Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Dynamical behaviour on the parameter space: new populational growth models proportional to beta densities

We present new populational growth models, generalized logistic models which are proportional to beta densities with shape parameters p and 2, where p > 1, with Malthusian parameter r. The complex dynamical behaviour of these models is investigated in the parameter space (r, p), in terms of topological entropy, using explicit methods, when the Malthusian parameter r increases. This parameter space is split into different regions, according to the chaotic behaviour of the models.

Controlo de tráfego

O crescente número de automóveis nas ruas das grandes cidades, assim como o crescente número de transportes urbanos para atender o crescimento das populações, veio fazer com que as cidades cada vez mais fiquem mais congestionadas e mais propícias para acidentes envolvendo viaturas e peões. Devido a isso, foram criados sistemas de controlo de tráfego capazes de melhorar o tráfego urbano nas cidades, sem deixar de lado as preocupações com os peões e nem com as emissões de poluentes para o ar. Baseado nesse cenário, este trabalho tem como objetivo abordar as possíveis soluções existentes no mercado para melhorar o fluxo das viaturas, principalmente dos transportes colectivos, com prioridades para viaturas de emergências e autocarros, assim como, as passagens de peões, e sistemas de mobilidade urbana. Desempenho do transporte público pode ser melhorado através de um melhor controlo e gerenciamento de tráfego em geral. Nos testes realizados em campo: foi medida a velocidade de viagem do autocarro no cruzamento fixo (Praça de Espanha), e correlacionando-os com intervalos do ciclo dos semáforos para este cruzamento. A flexibilidade do controlador actuando, com o auxílio de detectores de veículos, sendo capaz de variar os intervalos dentro do ciclo, bem como o volume de carros e de prestações em velocidade de viagem do autocarro. Resultados mostram que, durante o período em estudo, os benefícios de velocidade da viagem do autocarro, seria possível, através de um verdadeiro controlo de tempo feedback de cooperação entre as áreas urbanas de controlo de tráfego (Gertrude) e do sistema de localização de veículos de transportes públicos (SAEIP). Ao longo prazo, sugerimos a implantação de um sistema integrado. Fazendo com que o volume no carro seja reduzido. Este efeito leva também, a um aumento da velocidade comercial do autocarro urbano, da mesma forma como foi proposto em nossa experiência.

Integrated vehicle classification system

This paper presents an integrated system for vehicle classification. This system aims to classify vehicles using different approaches: 1) based on the height of the first axle and_the number of axles; 2) based on volumetric measurements and; 3) based on features extracted from the captured image of the vehicle. The system uses a laser sensor for measurements and a set of image analysis algorithms to compute some visual features. By combining different classification methods, it is shown that the system improves its accuracy and robustness, enabling its usage in more difficult environments satisfying the proposed requirements established by the Portuguese motorway contractor BRISA.

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Short-term Feature Space and Music Genre Classification

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.

Smart Electric Vehicle Charging System

In this work is proposed the design of a system to create and handle Electric Vehicles (EV) charging procedures, based on intelligent process. Due to the electrical power distribution network limitation and absence of smart meter devices, Electric Vehicles charging should be performed in a balanced way, taking into account past experience, weather information based on data mining, and simulation approaches. In order to allow information exchange and to help user mobility, it was also created a mobile application to assist the EV driver on these processes. This proposed Smart ElectricVehicle Charging System uses Vehicle-to-Grid (V2G) technology, in order to connect Electric Vehicles and also renewable energy sources to Smart Grids (SG). This system also explores the new paradigm of Electrical Markets (EM), with deregulation of electricity production and use, in order to obtain the best conditions for commercializing electrical energy.

The electric vehicle integration into the power system: an application to the portuguese case

Electric vehicles (EV) offer a great potential to address the integration of renewable energy sources (RES) in the power grid, and thus reduce the dependence on oil as well as the greenhouse gases (GHG) emissions. The high share of wind energy in the Portuguese energy mix expected for 2020 can led to eventual curtailment, especially during the winter when high levels of hydro generation occur. In this paper a methodology based on a unit commitment and economic dispatch is implemented, and a hydro-thermal dispatch is performed in order to evaluate the impact of the EVs integration into the grid. Results show that the considered 10 % penetration of EVs in the Portuguese fleet would increase load in 3 % and would not integrate a significant amount of wind energy because curtailment is already reduced in the absence of EVs. According to the results, the EV is charged mostly with thermal generation and the associated emissions are much higher than if they were calculated based on the generation mix.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

Aplicações e algoritmos de segurança rodoviária com o uso de sistemas de GPS e de comunicações WAVE

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Modelling and aerodynamic simulation of a vehicle and failure analysis of a laminated front fender

Master Thesis in Mechanical Engineering field of Maintenance and Production

East of Suez and the imaginary tangles of space and self

Drawing on postcolonial studies and the theorization on imperial gothic, this paper centres on three texts: The Hosts of the Lord (1900) by Flora Annie Steel; East of Suez (1901) by Alice Perrin, and The Way of an Eagle (1912)by Ethel Dell. These three texts highlight in different ways the discursive mediation of the Other and its destabilizing effects on the identity of the European-minded colonizer, thus foregrounding the multifarious nature of the British imaginative engagement with India. In this context, it is particularly relevant to examine the political and ideological implications of representing anywhere East of Suez as a locus of primitivism and chaos vis-à-vis the colonizer’s ambivalent reactions. Thus we seek to demonstrate the power of two distinct practices or modes of representation – namely, the power of a metaphorical discourse versus metonymic discourse- within the proces of constructing the East for a vast Western readership.

Red light (Processo contra-ordenacional em meio urbano)

Devido ao acréscimo significativo de viaturas e peões nas grandes cidades foi necessário recorrer aos mecanismos existentes para coordenar o tráfego. Nesta perspectiva surge a implementação de semáforos com o objectivo de ordenar o tráfego nas vias rodoviárias. A gestão de tráfego, tem sido sujeita a inovações tanto ao nível dos equipamentos, do software usado, gestão centralizada, monitorização das vias e na sincronização semafórica, sendo possível a criação de programas ajustados às diferentes exigências de tráfego verificadas durante as vinte e quatro horas para pontos distintos da cidade. Conceptualmente foram elaborados estudos, com o objectivo de identificar a relação entre a velocidade o fluxo e o intervalo num determinado intervalo de tempo, bem como a relação entre a velocidade e a sinistralidade. Até 1995 Portugal era um dos países com maior número de sinistros rodoviários Na sequência desta evolução foram instalados radares de controlo de velocidade no final de 2006 com o objectivo de obrigar ao cumprimento dos limites de velocidade impostos pelo código da estrada e reduzir a sinistralidade automóvel na cidade de Lisboa. Passados alguns anos sobre o investimento realizadoanteriormente, constatamos que existe a necessidade de implementar novas tecnologias na detecção das infracções, sejam estas de excesso de velocidade ou violação do semáforo vermelho (VSV), optimizar a informação disponibilizada aos automobilistas e aos peões, coordenar a interacção entre os veículos prioritários e os restantes presentes na via, dinamizar a gestão interna das contra ordenações, agilizar os procedimentos informatizar a recolha deinformação de modo a tornar os processos mais céleres.

A Spatial Econometrics Analysis for Road Accidents in Lisbon

This paper presents a spatial econometrics analysis for the number of road accidents with victims in the smallest administrative divisions of Lisbon, considering as a baseline a log-Poisson model for environmental factors. Spatial correlation on data is investigated for data alone and for the residuals of the baseline model without and with spatial-autocorrelated and spatial-lagged terms. In all the cases no spatial autocorrelation was detected.