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Positioning is a key task in most field robotics applications but can be very challenging in GPS‐denied or high‐slip environments. The purpose of this paper is to describe a visual odometry strategy using only one camera in country roads.

This monocular odometery system uses as input only those images provided by a single camera mounted on the roof of the vehicle and the framework is composed of three main parts: image motion estimation, ego‐motion computation and visual odometry. The image motion is estimated based on a hyper‐complex wavelet phase‐derived optical flow field. The ego‐motion of the vehicle is computed by a blocked RANdom SAmple Consensus algorithm and a maximum likelihood estimator based on a 4‐degrees of freedom motion model. These as instantaneous ego‐motion measurements are used to update the vehicle trajectory according to a dead‐reckoning model and unscented Kalman filter.

The authors' proposed framework and algorithms are validated on videos from a real automotive platform. Furthermore, the recovered trajectory is superimposed onto a digital map, and the localization results from this method are compared to the ground truth measured with a GPS/INS joint system. These experimental results indicate that the framework and the algorithms are effective.

The effective framework and algorithms for visual odometry using only one camera in country roads are introduced in this paper.

Due to the increasing awareness of environmental and social issues, many practitioners and researchers have paid attention to sustainable supply chain management. As the performance of suppliers determines the success of supply chains, sustainable supplier selection becomes more and more important. Existing sustainable supplier selection models evaluated the sustainability of suppliers in three aspects (economic, environmental and social) and assumed that values on different criteria can completely compensate for each other directly. However, in reality, criteria in economic, environmental and social aspects are heterogeneous, and the decision-maker’s preferences on criteria belonging to different aspects are different. In this case, values on criteria belonging to different aspects are not allowed to completely compensate for each other directly. To solve this problem, this paper aims to propose a hybrid sustainable supplier selection approach integrating compensatory and non-compensatory decision rules.

In the proposed approach, the compensatory decision method Technique for Order of Preference by Similarity to Ideal Solution is used to evaluate performances of suppliers with respect to economic, environmental and social aspects. The non-compensatory decision method Elimination and Choice Translating Reality is used to evaluate performances of suppliers on sustainable criteria comprehensively. Through the proposed approach, only criteria belonging to the same aspects are allowed to compensate for each other directly. Finally, experimental results show that the proposed integrated approach is effective and efficient to help the decision-maker select optimal sustainable suppliers.

This is an original approach that integrates compensatory and non-compensatory decision rules, which can benefit from the two kinds of decision rules simultaneously. The integrated approach can be used as an aid for companies to select the best sustainable suppliers.

This paper presents an original integrated sustainable supplier selection approach using both compensatory and non-compensatory methods. It can benefit from the advantages of both compensatory and non-compensatory methods. The proposed approach can express preferences of the decision-maker on sustainable criteria sufficiently and maximize economic benefits while meeting environmental needs.

The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.

First, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.

The paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.

The paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.

Micro-texture is processed on the surface to reduce the friction of the contact surface, and its application is more and more extensive. The purpose of this paper is to create a texture function model to study the influence of surface parameters on the accuracy of the simulated surface so that it can more accurately reflect the characteristics of the real micro-textured surface.

The microstructure function model of rough surfaces is established based on fractal geometry and polar coordinate theory. The offset angle θ is introduced into the fractal geometry function to make the surface asperity normal perpendicular to the tangent of the surface. The 2D and 3D contour surfaces of the surface groove texture are analyzed by MATLAB simulation. The effects of fractal parameters (D and G) and texture parameter h on the curvature of the surface micro-texture model were studied.

This paper more accurately characterizes the textured 3D curved surface, especially the surface curvature. The scale coefficient G significantly affects curvature, and the influence of fractal dimension D and texture parameters on curvature can be ignored.

The micro-texture model of the rough surface was successfully established, and the range of fractal parameters was determined. It provides a new method for the study of surface micro-texture tribology.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2023-0298/

This study explored how teachers change, what teachers learn and how they learn during the implementation of project-based learning through lesson study.

In this study, three university researchers, one doctoral student and six mathematics school teachers formed a lesson study team. Using a qualitative research method, this study employed a locally integrating networking strategy to combine the modified Interconnected Model of Teacher Professional Growth (IMTPG) and Bannister's framework to describe the teachers' knowledge change when participating in a lesson study on project-based learning.

The research revealed that the school teachers' knowledge about authenticity and assessment in the context of project-based learning was changed after the lesson study and how the changes were triggered.

The study demonstrates how the networking of two different theories—modified IMTPG and Bannister's framework—contributes to a better understanding of the process of teachers' collective practice, as well as the knowledge change in PjBL. This networking was done by combining the two theories, which were superimposed at the domain of practice.

This study aims to investigate a chromium-free sealing treatment process to replace the chromate sealing process in response to the environmental hazards caused by chromate in the Phosphate chemical conversion (PCC) coating post-treatment sealing process.

In this paper, chromium-free sealing technology was used to post-treat PCC coatings. Scanning electron microscopy was used to investigate the structure of the surface of the PCC coatings after the sealing treatment, and the corrosion resistance, hydrophobicity and bonding were tested using an electrochemical workstation, a copper sulfate spot-drop test, a lacquer bonding test, a contact angle meter and a neutral salt spray test.

Chromium-free closure makes the grain distribution on the surface of the PCC coating more uniform and dense, and forms an organic film on the surface of the coating, which significantly improves the corrosion resistance and hydrophobicity of the PCC coating, does not affect the coating film bonding force and has similar performance with potassium dichromate solution.

The results show that the corrosion resistance of PCC coatings after chromium-free sealing treatment is improved, and chromium-free sealing has the potential to replace chromium sealing.

The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods.

In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach.

Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes.

The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.

This paper aims to propose a novel blockchain crowdfunding projects evaluation approach using extended techniques for order preferences by similarity to ideal solution (TOPSIS) under fuzzy environment.

By analyzing the characteristics and operation process of blockchain crowdfunding model, this paper formulates the evaluation index system from three dimensions of human resources, capital and publicity. In addition, the entropy method is used to calculate the weight of each indicator to avoid subjective judgments; different alternatives are evaluated using the grey correlation analysis (GRA) and TOPSIS-integrated method which considers the distance and similarity between alternatives simultaneously.

By analyzing the characteristics and operation process of blockchain crowdfunding model, this paper formulates the evaluation index system from three dimensions of human resources, capital and publicity. In addition, the entropy method is used to calculate the weight of each indicator to avoid subjective judgments; different alternatives are evaluated using the GRA and TOPSIS-integrated method which considers the distance and similarity between alternatives simultaneously.

Blockchain crowdfunding has become a new model for fund-raisers to raise funds from public investors. This paper proposes a novel blockchain crowdfunding projects evaluation approach using extended TOPSIS under fuzzy environment.

Manipulator motion accuracy is a fundamental requirement for precision manufacturing equipment. Light weight manipulators in high speed motions are vulnerable to deformations. The purpose of this work is to analyze the effect of link deformation on the motion precision of parallel manipulators.

The flexible dynamics model of the links is first established by applying the Euler–Bernoulli beam theory and the assumed modal method. The rigid-flexible coupling equations of the parallel mechanism are further derived by using the Lagrange multiplier approach. The elastic energy resulting from spiral motion and link deformations are computed and analyzed. Motion errors of the 3-link torque-prismatic-torque parallel manipulator are then evaluated based on its inverse kinematics. The validation experiments are also conducted to verify the numerical results.

The lateral deformation and axial deformation are largest at the middle of the driven links. The axial deformation at the middle of the driven link is approximately one-tenth of the transversal deformation. However, the elastic potential energy of the transversal deformation is much smaller than the elastic force generated from axial deformation.

Knowledge on the relationship between link deformation and motion precision is useful in the design of parallel manipulators for high performing dynamic responses.

This work establishes the relationship between motion precision and the amount of link deformation in parallel manipulators.

The purpose of this paper is to investigate the determinants of capital structure using a cross-section sample of 1,481 non-financial firms listed on the Chinese stock exchanges in 2011.

Employing four leverage measures (total leverage and long-term leverage in terms of both book value and market value, respectively) this study examines the effects of factors with proven influences on capital structure in literature, along with industry effect and ownership effect.

The authors find that large firms favour debt financing while profitable firms rely more on internal capital accumulation. Intangibility and business risk increase the level of debt financing but tax has little impact on capital structure. The authors also observe strong industrial effect and ownership effect. Real estate firms borrow considerably more and firms from utility and manufacturing industries use more long-term debt despite compared with commercial firms. On the other hand, firms with state ownership tend to borrow more, while firms with foreign ownership choose more equity financing.

The study uses cross-section data to avoid any potential time effects, which allows the authors to focus on their main research question – to identify the determinants of capital structure for Chinese firms. Future research may gain more insights using panel data and considering other factors such as crisis and financial reforms.

These results may provide important implications to investors in making investment decision and to firms in making financing decisions.

This paper uses by far the largest and latest cross-section sample from the Chinese stock markets, offering a more complete picture of the financing behaviours in the Chinese firms, with known characters and the impact of ownerships.