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Buffer operators can be utilized to improve the smooth degree of the raw data sequence, and to increase the simulation accuracy of the model. The purpose of this paper is to analyze the cause of increase in the simulation accuracy of the buffer operator.

This paper probed into the modeling mechanism of several typical buffer operators such as the arithmetic buffer operators, the buffer operators with monotonic function and weighted buffer operators. The paper also gives an example of the buffer operator sequence.

The results indicate that after applying an infinite buffer operator, whether the authors adopt a weakening buffer operator or a strengthen buffer operator, the raw sequence can be changed into a constant sequence. Because the discrete GM(1,1) model can completely simulate constant sequence, the simulation accuracy is 100 percent. Because the discrete GM(1,1) model is the accurate form of the GM(1,1) model, after applying an infinite buffer operator, the GM(1,1) model can have a very high simulation accuracy. The buffer operator model can increase the simulation accuracy of both the GM(1,1) model and the discrete GM(1,1) model.

The paper analyses the cause of increasing simulation accuracy of the buffer operator model. The paper may indicate that possible results can be studied in the future. All the buffer operator models have similar properties. After applying an infinite buffer operator, the raw sequence can be changed into a constant sequence. A fixed-point axiom may be the basic cause.

Describes how the USA and UK have established many and varied tough new provisions in the fight against crime, and corruption in particular. Traces the long history of corruption and attempts to suppress it, and defines the terms bribery and corruption. Looks at the US legislation against corruption, focusing on the Racketeer Influenced and Corrupt Organizations Act (RICO) 1970 and the Foreign Corrupt Practices Act (FCPA) 1977, also the Financial Institutions Reform, Recovery and Enforcement Act (FIRREA) 1989 and most recently the PATRIOT Act 2001, which covers corruption as part of a wider response to the terrorist attacks on the USA. Moves onto UK legislation since 1889, including the OECD Convention, the Anti‐Terrorism, Crime and Security Act 2001, the draft Corruption Bill, and legislation enacted against money laundering and to seize the proceeds of crime.

The authors derive a nonlinear MOR based on the Cauer ladder network (CLN) representation, which serves as an application of the parameterized MOR. Two parametrized CLN representations were developed to handle the nonlinear magnetic field. Simulations using the parameterized CLN were also conducted using an iron-cored inductor model under the first-order approximation.

This work studies the effect of parameter variations on reduced systems and aims at developing a general formulation for parametrized model order reduction (MOR) methods with the dynamical transition of parameterized state.

Terms including time derivatives of basis vectors appear in nonlinear state equations, in addition to the linear network equations of the CLN method. The terms are newly derived by an exact formulation of the parameterized CLN and are named parameter variation terms in this study. According to the simulation results, the parameter variation terms play a significant role in the nonlinear state equations when reluctivity is used, while they can be neglected when differential reluctivity is used.

The computational time of nonlinear transient analyses can be greatly reduced by applying the parameterized CLN when the number of time steps is large.

The authors introduced a general representation for the dynamical behavior of the reduced system with time-varying parameters, which has not been theoretically discussed in previous studies. The effect of the parameter variations is numerically given as a form of parameter variation terms by the exact derivation of the nonlinear state equations. The influence of parameter variation terms was confirmed by simulation.

The purpose of this paper is to present the terms of sequence operators and grey data mining.

The definitions of basic terms about sequence operators and grey data mining are presented one by one.

The reader could know the basic explanation about the important terms about sequence operators and grey data mining from this paper.

Many of the colleagues thought that unified definitions of key terms would be beneficial for both the readers and the authors.

It is a fundamental work to standardize all the definitions of terms for a new discipline. It is also propitious to spread the universal principles of grey system theory.

The purpose of this study was to address waste management in the food supply chain (FSC) through the integration of inspection processes in production and distribution centers under uncertain conditions, aiming to enhance sustainability across environmental, economic and social dimensions. The study introduces a sustainable forward and reverse FSC network using a closed-loop supply chain network approach to prevent the transfer of spoiled products, ultimately providing competitive advantages to stakeholders.

A robust multi-objective mathematical programming model is proposed, incorporating inspection processes to manage perishable products effectively. The model is solved using the Augmented Epsilon Constraint technique implemented in GAMS software, providing Pareto-optimal solutions tailored to decision-makers’ preferences. Furthermore, the methodology is applied in a real-world case study and solved with the Benders Decomposition algorithm to validate its practicality and effectiveness.

The proposed methodology effectively minimizes waste and enhances sustainability in the FSC by optimizing decision-making processes under uncertainty. The illustrative examples and real case study demonstrate the efficiency of the model and solution approach, highlighting the significant role of inspection in improving all three dimensions of sustainability.

The study offers valuable insights into and tools for food industry managers to make informed strategic and tactical decisions. By addressing waste management through advanced supply chain modeling, the research helps organizations reduce costs, improve sustainability and gain a competitive edge in the market.

This research is novel in its focus on integrating inspection into the FSC network and addressing uncertainty through robust mathematical modeling. It contributes to the existing literature by demonstrating the impact of inspection on sustainability in FSCs and providing practical solutions for real-world implementation.

This paper is concerned with the study of the propagation of Rayleigh waves in a homogeneous isotropic, generalized thermoelastic medium with mass diffusion and double porosity structure using the theoretical framework of three-phase-lag model of thermoelasticity.

Using Eringen’s nonlocal elasticity theory and normal mode analysis technique, this paper solves the problem. The medium is subjected to isothermal, thermally insulated stress-free, and chemical potential boundary conditions.

The frequency equation of Rayleigh waves for isothermal and thermally insulated surfaces is derived. Propagation speed, attenuation coefficient, penetration depth and specific loss of the Rayleigh waves are computed numerically. The impact of nonlocal, void and diffusion parameters on different physical characteristics of Rayleigh waves like propagation speed, attenuation coefficient, penetration depth and specific loss with respect to wave number for isothermal and thermally insulated surfaces is depicted graphically.

Some limiting and particular cases are also deduced from the present investigation and compared with the existing literature. During Rayleigh wave propagation, the path of the surface particle is found to be elliptical. This study can be extended to fields like earthquake engineering, geophysics and the degradation of old building materials.

The aim of this work is to establish a computationally efficient iterative technique for solving the highly nonlinear derivative-dependent boundary value problem (DDBVP). The proposed iterative technique is tested on a one-dimensional mathematical model of the shape of the human cornea, which leads to the highly nonlinear DDBVP.

The approach is a combined venture of quasilinearization along with Picard’s iterative technique. The nonlinear DDBVP is simplified to a sequence of linear problems through a quasilinearization technique. Making use of Picard’s iteration approach, an analogous integral form for the quasilinearized DDBVPs is developed in terms of Green’s function and the convergence controller parameter. The study also covered the convergence analysis of the iterative technique.

Numerical illustrations are presented to evaluate the applicability, efficiency and accuracy of the technique. The proposed technique provides approximate numerical solutions to the corneal shape model with a variety of constant parameters that can arise in different physical situations. In comparison with existing works, the proposed coupled iterative approach has been found to be more accurate and less computationally complex.

This study introduces an efficient coupled iterative technique based on quasilinearization and Picard’s iterative technique to solve a one-dimensional model of a human cornea. The proposed approach is tested on various physical situations that affect the human cornea. Numerical findings are compared with other published results to demonstrate the method’s efficiency and ease of usage.

We provide a new characterization of the equality of two positive-definite matrices A and B, and we use this to propose several new computationally convenient statistical tests for the equality of two unknown positive-definite matrices. Our primary focus is on testing the information matrix equality (e.g. White, 1982, 1994). We characterize the asymptotic behavior of our new trace-determinant information matrix test statistics under the null and the alternative and investigate their finite-sample performance for a variety of models: linear regression, exponential duration, probit, and Tobit. The parametric bootstrap suggested by Horowitz (1994) delivers critical values that provide admirable level behavior, even in samples as small as n = 50. Our new tests often have better power than the parametric-bootstrap version of the traditional IMT; when they do not, they nevertheless perform respectably.