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As the demand for human–robot collaboration in manufacturing applications grows, the necessity for collision detection functions in robots becomes increasingly paramount for safety. Hence, this paper aims to improve the existing method to achieve efficient, accurate and sensitive robot collision detection.

The external torque is estimated by momentum observers based on the robot dynamics model. Because the state of the joints is more accessible to distinguish under the action of the suppression operator proposed in this paper, the mutated external torque caused by joint reversal can be accurately attenuated. Finally, time series analysis (TSA) methods can continuously generate dynamic thresholds based on external torques.

Compared with the collision detection method based only on TSA, the invalid time of the proposed method is less during joint reversal. Although the soft-collision detection accuracy of this method is lower than that of the symmetric threshold method, it is superior in terms of detection delay and has a higher hard-collision detection accuracy.

Owing to the mutated external torque caused by joint reversal, which seriously affects the stability of time series models, the collision detection method based only on TSA cannot detect continuously. The consequences are disastrous if the robot collides with people or the environment during joint reversal. After multiple experimental verifications, the proposed method still exhibits detection capabilities during joint reversal and can implement real-time collision detection. Therefore, it is suitable for various engineering applications.

The salinity of the oilfield produced water has a significant effect on steel corrosion. The purpose of this paper is to study the influence of salinity on corrosion behavior of X60 steel and it also provides basic for material selection of gas wells with high salinity.

The weight loss experiment was carried out on steel with high temperature and high pressure autoclave. The surface morphology and composition of corrosion scales were studied by means of scanning electron microscopy, energy dispersive spectroscopy and X-ray diffractometry.

The results show that as salinity increases, the corrosion rate of X60 steel will gradually experience a rapid decline stage and then a slow decline stage. X60 steel is mainly exhibiting uniform corrosion in the first rapid decline stage and pitting corrosion in the second slow decline stage. The increase in salinity reduces gas solubility, which, in turn, changes the morphology and density of the corrosion scales of X60 steel. At low salinity, loose iron oxides generated on the surface of the steel, which poorly protects the substrate. At high salinity, surface of the steel gradually forms protective films. Chloride ions in the saline solution mainly affect the structure of the corrosion scales and initiate pitting corrosion. The increased chloride ions lead to more pitting pits on the surface of steel. The recrystallization of FeCO₃ in pitting pits causes the corrosion scales to bulge.

The investigation determined the critical concentration of pitting corrosion and uniform corrosion of X60 steel, and the new corrosion mechanism model was presented.

The motion picture industry is a cultural and creative industry. Unlike its US counterpart, the Chinese motion picture industry is still developing. Therefore, learning from the US market, the purpose of this paper is to analyze the business model of Chinese movies from the perspective of new product diffusion.

Based on 66 movies released in the US and 21 movies released in China, this paper first compares the diffusion curves of Chinese and US movies through the movie life cycle and box office trends. Next, it analyzes the moviegoing behaviors of Chinese and US audiences based on the innovation and imitation coefficients in the Bass model. Finally, it compares the attention to information of Chinese and US audiences from the perspective of interpersonal word-of-mouth (WOM).

In the USA, a movie’s highest weekly box office is usually in its opening week, followed by a weekly decline in revenue; in China, there is no difference in box office performance between the first two weeks, but a weekly decline in revenue similarly follows. US audiences pay more attention to advertisements for movies than WOM recommendations, while Chinese people pay more attention to WOM recommendations. Neither the Chinese nor the US market differs in the volume of WOM between the first week before release and the opening week, and these two weeks are the most active period of WOM in both markets.

During the production phase for Chinese movies, we should satisfy opinion leaders’ needs. During the distribution phase, we should not only focus on market spending before the movie’s release, but also increase market spending in the opening week. During the theater release phase, we should stimulate WOM communication between moviegoers and thereby attract many more opinion seekers.

Few studies have investigated the Chinese motion picture industry from the perspective of new products. This paper compares and analyzes the diffusion of Chinese and US movies using the Bass model of new product diffusion, providing systematic theoretical guidelines for the commercial operation of the Chinese motion picture industry.

This study aims to predict the construction cost in China, the authors purposed a fused method.

The authors extracted 22 factors which may influence the cost and performed the correlation analysis with cost. They chose the highest 10 factors to predict cost by the fused method. The method fused the Kalman filter with least squares support vector machine and multiple linear regression.

Ten factors which affect the cost most were found. The construction cost in China can be predicted by the presented method precisely. The statistical filter method could be used in the field of construction cost prediction.

The construction cost and construction interior factors are a business secret in China. So, the authors only collected 24 buildings’ data to perform the experiments.

There is no standard and precise method to predict construction cost in China, so the presented method offers a new way to judge the feasibility of projects and select design schemes of construction.

The authors purposed a new fused method to predict construction cost. It is the first time that the statistical filtering method was used in this field. The effectiveness was verified by the experiments. Ten factors which have a high relationship with construction cost were found.

The purpose of this paper is to discuss the role of reference effect on newsvendor’s decision behavior in a market with strategic customers and work out the newsvendor’s optimal pricing policy and ordering quantity.

This study utilizes the prospect theory and strategic customer framework to analyze the decision-making behavior on the newsvendor’s optimal pricing policy and ordering quantity. The paper further presents an extension of newsvendor model and provides the model’s properties. The paper finally analyzes the results with various parameters on the model and reports on the insights generated by the model.

The paper indicates that the ordering quantity is not altered with the changing proportion of strategic customers and myopic customers, but the ordering quantity and the pricing strategy are influenced in terms of newsvendor’s reference effect, loss aversion, product cost, and salvage price.

The research findings have important implications for decision makers. Previous researches have studied the incomplete rationality newsvendor’s decision-making behavior mainly by analyzing the vendor’s risk preferences or loss aversion, but the effect of reference point also plays an important role in analyzing the decision-maker’s behavior. The paper provides the optimal pricing policy and ordering quantity with the reference effect considering the strategic customers behavior. This model is also a valid complementarity to behavioral operations management research area.

The paper examines the role of reference effect in newsvendor problem with the strategic customers and analyzes the impact of parameters such as loss aversion on the newsvendor’s decision behavior.

Understanding customer behavior from the perspective of channel integration has become a major stream of research in multi-channel retailing literature. Yet, despite recent advancements in scholarship, how retailers can most effectively sustain customers in online retailing remains unclear. Scholars have suggested online–offline channel integration (OOCI) as an effective multi-channel approach for increasing online loyalty; yet, few studies have explored OOCI's influencing mechanism. This study addresses that gap by investigating how OOCI helps achieve customer loyalty online and further examines the moderating role of retailer credibility in the influencing mechanism of OOCI.

The research model driving this study draws upon the stimulus-organism-response (S-O-R) model and cue consistency theory. The authors collected a sample of 259 customers in China with experience making multi-channel purchases from retailers that have implemented OOCI in online retailing. Structural equation modeling and response surface analyses were employed to conduct data analysis.

The results revealed that the relationship between OOCI and customers' online channel loyalty was mediated by customers' perceptions of the usefulness and risks of online channel usage. The results also found that congruence and incongruence between informational OOCI (IOOCI) and fulfillment OOCI (FOOCI) had different curvilinear associations with perceived online channel usefulness and perceived online channel risk. In addition, retailer credibility weakened the effects of IOOCI on perceived online channel usefulness and FOOCI on perceived online channel risk but strengthened the effect of IOOCI on perceived online channel risk and had no impact on the effect of FOOCI on perceived online channel risk.

Theoretical and practical implications of this study are also discussed.

This paper aims to solve the problem of free-form tubes’ machining errors which are caused by their complex geometries and material properties.

In this paper, the authors propose a multi-view vision-based method for measuring free-form tubes. The authors apply photogrammetry theory to construct the initial model and then optimize the model using an energy function. The energy function is based on the features of the image of the tube. Solving the energy function allows to use the gray features of the images to reconstruct centerline point clouds and thus obtain the pertinent geometric parameters.

According to the experiments, the measurement process takes less than 2 min and the precision of the proposed system is 0.2 mm. The authors used simple operations to carry out the measurements, and the process is fully automatic.

This paper proposes a method for measuring free-form tubes based on multi-view vision, which has not been attempted to the best of authors’ knowledge. This method differs from traditional multi-view vision measurement methods, because it does not rely on the data of the design model of the tube. The application of the energy function also avoids the problem of matching corresponding points and thus simplifying the calculation and improving its stability.

In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping.

This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target.

In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained.

The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.

Self-organization has been regarded as a tool for the synthesis of well-defined organic nanostructures. Heterocyclic annulated perylene diimides are the subjects of considerable current research studies. The purpose of this study is to reveal the photophysical property, electronic structure and solid-state packing of O-heterocyclic annulated perylene diimide.

Asymmetrically five-membered O-heterocyclic annulated perylene diimide (OAPDI) was synthesized. Structure and purity of OAPDI were confirmed by ¹H NMR, ¹³C NMR, IR and mass spectral techniques. Photophysical properties of OAPDI were studied using UV–vis absorption and fluorescence in both solution (CHCl₃) and solid state. Scanning electron microscopic and atomic force microscopy were used to characterize the surface morphology of OAPDI. Conducting properties of the OAPDI were evaluated by current–voltage measurements. The compounds geometries were also optimized at 6-31G* using density functional theory.

The UV–vis absorption and fluorescence spectra of OAPDI in solution are blue-shifted in comparison with that of unsubstituted perylene bisimide. Solid-state UV–vis measurements of OAPDI indicate that it is capable of forming highly ordered structure. The non-covalent interactions, electrostatic attraction and p-p stacking moieties of OAPDI synergistically guide assembly and domain growth while maintaining the interpenetrating network of nanofibers in the solid film. The OAPDI gave higher current at −2.0 V (0.68 µA) and 4.0 V (1.0 µA).

This study will be helpful for exploring feasible routes to acquire soluble perylene diimides and well-defined organic nanostructures. Furthermore, such molecular tailoring approach would be helpful for designing and synthesizing novel organic semiconductive materials with excellent charge-transporting and light-emitting capabilities.

The purpose of this paper is to propose an accurate and practical imitation learning for robotics. The modified dynamic movement primitives (DMPs), global fitting DMPs (GLDMPs), is presented. Framework design, theoretical derivation and stability proof of GLDMPs are discussed in the paper.

Based on the DMPs, the hierarchical iterative parameter adaptive framework is developed as the hierarchical iteration stage of the GLDMPs to tune the designed parameters adaptively to extract richer features. Inspired by spatial transformations, the coupling analytical module which can be regarded as a reversible transformation is proposed to analyze the high-dimensional coupling information and transfer it to trajectory.

With the proposed framework and module, DMPs derive majority features of the demonstration and cope with three-dimensional rotations. Moreover, GLDMPs achieve favorable performance without specialized knowledge. The modified method has been demonstrated to be stable and convergent through inference.

GLDMPs have an advantage in accuracy, adaptability and practicality for it is capable of adaptively computing parameters to extract richer features and handling variations in coupling information. With demonstration and simple parameter settings, GLDMPs can exhibit excellent and stable performance, accomplish learning and generalize in other regions. The proposed framework and module in the paper are useful for imitation learning in robotics and could be intuitive for similar imitation learning methods.