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The purpose of this paper is to provide an accurate model and method to simulate the transient performances of an insulated gate bipolar transistor (IGBT) in an arbitrary free-carrier injection condition.

A numerical model and method for solving the physics-based model, an ambipolar diffusion equation-based model, of an IGBT is proposed.

The results of the proposed model are very close to the tested ones.

A mathematical model for an IGBT considering all free-carrier injection conditions is introduced, and a numerical solution methodology is proposed.

Navigating in off-road environments is a huge challenge for autonomous vehicles, due to the safety requirement, the effects of noises and non-holonomic constraints of vehicle. This paper aims to describe a path planning method based on fuzzy support vector machine (FSVM) and general regression neural network (GRNN) that is able to provide a solution path for the autonomous vehicle navigating in the off-road environments.

The authors decompose the path planning problem into three steps. In the first step, A* algorithm is applied to obtain the positive and negative samples. In the second step, the authors use a learning approach based on radial basis function kernel FSVM to maximize the safety margin for driving, and the fuzzy membership is designed based on GRNN which can help to resolve the problem that the traditional path planning method is easily influenced by noises or outliers. In the third step, the Bezier interpolation algorithm is used to smooth the path. The simulations are designed to verify the parameters of the path planning algorithm.

The method is implemented on autonomous vehicle and verified against many outdoor scenes. Road test indicates that the proposed method can produce a flexible, smooth and safe path with good anti-jamming performance.

This paper applied a new path planning method based on GRNN-FSVM for autonomous vehicle navigating in off-road environments. GRNN-FSVM can reduce the effects of outliers and maximize the safety margin for driving, the generated path is smooth and safe, while satisfying the constraint of vehicle kinematic.

The purpose of this paper is to find the key influence factors of executive compensation within China ports and listed shipping companies and provide some reasonable suggestions. Eventually, help to perfect the executive compensation evaluation mechanism against the background of new area.

Grey correlation analysis is an important part of grey system theory. Professor Liu Sifeng further studies the relationship between two sequences absolute increment on the basis of Deng’s degree and put forward the “Grey absolute correlation degree,” which is widely used in practice. In the study, on the basis of the area of the line between sequences size, it measures the correlation degrees of firm performance, executive stock holding, continuous growth capacity and other relevant factors of executive payment in China ports and listed shipping companies.

The paper concludes that the main factors influence CEO salary in China ports and listed shipping companies are return on equity and growth rate of fixed assets. However, the authors consider the frequent occurrence of executives’ corruption in China listed state-owned enterprise under the environment of financial and economic crisis, the authors argue that the significant influence of net assets attributed to shareholders cannot be ignored. In addition, cash flow in operating activities and executive stock holding both have relatively important effect on executive compensation.

This paper still has some limitations. First, it merely takes into account the financial indicators and ignores the influence of non-financial indicators to the performance evaluation of listed companies, such as: innovation ability, human capital and goodwill. Second, it has not considered the power consumption and other types of “invisible income” in the executive compensation structure, neither the influence of investing and financing activities on corporate performance. Consequently, these are likely to cause a certain deviation to the results of the study.

The outcome obtained in this paper can be provided for China ports and listed shipping companies to establish a reasonable executive compensation evaluation and incentive mechanism under the background of depressed shipping market.

This paper intends to use correlation analysis between firm performance, executive stock holding, sustainability and executive compensation in the new area of time, tries to make a greater contribution to the major component of salary policy and then make some suggestions on incentive supervising and restraining mechanisms for the ports and listed shipping firms in China.

Although scholars have done many studies about the association analysis of executive compensation and firm performance, they neglect the economic environment of industry. Meanwhile, considering the non-financial indicators and incomplete information, this paper studies the grey correlation analysis of executive compensation and influence factors in China ports and listed shipping firms under the background of the Chinese flagging shipping industry.

The implied assembly constraints of a computer-aided design (CAD) model (e.g. hierarchical constraints, geometric constraints and topological constraints) represent an important basis for product assembly sequence intelligent planning. Assembly prior knowledge contains factual assembly knowledge and experience assembly knowledge, which are important factors for assembly sequence intelligent planning. This paper aims to improve monotonous assembly sequence planning for a rigid product, intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge is proposed.

A spatio-temporal semantic assembly information model is established. The internal data of the CAD model are accessed to extract spatio-temporal semantic assembly information. The knowledge system for assembly sequence intelligent planning is built using an ontology model. The assembly sequence for the sub-assembly and assembly is generated via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge. The optimal assembly sequence is achieved via a fuzzy comprehensive evaluation.

The proposed spatio-temporal semantic information model and knowledge system can simultaneously express CAD model knowledge and prior knowledge for intelligent planning of product assembly sequences. Attribute retrieval and rule reasoning of spatio-temporal semantic knowledge can be used to generate product assembly sequences.

The assembly sequence intelligent planning example of linear motor highlights the validity of intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge.

The spatio-temporal semantic information model and knowledge system are built to simultaneously express CAD model knowledge and assembly prior knowledge. The generation algorithm via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge is given for intelligent planning of product assembly sequences in this paper. The proposed method is efficient because of the small search space.

The construction industry is facing challenges not only for workers' mobility in the pandemic situation but also for Lean Construction (LC) practise in responding to the high-quality development during the post-pandemic. As such, this paper presents a construction workforce management framework based on LC to manage both the emergency goal in migrant worker management and the long-term goal in labour productivity improvement in China.

The framework is created based on the integrated culture and technology strategies of LC. A combination of qualitative and quantitative methods is taken to explore factors influencing the mobility of construction workers and to measure labour productivity improvement. The case study approach is adopted to demonstrate the framework application.

For method application, a time-and-motion study and Percent Plan Complete indicator are proposed to offer labour productivity measurements of “resources efficiency” and “flow efficiency”. Moreover, the case study provides an industry level solution for construction workforce management and Lean Construction culture shaping, as well as witnesses the LC culture and technology strategies alignment contributing to LC practise innovation.

Compared with previous studies which emphasised solely LC techniques rather than socio-technical system thinking, the proposed integration framework as well as implementation of “Worker's Home” and “Lean Work Package” management models in the COVID-19 pandemic contribute to new extensions of both the fundamental of knowledge and practise in LC.

Proper platform pose is important for the mobile manipulator to accomplish dexterous manipulation tasks efficiently and safely, and the evaluation criterion to qualify manipulation performance is critical to support the pose decision process. This paper aims to present a comprehensive index to evaluate the manipulator’s operation performance from various aspects.

In this research, a criterion called hybrid manipulability (HM) is proposed to assess the performance of the manipulator’s operation, considering crucial factors such as joint limits, obstacle avoidance and stability. The determination of the optimal platform pose is achieved by selecting the pose that maximizes the HM within the feasible inverse reachability map associated with the target object.

A self-built mobile manipulator is adopted as the experimental platform, and the feasibility of the proposed method is experimentally verified in the context of object-grasping tasks both in simulation and practice.

The proposed HM extends upon the conventional notion of manipulability by incorporating additional factors, including the manipulator’s joint limits, the obstacle avoidance situation during the operation and the manipulation stability when grasping the target object. The manipulator can achieve enhanced stability during grasping when positioned in the pose determined by the HM.

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.

The purpose of this paper is to study the effect of micro-nano surface texture on the corrosion resistance of a titanium alloy and investigate the correlation between corrosion resistance and hydrophobicity.

The surface of the Ti₆Al₄V alloy was modified by laser processing and anodizing to fabricate micro-pits, nanotubes and micro-nano surface textures. Afterward, the surface morphology, hydrophobicity and polarization curve of the samples were analyzed by cold field scanning electron microscopy, contact angle measurement instruments and a multi-channel electrochemical workstation.

The micro-nano surface texture can enhance the hydrophobicity of the Ti₆Al₄V surface, which may lead to better drag reduction to ease the friction of implants in vivo. Nevertheless, no correlation existed between surface hydrophobicity and corrosion resistance; the corrosion resistance of samples with nanotubes and high-density samples with micro-nano surface texture was extremely enhanced, indicating the similar corrosion resistance of the two.

The mechanism of micro-dimples on the corrosion resistance of the micro-nano surface texture was not studied.

The density of micro-pits needs to be optimized to guarantee excellent corrosion resistance in the design of the micro-nano surface texture; otherwise, it will not fulfill the requirement of surface modification.

The influence of the micro-nano surface texture on the corrosion resistance, as well as the relationship between hydrophobicity and corrosion resistance of the titanium alloy surface, were systematically investigated for the first time. These conclusions offer new knowledge.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

This paper aims to present a one-shot gesture recognition approach which can be a high-efficient communication channel in human–robot collaboration systems.

This paper applies dynamic time warping (DTW) to align two gesture sequences in temporal domain with a novel frame-wise distance measure which matches local features in spatial domain. Furthermore, a novel and robust bidirectional attention region extraction method is proposed to retain information in both movement and hold phase of a gesture.

The proposed approach is capable of providing efficient one-shot gesture recognition without elaborately designed features. The experiments on a social robot (JiaJia) demonstrate that the proposed approach can be used in a human–robot collaboration system flexibly.

According to previous literature, there are no similar solutions that can achieve an efficient gesture recognition with simple local feature descriptor and combine the advantages of local features with DTW.