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This work presents a new two-step iterative technique for solving absolute value equations. The developed technique is valuable and effective for solving the absolute value equation. Various examples are given to demonstrate the accuracy and efficacy of the suggested technique.

In this paper, we present a new two-step iterative technique for solving absolute value equations. This technique is very straightforward, and due to the simplicity of this approach, it can be used to solve large systems with great effectiveness. Moreover, under certain assumptions, we examine the convergence of the proposed method using various theorems. Numerical outcomes are conducted to present the feasibility of the proposed technique.

This paper gives numerical experiments on how to solve a system of absolute value equations.

Nowadays, two-step approaches are very popular for solving equations (1). For solving AVEs, Liu in Shams (2021), Ning and Zhou (2015) demonstrated two-step iterative approaches. Moosaei et al. (2015) introduced a novel approach that utilizes a generalized Newton’s approach and Simpson’s rule to solve AVEs. Zainali and Lotfi (2018) presented a two-step Newton technique for AVEs that converges linearly. Feng and Liu (2016) have proposed minimization approaches for AVEs and presented their convergence under specific circumstances. Khan et al. (2023), suggested a nonlinear CSCS-like technique and a Picard-CSCS approach. Based on the benefits and drawbacks of the previously mentioned methods, we will provide a two-step iterative approach to efficiently solve equation (1). The numerical results show that our proposed technique converges rapidly and provides a more accurate solution.

The purpose of this study is to study the quantitative evaluation method of contact wire cracks by analyzing the changing law of eddy current signal characteristics under different cracks of contact wire of high-speed railway so as to provide a new way of thinking and method for the detection of contact wire injuries of high-speed railway.

Based on the principle of eddy current detection and the specification parameters of high-speed railway contact wires in China, a finite element model for eddy current testing of contact wires was established to explore the variation patterns of crack signal characteristics in numerical simulation. A crack detection system based on eddy current detection was built, and eddy current detection voltage data was obtained for cracks of different depths and widths. By analyzing the variation law of eddy current signals, characteristic parameters were obtained and a quantitative evaluation model for crack width and depth was established based on the back propagation (BP) neural network.

Numerical simulation and experimental detection of eddy current signal change rule is basically consistent, based on the law of the selected characteristics of the parameters in the BP neural network crack quantitative evaluation model also has a certain degree of effectiveness and reliability. BP neural network training results show that the classification accuracy for different widths and depths of the classification is 100 and 85.71%, respectively, and can be effectively realized on the high-speed railway contact line cracks of the quantitative evaluation classification.

This study establishes a new type of high-speed railway contact wire crack detection and identification method, which provides a new technical means for high-speed railway contact wire injury detection. The study of eddy current characteristic law and quantitative evaluation model for different cracks in contact line has important academic value and practical significance, and it has certain guiding significance for the detection technology of contact line in high-speed railway.

Based on the person-environment (P-E) fit theory, this study aims to explore the effect of customer mistreatment on the reduced service performance of hospitality employees mediated by person-job (P-J) fit perceptions and moderated by job crafting.

The authors tested this study’s hypotheses with a nine-day diary study involving 83 service employees located in Lanzhou, China; a total of 548 daily surveys were completed. The authors used multilevel structural equation modeling to analyze the data.

Employees who experienced daily customer mistreatment suffered diminished P-J fit perceptions, leading to lower levels of service performance the next day. In addition, job crafting significantly buffered the impact of customer mistreatment on P-J fit perceptions and the indirect impact of customer mistreatment on service performance through P-J fit perceptions.

Given the damaging effect that customer mistreatment has on service performance, where employees’ P-J fit perceptions are impaired, hotel managers should implement service competence improvement training programs and managerial preventions to reduce the possibility of customer mistreatment behavior. The moderating role of job crafting behavior suggests that managers should offer supportive practices (i.e. job autonomy) to encourage job crafting behaviors among employees.

This study reveals that individuals’ P-J fit perceptions can explain the damaging impacts of customer mistreatment on service performance, a finding that contributes valuable information to the literature on customer mistreatment and P-E fit. Second, this study also tests the impact of individuals’ job crafting behaviors in terms of mitigating the negative effect of customer mistreatment. Finally, this study’s findings broaden the scope of predictors of P-J fit perceptions by revealing that customer mistreatment can pose a threat to hospitality employees’ P-J fit perceptions.

Drawing on the self-cognitive theory, this study aims to propose a conceptual model that links customer mistreatment with different types of helping behaviors through the self-efficacy mechanism.

The empirical analysis made use of the original data of three hotels located in southern China. The authors tested the hypotheses with a three-wave survey of a sample of 430 frontline workers in 95 groups.

Customer mistreatment may reduce employees’ self-efficacy, which has both positive and negative effects depending on the type of helping. Moreover, the coworkers’ supporting climate buffered the influence of self-efficacy on autonomous and dependent helping.

The authors resolve the ambiguity surrounding customer mistreatment-helping and self-efficacy-helping relations. Thus, the authors extend the knowledge on the influence of customer mistreatment and self-efficacy on helping behaviors by establishing that both positive and negative effects may exist depending on the type of helping. Moreover, this study identifies the predictive role of self-efficacy in autonomous and dependent helping.

This meta-analytical review aims to clarify the relationships between three bundles of human resource management (HRM) practices—competency-enhancing, motivation-enhancing and opportunity-enhancing—and organizational innovation by addressing two questions: (a) Which types of HRM bundles are most strongly related to different forms of innovation (i.e. process and product innovation)? And (b) Which mechanism provides a stronger explanation for the positive effects of HRM bundles on innovation?

Based on data from 103 studies, a meta-analysis was conducted to quantitatively summarize existing HRM–innovation studies at the organizational level.

The results showed that the competency-enhancing bundle was more positively related to product innovation than the motivation-enhancing and opportunity-enhancing bundles. The opportunity-enhancing bundle was most strongly associated with process innovation. The authors further found that knowledge management capability (KMC) and employee motivation mediated the positive relationship between the three HRM bundles and innovation outcomes. In comparing the two mechanisms, this review suggests that KMC better explains both the impact of the competency-enhancing HRM bundle on product innovation and the effect of the opportunity-enhancing bundle on process innovation.

Based on behavioral and knowledge management perspectives, this study takes a sub-bundle approach to providing an integrative review by comparing the direct effects and mediating paths of HRM bundles on product and process innovation.

To achieve stable gait planning and enhance the motion performance of quadruped robot, this paper aims to propose a motion control strategy based on central pattern generator (CPG) and back-propagation neural network (BPNN).

First, the Kuramoto phase oscillator is used to construct the CPG network model, and a piecewise continuous phase difference matrix is designed to optimize the duty cycle of walk gait, so as to realize the gait planning and smooth switching. Second, the mapper between CPG output and joint drive is established based on BP neural network, so that the quadruped robot based on CPG control has better foot trajectory to enhance the motion performance. Finally, to obtain better mapping effect, an evaluation function is resigned to evaluate the proximity between the actual foot trajectory and the ideal foot trajectory. Genetic algorithm and particle swarm optimization are used to optimize the initial weights and thresholds of BPNN to obtain more accurate foot trajectory.

The method provides a solution for the smooth gait switching and foot trajectory of the robot. The quintic polynomial trajectory is selected to testify the validity and practicability of the method through simulation and prototype experiment.

The paper solved the incorrect duty cycle under the walk gait of CPG network constructed by Kuramoto phase oscillator, and made the robot have a better foot trajectory by mapper to enhance its motion performance.

The purpose of this paper is to investigate the wear resistance behavior of the striated tool for cross wedge rolling (CWR).

A mechanical-thermal coupled, temperature-dependent FE wear model was developed to explore the wear behaviors for striated CWR tools. To verify the proposed FE model, a newly developed measuring device was also developed to measure wear on the tool ridge. To find the impact order of the parameters of striate unit, orthogonal experiment was carried out.

The experimental and numerical results both indicate that the wear resistance of striated tool is better than that of smooth tool. Minimum tool ridge wear can be achieved by choosing proper tool contact temperature with striated units on crossed ridge. The order of the striation geometrical factors’ impact on ridge wear is striation width > striation interval > striation length.

Because of the specified tool, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.

It is shown that the wear resistance of striated CWR tool is better than that of smooth tool. The information may help CWR manufactures to design and produce tools with less wear.

A low-level controller is critical to the overall performance of multirotor unmanned aerial vehicles. The purpose of this paper is to propose a nonlinear low-level angular velocity controller for multirotor unmanned aerial vehicles in various operating conditions (e.g. different speed and different mode).

To tackle the above challenge, the authors have designed a nonlinear low-level controller taking the actuator dynamics into account. The authors first build the actuator subsystem by combining the actuator dynamics with the angular velocity dynamics model. Then, a recursive low-level controller is developed by designing a high-gain observer to estimate unmeasurable states. Furthermore, a detailed stability analysis is given with the Lyapunov theory.

Simulation tests and real-world flying experiments are provided to validate the proposed approach. In particular, we illustrate the performance of the proposed controller using violent random command test, attitude mode flight and high-speed flight of up to 18.7 m/s in real world. Compared with the classical method used in PX4 autopilot and the estimation-based incremental nonlinear dynamic inversion method, experimental results show that the proposed method can further reduce the control error.

Low-level control of multirotor UAVs is challenging due to the complex dynamic characteristics of UAVs and the diversity of tasks. Although some progress has been made, the performance of existing methods will deteriorate as operating conditions change due to the disregard for the electromechanical characteristics of the actuator.

To solve the low-level angular velocity control problem in various operating conditions of multirotor UAVs, this paper proposes a nonlinear low-level angular velocity controller which takes the actuator dynamics into account.

The purpose of this study is to provide insights into bootleg innovation by investigating whether perceived hindrance stressors play an important role in bootlegging and how different organizational ownership types (state-owned enterprises (SOEs) vs non-SOEs) affect this relationship.

The study samples comprised 3,967 employees from 674 knowledge-intensive companies in southern China. Multilevel structural equation modeling was used to test the hypotheses.

Drawing on the conservation of resources (COR) theory, the results show that hindrance stressors have a curvilinear (U-shaped) influence on bootleg innovation, and that the curve relationship between the hindrance stressors and bootlegging is more pronounced among employees in non-SOEs.

The findings indicate that either a low or high level of hindrance stressors can activate a high level of bootlegging activities among employees. These results suggest that managers need to be vigilant in detecting the level of hindrance because different motivations predominate at different stressor levels.

Based on the COR theory, the findings cast perceived hindrance stressors as an antecedent of bootlegging at the individual level. The inquiry into state ownership types further provides a comprehensive understanding of the non-linear relationship between hindrance stressors and bootlegging.

Drawing on the transaction theory of stress, the purpose of this paper is to conceptualize customer mistreatment as a stressor and examine how job routinization and proactive personality help employees cope with the effects of customer mistreatment on emotional exhaustion and work engagement. The interaction of job routinization and proactive personality was also tested.

In total, 128 hundred nurses were recruited to participate in the current study, which was a daily survey for two consecutive weeks (10 working days).

The results revealed that job routinization and proactive personality attenuated the effects of customer mistreatment on emotional exhaustion and work engagement. The analyses also showed that, with more proactive personality and high job routinization, the effects of customer mistreatment were minimized.

Job routinization is a type of job resources that attenuates the negative influence of customer mistreatment. Proactive personality strengthens job routinization’s function, when proactive personality and job routinization are both high, the ill effect of customer mistreatment will be minimized.