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Although high-order smooth reproducing kernel mesh-free approximation enables the analysis of structural vibrations in an efficient collocation formulation, there is still a lack of systematic theoretical accuracy assessment for such approach. The purpose of this paper is to present a detailed accuracy analysis for the reproducing kernel mesh-free collocation method regarding structural vibrations.

Both second-order problems such as one-dimensional (1D) rod and two-dimensional (2D) membrane and fourth-order problems such as Euler–Bernoulli beam and Kirchhoff plate are considered. Staring from a generic equation of motion deduced from the reproducing kernel mesh-free collocation method, a frequency error measure is rationally attained through properly introducing the consistency conditions of reproducing kernel mesh-free shape functions.

This paper reveals that for the second-order structural vibration problems, the frequency accuracy orders are p and (p − 1) for even and odd degree basis functions; for the fourth-order structural vibration problems, the frequency accuracy orders are (p − 2) and (p − 3) for even and odd degree basis functions, respectively, where p denotes the degree of the basis function used in mesh-free approximation.

A frequency accuracy estimation is achieved for the reproducing kernel mesh-free collocation analysis of structural vibrations, which can effectively underpin the practical applications of this method.

Most source recording device identification models for Web media forensics are based on a single feature to complete the identification task and often have the disadvantages of long time and poor accuracy. The purpose of this paper is to propose a new method for end-to-end network source identification of multi-feature fusion devices.

This paper proposes an efficient multi-feature fusion source recording device identification method based on end-to-end and attention mechanism, so as to achieve efficient and convenient identification of recording devices of Web media forensics.

The authors conducted sufficient experiments to prove the effectiveness of the models that they have proposed. The experiments show that the end-to-end system is improved by 7.1% compared to the baseline i-vector system, compared to the authors’ previous system, the accuracy is improved by 0.4%, and the training time is reduced by 50%.

With the development of Web media forensics and internet technology, the use of Web media as evidence is increasing. Among them, it is particularly important to study the authenticity and accuracy of Web media audio.

This paper aims to promote the development of source recording device identification and provide effective technology for Web media forensics and judicial record evidence that need to apply device source identification technology.

The paper aims to fabricate shape memory composites using polylactic acid (PLA) matrix and graphite. Shape memory polymers are a promising family of materials for biomedical applications because of their favourable mechanical properties, fast reactions and good biocompatibility. For most SMPs, however, achieving controllable sequential shape change is challenging.

In the present work, 4D printing technology is used to fabricate shape memory composites using polylactic acid (PLA) matrix and graphite. A comparative study of pure PLA and graphite’s different weight % composition has been done.

By carefully managing the deformation state, PLA with graphite shape memory composites produced controllable sequential deformation with an amazing shape memory effect. Surface morphology, thermal properties, melt flow index and shape recovery tests have all been carried out to assess the qualities of manufactured samples.

This is a one-of-a-kind to fabricate shape memory composites using graphite and a PLA matrix. Thus, this research attempts to deliver the possible use of PLA/graphite composites fabricated using 4D printing in robotics and biomedical devices.