Social learning against data falsification in sensor networks

Sensor networks generate large amounts of geographically-distributed data. The conventional approach to exploit this data is to first gather it in a special node that then performs processing and inference. However, what happens if this node is destroyed, or even worst, if it is hijacked? To explore this problem, in this work we consider a smart attacker who can take control of critical nodes within the network and use them to inject false information. In order to face this critical security thread, we propose a novel scheme that enables data aggregation and decision-making over networks based on social learning, where the sensor nodes act resembling how agents make decisions in social networks. Our results suggest that social learning enables high network resilience, even when a significant portion of the nodes have been compromised by the attacker

Oxy-fuel combustion of coal and biomass blends

The ignition temperature, burnout and NO emissions of blends of a semi-anthracite and a high-volatile bituminous coal with 10 and 20 wt.% of olive waste were studied under oxy-fuel combustion conditions in an entrained flow reactor (EFR). The results obtained under several oxy-fuel atmospheres (21%O2–79%CO2, 30%O2–70%CO2 and 35%O2–65%CO2) were compared with those attained in air. The results indicated that replacing N2 by CO2 in the combustion atmosphere with 21% of O2 caused an increase in the temperature of ignition and a decrease in the burnout value. When the O2 concentration was increased to 30 and 35%, the temperature of ignition was lower and the burnout value was higher than in air conditions. A significant reduction in ignition temperature and a slight increase in the burnout value was observed after the addition of biomass, this trend becoming more noticeable as the biomass concentration was increased. The emissions of NO during oxy-fuel combustion were lower than under air-firing. However, they remained similar under all the oxy-fuel atmospheres with increasing O2 concentrations. Emissions of NO were significantly reduced by the addition of biomass to the bituminous coal, although this effect was less noticeable in the case of the semi-anthracite.This work was carried out with financial support from the Spanish MICINN (Project PS-120000-2005-2) co-financed by the European Regional Development Fund. M.V.G. and L.A. acknowledge funding from the CSIC JAE-Doc and CSIC JAE-Pre programs, respectively, co-financed by the European Social Fund. J.R. acknowledges funding from the Government of the Principado de Asturias (Severo Ochoa program).Peer reviewe

Overview of biologically digested leachate treatment using adsorption

Biological process is effective in treating most biodegradable organic matter present in leachate; however, a significant amount of ammonia, metals and refractory organic compounds may still remain in this biologically digested leachate. This effluent cannot be released to receiving bodies until the discharge limit is met. Several physical/chemical processes have been practiced as post-treatment to remove the remaining pollutants including coagulation–flocculation, oxidation and adsorption. Adsorption is often applied in leachate treatment as it enhances removal of refractory organic compounds. This chapter will focus on works related to adsorption as one of the commonly used methods to treat biologically digested leachate further down to acceptable discharge limit

Overview of biologically digested leachate treatment using adsorption

Biological process is effective in treating most biodegradable organic matter present in leachate; however, a significant amount of ammonia, metals and refractory organic compounds may still remain in this biologically digested leachate. This effluent cannot be released to receiving bodies until the discharge limit is met. Several physical/chemical processes have been practiced as post-treatment to remove the remaining pollutants including coagulation–flocculation, oxidation and adsorption. Adsorption is often applied in leachate treatment as it enhances removal of refractory organic compounds. This chapter will focus on works related to adsorption as one of the commonly used methods to treat biologically digested leachate further down to acceptable discharge limit

Error Exponents for Decentralized Detection in Tree Networks

We consider the problem of decentralized detection in a sensor network consisting of nodes arranged as a tree of bounded height. We characterize the optimal error exponent under a Neyman-Pearson formulation, and show that the Type II error probability decays exponentially with the number of nodes. Surprisingly, the optimal error exponent is often the same as that corresponding to a parallel configuration. We provide sufficient, as well as necessary, conditions for this to happen. We also consider the impact of failure-prone sensors or unreliable communications between sensors on the detection performance. Simple strategies that nearly achieve the asymptotically optimal performance in these cases are also developed