International Journal of Modern Physics C

In this paper, an autonomous ensemble approach of improved quantum inspired gravitational search algorithm (IQI-GSA) and hybrid deep neural networks (HDNN) is proposed for the optimization of computational problems. The IQI-GSA is a combinational variant of gravitational search algorithm (GSA) and quantum computing (QC). The improved variant enhances the diversity of mass collection for retaining the stochastic attributes and handling the local trapping of mass agents. Further, the hybrid deep neural network encompasses the convolutional and recurrent neural networks (HDCR-NN) which analyze the relational & temporal dependencies among the different computational components for optimization. The proposed ensemble approach is evaluated for the application of facial expression recognition by experimentation on Karolinska Directed Emotional Faces (KDEF) and Japanese Female Facial Expression (JAFFE) datasets. The experimentation evaluations evidently exhibit the outperformed recognition rate of the proposed ensemble approach in comparison with state-of-the-art techniques.

The robustness of interdependent networks has attracted much attention recently. Existing studies mainly focus on random failures, however, targeted attacks are ubiquitous in the real world. In this paper, a low degree neighbor node priority coupling (LDNPC) strategy is proposed, which enhances the robustness of interdependent networks under high-degree node targeted attacks by changing the relationship between layers to generate structures of overlapping links. First, nodes are ranked in descend according to their degrees. Then, nodes with low degrees have priority to choose their dependency partners to generate structures of overlapping links. Finally, experiments on three models of interdependent networks show that LDNPC can enhance the robustness of interdependent networks against high-degree node targeted attacks effectively.

Robustness is a critical characteristic of ubiquitous real networked systems which are often very vulnerable to the random failures or targeted attacks. In this work, we aim to evaluate the robustness of a traffic network which is constructed from real trajectory data. First, we divide a city into grids which are considered as nodes and a link is established if there is at least one taxi dispatch order from one grid to another. Second, we propose two categories of attack strategies: node attacks (e.g. random node failure, and degree, in-degree, out-degree, closeness, clustering coefficient, PageRank-based targeted attacks) and link attacks (e.g. random link failure and link weight, link degree, link betweenness-based targeted attacks). Third, we suppose all elements (i.e. node or link) are simultaneously or iteratively removed, and evaluate the network robustness by employing the relative size of the giant components, average clustering coefficient and average shortest path length. The results show that the degree-based targeted attacks are the most destructive among all attacks, and no matter node or link, the betweenness-based attack is the most effective method to be beneficial to the target index. Moreover, most methods with recalculations take priority over the ones without recalculations.

Robustness studies on integrated urban public transport networks have attracted growing attention in recent years due to the significant influence on the overall performance of urban transport system. In this paper, topological properties and robustness of a bus–subway coupled network in Beijing, composed of both bus and subway networks as well as their interactions, are analyzed. Three new models depicting cascading failure processes on the coupled network are proposed based on an existing binary influence modeling approach. Simulation results show that the proposed models are more accurate than the existing method in reflecting actual passenger flow redistribution in the cascading failure process. Moreover, the traffic load influence between nodes also plays a vital role in the robustness of the network. The proposed models and derived results can be utilized to improve the robustness of integrated urban public transport systems in traffic planning.

To detect the influence of MHD on migration of hybrid nanopowders, CVFEM has been employed in this paper. Mixture of Fe₃O₄ and MWCNT was added in water and for calculating properties, experimental formulas were utilized. To increase the convective mode, porous media has been used and tank was experienced in the horizontal magnetic field. In governing equations, there exist two new terms, one for permeable media and the other for MHD effect. Such complex physics needs special numerical approach and CVFEM has been utilized for this goal. Final formulation of PDEs did not have pressure terms and the stream function scalar was introduced. As permeability of zone enhances, nanopowders can transfer faster and the interaction of them with wall enhances, so, Nusselt number augments as well as stream function. Besides, employing higher Ha, the force against the buoyancy force increases and the velocity of operating fluid declines which provides lower convective flow. With rise of Ha, stream function declines about 48% and Nu declines about 31.92% when $\mathrm{\text{Da}}=100$. As Da rises, Nu rises about 33.43% when $\mathrm{\text{Ha}}=0$. Augment of Rd leads to augmentation of Nu.

In this paper, we present a numeric bifurcation analysis of the normal form of degenerate Hopf bifurcation truncated up to seventh order with an equilibrium point located at the origin. By applying the genericity nondegenerate conditions and normal form theory, we study the bifurcation analysis of the codimension-3 Takens–Hopf bifurcation for the difficult case, where a rich bifurcation scenario is displayed. The third Lyapunov coefficient is used to distinguish the different cases of a codimension-3 Takens–Hopf bifurcation point, which can be efficiently computed with the aid of a software program based on the symbolic package Maple, presented in Appendix A. The normal form analysis results can be used to depict the complete bifurcation diagrams and phase portraits. In order to investigate the mechanism of the transitions between equilibrium and limit cycles, the methods of two scales in frequency domain are employed to study the evolutions.

Researchers in heat transfer field always attempt to find new solutions to optimize the performance of energy devices through heat transfer enhancement. Among various methods which are implemented to reinforce the thermal performance of energy systems, one is utilizing porous media in heat exchangers. In this study, characteristics of laminar mixed convection in a porous two-sided lid-driven square cavity induced by an internal heat generation at the bottom wall have been carried out by using a numerical methodology based on the finite volume method and the full multigrid acceleration. The two-sided and top walls of the enclosure are assumed to have cold temperature while the remaining walls of the bottom wall are insulated. The working fluid is air so that the Prandtl number equates 0.71. The behavior of different physical parameters is shown graphically so that computations have been conducted over a wide range of pertinent parameters; (10${}^{-2}\le$ Ri $\le 10$), Darcy number ($10^{-4}\le$ Da $\le 10^{-1}$), internal Rayleigh number ($0\le$ Ra${}_I\le 10^4$), the porosity ($0.2\le \epsilon \le 0.8$) and the Grashof number (10${}^3\le$ Gr $\le 10^6$). Results revealed that heat transfer mechanism and the flow characteristics inside the enclosure are strongly dependent on the Grashof number. For instance, the best heat transfer rates at the considered values of internal Rayleigh numbers are obtained for a high Grashof number. Furthermore, an increase of internal heat generation (Ra_I) leads to a higher flow and temperature intensities for Grashof numbers ranging from $10^4$ to $10^6$ and a specific Richardson number value. Besides, an increase in porosity values ($\epsilon$) leads to an obvious decrease in the average Nusselt number. Maximum temperature ${\theta }_{\mathrm{\text{max}}}$ is optimal for high ($\epsilon$) value. A correlation expression for the average Nusselt number relative to the internal heat source was established in function of two control parameters such as Darcy and Richardson numbers.

We study the potential scenarios from a Susceptible-Infected-Recovered-Asymptomatic-Symptomatic-Dead (SIRASD) model. As a novelty, we consider populations that differ in their degree of compliance with social distancing policies following socioeconomic attributes that are observed in emerging and developing countries. Considering epidemiological parameters estimated from data of the propagation of SARS-CoV-2 in Brazil — where there is a significant stake of the population making their living in the informal economy and thus prone to not follow self-isolation — we assert that if the confinement measures are lifted too soon, namely as much as one week of consecutive declining numbers of new cases, it is very likely the appearance of a second peak. Our approach should be valid for any country where the number of people involved in the informal economy is a large proportion of the total labor force. In summary, our results point out the crucial relevance of target policies for supporting people in the informal economy to properly comply with preventive measures during the pandemic.

As one of the most densely populated countries in the world, Bangladesh has been trying to contain the impact of a pandemic like coronavirus disease 2019 (COVID-19) since March, 2020. Although government announced an array of restricted measures to slow down the diffusion in the beginning of the pandemic, the lockdown has been lifted gradually by reopening all the industries, markets and offices with a notable exception of educational institutes. As the physical geography of Bangladesh is highly variable across the largest delta, the population of different regions and their lifestyle also differ in the country. Thus, to get the real scenario of the current pandemic and a possible second wave of COVID-19 transmission across Bangladesh, it is essential to analyze the transmission dynamics over the individual districts. In this paper, we propose to integrate the Unscented Kalman Filter (UKF) with classic SIRD model to explain the epidemic evolution of individual districts in the country. We show that UKF-SIRD model results in a robust prediction of the transmission dynamics for 1–4 months. Then we apply the robust UKF-SIRD model over different regions in Bangladesh to estimates the course of the epidemic. Our analysis demonstrates that in addition to the densely populated areas, industrial areas and popular tourist spots will be in the risk of higher COVID-19 transmission if a second wave of COVID-19 occurs in the country. In the light of these outcomes, we also provide a set of suggestions to contain the future pandemic in Bangladesh.

In this paper, we give an equivalent form of Dickson’s conjecture. Based on this equivalent form, we propose a computational problem and obtain several interesting results.

From the perspective of mathematical epidemiology, COVID-19 epidemics emerge due to instabilities in epidemiological systems. It is shown that the COVID-19 outbreaks follow highly specified paths in epidemiological state spaces. These paths are described by phase portraits that can be readily computed from epidemiological models defined in terms of nonlinear dynamical systems. The paths are predicted by order parameters and amplitude equations that are well known in nonlinear physics and synergetics to exist at instability points. The approach is illustrated for SIR, SEIR and SEIAR models and epidemic outbreaks in China, Italy and West Africa. Identifying such COVID-19 order parameters may help in forecasting COVID-19 epidemics and predicting the impacts of intervention measures.

This paper introduces a theoretical and numerical study for the problem of Casson fluid flow and heat transfer over an exponentially variable stretching sheet. Our contribution in this work can be observed in the presence of thermal radiation and the assumption of dependence of the fluid thermal conductivity on the heat. This physical problem is governed by a system of ordinary differential equations (ODEs), which is solved numerically by using the differential transformation method (DTM). This numerical method enables us to plot figures of the velocity and temperature distribution through the boundary layer region for different physical parameters. Apart from numerical solutions with the DTM, solutions to our proposed problem are also connected with studying the skin-friction coefficient. Estimates for the local Nusselt number are studied as well. The comparison of our numerical method with previously published results on similar special cases shows excellent agreement.

World Trade Web is the backbone of the global economy system. Identifying influential countries and regions in such a network and revealing their importance evolution over time are helpful for understanding global economic development. Here, we collect the worldwide trade data in commodities of 232 countries and regions from 1996 to 2015 from the UN Comtrade Database, based on which a series of weighted world trade networks are constructed. Since the networks are almost fully connected, most of the existing methods may fail in identifying the important nodes. To tackle this issue, we apply the generalized Degree, $H$-index and Coreness (DHC) theorem to the constructed networks and use weighted degree and coreness to quantify nodes’ importance, since they can make full use of the weight information to accurately evaluate nodes’ significance. Then, we analyze the rankings of countries and regions measured by various indicators, whose differences and advantages are also compared. We further present the evolution of countries’ significance over time, two typical groups of countries. The results show that the influence of a country or region has a strong correlation with its economic scale, but a relatively weak correlation with the diversity of its trade structure. Finally, based on the findings, we put forward corresponding strategies to enhance the trade influence for different types of countries.