Propostas de técnicas para caracterização e classificação automática de sons pulmonares adventícios

In this thesis, the investigation of methods to characterize and classify adventitious lung sounds by spectral analysis is described. To accomplish this task, two novel techniques were developed, through Multiressolution Analysis, based on the Discrte Wavelet Transform. The first technique aims to detect abnormal sounds and classity them info four groups: normal, continuous and discontinuous adventitions lung sounds, also notifying their simultaneous occurence. During its processing, the respiratory cycle signal is decomposed up to its tenth level, and the energy present in the detail and approximation coefficients for each decomposition level is calculated, resulting on a curve of energy versus decomposition level. The resulting curves show different signatures for each kind of adventitious sound. These signatures are used as data source for a classifier system based on Radial Basis Function Artificial Neural Networks. This technique was tested for ten different wavelets, training a hundred neural networks for each wavelet, totalizing a thousand neural networks trained. The best performance rates for each wavelet reach values from 88% to 92.36% for the test group, in a set of 275 respiratory cycles. In the second technique, named Filtering by Selective Spectral Analysis, the lung sound is decomposed until its fourth level, the approximation coefficients spectra are calculatedand, based on the highest frequency component found on those coefficients, a multiband FIR filter is determined. This filter is used to eliminate all frequency components in the approximation coefficients except the highest one. After the filtering procedure, the signal is recomposed by wavelet reconstruction. In order to evaluate the proposed technique, ten wavelets were used in the decomposition and reconstruction stages. The wavelet which presented the best performance attenuated heart sounds 6 dB more than the adventitious sounds that occur in the same spectral band. For measuring this attenuation, the Power Spectral Density was used. This procedure showed satisfactory results, elimination the normal airflow noise and cardiac sounds, leaving only the adventitious sounds in the recorded lung sounds.Nesta tese, descrevem-se técnicas matemáticas visando a caracterização e classificação de sons pulmonares adventícios, por meio de sua análise espectral. Para alcançar este objetivo, desenvolveu-se duas novas metodologias, que utilizam Análise em Multiresolução, implementada a partir da Transformada Wavelet Discreta. A primeira metodologia desenvolvida é utilizada para classificar automaticamente os sons pulmonares em quatro grupos: sons normais e sons adventícios contínuos e descontínuos, notificando também o caso de ocorrência das duas anomalias no mesmo ciclo respiratório. Durante o processamento, o ciclo respiratório é decomposto até seu décimo nível, calculando a energia dos coeficientes detalhe em cada nível de decomposição, assim como a energia dos coeficientes de aproximação. Deste cálculo, obtém-se uma curva de variação da energia em relação ao nível de decomposição, sendo que as curvas obtidas se mostraram curvas caracterísitcas em relação ao tipo de som adventício. Tais curvas são aplicadas a uma simulação de Rede Neural Artificial de Função de Base Radial, que atua como classificador entre os quatro grupos. Esta técnica foi testada utilizando dez wavelets, sendo treinadas cem redes neurais para cada uma. Os melhores resultados apresentaram índice de acerto entre 88% e 92,36% para o conjunto de teste, em um total de 275 ciclos respiratórios. A segunda metodologia, denominada Filtragem por Análise Espectral Seletiva, decompõe o som pulmonar até seu quarto nível, calculando o espectro dos coeficientes aproximação e, baseado na componente de frequência prepoderante, calcula um filtro FIR multibanda. Este filtro é utilizado para eliminar todas as {sic} componentes espectrais dos coeficientes de aproximação, com exceção do mais proeminente. Após o procedimento de filtragem, o sinal é recomposto através de reconstrução wavelet. Para a avaliação de seus resultados, foram testadas dez wavelets no processo de decomposição e reconstrução. Para a wavelet que apresentou melhores resultados, obteve-se uma atenuação dos sons cardíacos da ordem de 6dB em relação aos sons adventícios que ocorrem na mesma faixa espectral, utilizando a Densidade Espectral de Potência dos sinais como referência. Esta metodologia mostrou resultados satisfatórios na tarefa de eliminar tanto os ruídos relativos ao fluxo aéreo normal nas vias aeríferas quanto os sons cardíacos, mantendo somente os sons adventícios nas gravações de sons pulmonares

Graph machine learning approaches to classifying the building and ground relationship Architectural 3D topological model to retrieve similar architectural precendents

Architects struggle to choose the best form of how the building meets the ground and may benefit from a suggestion based on precedents. A precedent suggestion may help architects decide how the building should meet the ground. Machine learning (ML), as a part of artificial intelligence (AI), can play a role in the following scenario to determine the most appropriate relationship from a set of examples provided by trained architects. A key feature of the system involves its classification of three-dimensional (3D) prototypes of architectural precedent models using a topological graph instead of two-dimensional (2D) images to classify the models. This classified model then predicts and retrieves similar architecture precedents to enable the designer to develop or reconsider their design. The research methodology uses mixed methods research. A qualitative interview validates the taxonomy collected in the literature review and image sorting survey to study the similarity of human classification of the building and ground relationship (BGR). Moreover, the researcher leverages the use of two primary technologies in the development of the BGR tool. First, a software library enhances the representation of 3D models by using non-manifold topology (Topologic). The second phase involves an end-to-end deep graph convolutional neural network (DGCNN). This study employs a two-stage experimental workflow. The first step sees a sizable synthetic database of building relationships and ground topologies created by generative simulation for a 3D prototype of architectural precedents. These topologies then undergo conversion into semantically rich topological dual graphs. Second, the prototype architectural graphs are imported to the DGCNN model for graph classification. This experiment's results show that this approach can recognise architectural forms using more semantically relevant and structured data and that using a unique data set prevents direct comparison. Our experiments have shown that the proposed workflow achieves highly accurate results that align with DGCNN’s performance on benchmark graphs. Additionally, the study demonstrates the effectiveness of using different machine learning approaches, such as Deep Graph Library (DGL) and Unsupervised Graph Level Representation Learning (UGLRL). This research demonstrates the potential of AI to help designers identify the topology of architectural solutions and place them within the most relevant architectural canons

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Particle Physics Reference Library

This second open access volume of the handbook series deals with detectors, large experimental facilities and data handling, both for accelerator and non-accelerator based experiments. It also covers applications in medicine and life sciences. A joint CERN-Springer initiative, the “Particle Physics Reference Library” provides revised and updated contributions based on previously published material in the well-known Landolt-Boernstein series on particle physics, accelerators and detectors (volumes 21A,B1,B2,C), which took stock of the field approximately one decade ago. Central to this new initiative is publication under full open access

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma

Usability analysis of contending electronic health record systems

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe