Search results

The differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array.

The authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array.

This paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance.

In this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

This study aims to analyze the influence of farmers’ degree of participation in collective action on their adoption decisions and waiting time regarding soil and water conservation (SWC) measures.

The Probit model and Generalized Propensity Score Match method are used to assess the effect of the degree of participation in collective action on farmers’ adoption decisions and waiting time for implementing SWC measures.

The findings reveal that farmers’ engagement in collective action positively influences the decision-making process regarding terrace construction, water-saving irrigation and afforestation measures. However, it does not significantly impact the decision-making process for plastic film and ridge-furrow tillage practices. Notably, collective action has the strongest influence on farmers’ adoption decisions regarding water-saving irrigation technology, with a relatively smaller influence on the adoption of afforestation and terrace measures. Moreover, the results suggest that participating in collective action effectively reduces the waiting time for terrace construction and expedites the adoption of afforestation and water-saving irrigation technology. Specifically, collective action has a significantly negative effect on the waiting time for terrace construction, followed by water-saving irrigation technology and afforestation measures.

The results of this study underscore the significance of fostering mutual assistance and cooperation mechanisms among farmers, as they can pave the way for raising funds and labor, cultivating elite farmers, attracting skilled labor to rural areas, enhancing the adoption rate and expediting the implementation of terraces, water-saving irrigation technology and afforestation measures.

Drawing on an evaluation of farmers’ degree of participation in collective action, this paper investigates the effect of participation on their SWC adoption decisions and waiting times, thereby offering theoretical and practical insights into soil erosion control in the Loess Plateau.

With interest in modern construction methods and new technologies on the rise, construction companies globally are increasingly looking at how to embrace new ideas and engage with new approaches to do things better. A significant amount of work has been carried out investigating the use of individual technologies in the construction sector. However, there is no holistic understanding of the new and emerging technologies that have had proven benefits for construction projects. To fill this gap, this paper aims to provide a landscape of technologies that have been implemented in the construction industry and the benefits associated with their implementation.

A systematic review approach and PRISMA guidelines were used. A total of 175 articles published between 2001 and 2020 were identified and thoroughly reviewed.

The results show that a total of 26 technologies were identified from the literature, and these can be categorised into five groups in terms of their functionality in construction process, namely: (1) data acquisition, (2) analytics, (3) visualisation, (4) communication and (5) design and construction automation. Digital technologies, especially for data acquisition and visualisation, generally appear to underpin and enable innovation in many aspects of construction. Improvements in work efficiency, health and safety, productivity, quality and sustainability have been cited as being the primary benefits of using these technologies. Of these, building information modelling (BIM) appears to be the single most commonly used technology thus far. With the development of computer technology, BIM has constantly been used in combination with other technologies/tools such as unmanned aerial vehicles/systems (unmanned aerial vehicle (UAV)/UAS), geographic information systems (GIS), light detection and ranging (LiDAR) and multidimensional modelling to realise a specifically defined benefit.

The findings from this review would help construction practitioners identify the types of technologies that can be implemented in different stages of construction projects to achieve desired outcomes, and thus, make appropriate decisions on technology investment and adoption. This review also suggests that to reap the full potential that these technologies offer, aside from construction companies changing their culture and business models, corresponding changes in the construction sector’s operating systems related to building regulation, education and training, as well as contracting and procurement are required.

This paper undertakes a comprehensive systematic review of studies on technology implementation in the construction sector published between 2001 and 2020. It is the first attempt internationally to provide a holistic picture of technologies that have been studied and implemented in construction projects.

This study aims to investigate the corrosion behavior of Cu-containing 3Ni steel in simulated marine environments and to provide basic guidance for improving the corrosion resistance of marine high-strength steels.

The corrosion properties of Cu-containing 3Ni steel were evaluated in five different NaCl concentrations by alternating wet and dry cycling method. The corrosion behavior was investigated by electrochemical impedance spectroscopy, scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. The mechanism of the influence of Cl ion concentrations on the corrosion behavior of Cu-containing 3Ni steel in marine environments was analyzed.

The results showed that the corrosion resistance of Cu-containing 3Ni steel decreased with NaCl concentration increasing. With the increase of NaCl concentration, the number of FeOOH particles decreased and their size increased, resulting in an increase in the porosity and a decrease in the density of corrosion products. High NaCl concentration could inhibit the formation of NiFe₂O₄ and disrupt the electronegativity of the inner film of corrosion products, which further weakened the enrichment of Ni and Cu, and enhanced the permeability of Cl ions.

The influence of NaCl concentrations on the corrosion behavior of Cu-containing 3Ni steel was systematically studied and the influence laws of corrosion behavior were obtained in this paper, providing basic data for the optimal design of Cu-containing 3Ni steels.

This study aims to improve the accuracy of hyperspectral estimation of soil organic matter content.

Based on the uncertainty in spectral estimation, 76 soil samples collected in Zhangqiu District, Jinan City, Shandong Province, were studied in this paper. First, the spectral transformation of the spectral data after denoising was carried out by means of 11 transformation methods such as reciprocal and square, and the estimation factor was selected according to the principle of maximum correlation. Secondly, the grey weighted distance was used to calculate the grey relational degree between the samples to be estimated and the known patterns, and the local linear regression estimation model of soil organic matter content was established by using the pattern samples closest to the samples to be identified. Thirdly, the models were optimized by gradually increasing the number of modeling samples and adjusting the decision coefficient, and a comprehensive index was constructed to determine the optimal predicted value. Finally, the determination coefficient and average relative error are used to evaluate the validity of the model.

The results show that the maximum correlation coefficient of the seven estimated factors selected is 0.82; the estimation results of 14 test samples are of high accuracy, among which the determination coefficient R² = 0.924, and the average relative error is 6.608%.

Studies have shown that it is feasible and effective to estimate the content of soil organic matter by using grey correlation local linear regression model.

The paper succeeds in realizing both the soil organic matter hyperspectral grey relation estimating pattern based on the grey relational theory and the estimating pattern by using the local linear regression.

Olfaction plays a very important role in daily life. The olfactory system has the ability to recognize, discriminate and identify thousands of odorant compounds with extremely high sensitivity and specificity. The research on olfactory system has very important values in exploring the mechanisms of information processing in the other sensory nervous systems and brain. Recently, with the development of molecular biological and microelectronics technology research, the study of olfactory cell-based sensors has made great progress. The purpose of this paper is to provide details of recent developments in olfactory cell-based sensors.

Following an introduction, this paper first discusses some olfactory cell-based biosensors, which focus on the light-addressable potentiometric sensors and the microelectrode arrays. Second, surface modification, microfabrication and microfluidic technology which can improve the efficiency of cell immobilization will be summarized. The research trends of olfactory cell-based sensor in future will be proposed.

This paper shows that the biosensors’ performance is expected to be greatly improved due to the fast development of nanotechnology, optical technology and microelectronics. More and more emerging intelligent olfactory sensors will have a promising prospect in many application fields, including food quality and safety assessment, environmental monitor and human diseases detection.

This paper provides a detailed and timely review of the rapidly growing research in the olfactory cell-based sensors.

Dynamic low adhesion (DLA) has become an urgent problem for the high-speed wheel-rail system because of continuous decrease of adhesion redundancy in the past decades. This article aims to provide a simulation method to reveal the mechanism of DLA under high-frequency vibrations.

A transient wheel-rail rolling contact model is developed for a typical Chinese high-speed railway system using the explicit finite element (FE) method. Instantaneous adhesion exploitation levels are studied in the time domain, for which driving cases over corrugated rails are taken as an example. A speed up to 500 km/h is considered together with different traction coefficients and corrugation dimensions. DLA is expected when the instantaneous adhesion exploitation level reaches 1.0, that is adhesion saturates and full sliding contact occurs.

The instantaneous adhesion exploitation level can be very high in the presence of corrugation, even at low traction coefficients. DLA is found to occur as great vertical unloading takes place and causes a significant increase of creepage. An approach is further developed to determine the critical depth of corrugation over which DLA occurs.

This study employs the transient wheel-rail rolling contact model to predict the instantaneous adhesion exploitation level under high-frequency vibrations. The presented results reveal a mechanism of DLA being beneficial to guidelines for future railway practice.

The purpose of this paper is to use the internal model control to deal with nonlinear stable systems affected by parametric uncertainties.

The dynamics of a considered system are approximated by a Takagi-Sugeno fuzzy model. The parameters of the fuzzy rules premises are determined manually. However, the parameters of the fuzzy rules conclusions are updated using the descent gradient method under inequality constraints in order to ensure the stability of each local model. In fact, without making these constraints the training algorithm can procure one or several unstable local models even if the desired accuracy in the training step is achieved. The considered robust control approach is the internal model. It is synthesized based on the Takagi-Sugeno fuzzy model. Two control strategies are considered. The first one is based on the parallel distribution compensation principle. It consists in associating an internal model control for each local model. However, for the second strategy, the control law is computed based on the global Takagi-Sugeno fuzzy model.

According to the simulation results, the stability of all local models is obtained and the proposed fuzzy internal model control approaches ensure robustness against parametric uncertainties.

This paper introduces a method for the identification of fuzzy model parameters ensuring the stability of all local models. Using the resulting fuzzy model, two fuzzy internal model control designs are presented.

Research investigating the association between religiosity and earnings management has concentrated on accruals-based earnings management, relying heavily on society’s religiosity, but it has neglected the interaction between religiosity and formal monitoring mechanisms. This study aims to examine how the religiosity and accounting expertise traits of top leaders are associated with real earnings management (REM) and how they interact to eliminate these practices.

Using a sample of 943 year-observations from more religious settings, this paper collects data for four measures of REM, and for religiosity and accounting expertise of audit committee (AC) chair and chief executive officer (CEO). Multivariate regression is used to test the study hypotheses.

The findings are consistent with the predictions that religious top leaders are not associated with lower REM, while top leaders with accounting expertise, in some cases, are associated with lower REM. This paper also finds that a leader with religious belief and accounting expertise dramatically lowers REM. These findings are robust under a battery of sensitive analyzes. In an additional analysis, this paper observes the interaction effect between these two traits is strengthened if the board chair is religious, and persists even for larger firms or those with a highly concentrated ownership structure.

The paper provides evidence that may serve a variety of decision-makers. It is the first to show that the interaction between religiosity and expertise is crucial in curbing REM. It also provides the first evidence for the role of the AC chair in relation to REM.