Motivating users’ civilized cycling plays a significant role in alleviating the troubles of dockless bike-sharing programs (DBSPs) and promoting the sustainable development of bike-sharing organizations. Based on the theory of planned behavior (TPB) and observed practices in China, this study develops a theoretical framework to examine how attitudes (ATT), subjective norms (SN), perceived behavioral control (PBC), and personal norms (PN) motivate users’ civilized cycling behavior through civilized cycling intentions. Furthermore, the moderating effect of perceived policy effectiveness (PPE) between users’ civilized cycling intention and their actual behavior is tested. Using structural equation model-multiple group analysis (SEM-MGA) for a sample of 874 valid questionnaire responses in Beijing and Shanghai, China, our results reveal that (1) ATT, PBC, and PN are positively related to both users’ civilized cycling intentions and their actual behavior, while SN positively affect users’ civilized cycling intention only; (2) users’ civilized cycling intentions mediate the relationship between the four influencing factors and their actual behavior; and (3) PPE plays a moderating role for the effect of users’ civilized cycling intentions on their actual civilized cycling behavior. Our results indicate that the four influencing factors can encourage users’ civilized cycling behavior, especially when civilized cycling intention exists. Policies like credit-based supervision mechanisms could promote users’ civilized-cycling intentions, which could then be transformed into actual behavior.

This paper presents a novel pressure-resistant oil-immersed proportional actuator with a magnetic grid magnetic-isolated ring (MGMR) on its single-piece sleeve. A two-dimensional finite element method is used to establish the model and analyze the static and dynamic performance. The experimental and simulation results agree well with each other and verify the static and dynamic performance characteristics of this proportional actuator. The results indicate that the actuator can produce 15 N force output when the ampere turns is 450AT in 2.2-mm wide working stroke; the rising step response time and the falling step response time are 24 and 17 ms, respectively, and the frequency response (−3dB) is 25 Hz. Consequently, its applications to electrohydraulic proportional/servo valve are acceptable.

Chlorine dosing is a complicated system with time delay, time-varying, non-linear and coupling. In this paper, multivariable adaptive generalized predictive controller based on Smith predictor is proposed. Instead of the optimal predictor, the Smith predictor with adaptive identifying parameters can increase the robustness of the MIMO system. Simulation and application in water-works at Suzhou (China) shows that the algorithm can overcome time-varying, time delay and disturbance.

During drinking water treatment, the chemical dosing processes, such as coagulant dosing process, ozone dosing process and chlorine dosing process are usually manually operated based on the operator knowledge and experience. However, due to the variations of water quality, water flow and process operational conditions and characteristics of large time-delay and nonlinear for the chemical dosing processes, it is difficult to adjust the chemical dosages in time by operators to keep the treated water quality stable, especially during the periods of rapid and frequent variations of water quality, water flow and process operational conditions. Thus, the improvements of control methods for the chemical dosing processes are essential to the operation of drinking water treatment plants. The Xiangcheng Water Treatment Plant in Suzhou, China has been utilizing the automatic control for chemical dosing processes since February 2012. Automatic controllers are designed respectively for the coagulant dosing process, ozone dosing process and chlorine dosing process. After the implementation of automatic control, operators are not necessary to keep constant attention. In addition, due to the improvements of control accuracies for the chemical dosing processes, the chemical dosages are reduced on the premise of ensuring safe water. Thus, both of the human resource costs and material costs can be saved. The practical control results demonstrate the efficiencies of proposed methods.

In order to overcome some disadvantages of LS-SVM, such as noise-sensitive and less sparsity, adaptive weighted p-norm LS-SVM is proposed. Experiments shows that different data, using a different regularization(p) can improve the accuracy of the regression, where 1<p<2. p-norm LS-SVM can be convented to the form of compressed sensing, then it can be solved using IRLS. For each sample, because they are not the same, weighted membership degree is introduced to the optimization function so that leading to less error. There are some parameters of weighted p-norm LS-SVM, genetic algorithm is introduced to obtain the optimal parameters. Case study shows that adaptive weighted p-norm LS-SVM is better than other SVM and good result is obtained.