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This paper aims to present a method for improving the performance of the visual-inertial navigation system (VINS) by using a bio-inspired polarized light compass.

The measurement model of each sensor module is derived, and a robust stochastic cloning extended Kalman filter (RSC-EKF) is implemented for data fusion. This fusion framework can not only handle multiple relative and absolute measurements, but can also deal with outliers, sensor outages of each measurement module.

The paper tests the approach on data sets acquired by a land vehicle moving in different environments and compares its performance against other methods. The results demonstrate the effectiveness of the proposed method for reducing the error growth of the VINS in the long run.

The main contribution of this paper lies in the design/implementation of the RSC-EKF for incorporating the homemade polarized light compass into visual-inertial navigation pipeline. The real-world tests in different environments demonstrate the effectiveness and feasibility of the proposed approach.

The purpose of this paper is to present some design guidelines for the selection of the materials of the main frictional pairs in a water hydraulic piston pump.

In the research, a specified test bench that can simulate the typical frictional pairs in a water hydraulic piston pump was built. The friction and wear behaviors of the three pairs in the pump with different materials combinations were tested on the test bench. The tested materials included metal, engineering ceramics and plastics. Some surface engineering technologies including plasma surface spray, laser clad and heat treatment were applied and tested. The matching schemes included hard‐to‐hard (such as ceramics‐to‐ceramics) and hard‐to‐soft (such as metal‐to‐plastics, ceramics‐to‐plastics).

Some principles for the materials selection in a water hydraulic piston pump were obtained. According to the test results, the combination schemes for the main frictional pairs in a water hydraulic piston pump were proposed.

A test apparatus that could simulate the movement of main frictional pairs in a water hydraulic piston pump more really than the other general materials machines was developed. Some materials including metal, engineering ceramics and plastics and some engineering technologies were tested. The research described here is an important foundation for the development of a water hydraulic piston pump.

Investments.

The case is suitable for students with diverse backgrounds – from different countries with different cultures, and from different programs (undergraduate or graduate). The case will be used for an all-English course “The research of Chinese stock markets” and has been used for the course “Portfolio theory and management” (junior student level) at Nankai University.

The case introduces Chinese stock markets' uniqueness that there exists a huge number of previously nontradable shares. The release of the shares radically changes the markets' balance and causes the absolute dominance of stock supply over stock demand. Based on the analysis for ICBC, the case demonstrates that the dominance can explain the drop of ICBC's stock price by supply-demand law but fundamental analysis cannot.

The case will help students to understand the uniqueness of Chinese stock markets and the applicability of supply-demand law in the markets and then be able to make investment decisions.

The case can help to educate not only students but also Chinese and foreign investors about the uniqueness of Chinese stock markets and arm the students and investors with the supply-demand methodology to analyse the markets and the reasoning of when and how to invest.

Teaching notes are available for educators only. Please contact your library to gain login details or e-mail support@emeraldinsight.com to request teaching notes.

This paper addresses the limitations of current graph neural network-based recommendation systems, which often neglect the integration of side information and the modeling of complex high-order interactions among nodes. The research motivation stems from the need to enhance recommendation performance by effectively utilizing all available data. We propose a novel method called MSHCN, which leverages hypergraph neural networks to integrate side information and model complex interactions, thereby improving user and item representations.

The MSHCN method employs a hypergraph structure to incorporate various types of side information, including social relationships among users and item attributes, which are essential for enriching user and item representations. The k-means clustering algorithm is utilized to create item-associated hypergraphs, while sentiment analysis on user reviews refines the modeling of user interests. Additionally, hypergraphs are constructed for user-user and item-item interactions based on interaction similarity. MSHCN also incorporates contrastive learning as an auxiliary task to enhance the representation learning process.

Extensive experiments demonstrate that MSHCN significantly outperforms existing recommendation models, particularly in its ability to capture and utilize side information and high-order interactions. This results in superior user and item representations and improved recommendation performance.

The novelty of MSHCN lies in its use of a hypergraph structure to integrate diverse side information and model intricate high-order interactions. The incorporation of contrastive learning as an auxiliary task sets it apart from other hypergraph-based models, providing a significant enhancement in recommendation accuracy.

South Africa is the highest consumer of commercial energy per capita in Africa, ranking 16th in the world for primary energy consumption. It is also ranked among the bottom 50 of the 150 countries regarding energy efficiency. The cold chain is a large contributor through refrigerated transport vehicles. To comply with the changing climate regulations, cryogenic and eutectic systems are systems with great potential for small distance refrigerated transport. The purpose of this paper is to introduce eutectic system to medium distance refrigerated transport.

This study presents the potential use of Eutectic plates inside a medium refrigerated transport vehicle, by numerically investigating the characteristics of phase change material eutectic plates applied at low-temperature ranges. A physical model and a mathematical model for three-dimensional transient natural flow were developed as proposed by Xiaofeng and Zhang. Using the governing equation of mass, momentum and energy conservation, three Eutectic plate configurations were modeled and simulated in ANSYS Fluent for 5 h.

A uniform heat transfer and airflow condition inside a refrigerated compartment were predicted using the Reynolds stress model. The configuration with eutectic plates placed at the top and side showed great potential for the system functioning in the South African climate.

Medium refrigerated transport vehicle.

This configuration had a high-temperature distribution across the compartment and promoted high air circulations, showing that it could be ideal for medium refrigerated transport vehicles delivering perishable foodstuffs or non-food goods.

The purpose of this paper is to define new criteria for measuring workload smoothness of two-sided assembly lines and propose an algorithm to solve a two-sided assembly line balancing problem focusing on distributing the idle time and the workload as evenly as possible among the workstations.

This paper points out that the mean absolute deviation (MAD) and the smoothness index (SI) used to measure the workload smoothing in one-sided assembly lines are both inappropriate to evaluate the workload balance among workstations in two-sided assembly lines, as the idle time occur at the beginning and in the middle of a cycle within workstations. Then, the finish-time-based SI and MAD (FSI and FMAD) are defined, and a heuristic procedure based on the core mechanism of Moodie and Young method is proposed to smooth the assembly workload in two-sided assembly lines.

The computational results indicate that the proposed heuristic algorithm combined with the FMAD is effective in distributing the idle time and the workload among workstations as evenly as possible in two-sided assembly lines.

The two-sided assembly line balancing problem with the objective of the line efficiency can be effectively solved by the proposed approach.

The FMAD is proposed to effectively improve the workload smoothing in two-sided assembly lines.

The purpose of this paper is to propose an improved method which can shorten the calculation time and improve the calculation efficiency under the premise of ensuring the calculation accuracy for calculating the response of dynamic systems with periodic time-varying characteristics.

An improved method is proposed based on Runge–Kutta method according to the composition characteristics of the state space matrix and the external load vector formed by the reduction of the dynamic equation of the periodic time-varying system. The recursive scheme of the holistic matrix of the system using the Runge–Kutta method is improved to be the sub-block matrix that is divided into the upper and lower parts to reduce the calculation steps and the occupied computer memory.

The calculation time consumption is reduced to a certain extent about 10–35% by changing the synthesis method of the time-varying matrix of the dynamics system, and the method proposed of paper consumes 43–75% less calculation time in total than the original Runge–Kutta method without affecting the calculation accuracy. When the ode45 command that implements the Runge–Kutta method in the MATLAB software used to solve the system dynamics equation include the time variable which cannot provide its specific analytic function form, so the time variable value corresponding to the solution time needs to be determined by the interpolation method, which causes the calculation efficiency of the ode45 command to be substantially reduced.

The proposed method can be applied to solve dynamic systems with periodic time-varying characteristics, and can consume less calculation time than the original Runge–Kutta method without affecting the calculation accuracy, especially the superiority of the improved method of this paper can be better demonstrated when the degree of freedom of the periodic time-varying dynamics system is greater.

The aim of the paper is to propose a global, automated and continuous curvature calibration strategy for bending sensors, which is used for the angle feedback control of soft fingers.

In this work, the proposed curvature calibration strategy for bending sensors is based on the constant curvature bending properties of soft fingers. The strategy is to install the bending sensor on the soft finger and use the laser distance sensor to assist calibration, then calculate the relationship between the curvature and the voltage of the bending sensor through geometric conversion. In addition, this work also develops a full set of standard calibration systems and collection procedures for the bending sensor curvature calibration and uses machine learning algorithms to fit the collected data.

First, compared with the traditional calibration methods, the proposed curvature calibration strategy can achieve constant curvature measurement with the advantages of better continuity. Second, using the sensor data obtained by the proposed calibration method as the feedback signal for the soft finger bending angle control, the control effect is better than that of the traditional method.

This work proposes and verifies a global, automated and continuous curvature calibration strategy for bending sensors and is used for the angle feedback control of soft fingers. In addition, this work also develops a full set of standard calibration systems and collection procedures, which can be applied to a variety of flexible bending sensors with a good adaptability.

This study aims to analyse the scientific relationship between technological innovation and carbon emissions. Taking the Chinese electric power industry as the empirical research object, this study examined the effect of power technological innovation on carbon emissions and proposed policy recommendations for the development of technological innovation in China.

This study first calculated the energy consumption and carbon emission level of the Chinese electric power industry from 2005 to 2018. Secondly, this study built an evaluation index system for technological innovation of electric power with six indicators: average utilisation hours of power generation equipment; power consumption rate of power plant; line loss rate; standard coal consumption for power generation; standard coal consumption for power supply; and number of patent applications granted for generation, conversion or distribution of electric power in China. Finally, from a practical point of view, the relationship between technological innovation and carbon emissions of the Chinese electric power industry from 2005 to 2018 is evaluated and analysed.

Power technology innovation has been found to have a long-term and relatively large effect on carbon emissions, and carbon emissions have a short-term and insignificant impact on power technology innovation.

This study puts forward relevant suggestions for developing technological innovation and technology transfer, which is essential to establishing a low-carbon or zero-carbon power system in China.

This study provides empirical evidence for clarifying the relationship between technological innovation and carbon emissions in the power industry and further develops research theories on technological innovation and carbon emissions.

Relevant authorities will adopt measures to promote technological innovation and development in the power sector to reduce carbon emissions.

This study built an evaluation index system with six indicators for technological innovation of electric power. The evaluation method was used to measure the technological innovation level of the Chinese electric power industry. The causal link between technological innovation and carbon emissions in China was analysed.

Customization, a marketing strategy through providing personalized products, might be a new solution to motivate consumer feedbacks in electronic commerce (e-commerce) websites. Taking the dual-value of customization (emotional involvement and uniqueness expression) as the theoretical basis, this study aims to investigate the impact of customization on consumer's word-of-mouth (WOM) behaviors and contents by motivating: (1) more, (2) faster, (3) positive at first and then negative, (4) longer and (5) more helpful WOMs.

A field study was conducted with multi-sourced data: customer order data from a Chinese retailer and WOM data from Amazon.com. The two datasets were matched to filter out 463 online reviews among 6,892 customers who placed customized orders. Heckman's two-stage model, logistic regression, Ordinary least squares regression, Tobit regression, analysis of covariance and Lind–Mehlum U Test were used in the data analysis.

This study has found that (1) customization level motivates WOM behaviors including WOM posting and WOM speed, (2) an inverted U-shaped relationship exists between customization level and consumer rating and (3) customization level has a significantly positive impact on WOM helpfulness but not on WOM length.

This study advances theoretical development in the area of WOM motivators by proposing a new product-centric approach, customization, to stimulate voluntary WOMs. Empirical field research that analyzes consumer's real responses to customization is in scarcity. The dual-value of customized products is proposed as the underlying mechanism to explain the impact of customization level on consumer's WOM behaviors/contents. An interesting inverted U-shaped relationship is found between customization level and customer rating. This research provides nuanced practical guidance for websites, companies and consumers.