Time series morphological analysis applied to biomedical signals events detection

Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

Pig bite in Brazil: a case series from a teaching hospital

A retrospective survey done from 1987 till 1990 revealed that 23 patients bitten by pigs sought medical help at a teaching hospital in Uberlândia, in southeastern Brazil. Most cases (21) were from Uberlândia. The cases were evenly distributed by month and by year; most of them (14/16; 87.5%) occurred between 7. OOa.m. and 7.00 p. m. The male to female ratio was 6.7:1. Age ranged from 6 to 73 (mean 38.95 ± SD 22.06, median 36). The bites were more common on the upper limbs, particularly on the forearms. In 11(47.8%) cases the injury was described as deep. In most cases where information was available the injury was related to capture, transport or immobilisation ofthe pigfor slaughter. The following medical procedures were performed: local cleansing in 19(82.6%) cases, rabies vaccine (12; 52.2%), antirabies serum (2; 8.7%), suturing (6; 26.1%) and tetanus vaccine (12; 52.2%). There was no case of infection at the bite site, neither of rabies or tetanus. By our data, the annual incidence of pig bite in Uberlândia can be estimated to be about 1.5/100.000.

Structural time series models and the Kalman filter: A concise review

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

A system’s approach to cache hierarchy-aware decomposition of data-parallel computations

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

State detection in a financial portfolio: a self-organizing maps approach for financial time series

This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

Chagas disease in the State of Pernambuco, Brazil: analysis of admissions and mortality time series

INTRODUCTION: A time series study of admissions, deaths and acute cases was conducted in order to evaluate the context of Chagas disease in Pernambuco. METHODS: Data reported to the Information Technology Department of the Brazilian National Health Service between 1980 and 2008 was collected for regions and Federal Units of Brazil; and microregions and municipalities of Pernambuco. Rates (per 100,000 inhabitants) of hospitalization, mortality and acute cases were calculated using a national hospital database (SIH), a national mortality database (SIM) and the national Information System for Notifiable Diseases (SINAN), respectively. RESULTS: The national average for Chagas disease admissions was 0.99 from 1995 to 2008. Pernambuco obtained a mean of 0.39 in the same period, with the highest rates being concentrated in the interior of the state. The state obtained a mean mortality rate of 1.56 between 1980 and 2007, which was lower than the national average (3.66). The mortality rate has tended to decline nationally, while it has remained relatively unchanged in Pernambuco. Interpolating national rates of admissions and deaths, mortality rates were higher than hospitalization rates between 1995 and 2007. The same occurred in Pernambuco, except for 2003. Between 2001 and 2006, rates for acute cases were 0.56 and 0.21 for Brazil and Pernambuco, respectively. CONCLUSIONS: Although a decrease in Chagas mortality has occurred in Brazil, the disease remains a serious public health problem, especially in the Northeast region. It is thus essential that medical care, prevention and control regarding Chagas disease be maintained and improved.

Paracoccidioidomycosis case series with and without central nervous system involvement

INTRODUCTION: Paracoccidioidomycosis (PCM) is the most important systemic mycosis in South America. Central nervous system involvement is potentially fatal and can occur in 12.5% of cases. This paper aims to contribute to the literature describing eight cases of neuroparacoccidioidomycosis (NPMC) and compare their characteristics with patients without neurological involvement, to identify unique characteristics of NPCM. METHODS: A cohort of 213 PCM cases was evaluated at the Infectious Diseases Clinic of the University Hospital, Federal University of Minas Gerais, Brazil, from October 1976 to August 2008. Epidemiological, clinical, laboratory, therapeutic and follow-up data were registered. RESULTS: Eight patients presented NPCM. The observed NPCM prevalence was 3.8%. One patient presented the subacute form of PCM and the other seven presented the chronic form of the disease. The parenchymatous form of NPCM occurred in all patients. 60% of the patients who proceeded from the north/ northeast region of Minas Gerais State developed NPCM. The neurological involvement of a mother and her son was observed. NPCM patients exhibited demographical and clinical profiles similar to what is described in the literature. When NPCM cases were compared to PCM patients, there were differences in relation to origin and positive PCM family history. CONCLUSIONS: The results corroborate the clinical view that the neurological findings are extremely important in the evaluation of PCM patients. Despite the limitations of this study, the differences in relation to patient's origins and family history point to the need of further studies to determine the susceptibility factors involved in the neurological compromise.

Hepatitis B revaccination for healthcare workers who are anti-HBs-negative after receiving a primary vaccination series

INTRODUCTION: This study aimed to evaluate the response to hepatitis B (HB) revaccination of healthcare workers (HCW) who are negative for antibodies to HB surface antigen (anti-HBs) after a complete vaccination series. METHODS: HCW whose anti-HBs test was performed > 90 days after a HB vaccination course were given a 4th dose. A post-vaccination test was done within 30 to 90 days. RESULTS: One hundred and seventy HCW were enrolled: 126 (74.1%) were anti-HBs-positive after the 4th dose. CONCLUSIONS: Rechecking anti-HBs after the 4th HB vaccine dose is a practical approach in case of post-vaccination tests performed >90 days after the full vaccination course.

Using an LED as a sensor and visible light communication device in a smart illumination system

The need for more efficient illumination systems has led to the proliferation of Solid-State Lighting (SSL) systems, which offer optimized power consumption. SSL systems are comprised of LED devices which are intrinsically fast devices and permit very fast light modulation. This, along with the congestion of the radio frequency spectrum has paved the path for the emergence of Visible Light Communication (VLC) systems. VLC uses free space to convey information by using light modulation. Notwithstanding, as VLC systems proliferate and cost competitiveness ensues, there are two important aspects to be considered. State-of-the-art VLC implementations use power demanding PAs, and thus it is important to investigate if regular, existent Switched-Mode Power Supply (SMPS) circuits can be adapted for VLC use. A 28 W buck regulator was implemented using a off-the-shelf LED Driver integrated circuit, using both series and parallel dimming techniques. Results show that optical clock frequencies up to 500 kHz are achievable without any major modification besides adequate component sizing. The use of an LED as a sensor was investigated, in a short-range, low-data-rate perspective. Results show successful communication in an LED-to-LED configuration, with enhanced range when using LED strings as sensors. Besides, LEDs present spectral selective sensitivity, which makes them good contenders for a multi-colour LED-to-LED system, such as in the use of RGB displays and lamps. Ultimately, the present work shows evidence that LEDs can be used as a dual-purpose device, enabling not only illumination, but also bi-directional data communication.

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

Real convergence in per capita output and growth in Eurozone: A time-series approach

The real convergence hypothesis has spurred a myriad of empirical tests and approaches in the economic literature. This Work Project intends to test for real output and growth convergence in all N(N-1)/2 possible pairs of output and output growth gaps of 14 Eurozone countries. This paper follows a time-series approach, as it tests for the presence of unit roots and persistence changes in the above mentioned pairs of output gaps, as well as for the existence of growth convergence with autoregressive models. Overall, significantly greater evidence has been found to support growth convergence rather than output convergence in our sample.

Mechanical characterization of old chestnut beams

The main objective of this work is to evaluate, by non-destructive techniques, seven old Chestnut beams. For that, after the geometric assessment and the detailed visual inspection that allowed to strength grade the beams, a series of non-destructive tests was setup. In a first step, non-destructive bending tests, under the elastic limit, were performed to quantify the modulus of elasticity in bending (MoE) of the seven beams. Then, Resistograph® and Pilodyn® tests were done to assess the superficial decay and to have aclearer idea of the voids dimensions. Then, two beams were tested in bending until failure to evaluate the bending strength. In a second step, end parts were cut from the beams, one per end of the beams, to perform Resistograph®, Pilodyn® and ultrasound tests, to quantify the density of the beams and to extract meso-specimens to be used in tension parallel to the grain tests