications to discrete data models

This paper suggests that a convenient score test against non-nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. It is shown that this procedure is essentially a test for the correct specification of the conditional distribution of the variable of interest.

PIASA: A power and interference aware resource management strategy for heterogeneous workloads in cloud data centers

Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%.