In this paper, by constructing a coupling equation, we establish the Harnack type inequalities for stochastic differential equations driven by fractional Brownian motion with Markovian switching. The Hurst parameter H...
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In this paper, by constructing a coupling equation, we establish the Harnack type inequalities for stochastic differential equations driven by fractional Brownian motion with Markovian switching. The Hurst parameter H is supposed to be in(1/2, 1). As a direct application, the strong Feller property is presented.
In this paper,we consider the weighted local polynomial calibration estimation and imputation estimation of a non-parametric function when the data are right censored and the censoring indicators are missing at random...
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In this paper,we consider the weighted local polynomial calibration estimation and imputation estimation of a non-parametric function when the data are right censored and the censoring indicators are missing at random,and establish the asymptotic normality of these *** their applications,we derive the weighted local linear calibration estimators and imputation estimations of the conditional distribution function,the conditional density function and the conditional quantile function,and investigate the asymptotic normality of these ***,the simulation studies are conducted to illustrate the finite sample performance of the estimators.
The three-dimensional variational (3DVar) data assimilation is a critical component of air quality prediction, and the forecast state in air quality prediction is inferred to be approximately low rank and heavily lade...
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Multiple classifier system exhibits strong classification capacity compared with single classifiers,but they require significant computational *** ensemble system aims to attain equivalent or better classification acc...
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Multiple classifier system exhibits strong classification capacity compared with single classifiers,but they require significant computational *** ensemble system aims to attain equivalent or better classification accuracy with fewer ***,current methods fail to identify precise solutions for constructing an ensemble *** this study,we propose an ensemble classifier design technique based on the perturbation binary salp swarm algorithm(ECDPB).Considering that extreme learning machines(ELMs)have rapid learning rates and good generalization ability,they can serve as the basic classifier for creating multiple candidates while using fewer computational ***,we introduce a combined diversity measure by taking the complementarity and accuracy of ELMs into account;it is used to identify the ELMs that have good diversity and low *** addition,we propose an ECDPB with powerful optimizing ability;it is employed to find the optimal subset of *** selected ELMs can then be used to forman ensemble *** on 10 benchmark datasets have been conducted,and the results demonstrate that the proposed ECDPB delivers superior classification capacity when compared with alternative methods.
A simple solvothermal method was used to obtain W-Mo bimetallic oxides from W-Mo alloy scrap,and pure metal powders were also used as the raw materials to simulate *** products had a sea urchin-like structure with abu...
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A simple solvothermal method was used to obtain W-Mo bimetallic oxides from W-Mo alloy scrap,and pure metal powders were also used as the raw materials to simulate *** products had a sea urchin-like structure with abundant oxygen vacancies and the products prepared at low temperatures forms a sosoloid resembling orthorhombic W_(0.4)Mo_(0.6)O_(3).The WMo bimetallic oxide prepared at the reaction temperature of 120℃exhibited excellent selective adsorption performance for methylene blue(MB),which the adsorption rate of MB reached 99%in 12 min and the adsorption rate reached 90%after6 adsorption *** the W-Mo molar ratio is 1:3,the maximum adsorption capacity of sample for MB can reach1148 mg·g^(-1).The adsorption process followed the Langmuir and pseudo-second-order models,which is surface-controlled monolayer *** experimental results show the feasibility of preparing W-Mo bimetal oxide products from pure materials and *** process is simple and effective,which offered a potential approach for secondary resource recycling and reusing.
In this study,spent WO_(3)/V_(2)O_(5)-TiO_(2) catalysts used for selective catalytic reduction were treated by a hydrometallurgical process to comprehensively recover valuable metallic elements,such as W,V,and *** and...
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In this study,spent WO_(3)/V_(2)O_(5)-TiO_(2) catalysts used for selective catalytic reduction were treated by a hydrometallurgical process to comprehensively recover valuable metallic elements,such as W,V,and *** and Si impurities were preferentially removed by selective micro wave-assisted alkali leaching.W and V were leached by enhanced high-pressure leaching with efficiencies estimated at 95% and 81%.The leaching of W and V followed the nuclear shrinkage model controlled by the combination of product layer diffusion and interfacial chemical reaction.A synergistic extraction was applied to separate W and V using an extractant mixture of di-(2-ethylhexyl)phosphoric acid P204 and the primary amine *** extraction efficiencies of V and W reached 86.5% and 6.3%,respectively,with a separation coefficient(V/W) of *** product was precipitated after extraction to yield ammonium paratung state(APT) and NH_(4)VO_(3).The TiO_(2)catalyst carrier residue meets commercial specifications for *** comprehensive recovery process with the characteristics of high-pressure leaching and synergistic extraction realizes the resourceful utilization of the spent catalysts.
The increasing data volume and the demand for real-time transmission highlight the necessity for efficient compression of dynamic point cloud data. Existing methods primarily focus on reducing inter-frame redundancy b...
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Semantic segmentation in the context of 3D point clouds for the railway environment holds a significant economic value,but its development is severely hindered by the lack of suitable and specific ***,the models train...
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Semantic segmentation in the context of 3D point clouds for the railway environment holds a significant economic value,but its development is severely hindered by the lack of suitable and specific ***,the models trained on existing urban road point cloud datasets demonstrate poor generalisation on railway data due to a large domain gap caused by non-overlapping special/rare categories,for example,rail track,track bed *** harness the potential of supervised learning methods in the domain of 3D railway semantic segmentation,we introduce RailPC,a new point cloud *** provides a large-scale dataset with rich annotations for semantic segmentation in the railway ***,RailPC contains twice the number of annotated points compared to the largest available mobile laser scanning(MLS)point cloud dataset and is the first railway-specific 3D dataset for semantic *** covers a total of nearly 25 km railway in two different scenes(urban and mountain),with 3 billion points that are finely labelled as 16 most typical classes with respect to railway,and the data acquisition process is completed in China by MLS *** extensive experimentation,we evaluate the performance of advanced scene understanding methods on the annotated dataset and present a synthetic analysis of semantic segmentation *** on our findings,we establish some critical challenges towards railway-scale point cloud semantic *** dataset is available at https://***/NNU-GISA/GISA-RailPC,and we will continuously update it based on community feedback.
This study used a two-step system generalized method of moments to examine the impact of the business environment in the Belt and Road countries on outward foreign direct investment(OFDI)of China while presenting a de...
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This study used a two-step system generalized method of moments to examine the impact of the business environment in the Belt and Road countries on outward foreign direct investment(OFDI)of China while presenting a deeper investigation into the spatial characteristics of OFDI through a spatial error *** results revealed that the impact mentioned above varies with different investment *** Chinese businesses are motivated by local consumer markets or seeking a human workforce to make an outward direct investment,they will choose countries with poor business *** will select countries with stable business environments for their natural resources or strategic *** spatial agglomeration exists in China's OFDI in the countries and regions along the routes,while substantial evidence is absent on the business environment investment effect with different ***,relevant recommen-dations concluded according to the study.
Given a multivariate quasi-interpolation operator with the partition of unity property,we propose a method to raise the accuracy with simple knots. The resulting operators possess higher accuracy while not requiring a...
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Given a multivariate quasi-interpolation operator with the partition of unity property,we propose a method to raise the accuracy with simple knots. The resulting operators possess higher accuracy while not requiring any derivative information of the underlying function. On that basis, we improve the multivariate spline quasi-interpolants with higher accuracy over type-2triangulations. Moreover, we apply the improved quasi-interpolants to simulate time developing partial differential equations(PDEs). The numerical experiments verify the efficiency of the proposed methods.
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