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Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

The purpose of this paper is to establish a new model for non‐equidistance sequence and research affine properties of the new model.

Generalized non‐equidistance GM(1,1) model is put forward based on generalized accumulated generating operation (AGO) theory, and particle swarm optimization is used to solve the parameters of the new model, then affine properties of the new model are researched based on matrix analysis.

The results are convincing: the simulation and prediction precisions of generalized non‐equidistance GM(1,1) model are raised greatly, and it is proved that the affine transformation sequence has the same simulative accuracy with the raw sequence for generalized non‐equidistance GM(1,1) model.

The method exposed in the paper can be used to model and predict for non‐equidistance sequence in the practical problem.

The paper succeeds in establishing a new non‐equidistance grey model and obtaining the affine properties of generalized non‐equidistance GM(1,1) model.

Fibrous porous media have a wide variety of applications in insulation, filtration, acoustics, sensing, and actuation. To design such materials, computational modeling methods are needed to engineer the properties systematically. There is a lack of efficient approaches to build and modify those complex structures in computers. The paper aims to discuss these issues.

In this paper, the authors generalize a previously developed periodic surface (PS) model so that the detailed shapes of fibers in porous media can be modeled. Because of its periodic and implicit nature, the generalized PS model is able to efficiently construct the three-dimensional representative volume element (RVE) of randomly distributed fibers. A physics-based empirical force field method is also developed to model the fiber bending and deformation.

Integrated with computational fluid dynamics (CFD) analysis tools, the proposed approach enables simulation-based design of fibrous porous media.

In the future, the authors will investigate robust approaches to export meshes of PS models directly to CFD simulation tools and develop geometric modeling methods for composite materials that include both fibers and resin.

The proposed geometric modeling method with implicit surfaces to represent fibers is unique in its capability of modeling bent and deformed fibers in a RVE and supporting design parameter-based modification for global configuration change for the purpose of macroscopic transport property analysis.

The framework, panorama, related applications and development of pansystems thinking are introduced and some problems concerning generalized systems, derivatives, symmetry and quantification are investigated, a sort of difference‐identity theory within the framework of pansystems thinking is cultivated, and a new type of clustering method with many intertransformations among some important pansystems concepts is presented. Related contents include: pansystems combination of mathematics, systems, dialectics and poetry thinking, methodology to comprehend laws by pansymmetries or by moving networks, the pansystems views of generalized order, quotientization and series‐parallel relations, control‐reachability, duality transformation, discoupling principle, communication theorems, general parental relations, etc.

The chapter focuses on how higher education (HE) influences the construction of social trust. Social trust is defined as one of the most important subjective aspect of people’s well-being. The analysis refers to impersonal trust and institutional trust, and uses various indicators for measuring the two, such as generalized trust, generalized fairness, trust in parliament, and trust in the legal system. The study covers 19 European countries and explores the problem at both aggregate and individual level. It draws on data from the European Social Survey (2006–2010), applying descriptive statistics and multilevel modeling for the analysis of data. The chapter argues that the higher the educational level of people is, the more trustful they are. Our findings clearly show that, at the individual level, HE influences positively the degrees of both impersonal and institutional trust. The results also suggest that the relationship between HE and trust differs substantially across European countries. As regards impersonal trust, the impact of HE is stronger in countries where people without HE have lower average levels of impersonal trust. However, with respect to institutional trust, HE tends to have a strong positive impact in countries with high levels of institutional trust among people without HE. Furthermore, both impersonal and institutional trust among HE graduates is greater in countries with full democracy than in those with a flawed democracy. This fact raises once again the question whether social trust is a characteristic of individuals or of social systems.

The development of digital technology has provided technical support to various industries. Specifically, Internet-based freight platforms can ensure the high-quality development of the logistics industry. Online freight platforms can use cargo transportation insurance to improve their service capabilities, promote their differentiated development, create products with platform characteristics and increase their core competitiveness.

This study uses a generalised linear model to fit the claim probability and claim intensity data and analyses freight insurance pricing based on the freight insurance claim data of a freight platform in China.

Considering traditional pricing risk factors, this study adds two risk factors to fit the claim probability data, that is, the purchase behaviour of freight insurance customers and road density. The two variables can significantly influence the claim probability, and the model fitting outcomes obtained with the logit connection function are excellent. In addition, this study examines the model results under various distribution types for the fitting of the claim intensity data. The fitting outcomes under a gamma distribution are superior to those under the other distribution types, as measured by the Akaike information criterion.

With actual data from an online freight platform in China, this study empirically proves that a generalised linear model is superior to traditional pricing methods for freight insurance. This study constructs a generalised linear pricing model considering the unique features of the freight industry and determines that the transportation distance, cargo weight and road density have a significant influence on the claim probability and claim intensity.

This paper aims to extend a widely used stochastic model of purchase loyalty to include covariates such as demographics, psychographics and geodemographics. Potentially, this allows covariates to explain variations in brand performance measures (BPMs) such as penetration/reach, average purchase frequency, sole buying, share of category requirements, repeat purchase and so forth. The result is to integrate consumer-based segmentation into previously unsegmented stochastic models of brand performance.

This paper describes a model for predicting BPMs. Covariates are then introduced into the model, with discussion of model specification, model estimation, overall model assessment, and the derivation of generalised theoretical BPMs. The outcome is a practical procedure for behavioural loyalty segmentation.

The implications for strategy and management in applying covariates to the BPMs are considerable. Where there are concentrations of consumers with high repeated purchase/consumption, then many aspects of the marketing mix will be affected. An investigation of the role of covariates in understanding BPMs in the laundry detergent market is presented as an example, and ways for market analysts to display results are demonstrated.

Despite the fact that BPMs are the best operationalisation of behavioural loyalty, until now there has not been a model to evaluate the impact of consumer characteristics as covariates on these BPMs. This paper's original contribution includes a model that fits covariates to the BPMs. New statistical and graphical methods are described. Computer software for fitting the model and generating the output is available from the authors.

This study aims at developing a comprehensive model for the analysis of electro-osmotic flow (EOF) through a fluid-saturated porous medium. To fully understand and exploit a number of applications, such a model for EOF through porous media is essential.

The proposed model is based on a generalised set of governing equations used for modelling flow through fluid saturated porous media. These equations are modified to incorporate appropriate modifications to represent electro-osmosis (EO). The model is solved through the finite element method (FEM). The validity of the proposed numerical model is demonstrated by comparing the numerical results of internal potential and velocity distribution with corresponding analytical expressions. The model introduced is also used to carry out a sensitivity analysis of the main parameters that control EOF.

The analysis carried out confirms that EO in free channels without porous obstruction is effective only at small scales, as largely discussed in the available literature. Using porous media makes EO independent of the channel scale. Indeed, as the channel size increases, the presence of the charged porous medium is essential to induce fluid flow. Moreover, results demonstrate that flow is significantly affected by the characteristics of the porous medium, such as particle size, and by the zeta potential acting on the charged surfaces.

To the best of the authors’ knowledge, a comprehensive FEM model, based on the generalised equations to simulate EOF in porous media, is proposed here for the first time.

The purpose of this paper is to frame a dual-phase-lag model using the fractional theory of thermoelasticity with relaxation time. The generalized Fourier law of heat conduction based upon Tzou model that includes temperature gradient, the thermal displacement and two different translations of heat flux vector and temperature gradient has been used to formulate the heat conduction model. The microstructural interactions and corresponding thermal changes have been studied due to the involvement of relaxation time and delay time translations. This results in achieving the finite speed of thermal wave. Classical coupled and generalized thermoelasticity theories are recovered by considering the various special cases for different order of fractional derivatives and two different translations under consideration.

The work presented in this manuscript proposes a dual-phase-lag mathematical model of a thick circular plate in a finite cylindrical domain subjected to axis-symmetric heat flux. The model has been designed in the context of fractional thermoelasticity by considering two successive terms in Taylor’s series expansion of fractional Fourier law of heat conduction in the two different translations of heat flux vector and temperature gradient. The analytical results have been obtained in Laplace transform domain by transforming the original problem into eigenvalue problem using Hankel and Laplace transforms. The numerical inversions of Laplace transforms have been achieved using the Gaver−Stehfast algorithm, and convergence criterion has been discussed. For illustrative purpose, the dual-phase-lag model proposed in this manuscript has been applied to a periodically varying heat source. The numerical results have been depicted graphically and compared with classical, fractional and generalized thermoelasticity for various fractional orders under consideration.

The microstructural interactions and corresponding thermal changes have been studied due to the involvement of relaxation time and delay time translations. This results in achieving the finite speed of thermal wave. Classical coupled and generalized thermoelasticity theories are recovered by considering the various special cases for different order of fractional derivatives and two different translations under consideration. This model has been applied to study the thermal effects in a thick circular plate subjected to a periodically varying heat source.

A dual-phase-lag model can effectively be incorporated to study the transient heat conduction problems for an exponentially decaying pulse boundary heat flux and/or for a short-pulse boundary heat flux in long solid tubes and cylinders. This model is also applicable to study the various effects of the thermal lag ratio and the shift time. These dual-phase-lag models are also practically applicable in the problems of modeling of nanoscale heat transport problems of semiconductor devices and accordingly semiconductors can be classified as per their ability of heat conduction.

To the authors’ knowledge, no one has discussed fractional thermoelastic dual-phase-lag problem associated with relaxation time in a finite cylindrical domain for a thick circular plate subjected to an axis-symmetric heat source. This is the latest and novel contribution to the field of thermal mechanics.