Summary
New solutions are required for the management of heterogeneous distributed sensor networks in order to address the problem of data quality and false data detection in wireless sensor networks ...(WSNs). In this paper, we present a nonlinear cooperative control algorithm based on game theory. Here, a new model is proposed for the automatic processing and management of information in heterogeneous distributed WSNs. We apply our algorithm to a case study with the aim of improving the quality of temperature data collected from indoor surfaces by a WSN. Unlike the classic unsupervised methods, in the proposed algorithm, it is not necessary to define the number of clusters beforehand. Once the game reaches the game equilibrium, the resulting number of clusters can be used as input for the unsupervised classification analysis. Anomalous temperature values are corrected according to their neighborhood, without modifying the temperature clusters.
Evaluating the probability of failure of a product during the warranty is key to estimating the cost of its entire life cycle. Photovoltaic (PV) modules are the most reliable elements of a PV system, ...and their high reliability translates into long warranty periods (typically 25 to 30 years). The number of PV modules that fail during warranty and when they failed is an important issue to estimate the life cycle cost of PV modules. In this paper, we propose a coupled degradation‐warranty model for PV modules. The proposed model is aimed to assess the probability of failure over time covered by warranty based on degradation data. This allows us to estimate the time of PV modules failure covered by the warranty. Although the warranty model has been applied to some forms of degradation and sales functions, our method can be applied to any real application. This allows the key parameters of the warranty to be obtained in a simple way. The required degradation parameters to fulfill warranty depend on the allowable ratio of warranted elements. However, the main conclusion of the influence of degradation rates on warranty is that it is not possible to fulfill 25 years of warranty if degradation rates are larger than 0.8%/year. The required degradation rates values, for 25 years of warranty, will be lower than 0.5%/year if the allowed warranted element is in the range of 1%.
To evaluate the probability that a photovoltaic (PV) module fails during the warranty period is key to estimate its whole life cycle cost. In this work, we propose a coupled degradation‐warranty model for PV modules that allows estimating the percentage of modules that fail covered by warranty and when they fail. The results show that the degradation of many PV modules in field will not fulfill the offered warranty.
Collective cell migration is a hallmark of wound repair, cancer invasion and metastasis, immune responses, angiogenesis, and embryonic morphogenesis. Wound healing is a complex cellular and ...biochemical process necessary to restore structurally damaged tissue. It involves dynamic interactions and crosstalk between various cell types, interaction with extracellular matrix molecules, and regulated production of soluble mediators and cytokines. In cutaneous wound healing, skin cells migrate from the wound edges into the wound to restore skin integrity. Analysis of cell migration in vitro is a useful assay to quantify alterations in cell migratory capacity in response to experimental manipulations. Although several methods exist to study cell migration (such as Boyden chamber assay, barrier assays, and microfluidics-based assays), in this short report we will explain the wound healing assay, also known as the “in vitro scratch assay” as a simple, versatile, and cost-effective method to study collective cell migration and wound healing.
In this paper, we study the phenomena of collapse and anomalous diffusion in shared mobility systems. In particular, we focus on a fleet of vehicles moving through a stations network and analyse the ...effect of self-journeys in system stability, using a mathematical simplex under stochastic flows. With a birth-death process approach, we find analytical upper bounds for random walk and we monitor how the system collapses by super diffusing under different randomization conditions. Using the multi-scale entropy metric, we show that real data from a bike-sharing fleet in the city of Salamanca (Spain) present a complex behaviour with more of a 1/f signal than a disorganized system with a white noise signal.
This paper analyses customers’ demand flexibility in a local power trading scenario through an Ising spin-based model. We look at quantitative information on the two-way relationships between power ...exchanges and spin dynamics. To this end, a modified version of the Metropolis-Hastings algorithm was implemented, including a gradient descent through the constraint surface. This allowed us to analyse the system on a large scale (considering the cumulated benefit of all the actors involved) and also from the perspective of total aggregation. In a maximum flexibility scenario, the total aggregation profit increases with the number of aggregators. We also investigate numerically the effect of aggregator boundaries on the spin dynamics.
Development of contaminant detection systems in various natural and industrial environments has been favored in recent years thanks to the evolution of processors and sensors. Our group works ...specifically on contaminant detection systems in inland waters: immediate and continuous detection is a fundamental requirement in this type of sensing. Regarding the sensors, the proposed system is based on fluorescence, since it offers a method in which there is no contact with water, which means less wear on the components and a great saving in cleaning and maintenance. On the other hand, the spectrum processing is of great importance, since it is used both in the generation of a library of fluorescence spectra taken in the laboratory and in the continuous analysis of the samples and in the comparison algorithm for identification. The validity of the system is based on the last process that is carried out in a very short time. This article describes a system to process spectra in a more accelerated way.
This paper proposes a predictive dispatch model to manage energy flexibility in the domestic energy system. Electric Vehicles (EV), batteries and shiftable loads are devices that provide energy ...flexibility in the proposed system. The proposed energy management problem consists of two stages: day-ahead and real time. A hybrid method is defined for the first time in this paper to model the uncertainty of the PV power generation based on its power prediction. In the day-ahead stage, the uncertainty is modeled by interval bands. On the other hand, the uncertainty of PV power generation is modeled through a stochastic scenario-based method in the real-time stage. The performance of the proposed hybrid Interval-Stochastic (InterStoch) method is compared with the Modified Stochastic Predicted Band (MSPB) method. Moreover, the impacts of energy flexibility and the demand response program on the expected profit and transacted electrical energy of the system are assessed in the case study presented in this paper.
In this paper we make a critical review of the existing technology in the smart cities and smart grid paradigms from the security perspective. First we summarize the findings about the evolution of ...renewable technology over time and in particular the benefits of a Cost reduction potential for solar and wind power in the period 2015-2025. Then we build from existing sources to highlight different ways for efficiency improvement in solar panel solutions during 1975-2015. Next we analyze growth of the smart metering and smart grid technology in the world. Also, the existing Blockchain solutions are critically reviewed in regard to cyber infrastructure security. From these findings we conclude that there is an increasing need for developing new Blockchain solutions in the smart grids ecosystem.
Rotors of spiral waves are thought to be one of the potential mechanisms that maintain atrial fibrillation (AF). However, disappointing clinical outcomes of rotor mapping and ablation to eliminate AF ...raise a serious doubt on rotors as a macro-scale mechanism that causes the micro-scale behavior of individual cardiomyocytes to maintain spiral waves. In this study, we aimed to elucidate the causal relationship between rotors and spiral waves in a numerical model of cardiac excitation. To accomplish the aim, we described the system in a series of spatiotemporal scales by generating a renormalization group, and evaluated the causal architecture of the system by quantifying causal emergence. Causal emergence is an information-theoretic metric that quantifies emergence or reduction between micro- and macro-scale behaviors of a system by evaluating effective information at each scale. We found that the cardiac system with rotors has a spatiotemporal scale at which effective information peaks. A positive correlation between the number of rotors and causal emergence was observed only up to the scale of peak causation. We conclude that rotors are not the universal mechanism to maintain spiral waves at all spatiotemporal scales. This finding may account for the conflicting benefit of rotor ablation in clinical studies.
In this work we show how a simple model based on chemical signaling can reduce the exploration times in urban environments. The problem is relevant for smart city navigation where electric vehicles ...try to find recharging stations with unknown locations. To this end we have adapted the classical ant foraging swarm algorithm to urban morphologies. A perturbed Markov chain model is shown to qualitatively reproduce the observed behaviour. This consists of perturbing the lattice random walk with a set of perturbing sources. As the number of sources increases the exploration times decrease consistently with the swarm algorithm. This model provides a better understanding of underlying process dynamics. An experimental campaign with real prototypes provided experimental validation of our models. This enables us to extrapolate conclusions to optimize electric vehicle routing in real city topologies.
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