947 resultados para data pre-processing
Resumo:
O estudo das curvas características de um transístor permite conhecer um conjunto de parâmetros essenciais à sua utilização tanto no domínio da amplificação de sinais como em circuitos de comutação. Deste estudo é possível obter dados em condições que muitas vezes não constam na documentação fornecida pelos fabricantes. O trabalho que aqui se apresenta consiste no desenvolvimento de um sistema que permite de forma simples, eficiente e económica obter as curvas características de um transístor (bipolar de junção, efeito de campo de junção e efeito de campo de metal-óxido semicondutor), podendo ainda ser utilizado como instrumento pedagógico na introdução ao estudo dos dispositivos semicondutores ou no projecto de amplificadores transistorizados. O sistema é constituído por uma unidade de condicionamento de sinal, uma unidade de processamento de dados (hardware) e por um programa informático que permite o processamento gráfico dos dados obtidos, isto é, traçar as curvas características do transístor. O seu princípio de funcionamento consiste na utilização de um conversor Digital-Analógico (DAC) como fonte de tensão variável, alimentando a base (TBJ) ou a porta (JFET e MOSFET) do dispositivo a testar. Um segundo conversor fornece a variação da tensão VCE ou VDS necessária à obtenção de cada uma das curvas. O controlo do processo é garantido por uma unidade de processamento local, baseada num microcontrolador da família 8051, responsável pela leitura dos valores em corrente e em tensão recorrendo a conversores Analógico-Digital (ADC). Depois de processados, os dados são transmitidos através de uma ligação USB para um computador no qual um programa procede à representação gráfica, das curvas características de saída e à determinação de outros parâmetros característicos do dispositivo semicondutor em teste. A utilização de componentes convencionais e a simplicidade construtiva do projecto tornam este sistema económico, de fácil utilização e flexível, pois permite com pequenas alterações
Resumo:
This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.
Resumo:
Arguably, the most difficult task in text classification is to choose an appropriate set of features that allows machine learning algorithms to provide accurate classification. Most state-of-the-art techniques for this task involve careful feature engineering and a pre-processing stage, which may be too expensive in the emerging context of massive collections of electronic texts. In this paper, we propose efficient methods for text classification based on information-theoretic dissimilarity measures, which are used to define dissimilarity-based representations. These methods dispense with any feature design or engineering, by mapping texts into a feature space using universal dissimilarity measures; in this space, classical classifiers (e.g. nearest neighbor or support vector machines) can then be used. The reported experimental evaluation of the proposed methods, on sentiment polarity analysis and authorship attribution problems, reveals that it approximates, sometimes even outperforms previous state-of-the-art techniques, despite being much simpler, in the sense that they do not require any text pre-processing or feature engineering.
Resumo:
In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.
Resumo:
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 Sara Cerqueira Pascoal
Resumo:
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
Resumo:
Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.
Resumo:
Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.
Resumo:
Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)
Resumo:
Inspired by the relational algebra of data processing, this paper addresses the foundations of data analytical processing from a linear algebra perspective. The paper investigates, in particular, how aggregation operations such as cross tabulations and data cubes essential to quantitative analysis of data can be expressed solely in terms of matrix multiplication, transposition and the Khatri–Rao variant of the Kronecker product. The approach offers a basis for deriving an algebraic theory of data consolidation, handling the quantitative as well as qualitative sides of data science in a natural, elegant and typed way. It also shows potential for parallel analytical processing, as the parallelization theory of such matrix operations is well acknowledged.
Resumo:
Over the past decades, several sensitive post-electrophoretic stains have been developed for an identification of proteins in general, or for a specific detection of post-translational modifications such as phosphorylation, glycosylation or oxidation. Yet, for a visualization and quantification of protein differences, the differential two-dimensional gel electrophoresis, termed DIGE, has become the method of choice for a detection of differences in two sets of proteomes. The goal of this review is to evaluate the use of the most common non-covalent and covalent staining techniques in 2D electrophoresis gels, in order to obtain maximal information per electrophoresis gel and for an identification of potential biomarkers. We will also discuss the use of detergents during covalent labeling, the identification of oxidative modifications and review influence of detergents on finger prints analysis and MS/MS identification in relation to 2D electrophoresis.
Resumo:
This paper presents reflexions about statistical considerations on illicit drug profiling and more specifically about the calculation of threshold for determining of the seizure are linked or not. The specific case of heroin and cocaine profiling is presented with the necessary details on the target profiling variables (major alkaloids) selected and the analytical method used. Statistical approach to compare illicit drug seizures is also presented with the introduction of different scenarios dealing with different data pre-treatment or transformation of variables.The main aim consists to demonstrate the influence of data pre-treatment on the statistical outputs. A thorough study of the evolution of the true positive rate (TP) and the false positive rate (FP) in heroin and cocaine comparison is then proposed to investigate this specific topic and to demonstrate that there is no universal approach available and that the calculations have to be revaluate for each new specific application.
Resumo:
Realistic rendering animation is known to be an expensive processing task when physically-based global illumination methods are used in order to improve illumination details. This paper presents an acceleration technique to compute animations in radiosity environments. The technique is based on an interpolated approach that exploits temporal coherence in radiosity. A fast global Monte Carlo pre-processing step is introduced to the whole computation of the animated sequence to select important frames. These are fully computed and used as a base for the interpolation of all the sequence. The approach is completely view-independent. Once the illumination is computed, it can be visualized by any animated camera. Results present significant high speed-ups showing that the technique could be an interesting alternative to deterministic methods for computing non-interactive radiosity animations for moderately complex scenarios
Resumo:
Of the approximately 25,000 bridges in Iowa, 28% are classified as structurally deficient, functionally obsolete, or both. Because many Iowa bridges require repair or replacement with a relatively limited funding base, there is a need to develop new bridge materials that may lead to longer life spans and reduced life-cycle costs. In addition, new and effective methods for determining the condition of structures are needed to identify when the useful life has expired or other maintenance is needed. Due to its unique alloy blend, high-performance steel (HPS) has been shown to have improved weldability, weathering capabilities, and fracture toughness than conventional structural steels. Since the development of HPS in the mid-1990s, numerous bridges using HPS girders have been constructed, and many have been economically built. The East 12th Street Bridge, which replaced a deteriorated box girder bridge, is Iowa’s first bridge constructed using HPS girders. The new structure is a two-span bridge that crosses I-235 in Des Moines, Iowa, providing one lane of traffic in each direction. A remote, continuous, fiber-optic based structural health monitoring (SHM) system for the bridge was developed using off-the-shelf technologies. In the system, sensors strategically located on the bridge collect raw strain data and then transfer the data via wireless communication to a gateway system at a nearby secure facility. The data are integrated and converted to text files before being uploaded automatically to a website that provides live strain data and a live video stream. A data storage/processing system at the Bridge Engineering Center in Ames, Iowa, permanently stores and processes the data files. Several processes are performed to check the overall system’s operation, eliminate temperature effects from the complete strain record, compute the global behavior of the bridge, and count strain cycles at the various sensor locations.
Resumo:
Yleisesti tiedetään hitsin pintageometrian vaikuttavan rakenteen väsymislujuuteen. Nopean, edullisen ja luotettavan pintageometrian mittausmenetelmän kehittäminen on askel kohti tarkempaa ja varmempaa rakenteen väsymislujuuden tarkastelua. Tässä työssä on tutkittu hitsejä, joiden pinnan geometria on mitattu norjalaisen SINTEF -yrityksen kehittämällä rakenteellisen valon menetelmällä. Osana työtä kehitettiin MatLab -pohjainen ohjelma, jolla jälkikäsitellään mittauksesta saadut x-y-z -mittapisteet. Mittausdatan jälkikäsittelyssä saadaan mittauksesta määritettyähitsin reunan pyöristys, liittymäkulma, a-mitta, reunahaava ja kateettisuhde. Kehitettyä menetelmää käyttämällä mitattiin lähes 300 voimaakantamatontaristiliitoksen hitsiä. Mittaustuloksia verrattiin vastaavista kappaleista tehtyihin hiemittauksiin. Manuaalisen hieestä tehdyn mittauksen havaittiin olevan tarkempi ja pystyttiin havaitsemaan paikallisempia muotoja. Rakenteellisen valon mittauksissa tapahtunut heijastelu saatiin pienenemään käsittelemällä mitattava pinta mattavalkoisella maalilla. Rakenteellisen valon mittatarkkuudeksi saatiin noin 0,2 mm. Pohjautuen mitattuun hitsin reunan pyöristykseen ja liittymäkulmaan voidaan yksinkertaista kaavaa käyttämällä laskea hitsin jännityskonsentraatio ja näin saada alkuarvaus väsymislujuudelle. Myös muiden tekijöiden tiedetään vaikuttavan hitsin väsymislujuuteen, joten pyöristyksen ja liittymäkulman avulla tehdyt arviot eivät ole absoluuttisen oikeita. Tämä havaittiin väsytyskokeilla, joista yhdessä väsymisvaurio ei syntynyt suurimmankaan jännityskonsentraation alueella.