Abstract
Purpose
The purpose of this paper is to propose a two-degrees-of-freedom wire-driven 4SPS/U rigid‒flexible parallel trunk joint mechanism based on spring, in order to improve the robot’s athletic ability, load capacity and rigidity, and to ensure the coordination of multi-modal motion.
Design/methodology/approach
First, based on the rotation transformation matrix and closed-loop constraint equation of the parallel trunk joint mechanism, the mathematical model of its inverse position solution is constructed. Then, the Jacobian matrix of velocity and acceleration is derived by time derivative method. On this basis, the stiffness matrix of the parallel trunk joint mechanism is derived on the basis of the principle of virtual work and combined with the deformation effect of the rope driving pair and the spring elastic restraint pair. Then, the eigenvalue distribution of the stiffness matrix and the global stiffness performance index are used as the stiffness evaluation index of the mechanism. In addition, the performance index of athletic dexterity is analyzed. Finally, the distribution map of kinematic dexterity and stiffness is drawn in the workspace by numerical simulation, and the influence of the introduced spring on the stiffness distribution of the parallel trunk joint mechanism is compared and analyzed. It is concluded that the stiffness in the specific direction of the parallel trunk joint mechanism can be improved, and the stiffness distribution can be improved by adjusting the spring elastic structure parameters of the rope-driven branch chain.
Findings
Studies have shown that the wire-driven 4SPS/U rigid‒flexible parallel trunk joint mechanism based on spring has a great kinematic dexterity, load-carrying capacity and stiffness performance.
Research limitations/implications
The soft-mixed structure is not mature, and there are few new materials for the soft-mixed mixture; the rope and the rigid structure are driven together with a large amount of friction and hindrance factors, etc.
Practical implications
It ensures that the multi-motion mode hexapod mobile robot can meet the requirement of sufficient different stiffness for different motion postures through the parallel trunk joint mechanism, and it ensures that the multi-motion mode hexapod mobile robot in multi-motion mode can meet the performance requirement of global stiffness change at different pose points of different motion postures through the parallel trunk joint mechanism.
Social implications
The trunk structure is a very critical mechanism for animals. Animals in the movement to achieve smooth climbing, overturning and other different postures, such as centipede, starfish, giant salamander and other multi-legged animals, not only rely on the unique leg mechanism, but also must have a unique trunk joint mechanism. Based on the cooperation of these two mechanisms, the animal can achieve a stable, flexible and flexible variety of motion characteristics. Therefore, the trunk joint mechanism has an important significance for the coordinated movement of the whole body of the multi-sport mode mobile robot (Huang Hu-lin, 2016).
Originality/value
In this paper, based on the idea of combining rigid parallel mechanism with wire-driven mechanism, a trunk mechanism is designed, which is composed of four spring-based wire-driven 4SPS/U rigid‒flexible parallel trunk joint mechanism in series. Its spring-based wire-driven 4SPS/U rigid‒flexible parallel trunk joint mechanism can make the multi-motion mode mobile robot have better load capacity, mobility and stiffness performance (Qi-zhi et al., 2018; Cong-hao et al., 2018), thus improving the environmental adaptability and reliability of the multi-motion mode mobile robot.
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Xunjia Zheng, Bin Huang, Daiheng Ni and Qing Xu
The purpose of this paper is to accurately capture the risks which are caused by each road user in time.
Abstract
Purpose
The purpose of this paper is to accurately capture the risks which are caused by each road user in time.
Design/methodology/approach
The authors proposed a novel risk assessment approach based on the multi-sensor fusion algorithm in the real traffic environment. Firstly, they proposed a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory. This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was accurately obtained. Then, they conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated. The prediction steering angle and trajectory were considered in the determination of traffic risk influence area.
Findings
The results of multi-object perception in the experiments showed that the proposed fusion approach achieved low false and missing tracking, and the road traffic risk was described as a field of equivalent force. The results extend the understanding of the traffic risk, which supported that the traffic risk from the front and back of the vehicle can be perceived in advance.
Originality/value
This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was used to reduce erroneous data association between tracks and detections. Then, the authors conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.
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Michelle M.E. van Pinxteren, Ruud W.H. Wetzels, Jessica Rüger, Mark Pluymaekers and Martin Wetzels
Service robots can offer benefits to consumers (e.g. convenience, flexibility, availability, efficiency) and service providers (e.g. cost savings), but a lack of trust hinders…
Abstract
Purpose
Service robots can offer benefits to consumers (e.g. convenience, flexibility, availability, efficiency) and service providers (e.g. cost savings), but a lack of trust hinders consumer adoption. To enhance trust, firms add human-like features to robots; yet, anthropomorphism theory is ambiguous about their appropriate implementation. This study therefore aims to investigate what is more effective for fostering trust: appearance features that are more human-like or social functioning features that are more human-like.
Design/methodology/approach
In an experimental field study, a humanoid service robot displayed gaze cues in the form of changing eye colour in one condition and static eye colour in the other. Thus, the robot was more human-like in its social functioning in one condition (displaying gaze cues, but not in the way that humans do) and more human-like in its appearance in the other (static eye colour, but no gaze cues). Self-reported data from 114 participants revealing their perceptions of trust, anthropomorphism, interaction comfort, enjoyment and intention to use were analysed using partial least squares path modelling.
Findings
Interaction comfort moderates the effect of gaze cues on anthropomorphism, insofar as gaze cues increase anthropomorphism when comfort is low and decrease it when comfort is high. Anthropomorphism drives trust, intention to use and enjoyment.
Research limitations/implications
To extend human–robot interaction literature, the findings provide novel theoretical understanding of anthropomorphism directed towards humanoid robots.
Practical implications
By investigating which features influence trust, this study gives managers insights into reasons for selecting or optimizing humanoid robots for service interactions.
Originality/value
This study examines the difference between appearance and social functioning features as drivers of anthropomorphism and trust, which can benefit research on self-service technology adoption.
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En-Ze Rui, Guang-Zhi Zeng, Yi-Qing Ni, Zheng-Wei Chen and Shuo Hao
Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural…
Abstract
Purpose
Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.
Design/methodology/approach
A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.
Findings
Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.
Originality/value
In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.
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Qing Zhu, Yiqiong Wu, Yuze Li, Jing Han and Xiaoyang Zhou
Library intelligence institutions, which are a kind of traditional knowledge management organization, are at the frontline of the big data revolution, in which the use of…
Abstract
Purpose
Library intelligence institutions, which are a kind of traditional knowledge management organization, are at the frontline of the big data revolution, in which the use of unstructured data has become a modern knowledge management resource. The paper aims to discuss this issue.
Design/methodology/approach
This research combined theme logic structure (TLS), artificial neural network (ANN), and ensemble empirical mode decomposition (EEMD) to transform unstructured data into a signal-wave to examine the research characteristics.
Findings
Research characteristics have a vital effect on knowledge management activities and management behavior through concentration and relaxation, and ultimately form a quasi-periodic evolution. Knowledge management should actively control the evolution of the research characteristics because the natural development of six to nine years was found to be difficult to plot.
Originality/value
Periodic evaluation using TLS-ANN-EEMD gives insights into journal evolution and allows journal managers and contributors to follow the intrinsic mode functions and predict the journal research characteristics tendencies.
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The purpose of this paper is to construct a digital collection and database of traditional clothing that is convenient for the digital dissemination and application of traditional…
Abstract
Purpose
The purpose of this paper is to construct a digital collection and database of traditional clothing that is convenient for the digital dissemination and application of traditional clothing and provide resources for research on clothing fashion, traditional clothing techniques, clothing culture, history and clothing teaching.
Design/methodology/approach
A real object analysis method was used in this paper, based on 15 core elements of the internationally common DC metadata standard, and with consideration to the characteristics of clothing products and clothing industry application specifications, the core elements of DC are expanded to facilitate the detailed record of the characteristic information of clothing, especially the implicit clothing culture. A code symbol compilation method was developed to give each piece of clothing a unique number, facilitating identification, classification and recording. At last, a metadata construction scheme for traditional clothing was developed. A traditional embroidered children's hat and Mamianqunt serve as examples to demonstrate the metadata elements.
Findings
The clothing meta-database provides a main body of traditional clothing while also paying attention to the collection of cultural elements. It is composed of five layers of classified data, source data, characteristic data, connotation data and management data, as well as 28 data elements, providing ease of sharing and interoperation.
Originality/value
This paper expands the subset of fashion metadata by describing traditional clothing metadata, especially the excavation of clothing cultural elements, and developing code compilation methods so that each clothing product can obtain a unique identification number, thereby building a traditional clothing metadata construction scheme consisting of five data layers and containing 28 data elements. This scheme records the information about each layer of traditional clothing in detail and provides shared data for discipline research and industry applications.
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Han Shen, Qiucheng Wang, Chuou Ye and Jessica Shihchi Liu
The purpose of this paper is to focus on the reforms in the public-holiday-policy system and their influence on the domestic tourism in China. The major reforms in the Chinese…
Abstract
Purpose
The purpose of this paper is to focus on the reforms in the public-holiday-policy system and their influence on the domestic tourism in China. The major reforms in the Chinese holiday system in the last 20 years and the overall changes in the demand for domestic tourism are analyzed in this paper to provide a better understanding of China’s holiday-system reform for policy makers in the future.
Design/methodology/approach
This paper summarizes the development and reform of the holiday system in China. Policy review and domestic tourism statistics were applied to study the intrinsic relationship between the holiday system and the domestic tourism. The statistics of domestic tourism are cited, including the growth rates of both urban and rural tourists, the domestic tourism expenditure per capita, etc. Finally, this research explains the trends of these rates in a comprehensive background.
Findings
The increasing length of holidays positively affects the domestic tourism demand by increasing the leisure time. Yet, the holiday-tourism activities lead to a series of problems, such as a huge pressure on transportation, overloaded tourist attractions, and threats to safety precautions. Paid leave, price leverage, and more reasonable tourist-attraction arrangements will be effective in easing China’s holiday rush.
Originality/value
Through studying the intrinsic relationship between the holiday system and the domestic tourism, this paper points out the problems of excessive concentration of domestic tourism demand in a particular time, caused by the holiday system. Solutions and suggestions are provided on the basis of the analysis.
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Karolina Oleksa-Marewska and Agnieszka Springer
Based on the theory of organizational socialization, this article broadens the knowledge in the field of organizational commitment by determining the relationship between the…
Abstract
Purpose
Based on the theory of organizational socialization, this article broadens the knowledge in the field of organizational commitment by determining the relationship between the organizational climate (OC) and the employees’ commitment, as well as the moderating role of the person-environment (P-E) fit.
Design/methodology/approach
We conducted quantitative research using three psychometric questionnaires. We investigated a large sample (N = 1,032) of employees hired in Poland.
Findings
We found strong relationships between the OC, the employees’ fit and their commitment. Moreover, both supplementary and complementary fit significantly moderated the relationships between the majority of climate dimensions and, especially, affective commitment. Interestingly, highly fitted employees with longer tenure showed a stronger relationship between material climate dimensions and commitment compared to similarly fitted newcomers, for whom the most important were relationships with co-workers and superiors.
Research limitations/implications
We analyzed only a subjective fit among employees working in Poland. Although it was beneficial for developing the OC knowledge of non-American sample, the results require cautious generalization.
Practical implications
Assessing a candidate’s fit with the organization through detailed interviews, behavioral questions or practical tasks during the selection process can improve candidates' and employees’ P-E fit. A better fit can increase commitment, even if the OC or other factors are not perfect. Socialization tactics aimed at strengthening the fit can facilitate better alignment with the climate and higher commitment among employees with longer tenure.
Originality/value
This study is the first to empirically verify the moderating role of the P-E fit on the relations between OC and organizational commitment. It also considers the comparison between more experienced employees and newcomers.
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Shanzhong Du and June Cao
Industrial robots are of great significance to the long-term development of family firms. Drawing on the lens of the principal–principal conflict, this paper aims to investigate…
Abstract
Purpose
Industrial robots are of great significance to the long-term development of family firms. Drawing on the lens of the principal–principal conflict, this paper aims to investigate the influence of family non-executive directors on robot adoption in Chinese family firms.
Design/methodology/approach
This paper selects the family firms in China from 2011 to 2019 as the sample. Furthermore, the authors manually collected the family non-executive directors and constructed the robot adoption variable utilizing data sourced from the International Federation of Robotics. In brief, this paper constructs a comprehensive framework of the mechanisms and additional tests pertaining to the influence of family non-executive directors on robot adoption.
Findings
This paper finds that family non-executive directors can promote robot adoption in family firms. The underlying mechanism analysis shows that family non-executive directors promote robot adoption by exerting financial and human effects. This paper further finds that the characteristics of family non-executive directors, such as kinship, differential shareholding and excessive directors, affect the role of family non-executive directors. Finally, robot adoption can improve future performance, and the promotional effect is more evident when family members are non-executive directors.
Originality/value
This paper contributes to the related literature from the following two aspects. Firstly, this paper decomposes the types of family directors to understand the role of family non-executive directors, which challenges the assumption that family board members are homogeneous in family firms. Second, this paper expands the research on the factors that influence robot adoption in emerging economies from the micro-enterprise level. In addition, the findings in this paper have managerial implications for family firms to optimize their strategic decisions with the help of the mode of board right allocation.
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Mercy Mpinganjira, Nobukhosi Dlodlo and Efosa C. Idemudia
In the quest to build a sense of human contact, e-retailers are increasingly depending on the scalability of chatbots to promote assistive dialogue during online shopping. Not…
Abstract
Purpose
In the quest to build a sense of human contact, e-retailers are increasingly depending on the scalability of chatbots to promote assistive dialogue during online shopping. Not much is known about the experiential value of customer interaction. This research proposes and evaluates a conceptual model for understanding the value perceptions emanating from the experiences of fashion shoppers utilising e-retail chatbots.
Design/methodology/approach
Data were collected using an online survey administered to 460 online panellists. Structural equation modelling was used to test the proposed research model.
Findings
Continued chatbot use intentions (CUIs) are influenced positively by perceived hedonic and utilitarian experiential value. Perceived social experiential value had a negative effect on shoppers’ continued intention to use the chatbot. Both perceived chatbot anthropomorphism and perceived chatbot intelligence positively and significantly affect shoppers’ experiential value while perceived chatbot risk yields a significantly negative effect.
Social implications
By using conversational artificial intelligence chatbots, engagement at e-retail stores can be driven based on the user data and made more interactive.
Originality/value
The study introduces an e-retail chatbot model which asserts the power of selected chatbot attributes as catalysts of shoppers’ experiential value. Cumulatively, the model is a first-step approach providing a novel and balanced (both positive attributes and negative risks) view of chatbot continued use intentions.