Cross recurrence quantification for cover song identification

There is growing evidence that nonlinear time series analysis techniques can be used to successfully characterize, classify, or process signals derived from realworld dynamics even though these are not necessarily deterministic and stationary. In the present study we proceed in this direction by addressing an important problem our modern society is facing, the automatic classification of digital information. In particular, we address the automatic identification of cover songs, i.e. alternative renditions of a previously recorded musical piece. For this purpose we here propose a recurrence quantification analysis measure that allows tracking potentially curved and disrupted traces in cross recurrence plots. We apply this measure to cross recurrence plots constructed from the state space representation of musical descriptor time series extracted from the raw audio signal. We show that our method identifies cover songs with a higher accuracy as compared to previously published techniques. Beyond the particular application proposed here, we discuss how our approach can be useful for the characterization of a variety of signals from different scientific disciplines. We study coupled Rössler dynamics with stochastically modulated mean frequencies as one concrete example to illustrate this point.

Aquatic weed automatic classification using machine learning techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Image processing algorithm for the identification of Martian dust devil tracks in MOC and HiRISE images

This paper presents a method for automatic identification of dust devils tracks in MOC NA and HiRISE images of Mars. The method is based on Mathematical Morphology and is able to successfully process those images despite their difference in spatial resolution or size of the scene. A dataset of 200 images from the surface of Mars representative of the diversity of those track features was considered for developing, testing and evaluating our method, confronting the outputs with reference images made manually. Analysis showed a mean accuracy of about 92%. We also give some examples on how to use the results to get information about dust devils, namelly mean width, main direction of movement and coverage per scene. (c) 2012 Elsevier Ltd. All rights reserved.

An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

Fault identification in distribution lines using intelligent systems and statistical methods

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.

What is the importance of selecting features for non-technical losses identification?

Although non-technical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy has not attracted much attention in this context. In this paper, we focus on this problem applying a novel feature selection algorithm based on Particle Swarm Optimization and Optimum-Path Forest. The results demonstrated that this method can improve the classification accuracy of possible frauds up to 49% in some datasets composed by industrial and commercial profiles. © 2011 IEEE.

Improving Parkinson's disease identification through evolutionary-based feature selection

Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification. © 2011 IEEE.

Automatic risk evaluation in elderly patients based on Autonomic Nervous System assessment

Dysfunction of Autonomic Nervous System (ANS) is a typical feature of chronic heart failure and other cardiovascular disease. As a simple non-invasive technology, heart rate variability (HRV) analysis provides reliable information on autonomic modulation of heart rate. The aim of this thesis was to research and develop automatic methods based on ANS assessment for evaluation of risk in cardiac patients. Several features selection and machine learning algorithms have been combined to achieve the goals. Automatic assessment of disease severity in Congestive Heart Failure (CHF) patients: a completely automatic method, based on long-term HRV was proposed in order to automatically assess the severity of CHF, achieving a sensitivity rate of 93% and a specificity rate of 64% in discriminating severe versus mild patients. Automatic identification of hypertensive patients at high risk of vascular events: a completely automatic system was proposed in order to identify hypertensive patients at higher risk to develop vascular events in the 12 months following the electrocardiographic recordings, achieving a sensitivity rate of 71% and a specificity rate of 86% in identifying high-risk subjects among hypertensive patients. Automatic identification of hypertensive patients with history of fall: it was explored whether an automatic identification of fallers among hypertensive patients based on HRV was feasible. The results obtained in this thesis could have implications both in clinical practice and in clinical research. The system has been designed and developed in order to be clinically feasible. Moreover, since 5-minute ECG recording is inexpensive, easy to assess, and non-invasive, future research will focus on the clinical applicability of the system as a screening tool in non-specialized ambulatories, in order to identify high-risk patients to be shortlisted for more complex investigations.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

Radio frequency identification and its application in e-commerce

This chapter presents Radio Frequency Identification (RFID), which is one of the Automatic Identification and Data Capture (AIDC) technologies (Wamba and Boeck, 2008) and discusses the application of RFID in E-Commerce. Firstly RFID is defined and the tag and reader components of the RFID system are explained. Then historical context of RFID is briefly discussed. Next, RFID is contrasted with other AIDC technologies, especially the use of barcodes which are commonly applied in E-Commerce. Lastly, RFID applications in E-Commerce are discussed with the focus on achievable benefits and obstacles to successful applications of RFID in E-Commerce, and ways to alleviate them.

Combining Leaf Shape and Texture for Costa Rican Plant Species Identification

In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap’s underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant. Further statistical analysis of visual noise impact, best algorithm combinations per species, and best value of , the minimal cardinality of the set of candidate species that the tested algorithms render as best matches is also presented in this research

Automatic Counting of Microglial Cells in Healthy and Glaucomatous Mouse Retinas

Proliferation of microglial cells has been considered a sign of glial activation and a hallmark of ongoing neurodegenerative diseases. Microglia activation is analyzed in animal models of different eye diseases. Numerous retinal samples are required for each of these studies to obtain relevant data of statistical significance. Because manual quantification of microglial cells is time consuming, the aim of this study was develop an algorithm for automatic identification of retinal microglia. Two groups of adult male Swiss mice were used: age-matched controls (naïve, n = 6) and mice subjected to unilateral laser-induced ocular hypertension (lasered; n = 9). In the latter group, both hypertensive eyes and contralateral untreated retinas were analyzed. Retinal whole mounts were immunostained with anti Iba-1 for detecting microglial cell populations. A new algorithm was developed in MATLAB for microglial quantification; it enabled the quantification of microglial cells in the inner and outer plexiform layers and evaluates the area of the retina occupied by Iba-1+ microglia in the nerve fiber-ganglion cell layer. The automatic method was applied to a set of 6,000 images. To validate the algorithm, mouse retinas were evaluated both manually and computationally; the program correctly assessed the number of cells (Pearson correlation R = 0.94 and R = 0.98 for the inner and outer plexiform layers respectively). Statistically significant differences in glial cell number were found between naïve, lasered eyes and contralateral eyes (P<0.05, naïve versus contralateral eyes; P<0.001, naïve versus lasered eyes and contralateral versus lasered eyes). The algorithm developed is a reliable and fast tool that can evaluate the number of microglial cells in naïve mouse retinas and in retinas exhibiting proliferation. The implementation of this new automatic method can enable faster quantification of microglial cells in retinal pathologies.

Post-processing and visualization techniques in 2D boundary element analysis

Most post-processors for boundary element (BE) analysis use an auxiliary domain mesh to display domain results, working against the profitable modelling process of a pure boundary discretization. This paper introduces a novel visualization technique which preserves the basic properties of the boundary element methods. The proposed algorithm does not require any domain discretization and is based on the direct and automatic identification of isolines. Another critical aspect of the visualization of domain results in BE analysis is the effort required to evaluate results in interior points. In order to tackle this issue, the present article also provides a comparison between the performance of two different BE formulations (conventional and hybrid). In addition, this paper presents an overview of the most common post-processing and visualization techniques in BE analysis, such as the classical algorithms of scan line and the interpolation over a domain discretization. The results presented herein show that the proposed algorithm offers a very high performance compared with other visualization procedures.

Prototipagem de um sistema de gestão de armazém com recurso à identificação por radiofrequência

A evolução tecnológica atingiu um ritmo que muitas empresas têm dificuldade de acompanhar, existem diversas opções no mercado, para um mesmo objectivo, e tornasse determinante o processo de tomada de decisão sobre qual tecnologia adoptar para determinado objectivo. O alvo de estudo desta dissertação de mestrado, é uma das tecnologias, que últimamente tem ganho especial relevo, quando aplicada ao ambiente industrial, o RFID (Radio Frequency Identification Devices). Na presente dissertação, foi efectuado um levantamento do estado da arte, na área da identificação automática, com especial foco no RFID. Esta revisão bibliográfica teve como principal objectivo perceber quais as tecnologias concorrentes do RFID, e explorar quais as suas principais características tecnológicas e funcionais, bem como as vantagens no uso desta tecnologia de forma a sustentar a implementação de um sistema protótipo de gestão de armazém. O contributo final da dissertação, consiste numa aplicação que tem como principal objectvo simular os fluxos de infomação resultantes dos fluxos fisícos de materiais em ambiente de armazém. Foi também tido em conta no desenvolvimento da aplicação, a demonstração de algumas das mais valias que esta tecnologia pode trazer para a gestão de armazéns. Para implementação da aplicação destaca-se a utilização da arquitectura MVC (Model-view-controlador), em ambiente web, para permitir uma descentalização do software no ambiente indoor do armazém.

Métodos de avaliação do impacto económico dos eventos adversos em meio hospitalar

RESUMO - O sistema de saúde é constantemente sujeito a pressões sendo as mais relevantes a pressão para o aumento da qualidade e a necessidade de contenção de custos. Os Eventos Adversos (EAs) ocorridos em meio hospitalar constituem um sério problema de qualidade na prestação de cuidados de saúde, com consequências clinicas, sociais, económicas e de imagem, que afectam pacientes, profissionais, organizações e o próprio sistema de saúde. Os custos associados à ocorrência de EAs em meio hospitalar, incrementam significativamente os custos hospitalares, representando cerca de um em cada sete dólares gastos no atendimento dos doentes. Só na última década surgiram estudos com o objectivo principal de avaliar esse impacto em meio hospitalar, subsistindo ainda uma grande indefinição quanto às variáveis e métodos a utilizar. O objectivo principal deste trabalho de projecto foi conhecer e caracterizar as diferentes metodologias utilizadas para avaliação dos custos económicos, nomeadamente dos custos directos, relacionados com a ocorrência de eventos adversos em meio hospitalar. Tendo em atenção as dificuldades referidas, utilizou-se como metodologia a revisão narrativa da literatura, complementada com a realização de uma técnica de grupo nominal. Os resultados obtidos foram os seguintes: i) a metodologia utilizada na maioria dos estudos para determinar a frequência, natureza e consequências dos EAs ocorridos em meio hospitalar, utiliza matrizes de base observacional, analítica, com base em estudos de coorte retrospectivo recorrendo aos critérios definidos pelo Harvard Medical Practice Study; ii) a generalidade dos estudos realizados avaliam os custos directos dos EAs em meio hospitalar, iii) verificou-se a existência de uma grande diversidade de métodos para a determinação dos custos associados aos EAs. A generalidade dos estudos determina esse valor com base na contabilização do número de dias adicionais de internamento, resultantes do EA, valorizados com base em custos médios; iv) o grupo de peritos, propôs como metodologia para a determinação do custo associado a cada EA, a utilização de sistemas de custeio por doente; v) propõe-se o desenvolvimento de uma plataforma informática, que permita o cruzamento da informação disponível no registo clinico electrónico do doente com um sistema automático de identificação de EAs, a desenvolver, e com sistemas de custeio por doente, de modo a valorizar os custos por doente e por tipo de EA. A avaliação dos custos directos associados à ocorrência de EAs em contexto hospitalar, pelo impacto económico e social que tem nos doentes e organizações, será seguramente uma das áreas de estudo e investigação futuras, no sentido de melhorar a eficiência do sistema de saúde e a qualidade e segurança dos cuidados prestados aos doentes.