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The purpose of this paper is to study the parameter estimation problem of nonlinear multivariable output error moving average systems.

A partially coupled extended stochastic gradient algorithm is presented for nonlinear multivariable systems by using the decomposition technique.

The proposed algorithm can realize the coupled computation of the parameter estimates between subsystems.

This paper develops a coupled parameter estimation algorithm for nonlinear multivariable systems and directly estimates the system parameters without over-parameterization.

This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.

Firstly, a single-train trajectory optimization (STTO) model is constructed based on train dynamics and operating conditions. The train kinematics parameters, including acceleration, speed and time at each position, are calculated to predict the arrival times in the train timetable. A STTO algorithm is developed to optimize a single-train time-efficient driving strategy. Then, a TTR approach based on multi-train tracking optimization (TTR-MTTO) is proposed with mutual information. The constraints of temporary speed restriction (TSR) and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train. The multi-train trajectories at each position are optimized to generate a time-efficient train timetable.

The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF. The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay (TTD). As for the TSR scenario, the proposed TTR-MTTO can reduce TTD by 60.60% compared with the traditional TTR approach with dispatchers’ experience. Moreover, TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.

With the cooperative relationship and mutual information between train rescheduling and control, the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

The purpose of this study is to make a prediction of the R&D output of China from the perspective of R&D institutions and put forward a set of policy recommendations for further development of the science and technology in China.

In this paper, an improved discrete grey multivariable model is proposed, which takes both the interaction effects and the accumulative effects into account. As the current research on China's R&D activities is generally based on the perspective of universities or industrial enterprises above designated size while few studies put their focus on R&D institutions, this paper applies the proposed model to carry out an empirical analysis based on the data of China's R&D institutions from 2009 to 2019. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of the R&D output in China's R&D institutions is conducted into a future horizon from 2020 to 2023 by using the model.

The results indicate that China's R&D institutions have a good development trend and broad prospects, which is closely related to China's long-term investment in science and technology. Additionally, the R&D inputs of China possess obvious interaction effects and accumulative effects.

The paper considers the interaction effects and the accumulative effects of R&D inputs simultaneously and proposes an improved discrete grey multivariable model, which fills the gap in previous studies.

Studies problems related to modelling, control and monitoring of circulatory systems with an artificial heart. First, presents a pulsatile model of cardiovascular systems. This model has a well‐grounded physiological basis and includes several reflex control systems, such as baroreceptor feedback loops, and nonlinearities of vessel compliance, which are inherent in the body. In addition, develops a model of an artificial heart. Based on these models, proposes a pulse frequency modulated (PFM) control scheme for the circulatory systems with an artificial heart. This scheme enables us to regulate the blood pressure and volume of the circulatory systems properly. To monitor the behaviour of the circulatory systems with an artificial heart an observation scheme is finally presented, with which the blood pressure and stroke volumes of the circulatory system can be estimated by using only the measurements of the driving pressure of the artificial heart.

Enterprise social media (ESM) are frequently used in enterprises for daily operation. Although many researchers have attempted to understand the antecedents and consequences of ESM use, the integrated model, boundary conditions and mechanism of the impact of ESM use on performance are still unclear. This study fill this research gap by adopting a grounded theory approach to study how ESM use affects employee performance.

Choosing representative cases, the authors collected interview data and analyzed the data using open coding, axial coding and selective coding.

The results showed four main categories including ESM use, work efficiency, emotional maintenance and work performance, as well as 14 sub-categories. This paper also constructs a model of the impact of ESM use on work performance. In addition, results showed that ESM use affects employees' work performance through work efficiency and emotional maintenance, and frequency of use and individual characteristics may moderate this process.

This study’s results contribute to the existing ESM literature by finding the integrated model, boundary conditions and mechanism of the impact of ESM use on performance. The authors also contributed to the social media literature by finding 14 sub-categories and four main categories including ESM use, work efficiency, emotional maintenance and work performance. The conclusion of this paper provides guidance and reference for the use and management of internal social media in enterprises.

Denim, a common fade fabric, can present different degrees of fade under different washing conditions. The phenomenon is similar to the washing efficiency. This study aims to discuss the relationship between impact factors and washing efficiency as well as the color fastness.

JMP software was used to design different experiments and 40 experimental groups were obtained. Then Statistical Package for the Social Sciences was used to analyze the results about washing efficiency and chromatic aberration.

Results showed that washing temperature, washing time and rotation speed have an effect on color fastness after washing in turn. In a certain range, when washing temperature, washing time or rotation speed increases, color fastness gradually increases as well. These three washing parameters work on washing efficiency as well. After setting and analyzing the mathematical model, the R² between the three washing parameters and washing efficiency is 0.855 and the R² between the three washing parameters and the post-wash chromatic is 0.849. There is a correlation between “Washing Efficiency of Sebum RM (P)” and “Post-wash Chromatic aberration (Q)”.

Denim could be used in some tests in laboratories instead of sebum standard stain cloth.

This paper provides an indirect research and feasible method for exploring a new object instead of the standard pollution cloth in the test of related textile study in the future.

This paper explores what factors influence household textile washing behaviour and how these factors relate to greenhouse gas emissions during the textile use stage.

A questionnaire survey related to textile summer washing and care behavior was conducted among households in 16 administrative districts of Shanghai. This study used the modified Consumer Lifestyle Approach framework of the washing and care ecosystem. The research hypotheses were established by selecting related factors from four aspects: household demographic characteristics, economy and consumption characteristics, washing machines and detergents characteristics.

First, we have demonstrated how some course factors do not significantly affect greenhouse emissions. None of the demographics, detergent-related activities, economy and consumption constructs significantly affect greenhouse emissions. Second, we have identified that washing machine and related activities has a direct positive effect on GHG emissions. The washing machine is not only the de facto carrier of all washing activities but also the core of washing activities. Washing machine is crucial in reducing greenhouse emissions and adjusting consumer behaviors.

This paper conducts a study related to the washing and care behavior of households in Shanghai. The paper examines the factors influencing household washing behavior and the relationship between these factors and greenhouse gas emissions during the textile use phase.

With the continuous increase of users, resources and tags, social tagging systems gradually present the characteristics of “big data” such as large number, fast growth, complexity and unreliable quality, which greatly increases the complexity of recommendation. The contradiction between the efficiency and effectiveness of recommendation service in social tagging is increasingly becoming prominent. The purpose of this study is to incorporate topic optimization into collaborative filtering to enhance both the effectiveness and the efficiency of personalized recommendations for social tagging.

Combining the idea of optimization before service, this paper presents an approach that incorporates topic optimization into collaborative recommendations for social tagging. In the proposed approach, the recommendation process is divided into two phases of offline topic optimization and online recommendation service to achieve high-quality and efficient personalized recommendation services. In the offline phase, the tags' topic model is constructed and then used to optimize the latent preference of users and the latent affiliation of resources on topics.

Experimental evaluation shows that the proposed approach improves both precision and recall of recommendations, as well as enhances the efficiency of online recommendations compared with the three baseline approaches. The proposed topic optimization–incorporated collaborative recommendation approach can achieve the improvement of both effectiveness and efficiency for the recommendation in social tagging.

With the support of the proposed approach, personalized recommendation in social tagging with high quality and efficiency can be achieved.

The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) system.

The idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, respectively.

From the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA system.

Compared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input–output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.

The purpose of this paper is to find a theoretical reference to adjust the unsymmetrical arc shape and plasma flow of overlapping deposition in wire arc additive manufacturing (WAAM) and ensure the effect of the gas shielding and stable heat and mass transfer in deposition process. The multiphysical numerical simulation and physical experiment are used for validation.

In this study, welding torch tilt deposition and external parallel magnetic field–assisted deposition are presented to adjust the unsymmetrical arc shape and plasma flow of overlapping deposition, and a three-dimensional numerical model is developed to simulate the arc of torch tilt overlapping deposition and external parallel magnetic field–assisted overlapping deposition.

The comparison of simulated results indicate that the angle of welding torch tilt equal to 20° and the magnetic flux density of external transverse magnetic field equal to 0.001 Tesla are capable of balancing the electric arc and shielding gas effectively, respectively. The arc profiles captured by a high-speed camera match well with simulated results.

These studies of this paper can provide a theoretical basis and reference for the calibration and optimization of WAAM process parameters.