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The purpose of this paper is to study the influence of pivot stiffness on the dynamic characteristics of tilting-pad journal bearings (TPJBs) and the stability of the bearing-rotor system.

A theoretical numerical model is established, and the influences of pivot stiffness on TPJBs and a bearing-rotor system are analyzed. Then, two kinds of pivot structures with different stiffness are designed and the vibration characteristics are tested on the vertical rotor bearing test bench.

The pivot stiffness has an obvious effect on the dynamic characteristics of the TPJBs and the stability of the bearing-rotor system. As a result of appropriate pivot stiffness, the critical speed and the vibration amplification factor can be reduced, the logarithmic decay rate and the stability of the rotor system can be effectively increased. While the journal whirl orbit is smoother and the rubbing is obviously reduced when the bearings have flexible pivots.

The influence of pivot stiffness on TPJBs and a vertical rotor-bearing system is studied by theoretical and experimental methods.

This study aims to determine the influence of social networking Twitter library on the level of utilization of college libraries.

The method used to explore this problem is explanative as it uses the multiple linear regression test. The research location is at Universitas Airlangga Library, Surabaya, Indonesia. The sampling technique was purposive, as it used the criteria of the academic community of Airlangga University that became an active member or often visited the homepage of the library’s Twitter account at least three times in the past one month. The sample of this study was 220 respondents.

The results of this study illustrate that the satisfaction of users of social networking Twitter library which includes surveillance, diversion/entertainment, personal identity and social relationship, either partially or simultaneously, affects the utilization of the college library.

Based on these results, libraries should always provide services in accordance with the characteristics of user behavior. In the era of booming social media Twitter for teenagers who are the largest users of college libraries, the use of social networking medium Twitter is considered effective in the libraries of universities.

The purpose of this paper is to cluster and analyse the level of agricultural science and technology in China’s provinces by using grey clustering model, to have an overall understanding of the current situation of agricultural science and technology development in these provinces, and to offer a reference for decision-making departments to draw up agricultural science and technology development plans.

First of all, the grey clustering assessment is used to evaluate the clustering of agricultural science and technology level in China’s provinces in 2011, 2013 and 2015. Also a comparative static analysis is made. Then, based on the prediction data of GM (1,1) model, the provincial agricultural science and technology levels in 2017 and 2019 are analysed by grey clustering. Finally, some suggestions are put forward, such as adjusting the allocation of agricultural science and technology resources and providing policy preferences to backward areas, so as to promote the coordinated development of agricultural science and technology in China.

The development of agricultural science and technology in various provinces and regions of the authors’ country is unbalanced, with a big gap of agricultural and technology level between different provinces. What’s more, the level of agricultural science and technology in remote areas has been developing slowly, but it has been lagging behind. Through the grey clustering analysis of the provincial agricultural science and technology level in 2017 and 2019, it is concluded that the level of agricultural science and technology will be promoted as a whole, but the gap of agricultural science and technology level between different provinces and cities will be enlarged.

This paper comprehensively studies the current situation and future development trends of agricultural science and technology in China’s provinces in recent years, and preliminarily analyses the reasons for the transformation of agricultural science and technology level, however, with no further inspection. Related research should be made for further study.

This paper will provide overall understanding of the current situation of agricultural science and technology development in China’s provinces and cities, and put forward relevant suggestions for the future development of agricultural science and technology in China’s provinces and cities, and provide references for decision-making departments to draw up agricultural science and technology development plans.

For the first time, the grey clustering method is used to the research of agricultural science and technology level in the province. It analyses and evaluates the past and present situation and predicts the future development trend of provincial agricultural science and technology level by the grey clustering analysis method, which is a complete research.

The purpose of this study was to identify the status of using crowdsourcing to develop information services through the Twitter platform and to determine the factors affecting such usage.

A qualitative action research approach was employed to achieve the objectives of the study and to provide answers to the research questions. The effectiveness of using crowdsourcing technique for improving information services has been explored through five procedural stages: diagnostics, action planning, action taking, evaluation and determined learning. Three tools were used to collect data: open interviews, content analysis of the sampled accounts on Twitter and users' perceptions regarding information services.

The results of the study revealed that crowdsourcing was not used in the development of information services per se, but it has been used for other purposes. The results also revealed that several factors influenced the adoption of using crowdsourcing to develop information services, including factors related to the institutional trust in crowds' capabilities, the nature of service and type of the needed development, and finally, the platform used to conduct crowdsourcing. The results of the action research proved that using crowdsourcing to develop information services could be effective.

The study suggests a model that can be used to test changes implemented in organizations, especially regarding adoption of crowdsourcing as a framework to achieve the objectives of the institution, particularly in the planning processes.

This research paper produces new knowledge through using a qualitative action research approach to understand the potential of social media in crowdsourcing. There have been no similar studies conducted in the region for the specified research design. The results add to the level of learning and raise awareness within the research community regarding the effectiveness of using crowdsourcing via social media platforms to improve the efficiency of information services.

An appropriate equivalent model is the key to the effective analysis of the system and structure in which permanent magnet takes part. At present, there are several equivalent models for calculating the interacting magnetic force between permanent magnets including magnetizing current, magnetic charge and magnetic dipole–dipole model. How to choose the most appropriate and efficient model still needs further discussion.

This paper chooses cuboid, cylindrical and spherical permanent magnets as calculating objects to investigate the detailed calculation procedures based on three equivalent models, magnetizing current, magnetic charge and magnetic dipole–dipole model. By comparing the accuracies of those models with experiment measurement, the applicability of three equivalent models for describing permanent magnets with different shapes is analyzed.

Similar calculation accuracies of the equivalent magnetizing current model and magnetic charge model are verified by comparison between simulation and experiment results. However, the magnetic dipole–dipole model can only accurately calculate for spherical magnet instead of other nonellipsoid magnets, because dipole model cannot describe the specific characteristics of magnet's shape, only sphere can be treated as the topological form of a dipole, namely a filled dot.

This work provides reference basis for choosing a proper model to calculate magnetic force in the design of electromechanical structures with permanent magnets. The applicability of different equivalent models describing permanent magnets with different shapes is discussed and the equivalence between the models is also analyzed.

With the increasing awareness of global warming and the important role of last mile distribution in logistics activities, the purpose of this paper is to build an environmental and effective last mile distribution model considering fuel consumption and greenhouse gas emission, vehicle capacity and two practical delivery service options: home delivery (HD) and pickup site service (PS). This paper calls the problem as the capacitated pollution-routing problem with pickup and delivery (CPRPPD). The goal is to find an optimal route to minimize operational and environmental costs, as well as a set of optimal speeds over each arc, while respecting capacity constraints of vehicles and pickup sites.

To solve this problem, this research proposes a two-phase heuristic algorithm by combining a hybrid ant colony optimization (HACO) in the first stage and a multiple population genetic algorithm in the second stage. First, the HACO is presented to find the minimal route solution and reduce distribution cost based on optimizing the speed over each arc.

To verify the proposed CPRPPD model and algorithm, a real-world instance is conducted. Comparing with the scenario including HD service only, the scenario including both HD and PS option is more economical, which indicates that the CPRPPD model is more efficient. Besides, the results of speed optimization are significantly better than before.

The developed CPRPPD model not only minimizes delivery time and reduces the total emission cost, but also helps logistics enterprises to establish a more complete distribution system and increases customer satisfaction. The model and algorithm of this paper provide optimal support for the actual distribution activities of logistics enterprises in low-carbon environment, and also provide reference for the government to formulate energy-saving and emission reduction policies.

This paper provides a great space for the improvement of carbon emissions in the last mile distribution. The results show that the distribution arrangement including HD and PS services in the last mile adopting speed optimization can significantly reduce the carbon emission. Additionally, an integrated real-world instance is applied in this paper to illustrate the validity of the model and the effectiveness of this method.

The paper formulates a bi-objective mixed-integer nonlinear programming model, aimed at minimizing the total labor hours and the workload unfairness for the multi-skilled worker assignment problem in Seru production system (SPS).

Three approaches, namely epsilon-constraint method, non-dominated sorting genetic algorithm 2 (NSGA-II) and improved strength Pareto evolutionary algorithm (SPEA2), are designed for solving the problem.

Numerous experiments are performed to assess the applicability of the proposed model and evaluate the performance of algorithms. The merged Pareto-fronts obtained from both NSGA-II and SPEA2 were proposed as final solutions to provide useful information for decision-makers.

SPS has the flexibility to respond to the changing demand for small amount production of multiple varieties products. Assigning cross-trained workers to obtain flexibility has emerged as a major concern for the implementation of SPS. Most enterprises focus solely on measures of production efficiency, such as minimizing the total throughput time. Solutions based on optimizing efficiency measures alone can be unacceptable by workers who have high proficiency levels when they are achieved at the expense of the workers taking more workload. Therefore, study the tradeoff between production efficiency and fairness in the multi-skilled worker assignment problem is very important for SPS.

The study investigates a new mixed-integer programming model to optimize worker-to-seru assignment, batch-to-seru assignment and task-to-worker assignment in SPS. In order to solve the proposed problem, three problem-specific solution approaches are proposed.

This paper aims to develop a dynamic two-sided stable matching method based on preference information of the matching objects in uncertain environments, so as to solve the matching problem of cloud manufacturing tasks and services with load balancing.

For dynamic two-sided matching, due to the complexity of social environment and the limitation of human cognition, hesitation and fuzziness always exist in the process of multi-criteria assessment. First, in order to obtain the accurate preference information of each matching object, uncertain linguistic variables, uncertain preference ordinal and incomplete complementary matrices are used to evaluate multi-criteria preference information. This process is undertaken by considering the probability of each possible matching pair. Second, the preference information at different times is integrated by using the time-series weight to obtain the comprehensive satisfaction degree matrices of the matching objects. Further, the load adjustment parameter is used to increase the satisfaction degree of the matching objects. Afterward, a dynamic two-sided stable matching optimization model is constructed by considering stable matching conditions. The model aims to maximize the satisfaction degree and minimizes the difference in the satisfaction degree of matching objects. The optimal stable matching results can be obtained by solving the optimization model. Finally, a numerical example and comparative analysis are presented to demonstrate the characteristics of the proposed method.

Uncertain linguistic variables, uncertain preference orders and incomplete complementary matrices are used to describe multi-criteria preference information of the matching objects in uncertain environments. A dynamic two-sided stable matching method is proposed, based on which a DTSMDM (dynamic two-sided matching decision-making) model of cloud manufacturing with load balancing can be constructed. The study proved that the authors can use the proposed method to obtain stable matching pairs and higher matching objective value through comparative analysis and the sensitivity analysis.

A new method for the two-sided matching decision-making problem of cloud manufacturing with load balancing is proposed in this paper, which allows the matching objects to elicit language evaluation under uncertain environment more flexibly to implement dynamic two-sided matching based on preference information at different times. This method is suitable for dealing with a variety of TSMDM (two-sided matching decision-making) problems.

The purpose of this paper is to propose a valid and quantitative measurement method of knowledge diffusion efficiency for the knowledge collaboration networks (KCNs).

This paper builds a weighted KCN model with the node and edge weights. Based on the weighted KCN, the factors of knowledge diffusion efficiency are proposed and analyzed. Then, the knowledge transfer effect between two nodes is proposed and measured by comprehensively integrating the above factors. Furthermore, the main metric of efficiency of knowledge diffusion is proposed by modifying Latora and Marchiori’s model of efficiency of network.

A case is studied to illustrate the applicability of the proposed weighted network model and the knowledge diffusion efficiency measurement method. The results show the methods proposed in this paper can better measure and analyze the knowledge diffusion efficiency of KCNs than the traditional un-weighted methods and the subjective evaluation methods.

The real KCNs are always weighted networks. The weighted model of KCN can better reflect the real networks than the un-weighted model. Based on the weighted networks, the measurement methods proposed in this paper can more efficiently and accurately measure and evaluate the knowledge diffusion efficiency than the traditional methods. This study can help researchers to better understand knowledge diffusion theoretically, and provide managers with a decision support for knowledge management in practice.

The purpose of this paper is to propose an extended Kalman particle filter (EPF) approach for dynamic state estimation of synchronous machine using the phasor measurement unit’s measurements.

EPF combines the extended Kalman filter (EKF) with the particle filter (PF) to accurately estimate the dynamic states of synchronous machine. EKF is used to make particles of PF transfer to the likelihood distribution from the previous distribution. Therefore, the sample impoverishment in the implementation of PF is able to be avoided.

The proposed method is capable of estimating the dynamic states of synchronous machine with high accuracy. The real-time capability of this method is also acceptable.

The effectiveness of the proposed approach is tested on IEEE 30-bus system.

Introducing EKF into PF, EPF is proposed to estimate the dynamic states of synchronous machine. The accuracy of a dynamic state estimation is increased.