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The influence of conjugate heat transfer based on radiation and magnetohydrodynamic utilization is an attractive research area, with progressive features; it has many applications in thermal engineering, heat exchangers, cooling phenomenon, magnetic cell separation, energy production, hyperthermia, etc. Following the motivating significances of the current research topic, this paper explores the influences of an electrically conducting and radiating fluid with internal friction, heat generation and thermal radiation embedded in a porous medium past a flat permeable plate. The boundary layer equations are dimensionally transformed and solved numerically using implicit finite difference technique called the Keller-box method. The effect of various fluid obeying parameters such as magnetic field, viscous dissipation and heat generation on the flow factors such as velocity and temperature are graphed and discussed in this paper. Growing heat source, energy inside the fluid boosts, thereby increasing the energy of the flow. Increase in generation of energy reduces the viscosity of the flow reduces thereby increasing the velocity of the flow particles. [ABSTRACT FROM AUTHOR]

This paper describes the fundamental characteristics of cavitation in non-Newtonian liquids and bubble dynamics and then applies them to the domains of bioengineering and biomedicine. The goal of this paper is to examine how Newtonian nanomaterial flows hydromagnetically when subjected to a spinning disc considering such biomedical and bioengineering applications. The vertical axis of the disc rotates with a uniform angular frequency. The fundamental mathematical expressions are governed by the Navier–Stokes equations with the Maxwell equations of magnetism, we obtained ordinary differential equations utilizing Von Kármán's similarity transformations. Additionally, the effects of the magnetic field and radiation restrictions are considered. The RK-4 technique is used to solve the transmuted nonlinear ODEs. The analysis of MATLAB generated flow profiles has looked for changes in the values of key parameters. It is discovered that an increase in the thermal radiation parameter causes a decrease in the nanofluid temperature while an increase in the volume fraction of magnetite nanoparticles causes an increase. The skin-friction and heat-transfer rate at the disc are highly influenced by its rotational, the porosity of the porous media, thermal radiation and nanoparticle size. The rotational parameter, which regulates the disk's rotation, is a result of the rotating phenomenon. The research demonstrates that when the disk's rotation increases, the fluid motion accelerates in both the radial and cross-radial directions. Additionally, increasing the Prandtl number significantly improves heat transport, and a higher value for the rotation parameter shows a lesser concentration phenomenon. Additionally, the Nusselt number shows a decrease curve for a changeable thermal conductivity parameter. Finally, the current research can effectively close a gap in the physique of knowledge. [ABSTRACT FROM AUTHOR]

In this paper, the influence of velocity slip and the Newtonian heating parameters on Williamson Nanofluid across a variable stretching sheet is studied. The basic fluid flow equations are turned into a system of coupled ordinary differential equations with appropriate conditions, which are solved numerically with the Keller-box approach. The outcomes show that, increasing Williamson parameter, due to the viscosity velocity of the fluid slowdown. As a result, it is noticed that the velocity slip parameter reduces Williamson Nanofluid velocity, while increasing shear stress, according to the results. Furthermore, it has been discovered that unlike velocity profiles, the slip influence is more pronounced on temperature and concentration profiles. Furthermore, the Newtonian heating parameter may be shown to have rising functions for velocity and dimensionless temperature. Newtonian heating has uses in the petroleum industry, heat exchangers, conjugate heat transfer around fins and solar radiation. It is discovered that the Joule heating parameter improves the thermal boundary layer thickness and slows down the velocity of the fluid, which aids in maintaining system temperature. Additionally, it has been found that the temperature profile exhibits a stronger slip effect compared with the velocity profile. To prepare toffee, chocolate and other delicacies as efficiently as possible, it is crucial to investigate the flow of Williamson fluids (such as drilling muds, clay coatings, various suspensions and some lubricating oils, thermoplastic melts, and a variety of colloids) in the incidence of heat transfer. The novelty of this paper is the effect of joule heating, Newtonian heating parameter and velocity slip on Williamson fluid velocity and temperature gradient. Furthermore, the heat and mass transfer rates are calculated for various parameters numerically and shown in tabular form. [ABSTRACT FROM AUTHOR]

The bioconvective flows are truly connected to real-life and engineering development. So, the models of biomicrosystems and biocells are considered for the technical analysis in this paper. Our intention for the current analysis was to theoretically examine electrical conduction flow into mass and heat transfer by an extensive gyrotactic microorganism into an inclined magnetic field toward a vertical stretching sheet with nonlinear solar radiation with different solar thermal appliances. The effect on velocity slip and Joule heating was again studied in detail. This classical problem on Navier Stokes equations to the current imitation was decreased to ordinary differential equations by applying the comparison method. The numerical solutions were changed by boundary value problem (BVP) to clarify the subject into finite difference numerical scheme by applying MATLAB. The important results show that the density of motile microorganisms reduces to the bioconvection Lewis number and Peclet number, although reverse performance was noticed for the bioconvection Rayleigh number. Further, solar radiation fosters heat transport. In this paper, complete analysis is provided for potential functions of solar thermoelectric cells, solar ponds, solar thermal power fabrication, etc. [ABSTRACT FROM AUTHOR]

To further expand the application range of cold-formed steel (CFS) members in practical engineering, a novel fold-fastened multi-cellular steel wall (FMSW) was introduced and investigated in detail. The FMSWs were mechanically connected by the hook-shaped and groove-shaped regions at both ends of the single limb members, by which the assembly efficiency was greatly improved. In this paper, a total of 10 slender FMSW specimens were subjected to axial compressive loadings, and the failure mode, load–vertical displacement curves, load–lateral displacement curves, and bearing capacity of the specimens were obtained. According to the experimental results, the development and failure modes of the local-global interactive buckling of FMSWs were revealed. All specimens experienced local buckling initially, followed by global buckling, and ultimately interactive buckling. The load–displacement curves exhibited similar trends, being characterized by three stages: the elastic stage, the elastic-plastic stage, and the descending stage. Furthermore, the nonlinear ascending segment was short, indicating that the failure was sudden. By comparing the bearing capacities among specimens, it was recognized that the ultimate resistance of FMSWs could be obtained by the superposition of the cells, and the bearing capacity was rarely affected by the height-to-thickness ratio. Based on the experimental results, refined finite element (FE) models were established and the accuracy and effectiveness of the modeling method were verified. Valuable reference could be provided by the research achievements of this paper for the subsequent research of CFS built-up members and their application in practical engineering. [ABSTRACT FROM AUTHOR]

The paper focuses on the cutting behavior of Glass Fiber Reinforced Polymer (GFRP) composites and GNP–GFRP composites that contain varying amounts of Graphene Nano Platelets (GNP). GFRP composites are increasingly being used in a variety of industrial applications due to their excellent mechanical properties, such as high strength, stiffness, and low weight. However, their machining and cutting behavior can be challenging due to the presence of the reinforcing fibers. Therefore, the study aims to investigate the machining behavior of GFRP composites and the effect of adding GNP on their cutting behavior. The effect of different parameters such as cutting speed, feed rate and reinforcement rate on cutting forces and delamination factor is investigated. In addition, the tensile strength and fatigue behavior of the composite materials with the best and worst delamination factors were also determined. Addition of up to 0.2 wt.% of GNP to GFRP composites resulted in an increase in cutting forces and delamination factor when drilling GFRP composites. While the cutting force and delamination factor decreased with the increase in cutting speed, the cutting force and delamination factor increased with the increase in the feed rate. Analysis of variance (ANOVA) was performed to determine the effects of drilling parameters and reinforcement ratio on cutting force and delamination factor according to full factorial experimental design. The most efficient factor on the cutting forces is found to be feed rate (84.97%), followed by the reinforced rate (6.48%) and cutting speed (6.13%). The most efficient factor on the delamination factor is determined to be feed rate for (44.49%), followed by the reinforced rate (29.20%) and cutting speed (21.73%). [ABSTRACT FROM AUTHOR]

Let P (x) : = a d x d + ⋯ + a 0 ∈ ℚ [ x ] , a d > 0 , be a polynomial of degree d ≥ 2. Let (x n) be a sequence of integers satisfying x n + 1 = P (x n) for all  n = 0 , 1 , 2 , ... and x n → ∞ as  n → ∞. Set α : = lim n → ∞ x n d − n . Then, under the assumption a d 1 / (d − 1) ∈ ℚ , in a recent result by [A. Dubickas, Transcendency of some constants related to integer sequences of polynomial iterations, Ramanujan J. 57 (2022) 569–581], either α is transcendental or α can be an integer or a quadratic Pisot unit with α − 1 being its conjugate over ℚ. In this paper, we study the nature of such α without the assumption that a d 1 / (d − 1) is in ℚ , and we prove that either the number α is transcendental, or α h is a Pisot number with h being the order of the torsion subgroup of the Galois closure of the number field ℚ α , a d − 1 d − 1 . Other results presented in this paper investigate the solutions of the inequality | | q 1 α 1 n + ⋯ + q k α k n + β | | < n in (n , q 1 , ... , q k) ∈ ℕ × (K ×) k , considering whether β is rational or irrational. Here, K represents a number field, and ∈ (0 , 1). The notation | | x | | denotes the distance between x and its nearest integer in ℤ. [ABSTRACT FROM AUTHOR]

Denote by h = h (− p) the class number of the imaginary quadratic field ℚ (− p) with p prime. It is well known that h = 1 for p ∈ { 3 , 7 , 1 1 , 1 9 , 4 3 , 6 7 , 1 6 3 }. Recently, all the solutions of the Diophantine equation x 2 + p s = 4 y n with h = 1 were given by Chakraborty et al. in [Complete solutions of certain Lebesgue–Ramanujan–Nagell type equations, Publ. Math. Debrecen 97(3–4) (2020) 339–352]. In this paper, we study the Diophantine equation x 2 + p s = 2 r y n in unknown integers (x , y , s , r , n) , where s ≥ 0 , r ≥ 3 , n ≥ 3 , h ∈ { 1 , 2 , 3 } and gcd (x , y) = 1. To do this, we use the known results from the modularity of Galois representations associated with Frey–Hellegoaurch elliptic curves, the symplectic method and elementary methods of classical algebraic number theory. The aim of this paper is to extend the above results of Chakraborty et al. [ABSTRACT FROM AUTHOR]

To address the issue of frequency stability in microgrids with limited communication resources and bandwidth, this paper proposed an event-triggered control method based on a cloud-edge collaborative architecture. Firstly, to address the limited communication resources, event-triggered detector is set up at the edge to upload state variables and update control instructions only when the frequency deviation exceeds a pre-set threshold. Secondly, a fractional-order PI–PD controller is designed at the cloud control center, which achieves higher control degrees of freedom and stronger robustness than traditional integer-order PID control schemes. Additionally, to obtain better control parameters, an optimized design method based on an improved Big Bang-Big Crunch method (BB-BC3) is proposed for the fractional-order PI–PD controller. At last, a simulation example is given to prove the validity of the proposed method. Simulation results show that compared to the integer-order PI–PD controller, the fractional-order PI–PD controller based on the BB-BC3 algorithm proposed in this paper reduces the peak value of the response curve by 5%, and shortens the setting time by 0.14 s. [ABSTRACT FROM AUTHOR]

In this paper, we investigate in this paper the Type IV singular bouncing in the framework of f (R ,) theory of gravity where R and mean the curvature scalar and the Gauss–Bonnet invariant, respectively. Cosmological f (R ,) models constrained by the slow-roll evolution is reconstructed and their explicit forms are provided near the bounce and far away from it. One obtains finally two models whose stability is numerically analyzed in this work. Our results show that the stability of the reconstructed models is very affected by their parameters. The model far from the singularity recovers stability quickly than the model near the singularity. [ABSTRACT FROM AUTHOR]

This paper presents an analytical study of the behavior of radial free-geodesics in the Friedmann–Lemaître–Robertson–Walker (FLRW) spacetime within the Lambda Cold Dark Matter (Λ CDM) model. Using the radial free motion solutions, we provide two methods for characterizing the geodesics and defines a general formula that encapsulates all possible solutions, determined by two initial conditions. We show that the past light cone, event horizon, and particle horizon, can be considered as special cases of this overarching formula. Furthermore, the paper explores the free geodesics within the currently accepted cosmological model based on the recent Planck results, thoroughly examining the various possible geodesic scenarios. [ABSTRACT FROM AUTHOR]

The optimization of robot controller parameters is a crucial task for enhancing robot performance, yet it often presents challenges due to the complexity of multi-objective, multi-dimensional multi-parameter optimization. This paper introduces a novel approach aimed at efficiently optimizing robot controller parameters to enhance its motion performance. While spiking neural P systems have shown great potential in addressing optimization problems, there has been limited research and validation concerning their application in continuous numerical, multi-objective, and multi-dimensional multi-parameter contexts. To address this research gap, our paper proposes the Entropy-Weighted Numerical Gradient Optimization Spiking Neural P System, which combines the strengths of entropy weighting and spiking neural P systems. First, the introduction of entropy weighting eliminates the subjectivity of weight selection, enhancing the objectivity and reproducibility of the optimization process. Second, our approach employs parallel gradient descent to achieve efficient multi-dimensional multi-parameter optimization searches. In conclusion, validation results on a biped robot simulation model show that our method markedly enhances walking performance compared to traditional approaches and other optimization algorithms. We achieved a velocity mean absolute error at least 35% lower than other methods, with a displacement error two orders of magnitude smaller. This research provides an effective new avenue for performance optimization in the field of robotics. [ABSTRACT FROM AUTHOR]

A charge and discharge management scheme is proposed. The stored electric energy in distributed storage devices will converge to the consistent. The consistency of the stored electric energy of the devices helps to maintain the maximum load capacity and maximum consumption capacity of distributed storage devices. The charging and discharging process is constructed as a time-varying optimization problem, and the proposed algorithm can respond to the time-varying parameters of the distributed storage devices in real time. The time-varying neurodynamic algorithms can obtain time-varying optimal solution trajectories to give the optimal charging and discharging strategy in real time. In addition, the proposed approach in this paper focuses on the privacy protection of device data. Each device can calculate the power of discharging or charging by communicating with the partially connected nodes. Numerical simulations of the proposed scheme in the paper are given to verify the effectiveness of the scheme. Numerical simulations show that our scheme can make the electric energy stored in each storage device converge and maintain the maximum load capacity or maximum consumption capacity of the whole distributed storage device. [ABSTRACT FROM AUTHOR]

Confronted with the fast social development, the speed of garbage generation has increased. Therefore, from every aspect, especially staying green and healthy, it is urgent and vital to ensure accurate and stable garbage classification. In the field of garbage classification, household garbage has a large volume and the classification process still requires manual intervention. Besides, most of the current studies focus on industrial waste and medical waste, while the existing studies on household garbage are not effective enough. Furthermore, these studies are mostly trained and validated in self-built datasets, making the experimental results insufficiently representative and severely limiting the development of research. Aiming to facilitate the study of household garbage classification, this paper proposes a simple yet effective network model (FConvNet) to improve classification performance. In this paper, an effective convolution block with fused convolution is designed to enhance the potential correlation of the features in the spatial dimension, and then a lightweight symmetric structure is constructed to infer more information about the feature representation. The experiments on public datasets have justified the effectiveness of FConvNet with accuracy rates of 95%, 95% and 97%, achieving better performance on public datasets compared to baselines. Additionally, an online system based on the WeChat mini program framework is designed to provide convenient household garbage classification services and enable the collection of uploaded images to perform model optimizations. [ABSTRACT FROM AUTHOR]

This paper introduces a nonconvex ℓ1−2-analysis model: minx(∥D∗x∥ 1 −∥D∗x∥ 2)s.t. Ax = y, where A is a measurement matrix and D is a tight frame. Our main motivation is to generalize the sparse recovery via ℓ1 − ℓ2 minimization to this new model. As a nonconvex model, it is well known that its global minimizer and local minimizer are usually inconsistent. This paper provides a type of null space property (NSP) characterization which are necessary and sufficient conditions for the measurement matrix A such that a vector x can be recovered from Ax with a tight frame D via ℓ1−2-analysis local minimization, or any vector x can be uniformly recovered from Ax with a tight frame D via ℓ1−2-analysis minimization locally and globally. [ABSTRACT FROM AUTHOR]

The collective motions are studied using a recently created pseudopotential and some elastic constants. This paper involves the calculations of the collective motions like phonon dispersion curves (PDCs) for longitudinal and transverse frequencies (ωL and ωT), longitudinal sound velocity (vl), transverse sound velocity (vt), isothermal bulk modulus (B), modulus of rigidity (G), Young’s modulus (Y), Poisson’s ratio (σ), Debye temperature (θD) of some monovalent (Na), divalent (Mg) and polyvalent liquid metals (Al, Pb, Bi). This investigation is based upon the theory of pseudopotential of second-order approach via the equations of Hubbard and Beeby (HB). g(r) The pair correlation function is calculated from the different mean spherical approximation (MSA), one-component plasma (OCP) and optimized random phase approximation (ORPA) structure factors employed in this work. Three different types of local field correction (screening) functions proposed by Hartree (H), Taylor (T) and Nagy (N) are utilized in this paper. The current findings are found to be in qualitative accord with experimental and theoretical data. [ABSTRACT FROM AUTHOR]

This research paper introduces a novel approach to deriving traveling wave solutions (TWSs) for the Caputo-fractional Klein–Gordon equations. This research presents a distinct methodological advancement by introducing TWSs of a particular time-fractional partial differential equation, utilizing a non-local fractional operator, specifically the Caputo derivative. To achieve our goal, a novel transformation is considered, that converts a time-fractional partial differential equation into fractional ordinary differential equations, enabling analytical solutions through various analytical methods. This paper employs the homotopy analysis method to achieve the target objectives. To demonstrate the efficiency and applicability of the proposed transform and method, two examples are discussed and analyzed in figures. [ABSTRACT FROM AUTHOR]

The possibility of the existence of multiquark hadrons made of 4-quarks for mesons and 5-quarks for baryons was predicted by Gell-Mann [Phys. Lett. 8, 214 (1964)]. The renewed interest for the search for exotic pentaquark states was initiated by the paper by Diakonov, Petrov, and Polyakov [Z. Phys. A 359, 305 (1997)]. The 2003 experimental reports on the observation of Θ+ pentaquark with uudds̄ quark content created a great excitement and many following experiments have reported its observation [K. H. Hicks, Eur. Phys. J. H 37, 1 (2012)]. After high-statistics experiments at JLab, which did not confirm previous claims by the CLAS collaboration, the community concluded that the Θ+ pentaquark either does not exist at all or has an extremely small cross-section, making it currently unobserved. There were different review papers on this subject, questioning the existence of Θ+ or trying to explain the reasons why reaching a conclusion based on production experiments is challenging [M. Amaryan, Eur. Phys. J. Plus 137, 684 (2022)]. To address the challenge of minimal 3-body final states, a formation experiment with a projectile-kaon beam is proposed. In the following, we discuss how the Θ+ could be observed in the KLp→Θ+→K+n reaction in the KLF experiment at JLab [M. Amaryan et al. [KLF Collaboration], arXiv:2008.08215 [nucl-ex]]. [ABSTRACT FROM AUTHOR]

The prediction of price trends in the stock market has always been a hot research topic in the financial field. However, due to the high instability and volatility of stock prices, it is very difficult to accurately predict stock trends. How to remove the noise of stock data, extract effective features, and pursue maximum value returns has always been a challenge. This paper proposes a hybrid model (DWT-DQN) that combines discrete wavelet transform with deep reinforcement learning to improve the accuracy and return rate of stock predictions. First, the model captures price fluctuation information on different scales by performing discrete wavelet transformation on the difference between long- and short-term moving averages of stock prices, and well extracts the changing characteristics of stock price data in the time domain and frequency domain. Then the feature data are input into the built DQN network for model training. The network can select the optimal trading action based on market status and historical experience and returns. At the same time, during the data sampling process, an attention mechanism is introduced to allow the model to further learn in the direction of maximizing returns. Through testing and verification on SSEC, HSI, NDX and SPX data sets, experiments show that the hybrid model proposed in this paper has excellent performance in terms of accuracy and return rate. [ABSTRACT FROM AUTHOR]

This paper reviews Holevo’s contributions to quantum information theory during the 20 century. At that time, he mainly studied three topics, classical-quantum channel coding, quantum estimation with Craméro–Rao approach and quantum estimation with the group covariant approach. This paper addresses these three topics. [ABSTRACT FROM AUTHOR]

In this paper, the effects of the Ohmic and magnetic density currents are investigated in the linearized Euler–Heisenberg (EH) electrodynamics (ED). The linearization is introduced through an external magnetic field, in which the vector potential of the EH ED is expanded around a magnetic background field that we consider uniform and constant in this paper. From the EH linearized equations, we obtain the solutions for the refractive index associated with the electromagnetic wave superposition, when the current density is ruled by the Ohm law, and in the second case, when the current density is set by an isotropic magnetic conductivity. These solutions are functions of the magnetic background (B) of the wave propagation direction (k). It also depends on the conductivity and on the wave frequency. As a consequence, the dispersion and the absorption of plane waves change when B is parallel to k in relation to the case of B perpendicular to k in the medium. The characteristics of the refraction index are related to direction of B and of the wave polarization, where there is an open discussion for the birefringence in this medium. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative composite sliding mode control strategy tailored for large-scale system, specifically tackling the intricate task of formulating a sliding mode control law for singularly perturbed systems. This paper delineates the development of a composite controller by dissecting it into subsystem controllers for both ‘slow’ and ‘fast’ subsystems, exploring its effectiveness in managing matched bounded external disturbances within the context of large-scale system. While sliding mode control proves to be a robust solution for handling uncertainty and disturbances, its inherent complexity and discontinuous characteristics pose significant challenges in crafting designs suitable for singularly perturbed systems. [ABSTRACT FROM AUTHOR]

Path planning is an essential subproblem of autonomous robots’ navigation. Reaching a given goal pose or covering the available space are typical navigation missions, that require different planning approaches. We focus on such problems in this paper, where a goal pose must be reached by a wheeled autonomous ground vehicle in challenging situations, i.e. in complex environments with limited free space. Many path-planning methods are available, from which the sampling-based approaches gained the highest interest due to their computational efficiency. However, the performance of such methods degrades if the free space is limited and narrow passages have to be crossed on the way to the goal. Finding real-time planning methods to deliver high-quality paths in such situations is challenging. This paper aims to take steps toward solving this problem. On the one hand, an approach is presented to characterize free space narrowness and the difficulty of planning tasks. This can be used as a tool to compare planning queries and evaluate the performance of planning methods from the perspective of their sensitivity to environmental narrowness. On the other hand, an improved variant of our previously proposed RTR planner, an incremental sampling-based path-planning method, is introduced that exhibits good performance even in narrow and difficult planning situations. It is shown by simulations that it outperforms the popular RRT and RRT* planners in terms of running time and path quality, and that it is less sensitive to the narrowness of the environment where the planning task has to be solved. [ABSTRACT FROM AUTHOR]

In this work, we generalize the theory of perturbations in a (D+1)-dimensional space–time with cosmological constant, studying scalar, vector and tensor perturbations, as well as its structure in Newtonian and Synchronous gauge. We also show the theory of perturbations in the context of brane cosmology, where branes are embedded in a set of D-spatial dimensions, a temporal dimension, and an additional spatial dimension. In both standard and brane cosmology, an unperturbed space–time is provided with a Friedmann–Lemaitre–Robertson–Walker metric and arbitrary sectional curvature, the matter content has the shape of a perfect fluid. In addition, we consider the arbitrary sectional curvature, obtaining the respective equations in the Newtonian and Synchronous gauge. We highlight that the results presented in this paper can be used to treat brane cosmology with two concentric branes or tackle the σ8 tension with a braneworld approach. Finally, as an example of the utility of all the technology presented in this paper, we show an application to the energy flux and the repercussions in the framework of the braneworlds. [ABSTRACT FROM AUTHOR]

In this paper, we have successfully obtained the mean mass-density parameter (ρm) using the nuclear masses AME2020 database and nuclear charge radius (CR) CR2013 database. The empirical formula is derived based on the relationship between ρm and N∕Z (the ratio of the number of neutrons to protons). Subsequently, we obtained an empirical formula for the difference in ρm between two neighboring isotopes. By utilizing this empirical formula along with the AME2020 and CR2013 databases, we then calculated 625 charge radii for nuclei with N≥21. The root-mean-square deviation (RMSD) between the calculated values and the experimental values in the CR2013 database is 0.0075fm. The predicted nuclear CR values are comparable to those of other researches, which some predictions closely matching the experimental values measured in recent years. Additionally, this work used the Back Propagation (BP) neural network to establish a model for describing and predicting the difference in the mean mass-density parameter between two neighboring isotopes. The RMSD between the calculated and experimental values obtained using this model is 0.0039fm. Some of our predicted values have good accuracy and compared well with experimental values. Both of the above methods indicate that the nuclear CR relationship proposed in this paper based on the difference in mean mass-density parameter has simplicity and reliability. [ABSTRACT FROM AUTHOR]

In previous works, we have proven that there are local tetrads in four-dimensional curved Lorentzian spacetimes that can be written in terms of two kinds of local structures, the skeletons and the gauge vectors. These tetrads diagonalize locally and covariantly the stress–energy tensors for systems of differential equations of the Einstein–Maxwell kind in the Abelian electromagnetic case, or of the Einstein–Maxwell–Yang-Mills kind when non-Abelian Yang–Mills fields are included, along with suitable Yang–Mills stress–energy tensors. Under local Lorentz transformations, these new tetrads conserve their skeleton-gauge vector structure. In this short paper, we will prove that given any general unit orthogonal tetrad in spacetime, we will be able to construct a new tetrad in the skeleton-gauge vector form. We will prove a theorem stating that the original orthonormal tetrad can be constructed or reexpressed with this same local tetrad skeleton-gauge vector structures. The theorems proved in this paper will enable the demonstration of new results in group isomorphism theorems in the future. [ABSTRACT FROM AUTHOR]

Battery Management System (BMS) functions to monitor individual cell in a battery pack and its crucial task is to maintain stability throughout the battery pack. The BMS is responsible for maintaining the safety of the battery as well as not to harm the user or environment. The parameters that are to be monitored in a battery are Voltage, Current and Temperature. With the collected data, BMS carefully monitors the charging–discharging behavior of the battery particularly in the Lithium-ion (Li-ion) batteries in which charging and discharging behavior are completely different. This paper proposes a real-time IOT connected deep learning algorithm for estimation of State-of-Charge (SoC) of Li-ion batteries. This paper provides unique objectives and congruence between model-based conventional methods and state-of-the-art deep learning algorithm, specifically Feed Forward Neural Network (FNN) which is nonRecurrent. This paper also highlights the advantages of Internet-of-Things (IoT) connected deep learning algorithm for estimation of State-of-Charge of Li-ion batteries in Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs). The major advantage of the proposed method is that the Artificial Intelligence (AI)-based techniques aim to bring the estimation error less than 2% at a low cost and time without the model of the battery, at par with conventional method of Extended Kalman Filter (EKF) which is the best ever practical estimation theory. Another advantage of the proposed method is that in an abnormal condition (i.e., Unsafe Temperature) the IF This Then That (IFTTT) IoT mobile application interfaced with BMS through ThingSpeak cloud, sends a notification alert to the battery expert or to the user prior to an emergency. Finally, the real-time data of the battery parameters are collected through ThingSpeak cloud platform for future research and analysis. [ABSTRACT FROM AUTHOR]

The 21st century is an era of rapid development of high-tech industry. Through continuous collection and sharing of data, IoT technology connected by things has penetrated into every aspect of human life. Modern organizations find that they increasingly rely on knowledge and information sharing and interconnection to enhance their innovation and development capabilities. Therefore, this paper studies the strategic decision-making of knowledge sharing among employees on the IoT platform drawing on evolutionary game theory, this paper constructs a three-party game model composed of "organization-knowledge sharers-knowledge seekers" from the perspective of stakeholders, and discusses the strategic choice of organization and employee behavior under the dynamic decision mechanism and when the game reaches equilibrium and stability. Moreover, this paper uses MATLAB 2016a to simulate the model. The results show that under the premise of higher organizational rewards, synergistic benefits, high-shared extra income, knowledge-sharing preferences, incentive preferences of the organization, the system is easier to reach the ideal state. With the smaller cost of sharing and incentive, organization and employees are more willing to be motivators and sharers, while the incentive degree of organization should be controlled within a reasonable range. This paper can provide specific theoretical and practical guidance for the practice of organizational knowledge management. [ABSTRACT FROM AUTHOR]

Accurately predicting the maximum temperature is essential for studying human comfort, ecological environment development and social progress. However, traditional prediction methods are inefficient and inaccurate when dealing with large volumes of meteorological data. To tackle these challenges, this paper introduces an integrated approach, the ARIMA–LSTM–XGBoost model, which combines the strengths of autoregressive integrated moving average (ARIMA), long short-term memory network (LSTM) and eXtreme Gradient Boosting (XGBoost) to predict the maximum temperature. The proposed model enhances the prediction accuracy and convergence rate through techniques like MAPE reciprocal weight (MAPE-RW) and Schedule Sampling. Additionally, the model selects the best performing model using the early stopping method. This paper compares and analyzes the prediction results of the ARIMA, LSTM, XGBoost and ARIMA–LSTM–XGBoost models. The experimental results indicate that the ARIMA–LSTM–XGBoost model proposed in this paper achieves superior prediction accuracy, performance, and confidence. The ARIMA–LSTM–XGBoost model shows a Root-Mean-Squared Error (RMSE) of 1.381, significantly outperforming the ARIMA model (3.828), LSTM model (3.360) and XGBoost model (1.422). The coefficient of determination ( R 2) is 0.977, surpassing the values of 0.905 for the ARIMA model, 0.922 for the LSTM model and 0.910 for the XGBoost model. The ARIMA–LSTM–XGBoost model also exhibits a higher confidence level compared to the individual models. [ABSTRACT FROM AUTHOR]

The low-light image enhancement task aims to improve the visibility of information in the dark to obtain more data and utilize it, while also improving the visual quality of the image. In this paper, we propose a dual cross-attention multi-stage embedding network (DCMENet) for fast and accurate enhancement of low-light images into high-quality images with high visibility. The problem that enhanced images tend to have more noise in them, which affects the image quality, is improved by introducing an attention mechanism in the encoder–decoder structure. In addition, the encoder–decoder can focus most of its attention on the dark areas of the image and better attend to the detailed features in the image that are obscured by the dark areas. In particular, the poor performance of the Transformer when the dataset size is small is solved by fusing the CNN-Attention and Transformer in the encoder. Considering the purpose of the low-light image enhancement task, we raise the importance of recovering image detail information to the same level as reconstructing the lighting. For features such as texture details in images, cascade extraction using spatial attention and pixel attention can reduce the model complexity while the performance is also improved. Finally, the global features obtained by the encoder–decoder are fused into the shallow feature extraction structure to reconstruct the illumination while guiding the network for the focused extraction of information in the dark. The proposed DCMENet achieves the best results in both objective quality assessment and subjective evaluation, while for the computer vision tasks working in low-light environments as well, the enhanced images using the DCMENet proposed in this paper show the best performance. [ABSTRACT FROM AUTHOR]

The real world is full of uncertainties, which we require appropriate mathematical structures to model and handle them. One such structure is the soft set, which can be combined with various algebraic and topological structures. The paper discusses how soft sets and hyperstructures can be combined to create new soft structures that can handle uncertainty and imprecision in algebraic structures. Soft sets are mappings from parameters to subsets of a universal set, and they can model fuzzy concepts. Hyperstructures are generalizations of classical algebraic structures, where the composition of two elements is a set instead of a single element. They can capture complex and diverse phenomena that cannot be modeled by single-valued operations. The paper gives examples of soft structures, such as soft polygroups, soft topological polygroups, soft topological soft polygroups and their applications in mathematics and science. The paper aims to show the usefulness and versatility of soft structures in dealing with uncertainty and imprecision in algebraic structures. We will define the concept of soft topological soft polygroups and examine its characteristics. [ABSTRACT FROM AUTHOR]

In this paper, we study a class of conformal metric deformations in the quasi-radial coordinate parametrizing the three-sphere in the conformally compactified Minkowski spacetime S1 × S3. Prior to reduction of the associated Laplace–Beltrami operators to a Schrödinger form, a corresponding class of exactly solvable potentials (each one containing a scalar and a gradient term) is found. In particular, the scalar piece of these potentials can be exactly or quasi-exactly solvable, and among them we find the finite range confining trigonometric potentials of Pöschl–Teller, Scarf and Rosen–Morse. As an application of the results developed in the paper, the large compactification radius limit of the interaction described by some of these potentials is studied, and this regime is shown to be relevant to a quantum mechanical quark deconfinement mechanism. [ABSTRACT FROM AUTHOR]

The discovery of the Jones polynomial made an important connection between quantum physics and knot theory. Kauffman and Lomonaco introduced the knot mosaic system to define the quantum knot system for the purpose of representing an actual physical quantum system. This paper is inspired by an open question about the knot mosaic enumeration suggested by them. A knot m × n-mosaic is an m × n array of 11 mosaic tiles representing a knot diagram by adjoining properly. The total number Dm×n of knot m × n-mosaics, which indicates the dimension of the Hilbert space of the quantum knot system, is known to grow in a quadratic exponential rate. Recently, Oh et al. developed the state matrix recursion method producing the exact enumeration of knot mosaics, which uses a recursion formula of state matrices. Furthermore, they showed the existence of the knot mosaic constant δ =limm,n→∞(Dm×n) 1 mn and found its upper and lower bounds in a series of papers. The latest upper bound was obtained through two new concepts: quasimosaics and cling mosaics. As a sequel to this research program, we adjust the state matrix recursion method to handle cling mosaics inside a quasimosaic, which is called the progressive state matrix recursion method. This method provides recursive matrix-relations producing a sharper bound of the knot mosaic constant: 4 ≤ δ ≤ 4.1035507⋯. [ABSTRACT FROM AUTHOR]

The rapid growth of contents on the Web in different languages increases the demand of Cross-Lingual Information Retrieval (CLIR). The accuracy of result suffers due to many problems such as ambiguity and drift issue in query. Query Expansion (QE) offers reliable solution for obtaining suitable documents for user queries. In this paper, we proposed an architecture for Hindi–English CLIR system using QE for improving the relevancy of retrieved results. In this architecture, for the addition of term(s) at appropriate position(s), we proposed a location-based algorithm to resolve the drift query issue in QE. User queries in Hindi language have been translated into document language (i.e. English) and the accuracy of translation is improved using Back-Translation. Google search has been performed and the retrieved documents are ranked using Okapi BM25 to arrange the documents in the order of decreasing relevancy to select the most suitable terms for QE. We used term selection value (TSV) for QE and for retrieving the terms, we created three test collections namely the (i) description and narration of the Forum for Information Retrieval Evaluation (FIRE) dataset, (ii) Snippets of retrieved documents against each query and (iii) Nearest-Neighborhood (NN) words against each query word among the ranked documents. To evaluate the system, 50 queries of Hindi language are selected from the FIRE-2012 dataset. In this paper, we performed two experiments: (i) impact of the proposed location-based algorithm on the proposed architecture of CLIR; and (ii) analysis of QE using three datasets, i.e. FIRE, NN and Snippets. In the first case, result shows that the relevancy of Hindi–English CLIR is improved by performing QE using the location-based algorithm and a 12% of improvement is achieved as compared to the results of QE obtained without applying the location-based algorithm. In the second case, the location-based algorithm is applied on three datasets. The Mean Average Precision (MAP) values of retrieved documents after QE are 0.5379 (NN), 0.6018 (FIRE) and 0.6406 (Snippets) for the three test collections, whereas the MAP before QE is 0.37102. This clearly shows the significant improvement of retrieved results for all three test collections. Among the three test collections, QE has been found most effective along with Snippets as indicated by the results with the improvements of 6.48% and 19.12% over FIRE and NN test collections, respectively. [ABSTRACT FROM AUTHOR]

In this paper, Kudryashov and modified Kudryashov methods are implemented for the first time to compute new exact traveling wave solutions of the space-time fractional (3+1)-dimensional Calogero–Bogoyavlenskii–Schiff (CBS) equation and Calogero–Bogoyavlenskii–Schiff and Bogoyavlensky Konopelchenko (CBS-BK) equation. With the help of wave transformation, the aforementioned fractional differential equations are converted into nonlinear ordinary differential equations. The purpose of this paper is to devise novel exact solutions for the space-time-fractional (3+1)-dimensional CBS and the space-time-fractional CBS-BK equations by utilizing the Kudryashov and modified Kudryashov techniques. The solutions, thus, acquired are demonstrated in figures by choosing appropriate values for the parameters. The solutions derived take the form of various wave patterns, including the kink type, the anti-kink type and the singular kink wave solutions. The obtained solutions are indeed beneficial to analyze the dynamic behavior of fractional CBS and CBS-BK equations in describing the interesting physical phenomena and mechanisms. The obtained solutions are entirely new and can be considered as a generalization of the existing results in the ordinary derivative case. The techniques presented here are very simple, efficacious and plausible and hence can be employed to attain new exact solutions for fractional PDEs. [ABSTRACT FROM AUTHOR]

This paper studies the task of vision-based MAV-catching-MAV, where a catcher MAV (micro aerial vehicle) can detect, localize, and pursue a target MAV autonomously. Since it is challenging to develop detectors that can effectively detect unseen MAVs in complex environments, the main novelty of this paper is to propose a real-to-sim-to-real approach to address this challenge. In this method, images of real-world environments are first collected. Then, these images are used to construct a high-fidelity simulation environment, based on which a deep-learning detector is trained. The merit of this approach is that it allows efficient automatic collection of large-scale and high-quality labeled datasets. More importantly, since the simulation environment is constructed from real-world images, this approach can effectively bridge the sim-to-real gap, enabling efficient deployment in real environments. Another contribution of this paper lies in the successful implementation of a fully autonomous vision-based MAV-catching-MAV system including proposed estimation and pursuit control algorithms. While the previous works mainly focused on certain aspects of this system, we developed a completely autonomous system that integrates detection, estimation, and control algorithms on real-world robotic platforms. [ABSTRACT FROM AUTHOR]

This paper presents full-scale observations of wind-induced vibrations on a 140m high cylindrical reinforced concrete tower under non-stationary and strong wind conditions. The vibration responses of the tower in two planar orthogonal axes and rotation, in conjunction with wind speed and direction data, have been utilized to extract the response characteristics. The primary focus is on discussing the correlation of wind-induced responses in three components: Along-wind, across-wind, and torsion. Throughout the varying levels of oscillation, the tower’s responses clearly exhibit correlations among these components. The correlation coefficients between along-wind and across-wind responses, as well as along-wind and torsional responses, remain negligible across the entire dataset. In contrast, during intense oscillations, there is a near-perfect correlation between the across-wind and torsional responses. Furthermore, the probability density functions (PDFs) of the response components under strong wind conditions significantly deviate from the Gaussian distribution and closely resemble the Cauchy distribution. The joint PDFs also indicate that the along-wind response is statistically independent of the other response components, while the across-wind response correlates well with the torsion, as indicated by the non-Gaussian distribution. This paper also includes distinct observations regarding dominant oscillating frequencies, torsional amplitudes, and vertical vibration amplitudes. The importance of this research lies in its examination of the relationship between different response components, a crucial aspect in understanding how structures behave under wind loading. By emphasizing the need for full-scale measurements, this study aims to provide valuable validation for previous theoretical and experimental research findings. [ABSTRACT FROM AUTHOR]

This paper considers the possibility that abstract thinking and advanced synthesis skills might encourage extraterrestrial civilizations to accept communication with mankind on Earth. For this purpose, a notation not relying upon the use of alphabet and numbers is proposed, in order to denote just some basic geometric structures of current physical theories: vector fields, 1-form fields, and tensor fields of arbitrary order. An advanced civilization might appreciate the way here proposed to achieve a concise description of electromagnetism and general relativity, and hence it might accept the challenge of responding to our signals. The abstract symbols introduced in this paper to describe the basic structures of physical theories are encoded into black and white bitmap images that can be easily converted into short bit sequences and modulated on a carrier wave for radio transmission. [ABSTRACT FROM AUTHOR]

Many medical reports and documents in printed form are available in huge sizes in archive units inside medical centers and hospitals around the world. The printed electrocardiogram paper is one type of archive data and is more powerful for expert cardiologists to study various cardiac diseases. On the other hand, the widespread development in the ability of intelligent computer systems to process digital signals increases the benefit of these data if converted to digital form. In this paper, a new approach for digital recovery of 12-lead electrocardiogram raw data from the printed colored scanned image has been proposed. This approach implements an algorithm with four steps including delineating effective regions, color filtering, contacting detected points, and sampling the resulted digital signals to reconstruct the digital electrocardiogram signal from the printed drawing of the same signal after digital scanning with significant resolution. Also, this algorithm is designed to process various kinds of printed electrocardiogram papers. The performance of the proposed approach is evaluated qualitatively by visual inspection of the recovered and original signals in the same graph. Also, the similarity of these signals is evaluated quantitatively using some standard evaluation metrics. The simulation results show the consistency and robustness of the proposed digital recovery approach to generate electrocardiogram digital data with a high percentage accuracy exceeding 98%. Also, plotting the recovered signal with the original printed signal on the same graph shows a significant percentage of congruence in time and amplitude. Finally, the proposed idea in this study opens the way for an unlimited bank of digital electrocardiogram data with different morphologies. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a popular neurological disorder affecting a critical part of the world's population. Its early diagnosis is extremely imperative for enhancing the quality of patients' lives. Recently, improved technologies like image processing, artificial intelligence involving machine learning, deep learning, and transfer learning have been introduced for detecting AD. This review describes the contribution of image processing, feature extraction, optimization, and classification approach in AD recognition. It deeply investigates different methods adopted for multiclass diagnosis of AD. The paper further presents a brief comparison of existing AD studies in terms of techniques adopted, performance measures, classification accuracy, publication year, and datasets. It then summarizes the important technical barriers in reviewed works. This paper allows the readers to gain profound knowledge regarding AD diagnosis for promoting extensive research in this field. [ABSTRACT FROM AUTHOR]

The focus of this paper is impulse noise reduction in digital color images. The most popular noise reduction schemes are the vector median filter and its many variants that operate by minimizing the aggregate distance from one pixel to every other pixel in a chosen window. This minimizing operation determines the most confirmative pixel based on its similarity to the chosen window and replaces the central pixel of the window with the determined one. The peer group filters, unlike the vector median filters, determine a set of pixels that are most confirmative to the window and then perform filtering over the determined set. Using a set of pixels in the filtering process rather than one pixel is more helpful as it takes into account the full information of all the pixels that seemingly contribute to the signal. Hence, the peer group filters are found to be more robust to noise. However, the peer group for each pixel is computed deterministically using thresholding schemes. A wrong choice of the threshold will easily impair the filtering performance. In this paper, we propose a peer group filtering approach using principles of Bayesian probability theory and clustering. Here, we present a method to compute the probability that a pixel value is clean (not corrupted by impulse noise) and then apply clustering on the probability measure to determine the peer group. The key benefit of this proposal is that the need for thresholding in peer group filtering is completely avoided. Simulation results show that the proposed method performs better than the conventional vector median and peer group filtering methods in terms of noise reduction and structural similarity, thus validating the proposed approach. [ABSTRACT FROM AUTHOR]

Mandelbrot set, which was provided as a highlight in fractal and chaos, is studied by many researchers. With the extension of Mandelbrot set to generalized M set with different kinds of exponent k (k − M set), properties are hard to understand when k is a complex number. In this paper, fractal property of generalized M set with complex exponent z is studied. First, a relation is constructed between generalized M set with complex and real exponent. Then, distribution of z − M set on complex plane is researched. Meanwhile, symmetry of generalized M set is proved. Finally, graphics, generated by escape time algorithm, are the validated results of this paper. [ABSTRACT FROM AUTHOR]

In this paper, within the scope of the local fractional derivative theory, the (4+1)-dimensional local fractional Fokas equation is researched. The study of exact solutions of high-dimensional nonlinear partial differential equations plays an important role in understanding complex physical phenomena in reality. In this paper, the exact traveling wave solution of generalized functions is analyzed defined on Cantor sets in high-dimensional integrable systems. The results of non-differentiable solutions in different cases are numerically simulated when the fractal dimension is equal to ρ = ln 2/ln 3. The results show that the exact solution of the local fractional Fokas equation represents the fractal waves on the shallow water surface. Through numerical simulation, we find that the exact solution of the local fractional Fokas equation can describe the fractal waves and waves characteristics of shallow water surface. It also shows that the study of traveling wave solutions of nonlinear local fractional equations has important significance in mathematical physics. [ABSTRACT FROM AUTHOR]

The time-varying delay is a peculiar phenomenon that occurs in almost all systems. It can cause numerous problems and instability during system operation. In this paper, the time-varying delay is considered in both the states and input vectors, which is a significant distinction between the proposed method here and previous algorithms. Furthermore, the time-varying delay is unknown but bounded. To address this issue, the Razumikhin approach is applied to the proposed method, as it incorporates a Lyapunov function with the original non-augmented state space of the system models, in contrast to the Krasovskii formula. Moreover, the Razumikhin method performs better and avoids the inherent complexity of the Krasovskii method, particularly when dealing with large delays and disturbances. For achieving output stabilization, the model predictive control (MPC) is designed for the system. The considered system in this paper is an interval type-2 (IT2) fuzzy T-S model, which provides a more accurate estimation of the dynamic model of the system. The online optimization problems are solved using linear matrix inequalities (LMIs), which reduces the computational burden and online computational costs compared to offline and non-LMI approaches. Finally, an example is provided to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The SFT (for strong finite type) condition was introduced by [J. T. Arnold, Krull dimension in power series rings, Trans. Amer. Math. Soc. 177 (1973) 299–304] in the context of studying the condition for formal power series rings to have finite Krull dimension. In the context of commutative rings, the SFT property is a near-Noetherian property that is necessary for a ring of formal power series to have finite Krull dimension behavior. Many others have studied this condition in the context of the dimension of formal power series rings. In this paper, we explore a specialization (and in some sense a more natural) variant of the SFT property that we dub as the VSFT (for very strong finite type) property. As is true of the SFT property, the VSFT property is a property of an ideal that may be extended to a global property of a commutative ring with identity. Any ideal (respectively, ring) that has the VSFT property has the SFT property. In this paper, we explore the interplay of the SFT property and the VSFT property. [ABSTRACT FROM AUTHOR]

In this paper, we prove a new extremal property of the Reuleaux triangle: it maximizes the Cheeger constant among all bodies of (same) constant width. The proof relies on a fine analysis of the optimality conditions satisfied by an optimal Reuleaux polygon together with an explicit upper bound for the inradius of the optimal domain. As a possible perspective, we conjecture that this maximal property of the Reuleaux triangle holds for the first eigenvalue of the p -Laplacian for any p ∈ (1 , + ∞) (this paper covers the case p = 1 whereas the case p = + ∞ was already known). [ABSTRACT FROM AUTHOR]

With a rapid development of artificial intelligence technology, fine-grained image classification has gained widespread application. For mobile terminals, this paper introduces an image classification method built on MobileViT, and it can apply into fine-grained image classification. The original MobileViT model has been optimized in three ways. Initially, the h-swish activation function is used to enhance the network performance. Second, the cross-entropy loss function is used to further realize the parameter optimization and model accuracy improvement. Finally, a dropout layer is joined before the fully connected layer can effectively decrease the model recognition time and prevent over-fitting. Experimental data on public tomato disease datasets demonstrate that the improved fine-grained image classification method put forward in this paper exhibits higher classification accuracy, better stability and network generalization ability than other models. [ABSTRACT FROM AUTHOR]

Phantom attractors in nonlinear systems under additive stochastic excitation have been recently discovered. This paper uncovers the existence of phantom attractors in a single-degree-of-freedom smooth nonlinear equation, which characterizes the vibration of an inextensible beam subjected to lateral stochastic excitation. It also elucidates that the stochastic averaging method, in this context, may lead to qualitatively erroneous probability density functions, identified as one of the reasons why these attractors were previously overlooked. The study then proceeds to analyze the formation process of the phantom attractor and the critical noise intensity associated with it. Subsequently, the key nonlinear term related to the emergence of phantom attractors is identified by observing whether the system still exhibits phantom attractors after the corresponding nonlinear terms are removed. It is revealed that in this system, the presence of phantom attractors is closely linked to the inertia nonlinearity of the hardening type. The system investigated in this paper is simpler compared to previously identified systems capable of generating phantom attractors. This simplicity aids in facilitating research focused on unraveling the general principles behind the formation of phantom attractors. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of stability of linear time-varying stochastic perturbed systems. We present sufficient conditions ensuring the global practical uniform exponential stability of a different class of stochastic perturbed systems based on generalized integral inequalities of Gronwall type. Finally, we provide numerical examples to prove the usefulness of the main results of this paper. [ABSTRACT FROM AUTHOR]

The Bouc–Wen nonlinear hysteretic model is widely used in nonlinear systems, and it is difficult to identify the parameters of Bouc–Wen model because of its high nonlinearity. In the paper, a hybrid genetic algorithm combined with sequential quadratic programming is proposed to solve the problem about the parameter identification of Bouc–Wen model. Sequential quadratic programming method has good local convergence and superlinear convergence rate. Therefore, compared with the genetic algorithm, the proposed identification method can accelerate the convergence speed in parameter recognition of Bouc–Wen model and achieve excellent recognition accuracy. Through the function test and the numerical simulation of the shear structure, it is proved that the proposed method has high convergence speed and accurate identification. In addition, the theory and method proposed in this paper are combined with Bouc–Wen model to identify parameters of overall restoring force model of the energy-dissipation structures, the identification results are in good agreement with the experimental results, verifying reliability and accuracy of the model and robustness of the proposed identification method. [ABSTRACT FROM AUTHOR]