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The purpose of this paper is to find the exact solutions of a (3 + 1)-dimensional non-integrable Korteweg-de Vries type (KdV-type) equation, which can be used to describe the stability of soliton in a nonlinear media with weak dispersion.

The authors apply the extended Bell polynomial approach, Hirota’s bilinear method and the homoclinic test technique to find the rogue waves, homoclinic breather waves and soliton waves of the (3 + 1)-dimensional non-integrable KdV-type equation. The used approach formally derives the essential conditions for these solutions to exist.

The results show that the equation exists rogue waves, homoclinic breather waves and soliton waves. To better understand the dynamic behavior of these solutions, the authors analyze the propagation and interaction properties of the these solutions.

These results may help to investigate the local structure and the interaction of waves in KdV-type equations. It is hoped that the results can help enrich the dynamic behavior of such equations.

The purpose of this paper is to find homoclinic breather waves, rogue waves and soliton waves for a (3 + 1)-dimensional generalized Kadomtsev–Petviashvili (gKP) equation, which can be used to describe the propagation of weakly nonlinear dispersive long waves on the surface of a fluid.

The authors apply the extended Bell polynomial approach, Hirota’s bilinear method and the homoclinic test technique to find the rogue waves, homoclinic breather waves and soliton waves of the (3 + 1)-dimensional gKP equation.

The results imply that the gKP equation admits rogue waves, homoclinic breather waves and soliton waves. Moreover, the authors also find that rogue waves can come from the extreme behavior of the breather solitary wave. The authors analyze the propagation and interaction properties of these solutions to better understand the dynamic behavior of these solutions.

These results may help us to further study the local structure and the interaction of waves in KP-type equations. It is hoped that the results can help enrich the dynamic behavior of such equations.

The purpose of this paper is to study the stability analysis and optical solitary wave solutions of a (2 + 1)-dimensional nonlinear Schrödinger equation, which are derived from a multicomponent plasma with nonextensive distribution.

Based on the ansatz and sub-equation theories, the authors use a direct method to find stability analysis and optical solitary wave solutions of the (2 + 1)-dimensional equation.

By considering the ansatz method, the authors successfully construct the bright and dark soliton solutions of the equation. The sub-equation method is also extended to find its complexitons solutions. Moreover, the explicit power series solution is also derived with its convergence analysis. Finally, the influences of each parameter on these solutions are discussed via graphical analysis.

The dynamics of these solutions are analyzed to enrich the diversity of the dynamics of high-dimensional nonlinear Schrödinger equation type nonlinear wave fields.

The purpose of this paper is to study stability analysis, solition solutions and Gaussian solitons of the generalized nonlinear Schrödinger equation with higher order terms, which can be used to describe the propagation properties of optical soliton solutions.

The authors apply the ansatz method and the Hamiltonian system technique to find its bright, dark and Gaussian wave solitons and analyze its modulation instability analysis and stability analysis solution.

The results imply that the generalized nonlinear Schrödinger equation has bright, dark and Gaussian wave solitons. Meanwhile, the authors provide the graphical analysis of such solutions to better understand their dynamical behavior. Some constraint conditions are provided which can guarantee the existence of solitons. The authors analyze its modulation instability analysis and stability analysis solution.

These results may help us to further study the local structure and the interaction of solutions in generalized nonlinear Schrödinger -type equations. The authors hope that the results provided in this work can help enrich the dynamic behavior of the generalized nonlinear Schrödinger--type equations.

The purpose of this study is to examine the lump solutions of the (3 + 1)-dimensional nonlinear evolution equations by considering a (3 + 1)-dimensional generalized Kadomtsev–Petviashvili (gKP) equation and a (3 + 1)-dimensional variable-coefficient generalized B-type Kadomtsev–Petviashvili (vcgBKP) equation as examples.

Based on Hirota’s bilinear theory, a direct method is used to examine the lump solutions of these two equations.

The complete non-elastic interaction solutions between a lump and a stripe are also discussed for the equations, which show that the lump solitons are swallowed by the stripe solitons.

The dynamics of these solutions are analyzed to enrich the diversity of the dynamics of high-dimensional KP-type nonlinear wave equations.

Because of the small size and high integration of capacitive micromachined ultrasonic transducer (CMUT) component, it can be made into large-scale array, but this lead to high hardware complexity, so the purpose of this paper is to use less elements to achieve better imaging results. In this research, an optimized sparse array is studied, which can suppress the side lobe and reduce the imaging artifacts compared with the equispaced sparse array with the same number of elements.

Genetic algorithm is used to sparse the CMUT linear array, and Kaiser window apodization is added to reduce imaging artifacts, the beam pattern and peak-to-side lobe ratio are calculated, point targets imaging comparisons are performed. Furthermore, a 256-elements CMUT linear array is used to carry out the imaging experiment of embedded mass and forearm blood vessel, and the imaging results are compared quantitatively.

Through the imaging comparison of embedded mass and forearm blood vessel, the feasibility of optimized sparse array of CMUT is verified, and the purpose of reducing the hardware complexity is achieved.

This research provides a basis for the large-scale CMUT array to reduce the hardware complexity and the amount of calculation. At present, the CMUT array has been used in medical ultrasound imaging and has huge market potential.

The aerodynamic differences between the head car (HC) and tail car (TC) of a high-speed maglev train are significant, resulting in control difficulties and safety challenges in operation. The arch structure has a significant effect on the improvement of the aerodynamic lift of the HC and TC of the maglev train. Therefore, this study aims to investigate the effect of a streamlined arch structure on the aerodynamic performance of a 600 km/h maglev train.

Three typical streamlined arch structures for maglev trains are selected, i.e. single-arch, double-arch and triple-arch maglev trains. The vortex structure, pressure of train surface, boundary layer, slipstream and aerodynamic forces of the maglev trains with different arch structures are compared by adopting improved delayed detached eddy simulation numerical calculation method. The effects of the arch structures on the aerodynamic performance of the maglev train are analyzed.

The dynamic topological structure of the wake flow shows that a change in arch structure can reduce the vortex size in the wake region; the vortex size with double-arch and triple-arch maglev trains is reduced by 15.9% and 23%, respectively, compared with a single-arch maglev train. The peak slipstream decreases with an increase in arch structures; double-arch and triple-arch maglev trains reduce it by 8.89% and 16.67%, respectively, compared with a single-arch maglev train. The aerodynamic force indicates that arch structures improve the lift imbalance between the HC and TC of a maglev train; double-arch and triple-arch maglev trains improve it by 22.4% and 36.8%, respectively, compared to a single-arch maglev train.

This study compares the effects of a streamlined arch structure on a maglev train and its surrounding flow field. The results of the study provide data support for the design and safe operation of high-speed maglev trains.

The purpose of this study is to investigate when and why supervisor negative feedback is associated with employees' job performance via two different pathways (i.e. emotion-focused coping and problem-focused coping) and to introduce proactive personality as a moderator.

Time-lagged data were collected using a field survey research design. Participants included 389 dyads of employees and their direct supervisors from five companies in China.

Supervisor negative feedback can lead to employees' emotion-focused coping, which in turn impairs their job performance. Meanwhile, supervisor negative feedback can trigger employees’ problem-focused coping, which subsequently promotes their job performance. Furthermore, proactive personality moderates the indirect effect of supervisor negative feedback on employee performance through emotion-focused coping.

This study explored the double-edged effects of supervisor negative feedback on employee job performance from a coping strategy perspective and investigated how proactive personality influences the choice of coping strategies.

The purpose of this paper is to expound the relationship among microstructure, mechanical property, tribological behavior and deformation mechanism of carburized layer deposited on Ti-6Al-4V alloy by double-glow plasma hydrogen-free carburizing surface technology.

Morphologies and phase compositions of the carburized layer were observed by scanning electron microscope and X-ray diffraction. The micro-hardness tests were used to evaluate the surface and cross-sectional hardness of carburized layer. The reciprocating friction and wear experiments under various load conditions were implemented to investigate the tribological behavior of carburized layer. Moreover, scratch test with ramped loading pattern was carried out to illuminate the deformation mechanism of carburized layer.

Compared to substrate, the hardness of surface improved to ∼1,100 HV_0.1, while the hardness profile of carburized layer presented gradual decrease from ∼1,100 to ∼300 HV_0.1 within the distance of the total carburizing-affected region about 30 µm. The coefficient of friction, wear rate and wear morphology of carburized layer were analyzed. Scratch test indicated that the deformation process of carburized layer could be classified into three mechanisms (elastic, changing elastic–plastic and stable elastic–plastic mechanisms), and the deformation transition of the carburizing-affected region was from changing elastic–plastic to elastic mechanisms. Both the elastic and changing elastic–plastic mechanisms are conducive to the wearing course.

Using this technology, hydrogen embrittlement was avoided and wear resistance property of titanium alloy was greatly improved. Simultaneously, the constitutive relation during the whole loading process was deduced in terms of scratch approach, and the deformation mechanism of carburized layer was discussed from a novel viewpoint.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2019-0489/

Classifying the types of fabric defects in the textile industry requires a way to effectively detect. The traditional textile fabric defects detection method is human eyes, which performs very low efficiency and high cost. Therefore, how to improve the classification accuracy of textile fabric defects by using current artificial intelligence and to better meet the needs in the textile industry, the purpose of this article is to develop a method to improve the accuracy of textile fabric defects classification.

To improve the accuracy of textile fabric defects classification, an ensemble learning-based convolutional neural network (CNN) method in terms of textile fabric defects classification (short for ECTFDC) on an enhanced TILDA database is used. ECTFDC first adopts ensemble learning-based model to classify five types of fabric defects from TILDA. Subsequently, ECTFDC extracts features of fabric defects via an ensemble multiple convolutional neural network model and obtains parameters by using transfer learning method.

The authors applied ECTFDC on an enhanced TILDA database to improve the robustness and generalization ability of the proposed networks. Experimental results show that ECTFDC outperforms the other networks, the precision and recall rates are 97.8%, 97.68%, respectively.

The ensemble convolutional neural network textile fabric defect classification method in this paper can quickly and effectively classify textile fabric defect categories; it can reduce the production cost of textiles and it can alleviate the visual fatigue of inspectors working for a long time.