The omnichannel business has becomes a hot topic due to the fast development on e-commerce and the customers' acquaintance with multichannel shopping mode. Various business organizations have started to work on omnichannel business issue in order to satisfy the new trend of customer demand and tend to devote their efforts to both online and offline business. Thus, there is no doubt that understanding the shopping behavior for online customers is vital for the omnichannel business. The RFM (recency, frequency, monetary) model and the k-means clustering method are commonly used to extract customers' information and segment customers, respectively. To extend the RFM model, we divide the total frequency and monetary information into weekly level data, and as a consequence, the number of variables corresponding to one customer increases significantly, leading to the problem of high-dimensional analysis. To address this issue, in this paper we extend the regularized k-means clustering method with L ₁ -norm for independent case to the clustering method with elastic net penalty with a focus on correlated variables. Our simulation results show that the proposed method performs better than the standard k-means method by providing lower error rates and can select variables simultaneously under 4 different scenarios. A real example of an online retailer is presented to illustrate the use of the proposed method and highlight its high potential in clustering high-dimensional applications. In particular, the number of variables is reduced from 108 to 98 without any loss on clustering accuracy.

The magnetorheology and dispersion stability of bidisperse magnetic particles (BMP)-based magnetorheological (MR) fluids were improved by applying a novel functional coating composed of gelatin and graphite oxide (GO) to the surfaces of the micron-sized carbonyl iron (CI) and nanoparticles Fe₃O₄. Gelatin acted as a grafting agent to reduce the aggregation and sedimentation of CI particles and prevent nanoparticles Fe₃O₄ from oxidation. In addition, a dense GO network on the surface of gelatin-coated BMP was synthesized by self-assembly to possess a better MR performance and redispersibility. The rheological properties of MR fluids containing dual-coated BMP were measured by a rotational rheometer under the presence of magnetic field and their dispersion stability was examined through sedimentation tests. The results showed that CI@Fe₃O₄@Gelatin@GO (CI@Fe₃O₄@G@GO) particles possessed enhanced MR properties and dispersion stability. In addition, the nanoparticle-enhancing effects on the dispersion stability of BMP-based MR fluids were investigated using Monte Carlo simulations.

Bionic artificial muscle made from chitosan gel is an emerging type of the ionic electro active polymer with advantages of large deformation, low cost and environmental protection etc, which leads to a research focus and wide application in the fields of bionic engineering and intelligence material recently. In this paper, effects and improvement mechanisms of the direct casting and genipin cross-linking processes on response speed properties of the chitosan gel artificial muscle (CGAM) were mainly studied. Based on in-depth analysis of the CGAM response mechanism, a platform was built for testing the response performance of the CGAM, then its equivalent circuit and mathematical models were also established. Furthermore, control experiments were carried out to test and analyze several performances of the CGAM on response speed, electrical conductivity, mechanical properties and microstructure with different control variables. The experimental results illustrated that the CGAM assembled by direct casting enabled its electric actuating membrane and non-metallic electrode membrane tightly attached together with low contact resistance, which dramatically promoted the electrical conductivity of the CGAM resulting in nearly doubled response speed. Besides, different concentrations of genipin were adopted to cross-link the CGAM actuating membranes, and then it was found that the response speed of the uncross-linked CGAM was fast in the initial stage, but as time increased, it declined rapidly with poor steadiness. While there was no obvious decrease over time on the response speed of the CGAM cross-linked with low genipin concentration. Namely, its stability was getting better and better. In addition, the response speed of the CGAM cross-linked with low concentration of genipin was roughly the same as uncross-linked CGAM, which was quicker than that of high concentration. In this work, its internal mechanisms, feasible assembly technique and green modification method were provided to further explore the practical applications significantly.

In this study, a two-component lattice Boltzmann method (TLBM) in combination with a discrete element approach (DEA) based on a representative volume element (RVE) with respect to a bidisperse magnetorheological fluid (MRF) was performed to simulate the behavior and microstructure formation of magnetic particles in a carrier liquid. The bidisperse MRF reported herein is a suspension dispersed by soft micron carbonyl iron (CI) particles and Fe₃O₄ nanoparticles dual-coated with gelatin and multi-walled carbon nanotubes (MWCNTs) in the carrier liquid. In the TLBM of two-component liquid and particle simulation, the inter-particle interactions were completely ignored; on the other hand, the DEA was just employed for calculating the dynamic behavior of particles. Therefore, due to the explicit nature of the combination of TLBM and DEA, it is a more efficient and accurate strategy for the simulation and calculation of complex MRF systems. Moreover, the immersed boundary method (IBM) was used to describe the interactions between the magnetic particles and the carrier liquid. The RVE of the bidisperse MRF was selected to eliminate specific operational conditions and reduce the calculation costs. New numerical results were obtained for the motion velocities, microstructure evolution and kinetic energy of bidisperse magnetic particles (BMPs) under the effect of a magnetic field; when the mass fraction of the nanoparticles was 0.1, the bidisperse MRF exhibited an improved response time in terms of the particle motion and microstructure formation. In addition, the effects of the Reynolds (Re) and Hartmann (Ha) numbers on the fluid–particle interaction and flow velocity were illustrated.