Иновативни услуги за диагностика и мониторинг на мрежова свързаност, използвани в GEANT

Доклад, поместен в сборника на Националната конференция "Образованието в информационното общество", Пловдив, май, 2012 г.

CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters.

The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive intercomparison due to the availability of quality checked in situ databases. The CoastColour Round Robin (CCRR) project, funded by the European Space Agency (ESA), was designed to bring together three reference data sets using these to test algorithms and to assess their accuracy for retrieving water quality parameters. This paper provides a detailed description of these reference data sets, which include the Medium Resolution Imaging Spectrometer (MERIS) level 2 match-ups, in situ reflectance measurements, and synthetic data generated by a radiative transfer model (HydroLight). These data sets, representing mainly coastal waters, are available from doi:10.1594/PANGAEA.841950. The data sets mainly consist of 6484 marine reflectance (either multispectral or hyperspectral) associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: total suspended matter (TSM) and chlorophyll a (CHL) concentrations, and the absorption of coloured dissolved organic matter (CDOM). Inherent optical properties are also provided in the simulated data sets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three data sets are compared. Match-up and in situ sites where deviations occur are identified. The distributions of the three reflectance data sets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Worldwide outdoor round robin study of organic photovoltaic devices and modules

Accurate characterization and reporting of organic photovoltaic (OPV) device performance remains one of the important challenges in the field. The large spread among the efficiencies of devices with the same structure reported by different groups is significantly caused by different procedures and equipment used during testing. The presented article addresses this issue by offering a new method of device testing using “suitcase sample” approach combined with outdoor testing that limits the diversity of the equipment, and a strict measurement protocol. A round robin outdoor characterization of roll-to-roll coated OPV cells and modules conducted among 46 laboratories worldwide is presented, where the samples and the testing equipment were integrated in a compact suitcase that served both as a sample transportation tool and as a holder and test equipment during testing. In addition, an internet based coordination was used via plasticphotovoltaics.org that allowed fast and efficient communication among participants and provided a controlled reporting format for the results that eased the analysis of the data. The reported deviations among the laboratories were limited to 5% when compared to the Si reference device integrated in the suitcase and were up to 8% when calculated using the local irradiance data. Therefore, this method offers a fast, cheap and efficient tool for sample sharing and testing that allows conducting outdoor measurements of OPV devices in a reproducible manner.

E-comparisons: A new approach to round robin tests for environmental noise assessment in transport infrastructures

The increasing importance of pollutant noise has led to the creation of many new noise testing laboratories in recent years. For this reason and due to the legal implications that noise reporting may have, it is necessary to create procedures intended to guarantee the quality of the testing and its results. For instance, the ISO/IEC standard 17025:2005 specifies general requirements for the competence of testing laboratories. In this standard, interlaboratory comparisons are one of the main measures that must be applied to guarantee the quality of laboratories when applying specific methodologies for testing. In the specific case of environmental noise, round robin tests are usually difficult to design, as it is difficult to find scenarios that can be available and controlled while the participants carry out the measurements. Monitoring and controlling the factors that can influence the measurements (source emissions, propagation, background noise…) is not usually affordable, so the most extended solution is to create very effortless scenarios, where most of the factors that can have an influence on the results are excluded (sampling, processing of results, background noise, source detection…) The new approach described in this paper only requires the organizer to make actual measurements (or prepare virtual ones). Applying and interpreting a common reference document (standard, regulation…), the participants must analyze these input data independently to provide the results, which will be compared among the participants. The measurement costs are severely reduced for the participants, there is no need to monitor the scenario conditions, and almost any relevant factor can be included in this methodology

SOPHIA CPV module round robin: power rating at CSOC

Within the European funded project SOPHIA, a Round Robin measurement on CPV module has been initiated. Seven different test laboratories located in Europe between 48°N and 37°N perform measurements of four SOITEC CPV modules. The modules are electrically characterized with different measurement equipment under various climatic conditions. One pyrheliometer and one spectral sensor based on component cells are shipped together with the modules. This ensures that the irradiance and spectrum, two factors with high impact on CPV module performance, are measured with the identical equipment at each site. The round robin activity is performed in closeco-operation with the IEC TC82 WG7 power rating team in order to support the work on the CPV module power rating draft standard 62670-3. The resultingrated module power outputs at CSOC (Concentrator Standard Operating Conditions) are compared amongst the power rating methods and amongst the test labs. In this manner, a deviation in rated power output between different test labs and power rating methods is determined.

SOPHIA CPV module round robin: power rating at CSOC

In the frame of the European project SOPHIA a concentrator photovoltaic (CPV) module measurement round robin has been initiated. The round robin includes measurements of four CPV modules at seven different test laboratories located in Europe. IV curves of the modules are measured with different measurement equipment under various climatic conditions. The aim of this activity is to perform at each site a rating of the modules at concentrator standard operating conditions CSOC according to IEC 62670-1. The outcome of the round robin is intended for direct feedback to the current draft standard IEC 62670-3 “Concentrator Photovoltaic (CPV) Performance Testing - Performance Measurements and Power Rating”. The paper discusses initial results from the first three partners that have already finished the measurements up to now.

Results of the IEA round robin on viscosity and stability of fast pyrolysis bio-oils

An international round robin study of the stability of fast pyrolysis bio-oil was undertaken. Fifteen laboratories in five different countries contributed. Two bio-oil samples were distributed to the laboratories for stability testing and further analysis. The stability test was defined in a method provided with the bio-oil samples. Viscosity measurement was a key input. The change in viscosity of a sealed sample of bio-oil held for 24 h at 80 °C was the defining element of stability. Subsequent analyses included ultimate analysis, density, moisture, ash, filterable solids, and TAN/pH determination, and gel permeation chromatography. The results showed that kinematic viscosity measurement was more generally conducted and more reproducibly performed versus dynamic viscosity measurement. The variation in the results of the stability test was great and a number of reasons for the variation were identified. The subsequent analyses proved to be at the level of reproducibility, as found in earlier round robins on bio-oil analysis. Clearly, the analyses were more straightforward and reproducible with a bio-oil sample low in filterable solids (0.2%), compared to one with a higher (2%) solids loading. These results can be helpful in setting standards for use of bio-oil, which is just coming into the marketplace. © 2012 American Chemical Society.

Learning Multirobot Hose Transportation and Deployment by Distributed Round-Robin Q-Learning

Multi-Agent Reinforcement Learning (MARL) algorithms face two main difficulties: the curse of dimensionality, and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL) algorithm for cooperative systems. The computational complexity of this algorithm increases linearly with the number of agents. Moreover, it eliminates environment non sta tionarity by carrying a round-robin scheduling of the action selection and execution. That this learning scheme allows the implementation of Modular State-Action Vetoes (MSAV) in cooperative multi-agent systems, which speeds up learning convergence in over-constrained systems by vetoing state-action pairs which lead to undesired termination states (UTS) in the relevant state-action subspace. Each agent's local state-action value function learning is an independent process, including the MSAV policies. Coordination of locally optimal policies to obtain the global optimal joint policy is achieved by a greedy selection procedure using message passing. We show that D-RR-QL improves over state-of-the-art approaches, such as Distributed Q-Learning, Team Q-Learning and Coordinated Reinforcement Learning in a paradigmatic Linked Multi-Component Robotic System (L-MCRS) control problem: the hose transportation task. L-MCRS are over-constrained systems with many UTS induced by the interaction of the passive linking element and the active mobile robots.