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High power rotating machinery requires large diameter bearings that can perform under extreme conditions. Vibrations and critical speeds of rotor supported by tilting pad journal bearing (TPJBs) exceeding their design limits may cause unit failure. This paper aims to investigate the experimental technique for large diameter bearings.

To obtain the experimental support for rotor-bearing system design, an experiment focusing on vibration monitoring is given. The sensors arrangement, monitoring system and critical speed identification method are provided.

By using test bench in factory unit, a large amount of vibrations data of different working situations is obtained. In addition, a method named non-excitation identification for critical speed is proposed. The critical speed of rotor identified through vibration data is given. The theoretical calculation results are also presented.

The basis for rotor-bearing system design can be obtained through comparisons between the experimental results and the theoretical calculation data.

The government plays an important role in the financing process of small and medium enterprises (SMEs), but the current government-enterprise cooperation (GEC) mechanism cannot well solve the financing problem of SMEs. In addition, since government-enterprise cooperation is a long-term dynamic process, this study aims to explore the cooperation strategy between the government and core enterprises in supply chain finance (SCF) under the dynamic structure.

Considering both parties have the characteristics of disappointment aversion, our research constructs a game theory model of government subsidy and the effort of the enterprise to implement SCF based on differential game and studies different game strategies in the non-cooperative game, the Stackelberg game and the cooperative game.

Our findings show that the government subsidy can significantly spur the enterprise in the supply chain to implement SCF. We also find that the limitation of the government subsidy exists. In addition, the optimal strategy, the optimal benefit and the total benefit of the financing system formed by the government and the enterprise in the cooperative game are better than those in the non-cooperative game. Pareto optimality is achieved.

The limitations of this paper are: (1) In theory, this paper only takes the government and enterprise as game subjects without considering other participants in the supply chain. In addition, only disappointment aversion is taken into consideration while in reality the participants often exhibit multiple behavior preferences. (2) In methodology, only the numerical solution is given through the solution algorithm and all parameters are assumed to be determined as time changes for the convenience of calculation.

The government can motivate enterprises in the supply chain to implement SCF by providing subsidies. However, it should be noted that excessive subsidy will make the enterprise dependent on the government and as a result, decrease the effort level to implement SCF. Thus, it is necessary for the government to keep track of the business conditions of the enterprise to make a subsidy strategy. In addition, the government can reduce the impact of disappointing aversion by making more targeted policies and taking risk management measures.

On one hand, it is necessary for the government to keep track of the business conditions of the enterprise to make a subsidy strategy. In addition, the government can reduce the impact of their own disappointing aversion by making more targeted policies and adopting risk management measures. On the other, it is important for the enterprise to improve the regulatory mechanism and optimize the compensation structure of decision-makers to inhibit the impact of decision-makers' disappointing aversion.

This study is the first to investigate the mechanism of GEC in the setting of SCF based on a differential game. Furthermore, our study provides a theoretical basis for the government and enterprises to cooperate in SCF.

The paper attempts to design an efficient algorithm for bearing track correlation of multi‐sensor on the same platform using grey incidence analysis which is on the basis of the line segment Hausdorff distance.

Starting from the line segment, Hausdorff distance that has been extended to calculate the distance between line segment sets by many scholars has been used for face recognition achieving good results. The degree of grey incidence is defined based on the above distance and properties which include normality, symmetry and closeness, are proved. Furthermore, a grey incidence matrix is built. With only the azimuth information detected by bearing sensors track correlation is difficult to judge, however grey incidence analysis can quickly and accurately determine whether two tracks are from the same target, and so an algorithm is designed to solve this dilemma. In the last part of the paper simulation experiment is conducted.

The results are convincing: not only the algorithm proposed in the paper can solve the problem of track correlation of bearing‐only sensors, but also the algorithm can judge the correlation degree of both tracks even in the case of intensive targets.

The method exposed in the paper can be used to judge correlation degree of tracks detected by different sensors even for less information, and also be used to determine the similarity of two waveforms in the field of engineering.

The paper succeeds in introducing the line segment Hausdorff distance into grey incidence analysis and on the basis of that an algorithm is designed to solve the problem of track correlation.

Due to the non-linear nature of the hysteresis behavior, the accurate identification of the parameters of the Bouc–Wen hysteresis model is still a challenging problem. The purpose of this paper is to explore the potential of a heuristic improved whale optimization algorithm (IWOA) to accurately identify the model parameters, which has never been applied to the field of piezoelectric hysteresis identification.

Based on the analysis of the Bouc–Wen model structure and WOA optimization process, an approach that can fully exploit the potential of WOA is proposed. In this work, the position updating formula is improved by introducing non-linear weights, and the convergence factor formula is modified. And thus, the iteration speed, accuracy and stability of the classical WOA can be improved.

The experimental results show that the model output is in good agreement with the response of the real piezoelectric platform. Compared with the standard WOA and particle swarm optimization algorithms, the search performance of the proposed IWOA is better than those two competitors in terms of convergence speed and identification accuracy.

An IWOA is proposed according to the properties of the Bouc–Wen model and piezoelectric hysteresis. It has been approved that the algorithm has a good prospect in the identification of piezoelectric hysteresis systems. Furthermore, this method is easy to implement and is a good candidate algorithm to identify Bouc–Wen model parameters.

This paper aims to automatically plan sequence for complex assembly products and improve assembly efficiency.

An assembly sequence planning system for workpieces (ASPW) based on deep reinforcement learning is proposed in this paper. However, there exist enormous challenges for using DRL to this problem due to the sparse reward and the lack of training environment. In this paper, a novel ASPW-DQN algorithm is proposed and a training platform is built to overcome these challenges.

The system can get a good decision-making result and a generalized model suitable for other assembly problems. The experiments conducted in Gazebo show good results and great potential of this approach.

The proposed ASPW-DQN unites the curriculum learning and parameter transfer, which can avoid the explosive growth of assembly relations and improve system efficiency. It is combined with realistic physics simulation engine Gazebo to provide required training environment. Additionally with the effect of deep neural networks, the result can be easily applied to other similar tasks.

With the development of social networking service and WeMedia, virtual brand community has become a typical platform of value co-creation and customers have become a core subject of value co-creation. The high proportion of negative members and even zombie members has become an obstacle to the sustainable development of many communities. Then, how to maintain and promote the sustainable development of virtual brand community? The purpose of this article is to examine how customers prefer community or brand.

This paper obtained data through an online questionnaire survey to test the proposed hypotheses of this study.

The findings of this study indicated that practical and social values not only promote customers to be loyal toward community but also drive customers to be loyal toward brand and their influence on community loyalty is greater than on brand loyalty, but entertainment value does not significantly affect community and brand loyalty. The effect of practical and social values on community loyalty is fully mediated by the effect of brand loyalty, and the effect of practical and social values on brand loyalty is fully mediated by the effect of community loyalty.

This research enriches the research study’s results of value co-creation theory and customer assets, thus providing a new perspective for research on customer loyalty.

In this study, a novel glutathione (GSH) surface molecular imprinting polymer (SMIP) was successfully prepared by using macroporous adsorption resins (MAR) as substrate, which could separate and purify GSH efficiently.

SMIP was synthesized by chloromethylated modified MAR (LX1180-Cl) as the substrate, N, N’-methylenebisacrylamide (NMBA) as a crosslinker, GSH as a template, acrylamide (AM) and N-vinylpyrrolidone (NVP) as functional monomers. The morphology and structure of the polymer were characterized by scanning electron microscope and Fourier transforms infrared spectroscopy.

The maximum adsorption capacity toward GSH was 39.0 mg/g and the separation decree had relation to L-cysteine (L-cys) was 4.2. The optimal operation conditions were studied in detail and the got as follows: the molar ratios of NMBA, AM, GSH and NVP, were 7.0, 0.8 and 0.5. The optimal time and temperature were 14 h and 40°C, respectively. The Langmuir and pseudo-first-order model were fitting these adsorption characteristics well.

GSH has a diversity of medicinal and bioactive functions, so the purpose of this study representing a method in separate and purify technology of GSH, which provided a way for the development of medicine.

This contribution provided a novel way to separate GSH from L-cys. Under the optimal conditions, the maximum adsorption capacity toward GSH was 39.0 mg/g and the separation decree had relation to L-cys was 4.2.

This study aims to explore the relationship between folk religious place-making and the development of urban public spaces and summarize its influence on community network construction and daily behavior to discover the authentic practices and role of folk faith culture in social space.

Taking Macau's Shi Gandang Temple and its belief culture as an example, on-site research, historical evidence and interviews were used to elaborate and analyze the processes of place-making, social functions, management mechanisms and folk culture to establish a new perception of folk religious place-making in contemporary urban spaces.

The article argues that the culture of folk beliefs profoundly influences urban spaces and the social management system of Macau and has a positive significance in building the local community and geopolitical relations. In addition, it suggests that the participation of folk religious places in local practices is important as key nodes and emotional hubs of local networks, reconciling conflicts between communities of different backgrounds and driving urban spaces toward diversity while forming a positive interaction and friendly cooperation between regional development and self-contained management mechanisms, governance models and cultural orientations.

This study takes an architectural and anthropological perspective of the impact of faith on urban spaces and local governance, using the Shi Gandang Temple in Macau as an example, to complement related studies.

The purpose of this study is to restore the spatial distribution of overseas remittance businesses in Shantou during the 1940s. It explores various socioeconomic factors that influenced the concentration of local remittance business investment in real estate. By reconstructing the spatial distribution of remittance business activities in Shantou, this study hopes to lay a foundation for further analysis of the business strategies of Chaoshan merchants.

This research draws on information from the published Swatow Guide, archival sources and cadastral maps to identify the location of remittance enterprises and the native place and overseas networks of property owners.

This study reveals that the spatial distribution of the remittance enterprises was determined by the native place origins of local property owners, and that the inflow of overseas Chinese capital contributed to real estate development in Shantou.

Despite the limited access to Chinese official archives, this paper manages to identify several building blocks and neighbors in Shantou for spatial analysis.

This study is the first attempt to use the geographical information system (GIS) method in Chinese urban history research and hopes to establish a larger historical database of Shantou as a sample for comparison.

This investigation advances the spatial study of urban history and overseas Chinese remittances in the maritime society of South China.

The paper aims to investigate the application of particle swarm optimisation and back propagation in weights optimisation and training of artificial neural networks within the mass appraisal industry and to compare the performance with standalone back propagation, genetic algorithm with back propagation and regression models.

The study utilised linear regression modelling before the semi-log and log-log models with a sample of 3,242 single-family dwellings. This was followed by the hybrid systems in the selection of optimal attribute weights and training of the artificial neural networks. Also, the standalone back propagation algorithm was used for the network training, and finally, the performance of each model was evaluated using accuracy test statistics.

The study found that combining particle swarm optimisation with back propagation in global and local search for attribute weights enhances the predictive accuracy of artificial neural networks. This also enhances transparency of the process, because it shows relative importance of attributes.

A robust assessment of the models’ predictive accuracy was inhibited by fewer accuracy test statistics found in the software. The research demonstrates the efficacy of combining two models in the assessment of property values.

This work demonstrated the practicability of combining particle swarm optimisation with back propagation algorithms in finding optimal weights and training of the artificial neural networks within the mass appraisal environment.