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In this paper, infrared thermography is applied to the quantitative characterization of optically semi-transparent media by using a newly introduced mathematical model. The method is specifically aimed to the detection and evaluations in graphic features buried beneath the surface of some particular kind of cultural heritage artefacts, such as books and documents. A numerical approach based on the finite element method, is proposed for solving the model equations. The computed thermographic signal depends on different inspected material physical properties, which have been selectively evaluated by comparing the theoretical results with the experimental ones in specifically designed test samples. Thereafter, the model is applied to the analysis of the results obtained in the case of graphic elements buried within samples constituted by the same previously characterized materials.

Highlights • It is proposed a model based on non-local operators capable of reproduce several of the equations traditionally used in research on population dynamics, as well as having additional features, useful for describing the phenomenon of pattern formation. • The combination of two of the parameters present in the model, namely, α and β, determines the existence of a phase space, characterized by regions with and without patterns. • The patterns formed will have M peaks and M valleys, with M ≥ 2. • There are (α, β) combinations which lead to the formation of degenerate states, where the system seems not to forget its initial conditions. • The model allows the study of real systems, such is the case of bacterial populations subjected to inhomogeneous growth conditions. • The parameter β represents a macroscopic measure of changes that occur at an individual level in the concentrations of proteins in bacteria, as a product of significant variations in the environment., Self-organization evolution of a population is studied considering generalized reaction-diffusion equations. We proposed a model based on non-local operators that has several of the equations traditionally used in research on population dynamics as particular cases. Then, employing a relatively simple functional form of the non-local kernel, we determined the conditions under which the analyzed population develops spatial patterns, as well as their main characteristics. Finally, we established a relationship between the developed model and real systems by making simulations of bacterial populations subjected to non-homogeneous lighting conditions. Our proposal reproduces some of the experimental results that other approaches considered previously had not been able to obtain.

We present a Volume Integral formulation for the solution of large scale eddy-current problems coupled with low-rank approximation techniques. Two alternative approaches are introduced to map the problem unknowns into a subset of grid elements forming a base of global or mixed (global and local) cycles, respectively, and guarantee the well-posedness of the problem both in simply and multiply connected domains. The paper shows that the adoption of mixed cycles is computationally more efficient than global ones. In particular, integral formulations based on global cycles cannot be safely coupled with low-rank approximation techniques, which, however, are crucial to increase the size of the largest solvable problem, like the ones involving conducting structures in magnetic confinement fusion devices. The aim of this paper is to demonstrate how such bottleneck can be overcome by considering local and global cycles differently, on the basis of the cohomology theory. An improved, efficient, and robust algorithm for computing a base of global cycles is described in detail. In particular, the presented algorithm is able to almost minimize the cohomology basis length, i.e. the number of mesh edges forming such a basis, in order to allow an efficient solution of large scale problems . Furthermore, a novel and general method to handle global and local cycles together, in the context of low-rank approximated matrices, is shown to be efficient for the solution of large scale eddy-current problems in multiply connected domains. Along the manuscript, pseudo-codes are given, which clarify the proposed methods and help to implement them by Volume Integral Equation practitioners.

In this paper, a generalized finite difference method (GFDM) based on the Peridynamic differential operator (PDDO) is investigated. The weighted moving least square (MLS) procedure involved in the GFDM is replaced by the PDDO. PDDO is capable to recast differentiation operators through an integration procedure which has the following advantages: the method is free of using any particular treatment near sharp gradients and where the solution is governed by a steep variation of field variables; it facilitates the imposition of boundary conditions compared to certain meshless methods as its formulation does not need a symmetric kernel function ; it is free of any particular correction function and parameter tunings; the method is easy to implement and we shall show that it generates a well-conditioned stiffness matrix for both structured and unstructured discretization . In this paper, the method is applied to 2D Helmholtz-type problems including time-harmonic acoustic problems, though the extension to 3D is straightforward. We also present a simple and efficient way to equip the method in the solution of unbounded domains . Moreover, a comprehensive study on the accuracy, convergence, and behavior of the method through a patch test is conducted. The test may be considered as a way to find the optimal region of the required integrations. We shall benefit from the advantage of the method in terms of accurate calculation of derivatives to determine the flow of acoustic energy, in a frequency problem domain, without employing any particular singular basis functions.

The aim of this paper is to present the implementation of 3D fractional viscoelastic constitutive theory presented in Alotta et al., 2016 [1]. Fractional viscoelastic models exactly reproduce the time dependent behaviour of real viscoelastic materials which exhibit a long “fading memory”. From an implementation point of view, this feature implies storing the stress/strain history throughout the simulations which may require a large amount of memory. We propose here a number of strategies to effectively limit the memory required. The form of the constitutive equations are summarized and the finite element implementation in a Newton-Raphson integration scheme is described in detail. The expressions that are needed to be coded in user-defined material subroutines for quasi static and dynamic implicit and explicit analysis (UMAT and VUMAT) in the commercial finite element software ABAQUS are readily provided. In order to demonstrate the accuracy of the numerical implementation we report a number of benchmark problems validated against analytical results. We have also analysed the behaviour of a viscoelastic plate with a hole in order to show the efficiency of these types of models. The source codes for the UMAT and VUMAT are provided as online supplements to this paper.

The a posteriori analysis of the realized motions (in other words, trajectories and controls) is an important part of the theory of optimal control and decision making. This paper is devoted to solving inverse problems of reconstruction of realized controls for control systems using known inaccurate measurements of the realized trajectories. A new method for solving inverse problems is suggested for a class of control systems with dynamics linear in controls and non-linear in state coordinates where the dimension of the control parameter is greater than or equal to the dimension of the state variable. This method relies on necessary optimality conditions in auxiliary variational problems. An illustrating example is exposed. © 2018 Russian Foundation for Basic Research, RFBR Russian Foundation for Basic Research, RFBR: 17-01-00074 Ural Branch, Russian Academy of Sciences, UB RAS: 18-1-1-10.

In this paper we present application of i-smooth analysis to approach-evasion linear differential game with delay. The main goal is to show that according to the methodology of i-smooth analysis one can realize extremal shift procedure by the finite dimensional component of the system state. © 2018 Russian Foundation for Basic Research, RFBR: 17-01-00636 The research was supported by the Russian Foundation for Basic Research (project 17-01-00636).

"Available online 28 December 2020", Hybrid-Trefftz finite elements are well suited for modeling the response of materials under highly transient loading. Their approximation bases are built using functions that satisfy exactly the differential equations governing the problem. This option embeds relevant physical information into the approximation basis and removes the well-known sensitivity of the conventional finite elements to high solution gradients and short wavelength excitations. Despite such advantages, no public software using hybrid-Trefftz finite elements to model wave propagation through solid and porous media exists to date. This paper covers the formulation and implementation of hybrid-Trefftz finite elements for single-phase, biphasic and triphasic media, subjected to dynamic loads. The formulation is cast in a unified framework, valid for the three types of materials alike, and independent of the nature (harmonic, periodic or transient) of the applied load. Displacement, traction, elastic and absorbing boundary conditions are accommodated. The implementation is made in three novel, open-source and user-friendly computational modules which are freely distributed online., This work was partly funded by Fundação para a Ciência e a Tecnologia (MCTES) through national funds (PIDDAC) under the R&D Units “Institute for Sustainability and Innovation in Structural Engineering (ISISE)” and “Civil Engineering Research and Innovation for Sustainability (CERIS)”, references UIDB/04029/2020 and UIDB/04625/2020, respectively, and through research project CEN-DynaGEO, reference PTDC/EAM-GTC/29923/2017.

This paper focuses on the modelling and simulation of gas networks to be used in an integrated multi-carrier energy scenario. A topological approach is followed, where a simplified graph-based description of the gas network is adopted and a systematic analysis of the metrics of three real test cases is carried out with the aim of discovering relevant network features. The governing equations of the basic building blocks such as pipelines, compressors and pressure reduction stations are readily derived under the assumptions of steady-state operation and isothermal behaviour, allowing a good matching between model compactness and accuracy. In addition, a circuit-based interpretation of model equations and well-established tools for circuit analysis are used. The obtained results proved that the proposed approach offers a feasible tool for gas networks, which can be readily integrated in a co-simulation framework.

Computer system vulnerabilities, computer viruses, and cyber attacks are rooted in software vulnerabilities. Reducing software defects, improving software reliability and security are urgent problems in the development of software. The core content is the discovery and location of software vulnerability. However, traditional human experts-based approaches are labor-consuming and time-consuming. Thus, some automatic detection approaches are proposed to solve the problem. But, they have a high false negative rate. In this paper, a deep learning based static taint analysis approach is proposed to automatically locate Internet of Things (IoT) software vulnerability, which can relieve tedious manual analysis and improve detection accuracy. Deep learning is used to detect vulnerability since it considers the program context. Firstly, the taint from the difference file between the source program and its patched program selection rules are designed. Secondly, the taint propagation paths are got using static taint analysis. Finally, the detection model based on two-stage Bidirectional Long Short Term Memory (BLSTM) is applied to discover and locate software vulnerabilities. The Code Gadget Database is used to evaluate the proposed approach, which includes two types of vulnerabilities in C/C++ programs, buffer error vulnerability (CWE-119) and resource management error vulnerability (CWE-399). Experimental results show that our proposed approach can achieve an accuracy of 0.9732 for CWE-119 and 0.9721 for CWE-399, which is higher than that of the other three models (the accuracy of RNN, LSTM, and BLSTM is under than 0.97) and achieve a lower false negative rate and false positive rate than the other approaches. This work was supported in part by the National Key R&D Plan under Grant CNS 2016QY06X1205 ,in part by the Basic Research Business Fees of Central Colleges under Grant CNS 20826041B4252 , in part by the National Natural Science Foundation (NSFC) under Grant CNS 61572115 , and in part by the Science and Technology Project of State Grid Corporation of China under Grant CNS 522722180007 . Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not reflect the views of the funding agencies.

We highlight the existence of a topological horseshoe arising from a a--priori stable model of the binary asteroid dynamics. The inspection is numerical and uses correctly aligned windows, as described in a recent paper by A. Gierzkiewicz and P. Zgliczy\'nski, combined with a recent analysis of an associated secular problem., Comment: 20 pages, 10 figures

In this paper, an evolution law for the modulus of the Short Time Fourier Transform, referred as spectrogram, of a frequency modulated multicomponent signal is proposed. Based on this result, an iterative reallocating method for the enhancement of spectrogram resolution is proposed. Compared to the standard reassignment method, the presented procedure allows us to obtain a time–frequency representation which better localizes the individual modes of a multicomponent signal even in the non separable case. The proposed method is computationally advantageous and robust to modes interference, then it could be employed for accurate instantaneous frequency estimation, which is a fundamental goal in applications dealing with non stationary signals such as radar, surveillance and audio signals.

The theoretical study of Genetic Algorithms and the dynamics induced by their genetic operators is a research field with a long history and many different approaches. In this paper we complete a recently presented approach to model one-point crossover using pretopologies (or Cechtopologies) in two ways. First, we extend it to the case of n-points crossover. We extend the definition of crossover distance between populations to work for n-points crossover, proving that computing it can be performed in polynomial time for any fixed number of crossover points. Secondly, we experimentally study how the distance distribution changes when the number of crossover points increases. In particular, the average distance between a population and the optimum decreases with the increase in the number of crossover points, showing that increasing the latter can reduce the number of crossover operations needed to evolve an optimal solution.

Limiting the weight of bad signals can recover the accuracy of the GNSS solution in signal-degraded scenarios, where multipath reflections and obstructions can easily generate multiple blunders. The fuzzy integration of the available information related to the quality of the received signals is exploited in this paper to derive an effective weighting schema in a Weighted Least Square estimation process. To validate the proposed schema, its performance in the position domain is compared to the most common weighting strategies proposed in the literature, based on GPS data collected through two different High Sensitivity GNSS receivers placed in urban canyons and processed in Single Point Positioning using pseudorange measurements.

Discrete nonlinear stochastic systems with general parametric noises are considered. To approximate the dispersion of random states, we propose an asymptotic approach based on the stochastic sensitivity analysis. This approach is used for the solution of the stabilization problem for the discrete controlled systems forced by parametric noise. A theory of the synthesis of the stochastic sensitivity by the feedback regulators is elaborated. Regulators minimizing the stochastic sensitivity are used in the problem of the structural stabilization of equilibrium regimes in population dynamics. The efficiency of this technique is demonstrated on the example of the suppression of undesired noisy large-amplitude regular and chaotic oscillations in the Hassell population model. © 2018 Российский Фонд Фундаментальных Исследований (РФФИ): 16-08-00388 This work was partially supported by RFBR (16-08-00388).

We consider a problem of the construction of feedback regulator which synthesizes the assigned stochastic sensitivity of the equilibrium in stochastically forced nonlinear dynamic system. In the case of complete information, it is shown that this problem can be reduced to the solution of the matrix algebraic equation. A presence of noise in measurements deforms the stochastic sensitivity. We find conditions when such deformation is extremely large, and the considered problem is ill-posed. For this ill-posed problem, a regularization method is suggested. We propose an analytical approach which allows us to take into account a presence of noise in measurements when we construct an optimal feedback regulator. General theoretical results are illustrated by examples.

Monitoring the status of infrastructural networks along their service life is fundamental to ensure a safe and good service quality. Due to the length and extension of infrastructures, it is fundamental to develop effective and low cost approaches that can allow a continuous monitoring. In this paper, an assessment method based on the ride comfort evaluation inside vehicles according to ISO 2631 (i.e. frequency weighted acceleration) was developed and tested on an Italian railway. In particular, the frequency weighted acceleration was calculated along the whole trip between two consecutive stops. In order to identify and localize the most critical areas along the traveling path, the vertical frequency weighted acceleration was also calculated for sub-sections of fixed lengths (i.e. 10 m) and then mapped on geographic information systems (GIS). In this way, it is also possible to determine, for example considering a railway infrastructure, whether the eventual discomfort may be due to localized irregularities or due to the passage on worn switches. Once proper threshold limit values are defined, early interventions can be planned in order to restore adequate comfort and safety levels. To test the proposed procedure, it was applied to a surface metropolitan railway characterized by an automatic guide, which granted the chance of evaluating the repeatability of the present approach. During the in-situ measurements, an inertial measurement unit (IMU) integrated together with a GPS receiver was used.

In this paper we introduce and characterize the notion of approximate predictability for the general class of metric systems, which are a powerful modeling framework to deal with complex heterogeneous systems such as hybrid systems. Approximate predictability corresponds to the possibility of predicting the occurrence of specific states belonging to a particular subset of interest, in advance with respect to their occurrence, on the basis of observations corrupted by measurement errors. We establish a relation between approximate predictability of a given metric system and approximate predictability of a metric system that approximately simulates the given one. This relation allows checking approximate predictability of a system with an infinite number of states, provided that one is able to construct a metric system with a finite number of states and inputs, approximating the original one in the sense of approximate simulation. The analysis of approximate predictability of Piecewise Affine (PWA) systems is carried out as an application of the proposed approach.

Internet of Things (IoT) is a novel paradigm attracting significant attention in the modern wireless telecommunications field. However, in some scenarios, the performance of IoT network is limited by energy-constrained devices. In order to improve the energy efficiency of such IoT devices, researchers have proposed several approaches based on duty cycle operation (switching devices between sleeping and active mode). However, current solutions adopting duty cycle (i.e., the fraction of time in which a node is active) have three issues: (i) they assign the same duty cycle ratio to all the nodes without balancing energy consumption; or (ii) they distribute different duty cycle ratios without considering the energy consumption during network construction phase; or (iii) their network structure models are based on concentric corona, instead of clustering structure. In this paper, we propose EnergIoT, a hierarchical clustering approach based on duty cycle ratio to maximize network lifetime of battery-powered IoT devices. In particular, we assign different duty cycle ratios to devices according to their distance from the sink, since different duty cycle ratios balance the energy consumption among devices at different layers. Furthermore, we calculate the energy consumption of IoT devices, considering both network construction phase and data processing phase. We evaluate EnergIoT through extensive simulation analyses on the OMNet++ platform. The result shows that EnergIoT is not only feasible but also efficient. Moreover, EnergIoT improves the network lifetime by 32%, compared to the uniform duty cycle approach, without sacrificing the network performance (i.e., end-to-end delay).