274 research outputs found
How a “China-made” label influences Chinese Youth’s product evaluation: The priming effect of patriotic and nationalistic news
No full textThis study is to verify whether and how a “China-made” label can influence online consumers’ product evaluation
as adding labels to highlight products’ attributes has become an acquainted measure online by e-tailers/
firms to attract online consumers’ attentions. For this purpose, we conduct a 2 (label of “China-made” vs. no
label) x 3 (patriotism priming vs. nationalism priming vs. no priming) between-subject factorial design to verify
hypotheses. The results reveal that when consumers’ nationalism is primed, the label significantly enhances the
product evaluation by increasing the perceived social value of the product. Priming consumers’ patriotism, on
the other hand, does not play a moderating role for this effect. A follow-up study confirms such effects for both
low involvement and high involvement products. Therefore, e-tailers/firms that own China-made brands/
products are advised to signal the “Chinese identity” of their products to online consumers under the current
circumstance when nationalism and domestic brands are rising in China. The results also indicate that although
products produced in a developing country are marked with a negative country of origin effect, marketers can
turn it into a strength in marketing in certain conditions
Data-driven and physics-informed Bayesian learning of spatiotemporally varying consolidation settlement from sparse site investigation and settlement monitoring data
No full textA digital twin of a geotechnical project (e.g., a reclamation or ground improvement project) is a virtual model that aims to continuously learn from actual observations (e.g., site investigation and monitoring data) and improve model prediction (e.g., spatiotemporally varying consolidation settlement). However, real geotechnical observation data obtained from a site are often spatially sparse (e.g., site investigation data) and spatiotemporally varying (e.g., settlement monitoring data). The sparse and spatiotemporally varying data pose great challenges for continuous learning of data and improvement in model prediction. To address these challenges, this study proposes a novel data-driven and physics-informed Bayesian learning framework that automatically develops ground models from spatially sparse site investigation data, performs geotechnical analysis, and integrates geotechnical analysis results with limited, but spatiotemporally varying, settlement monitoring data to improve model prediction in a systematic and quantitative manner. The proposed method contains three key components, (1) data-driven ground modeling by Bayesian compressive sampling (BCS) using sparse site investigation data as input, (2) finite element modeling (FEM) of consolidation settlement that incorporates domain knowledge, and (3) Bayesian sparse dictionary learning of settlement monitoring data together with FEM results. The proposed method is illustrated using a real ground improvement project, and the results show that the proposed approach performs well.</p
APPLICATION OF GEOSTATISTICS IN THE ESTIMATION OF SUJISHAN GRAPHITE DEPOSITS, MONGOLIA
No full textIn this paper, the author used mine 3D software to establish the 3D geological model of Sujishan Graphite deposit, and applied geostatistics to estimate the resource, offered references for next exploration and mining. Surpac was used to set up geological database of Sujishan Graphite deposit, topographical DTM, ore body model and grade model, 3D of drilling database, also analysis the spatial grade distribution in reality. Based on geostatistics, drilling samples are composited and statistically analysed and eliminate the impact of outliers. Experimental variograms were constructed for the striking, dipping and vertical directions. Grade and resource are estimated by ordinary kriging. Comparing to the traditional estimation methods, this 3D software gives reliable estimation, which provides references for dynamic management of mine's resource
How a “China-made” label influences Chinese Youth's product evaluation: The priming effect of patriotic and nationalistic news
No full textThis study is to verify whether and how a “China-made” label can influence online consumers' product evaluation as adding labels to highlight products' attributes has become an acquainted measure online by e-tailers/firms to attract online consumers' attentions. For this purpose, we conduct a 2 (label of “China-made” vs. no label) x 3 (patriotism priming vs. nationalism priming vs. no priming) between-subject factorial design to verify hypotheses. The results reveal that when consumers' nationalism is primed, the label significantly enhances the product evaluation by increasing the perceived social value of the product. Priming consumers’ patriotism, on the other hand, does not play a moderating role for this effect. A follow-up study confirms such effects for both low involvement and high involvement products. Therefore, e-tailers/firms that own China-made brands/products are advised to signal the “Chinese identity” of their products to online consumers under the current circumstance when nationalism and domestic brands are rising in China. The results also indicate that although products produced in a developing country are marked with a negative country of origin effect, marketers can turn it into a strength in marketing in certain conditions.publishedVersio
How a "China-made" label influences Chinese Youth's product evaluation : the priming effect of patriotic and nationalistic news
No full textAbstract: This study is to verify whether and how a "China-made" label can influence online consumers' product evaluation as adding labels to highlight products' attributes has become an acquainted measure online by e-tailers/ firms to attract online consumers' attentions. For this purpose, we conduct a 2 (label of "China-made" vs. no label) x 3 (patriotism priming vs. nationalism priming vs. no priming) between-subject factorial design to verify hypotheses. The results reveal that when consumers' nationalism is primed, the label significantly enhances the product evaluation by increasing the perceived social value of the product. Priming consumers' patriotism, on the other hand, does not play a moderating role for this effect. A follow-up study confirms such effects for both low involvement and high involvement products. Therefore, e-tailers/firms that own China-made brands/ products are advised to signal the "Chinese identity" of their products to online consumers under the current circumstance when nationalism and domestic brands are rising in China. The results also indicate that although products produced in a developing country are marked with a negative country of origin effect, marketers can turn it into a strength in marketing in certain conditions
Real-time model updating and prediction of three-dimensional time-varying consolidation settlement using machine learning
No full textThe development of digital twins for geotechnical structures necessitates the real-time updates of three-dimensional (3D) virtual models (e.g. numerical finite element method (FEM) model) to accurately predict time-varying geotechnical responses (e.g. consolidation settlement) in a 3D spatial domain. However, traditional 3D numerical model updating approaches are computationally prohibitive and therefore difficult to update the 3D responses in real time. To address these challenges, this study proposes a novel machine learning framework called sparse dictionary learning (T-3D-SDL) for real-time updating of time-varying 3D geotechnical responses. In T-3D-SDL, a concerned dataset (e.g. time-varying 3D settlement) is approximated as a linear superposition of dictionary atoms generated from 3D random FEM analyses. Field monitoring data are then used to identify non-trivial atoms and estimate their weights within a Bayesian framework for model updating and prediction. The proposed approach enables the real-time update of temporally varying settlements with a high 3D spatial resolution and quantified uncertainty as field monitoring data evolve. The proposed approach is illustrated using an embankment construction project. The results show that the proposed approach effectively improves settlement predictions along temporal and 3D spatial dimensions, with minimal latency (e.g. within minutes), as monitoring data appear. In addition, the proposed approach requires only a reasonably small number of 3D FEM model evaluations, avoids the use of widely adopted yet often criticized surrogate models, and effectively addresses the limitations (e.g. computational inefficiency) of existing 3D model updating approaches.</p
Theoretical Studies of the Electron Paramagnetic Resonance Parameters and Local Structure for VO<sup>2+</sup>in Oxyfluoroborate Glasses
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