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The purpose of this paper is to develop a human activity-aware adaptive shared control solution for human–robot interaction in surgical operation. Hands-on control and teleoperation are two main procedures switched frequently in teleoperated minimally invasive surgery (MIS). The detailed human activity in the procedures can be defined and recognized using the sensor information. In this paper, a novel continuous adaptive shared control method is proposed for manipulators with Cartesian impedance control in the surgical scenario.

A human activity-aware shared control solution by adjusting the weight function is introduced to achieve smooth transition among different human activities, including hands-on control and teleoperation. Instead of introducing various controllers and switching among them during the surgical procedures, the proposed solution integrated all the human activity-based controllers into a single controller and the transition among the procedures is smooth and stable. The effectiveness of the proposed control approach was verified in a lab setup environment. The results prove that the robot behavior is stable and smooth. The algorithm is feasible and can achieve a human activity-aware adaptive shared control solution for human–robot interaction in surgical operation.

Based on the experiment, the results confirm that the proposed human activity-aware adaptive shared control solution can switch the device behavior automatically using the real-time sensor information. The transition between different activities is smooth and stable.

For teleoperated surgical applications, the proposed method integrated different controllers for various human activities into a single controller by recognizing the activities using the real-time sensor information and the transition between different procedures is smooth and stable. It eases the surgical work for the surgeon and enhances the safety during the transition of control modes. The presented scheme provides a general solution to address the switching of working procedures in teleoperated MIS.

To the best of the authors’ knowledge, this paper is the first to propose human activity-aware adaptive shared control solution for human–robot interaction in surgical operations.

The purpose of this paper is to mainly center on the touchless interaction between humans and robots in the real world. The accuracy of hand pose identification and stable operation in a non-stationary environment is the main challenge, especially in multiple sensors conditions. To guarantee the human-machine interaction system’s performance with a high recognition rate and lower computational time, an adaptive sensor fusion labeling framework should be considered in surgery robot teleoperation.

In this paper, a hand pose estimation model is proposed consisting of automatic labeling and classified based on a deep convolutional neural networks (DCNN) structure. Subsequently, an adaptive sensor fusion methodology is proposed for hand pose estimation with two leap motions. The sensor fusion system is implemented to process depth data and electromyography signals capturing from Myo Armband and leap motion, respectively. The developed adaptive methodology can perform stable and continuous hand position estimation even when a single sensor is unable to detect a hand.

The proposed adaptive sensor fusion method is verified with various experiments in six degrees of freedom in space. The results showed that the clustering model acquires the highest clustering accuracy (96.31%) than other methods, which can be regarded as real gestures. Moreover, the DCNN classifier gets the highest performance (88.47% accuracy and lowest computational time) than other methods.

This study can provide theoretical and engineering guidance for hand pose recognition in surgery robot teleoperation and design a new deep learning model for accuracy enhancement.

This paper aims on the trajectory tracking of the developed six wheel-legged robot with heavy load conditions under uncertain physical interaction. The accuracy of trajectory tracking and stable operation with heavy load are the main challenges of parallel mechanism for wheel-legged robots, especially in complex road conditions. To guarantee the tracking performance in an uncertain environment, the disturbances, including the internal friction, external environment interaction, should be considered in the practical robot system.

In this paper, a fuzzy approximation-based model predictive tracking scheme (FMPC) for reliable tracking control is developed to the six wheel-legged robot, in which the fuzzy logic approximation is applied to estimate the uncertain physical interaction and external dynamics of the robot system. Meanwhile, the advanced parallel mechanism of the electric six wheel-legged robot (BIT-NAZA) is presented.

Co-simulation and comparative experimental results using the BIT-NAZA robot derived from the developed hybrid control scheme indicate that the methodology can achieve satisfactory tracking performance in terms of accuracy and stability.

This research can provide theoretical and engineering guidance for lateral stability of intelligent robots under unknown disturbances and uncertain nonlinearities and facilitate the control performance of the mobile robots in a practical system.

Snake-inspired robots are of great significance in many fields because of their great adaptability to the environment. This paper aims to systematically illustrate the research progress of snake-inspired robots according to their application environments. It classifies snake-inspired robots according to the numbers of degrees of freedom in each joint and briefly describes the modeling and control of snake-inspired robots. Finally, the application fields and future development trends of snake-inspired robots are analyzed and discussed.

This paper summarizes the research progress of snake-inspired robots and clarifies the requirements of snake-inspired robots for self-adaptive environments and multi-functional tasks. By equipping various sensors and tool modules, snake-inspired robots are developed from fixed-point operation in a single environment to autonomous operation in an amphibious environment. Finally, it is pointed out that snake-inspired robots will be developed in terms of rigid and flexible deformable structure, long endurance and multi-function and intelligent autonomous control.

Inspired by the modular and reconfigurable concepts of biological snakes, snake-inspired robots are well adapted to unknown and changing environments. Therefore, snake-inspired robots will be widely used in industrial, military, medical, post-disaster search and rescue applications. Snake-inspired robots have become a hot research topic in the field of bionic robots.

This paper summarizes the research status of snake-inspired robots, which facilitates the reader to be a comprehensive and systematic understanding of the research progress of snake-inspired robots. This helps the reader to gain inspiration from biological perspectives.

Prior studies on major customer relationships (i.e. embedded ties) focus mostly on the ties between a focal firm and its immediate customers, hindering the understanding of the influence of indirect ties (both upstream and downstream) on a focal firm's operational performance. In this study, the authors analyze how a focal firm's upstream and downstream connectedness and network location affect its productive efficiency.

Utilizing Compustat segment files, the authors constructed large-scale major customer networks covering the period 2007–2013. The authors applied a fixed-effect panel stochastic frontier model to conduct estimation. Moreover, the authors applied an endogenous panel stochastic frontier model to ensure the robustness of the main analysis.

The authors found that a focal firm's upstream and downstream connectedness both have a positive influence on a firm's productive efficiency, whereas a focal firm's centeredness in the major customer network has a negative influence on productive efficiency. Moreover, it was found that centeredness lessens the positive influences of upstream and downstream connectedness on productive efficiency. The post hoc analysis further confirmed that a focal firm's indirect ties, both upstream and downstream, positively influence a focal firm's productive efficiency.

This study contributes to the literature by evaluating the relative effectiveness of a focal firm's direct and indirect major customer ties, both upstream and downstream. More importantly, this study suggests potential exploitation–exploration trade-offs (i.e. productive efficiency vs. innovation) triggered by a firm's network location.

This study investigates how a firm's structural embeddedness, the structural position in a supply network that consists of major customers, influences the acquisition of supplier trade credit. Specifically, this study examines how network interconnectedness, network integration and network independence of a firm affect its ability to acquire supplier trade credit.

This study utilizes financial data from Compustat to build a longitudinal dataset of manufacturing firms from 1998 to 2013. Customer segment disclosure data are used to construct firm-level network variables. A fixed effect regression approach is used for estimation.

The study results show that network interconnectedness is negatively associated with supplier trade credit, while network integration is positively associated with supplier trade credit. Network independence does not influence the extent of supplier trade credit. The post hoc analysis shows that the effects of the hypothesized factors vary under different product categories and credit ratings.

This study broadens the supply chain finance literature by showing how a firm's embedded network structural position can influence its ability to obtain supplier trade credit.

The purpose of this study is to examine the effects of three strategic environmental options on reducing greenhouse gas (GHG) emissions. Namely, we examine the effects of pollution prevention and waste management (PPWM) practices, green supply chain (GSC) practices, and outsourcing on reducing local and supply chain GHG emissions.

Using ASSET4 and deploying first-differencing fixed-effects panel data models, the study conducts a large-scale empirical examination on the effects of these focal strategic environmental options on GHG emissions.

This study finds that PPWM practices reduce local GHG emissions and that GSC practices reduce supply chain GHG emissions. The results also show that outsourcing does not reduce local GHG emissions and has an adverse effect on supply chain GHG emissions.

The study findings indicate that environmental practices are effective in reducing GHG emissions. However, they are effective only in their corresponding domain. Further, outsourcing is not a viable strategic option, and managers should be mindful of its undesired environmental consequences.

Firms undertake strategic environmental options, such as implementing environmental practices and reallocating production activities, to improve their environmental performance. Nevertheless, the effectiveness of these options on reducing GHG emissions has not been thoroughly examined.

China’s expanded rice imports offer a profitable business opportunity for both domestic and international grain marketers. The purpose of this paper is to analyze the impact of select variables on Chinese consumers’ rice choices, specifically focusing on country-of-origin, price, organic, brand, freshness, and taste. The study concludes with suggestions for domestic and international rice marketers to help them develop more efficient rice marketing plans.

This study developed a conditional logit model to analyze survey data gathered from Chongqing and Chengdu, two of China’s largest rice consumption cities.

Chinese consumers are price sensitive in their rice choices. Country-of-origin is the most imperative factor affecting rice selection for lower food expense consumers but branded rice attracts the attention of higher food expense consumers. Furthermore, these higher food expense consumers are willing to pay a small premium of $0.22 for a pound of organic rice.

A general trend in demand for organic rice from higher food expense consumers was identified, and this trend predicts a profitable market for organic rice sellers. However, these research findings are geographically limited and may only represent a consumption trend from the two sampled cities rather than all of China.

The study concludes with meaningful recommendations to rice marketers to aid in developing profitable market entrance strategies to China.

In 2022, the International Network for Quality Assurance (QA) Agencies in Higher Education (INQAAHE) published the new guidelines by adding three QA modules in response to the changing higher education landscape. The paper aims to investigate the transformative focus of quality assurance in higher education globally as well as Asian response to three new QA modules according to the INQAAHE ISGs.

The research conducted a quantitative approach for data collection. An on-line survey was conducted to perceive QA practices, perceptions toward new emerging QA modules and challenges encountered. In total, there were 26 responses from 18 territories with 22 QA agencies. A total of 13 out of them have a national qualifications framework in place.

Three are three major findings in the study. First, national policy and criteria and standards in distance education have been developed in the majority of Asian nations. Second, non-signatories of the Tokyo Convention had a higher proportion of having related policies, regulations and criteria in CBHE and distance education. Third, national policies and regulations; and lack of professional staff are two common challenges implementing QA in new types of providers.

The findings are of value for policymakers, QA agencies and universities to advocate the new QA model as a systematic approach in response to changing higher education landscape in the post pandemic era.

The 2020 pandemic disrupted traditional student mobility and forced a larger majority of transnational programmes to switch to a virtual or hybrid mode, including joint and double degree programmes. Therefore, this study aims to perceive the linkage between quality assurance (QA) and delivery modes of cross-border higher education (CBHE) in Asia before and during the pandemic.

Through an online survey and semi-structured interviews, the process by which top 200 ranked universities in the 2022 QS global ranking responded to QA and qualification issues of joint/dual degree programs in conjunction with delivery modes was explored.

The study has discovered that most respondents from universities, to some extent, tended to be positive about the effectiveness of hybrid delivery of the joint/dual degree programs, even if they still preferred the physical mode to alternatives. Either “divergence” or “responsiveness” QA modes were not applied appropriately in most joint/dual degree programs of the selected universities during the pandemic. Moreover, a fair, transparent and convergent quality and qualification system should be established to facilitate agility and responsiveness of CBHE.

The findings are of value for policymakers, QA agencies and universities to advocate the new QA model for CBHE as a systematic approach in response to changing higher education landscape in the post-pandemic era.