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This paper aims to analyze the key factors influencing the synchronization performance of distributed motion control system and to improve the synchronization performance for peripherals control of this system.

This paper deals with the software synchronization problems of distributed motion control system based on real-time Ethernet. First, combined with communication and control tasks, the key factors affecting synchronization performance of system are analyzed. Then, aiming at key factors and considering the synchronization of system bus, protocol conversion and task scheduling, a software synchronization method based on CANopen protocol and real-time Ethernet is proposed. Finally, the feasibility of this method is verified by establishing distributed motion control system and testing the synchronization performance of terminal control signals of slaves.

Based on this method, the results show that the synchronization accuracy for peripherals control of all slaves could be about 100 ns.

This research provides high-precision synchronization method, which could lay a foundation for the application of distributed motion control system in the field of assembly automation, such as multi-axis assembly robots control.

In distributed motion control system, many factors affect the synchronization performance. At present, there is no synchronization method that could comprehensively consider these factors. This paper not only analyzes the key factors influencing the synchronization performance of system but also proposes a synchronization method. Therefore, the method proposed in this paper has certain theoretical value and engineering significance.

Building on a small body of work, the authors' study aims to investigate some important antecedents of online review characteristics in the Chinese restaurant industry.

Using a data set of restaurant reviews collected from a most popular review platform in China, the authors conduct a series of analyses to examine the influence of travel experience and travel distance on travelers' review characteristics in terms of review rating and media richness. The moderating effect of restaurant price on the influence is also investigated.

Travelers with a longer travel distance and more travel experience tend to provide higher and lower online ratings, respectively, which can be explained by the construal level theory (CLT) and the expectation-confirmation theory (ECT), respectively. Furthermore, these strong feelings can then induce travelers to post enriched reviews with more pictures, more words and more affective words to release consumption tension. Besides, restaurant price can moderate these relationships.

Distinguished from most studies which mainly focus on the consequences of online review characteristics or antecedents of review helpfulness, the authors pay attention to the effects of travelers' individual differences in terms of travel distance and travel experience on travelers' online reviewing behavior. In addition to review rating, the authors also focus on media richness in terms of visual and textual information. The authors' research findings can benefit restaurant consumers and managers for their online word-of-mouth utilization and management.

The purpose of this study is to present a novel hybrid closed-loop control method together with its performance validation for the dexterous prosthetic hand.

The hybrid closed-loop control is composed of a high-level closed-loop control with the user in the closed loop and a low-level closed-loop control for the direct robot motion control. The authors construct the high-level control loop by using electromyography (EMG)-based human motion intent decoding and electrical stimulation (ES)-based sensory feedback. The human motion intent is decoded by a finite state machine, which can achieve both the patterned motion control and the proportional force control. The sensory feedback is in the form of transcutaneous electrical nerve stimulation (TENS) with spatial-frequency modulation. To suppress the TENS interfering noise, the authors propose biphasic TENS to concentrate the stimulation current and the variable step-size least mean square adaptive filter to cancel the noise. Eight subjects participated in the validation experiments, including pattern selection and egg grasping tasks, to investigate the feasibility of the hybrid closed-loop control in clinical use.

The proposed noise cancellation method largely reduces the ES noise artifacts in the EMG electrodes by 18.5 dB on average. Compared with the open-loop control, the proposed hybrid closed-loop control method significantly improves both the pattern selection efficiency and the egg grasping success rate, both in blind operating scenarios (improved by 1.86 s, p < 0.001, and 63.7 per cent, p < 0.001) or in common operating scenarios (improved by 0.49 s, p = 0.008, and 41.3 per cent, p < 0.001).

The proposed hybrid closed-loop control method can be implemented on a prosthetic hand to improve the operation efficiency and accuracy for fragile objects such as eggs.

The primary contribution is the proposal of the hybrid closed-loop control, the spatial-frequency modulation method for the sensory feedback and the noise cancellation method for the integrating of the myoelectric control and the ES-based sensory feedback.

This study aims to analyze the impact of the source of online word-of-mouth (WOM) on retail sales. Specifically, the authors focus on the relative impact of external and internal WOMs on book sales.

An empirical analysis is conducted with a panel data of sales and WOM for 87 books from Dangdang and Douban over a 14-day period based on two generalized least square regression models.

Results suggest that both internal WOM and external WOM have significant impact on product sales, and the impact of external WOM is relatively more significant.

WOM, especially the external WOM, plays an important role in consumers’ online purchase decisions.

This study is helpful for retailers to better understand the factors influencing the sales and thereby forecast the future sales more precisely. Besides, the research conclusion could also enlighten related decision makers to constantly improve technical platforms.

The paper aims to investigate tool wear mechanism and tool geometry optimization of drilling PCB fixture hole.

An experimental study was carried out to investigate the chip formation and tool wear mechanism of drilling PCB fixture holes. Two types of drill with different types of chip-split groove were used in this study. The performances of these two types of drill bots were evaluated by tool wear and the shapes of chips.

The chips of drilling fixture holes contain aluminum chips from the cover board, copper chips from the copper foil, discontinuous glass fiber and resin from the CFRP. Feed rate and drilling speed have a great influence on the chip morphology. Abrasive wear of the drill lip is the main reason of the fixture drill bit in drilling PCB, and micro-chipping is observed on the tool nose and chisel edge. The influence of distance between the chip-split groove and drill point center on the axial force and torque is not obvious.

In this paper, hole wall roughness and drilling temperature were not analyzed in the optimization of drilling parameters. The future research work should consider them.

This paper investigated the mechanism of burr formation and tool wear in drilling of PCB fixture holes. Tool geometry was optimized by adding chip-split grooves.

This paper aims to study the tribological behavior of the WS2/oil-impregnated porous polyimide (PPI) solid/liquid composite system, in which both PFPE (perfluoropolyether) and SiCH (silahydrocarbons) oils with different hydrocarbon chains were used, respectively. Lubricating mechanism of the composite system was also explored.

The tribological behaviors of the WS2 films against the PPI cylindrical pins before and after immersing oil were evaluated under different loads by a reciprocating-type ball-on-disc tribometer.

The composite system exhibited the low and stable friction coefficient after the running-in stage, and the lubricant oil played a positive effect. It was found that the WS2/PFPE composite system exhibited more excellent lubricating property, although sole SiCH far exceeds PFPE in lubrication. The abnormal phenomenon mainly resulted from the influence of the oil amount. XRD results on the wear track surfaces indicated that PFPE and SiCH oils with different hydrocarbon chains were likely to preferentially adsorb to the edge plane and basal plane of the WS2 crystals, respectively.

In previous studies, liquid lubricants were directly dripped or spin-coated on the solid lubricant surface. Based on its potential advantage in application, the tribological behavior and mechanism of the solid lubricating film/oil-impregnated PPI composite system were investigated in this study.

The purpose of this paper is to present a five-fingered, multisensory prosthetic hand integrating both intuitive myoelectric control and sensory feedback.

The artificial hand’s palm has a three-arcuate configuration and the thumb can move along a cone surface, improving the resemblance with the biological hand. By using a coupling linkage mechanism, each finger is independently actuated by a direct current motor. Both torque and position sensors are embedded in the finger to sense the hand’s status and its interaction with the outer environment. The proposed human-in-the-loop control system consists of an internal motion control scheme and an external human–machine interface. The pattern recognition-based electromyography (EMG) control scheme is adopted to control the motion of the hand, and the transcutaneous electrical nerve stimulation (TENS) is utilized to feedback the hand’s sensory information to its user.

The hand prototype shows that it has an anthropomorphic appearance (85 per cent to an average human hand), low weight (420 g), great power (10 N on the fingertip) and eligible dexterity. Clinical evaluation of the prosthetic hand on transradial amputees also approves the hand design.

From a systematic view, the paper details the design concepts of the HIT–DLR prosthetic hand IV, especially on its appearance, mechanism, myoelectric control and sensory feedback.

With the increasing importance of e-commerce to the economy and people's lives, user-generated content, such as electronic word-of-mouth (eWOM) represented by online reviews, has exploded. On one hand, it is of great significance for review consumers (readers) to identify high-quality ones from a large number of existing reviews to assist their purchase decision. On the other hand, how to use appropriate strategies to make their published reviews more concerned by others is also important to review generators (reviewers). The purpose of this study is to understand the comprehensive relationship among review characteristics, review helpfulness and receiver attention.

This study uses the online movie reviews obtained from the most popular review platform in China to conduct multiple empirical analyses.

The results show that the review helpfulness plays a mediating role between the emotional characteristics of online reviews and the receiver attention, and such a mediating role is more significant among reviewers with rich review expertise. The reviewer's expertise also moderates the impact of review emotions on review helpfulness.

This work studies eWOM receiver involvement, which can ultimately impact product sales, but seldom be investigated in eWOM domain. Therefore, this research can enrich studies on eWOM and provide valuable practical implications as well.

The concept of entrepreneurship in platform enterprises has evolved and developed. The purpose of this paper is to explore how entrepreneurship in platform enterprises can be transformed into the sustainable innovation capability of enterprises based on knowledge integration.

This study adopts a questionnaire survey. The research samples are mainly from well-known domestic platform enterprises, EMBA students and professional online websites, 389 valid questionnaires were collected.

The results show that entrepreneurship has a positive impact on the sustainable innovation capability of platform enterprises, knowledge integration plays a partial mediating role between entrepreneurship and sustainable innovation capability of platform enterprises. Shared leadership plays a moderating role between entrepreneurship and knowledge integration and knowledge-sharing atmosphere plays a moderating role between knowledge integration and sustainable innovation capability of platform enterprises.

This paper emphasizes the key role of entrepreneurship in platform enterprises on the sustainable innovation capability and discusses the realization path of the sustainable innovation capability of platform enterprises from the perspective of knowledge integration, which is of great significance for developing the research system of entrepreneurship and promoting the construction of sustainable innovation capability of platform enterprises.

This study aims to propose a novel method based on model learning with sparsity inducing norms for estimating dynamic gravity terms of the serial manipulators. This method is realized by operating the robot, acquiring data and filtering the features in signal acquisition to adapt to the dynamic gravity parameters.

The core principle of the method is to analyze the dictionary composition of the basis function of the model based on the dynamic equation and the Jacobian matrix of an arm. According to the structure of the basis function and the sparsity of the features, combined with joint-angle and driving-torque data acquisition, the effective features of dynamic gravity parameters are screened out using L1-norm optimization and learning algorithms.

The theoretical analysis revealed that training data obtained based on joint angles and driving torques could rapidly update dynamic gravity parameters. The simulation experiment was carried out by using the publicly available robot model and compared with the previous disassembly method to evaluate the feasibility and performance. The real 7-degree of freedom (DOF) industrial manipulator was used to further discuss the effects of the feature selection. The results show that this estimation method can be fully operational and efficient in industrial applications.

This approach is applicable to most serial robots with multi-DOF and the dynamic gravity parameters of the robot are estimated through learning and optimization. The method does not require prior knowledge of the robot arm structure and only requires joint-angle and driving-torque data acquisition under low-speed motion. Furthermore, as it is a data-driven-based method, it can be applied to gravity parameters updating.

Different from previous general robot dynamic modelling methods, the sparsity of the analytical form of dynamic equations was exploited and model learning was formulated as a convex optimization problem to achieve effective gravity parameters screening. The novelty of this estimation approach is that the method does not only require any prior knowledge but also does not require a specifically designed trajectory. Thus, this method can avoid the laborious work of parameter calibration and the induced modelling errors. By using a data-driven learning approach, the new parameter updating process can be completed conveniently when the robot carries additional mass or the end-effector changes for different tasks.