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The purpose of this paper is to employ a fractional approach to predict the permeability of nonwoven fabrics by simulating diffusion process.

The method described here follows a similar approach to anomalous diffusion process. The relationship between viscous hydraulic permeability and electrical conductivity of porous material is applied in the derivation of fractional power law of permeability.

The presented power law predicted by fractional method is validated by the results obtained from simulation of fluid flow around a 3D nonwoven porous material by using the lattice-Boltzmann approach. A relation between the fluid permeability and the fluid content (filling fraction), namely, following the power law of the form, was derived via a scaling argument. The exponent n is predominantly a function of pore-size distribution dimension and random walk dimension of the fluid.

The fractional scheme by simulating diffusion process presented in this paper is a new method to predict wicking fluid flow through nonwoven fabrics. The forecast approach can be applied to the prediction of the permeability of other porous materials.

The current chapter is a tentative step toward investigating the allocation of advertising budget between the internet platform and the entity platform according to the long-term and short-term achievement of advertising investment. We provide a decision-making framework on how to allocate the advertising budget to the two platforms for the best results. The integrated effect of advertising investment consists of two parts. Goodwill and customer scale reflect the long-term achievement, and sale profit represents the short-term achievement. We selected some representative feasible investment plans as decision-making units (DMUs), and calculated the values of sale profit, goodwill, and customer scale as three outputs. To determine the best advertising investment plan, we use data envelopment analysis (DEA) model to seek efficient plans, and then determine the best one from those efficient plans through preference investigation and super-efficiency technique.

This paper aims to estimate the performance of the social security administration (SSA) in dealing with disability benefits applications in American.

The authors propose a multi-stage data envelopment analysis (DEA) method to analyze the efficiency of 167 hearing offices (HOs) to find the best performed HOs and inefficient ones and detect total improvement of inefficient and weak efficient offices.

The results show that totally 299,711 applications were processed and more applications will be processed if all offices can work efficiently. To the best of the authors’ knowledge, this paper is the first one to analyze the performance of SSA HOs using the multi-stage DEA method.

To the best of the authors’ knowledge, this paper is the first one to analyze the performance of SSA HOs using the multi-stage DEA method.

The purpose of this study is to explore the mechanisms underlying the transformation of records management (RM) to digital processes in the context of electronic records management systems (ERMS). The aim is to facilitate the evaluation of the long-term performance of ERMS and the effectiveness of the current standards.

Qualitative methods, such as participant observation and the constructivist grounded theory, were applied on a case of ERMS implementation in the Chinese public sector.

The results revealed that the application of transition-oriented ERMS would stimulate restructuring in the RM pattern and expectation on the functions of ERMS, with information quality underlying as a key challenging factor. The above-stated factors together drive the digital transformation of RM. A model for this mechanism is provided in the present study.

The selected case serves as an example for the cases that are not conditional on enforcing the electronic documents and RMS. As preliminary research, only one case has been studied here. However, it is possible to conduct other case studies to develop a further understanding of the transformation process.

The novelty of the present study is that it draws attention to the challenges encountered in moving RM towards digital transformation, by providing a theoretical foundation for developing sustainable evaluations of the ERMS and the associated current standards.

The purpose of this paper is to propose a deformable two-wheel-like mobile mechanism based on overconstrained mechanism, with the abilities of fast rolling and obstacle surmounting. The drive torque of the multi-mode motions is generated by self-deformation. Moreover, the analyses of feasibility and locomotivity of two mobile modes are presented.

The main body of the two-wheel-like mobile mechanism is a kind of centrally driven 4 R linkages. The mobile mechanism can achieve the capabilities of fast rolling and obstacle surmounting through integrating two mobile modes (spherical-like rolling mode and polyhedral-like obstacle-surmounting mode) and can switch to the corresponding mode to move or surmount obstacles. The mobility and kinematics of the mobile modes are analyzed.

Based on the results of kinematics analysis and dynamics analysis of the wheel-like mechanism, the spherical-like rolling mode has the capability of fast rolling, and the polyhedral-like obstacle-surmounting mode has the capability of surmounting different obstacle heights by two submodes (quasi-static obstacle-surmounting submode and dynamic obstacle-surmounting submode). The proposed concept is verified by experiments on a physical prototype.

The work presented in this paper is a novel exploration to apply bar linkages in the field of scout. The two-wheel-like mobile mechanism improves the torque imbalance of bar linkages by centrally driven method, removes the rear support structures of the traditional two-wheeled mechanisms by self-deformation and increases the height of obstacle surmounting by mode switching angle.

This paper aims to study the characteristics and evolution rules of tagging knowledge network for users with different activity levels in question-and-answer (Q&A) community represented by Zhihu.

A random sample of issue tag data generated by topics in the Zhihu network environment is selected. By defining user quality and selecting the top 20% and bottom 20% of users to focus on, i.e. top users and bot users, the authors apply time slicing for both types of data to construct label knowledge networks, use Q-Q diagrams and ARIMA models to analyze network indicators and introduce the theory and methods of network motif.

This study shows that when the power index of degree distribution is less than or equal to 3.1, the ARIMA model with rank index of label network has a higher fitting degree. With the development of the community, the correlation between tags in the tagging knowledge network is very weak.

It is not comprehensive and sufficient to classify users only according to their activity levels. And traditional statistical analysis is not applicable to large data sets. In the follow-up work, the authors will further explore the characteristics of the network at a larger scale and longer timescale and consider adding more node features, including some edge features. Then, users are statistically classified according to the attributes of nodes and edges to construct complex networks, and algorithms such as machine learning and deep learning are used to calculate large-scale data sets to deeply study the evolution of knowledge networks.

This paper uses the real data of the Zhihu community to divide users according to user activity and combines the theoretical methods of statistical testing, time series and network motifs to carry out the time series evolution of the knowledge network of the Q&A community. And these research methods provide other network problems with some new ideas. Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates.

Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates. For the community, understanding the formation mechanism of its network structure and key nodes in the network is conducive to improving the knowledge system of the content, finding user behavior preferences and improving user experience. Future research work will focus on identifying outbreak points from a large number of topics, predicting topical trends and conducting timely public opinion guidance and control.

In terms of data selection, the user quality is defined; the Zhihu tags are divided into two categories for time slicing; and network indicators and network motifs are compared and analyzed. In addition, statistical tests, time series analysis and network modality theory are used to analyze the tags.

The purpose of this paper is to establish a new dynamic coupled discrete-element contact model used for investigating fresh concrete with different grades and different motion states, and demonstrate its correctness and reliability according to the rheological property results of flow fresh concrete in different working states through simulating the slump process and mixing process.

To accurately express the motion and force of flowing fresh concrete in different working states from numerical analysis, a dynamic coupled discrete-element contact model is proposed for fresh concrete of varying strength. The fluid-like fresh concrete is modelled as a two-phase fluid consisting of mortar and aggregate. Depending on the contact forms of the aggregate and mortar, the model is of one of the five types, namely, Hertz–Mindlin, pendular LB contact, funicular mucous contact, capillary LB contact or slurry lift/drag contact.

To verify the accuracy of this contact model, concrete slump and cross-vane rheometer tests are simulated using the traditional LB model and dynamic coupled contact model, for five concrete strengths. Finally, by comparing the simulation results from the two different contact models with experimental data, it is found that those from the proposed contact model are closer to the experimental data.

This contact model could be used to address issues such as (a) the mixing, transportation and pumping of fresh concrete, (b) deeper research and discussion on the influence of fresh concrete on the dynamic performance of agitated-transport vehicles, (c) the behaviour of fresh concrete in mixing tanks and (d) the abrasion of concrete pumping pipes.

To accurately express the motion and force of flowing fresh concrete in different working states from numerical analysis, a dynamic coupled discrete-element contact model is proposed for fresh concrete of varying strength.