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The purpose of this paper is to enhance control accuracy, energy efficiency and productivity of customized industrial robots by the proposed multi-objective trajectory optimization approach. To obtain accurate dynamic matching torques of the robot joints with optimal motion, an improved dynamic model built by a novel parameter identification method has been proposed.

This paper proposes a novel multi-objective optimal approach to minimize the time and energy consumption of robot trajectory. First, the authors develop a reliable dynamic parameters identification method to obtain joint torques for formulating the normalized energy optimization function and dynamic constraints. Then, optimal trajectory variables are solved by converting the objective function into relaxation constraints based on second-order cone programming and Runge–Kutta discrete method to reduce the solving complexity.

Extensive experiments via simulation and in real customized robots are conducted. The results of this paper illustrate that the accuracy of joint torque predicted by the proposed model increases by 28.79% to 79.05% over the simplified models used in existing optimization studies. Meanwhile, under the same solving efficiency, the proposed optimization trajectory consumes a shorter time and less energy compared with the existing optimization ones and the polynomial trajectory.

A novel time-energy consumption optimal trajectory planning method based on dynamic identification is proposed. Most existing optimization methods neglect the effect of dynamic model reliability on energy efficiency optimization. A novel parameter identification approach and a complete dynamic torque model are proposed. Experimental results of dynamic matching torques verify that the control accuracy of optimal robot motion can be significantly improved by the proposed model.

Sensorless passive lead-through programming (LTP) is a promising physical human-robot interaction technology that enables manual trajectory demonstrations based on gravity and friction compensation. The major difficulty lies in static friction compensation during LTP start-up. Instead of static friction compensation, conventional methods only compensate for Coulomb friction after the joint velocity exceeds a threshold. Therefore, conventional start-up external torques must overcome static friction. When the static friction is considerable, it is difficult for conventional LTP to start up and make small movements. This paper aims to decrease the start-up external torque and improve the small movement performance.

This paper reveals a novel usage of a high-gain position-loop in industrial robot applications aimed at sensitively detecting external torque during start-up. Then, the static friction is partly compensated by Coulomb friction to facilitate start-up. In addition, a detailed transition method between the proposed start-up and conventional passive LTP is proposed based on a finite state machine.

Experiments are implemented on the ROKAE XB4 robot to verify the effectiveness of the proposed external torque detection. Compared with the conventional LTP method, the proposed LTP method significantly decreases the start-up external torque and facilitates small movements.

This paper proposes and verifies a novel start-up method of sensorless LTP based on a start-up external torque detection and a transition method between start-up and conventional LTP. This research improves the LTP start-up performance, especially for industrial robots with large static friction.

The purpose of this paper is to present a conceptual stage model of education and innovation type. The model depicts the influence of education on innovation and the paper aims to discuss the implications of it for the national competitiveness of China.

The paper presents a newly created conceptual stage model of education and innovation supported by observations and a literature review based on past and present innovation efforts in China.

The paper demonstrates the importance of linking creative education with radical innovation that is associated with higher value‐added economic activities. The findings of the empirical studies to date in China suggest that such a change will not be easy. There is a need to increase the propensity towards creative thought processes even if this is considered “undesirable behavior” both in the Chinese classroom and for the Chinese Communist party. Evidence suggests that without such creativity, self‐initiated radical innovation is not possible across a broader spectrum of the educational system, and that break‐through inventions in value‐added technology and design industries will be limited in China.

The model in the paper is designed to stimulate further research, initiate discussion and encourage action on driving creativity in Chinese educational policy and practices. The paper's analysis and findings will be of interest to managers and government policy makers in China that are charged with developing new programs to spur value‐added innovation. Researchers will find the ideas for further empirical research potentially valuable in helping them to design studies surrounding the phenomena of creativity, education and innovation practices.

In era of industry 4.0 all the organizations are investing their resources so they can adopt the latest technologies with no exception of supply chain. Accordingly, the present study attempted to examine the influence of digitalization of supply chain and performance in context of Chinese sports industry. Additionally, it has considered the supply chain integration and time management as a mechanism along with boundary condition of supply chain resilience.

The study followed positivism philosophy and adopted quantitative methods. The data were collected by using the questionnaire from the Chinese sport industry organizations’ professionals related to logistics and supply chain. A total 746 questionnaires were distributed and 570 of them subjected to SPSS and Smart PLS for data analysis. Hypotheses were tested using PLS-SEM through the Smart-PLS 4.

The results of the study revealed that supply chain digitalization positively influences the both internal and external supply chain integration. Moreover, supply chain planning and scheduling influenced by both internal and external supply chain integration lead by supply chain digitalization. Ultimately resulting in improved sports industry performance. However, the supply chain resilience did not found as a significant moderator.

The study is few of the attempts that have tested a comprehensive mechanism through which the supply chain digitalization lead towards the higher performance. Also, the study results signify that the digitization can help the organizations to accomplish superior performance specifically in sports industry.

This paper reviews the major publications by Qun G. Jiao and Anthony J. Onwuegbuzie that chronicles the development of empirical research conducted on the construct of library anxiety among college students in the United States during the past decade. It also examines the sizeable contribution that these two researchers have made to the body of knowledge of this emerging field of study in library and information science. The paper concludes by encouraging more researchers to continue the work of Jiao and Onwuegbuzie by examining further this widespread and pervasive phenomenon.

Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

This study aims to enhance the classification and processing of online appeals by employing a deep-learning-based method. This method is designed to meet the requirements for precise information categorization and decision support across various management departments.

This study leverages the ALBERT–TextCNN algorithm to determine the appropriate department for managing online appeals. ALBERT is selected for its advanced dynamic word representation capabilities, rooted in a multi-layer bidirectional transformer architecture and enriched text vector representation. TextCNN is integrated to facilitate the development of multi-label classification models.

Comparative experiments demonstrate the effectiveness of the proposed approach and its significant superiority over traditional classification methods in terms of accuracy.

The original contribution of this study lies in its utilization of the ALBERT–TextCNN algorithm for the classification of online appeals, resulting in a substantial improvement in accuracy. This research offers valuable insights for management departments, enabling enhanced understanding of public appeals and fostering more scientifically grounded and effective decision-making processes.

Considers TQM from a cultural perspective using the influence of Confucian work dynamism and Chinese cultural beliefs on Hong Kong companies. Asks if these cultural beliefs conflict with modern quality management philosophy and presents the findings of research covering Chinese literature, experts in Chinese philosophy and Hong Kong TQM experts. Outlines research methods and concludes that there are relevant principles which can be used when implementing TQM.

Drawing on the resource-based view, this study examines the effect of distribution adaptation on export performance. The study also examines the moderating role of responsiveness and commitment. Two distinct factors for commitment (i.e. managerial export commitment and financial export commitment) and two distinct factors for responsiveness (i.e. export customer responsiveness and export competitor responsiveness) are considered as moderators in the relationship between distribution adaptation and export performance.

Using a Spanish governmental database of exporting firms, this study collected data from 208 firms to run the analysis.

The results indicate that distribution adaptation has a positive impact on export performance. Findings also support the moderating roles of the two types of commitment and the two types of responsiveness. Managerial export commitment positively moderates the relationship, whereas financial export commitment plays a negative moderating role. Both export customer responsiveness and export competitor responsiveness have a positive moderating impact.

To consider distribution adaptation as a distinct variable rather than mixing it with other elements of the marketing mix. This distinction facilitates a clearer comprehension of its unique contribution to export performance. Two distinct factors for commitment and two distinct factors for responsiveness are considered. This approach offers a more detailed analysis of how the different aspects of commitment and responsiveness moderate this relationship.

Despite the literature on subordinates' destructive responses to abusive leadership, an emerging body of literature proposes that subordinates may react constructively to abusive supervision under certain conditions. The authors contribute to this line of research by proposing and testing the moderating effects of performance-approach and -avoidance goal orientation on the relationship between abusive supervision and task performance, and by testing work effort as a mechanism underlying this moderating effect.

The study hypotheses were tested in two studies. In Study 1 (field survey, N = 230), the moderation hypotheses were tested. Study 2 (experiment, N = 116) extended Study 1 and examined the mediated moderation model.

The study empirical evidence from the two studies showed that (1) abusive supervision was more positively related to an employee's task performance when that employee's performance-approach goal orientation was high (vs low), (2) abusive supervision was not more positively related to task performance when performance-avoidance goal orientation was high (vs low) and (3) the employee's work effort mediated the moderating effect of performance-approach goal orientation.

This research suggests that organizations and subordinates should be aware of the positive contextual role of performance-approach goal orientation, which may shape subordinates' subsequent work behavior in response to supervisors' hostility, and should invest more time and effort in reinforcing subordinates' performance-approach goal orientation.

This study has identified a new condition and offers new evidence of the potential functional effect of abusive supervision. Specifically, the study finding of the positive moderating role of performance-approach goal orientation adds to the literature examining when abused subordinates respond constructively to abusive supervision. The study analysis of the mediating effect of work effort further reveals the mechanism of this effect.