Genetic Algorithm for Epidemic Mitigation by Removing Relationships

Min-SEIS-Cluster is an optimization problem which aims at minimizing the infection spreading in networks. In this problem, nodes can be susceptible to an infection, exposed to an infection, or infectious. One of the main features of this problem is the fact that nodes have different dynamics when interacting with other nodes from the same community. Thus, the problem is characterized by distinct probabilities of infecting nodes from both the same and from different communities. This paper presents a new genetic algorithm that solves the Min-SEIS-Cluster problem. This genetic algorithm surpassed the current heuristic of this problem significantly, reducing the number of infected nodes during the simulation of the epidemics. The results therefore suggest that our new genetic algorithm is the state-of-the-art heuristic to solve this problem.Comment: GECCO '17 - Proceedings of the Genetic and Evolutionary Computation Conferenc

Time-delay identification using multiscale ordinal quantifiers

Time-delayed interactions naturally appear in a multitude of real-world systems due to the finite propagation speed of physical quantities. Often, the time scales of the interactions are unknown to an external observer and need to be inferred from time series of observed data. We explore, in this work, the properties of several ordinal-based quantifiers for the identification of time-delays from time series. To that end, we generate artificial time series of stochastic and deterministic time-delay models. We find that the presence of a nonlinearity in the generating model has consequences for the distribution of ordinal patterns and, consequently, on the delay-identification qualities of the quantifiers. Here, we put forward a novel ordinal-based quantifier that is particularly sensitive to nonlinearities in the generating model and compare it with previously-defined quantifiers. We conclude from our analysis on artificially generated data that the proper identification of the presence of a time-delay and its precise value from time series benefits from the complementary use of ordinal-based quantifiers and the standard autocorrelation function. We further validate these tools with a practical example on real-world data originating from the North Atlantic Oscillation weather phenomenon.Fil: Soriano, Miguel C.. Consejo Superior de Investigaciones Científicas. Instituto de Física Interdisciplinar y Sistemas Complejos; EspañaFil: Zunino, Luciano José. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentin

Discriminating chaotic and stochastic dynamics through the permutation spectrum test

In this paper, we propose a new heuristic symbolic tool for unveiling chaotic and stochastic dynamics: the permutation spectrum test. Several numerical examples allow us to confirm the usefulness of the introduced methodology. Indeed, we show that it is robust in situations in which other techniques fail (intermittent chaos, hyperchaotic dynamics, stochastic linear and nonlinear correlated dynamics, and deterministic non-chaotic noise-driven dynamics). We illustrate the applicability and reliability of this pragmatic method by examining real complex time series from diverse scientific fields. Taking into account that the proposed test has the advantages of being conceptually simple and computationally fast, we think that it can be of practical utility as an alternative test for determinism. The importance of distinguishing between periodic, chaotic, and stochastic dynamics from time series analysis is well-recognized for understanding the mechanisms that govern the regarded complex systems. In this work, we have introduced a conceptually simple and computationally fast symbolic visual test for discriminating chaotic and stochastic dynamics, called the permutation spectrum test. Because the symbolization is made by implementing the Bandt and Pompe methodology, all the advantages associated with this natural encoding (simplicity, extremely fast calculation, robustness, and invariance with respect to monotonous transformations) are inherited by the permutation spectrum test. We have shown that this pragmatic approach is robust in situations in which other tests fail. We have also confirmed its practical utility by examining several experimental and natural time series.Centro de Investigaciones Óptica

Discriminating chaotic and stochastic dynamics through the permutation spectrum test

In this paper, we propose a new heuristic symbolic tool for unveiling chaotic and stochastic dynamics: the permutation spectrum test. Several numerical examples allow us to confirm the usefulness of the introduced methodology. Indeed, we show that it is robust in situations in which other techniques fail (intermittent chaos, hyperchaotic dynamics, stochastic linear and nonlinear correlated dynamics, and deterministic non-chaotic noise-driven dynamics). We illustrate the applicability and reliability of this pragmatic method by examining real complex time series from diverse scientific fields. Taking into account that the proposed test has the advantages of being conceptually simple and computationally fast, we think that it can be of practical utility as an alternative test for determinism. The importance of distinguishing between periodic, chaotic, and stochastic dynamics from time series analysis is well-recognized for understanding the mechanisms that govern the regarded complex systems. In this work, we have introduced a conceptually simple and computationally fast symbolic visual test for discriminating chaotic and stochastic dynamics, called the permutation spectrum test. Because the symbolization is made by implementing the Bandt and Pompe methodology, all the advantages associated with this natural encoding (simplicity, extremely fast calculation, robustness, and invariance with respect to monotonous transformations) are inherited by the permutation spectrum test. We have shown that this pragmatic approach is robust in situations in which other tests fail. We have also confirmed its practical utility by examining several experimental and natural time series.Fil: Kulp, C. W.. Lycoming College; Estados UnidosFil: Zunino, Luciano José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentin

Characterizing the Hyperchaotic Dynamics of a Semiconductor Laser Subject to Optical Feedback Via Permutation Entropy

The time evolution of the output of a semiconductor laser subject to delayed optical feedback can exhibit highdimensional chaotic fluctuations. In this contribution, our aim is to quantify the degree of unpredictability of this hyperchaotic time evolution. To that end, we estimate permutation entropy, a novel information-theory-derived quantifier particularly robust in a noisy environment. The permutation entropy is defined as a functional of a symbolic probability distribution, evaluated using the Bandt-Pompe recipe to assign a probability distribution function to the time series generated by the chaotic system. This measure quantifies the diversity of orderings present in the associated time series. In order to evaluate the performance of this novel quantifier, we compare with the results obtained by using a more standard chaos quantifier, namely the KolmogorovSinai entropy. Here, we present numerical results showing that the permutation entropy, evaluated at specific time-scales involved in the chaotic regime of the semiconductor laser subject to optical feedback, give valuable information about the degree of unpredictability of the chaotic laser dynamics. The influence of additive observational noise on the proposed tool is also investigated.L.Z. and O.A.R. were supported by Consejo Nacional de Investigaciones Cient´ıficas y T´ecnicas (CONICET), Argentina. O.A.R. is PVE fellowship, CAPES, Brazil. Part of this work was funded by MEC (Spain), MICINN (Spain) and FEDER under Projects TEC2009-14101 (DeCoDicA) and FIS2007-60327 (FISICOS), and by the EC Project PHOCUS Grant 240763.Peer reviewe

Time-Sensitive Networking to Improve the Performance of Distributed Functional Safety Systems Implemented over Wi-Fi

Industry 4.0 has significantly improved the industrial manufacturing scenario in recent years. The Industrial Internet of Things (IIoT) enables the creation of globally interconnected smart factories, where constituent elements seamlessly exchange information. Industry 5.0 has further complemented these achievements, as it focuses on a human-centric approach where humans become part of this network of things, leading to a robust human–machine interaction. In this distributed, dynamic, and highly interconnected environment, functional safety is essential for adequately protecting people and machinery. The increasing availability of wireless networks makes it possible to implement distributed and flexible functional safety systems. However, such networks are known for introducing unwanted delays that can lead to safety performance degradation due to their inherent uncertainty. In this context, the Time-Sensitive Networking (TSN) standards present an attractive prospect for enhancing and ensuring acceptable behaviors. The research presented in this paper deals with the introduction of TSN to implement functional safety protocols for wireless networks. Among the available solutions, we selected Wi-Fi since it is a widespread network, often considered and deployed for industrial applications. The introduction of a reference functional safety protocol is detailed, along with an analysis of how TSN can enhance its behavior by evaluating relevant performance indexes. The evaluation pertains to a standard case study of an industrial warehouse, tested through practical simulations. The results demonstrate that TSN provides notable advantages, but it requires meticulous coordination with the Wi-Fi MAC layer protocol to guarantee improved performance

Feasibility of mini combined cycles for naval applications

The objective of energy production with low environmental impact will have, in the near future, high potential of development also for naval applications. The containment of pollutant emissions can be achieved by the combined use of an innovative mini gas-steam combined cycle with thermal energy cogeneration to feed the ship thermal utilities, in place of the current Diesel engine application, and liquefied natural gas as fuel (LNG). The present work is focused on the definition of the architecture of the plant, by selecting optimal distribution of pressure and temperature and repartition of power between Gas Turbine (GT), Steam Turbine (ST) and thermal utilities, as well as on the choice and sizing of the individual components. The main purpose is the definition of a compact, high efficiency, system. The proposed basic mini-cycle ranges from 2 MW to 10 MW electric power. Thanks to the combined heat and power cogeneration plant adopted, for an overall electrical efficiency of about 30%, a total return (thermal + electricity) of about 75% can be achieved. An example of plant providing large power, in a partially modular arrangement is also proposed

A Comprehensive Framework for the Security Risk Management of Cyber-Physical Systems

Cyber Physical Systems are facing huge and diverse set of security risks, especially cyber-attacks that can cause disruption to physical services or create a national disaster. Information and communication technology (ICT) has made a remarkable impact on the society. A Cyber Physical System (CPS) relies basically on information and communication technology, which puts the system\u2019s assets under certain risks especially cyber ones, and hence they must be kept under control by means of security countermeasures that generate confidence in the use of these assets. And so there is a critical need to give a great attention on the cybersecurity of these systems, which consequently leads to the safety of the physical world. This goal is achieved by adopting a solution that applies processes, plans and actions to prevent or reduce the effects of threats. Traditional IT risk assessment methods can do the job, however, and because of the characteristics of a CPS, it is more efficient to adopt a solution that is wider than a method, and addresses the type, functionalities and complexity of a CPS. This chapter proposes a framework that breaks the restriction to a traditional risk assessment method and encompasses wider set of procedures to achieve a high level strategy that could be adopted in the risk management process, in particular the cybersecurity of cyber-physical systems

A Formal Model of Algorand Smart Contracts

We develop a formal model of Algorand stateless smart contracts (stateless ASC1). We exploit our model to prove fundamental properties of the Algorand blockchain, and to establish the security of some archetypal smart contracts. While doing this, we highlight various design patterns supported by Algorand. We perform experiments to validate the coherence of our formal model w.r.t. the actual implementation

Efectividad del aceite esencial de orégano mexicano de República Dominicana (Lippia graveolens) contra plagas del maíz (Sitophilus zeamais y Fusarium verticillioides)

The insecticidal and antifungal properties of Mexican oregano (Lippia graveolens) essential oil from the Dominican Republic were investigated under laboratory conditions against two main pests of stored grains: Sitophilus zeamais and Fusarium verticillioides. Although oregano essential oil at 600 ?l/l air did not result in a significant mortality of S. zeamais after 24 hours of exposure by fumigation, this essential oil was a powerful acetylcholinesterase (AChE) inhibitor in vitro. One of the main components of oregano essential oil, p-cymene, presented fumigant toxicity and AChE inhibition activity against the maize weevil. The L. graveolens essential oil antifungal activity against F. verticillioides was evaluated at 50, 100 and 200 ?l/l, and it was found that growth parameters were affected by the presence of oregano essential oil in the media, whereas FB1 production was not inhibited. The results demonstrate that oregano essential oil and p-cymene can be used as alternatives to synthetic pesticides against F. verticillioides and S. zeamais, respectively.Se estudiaron en condiciones de laboratorio las propiedades insecticidas y fungicidas del aceite esencial de orégano mexicano (Lippia graveolens) de República Dominicana contra dos plagas principales de granos almacenados: Sitophilus zeamais y Fusarium verticillioides. Aunque el aceite esencial de orégano a 600 ?l/l de aire no resultó en una mortalidad significativa de S. zeamais después de 24 horas de exposición a la fumigación, fue un potente inhibidor de la acetilcolinesterasa (AChE) in vitro. El p-cimeno, uno de los principales componentes del aceite esencial, presentó actividad fumigante y de inhibición de la AChE contra el gorgojo del maíz. Además se evaluó la actividad antifúngica frente a F. verticillioides a 50, 100 y 200 ?l/l y se encontró que los parámetros de crecimiento del hongo fueron afectados por la presencia del aceite esencial de orégano en el medio, mientras que la producción de fumonisina B1 (FB1) no se inhibió. Los resultados demuestran que el aceite esencial de orégano y el p-cimeno se pueden usar como alternativas a los pesticidas sintéticos contra F. verticillioides y S. zeamais, respectivamente