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The microstructure and properties of Zn-Sn coating on sintered Nd-Fe-B magnets were investigated by the grain boundary diffusion process, to improve the corrosion resistance of magnet surface and explore the feasibility of realizing the lower-temperature grain boundary diffusion.

The Zn-Sn coating was deposited on sintered Nd-Fe-B magnets by magnetron sputtering, and then the Zn-Sn coated magnets were put into the vacuum tube furnace for grain boundary diffusion process. The morphology and structure of Zn-Sn coating as well as its mechanical properties and corrosion resistance were investigated.

Results showed that the particle size of vacuum diffusion-treated Zn-Sn coating increased and the particle agglomeration was weakened with increasing diffusion temperature, and the non-vacuum diffusion-treated Zn-Sn coating was oxidized to generate SnO₂ and ZnO compounds. The binding force of coating first increased and then decreased with increasing diffusion temperature, and the maximum binding force was obtained at 540 °C. The binding force and corrosion resistance of non-vacuum diffusion-treated Zn-Sn coating were higher than the vacuum diffusion-treated Zn-Sn coating at the same diffusion temperature.

The Zn-Sn coating after diffusion treatment can provide complete protection, and the coating elements diffusion can be carried out at the same temperature as the secondary aging of sintered Nd-Fe-B magnets. Simultaneously, further diffusion process optimization needs to be completed because the diffusion depth is very low and only about 10 µm, which does not meet the requirements of traditional grain boundary diffusion method.

This paper aims to convict the offender of real concurrence offenses of the most severe offense and applying the most severe penalty will result in no distinction between the perpetrator who conducted more than one act and the one who conducted only one act. This approach deviates from the purpose of criminal law. The real concurrence of offenses means several offenses, the perpetrator’s dangerousness and culpability are much higher than the perpetrator who commits just one crime, so combined punishments for several offenses should be applied to the real concurrence of offenses.

If the depositors are acquaintances or relatives and friends, the relationship can be explained by “personality trust.” If the depositors are strangers, but they have complied with their duties of care, the deposit relationship can be explained by “system trust.”

The real concurrence of offenses means several offenses, the perpetrator’s dangerousness and culpability are much higher than the perpetrator who commits just one crime, so combined punishments for several offenses should be applied to the real concurrence of offenses.

The principle of choosing the most severe punishment applied to the real concurrence of offense should be abolished. As the perpetrator separately conducts two acts at different times, these acts infringe on different legal interests. Although these acts exist closely, the authors cannot deny that these acts constitute more than one offense.

For autonomous vehicles, trajectory prediction of surrounding vehicles is beneficial to improving the situational awareness of dynamic and stochastic traffic environments, which is a crucial and indispensable element to realize highly automated driving.

In this paper, the overall framework consists of two parts: first, a novel driver characteristic and intention estimation (DCIE) model is built to indicate the higher-level information of the vehicle using its low-level motion variables; then, according to the estimation results of the DCIE model, a classified Gaussian process model is established for probabilistic vehicle trajectory prediction under different motion patterns.

The whole method is later applied and analyzed in the highway lane-change scenarios with the parameters of models learned from the public naturalistic driving data set. Compared with other traditional methods, the performance of this proposed approach is proved superior, demonstrated by the higher accuracy in the long prediction horizon and a more reasonable description of uncertainty.

This hierarchical approach is proposed to make trajectory prediction accurately both in the short term and long term, which can also deal with the uncertainties caused by the perception system or indeterminate vehicle behaviors.

This research examines the effects of firm ownership and size on innovation capability using data from the World Bank China Enterprise Survey (WBCES), which provides directly measurable innovation-related variables. Key consideration is given to the role and innovation capability of state-owned enterprises (SOEs) compared with domestic and foreign private enterprises in the Chinese economy.

In its quest for technological self-reliance and a new developmental path, China is focusing on its enterprise innovation capability.

The findings suggest that SOEs and domestic private enterprises are similar in terms of innovation participation but differ in terms of innovation diversification, which implies ownership-specific innovative advantages. In general, the authors find that SOEs are more innovative with respect to processes innovation but less so with respect to product, management and promotion innovations. Foreign-owned enterprises are superior in all types of innovation except product innovation.

The authors also find that size is an important determinant of innovation capability, with the effect varying depending on location and industry. Moreover, the joint effect of firm ownership and size on innovation declines with increasing size. These findings provide new insights into the evaluation of China's major policies.

This research examines the effects of ownership and size on enterprise innovation capability, using the WBCES (2013) data, which include direct measurable innovation related variables.

This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict requirements. Therefore, how to design a docking robot mechanism to achieve accurate docking between vehicles has become a challenge.

In this paper, first, the docking mechanism system is described, and the inverse kinematics model of the docking robot based on Stewart is established. Second, the genetic algorithm-based optimization method for multiobjective parameters of parallel mechanisms including workspace volume and mechanism flexibility is proposed to solve the problem of multiparameter optimization of parallel mechanism and realize the docking of unmanned vehicle space flexibility. The optimization results verify that the structural parameters meet the design requirements. Besides, the static and dynamic finite element analysis are carried out to verify the structural strength and dynamic performance of the docking robot according to the stiffness, strength, dead load and dynamic performance of the docking robot. Finally, taking the docking robot as the experimental platform, experiments are carried out under different working conditions, and the experimental results verify that the docking robot can achieve accurate docking tasks.

Experiments on the docking robot that the proposed design and optimization method has a good effect on structural strength and control accuracy. The experimental results verify that the docking robot mechanism can achieve accurate docking tasks, which is expected to provide technical guidance and reference for unmanned vehicles docking technology.

This research can provide technical guidance and reference for spatial docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

Pb‐free soldering challenged printed circuit board (PCB) assembly with high temperature. The purpose of this paper is to explain the failure mechanism of printed circuit board (PCB) assembly with solder bubbles of vias to avoid the problems of via‐drilling defects and solder joint failure.

The failure of PCB vias with solder bubbles was investigated through cross sections and SEM microstructure inspection, TMA measurement, moisture absorption analysis and DSC measurement. The moisture absorption and CTE of FR4 laminate matched with manufacturing requirement to avoid the effects of solder bubbles. The effects of via drilling with a dull drill bit were compared to that with a new drill bit.

The moisture absorbed inside holes of via plating layers could be exposed to induce solder bubbles during Pb‐free soldering assembly and dull drill bits should be prevented during the drilling process to avoid the no‐bearing drilling effects.

The failure of PCB vias is not only involved in the voiding in solder joints but manufacturing processes of PCB. The paper designs an approach to analyse the properties of PCB materials and the drilling effects of vias to find out the mechanism resulting in solder bubbles of vias. The problem of drill bits should be considered to prevent the moisture absorbed in drilling vias with defects.

Crowdsourcing refers to a new business model in which enterprises or individuals publish tasks or problems, attracting freelancers or contributors to participate in solving tasks, submitting bids and allowing task seekers to choose the final solution. How to attract more quantity and quality of contributors to submit their solutions through a crowdsourcing platform has become a vital question.

In this study, the authors use web crawling to obtain 43,265 effective tasks in EPWK website (www.epwk.com) to probe how to elevate the quantity and quality of contributors via task reward design. This study uses the hierarchical linear model to probe the research questions.

Results show that, with the increase of task reward, the quantity of contributors goes up first and then goes down (inverted U shape), whereas the quality of contributors goes down first and then goes up (U sharp). Moreover, the authors investigate the moderating effects of another task design attribute, task duration. This study finds that task duration weakens the effect of task reward on the quantity of contributors while strengthening the effects of task reward on the quality of contributors.

First, this study theoretically probes two key aspects of task performance, namely, the quantity and quality of contributors, which expand the scope of task performance evaluation. Second, this study reconciles previous concern about the relationship of task reward and performance, which is different from previous studies that have paid more attention to the single perspective of their relationship. Finally, the authors investigate the moderating effects of task duration, which further uncover the mechanism behind task reward and performance, that is, the quantity and quality of task contributors.

The purpose of this study to analyze the plastic anisotropy of 6061 aluminum alloy with finite deformation using crystal plasticity finite element method.

A representative volume element (RVE) model was constructed by Voronoi tessellation. In this model, grain shapes, grain orientations and distribution of grains were involved. The mechanical response of the component under composite loading was tested using specify cruciform specimen. Moreover, different stress and strain states in the specific central region were analyzed to reveal the effects of complex loading.

We calculated the influence of misorientation of adjacent grains as well as the evolution of the micro structure’s plastic deformation on the macroscopic deformation of the structure. Geometry design for the cruciform specimen helps obtain a homogenous distribution of the stress and strain at the specimen center. In this process, the initial grain orientation is also an important factor, and the larger misorientations between special grains may cause greater stress concentration.

The influence of micro-scale factors on macro-scale plastic anisotropy of AA6061 is analyzed using RVE model and cruciform specimen, and they offer a reference for related research.

The high-efficient processing of mass data is a primary issue in building and maintaining security video surveillance system. This paper aims to focus on the architecture of security video surveillance system, which was based on Hadoop parallel processing technology in big data environment.

A hardware framework of security video surveillance network cascaded system (SVSNCS) was constructed on the basis of Internet of Things, network cascade technology and Hadoop platform. Then, the architecture model of SVSNCS was proposed using the Hadoop and big data processing platform.

Finally, we suggested the procedure of video processing according to the cascade network characteristics.

Our paper, which focused on the architecture of security video surveillance system in big data environment on the basis of Hadoop parallel processing technology, provided high-quality video surveillance services for security area.

Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.