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This paper aims to solve the problem that the changing of groove size and assembly gap would affect the precision of the multi-pass path planning and the welding quality and realize the automatic welding of a thick plate.

First, a double-sided double arc welding (DSAW) system with a self-designed passive vision sensor was established, then the image of the groove was captured and the characteristic parameters of groove were extracted by image processing. According to the welding parameters and the extracted geometry size, multi-pass path planning was executed by the DSAW system.

A DSAW system with a self-designed passive vision sensor was established which can realize the welding thick plate by double-sided double arc by two robots. The clear welding image of the groove was acquired, and an available image processing algorithm was proposed to accurately extract the characteristic parameters of the groove. According to the welding parameters and the extracted geometry size, multi-pass path planning can be executed by the DSAW system automatically.

Gas metal arc welding is used for root welding and filler passes in DSAW. Multi-pass path planning for thick plate by Double-sided Double Arc Welding (DSAW) based on vision sensor was proposed.

The purpose of this study is to improve the thermal management of lithium-ion batteries. The phase change material (PCM) cooling does not require additional equipment to consume energy. To improve the heat dissipation capacity of batteries, fins are added in the PCM to enhance the heat transfer process.

Computational fluid dynamics method is used to study the influence of number of vertical fins and ring fins (i.e. 2, 4, 6 and 8 vertical fins, and 2, 3, 4 and 5 ring fins) and the combination of them on the cooling performance.

The battery maximum temperature can be decreased by the PCM with vertical or ring fins, and it can be further decreased by the combination of them. The PCM with eight vertical fins and five ring fins reduces the battery maximum temperature by 5.21 K. In addition, the temperature and liquid-phase distributions of the battery and PCM are affected by the design of the cooling system.

This work can provide guidelines for the development of new and efficient PCM cooling systems for lithium-ion batteries.

The combination of PCM and fins can be used to reduce the battery maximum temperature and temperature difference.

The purpose of this study is to design a new type of cold plate to improve the thermal performance of liquid-cooled thermal management system of lithium-ion batteries.

A cold plate with leaf type channels is proposed to enhance the cooling performance. Effects of the leaf type channel parameters (i.e. channel angle 20°, 40°, 60°, 80°; coolant mass flow rate 0.25 × 10^–3, 0.50 × 10^–3, 0.75 × 10^–3, 1.00 × 10^–3, 1.25 × 10^–3 kg·s⁻¹; channel number 1, 3, 5, 7) on the performance are numerically investigated by using a 3D mathematical model.

Compared to the traditional I type channels, the leaf type channels have better cooling performance. It is found that the battery temperature variation and channel pressure drop are decreased with decreasing channel angle and increasing channel number. In addition, the cooling performance can be improved by increasing the coolant mass flow rate.

This study can provide guidance for the development of novel effective cold plates.

The design of cold plates with leaf type channels can be used in liquid-cooled thermal management system to reduce the battery temperature difference.

A robotic wheelchair system was designed to assist disabled people with disabilities to walk.

An anticipated sharing control strategy based on topological map is proposed in this paper, which is used to assist robotic wheelchairs to realize interactive navigation. Then, a robotic wheelchair navigation control system based on the brain-computer interface and topological map was designed and implemented.

In the field of robotic wheelchairs, the problems of poor use, narrow application range and low humanization are still not improved.

In the system, the topological map construction is not restricted by the environment structure, which helps to expand the scope of application; the shared control system can predict the users’ intention and replace the users’ decision to realize human-machine interactive navigation, which has higher security, robustness and comfort.

Based on the framework of Krylov subspace-based model order reduction (MOR), compact models of the piezoelectric energy harvester devices can be generated. However, the stability of reduced piezoelectric model often cannot be preserved. In previous research studies, “MOR after Schur,” “Schur after MOR” and “multiphysics structure preserving MOR” methods have proven successful in obtaining stable reduced piezoelectric energy harvester models. Though the stability preservation of “MOR after Schur” and “Schur after MOR” methods has already been mathematically proven, the “multiphysics structure preserving MOR” method was not. This paper aims to provide the missing mathematical proof of “multiphysics structure preserving MOR.”

Piezoelectric energy harvesters can be represented by system of differential-algebraic equations obtained by the finite element method. According to the block structure of its system matrices, “MOR after Schur” and “Schur after MOR” both perform Schur complement transformations either before or after the MOR process. For the “multiphysics structure preserving MOR” method, the original block structure of the system matrices is preserved during MOR. 

This contribution shows that, in comparison to “MOR after Schur” and “Schur after MOR” methods, “multiphysics structure preserving MOR” method performs the Schur complement transformation implicitly, and therefore, stabilizes the reduced piezoelectric model.

The stability preservation of the reduced piezoelectric energy harvester model obtained through “multiphysics structure preserving MOR” method is proven mathematically and further validated by numerical experiments on two different piezoelectric energy harvester devices.

This study aims to examine how servitization affects the environmental and social performance of manufacturing firms.

The hypotheses are tested using fixed-effect panel models based on secondary data of 1,413 manufacturing firms publicly listed in the USA.

Results show that servitization is positively related to the social performance of manufacturing firms; this positive relationship is more prominent under high levels of human resource slack. However, the impact of servitization on environmental performance depends on the level of absorptive capacity and human resource slack. Servitization improves environmental performance under high levels of absorptive capacity and human resource slack, while this positive impact is insignificant under low levels of absorptive capacity and human resource slack.

The study focuses on the degree (depth) of servitization but ignores the scope of services provided by manufacturing firms (breadth of servitization).

This research suggests that servitization is an effective way of achieving simultaneous improvements in environmental and social performance. However, high levels of absorptive capacity and human resource slack are needed to achieve this goal.

This study contributes to the servitization literature by demonstrating the environmental and social sustainability benefits of servitization. The findings also highlight the crucial role of absorptive capacity and human resource slack on improving environmental and social performance through servitization.

This paper presents a comprehensive review of the available literature on applications of the rough set theory. Concepts of the rough set theory are discussed for approximation, dependence and reduction of attributes, decision tables and decision rules. The applications of rough sets are discussed in pattern recognition, information processing, business and finance, industry, environment engineering, medical diagnosis and medical data analysis, system fault diagnosis and monitoring and intelligent control systems. Development trends and future efforts are outlined. An extensive list of references is also provided to encourage interested readers to pursue further investigations.

This study explores how lesson study (LS) can promote elementary Science, Technology, Engineering, and Mathematics (STEM) teachers’ professional development (TPD) in terms of new pedagogical practices, attitudes and beliefs in the maker education (ME) context.

This is a case study of a LS conducted in China involving four primary school teachers, 20 grade-4 students, and one researcher who also acted as a facilitator. This study adopted an integrated model that combined the unique characteristics of Chinese LS (CLS) with the Dutch LS (LSNL) model.

This study revealed that LS participation facilitates teachers’ integration of new ME pedagogical practices in their classrooms, while their attitudes and beliefs regarding teaching and learning are increasingly aligned with ME principles. However, challenges such as time constraints, lack of research skills, and insufficient learning resources have also been identified.

This was a small-scale study, which may limit the generalizability of the findings.

This study expands the use of LS in the ME context by highlighting its effectiveness in enhancing teachers’ PD in terms of new pedagogical practices, attitudes, and beliefs. It also recommends incorporating diverse international LS models to address the limitations associated with localized models of TPD.

The originality of this study lies in its adoption of an integrated LS model to enhance STEM teachers’ PD in an ME context. The findings of this study further strengthen evidence supporting the positive impact of LS on teachers’ PD.

In 2016, the Chinese central government decentralized the responsibilities of housing market regulation to the municipal level. This paper aims to assess whether the decentralized market regulation is effective.

This study first investigates the fundamental drivers of urban housing prices in China. Taking into consideration the factors driving housing prices, the authors further investigate the effectiveness of decentralized housing market regulation by a pre- and post-policy comparison test using a panel data set of 35 major cities for the years from 2014 to 2019.

The results reveal heterogenous policy effects on housing price growth among cities with a one-year lag in effectiveness. With the decentralized housing market regulation, cities with fast price growth are incentivized to implement tightening measures, while cities with relatively low housing prices and slow price growth are more likely to do nothing or deregulate the markets. The findings indicate that the shift from a centralized housing market regulation to a decentralized one is more appropriate and effective for the individual cities.

Few policy evaluation studies have been done to examine the effects of decentralized housing market regulation on the performance of urban housing markets in China. The authors devise a methodology to conduct a policy evaluation that is important to inform public policy and decisions. This study helps enhance the understanding of the fundamental factors in China’s urban housing markets and the effectiveness of municipal government interventions.

The purpose of this paper is to present a new methodology for identification of the parameters of the local linear Takagi‐Sugeno fuzzy models using weighted recursive least squares. The weighted recursive least squares (WRLS) is sensitive to initialization which leads to no converge. In order to overcome this problem, Euclidean particle swarm optimization (EPSO) is employed to optimize the initial states of WRLS. Finally, validation results are given to demonstrate the effectiveness and accuracy of the proposed algorithm. A comparative study is presented. Validation results involving simulations of numerical examples and the liquid level process have demonstrated the practicality of the algorithm.

A new method for nonlinear system modelling. The proposed algorithm is employed to optimize the initial states of WRLS algorithm in two phases of learning algorithm.

The results obtained using this novel approach were comparable with other modeling approaches reported in the literature. The proposed algorithm is able to handle various types of modeling problems with high accuracy.

In this paper, a new method is employed to optimize the initial states of WRLS algorithm in two phases of the learning algorithm.