An Efficient Three-Dimensional Coupled Normal Mode Model and Its Application to Internal Solitary Wave Problems

We present an efficient three-dimensional coupled-mode model based on the Fourier synthesis technique. In principle, this model is a one-way model, and hence provides satisfactory accuracy for problems where the forward scattering dominates. At the same time, this model provides an efficiency gain of an order of magnitude or more over two-way coupled-mode models. This model can be applied to three-dimensional range-dependent problems with a slowly varying bathymetry or internal waves. A numerical example of the latter is demonstrated in this work. Comparisons of both accuracy and efficiency between the present model and a benchmark model are also provided.

Dual Frequency Transformer for Efficient SDR-to-HDR Translation

The SDR-to-HDR translation technique can convert the abundant standard-dynamic-range (SDR) media resources to high-dynamic-range (HDR) ones, which can represent high-contrast scenes, providing more realistic visual experiences. While recent vision Transformers have achieved promising performance in many low-level vision tasks, there are few works attempting to leverage Transformers for SDR-to-HDR translation. In this paper, we are among the first to investigate the performance of Transformers for SDR-to-HDR translation. We find that directly using the self-attention mechanism may involve artifacts in the results due to the inappropriate way to model long-range dependencies between the low-frequency and high-frequency components. Taking this into account, we advance the self-attention mechanism and present a dual frequency attention (DFA), which leverages the self-attention mechanism to separately encode the low-frequency structural information and high-frequency detail information. Based on the proposed DFA, we further design a multi-scale feature fusion network, named dual frequency Transformer (DFT), for efficient SDR-to-HDR translation. Extensive experiments on the HDRTV1K dataset demonstrate that our DFT can achieve better quantitative and qualitative performance than the recent state-of-the-art methods. The code of our DFT is made publicly available at https://github.com/CS-GangXu/DFT.

Torque-based Optimal Acceleration Control for Electric Vehicle

The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin＇s maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle（EV） has not been reported. In this paper, the permanent magnet synchronous motor（PMSM） is controlled by the field oriented control（FOC） method and the electric drive system for the EV（including the PMSM, the inverter and the battery） is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming（DP）. This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV＇s acceleration process and the analytical algorithm is easy to be implemented in real-time control.

Deep Gradient Learning for Efficient Camouflaged Object Detection

This paper introduces deep gradient network(DGNet),a novel deep framework that exploits object gradient supervision for camouflaged object detection(COD).It decouples the task into two connected branches,i.e.,a context and a texture encoder.The es-sential connection is the gradient-induced transition,representing a soft grouping between context and texture features.Benefiting from the simple but efficient framework,DGNet outperforms existing state-of-the-art COD models by a large margin.Notably,our efficient version,DGNet-S,runs in real-time(80 fps)and achieves comparable results to the cutting-edge model JCSOD-CVPR21 with only 6.82%parameters.The application results also show that the proposed DGNet performs well in the polyp segmentation,defect detec-tion,and transparent object segmentation tasks.The code will be made available at https://github.com/GewelsJI/DGNet.

Numerical modeling of a linear photonic system for accurate and efficient time-domain simulations

In this paper, a novel modeling and simulation method for general linear, time-invariant, passive photonic devices and circuits is proposed. This technique, starting from the scattering parameters of the photonic system under study, builds a baseband equivalent state-space model that splits the optical carrier frequency and operates at baseband, thereby significantly reducing the modeling and simulation complexity without losing accuracy.Indeed, it is possible to analytically reconstruct the port signals of the photonic system under study starting from the time-domain simulation of the corresponding baseband equivalent model. However, such equivalent models are complex-valued systems and, in this scenario, the conventional passivity constraints are not applicable anymore. Hence, the passivity constraints for scattering parameters and state-space models of baseband equivalent systems are presented, which are essential for time-domain simulations. Three suitable examples demonstrate the feasibility, accuracy, and efficiency of the proposed method.

Efficiency of Model Induction Motor Using Various Non-Oriented Electrical Steels

The performance of a 3-phase 6-pole 400 W inverter-drive induction motor was investigated using a variety of non-oriented electrical steels for stator core at PWM inverter fundamental wave frequencies of 30 to 300 Hz. There existed an optimum Si content of the material depending on the tooth flux density. Both reduction of material thickness and stress-relief annealing of the stator core improved the motor efficiency. The influence of Si content on the efficiency was small at lower PWM frequencies, while at higher frequencies the motor efficiency increased with increasing Si content. The Cu loss WC increased and the Fe loss Wi counteractiveiy decreasedwith increasing Si content at lower frequencies; while at higher frequencies Wi had dominant effect on the efficiency. Newly developed materials RMA, having lower Fe losses after stress-relief annealing and higher flux densities with lower Si contents, showed motor efficiencies superior to conventional J1S grade materials with comparable Fe losses.

Research on image sentiment analysis technology based on sparse representation

Many methods based on deep learning have achieved amazing results in image sentiment analysis.However,these existing methods usually pursue high accuracy,ignoring the effect on model training efficiency.Considering that when faced with large-scale sentiment analysis tasks,the high accuracy rate often requires long experimental time.In view of the weakness,a method that can greatly improve experimental efficiency with only small fluctuations in model accuracy is proposed,and singular value decomposition(SVD)is used to find the sparse feature of the image,which are sparse vectors with strong discriminativeness and effectively reduce redundant information;The authors propose the Fast Dictionary Learning algorithm(FDL),which can combine neural network with sparse representation.This method is based on K-Singular Value Decomposition,and through iteration,it can effectively reduce the calculation time and greatly improve the training efficiency in the case of small fluctuation of accuracy.Moreover,the effectiveness of the proposed method is evaluated on the FER2013 dataset.By adding singular value decomposition,the accuracy of the test suite increased by 0.53%,and the total experiment time was shortened by 8.2%;Fast Dictionary Learning shortened the total experiment time by 36.3%.

Crossing the Growth Threshold： Service-Based Economy, Knowledge Process and Reshaping of Efficiency Model

The transition from middle-income to high-income stage is fraught with risks of growth divergence.Economic transition is clouded by the following possibilities:(1) falling share of industrial sector through industrial depression and weakening growth momentum caused by the large urbanization costs;(2) the subordination of service sector as a result of nearly irreversibly industrial professional,which falters the process of service sector transition and upgrading;(3) inefficient knowledge production allocation and human capital upgrade due to the absence of incentivized compensation of knowledge consumption.We suggest that a country should reshape its efficiency model by upgrading knowledge factor and human capital as the pre-requisite.Given the dilemmas of transition,China should take the factorization trend of service sector and reshape efficiency model through institutional reform,ensuring that service sector will develop in tandem with industrial sector.

Empirical Analysis of Forest Pest Control Efficiency from 2003 to 2014 in China

Three indexes including forest pest occurrence area,control area and input fund of 31 provinces from 2003 to 2014 were selected from Forestry Statistical Yearbook,to establish dynamic interaction index evaluation system with clustering robust regression model and Stata 13. 0 software. Total forest pest control efficiency in China was determined according to the computing result of entropy method. Suggestions such as improving forest pest control efficiency,increasing service efficiency and input amount of forest pest control input funds were put forward. It will provide empirical basis for target management evaluation of forest pest control work and accountability system.

Efficient generation of the mouse model with a defined point mutation through haploid cell-mediated gene editing

Generation of mouse models carrying a defined point mutation,especially disease-related point mutations,is of considerable interest for research in biology and medicine.The standard method based on embryonic stem cell（ESC）-mediated homologous recombination（HR）is time-and labor-consuming.

Simulating dispatchable grid services provided by flexible building loads:State of the art and needed building energy modeling improvements

End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability,reduce costs,and support increased hosting of distributed renewable generation.This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling.We consider services delivered to(1)the high-voitage bulk power system through the coordinated action of many,distributed building loads working together,and(2)targeted support provided to the operation of low-voltage electric distribution grids.Although an exhaustive exploration is not possible,we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling(BEM)tools,suggesting pathways for future research and development.

An efficient absorbing boundary for finite-difference time-domain field modelling in acoustics

A highly efficient absorbing boundary condition suitable for use in the finitedtherence time-domain (FDTD) modelling of acoustic fields is presented in this paper. The new method seeks a least square esthoate of a transfer matrix for field components near truncating boundaries by matrir pseud-inversion. The proposed absorbing boundary is considerably more effective than most ekisting ones. The method is also computationally econondcal and robust.The performance of the new method is shown by numerical experiments on a point-source radiation problem, a wedge dimaction problem, and a scattering problem in which a plane wave is scattered by a circular cylinder.

Experimental study on filtration performance of the moving bed granular filter with axial flow

The filtration performance of the moving bed granular filter with axial flow (MBGF-AF) is investigated through a large cold experiment. The effect of different operation parameters on the filtration performance (collection efficiency, pressure drop) of the axial-flow moving bed filter is investigated in combination with the dust deposition effect and the mechanism of trapping dust by the capturing particles. The results show that the collection efficiency of MBGF-AF is enhanced by decreasing the superficial gas velocity, increasing the inlet dust concentration properly, or decreasing the moving velocity of the capturing particles. A model covering the above operation parameters is established to calculate the collection efficiency of the moving bed granular filter. It is used in a wide range of operating parameters for the MBGFs.

Predicting effect factors of dual bag filter system for PCDD/Fs removal from hazardous waste incineration flue gas

The dual bag filter(DBF)system is a new polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans(PCDD/Fs)emission control technology that has more efficient(PCDD/Fs)removal performance,a higher activated carbon utilization rate and less activated carbon consumption compared with the traditional single bag filter system.Moreover,few studies have been relevant to the mechanism of the PCDD/Fs removal process in the DBF system,and the selection of operating conditions of the DBF system lacks an academic basis.This study established a PCDD/Fs removal efficiency model of activated carbon injection combined bag filter(ACI+DBF)system for hazardous waste incineration flue gas and predicted the crucial effect factors.New adsorption coefficients k_(1)=532,145 Nm^(3)/(mol s)and k_(2)=45 Nm^(3)/(mol s),and the relationship expression between the number of available adsorption positions of recycled AC(AAC′)and cycle times(n)are proposed in the model.The results verify that the model error was below 5%.In addition,the PCDD/Fs removal efficiency model predicts that in a certain range,the PCDD/Fs removal efficiency increases with increasing activated carbon injection concentration.The best cycle number of activated carbon was less than 3,and the ratio of circulating activated carbon to fresh activated carbon in second bag filter(SBF)should be controlled at 7–8.

Model Construction and Numerical Simulation for Hydroplaning of Complex Tread Tires

Euler-Lagrange coupling method is used to establish the fluid-structure interaction model for tires with different tread patterns by obtaining the grounding mark and normal contact force between tire and the road surface during tire rolling.The altering of load force,tire pressure,and water film thickness in relation to the effect on tire-road force during both constant speed and critical hydroplaning speed was analyzed.Results show that the critical hydroplaning speed and normal contact force between tire and the road surface are positively correlated with vehicle load and tire pressure and negatively correlated with water film thickness.Python language is used to develop the pre-processing plug-ins to achieve parametric modeling and rapid creation of Finite Element Analysis(FEA)model to reduce time costs,and the effectiveness of the plug-ins is verified through comparative tests.

中国耕地中低产田空间分布格局及产能提升潜力（英文）

With a continuously increasing population and better food consumption levels, im- proving the efficiency of arable land use and increasing its productivity have become funda- mental strategies to meet the growing food security needs in China. A spatial distribution map of medium- and low-yield cropland is necessary to implement plans for cropland improvement In this study, we developed a new method to identify high-, medium-, and low-yield cropland from Moderate Resolution Imaging Spectroradiometer （MODIS） data at a spatial resolution of 500 m. The method could be used to reflect the regional heterogeneity of cropland productiv- ity because the classification standard was based on the regionalization of cropping systems in China. The results showed that the proportion of high-, medium-, and low-yield cropland in China was 21%, 39%, and 40%, respectively. About 75% of the low-yield cropland was lo- cated in hilly and mountainous areas, and about 53% of the high-yield cropland was located in plain areas. The five provinces with the largest area of high-yield cropland were all located in the Huang-Huai-Hai region, and the area amounted to 42% of the national high-yield cropland area. Meanwhile, the proportion of high-yield cropland was lower than 15% in Hei- Iongjiang, Sichuan, and Inner Mongolia, which had the largest area allocated to cropland in China. If all the medium-yield cropland could be improved to the productive level of high-yield cropland and the low-yield cropland could be improved to the level of medium-yield cropland, the total productivity of the land would increase 19% and 24%, respectively.

Improvement of 3-D FEM Coupled Model on Strip Crown in Hot Rolling

In order to simulate and analyze hot strip crown and flatness accurately and efficiently, the 3-D （three-di- mensional） coupled model involved in RPFEM （rigid-plastic finite element method） is improved based on the analyti- cal model of forecasting rolling force distribution. In the analytical model, variational method is employed to solve the lateral flow of metal and influential function method is employed to calculate roll deflection, the lateral distribution of rolling force can be obtained rapidly by iterative strategy. Then the 3-D coupled model uses the result as initial distri- bution of rolling force to calculate roll deflection and makes the initial on-load roll gap profile close to the final value, so as to reduce iterations and increase efficiency. Compared with previous algorithms, the improved model can reduce the iterations by about 50% and shorten the computing time by about 60% on the basis of the calculation accuracy.

IMPROVEMENTS OF A DISTRIBUTED HYDROLOGY MODEL DHSVM AND ITS CLIMATOLOGICAL-HYDROLOGICAL OFF-LINE SIMULATIONAL EXPERIMENTS

The advanced distributed hydrology-soil-vegetation model DHSVM,developed by Wigmosta et al.(1994)is introduced from US Pacific Northwest National Laboratory.To apply DHSVM in China for the first time some improvements have been made in terms of the basin characteristics: 1)to change evapotranspiration model,using the improved Penman-Monteith approach in place of the original one;2)to change the model structure,inserting datasets from 4 stations to grid cells for each river basin,instead of datasets from one or two stations;3)to develop new hydrology, vegetation and soil parameterization schemes for improving the simulated results,with focus on calculation and adjustment of 11 parameters,such as soil porosity (?),field capacity θ_(fc),leaf area index LAI,stochastic resistance γ_s,among the total 33 parameters.Then the improved DHSVM is driven by observed datasets for Luanhe River Basin and Sanggan River Basin,respectively.The simulated evapotranspiration(ET),runoff,snow water equivalent,water table,soil moisture and percolation are then gained as DHSVM outputs.The simulated ET shows that the highest peak appears in May or June instead of July or August.This is consistent with the real situations, owing to the improvement of ET model.The simulated runoff process and flood peak are quite consistent with the observed ones.The model efficiency values for Luanhe River and Sanggan River Basins are 0.89 and 0.82,respectively,which shows high simulating ability of the model system for both relatively humid and dry basins.

An Analysis of Energy and Environment Efficiency of China＇s Iron and Steel Industry

Due to heavy energy consumption and low technical efficiency, China＇s iron and steel industry is trapped in the dilemma ＂large but not strong＂. This situation not only exerts enormous pressure on energy security but also on increased carbon emission and environmental pollution. The contribution of this study is to calculate the energy and environment efficiency of China＇s iron and steel industry and to analyze the factors affecting this efficiency. An index of energy and environment efficiency is introduced based on Directional Slacks-based Distance Measure Model. This index is adopted to measure the energy and environment efficiency of China＇s iron and steel industry using 2,382 firm observations during 2001 to 2005. In addition, Hierarchy Linear Model （HLM） is applied to analyze the factors which can influence the efficiency with both firm-level and province-level data. The conclusions are as follows： The energy and environment efficiency of China＇s iron and steel industry did not have a significant change during the research period. A firm＇s age, size, ownership, product category and the economy of its province have significant influence on its energy and environment efficiency.

Three-dimensional computational fluid dynamics （volume of fluid） modelling coupled with a stochastic discrete phase model for the performance analysis of an invert trap experimentally validated using field sewer solids

Invert traps are used to trap sewer solids flowing into a sewer drainage system, The performance of the invert trap in an open rectangular channel was experimentally and numerically analysed using field sewer solids collected from a sewer drain. Experiments showed that the free water surface rises over the central opening （slot） of the invert trap, which reduces the velocity near the slot and allows more sediment to be trapped in comparison with the case for the fixed-lid model （assuming closed conduit flow with a shear-free top wall） used by earlier investigators. This phenomenon cannot be modelled using a closed conduit model as no extra space is provided for the fluctuation of the water surface, whereas this space is provided in the volume of fluid （VOF） model in the form of air space in ANSYS Fluent 14.0 software. Additionally, the zero atmospheric pressure at the free water surface cannot be modelled in a fixed-lid model. In the present study, experimental trap efflciencies of the invert trap using field sewer solids were fairly validated using a three-dimensional computational fluid dynamics model （VOF model） coupled with a stochastic discrete phase model. The flow field （i.e., velocities） predicted by the VOF model were compared with experimental velocities obtained employing particle image velocimetry. The water surface profile above the invert trap predicted by the VOF model was found to be in good agreement with the experimentally measured profile. The present study thus showed that the VOF model can be used with the stochastic discrete phase model to well predict the performance of invert traps.