Using floating car data to analyse the effects of ITS measures and eco-driving

The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied.

Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibration data, with calibrations applied independently to the same models in three cases. The sensitivity of modelled yield to changes in temperature and precipitation was tested by systematically modifying values of 1981-2010 baseline weather data to span the range of 19 changes projected for the late 21st century at three locations in Europe.

Evaluation of the PV cell operation temperature in the process of fast switching to open-circuit mode

A procedure for measuring the overheating temperature (ΔT ) of a p-n junction area in the structure of photovoltaic (PV) cells converting laser or solar radiations relative to the ambient temperature has been proposed for the conditions of connecting to an electric load. The basis of the procedure is the measurement of the open-circuit voltage (VO C ) during the initial time period after the fast disconnection of the external resistive load. The simultaneous temperature control on an external heated part of a PV module gives the means for determining the value of VO C at ambient temperature. Comparing it with that measured after switching OFF the load makes the calculation of ΔT possible. Calibration data on the VO C = f(T ) dependences for single-junction AlGaAs/GaAs and triple-junction InGaP/GaAs/Ge PV cells are presented. The temperature dynamics in the PV cells has been determined under flash illumination and during fast commutation of the load. Temperature measurements were taken in two cases: converting continuous laser power by single-junction cells and converting solar power by triple-junction cells operating in the concentrator modules.

New data on the specular reflectance of ores (VNIR: 400 - 1000 nm) and their significance for ore microscopy

This work is part of the project CAMEVA for the development of an expert system aimed at the automatic identification of ores [1, 2]. It relies on the measure of their reflectance values, R, on digital images. Software for calibration, acquisition and analysis of the multispectral data was designed by AITEMIN [3]; the research was also assessed by H.J. Bernhardt and E. Pirard [1].

Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

Calibration process on the study of new antenna array architectures for space communications

This paper introduces novel calibration processes applied to antenna arrays with new architectures and technologies designed to improve the performance of traditional earth stations for satellite communications due to the increasing requirement of data capacity during last decades. Besides, the Radiation Group from the Technical University of Madrid has been working on the development of new antenna arrays based on novel architecture and technologies along many projects as a solution for the ground segment in the early future. Nowadays, the calibration process is an interesting and cutting edge research field in a period of expansion with a lot of work to do for calibration in transmission and also for reception of these novel antennas under development.

Simplifying data acquisition in plant canopies- Measurements of leaf angles with a cell phone

1. Canopies are complex multilayered structures comprising individual plant crowns exposing a multifaceted surface area to sunlight. Foliage arrangement and properties are the main mediators of canopy functions. The leaves act as light traps whose exposure to sunlight varies with time of the day, date and latitude in a trade-off between photosynthetic light harvesting and excessive or photoinhibitory light avoidance. To date, ecological research based upon leaf sampling has been limited by the available echnology, with which data acquisition becomes labour intensive and time-consuming, given the verwhelming number of leaves involved. 2. In the present study, our goal involved developing a tool capable of easuring a sufficient number of leaves to enable analysis of leaf populations, tree crowns and canopies.We specifically tested whether a cell phone working as a 3Dpointer could yield reliable, repeatable and valid leaf anglemeasurements with a simple gesture. We evaluated the accuracy of this method under controlled conditions, using a 3D digitizer, and we compared performance in the field with the methods commonly used. We presented an equation to estimate the potential proportion of the leaf exposed to direct sunlight (SAL) at any given time and compared the results with those obtained bymeans of a graphicalmethod. 3. We found a strong and highly significant correlation between the graphical methods and the equation presented. The calibration process showed a strong correlation between the results derived from the two methods with amean relative difference below 10%. Themean relative difference in calculation of instantaneous exposure was below 5%. Our device performed equally well in diverse locations, in which we characterized over 700 leaves in a single day. 4. The newmethod, involving the use of a cell phone, ismuchmore effective than the traditionalmethods or digitizers when the goal is to scale up from leaf position to performance of leaf populations, tree crowns or canopies. Our methodology constitutes an affordable and valuable tool within which to frame a wide range of ecological hypotheses and to support canopy modelling approaches.

Calibration of WAVE in irrigated maize: fallow vs. cover crops.

Nitrate leaching decreases crop available N and increases water contamination. Replacing fallow by cover crops (CC) is an alternative to reduce nitrate contamination, because it reduces overall drainage and soil mineral N accumulation. A study of the soil N and nitrate leaching was conducted during 5 years in a semi-arid irrigated agricultural area of Central Spain. Three treatments were studied during the intercropping period of maize (Zea mays L.): barley (Hordeum vulgare L.), vetch (Vicia villosa L.), and fallow. Cover crops, sown in October, were killed by glyphosate application in March, allowing direct seeding of maize in April. All treatments were irrigated and fertilised following the same procedure. Soil water content was measured using capacity probes. Soil Nmin accumulation was determined along the soil profile before sowing and after harvesting maize. Soil analysis was conducted at six depths every 0.20m in each plot in samples from 0 to 1.2-m depth. The mechanistic water balance model WAVE was applied in order to calculate drainage and plant growth of the different treatments, and apply them to the N balance. We evaluated the water balance of this model using the daily soil water content measurements of this field trial. A new Matlab version of the model was evaluated as well. In this new version improvements were made in the solute transport module and crop module. In addition, this new version is more compatible with external modules for data processing, inverse calibration and uncertainty analysis than the previous Fortran version. The model showed that drainage during the irrigated period was minimized in all treatments, because irrigation water was adjusted to crop needs, leading to nitrate accumulation on the upper layers after maize harvest. Then, during the intercrop period, most of the nitrate leaching occurred. Cover crops usually led to a shorter drainage period, lower drainage water amount and lower nitrate leaching than the treatment with fallow. These effects resulted in larger nitrate accumulation in the upper layers of the soil after CC treatments.

Joint 4-D variational stereo reconstruction and camera calibration refinement for oceanic sea state measurements

Validating modern oceanographic theories using models produced through stereo computer vision principles has recently emerged. Space-time (4-D) models of the ocean surface may be generated by stacking a series of 3-D reconstructions independently generated for each time instant or, in a more robust manner, by simultaneously processing several snapshots coherently in a true ?4-D reconstruction.? However, the accuracy of these computer-vision-generated models is subject to the estimations of camera parameters, which may be corrupted under the influence of natural factors such as wind and vibrations. Therefore, removing the unpredictable errors of the camera parameters is necessary for an accurate reconstruction. In this paper, we propose a novel algorithm that can jointly perform a 4-D reconstruction as well as correct the camera parameter errors introduced by external factors. The technique is founded upon variational optimization methods to benefit from their numerous advantages: continuity of the estimated surface in space and time, robustness, and accuracy. The performance of the proposed algorithm is tested using synthetic data produced through computer graphics techniques, based on which the errors of the camera parameters arising from natural factors can be simulated.