Search results

This paper aims to propose a real-time evolutionary multi-objective semi-analytical inverse kinematics (IK) algorithm (EMSA-IK) for solving the multi-objective IK of redundant manipulators.

Within EMSA-IK, the parameterization method is applied to reduce the number of optimization variables of the evolutionary algorithm and calculate semi-analytical solutions that meet high target pose accuracy. The original evolutionary algorithm is improved with the proposed adaptive search sub-space strategy so that the improved evolutionary algorithm can be used to efficiently perform global search within the parametric joint space to obtain the global optimal parametric joint angles that satisfy multi-objective constraints.

Ablation experiments show the effectiveness of the improved strategy used for evolutionary algorithms. Comparative experiments on different manipulators demonstrate the advantages of EMSA-IK in terms of generalizability and balancing multiple objectives, for example, motion continuity, joint limits and obstacle avoidance. Real-world experiments further validate the effectiveness of the proposed algorithm for real-time application.

The semi-analytical IK solution that simultaneously satisfies high target pose accuracy and multi-objective constraints can be obtained in real time. Compared to existing semi-analytical IK algorithms, the proposed algorithm achieves obstacle avoidance for the first time. The proposed algorithm demonstrates superior generalizability, applicable to not only redundant manipulators with revolute joints but also those with prismatic joints.

This study aims to investigate the effect of the virtual spokesperson type on the consumers' preference for new products. To meet the consumer needs of Generation Z, virtual spokespeople have become new assistants in brand marketing. However, how virtual spokespersons drive consumer preference for new products is minimally understood.

This research conducts three experiments to investigate the influence of virtual spokesperson type on consumers' preference for new products.

The research shows that, for radically new products, competent virtual spokespersons improve consumers' perception of self-efficacy and thus consumers' preference; for incrementally new products, warm virtual spokespersons improve consumers' perception of social connection and thus consumers' willingness to buy.

This study broadens research on brand spokespersons and virtual spokespersons. This research also enriches and expands research on the consideration of new product types in brand spokespersons.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

Employee green behavior (EGB) is a type of pro-environment behavior at the workplace strategized by organizations to attain sustainable development goals. While organizations have prioritized eco-friendly practices to attain sustainability objectives, EGB has emerged as an essential area of research. Considering the need for sustained employee green behavior, it is important to understand what stimulates such behaviors in an organization. Therefore, we propose a theoretical model grounded in social exchange theory to assess the effect of organizational commitment on employee green behavior, work-related use of social media, social well-being and psychological well-being.

A questionnaire-based survey approach was used to collect data from 203 employees of Indian manufacturing and service industries. Partial least square structural equation modeling (PLS-SEM) analysis was applied to examine the proposed hypothesis.

The results revealed positive and significant effects of organizational commitment on psychological well-being, social well-being, work-related social media use and employee green behavior. Further, psychological well-being mediates the association between work-related social media use and employee green behavior.

This is one of the first studies to examine the effect of organizational commitment on employee green behavior to the best of our knowledge. Additionally, the findings empirically establish organizational commitment, work-related social media use and psychological well-being as antecedents to employee green behavior, thus offering novel insights and theoretically contributing to the employee green behavior, well-being and organizational literature.