Influência de protocolos de treino de equilíbrio no desempenho funcional de idosas com osteoporose

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Postactivation Potentiation Biases Maximal Isometric Strength Assessment

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Reconhecimento de voz para aplicações em automação implementado em FPGA

In many movies of scientific fiction, machines were capable of speaking with humans. However mankind is still far away of getting those types of machines, like the famous character C3PO of Star Wars. During the last six decades the automatic speech recognition systems have been the target of many studies. Throughout these years many technics were developed to be used in applications of both software and hardware. There are many types of automatic speech recognition system, among which the one used in this work were the isolated word and independent of the speaker system, using Hidden Markov Models as the recognition system. The goals of this work is to project and synthesize the first two steps of the speech recognition system, the steps are: the speech signal acquisition and the pre-processing of the signal. Both steps were developed in a reprogrammable component named FPGA, using the VHDL hardware description language, owing to the high performance of this component and the flexibility of the language. In this work it is presented all the theory of digital signal processing, as Fast Fourier Transforms and digital filters and also all the theory of speech recognition using Hidden Markov Models and LPC processor. It is also presented all the results obtained for each one of the blocks synthesized e verified in hardware

Avaliação experimental de medidas de aceleração

Acceleration is a key parameter for engineering and is becoming increasingly important because of the need for companies to become more competitive in the market. Both applying new technologies to their products and optimizing their process lines with predictive maintenance and robotic automation. This study aims to analyze the quality of the signals obtained from a capacitive accelerometer. To do that a test rig was mounted, which consist of a shaker, fed by a signal generator, a linear potentiometer and a capacitive accelerometer; for the signal acquisition was used a acquisition board and the Labview software, in order to integrate twice the signal from the accelerometer and compare it with the sign of the potentiometer. This work also demonstrates the impact of acquired signal processing as well as techniques of pre and post processing of signal via software GNU/Octave

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

Quantitative end qualitative analysis of the electrical activity of rectus abdominis muscle portions

The purpose of this study was to investigate the electrical behavior pattern of the Rectus abdominis muscle by qualitative and quantitative analysis of the electromyographic signal obtained from its superior, medium and inferior portions during dynamic and static activities. Ten voluntaries (aged X = 17.8 years, SD = 1.6) athletic males were studied without history of muscle skeletal disfunction. For the quantitative analysis the RMS (Root Mean Square) values obtained in the electromyographic signal during the isometric exercises were normalized and expressed in maximum voluntary isometric contraction percentages. For the qualitative analysis of the dynamic activity the electromyographic signal was processed by full-wave rectification, linear envelope and normalization (amplitude and time), so that the resulting curve of the processed signal was submitted to descriptive graphic analysis. The results of the quantitative study show that there is not a statistically significant difference among the portions of the muscle. Qualitative analysis demonstrated two aspects: the presence of a common activation electric pattern in the portions of Rectus abdominis muscle and the absence of significant difference in the inclination angles in the electrical activity curve during the isotonic exercises.

A influência da fadiga nos músculos eversores durante a entorse lateral do tornozelo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

In this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification.

Applications of High Speed Configurable Logic Devices in Modern Particle Physics Experiments

Several activities were conducted during my PhD activity. For the NEMO experiment a collaboration between the INFN/University groups of Catania and Bologna led to the development and production of a mixed signal acquisition board for the Nemo Km3 telescope. The research concerned the feasibility study for a different acquisition technique quite far from that adopted in the NEMO Phase 1 telescope. The DAQ board that we realized exploits the LIRA06 front-end chip for the analog acquisition of anodic an dynodic sources of a PMT (Photo-Multiplier Tube). The low-power analog acquisition allows to sample contemporaneously multiple channels of the PMT at different gain factors in order to increase the signal response linearity over a wider dynamic range. Also the auto triggering and self-event-classification features help to improve the acquisition performance and the knowledge on the neutrino event. A fully functional interface towards the first level data concentrator, the Floor Control Module, has been integrated as well on the board, and a specific firmware has been realized to comply with the present communication protocols. This stage of the project foresees the use of an FPGA, a high speed configurable device, to provide the board with a flexible digital logic control core. After the validation of the whole front-end architecture this feature would be probably integrated in a common mixed-signal ASIC (Application Specific Integrated Circuit). The volatile nature of the configuration memory of the FPGA implied the integration of a flash ISP (In System Programming) memory and a smart architecture for a safe remote reconfiguration of it. All the integrated features of the board have been tested. At the Catania laboratory the behavior of the LIRA chip has been investigated in the digital environment of the DAQ board and we succeeded in driving the acquisition with the FPGA. The PMT pulses generated with an arbitrary waveform generator were correctly triggered and acquired by the analog chip, and successively they were digitized by the on board ADC under the supervision of the FPGA. For the communication towards the data concentrator a test bench has been realized in Bologna where, thanks to a lending of the Roma University and INFN, a full readout chain equivalent to that present in the NEMO phase-1 was installed. These tests showed a good behavior of the digital electronic that was able to receive and to execute command imparted by the PC console and to answer back with a reply. The remotely configurable logic behaved well too and demonstrated, at least in principle, the validity of this technique. A new prototype board is now under development at the Catania laboratory as an evolution of the one described above. This board is going to be deployed within the NEMO Phase-2 tower in one of its floors dedicated to new front-end proposals. This board will integrate a new analog acquisition chip called SAS (Smart Auto-triggering Sampler) introducing thus a new analog front-end but inheriting most of the digital logic present in the current DAQ board discussed in this thesis. For what concern the activity on high-resolution vertex detectors, I worked within the SLIM5 collaboration for the characterization of a MAPS (Monolithic Active Pixel Sensor) device called APSEL-4D. The mentioned chip is a matrix of 4096 active pixel sensors with deep N-well implantations meant for charge collection and to shield the analog electronics from digital noise. The chip integrates the full-custom sensors matrix and the sparsifification/readout logic realized with standard-cells in STM CMOS technology 130 nm. For the chip characterization a test-beam has been set up on the 12 GeV PS (Proton Synchrotron) line facility at CERN of Geneva (CH). The collaboration prepared a silicon strip telescope and a DAQ system (hardware and software) for data acquisition and control of the telescope that allowed to store about 90 million events in 7 equivalent days of live-time of the beam. My activities concerned basically the realization of a firmware interface towards and from the MAPS chip in order to integrate it on the general DAQ system. Thereafter I worked on the DAQ software to implement on it a proper Slow Control interface of the APSEL4D. Several APSEL4D chips with different thinning have been tested during the test beam. Those with 100 and 300 um presented an overall efficiency of about 90% imparting a threshold of 450 electrons. The test-beam allowed to estimate also the resolution of the pixel sensor providing good results consistent with the pitch/sqrt(12) formula. The MAPS intrinsic resolution has been extracted from the width of the residual plot taking into account the multiple scattering effect.

Data Mining in Clinical Practice for the Quantification of Motor Impairment in Parkinson's Disease

Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.

Antipodal random sequences with prescribed second-order statistics: application to Compressive Sensing and UWB system based on DS-CDMA

It is usual to hear a strange short sentence: «Random is better than...». Why is randomness a good solution to a certain engineering problem? There are many possible answers, and all of them are related to the considered topic. In this thesis I will discuss about two crucial topics that take advantage by randomizing some waveforms involved in signals manipulations. In particular, advantages are guaranteed by shaping the second order statistic of antipodal sequences involved in an intermediate signal processing stages. The first topic is in the area of analog-to-digital conversion, and it is named Compressive Sensing (CS). CS is a novel paradigm in signal processing that tries to merge signal acquisition and compression at the same time. Consequently it allows to direct acquire a signal in a compressed form. In this thesis, after an ample description of the CS methodology and its related architectures, I will present a new approach that tries to achieve high compression by design the second order statistics of a set of additional waveforms involved in the signal acquisition/compression stage. The second topic addressed in this thesis is in the area of communication system, in particular I focused the attention on ultra-wideband (UWB) systems. An option to produce and decode UWB signals is direct-sequence spreading with multiple access based on code division (DS-CDMA). Focusing on this methodology, I will address the coexistence of a DS-CDMA system with a narrowband interferer. To do so, I minimize the joint effect of both multiple access (MAI) and narrowband (NBI) interference on a simple matched filter receiver. I will show that, when spreading sequence statistical properties are suitably designed, performance improvements are possible with respect to a system exploiting chaos-based sequences minimizing MAI only.

Assessment of vibratory stimulation on neuromuscular system

The thesis analyze a subject of renewed interest in bioengineering, the research and analysis of exercise parameters that maximize the neuromuscular and cardiovascular involvement in vibration treatment. The research activity was inspired by the increasing use of device able to provide localized or whole body vibration (WBV). In particular, the focus was placed on the vibrating platform and the effect that the vibrations have on the neuromuscular system and cardiovascular system. The aim of the thesis is to evaluate the effectiveness and efficiency of vibration applied to the entire body, in particular, it was investigated the effect of WBV on: 1) Oxygen consumption during static and dynamic squat; 2) Resonant frequency of the muscle groups of the lower limbs; 3) Oxygen consumption and electromyographic signals during static and dynamic squat. In the first three chapters are explained the state of the art concerning vibration treatments, the effects of vibration applied to the entire body, with the explanation of the basic mechanisms (Tonic Vibration Reflex, TVR) and the neuromuscular system, with particular attention to the skeletal muscles and the stretch reflex. In the fourth chapter is illustrated the set-up used for the experiments and the software, implemented in LabWindows in order to control the platform and acquire the electromyographic signal. In the fifth chapter were exposed experiments undertaken during the PhD years. In particular, the analysis of Whole Body Vibration effect on neurological and cardiovascular systems showed interesting results. The results indicate that the static squat with WBV produced higher neuromuscular and cardiorespiratory system activation for exercise duration <60 sec. Otherwise, if the single bout duration was higher than 60 sec, the greater cardiorespiratory system activation was achieved during the dynamic squat with WBV while higher neuromuscular activation was still obtained with the static exercise.

Design of a GNSS receiver for the ESEO mission

This thesis was carried out inside the ESA's ESEO mission and focus in the design of one of the secondary payloads carried on board the spacecraft: a GNSS receiver for orbit determination. The purpose of this project is to test the technology of the orbit determination in real time applications by using commercial components. The architecture of the receiver includes a custom part, the navigation computer, and a commercial part, the front-end, from Novatel, with COCOM limitation removed, and a GNSS antenna. This choice is motivated by the goal of demonstrating the correct operations in orbit, enabling a widespread use of this technology while lowering the cost and time of the device’s assembly. The commercial front-end performs GNSS signal acquisition, tracking and data demodulation and provides raw GNSS data to the custom computer. This computer processes this raw observables, that will be both transferred to the On-Board Computer and then transmitted to Earth and provided as input to the recursive estimation filter on-board, in order to obtain an accurate positioning of the spacecraft, using the dynamic model. The main purpose of this thesis, is the detailed design and development of the mentioned GNSS receiver up to the ESEO project Critical Design Review, including requirements definition, hardware design and breadboard preliminary test phase design.

Structural kinetics of transcription activation at the malT promoter of Escherichia coli by UV laser footprinting

We have studied the kinetics of transcriptional initiation and activation at the malT and malTp1 promoters of Escherichia coli using UV laser footprinting. Contrary to previous studies and because of the very rapid signal acquisition by this technique, we can obtain structural information about true reaction intermediates of transcription initiation. The consequences of adding a transcriptional activator, the cAMP receptor protein/cAMP complex (CRP), are monitored in real time, permitting us to assign specific interactions to the activation of discrete steps in transcription initiation. Direct protein–protein contacts between CRP and the RNA polymerase appeared very rapidly, followed by DNA melting around the −10 hexamer. CRP slightly increased the rate of this isomerization reaction but, more importantly, favored the establishment of additional contacts between the DNA upstream of the CRP binding site and RNA polymerase subsequent to open complex formation. These contacts make a major contribution to transcriptional activation by stabilizing open forms of the promoter complex, thereby indirectly accelerating promoter escape. The ensemble of the kinetic, structural signals demonstrated directly that CRP exerts most of its activating effects on the late stages of transcriptional initiation at the malT promoter.

Attenuated T2 relaxation by mutual cancellation of dipole–dipole coupling and chemical shift anisotropy indicates an avenue to NMR structures of very large biological macromolecules in solution

Fast transverse relaxation of 1H, 15N, and 13C by dipole-dipole coupling (DD) and chemical shift anisotropy (CSA) modulated by rotational molecular motions has a dominant impact on the size limit for biomacromolecular structures that can be studied by NMR spectroscopy in solution. Transverse relaxation-optimized spectroscopy (TROSY) is an approach for suppression of transverse relaxation in multidimensional NMR experiments, which is based on constructive use of interference between DD coupling and CSA. For example, a TROSY-type two-dimensional 1H,15N-correlation experiment with a uniformly 15N-labeled protein in a DNA complex of molecular mass 17 kDa at a 1H frequency of 750 MHz showed that 15N relaxation during 15N chemical shift evolution and 1HN relaxation during signal acquisition both are significantly reduced by mutual compensation of the DD and CSA interactions. The reduction of the linewidths when compared with a conventional two-dimensional 1H,15N-correlation experiment was 60% and 40%, respectively, and the residual linewidths were 5 Hz for 15N and 15 Hz for 1HN at 4°C. Because the ratio of the DD and CSA relaxation rates is nearly independent of the molecular size, a similar percentagewise reduction of the overall transverse relaxation rates is expected for larger proteins. For a 15N-labeled protein of 150 kDa at 750 MHz and 20°C one predicts residual linewidths of 10 Hz for 15N and 45 Hz for 1HN, and for the corresponding uniformly 15N,2H-labeled protein the residual linewidths are predicted to be smaller than 5 Hz and 15 Hz, respectively. The TROSY principle should benefit a variety of multidimensional solution NMR experiments, especially with future use of yet somewhat higher polarizing magnetic fields than are presently available, and thus largely eliminate one of the key factors that limit work with larger molecules.