Application of EPR-MOGA in computing the liquefaction-induced settlement of a building subjected to seismic shake

Accurate prediction of the liquefaction-induced settlement (\({S}_{\mathrm{lc}}\)) is an essential requirement for a good design of buildings resting on liquefiable ground and subjected to seismic shake. However, prediction of the \({S}_{\mathrm{lc}}\) is not straightforward process and it requires advanced soil models and calibrated soil parameters that are not readily available for designers/practitioners. In addition, the available empirical models to estimate the \({S}_{\mathrm{lc}}\) have been developed using either classical regression analysis or multivariate adaptive regression splines and such techniques produce complicated models. Also, these empirical models have been developed utilizing results of numerical modelling. To overcome these limitations, novel model has been developed in this paper utilizing robust regression analysis driven by artificial intelligence called the evolutionary polynomial regression analysis. The new model has been developed using centrifuge results (real laboratory measurements) and can be easily used to accurately estimate the liquefaction induced settlement. The developed model scored a mean absolute error, root mean square error, mean, standard deviation of the predicted to measured values, coefficient of determination, \(a20 - \mathrm{index}\), and EPR coefficient of determination of 2.12 cm, 2.84 cm, 1.06, 0.19, 0.98, 0.77, and 97%, respectively, for the learning data and 1.73 cm, 3.31 cm, 0.99, 0.17, 0.97, 0.75, and 97%, respectively, for the examination data. The developed model has also been used in a parametric study to provide an insight into the sensitivity of the \({S}_{\mathrm{lc}}\) to the foundation width, building height, pressure applied on the foundation, thickness and relative density of the liquefiable layer, and earthquake intensity. The results obtained from the parametric study are reasonable and in agreement with previous studies in the literature. Thus, the developed model can be employed to optimize designs and to reduce design costs as it does not require complicated analyses and/or expensive computational facilities.

     

Large deflection electro-mechanical analysis of composite structures bonded with macro-fiber composite actuators considering thermal loads

In this paper, static analysis of laminated composite plates and shells bonded with macro-fiber composite (MFC) actuators under thermo-electro-mechanical loads is considered. Most earlier studies in the literature focused on the effects of MFC actuation power and fiber orientations on shape deformation of composite plates/shells subjected to electrical voltage only. Also most of the earlier studies on MFC-\(\hbox {d}_{33}\) bonded smart structures in literature are performed by commercial softwares like Ansys or Abaqus using the thermal strain equivalent approach to model the piezomechanical coupling. Here, our earlier developed geometrically nonlinear plate and shell finite elements considering finite rotation theory are extended for MFC actuator-bonded composite structures taking into account additionally the response to temperature gradients. An improved Reissner–Mindlin hypothesis is considered to derive the variational formulation, in which a parabolic assumption of transverse shear strains across the thickness is assumed. MFC actuators dominated by the \(\hbox {d}_{33}\) effect (MFC-\(\hbox {d}_{33}\)) with arbitrary fiber orientations are considered. The numerical model is validated with composite beams and plates by comparing the results of simulations with experimental investigations existing in the literature. An angle-ply composite shell structure is studied in detail concerning geometrically nonlinear analysis of bending and twisting deformations under different MFC-\(\hbox {d}_{33}\) fiber orientations under electric loading. Shape control of thermally induced deformations of composite plates and shells is performed using bonded MFC-\(\hbox {d}_{33}\) actuators and the significance of the present geometrically nonlinear model is highlighted.

     

Efficient monitoring of hyperproperties using prefix trees

Hyperproperties, such as non-interference and observational determinism, relate multiple computation traces with each other and are thus not monitorable by tools that consider computations in isolation. We present the monitoring approach implemented in the latest version of \(\text {RVHyper}\), a runtime verification tool for hyperproperties. The input to the tool are specifications given in the temporal logic \(\text {HyperLTL}\), which extends linear-time temporal logic (LTL) with trace quantifiers and trace variables. \(\text {RVHyper}\) processes execution traces sequentially until a violation of the specification is detected. In this case, a counterexample, in the form of a set of traces, is returned. \(\text {RVHyper}\) employs a range of optimizations: a preprocessing analysis of the specification and a procedure that minimizes the traces that need to be stored during the monitoring process. In this article, we introduce a novel trace storage technique that arranges the traces in a tree-like structure to exploit partially equal traces. We evaluate \(\text {RVHyper}\) on existing benchmarks on secure information flow control, error correcting codes, and symmetry in hardware designs. As an example application outside of security, we show how \(\text {RVHyper}\) can be used to detect spurious dependencies in hardware designs.

     

On the modeling of bending responses of graphene-reinforced higher order annular plate via two-dimensional continuum mechanics approach

This research presents bending responses of FG-GPLRC plates based upon higher order shear deformation theory (HSDT) for various sets of boundary conditions. The rule of the mixture and modified Halpin–Tsai model are engaged to provide the effective material constant of the composite layers. By employing Hamilton’s principle, the governing equations of the structure are derived and solved with the aid of the differential quadrature method (DQM). Afterward, a parametric study is done to present the effects of three kinds of FG patterns, weight fraction of the GPLs, radius ratio, and thickness to inner radius ratio on the bending characteristics of the FG-GPLRC disk. Numerical results reveal that in the initial value of the \(Zt/h\), using more GPLs for reinforcing the structure provides an increase in the normal stresses but this matter is inverse for the higher value of the \(Zt/h\). The results show that considering the smaller radius ratio is a reason for boosting the shear stresses of the structure for each \(Zt/h\). Another consequence is that for the negative value of \(Zt/h\), it is true that by increasing \(h/{R}_{i}\) , the normal stresses increases but if there is positive value for \(Zt/h\), the radial and circumferential stresses fall down by having an increase in the \(h/{R}_{i}\).

     

Numerical solution of a phase field model for polycrystallization processes in binary mixtures

We consider the numerical solution of a phase field model for polycrystallization in the solidification of binary mixtures in a domain \( \varOmega \subset \mathbb {R}^2\). The model is based on a free energy in terms of three order parameters: the local orientation \(\varTheta \) of the crystals, the local crystallinity \(\phi \), and the concentration c of one of the components of the binary mixture. The equations of motion are given by an initial-boundary value problem for a coupled system of partial differential equations consisting of a regularized second order total variation flow in \( \varTheta \), an \(L^2\) gradient flow in \(\phi \), and a \(W^{1,2}(\varOmega )^*\) gradient flow in c. Based on an implicit discretization in time by the backward Euler scheme, we suggest a splitting method such that the three semidiscretized equations can be solved separately and prove existence of a solution. As far as the discretization in space is concerned, the fourth order Cahn–Hilliard type equation in c is taken care of by a \(\hbox {C}^0\) Interior Penalty Discontinuous Galerkin approximation which has the advantage that the same finite element space can be used as well for the spatial discretization of the equations in \( \varTheta \) and \( \phi \). The fully discretized equations represent parameter dependent nonlinear algebraic systems with the discrete time as a parameter. They are solved by a predictor corrector continuation strategy featuring an adaptive choice of the time-step. Numerical results illustrate the performance of the suggested numerical method.

     

Weaknesses of some lightweight blockciphers suitable for IoT systems and their applications in hash modes

Twelve PGV models, MDC-2, and HIROSE, which are blockcipher-based hash functions, have been proven to be secure as hash functions when they are instantiated with ideal blockciphers. However, their security cannot be guaranteed when the base blockciphers use weak key-schedules. In this paper, we propose various related-key or chosen-key differential paths of Fantomas, Midori-128, GOST, and 12-round reduced AES-256 using key-schedules with weak diffusion effects. We then describe how these differential paths undermine the security of PGV models, MDC-2, or HIROSE. In addition, we show that the invariant subspace attacks on PRINT and Midori-64 can be transferred to collision attacks on their some hash modes.

     

Enhancing parameter estimation precision by non-Hermitian operator process

Recently, Zhong et al. (Phys Rev A 87:022337, 2013) investigated the dynamics of quantum Fisher information (QFI) in the presence of decoherence. We here reform their results and propose two schemes to enhance and preserve the QFIs for a qubit system subjected to a decoherence noisy environment by applying \({non\text {-}Hermitian}\) operator process either before or after the amplitude damping noise. Resorting to the Bloch sphere representation, we derive the exact analytical expressions of the QFIs with respect to the amplitude parameter \(\theta \) and the phase parameter \(\phi \), and in detail investigate the influence of \({non\text {-}Hermitian}\) operator parameters on the QFIs. Compared with pure decoherence process (without non-Hermitian operator process), we find that the \({post non\text {-}Hermitian}\) operator process can potentially enhance and preserve the QFIs by choosing appropriate \({non\text {-}Hermitian}\) operator parameters, while with the help of the \({prior non\text {-}Hermitian}\) operator process one could completely eliminate the effect of decoherence to improve the parameters estimation. Finally, a generalized non-Hermitian operator parameters effect on the parameters estimation is also discussed.     

Quantum Query Complexity of Almost All Functions with Fixed On-set Size

This paper considers the quantum query complexity of almost all functions in the set \({\mathcal{F}}_{N,M}\) of \({N}\)-variable Boolean functions with on-set size \({M (1\le M \le 2^{N}/2)}\), where the on-set size is the number of inputs on which the function is true. The main result is that, for all functions in \({\mathcal{F}}_{N,M}\) except its polynomially small fraction, the quantum query complexity is \({ \Theta\left(\frac{\log{M}}{c + \log{N} - \log\log{M}} + \sqrt{N}\right)}\) for a constant \({c > 0}\). This is quite different from the quantum query complexity of the hardest function in \({\mathcal{F}}_{N,M}\): \({\Theta\left(\sqrt{N\frac{\log{M}}{c + \log{N} - \log\log{M}}} + \sqrt{N}\right)}\). In contrast, almost all functions in \({\mathcal{F}}_{N,M}\) have the same randomized query complexity \({\Theta(N)}\) as the hardest one, up to a constant factor.     

MISCELA: discovering simultaneous and time-delayed correlated attribute patterns

This article addresses a new pattern mining problem in time series sensor data, which we call correlated attribute pattern mining. The correlated attribute patterns (CAPs for short) are the sets of attributes (e.g., temperature and traffic volume) on sensors that are spatially close to each other and temporally correlated in their measurements. Although the CAPs are useful to accurately analyze and understand spatio-temporal correlation between attributes, the existing mining methods are inefficient to discover CAPs because they extract unnecessary patterns. Therefore, we propose a mining method Miscela to efficiently discover CAPs. Miscela can discover not only simultaneous correlated patterns but also time delayed correlated patterns. Furthermore, we extend Miscela to automatically search for correlated patterns with any time delays. Through our experiments using three real sensor datasets, we show that the response time of Miscela is up to 20.84 times faster compared with the state-of-the-art method. We show that Miscela discovers meaningful patterns for urban managements and environmental studies.

     

Cryptanalysis of hash functions based on blockciphers suitable for IoT service platform security

It is well-known that blockcipher-based hash functions may be attacked when adopting blockciphers having related-key differential properties. However, all forms of related-key differentials are not always effective to attack them. In this paper we provide the general frameworks for collision and second-preimage attacks on hash functions by using related-key differential properties of instantiated blockciphers, and show their various applications. In the literature, there have been several provably secure blockcipher-based hash functions such as 12 PGV schemes, MDC-2, MJH, Abreast-DM, Tandem-DM, and HIROSE. However, their security cannot be guaranteed when they are instantiated with specific blockciphers. In this paper, we first observe related-key differential properties of some blockciphers such as Even-Mansour (EM), Single-key Even-Mansour (SEM), XPX with a fixed tweak (XPX₁₁₁₁), Chaskey cipher, and LOKI, which are suitable for IoT service platform security. We then present how these properties undermine the security of the aforementioned blockcipher-based hash functions. In our analysis, the collision and second-preimage attacks can be applied to several PGV schemes, MDC-2, MJH instantiated with SEM, XPX₁₁₁₁, Chaskey cipher, to PGV no.5, MJH, HIROSE, Abreast-DM, Tandem-DM instantiated with EM. Furthermore, LOKI-based MDC-2 is vulnerable to the collision attack. We also provide the necessary conditions for related-key differentials of blockciphers in order to attack each of the hash functions. To the best of our knowledge, this study is the first comprehensive analysis of hash functions based on blockciphers having related-key differential properties. Our cryptanalytic results support the well-known claim that blockcipher-based hash functions should avoid adopting blockciphers with related-key differential properties, such as the fixed point property in compression functions. We believe that this study provides a better understanding of the security of blockcipher-based hash functions.

     

Numerical simulations based on shifted second-order difference/finite element algorithms for the time fractional Maxwell’s system

In this article, mixed element algorithms with second-order time convergence results for the two-dimensional time fractional Maxwell’s equations in the Cole–Cole dispersive medium are developed. Fully discrete mixed element systems with shifted parameters \(\theta\) at time \(t=t_{n-\theta }\), which are constructed by combining the generalized BDF2-\(\theta\) schemes in temporal direction and a mixed element method in space direction, are formulated. For the two-dimensional case of the fractional Maxwell’s system, the algorithm implementation process based on the rectangular subdivision is shown in detail. Finally, two numerical examples are provided to confirm the validity of our method and to analyze the influence of parameters \(\alpha\), \(\theta\) for numerical solutions.

     

Bounds on Threshold Probabilities for Coloring Properties of Random Hypergraphs

We study the threshold probability for the property of existence of a special-form \(r\)?-?coloring for a random \(k\)?-?uniform hypergraph in the \(H(n,k,p)\) binomial model. A parametric set of \(j\)?-?chromatic numbers of a random hypergraph is considered. A coloring of hypergraph vertices is said to be \(j\)?-?proper if every edge in it contains no more than \(j\) vertices of each color. We analyze the question of finding the sharp threshold probability of existence of a \(j\)?-?proper \(r\)?-?coloring for \(H(n,k,p)\). Using the second moment method, we obtain rather tight bounds for this probability provided that \(k\) and \(j\) are large as compared to \(r\).

     

Scaling up stochastic gradient descent for non-convex optimisation

Stochastic gradient descent (SGD) is a widely adopted iterative method for optimizing differentiable objective functions. In this paper, we propose and discuss a novel approach to scale up SGD in applications involving non-convex functions and large datasets. We address the bottleneck problem arising when using both shared and distributed memory. Typically, the former is bounded by limited computation resources and bandwidth whereas the latter suffers from communication overheads. We propose a unified distributed and parallel implementation of SGD (named DPSGD) that relies on both asynchronous distribution and lock-free parallelism. By combining two strategies into a unified framework, DPSGD is able to strike a better trade-off between local computation and communication. The convergence properties of DPSGD are studied for non-convex problems such as those arising in statistical modelling and machine learning. Our theoretical analysis shows that DPSGD leads to speed-up with respect to the number of cores and number of workers while guaranteeing an asymptotic convergence rate of \(O(1/\sqrt{T})\) given that the number of cores is bounded by \(T^{1/4}\) and the number of workers is bounded by \(T^{1/2}\) where T is the number of iterations. The potential gains that can be achieved by DPSGD are demonstrated empirically on a stochastic variational inference problem (Latent Dirichlet Allocation) and on a deep reinforcement learning (DRL) problem (advantage actor critic - A2C) resulting in two algorithms: DPSVI and HSA2C. Empirical results validate our theoretical findings. Comparative studies are conducted to show the performance of the proposed DPSGD against the state-of-the-art DRL algorithms.

     

CoVeriTest: interleaving value and predicate analysis for test-case generation

Verification techniques are well-suited for automatic test-case generation. They basically need to check the reachability of every test goal and generate test cases for all reachable goals. This is also the basic idea of our CoVeriTest submission. However, the set of test goals is not fixed in CoVeriTest , instead we can configure the set of test goals. For Test-Comp’19, we support the set of all __VERIFIER_error() calls as well as the set of all branches. Thus, we can deal with the two test specifications considered in Test-Comp’19. Since the tasks in Test-Comp are diverse and verification techniques have different strengths and weaknesses, we also do not stick to a single verification technique, but use a hybrid approach that combines multiple techniques. More concrete, CoVeriTest interleaves different verification techniques and allows to configure the cooperation (i.e., information exchange and time limits). To choose from a large set of verification techniques, CoVeriTest is integrated into the analysis framework CPAchecker. For the competition, we interleave CPAchecker’s value and predicate analysis and let both analyses resume their analysis performed in the previous iteration.

     

Combined analytical and numerical approach for auxetic FG-CNTRC plate subjected to a sudden load

In the current work, the dynamic behavior of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) plate with negative Poisson’s ratio (NPR) is investigated by combining higher-order shear deformation theory and large deflection theory. First, explicit solutions are proposed to predict the effective Poisson’s ratio (EPR) of the laminates. Taking carbon nanotube-reinforced composite (CNTRC) as an example, the maximum NPR is obtained for \(\left( { \pm \theta } \right)_{{3{\text{T}}}}\) laminate as well. Results show that the EPR (\(v_{13}^{\text{e}}\),\(v_{23}^{\text{e}}\)) can range from a positive value of 0.311 to a negative value of 0.63. For the dynamic response problem, the asymptotic solutions with a two-step perturbation approach are derived for FG-CNTRC plates to capture the relationship between the center deflection and time. Several key factors such as functionally graded distribution, variations in the elastic foundation, and thermal stress produced by changing the temperature field are considered in the subsequent analysis. Numerical simulations are carried out to examine the corresponding dynamic behavior of FG-CNTRC plates when these factors are taken into account.

     

Finite approximation of the first passage models for discrete-time Markov decision processes with varying discount factors

This paper deals with the finite approximation of the first passage models for discrete-time Markov decision processes with varying discount factors. For a given control model \(\mathcal {M}\) with denumerable states and compact Borel action sets, and possibly unbounded reward functions, under reasonable conditions we prove that there exists a sequence of control models \(\mathcal {M}_{n}\) such that the first passage optimal rewards and policies of \(\mathcal {M}_{n}\) converge to those of \(\mathcal {M}\), respectively. Based on the convergence theorems, we propose a finite-state and finite-action truncation method for the given control model \(\mathcal {M}\), and show that the first passage optimal reward and policies of \(\mathcal {M}\) can be approximated by those of the solvable truncated finite control models. Finally, we give the corresponding value and policy iteration algorithms to solve the finite approximation models.