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The purpose of this paper is to construct a multiwing chaotic system that has hidden attractors with multiple stable equilibrium points. Because the multiwing hidden attractors chaotic systems are safer and have more dynamic behaviors, it is necessary to construct such a system to meet the needs of developing engineering.

By introducing a multilevel pulse function into a three-dimensional chaotic system with two stable node–foci equilibrium points, a hidden multiwing attractor with multiple stable equilibrium points can be generated. The switching behavior of a hidden four-wing attractor is studied by phase portraits and time series. The dynamical properties of the multiwing attractor are analyzed via the Poincaré map, Lyapunov exponent spectrum and bifurcation diagram. Furthermore, the hardware experiment of the proposed four-wing hidden attractors was carried out.

Not only unstable equilibrium points can produce multiwing attractors but stable node–foci equilibrium points can also produce multiwing attractors. And this system can obtain 2N + 2-wing attractors as the stage pulse of the multilevel pulse function is N. Moreover, the hardware experiment matches the simulation results well.

This paper constructs a new multiwing chaotic system by enlarging the number of stable node–foci equilibrium points. In addition, it is a nonautonomous system that is more suitable for practical projects. And the hardware experiment is also given in this article which has not been seen before. So, this paper promotes the development of hidden multiwing chaotic attractors in nonautonomous systems and makes sense for applications.

The purpose of this paper is to reveal the inner mechanisms of the role of industrial internet platforms in empowering the digital transformation of SMEs. This ROOTCLOUD-based case study shows that knowledge integration and knowledge sharing and driving play essential empowering roles in the impact of industrial internet platforms on the digital transformation of SMEs. The industrial internet platform promotes knowledge integration on the supply side, empowers cross-domain knowledge sharing and shapes the knowledge-driven digital supply chain system in the digital transformation processes of SMEs.

This paper presents a qualitative analysis of the knowledge empowerment role played by industrial internet platforms in the digital transformation process of SMEs. Based on theoretical sampling, this paper selects ROOTCLOUD as a typical case to analyse the implementation mechanism of the industrial internet platform in solving the digital transformation problems and challenges faced by SMEs.

Knowledge management (knowledge integration, sharing and driving) plays an important intermediary role between the empowerment of industrial internet platform and the digital transformation of SMEs. Specifically, the industrial internet platform empowers SMEs with knowledge, empowers supply-side knowledge integration, empowers cross-domain knowledge sharing and facilitates the formation of knowledge-driven supply chain systems.

This study clarifies the mechanism underlying the digital transformation of SMEs empowered by industrial internet platforms, that is, the empowerment of industrial internet platform enhances the level of knowledge integration and sharing of SMEs, thus improving the effectiveness of SMEs in achieving digital transformation. Further empirical studies should be conducted on the above mechanism.

Based on the theoretical perspective of knowledge management, this paper discusses the problems and challenges faced in the digital transformation of SMEs through knowledge empowerment by the industrial internet platform ROOTCLOUD and proposes that knowledge empowerment in the industrial internet platform helps supply-side knowledge integration, promotes cross-domain knowledge sharing and contributes to forming a knowledge-driven supply chain system, thereby promoting the digital transformation of SMEs. System architects and relevant policy departments should pay attention to data-centred system construction, improve the construction of data-based collaborative application ecology and encourage industrial internet platforms to provide more targeted knowledge empowerment solutions for SMEs.

Travel companies are increasingly hosting online communities to extend their initiatives of customer relationship management and gain additional insight into their business. While the benefits to companies from hosting online communities are clear, another closely related issue has not been given comparative attention: Why do customers engage voluntarily in online travel communities? The purpose of this paper is to answer the question by developing and testing a conceptual model that exploring the influence of socialization interactions on customer engagement with the community.

Hypotheses were tested by applying structural equation modeling based on survey data collected from an online travel community (n=665).

The results supported the research hypotheses and demonstrated that socialization interactions (i.e. information and social exchange) in the online travel community are important catalysts for customer engagement.

The contribution of this study is twofold. First, from a theoretical perspective, it offers new insights into the conceptualization of customer engagement and its antecedents in the context of the online travel community. Second, from a pragmatic perspective, the conceptual model derived from this research aids practitioners in stimulating customer engagement from the perspective of socialization interactions.

The purpose of this paper is to present a general formulation of the quadrature element method (QEM). The method is then used to investigate the free vibration of functionally graded (FG) beams with general boundary conditions and different variations of material properties.

The quadrature elements with arbitrary number of nodes and nodal distributions are established on the basis of two types of FG Timoshenko beam theories. One called TBT-1 takes the cross-sectional rotation as the unknown function and the other called TBT-2 uses the transverse shear strain as the unknown function. Explicit formulas are provided via the help of the differential quadrature (DQ) rule and thus the elements can be implemented adaptively with ease.

The suitability and computational efficiency of the proposed quadrature elements for the vibration analysis of FG beams are demonstrated. The convergence rate of the proposed method is high. The elements are shear-locking free and can yield accurate solutions with a small number of nodes for both thin and moderately thick beams. The performance of the element based on TBT-1 is better than the one based on TBT-2.

The present QEM is different from the existing one which exclusively uses Gauss–Lobatto–Legendre (GLL) nodes and GLL quadrature and thus is more general. The element nodes can be either the same or different from the integration points, making the selection of element nodes more flexible. Presented data are accurate and may be a reference for other researchers to develop new numerical methods. The QEM may be also useful in multi-scale modeling and in the analysis of civil infrastructures.

The paper aims to study cut resistant property of basic weft plain-knitted fabric for protective clothing.

Effects of fiber materials, fabric direction and knitting technology (sinking-depth) were explored, respectively. Cut process of fabric was tracked and the theoretical analysis was provided to evaluate energy transferring of cutting. Fiber-based cut behavior was observed by SEM images. Deformation energy stored in the loop due to yarn bending was regard as initial elastic potential energy of the fabric, which was related to loop structure.

Cut resistance of the fiber material was the dominant factor for cut resistance of weft plain-knitted fabric, while unit loop structure played a critical role in improving cut resistance.

Cut resistance of the fiber material was the dominant factor for cut resistance of weft plain-knitted fabric, while the unit loop structure played a critical role in improving cut resistance.

The paper provides theoretical support of developing flexible protective clothing.

The purpose of this paper is to present a transition detector (TD)-based radiation hardened flip-flop (TDRH-FF) for single event upset (SEU).

With SEU recovery and single event transient (SET) detector mechanism, the TDRH-FF can tolerate SEU during hold mode and generate a warning signal for architecture-level recovery during transport mode when input signal contains SET. Evaluation results show that the TDRH-FF outperforms comparable comprehensive performance.

Simulation results show that 1) the mean pulse width of the correction glitches (at full width half maximum) of TDRH-FF is less than 10 ps; 2) the area overhead of TDRH-FF is similar to the EVFERST-FF, BISER-FF and DNURHL-FF; 3) TDRH-FF has the same average power consumption as SETTOF, and moderate PDP and Ps values among these compared FFs.

In this paper, a TD-based TDRH-FF is proposed to solve the problems in the previous design. And the main contributions of the proposed TDRH-FF are summarized: Minimum size transistors are used in the proposed TD which leads to a considerable decrease in area overheads and propagation delay (resulting in an ignorable correction glitch); and compared with other radiation hardened flip-flop, TDRH-FF outperforms comparable comprehensive performance.

In the online marketing context, virtual reality (VR) has been used to display products and shopping environment, which effectively enhances the consumer experience. VR technology can not only recreate scenes similar to the real world (virtual authenticity, VA) but also create fictitious and desirable scenes that do not exist in the real world (virtual ideality, VI). The differences between VA and VI in influencing consumers' responses have not been fully understood. In addition, social signals have appeared in VR apps. However, the role of social signals in a VR context has rarely been studied. To fill the gaps in the literature, this study investigates the roles of VA and VI in shaping consumers' responses, as well as whether and how their effectiveness in shaping consumers' responses is influenced by social signals.

A VR real estate service platform was selected as the experimental platform, and two experiments were conducted to test the hypotheses. The ANOVAs and regressions were used for data analysis.

Results show that VA leads to a higher level of perceived diagnosticity than VI, whereas VI leads to a higher level of inspiration than VA; perceived diagnosticity and inspiration positively affect visit intention. Furthermore, the relationship between consumers' perceived diagnosticity, inspiration and visit intention is moderated by the presence of social signals.

The study revealed the differences between VA and VI in shaping consumers' responses, as well as the effect of social signals in VR environment, which provide a new perspective for future VR research in the context of interactive marketing.

Recently, the double joint photographic experts group (JPEG) compression detection tasks have been paid much more attention in the field of Web image forensics. Although there are several useful methods proposed for double JPEG compression detection when the quantization matrices are different in the primary and secondary compression processes, it is still a difficult problem when the quantization matrices are the same. Moreover, those methods for the different or the same quantization matrices are implemented in independent ways. The paper aims to build a new unified framework for detecting the doubly JPEG compression.

First, the Y channel of JPEG images is cut into 8 × 8 nonoverlapping blocks, and two groups of features that characterize the artifacts caused by doubly JPEG compression with the same and the different quantization matrices are extracted on those blocks. Then, the Riemannian manifold learning is applied for dimensionality reduction while preserving the local intrinsic structure of the features. Finally, a deep stack autoencoder network with seven layers is designed to detect the doubly JPEG compression.

Experimental results with different quality factors have shown that the proposed approach performs much better than the state-of-the-art approaches.

To verify the integrity and authenticity of Web images, the research of double JPEG compression detection is increasingly paid more attentions.

This paper aims to propose a unified framework to detect the double JPEG compression in the scenario whether the quantization matrix is different or not, which means this approach can be applied in more practical Web forensics tasks.

Measurement-while-drilling (MWD) system has been used to provide trajectory and inclination parameters of the oil and gas well. Fluxgate magnetometer is a traditional choice for one MWD system; however, it cannot obtain effective trajectory parameters in nonmagnetic environments. Fiber-optic-gyroscope (FOG) inclinometer system is a favorable substitute of fluxgate magnetometer, which can avoid the flaws associated with magnetic monitoring devices. However, there are some limitations and increasing surveying errors in this system under high impact conditions. This paper aims to overcome these imperfections of the FOG inclinometer system.

To overcome the imperfections, filtering algorithms are used to improve the precision of the equipment. The authors compare the low-pass filtering algorithm with the wavelet de-noising algorithm applied to real experimental data. Quantitative comparison of the error between the true and processed signal revealed that the wavelet de-noising method outperformed the low-pass filtering method. To achieve optimal positioning effects, the wavelet de-noising algorithm is finally used to inhibit the interference caused by the impact.

The experimental results show that the method proposed can ensure the azimuth accuracy lower than ±2 degrees and the inclination accuracy lower than ± 0.15 degrees under the condition of interval impact. The method proposed can overcome the interference generated by the impact in the well, which makes the instrument suitable for the measurement of small-diameter casing well.

After conducting the wavelet threshold filtering on the raw data of accelerometers, the noise generated by the impact is successfully suppressed, which is expected to meet the special requirement of the down-hole survey environment.