Electric vehicle adopters in Lisbon: motivation, utilization patterns and environmental impacts

The introduction of alternative vehicle technologies as a response to pressure regarding fossil fuel dependency in the transportation sector poses several questions regarding their impact on travel and driving behaviour and also on the environment. This project aims to assess electric vehicle users’ motivations, daily patterns and vehicle operation and management. Promoted by EMEL – Lisbon’s mobility and parking municipal company – the project was publicized among Lisbon’s electric vehicle users, who were offered, as an incentive, a green permit which allowed them to park the vehicles for free on the street within the city’s metropolitan central area. Data were gathered over a period of one year from 25 users (private and fleet drivers) through interviews and on-board diaries, comprising a total of 5,132 trips, 49,785 km travelled and a total of 8,529 kWh charged related to 831 charges. The results indicate that environmental and economic (lower running costs) factors are the main drivers for electric vehicle adoption by private users, whereas fleet drivers mention their company’s image as the motive behind the deployment of this technology in fleets. Private users’ energy consumption and CO2 emissions were also estimated. When compared to conventional internal combustion engine vehicles running on gasoline or diesel, electric vehicles reveal considerable reductions in both energy consumption and CO2 emissions in a Well-to-Wheel life cycle approach. These decreases are between 35–43% for energy consumption and 58–63% for CO2 emissions

Impacts of On-board Devices and Training on Light Duty Vehicle Driving Behavior

AbstractThe main objective of this investigation was to assess the impacts of an eco-driving education session on the energy and environmental performance of a group of drivers as well as changes on their driving patterns. Driving behavior was assessed with an on-board monitoring device, the CarChip Pro. This on-board data logger allowed the characterization of driving patterns, collecting data regarding driving parameters - such as speed and acceleration - and engine parameters. Potential savings in fuel consumption and reduction of CO2 and NOx emissions were assessed based on the VSP “Vehicle Specific Power” methodology.A sample of 20 drivers was monitored in two distinct periods. Two groups were defined. A group of 9 drivers received at the end of the first monitoring period, an eco-driving educational session, where information regarding which conducts should be adopted in order to assume a more ecological driving behavior was shared as well as insight concerning their driving performance was given. The remaining drivers received no information. A total of 1364 days and 1928hours of driving were monitored, corresponding to 8137 trips and 100212km travelled. The results show that, after the eco-driving education session, drivers decreased the time spent in excessive speed and excessive engine speed by 24% and 38% respectively. A reduction in the number of events such as extreme accelerations and decelerations was also observed. The results indicate an average 4.8% fuel consumption decrease, corresponding to savings of 0.09MJ/km and 6.56g/km of CO2 emissions in the Tank-To-Wheel stage. Concerning NOx emissions a decrease of 8% was observed for this experimental group

Source Classification in Atrial Fibrillation Using a Machine Learning Approach

International audienceA precise analysis of the atrial activity (AA) signal in electrocardiogram (ECG) recordings is necessary for a better understanding of the mechanisms behind atrial fibrillation (AF). Blind source separation (BSS) techniques have proven useful in extracting the AA source from ECG recordings. However, the automated selection of the AA source among the other sources after BSS is still an issue. In this scenario, the present work proposes two contributions: i) the use of the normalized mean square error of the TQ segment (NMSE-TQ) as a new feature to quantify the AA content of a source, and ii) an automated classification of AA and non-AA sources using three well-known machine learning algorithms. The tested classifiers outperform the techniques present in literature. A pattern in the mean and standard deviation of the used features, for AA and non-AA sources, is also observed

ULTRASOUND AS TOOL FOR DIAGNOSIS OF DISEASES OF THE REPRODUCTIVE TRACT BULLS

AbstractThe purpose of this study was to evaluate by ultrasound and breeding soundness examination (BSE) the major diseases affecting the reproductive system of Nelore bulls, bred extensively in the state of Para, Brazil. Fifty-nine pure Nelore bulls were used, aged between 5 to 10 years, raised extensively in a commercial farm in the municipality of Paragominas, Pará state, Brazil.  Scrotal circumference, testicular length and width were measured. Semen collection for evaluation of ejaculate volume, turbulence, motility, vigor, concentration and sperm pathologies was performed. Ultrasound examination was performed by equipment type Ultrasonic Transducer - CHISON/D600vet, linear transducers, where the frequency used was 5 MHz, being held two images of each testis, the longitudinal-lateral, lateral and transverse planes. The images were processed using the program Image J. The data were analyzed using the statistical program SAS (2000) and means were compared using Tukey's test (p 0.05). Thus, it can be concluded that ultrasonography is an essential complementary tool in the diagnosis of reproductive disorders in animals subjected to BSE and its use should be recommended

MultiS: A Context-Server for Pervasive Computing

AbstractContext-aware applications are capable of recognizing environmental changes and adapting their behavior to the new context. This process can be divided into three stages: monitoring, context recognition and adaptation. On the monitoring layer, raw information about the environment is collected from sensors. The context recognition layer processes the data acquired from the context and transforms it into information which can be useful for the adaptation process. With this information, the adaptation system can determine what behavior is correct for the application in each different context. This paper proposes a context server called MultiS, which has the goal of solving the problems arising from the context recognition layer, and which includes the following advantages: a) the production of new context data based on the information of several sensors and an ability to react to changes in the environment; b) definition of a composed language for the context data called CD-XML; c) support for mobility

Pseudo-Hermitian continuous-time quantum walks

In this paper we present a model exhibiting a new type of continuous-time quantum walk (as a quantum mechanical transport process) on networks, which is described by a non-Hermitian Hamiltonian possessing a real spectrum. We call it pseudo-Hermitian continuous-time quantum walk. We introduce a method to obtain the probability distribution of walk on any vertex and then study a specific system. We observe that the probability distribution on certain vertices increases compared to that of the Hermitian case. This formalism makes the transport process faster and can be useful for search algorithms.Comment: 13 page, 7 figure

Asymptotic entanglement in a two-dimensional quantum walk

The evolution operator of a discrete-time quantum walk involves a conditional shift in position space which entangles the coin and position degrees of freedom of the walker. After several steps, the coin-position entanglement (CPE) converges to a well defined value which depends on the initial state. In this work we provide an analytical method which allows for the exact calculation of the asymptotic reduced density operator and the corresponding CPE for a discrete-time quantum walk on a two-dimensional lattice. We use the von Neumann entropy of the reduced density operator as an entanglement measure. The method is applied to the case of a Hadamard walk for which the dependence of the resulting CPE on initial conditions is obtained. Initial states leading to maximum or minimum CPE are identified and the relation between the coin or position entanglement present in the initial state of the walker and the final level of CPE is discussed. The CPE obtained from separable initial states satisfies an additivity property in terms of CPE of the corresponding one-dimensional cases. Non-local initial conditions are also considered and we find that the extreme case of an initial uniform position distribution leads to the largest CPE variation.Comment: Major revision. Improved structure. Theoretical results are now separated from specific examples. Most figures have been replaced by new versions. The paper is now significantly reduced in size: 11 pages, 7 figure