Search results

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.

This paper aims to improve performance prediction and to acquire more detailed flow structures so as to analyze the turbulence in complex rotor-stator flow.

Hydraulic retarder as typical fluid machinery was numerically investigated by using hybrid Reynolds-averaged Navier–Stokes (RANS)/large eddy simulation (LES) models CIDDES Algebraic Wall-Modeled Large Eddy Simulation (LES) (WMLES) S-Ω and dynamic hybrid RANS/LES (DHRL). The prediction results were compared and analyzed with a RANS model shear stress transport (SST) k-omega which was a recommended choice in engineering.

The numerical results were verified by experiment and indicated that the predicted values for three hybrid turbulence models were more accurate. Then, the transient flow field was further analyzed visually in terms of turbulence statistics, Reynolds number, pressure-streamline, vortex structure and eddy viscosity ratio. The results indicated that HRL approaches could capture unsteady flow phenomena.

This study achieves both in performance prediction improvement and better flow mechanism understanding. The computational fluid dynamics (CFD) could be used instead of flow visualization to a certain extent. The improved CFD method, the fine computational grid and the reasonable simulation settings jointly enhance the application of CFD in the rotor-stator flow.

The improvement was quite encouraging compared with the reported literatures, contributing to the CFD playing a more important role in the flow machinery. DHRL provided the detailed explanation of flow transport between rotor and stator, which was not reported before. Through it, the flow mechanism can be better understood.

The purpose of this study is to investigate the effect of the strut size and tilt angle on the densification behavior, surface roughness and dimensional accuracy of the selective laser melting AlSi10Mg lattice structure was investigated in this study. In this study, the characteristics such as the density, up-skin and down-skin roughness and dimensional accuracy of selective laser melting forming technology manufacturing (SLMed) AlSi10Mg cellular lattice structure were carried. This work reveals the effect of the strut size and tilt angle on the geometric characteristics of SLMed AlSi10Mg and is benefit for controlling the forming performance of the SLMed cellular lattice structure.

Based on AlSi10Mg powder, the influence of the tilt angle changed from 10° to 45° with an increment of 5° were investigated, the influence of the strut size was varied from 0.4 mm to 1.2 mm with an increment of 0.2 mm were investigated. The characteristics such as the density, up-skin and down-skin roughness, dimensional accuracy and mechanical properties of SLM-ed AlSi10Mg cellular lattice structure was carried.

Greater than 99% relative density can be achieved for different strut size when optimal process parameters are used. In the optimized process interval, the struts with a tilt angle of 10° can still be formed well, which is higher than the design limit of the inclined angle given in the related literature. The tilt angle has a significant effect on the surface roughness of the strut. The microhardness reached to 157 ± 3 HV, and the maximum compressive strength was 58.86 MPa, with the optimal process parameters.

In this study, the characteristics such as the density, up-skin and down-skin roughness and dimensional accuracy of SLMed AlSi10Mg cellular lattice structure were carried. With the optimal geometric parameters, the authors tested microhardness and compressive strength of the cellular lattice structure. The results of this study provide theoretical and experimental basis for the realization of high-quality manufacturing and optimization design of aluminum alloy cellular lattice structure, which will meet more diversified industrial needs.

This study aims to analyze passenger service quality in Beijing West Railway Station from the perspective of passengers, to better understand the current service quality and obtain the areas of weakness for improvement.

The research investigates the passenger experience of service in Beijing West Railway Station by using a questionnaire survey. The service quality (SERVQUAL) evaluation method is used to analyze the survey data, and it divides the passenger service into 5 attributes with 20 indicators. This research uses the Likert five-level scale method to process data and calculates the SERVQUAL value and weight difference of each attribute to evaluate the passenger service. Therefore, the deficiencies have been pointed out, so the station manager can improve the passenger service accordingly.

It is indicated that among the five studied attributes, Beijing West Railway Station has the smallest service quality value in terms of timeliness, which means this part needs the largest improvement. To the five attributes, each lacks in station security check, ticketing efficiency, station identification accuracy, emergency processing of train delays and the restroom environment, respectively.

The research can provide specific suggestions for the optimization of the passenger service of Beijing West Railway Station, and provide reference information for the formulation of policies.

The paper aims to construct a method to simulate the relationship between the parameters of soil properties and the area of sliding mass of the true slip surface of a landslide.

The smoothed particle hydrodynamics (SPH) algorithm is used to calibrate a response surface function which is adopted to quantify the area of sliding mass of the true slip surface for each failure sample in Monte Carlo simulation. The proposed method is illustrated through a homogeneous and a heterogeneous cohesive soil slope.

The comparison of the results between the proposed method and the traditional method using the slip surface with minimum factor of safety (FS_min) to quantify the failure consequence has shown that the landslide risk tends to be attributed to a variety of risk sources, and that the use of a slip surface with FS_min to quantify the consequence of a landslide underestimates the landslide risk value. The difference of the risk value between the proposed method and the traditional method increases dramatically as the uncertainty of soil properties becomes significant.

A geotechnical engineer could use the proposed method to perform slope failure analysis.

The failure consequence of a landslide can be rationally predicted using the proposed method.

The serious wear problem of heavy-haul freight vehicle wheels affects the safety and economy of vehicle operation. This paper aims to study wheel wear evolution law and the influence of line parameters on wheel wear of heavy-haul freight, and provide the basis for operation and line maintenance.

The wheel wear test data of heavy-haul freight vehicles were analyzed. Then a heavy-haul freight vehicle dynamic model was established. The line parameters influencing wheel wear in heavy-haul freight vehicles were also analyzed by the Jendel wear model, and the effects of rail cant, rail gauge, rail profile and line ramp on wheel wear were analyzed.

A rail cant of 1:40 results in less wheel wear; an increase in the rail gauge can reduce wheel wear; and when matched with the CHN60 rail, the wear depth is relatively small. A decrease of 9.21% in wheel wear depth when matched with the CHN60 rail profile. The ramp of the heavy-haul line is necessary to consider for calculating wheel wear. When the ramp is considered, the wear depth increases by 8.47%. The larger the ramp, the greater the braking force and therefore, the greater of the wheel wear.

This paper first summarizes the wear characteristics of wheels in heavy-haul freight vehicles and then systematically analyzes the effect of line parameters on wheel wear. In particular, this study researched the effects of rail cant, rail gauge, rail profile and line ramp on wheel wear.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0038/

Extensively public concern on “Huge Executive Compensation” makes it urgent to investigate the reasonability of high executive compensation. The purpose of this paper is to explore the effectiveness of compensation contracting based on the specific responsibility of executives. More specifically, this paper is to examine whether high compensation is helpful to mitigate agency problems.

Considering that board secretaries of listed companies are responsible for information disclosure in China, this paper examines the effect of board secretaries’ excess compensation on firms’ disclosure quality using listed company data from 2007 to 2015. The first measure of disclosure quality is based on the disclosure violation behavior of firms, and the second is KV value that represents the extent to which the investors relay on the stock trading volume. To provide additional confidence that the findings are robust, this paper further conducts two indirect tests based on rumors and cost of equity capital.

The results show that board secretaries’ excess compensation is negatively associated with the probability of information disclosure violation and also negatively associated with firms’ KV value, suggesting firms that pay high compensation to their information providers are more likely to provide high-quality disclosures. Besides, this paper further finds that board secretaries’ excess compensation is negatively related to the incidence of rumors, the number of rumors incurred or the cost of equity capital.

Overall, the findings provide support to the efficient contracting of executive compensation, which implies that highly paid board secretaries would be better information providers than those poorly paid.

This paper provides empirical evidence that firms’ disclosure quality can be improved by modifying the compensation contract of information providers. This may indicate a new way to improve the quality of disclosures, so as to mitigate the agency problem.

In spite of the public criticism on executive excess compensation, the high compensation is not always a signal of manipulation, collusion and self-interest. It also can be a signal of individual talents and great efforts. Board secretaries are worth to be highly paid if they can improve firms’ disclosures, thereby reducing the incidence of rumors and reducing the cost of equity capital.

This paper is the first research to examine the effectiveness of compensation contracting based on information providers’ disclosure responsibility in the Chinese context. It documents a positive relation between board secretaries’ excess compensation and corporate disclosure quality.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.

A current technological trend, which has gained even more traction recently due to the COVID-19 pandemic, is the use of augmented reality (AR) in shopping environments. AR is addressing contemporary challenges rooted in online shopping (e.g. in terms of experientiality and try-on) and is fundamentally reshaping consumers' experiences. The purpose of this study is to provide a synthesized and structured overview of the state-of-the-art research focused on AR shopping.

The authors conduct a systematic literature review of the empirical academic corpus focused on shopping via AR technology.

The review reveals the diverse psychological (cognitive, affective, and social) as well as behavioral outcomes related to the use of AR in the shopping context. The authors integrate the results into a framework for AR induced consumer behavior in shopping, thereby providing an important overview of the dynamics in AR-related shopping and the factors influencing the adoption of the technology by consumers. Specifically, the authors encountered that the technological abilities of AR (e.g. in terms of interactivity, vividness, informativeness, etc.) are a source for enhanced utilitarian and hedonic shopping experiences that can support intentions to purchase a product, reuse an AR app, or recommend it to others. Importantly, our review reveals the demand for several avenues for future research.

The authors provide an overview and synthesis of how and where AR is employed in shopping contexts, what theories and technological characteristics of AR are commonly analyzed, and what psychological and behavioral outcomes AR has been found to evoke. Based on our findings, the authors derive a framework that illustrates the dynamics in AR shopping and give an in-depth discourse on 13 future research agenda points related to thematic, theoretical, methodological, and technological matters.