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The purpose of this paper is to propose a novel combined finite-discrete element method (FDEM), based on the cohesive zone model, for simulating rockslide problems at the laboratory scale.

The combined FDEM is realized using ABAQUS/Explicit. The rock mass is represented as a collection of elastic bulk elements glued by cohesive elements with zero thickness. To reproduce the tensile and shear micro-fractures in rock material, the Mohr-Coulomb model with tension cut-off is employed as the damage initiation criterion of cohesive elements. Three simulated laboratory tests are considered to verify the capability of combined FDEM in reproducing the mechanical behavior of rock masses. Three slope models with different joint inclinations are taken to illustrate the application of the combined FDEM to rockslide simulation.

The results show that the joint inclination is an important factor for inducing the progressive failure behavior. With a low joint inclination, the slope failure process is observed to be a collapse mode. As the joint inclination becomes higher, the failure mode changes to sliding and the steady time of rock blocks is shortened. Moreover, the runout distance and post-failure slope angle decrease as the joint inclination increases.

These studies indicate that the combined FDEM performed within ABAQUS can simulate slope stability problems for research purposes and is useful for studying the slope failure mechanism comprehensively.

The purpose of this paper is to discretely model rockfill materials considering the irregular shape of the particles and their crushability. The scientific goal was to investigate the influence of particle crushability and shape on the mechanical behavior of rockfill materials.

The method of generating irregular-shaped particles was based on the observation that most rockfill grains can be approximately circumscribed by an ellipsoid. Two shape descriptors were used to make the virtual particles closely replicate the geometric features of natural rockfill grains. The combined finite-discrete element method (FDEM) was used to numerically simulate a drained, tri-axial compression test. The particle assemblies were subjected to tri-axial compression under strain controlled conditions while a constant confining pressure was maintained.

The non-breakable particles showed a remarkable ability to dilate as a result of a higher inter-particle locking effect. Dilation forces the particles to move from a lower potential energy state to a higher potential energy state, which causes the micro-structure to become less stable, resulting in a dramatic decline in the angle of friction from the peak state to the residual state. In addition, the elongated particles enhance the interlocking effect, but breakage is also more likely to occur. The net effect of those two mechanisms controls the overall shearing resistance of rockfill materials.

After calibration using a few micro-parameters, the combined FDEM was able to reproduce the typical behavior of rockfill materials without requiring a description of the complex relationship that exists between constituents; this relationship must be described in continuum mechanics. The simulation results showed that this approach is predictive. The combined FDEM also provides an opportunity for a quantitative study of the micro-structure of granular materials, and this study will help us to better understand the mechanical characteristics of rockfill materials.

This paper aims to report on a study that used the practice theory lens to understand how Chinese ethnic culture influences restaurant workers' learning through engagement in everyday work practices.

A multiple case study approach was used. Data were collected from semi-structured interviews and site observations. Thematic analysis was conducted to identify how workers learnt the sayings, doings and relatings in their workplaces.

The findings show that the ethnic culture of the participants influences and enriches their learning in practice settings such as small Chinese restaurants.

The understandings presented here need to be verified through more research in different regions and nations. In addition, cross-cultural studies on other ethnic restaurants may contribute to deeper understandings of the influences of ethnic culture on practice-based learning.

The research contributes to understanding the influence of ethnic culture on practice-based learning.

The understandings gained from the findings of this study form a useful basis for curriculum development and instructional design of training programmes for practice-based as well as work-integrated-learning components of vocational curriculum. Furthermore, awareness of the strengths of the ethnic culture is of interest to owner/managers of small Chinese restaurants to afford supportive learning environments for workers.

Although recent years have shown increasing popularity of e-commerce worldwide, there is still a lack of studies comprehensively exploring trust issue in e-commerce. Based on trust transfer theory and signaling theory, the purpose of this paper is to present an integrated research model to test the relationships between trust dimensions and e-loyalty, interactions among trust dimensions, as well as antecedents of different trust dimensions.

Data were collected through a web-based survey in Chinese markets and structural equation modeling with partial least squares was used to analyze the data.

The results identified that three trust dimensions all have significant impacts on e-loyalty, and relationships existed in different trust dimensions. Moreover, information quality and security protection are important factors determining institutional trust while store reputation is the most salient factor determining interpersonal trust.

This research contributes to the body of knowledge on trust by exploring the nature of trust with a multidimensional scale. Another theoretical contribution is the provision of a comprehensive understanding of the trust antecedents in e-commerce. Furthermore, this research benefits the companies doing e-businesses by allowing them to better understand how to improve consumers’ trust in the online environment and thus to retain and attract more loyal customers and succeed in online businesses.

With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues.

First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives.

This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective.

This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value.

Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.

Short-form video advertisements have recently gained popularity and are widely used. However, creating attractive short video advertisements remains a challenge for sellers. Based on the visual-audio perspective and signaling theory, this study investigated the impacts of three visual features (number of shots, pixel-level image complexity and vertical versus horizontal formats) and two audio features (speech rate and average spectral centroid) on user engagement behavior.

We conducted a field study on TikTok. To test our various hypotheses, we used regression analysis on 2,511 videos containing product promotion information posted by 60 sellers between January 1, 2020 and November 20, 2021.

For visual variables, the number of shots and pixel-level image complexity were found to have nonlinear (inverted U-shaped) relationships with user engagement behavior. The vertical video form was found to have a positive effect on comments and shares. In the case of audio variables, speech rate was found to have a significant positive effect on shares but not on likes and comments. The average spectral centroid was found to have significant negative influences on likes and comments.

This study provides specific suggestions for sellers who create short-form videos to improve user engagement behavior.

This study contributes to the literature on short-form video advertising by extending the potential drivers of user engagement behavior. Additionally, from a methodological perspective, it contributes to the literature by using computer vision and speech-processing techniques to analyze user behavior in a video-related context, effectively overcoming the limitations of the widely adopted survey method.

This study aimed to investigate the collective effects of bending load and hygrothermal aging on glass fibre-reinforced plastics (GFRP) due to the fact that stress and water absorption is inevitable during GFRP applications.

The water boiling method was used to study the moisture absorption, desorption behaviour and evaluate the performance of GFRP laminates under loading in this article. The moisture diffusion of laminates is characterized in three aging conditions (25°C, 45°C and 65°C water), along with three levels of bending load coefficients (0, 0.3 and 0.6). The moisture diffusion coefficients are determined through the curve fitting method of the experimental data of the initial process, based on the Fickian diffusion model. Moreover, the laminates’ performance is further discussed after adequate environmental aging and loading.

It was found that moisture absorption is promoted by the presence of bending load and boiling during this study. The absorption diffusion coefficient and moisture equilibrium content of the specimens increased with an increasing loading ratio and temperature. The bending strength of the laminate varied according to a contrary trend. Furthermore, the desorbed moisture content is found to be much higher after higher levels of bending load because it is harder to desorb the moisture in the interfaces and micro cracks.

Collective effects of bending load and hygrothermal aging promote the absorption and result in accelerating property degradation of GFRP. It is significant to focus on these effects on the failure of GFRP.

A novel unit was designed to simulate the various loading acted on containers in this work.

The purpose of this paper is to develop a new composite model using structural equation modelling (SEM) and analytic hierarchy process (AHP) for the selection of suppliers.

In this paper the authors have made an attempt to arrive at the supplier selection score using SEM and AHP. An attempt has been made to develop a new composite model using SEM and AHP technique, based on the survey of 151 respondents. Attributes' weightage are found out using cluster analysis.

Based on the output from the composite model, cluster analysis has been carried out to find out the strengths and weakness of each supplier on the influencing factors. Based on these findings, the supplier can improve on factors where they lag and can maintain the factors where they excel.

In this paper the authors have made an attempt to arrive at the supplier selection score using SEM and AHP.

The purpose of this paper is to provide an overview of the history and existing research on continuous improvement (CI).

Extensive review of the literature.

This paper provides an overview of CI, its inception, how it evolved into sophisticated methodologies used in organizations today, and existing research in this field in the literature.

The literature on classification of CI has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of various CI implementation practices demonstrated by manufacturing organizations globally. It also highlights the sophisticated CI methodologies suggested by various researchers and practitioners in the field of CI.

The literature on classification of CI has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of various CI implementation practices demonstrated by manufacturing organizations globally. It also highlights the sophisticated CI methodologies suggested by various researchers and practitioners in the field of CI.

The paper contains a comprehensive listing of publications on the field in question and its classification. It will be useful to researchers, improvement professionals and others concerned with improvement to understand the significance of CI. It should be of value to practitioners of CI programmes and to academics who are interested in how CI has evolved, and where it is today. To the authors’ knowledge, no recent papers have provided an historical perspective of CI.

This work provides a generic review of the existing data mining ontologies (DMOs) and also provides a base platform for ontology developers and researchers for gauging the ontologies for satisfactory coverage and usage.

The study uses a systematic literature review approach to identify 35 DMOs in the domain between the years 2003 and 2021. Various parameters, like purpose, design methodology, operations used, language representation, etc. are available in the literature to review ontologies. Accompanying the existing parameters, a few parameters, like semantic reasoner used, knowledge representation formalism was added and a list of 20 parameters was prepared. It was then segregated into two groups as generic parameters and core parameters to review DMOs.

It was observed that among the 35 papers under the study, 26 papers were published between the years 2006 and 2016. Larisa Soldatova, Saso Dzeroski and Pance Panov were the most productive authors of these DMO-related publications. The ontological review indicated that most of the DMOs were domain and task ontologies. Majority of ontologies were formal, modular and represented using web ontology language (OWL). The data revealed that Ontology development 101, METHONTOLOGY was the preferred design methodology, and application-based approaches were preferred for evaluation. It was also observed that around eight ontologies were accessible, and among them, three were available in ontology libraries as well. The most reused ontologies were OntoDM, BFO, OBO-RO, OBI, IAO, OntoDT, SWO and DMOP. The most preferred ontology editor was Protégé, whereas the most used semantic reasoner was Pellet. Even ontology metrics for 16 DMOs were also available.

This paper carries out a basic level review of DMOs employing a parametric approach, which makes this study the first of a kind for the review of DMOs.