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1 – 4 of 4Yuling Ran, Wei Bai, Lingwei Kong, Henghui Fan, Xiujuan Yang and Xuemei Li
The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three…
Abstract
Purpose
The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three influential factors: moisture content, electrical conductivity and temperature, towards the prediction of soil compaction degree.
Design/methodology/approach
Taking fine-grained soil A and B as the research object, this paper utilized the laboratory test data, including compaction parameter (moisture content), electrical parameter (electrical conductivity) and temperature, to predict soil degree of compaction based on five types of commonly used machine learning models (19 models in total). According to the prediction results, these models were preliminarily compared and further evaluated.
Findings
The Gaussian process regression model has a good effect on the prediction of degree of compaction of the two kinds of soils: the error rates of the prediction of degree of compaction for fine-grained soil A and B are within 6 and 8%, respectively. As per the order, the contribution rates manifest as: moisture content > electrical conductivity >> temperature.
Originality/value
By using moisture content, electrical conductivity, temperature to predict the compaction degree directly, the predicted value of the compaction degree can be obtained with higher accuracy and the detection efficiency of the compaction degree can be improved.
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Keywords
Jianfeng Guo, Xiaohan Yang, Sihang Yao, Fu Gu and Xuemei Zhang
The purpose of this paper is to examine the influences of positive-framed and negative-framed green advertising on pro-environmental WTP. This study also explores the impacts of…
Abstract
Purpose
The purpose of this paper is to examine the influences of positive-framed and negative-framed green advertising on pro-environmental WTP. This study also explores the impacts of regulatory focus, environmental concern and pleasant level on green advertising effectiveness.
Design/methodology/approach
Data are collected from a within-participant between-group online experiment in China. The generalized estimating equation (GEE) is employed to investigate the impact of green advertising on WTP. Grouped regression and mediation analyses are conducted to explore the influences of regulatory focus, environmental concern and pleasure on advertising efficacy.
Findings
The experimental outcomes indicate that green advertising significantly increases participants’ pro-environmental WTP, and negative-framed advertising is more effective than its positive-framed counterpart. Prevention focus heightens receptivity to green advertising, and the relation of environmental concern to advertising effectiveness is inverted U-shaped. Pleasure mediates the effect of green advertising on the WTP, and this mediating role is influenced by emotional intensity when advertising is negatively framed.
Originality/value
Evidence suggests that green advertising may propel pro-environmental WTP by raising environmental awareness, but such a relationship remains severely understudied. As such, this study pioneers in exploring the impact of different-framed green advertising on pro-environmental WTP, extending the concept of green advertising to environmental management. By considering the influences of regulatory focus, environmental concern and pleasure, this study raises practical implications for designing green advertisements, such as increasing the usage of visual elements.
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Chao Li, Jin Gao, Qingqing Xu, Chao Li, Xuemei Yang, Kui Xiao and Xiangna Han
The color painting of ancient buildings has high historical and artistic value but is prone to aging due to long-term outdoor exposure. The purpose of this study is to develop a…
Abstract
Purpose
The color painting of ancient buildings has high historical and artistic value but is prone to aging due to long-term outdoor exposure. The purpose of this study is to develop a new type of sealing coating to mitigate the impact of ultraviolet (UV) light on color painting.
Design/methodology/approach
The new coating was subjected to a 500-h UV-aging test. Compared with the existing acrylic resin Primal AC33, the UV aging behavior of the new coating, such as color difference and gloss, was studied with aging time. The Fourier infrared spectra of the coatings were analyzed after the UV-aging test.
Findings
Compared with AC33, the antiaging performance of SF8 was substantially improved. SF8 has a lower color difference value and better light retention and hydrophobicity. The Fourier transform infrared spectroscopy results showed that the C-F bond and Si-O bonds in the resin of the optimized sealing coating protected the main chain C-C structure from degradation during the aging process; thus, the resin maintained good stability. The hindered amine light stabilizer TN292 added to the coating inhibited the antiaging process by trapping active free radicals.
Originality/value
To address the problem of UV aging of oil-decorated colored paintings, a new type of sealing coating with excellent antiaging properties was developed, laying the foundation for its demonstration application on the surface of ancient buildings.
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Benna Hu, Laifu Wen and Xuemei Zhou
Vertical electrical sounding (VES) and Rayleigh wave exploration are widely used in the exploration of near-surface structure, but both have limitations. This study aims to make…
Abstract
Purpose
Vertical electrical sounding (VES) and Rayleigh wave exploration are widely used in the exploration of near-surface structure, but both have limitations. This study aims to make full use of the advantages of the two methods, reduce the multiple solutions of single inversion and improve the accuracy of the inversion. Thus, a nonlinear joint inversion method of VES and Rayleigh wave exploration based on improved differential evolution (DE) algorithm was proposed.
Design/methodology/approach
Based on the DE algorithm, a new initialization strategy was proposed. Then, taking AK-type with high-velocity interlayer model and HA-type with low-velocity interlayer model near the surface as examples, the inversion results of different methods were compared and analyzed. Then, the proposed method was applied to the field data in Chengde, Hebei Province, China. The stratum structure was accurately depicted and verified by drilling.
Findings
The synthetic data and field data results showed that the joint inversion of VES and Rayleigh wave data based on the improved DE algorithm can effectively improve the interpretation accuracy of the single-method inversion and had strong stability and large generalizable ability in near-surface engineering problems.
Originality/value
A joint inversion method of VES and Rayleigh wave data based on improved DE algorithm is proposed, which can improve the accuracy of single-method inversion.
Details