6 resultados para unfair rating

em Universidad Politécnica de Madrid


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The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. Even though several topological properties from subsets of this bipartite network have been reported with a model that combines random and preferential attachment mechanisms [Beguerisse Díaz et al., 2010], there are still many aspects worth to be explored, as they are connected to relevant phenomena underlying the evolution of the network. In this work, we test the hypothesis that bursty human behavior is essential in order to describe how a bipartite user-item network evolves in time. To that end, we propose a novel model that combines, for user nodes, a network growth prescription based on a preferential attachment mechanism acting not only in the topological domain (i.e. based on node degrees) but also in time domain. In the case of items, the model mixes degree preferential attachment and random selection. With these ingredients, the model is not only able to reproduce the asymptotic degree distribution, but also shows an excellent agreement with the Netflix data in several time-dependent topological properties.

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This paper describes the design of an original twin capacitive load that is able of tracing simultaneously the I?V characteristics of two photovoltaic modules. Besides, an example of the application of this dual system to the outdoor rating of photovoltaic modules is presented, whose results have shown a good degree of repeatability.

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It has been demonstrated that rating trust and reputation of individual nodes is an effective approach in distributed environments in order to improve security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario, the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as bad mouthing attack. In another scenario, a number of entities agree to give positive feedback on an entity (often with adversarial intentions). This attack is known as ballot stuffing. Both attack types can significantly deteriorate the performances of the network. The existing solutions for coping with these attacks are mainly concentrated on prevention techniques. In this work, we propose a solution that detects and isolates the abovementioned attackers, impeding them in this way to further spread their malicious activity. The approach is based on detecting outliers using clustering, in this case self-organizing maps. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrate the capability of the approach in detecting both bad mouthing and ballot stuffing attack in various scenarios.

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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.

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A methodology is presented to determine both the short-term and the long-term influence of the spectral variations on the performance of Multi-Junction (MJ) solar cells and Concentrating "This is the peer reviewed version of the following article: R. Núñez, C. Domínguez, S. Askins, M. Victoria, R. Herrero, I. Antón, and G. Sala, “Determination of spectral variations by means of component cells useful for CPV rating and design,” Prog. Photovolt: Res. Appl., 2015., which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/pip.2715/full. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving [http://olabout.wiley.com/WileyCDA/Section/id-820227.html#terms]." Photovoltaic (CPV) modules. Component cells with the same optical behavior as MJ solar cells are used to characterize the spectrum. A set of parameters, namely Spectral Matching Ratios (SMRs), is used to characterize spectrally a particular Direct Normal Irradiance (DNI) by comparison to the reference spectrum (AM1.5D-ASTM-G173-03). Furthermore, the spectrally corrected DNI for a given MJ solar cell technology is defined providing a way to estimate the losses associated to the spectral variations. The last section analyzes how the spectrum evolves throughout a year in a given place and the set of SMRs representative for that location are calculated. This information can be used to maximize the energy harvested by the MJ solar cell throughout the year. As an example, three years of data recorded in Madrid shows that losses lower than 5% are expected due to current mismatch for state-of-the-art MJ solar cells.

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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.