A fuzzy extension of MAGERIT methodology for risk analysis in information systems

We propose a fuzzy approach to deal with risk analysis for information systems. We extend MAGERIT methodology that valuates the asset dependencies to a fuzzy framework adding fuzzy linguistic terms to valuate the different elements (terminal asset values, asset dependencies as well as the probability of threats and the resulting asset degradation) in risk analysis. Computations are based on the trapezoidal fuzzy numbers associated with these linguistic terms and, finally, the results of these operations are translated into a linguistic term by means of a similarity function.

Evaluation of the reliability of commercial concentrator triple-junction solar cells by means of accelerated life tests (ALT)

A temperature accelerated life test on commercial concentrator lattice-matched GaInP/GaInAs/Ge triple-junction solar cells has been carried out. The solar cells have been tested at three different temperatures: 119, 126 and 164 °C and the nominal photo-current condition (820 X) has been emulated by injecting current in darkness. All the solar cells have presented catastrophic failures. The failure distributions at the three tested temperatures have been fitted to an Arrhenius-Weibull model. An Arrhenius activation energy of 1.58 eV was determined from the fit. The main reliability functions and parameters (reliability function, instantaneous failure rate, mean time to failure, warranty time) of these solar cells at the nominal working temperature (80 °C) have been obtained. The warranty time obtained for a failure population of 5 % has been 69 years. Thus, a long-term warranty could be offered for these particular solar cells working at 820 X, 8 hours per day at 80 °C.

Vibration reduction for vision systems on board unmanned aerial vehicles using a neuro-fuzzy controller

In this paper, an intelligent control approach based on neuro-fuzzy systems performance is presented, with the objective of counteracting the vibrations that affect the low-cost vision platform onboard an unmanned aerial system of rotating nature. A scaled dynamical model of a helicopter is used to simulate vibrations on its fuselage. The impact of these vibrations on the low-cost vision system will be assessed and an intelligent control approach will be derived in order to reduce its detrimental influence. Different trials that consider a neuro-fuzzy approach as a fundamental part of an intelligent semi-active control strategy have been carried out. Satisfactory results have been achieved compared to those obtained by means of vibration reduction passive techniques.

Fuzzy MCDA for remediation of a uranium tailing

The Pridneprovsky Chemical Plant was a largest uranium processing enterprises, producing a huge amount of uranium residues. The Zapadnoe tailings site contains the majority of these residues. We propose a theoretical framework based on Multi-Criteria Decision Analysis and fuzzy logic to analyse different remediation alternatives for the Zapadnoe tailings, in which potentially conflicting economic, radiological, social and environmental objectives are simultaneously taken into account. An objective hierarchy is built that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, it is proposed that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic

Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.

Determination of spectral variations by means of component cells useful for CPV rating and design

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.