A Loss-model-based Efficiency Optimization Control Method for Induction Traction System of High-speed Train under Emergency Self-propelled Mode

Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link voltage and the traction power of the motor are significantly reduced, resulting in decreased traction efficiency due to the low load and low speed operations. Aiming to tackle this problem, a novel efficiency improved control method is introduced to the emergency mode of high-speed train traction system in this paper. In the proposed method, a total loss model of induction motor considering the behaviors of both iron and copper loss is established. An improved iterative algorithm with decreased computational burden is then introduced, resulting in a fast solving of the optimal flux reference for loss minimization at each control period. In addition, considering the parameter variation problem due to the low load and low speed operations, a parameter estimation method is integrated to improve the controller's robustness. The effectiveness of the proposed method on efficiency improvement at low voltage and low load conditions is demonstrated by simulated and experimental results.

Low rank optimization for efficient deep learning:making a balance between compact architecture and fast training

Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices,and it is not environmental-friendly with much power cost.In this paper,we focus on low-rank optimization for efficient deep learning techniques.In the space domain,DNNs are compressed by low rank approximation of the network parameters,which directly reduces the storage requirement with a smaller number of network parameters.In the time domain,the network parameters can be trained in a few subspaces,which enables efficient training for fast convergence.The model compression in the spatial domain is summarized into three categories as pre-train,pre-set,and compression-aware methods,respectively.With a series of integrable techniques discussed,such as sparse pruning,quantization,and entropy coding,we can ensemble them in an integration framework with lower computational complexity and storage.In addition to summary of recent technical advances,we have two findings for motivating future works.One is that the effective rank,derived from the Shannon entropy of the normalized singular values,outperforms other conventional sparse measures such as the?_1 norm for network compression.The other is a spatial and temporal balance for tensorized neural networks.For accelerating the training of tensorized neural networks,it is crucial to leverage redundancy for both model compression and subspace training.

eQUEST Based Building Energy Modeling Analysis for Energy Efficiency of Buildings

Building energy performance is a function of numerous building parameters.In this study,sensitivity analysis on twenty parameters is performed to determine the top three parameters that have the most significant impact on the energy performance of buildings.Actual data from two fully operational commercial buildings were collected and used to develop a building energy model in the Quick Energy Simulation Tool(eQUEST).The model is calibrated using the Normalized Mean Bias Error(NMBE)and Coefficient of Variation of Root Mean Square Error(CV(RMSE))method.The model satisfies the NMBE and CV(RMSE)criteria set by the American Society of Heating,Refrigeration,and Air-Conditioning(ASHRAE)Guideline 14,Federal Energy Management Program(FEMP),and International Performance Measurement and Verification Protocol(IPMVP)for building energy model calibration.The values of the parameters are varied in two levels,and then the percentage change in output is calculated.Fractional factorial analysis on eight parameters with the highest percentage change in energy performance is performed at two levels in a statistical software JMP.For building A,the top 3 parameters from the percentage change method are:Heating setpoint,cooling setpoint and server room.From fractional factorial design,the top 3 parameters are:heating setpoint(p-value=0.00129),cooling setpoint(p-value=0.00133),and setback control(p-value=0.00317).For building B,the top 3 parameters from both methods are:Server room(pvalue=0.0000),heating setpoint(p-value=0.00014),and cooling setpoint(p-value=0.00035).If the best values for all top three parameters are taken simultaneously,energy efficiency improves by 29%for building A and 35%for building B.

High Efficient Methods of Content-based 3D Model Retrieval

Content-based 3D model retrieval is of great help to facilitate the reuse of existing designs and to inspire designers during conceptual design. However, there is still a gap to apply it in industry due to the low time efficiency. This paper presents two new methods with high efficiency to build a Content-based 3D model retrieval system. First, an improvement is made on the ＂Shape Distribution （D2）＂ algorithm, and a new algorithm named ＂Quick D2＂ is proposed. Four sample 3D mechanical models are used in an experiment to compare the time cost of the two algorithms. The result indicates that the time cost of Quick D2 is much lower than that of D2, while the descriptors extracted by the two algorithms are almost the same. Second, an expandable 3D model repository index method with high performance, namely, RBK index, is presented. On the basis of RBK index, the search space is pruned effectively during the search process, leading to a speed up of the whole system. The factors that influence the values of the key parameters of RBK index are discussed and an experimental method to find the optimal values of the key parameters is given. Finally, ＂3D Searcher＂, a content-based 3D model retrieval system is developed. By using the methods proposed, the time cost for the system to respond one query online is reduced by 75% on average. The system has been implemented in a manufacturing enterprise, and practical query examples during a case of the automobile rear axle design are also shown. The research method presented shows a new research perspective and can effectively improve the content-based 3D model retrieval efficiency.

Prediction of efficient outputs based on GM(1,N) model and weak DEA efficiency

This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.

Efficient Mass Transport and Electrochemistry Coupling Scheme for Reliable Multiphysics Modeling of Planar Solid Oxide Fuel Cell Stack

A multiphysics model for a production scale planar solid oxide fuel cell （SOFC） stack is important for the SOFC technology, but usually requires an unpractical amount of computing resource. The major cause for the huge computing resource requirement is identified as the need to solve the cathode O2 transport and the associated electrochemistry. To overcome the technical obstacle, an analytical model for solving the O2 transport and its coupling with the electrochemistry is derived. The analytical model is used to greatly reduce the numerical mesh complexity of a multiphysics model. Numerical test shows that the analytical approximation is highly accurate and stable. A multiphysics numerical modeling tool taking advantage of the analytical solution is then developed through Fluent@. The numerical efficiency and stability of this modeling tool are further demonstrated by simulating a 30- cell stack with a production scale cell size. Detailed information about the stack performance is revealed and briefly discussed. The multiphysics modeling tool can be used to guide the stack design and select the operating parameters.

Evaluation of Green Development Efficiency in Chongqing Municipality Based on Super-SBM and Malmquist Models

The green development of Chongqing municipality is crucial in establishing a major ecological shield in the upper reaches of the Yangtze River.By developing a Super-SBM model and using the Malmquist index to analyze and calculate the green development efficiency and its influencing factors in Chongqing from 2011 to 2021,this study reveals an accelerating trend in the overall green development efficiency in Chongqing.The significant enhancement of green development efficiency in Chongqing is primarily attributed to changes in returns to scale.Pure technical efficiency and technological advancements have a considerable potential impact on improving green development efficiency in Chongqing.Furthermore,there are discernible disparities in green development efficiency among districts and counties in Chongqing,with different factors influencing these variations.Chongqing is suggested to promote clean and efficient energy utilization,bolster the application and commercialization of scientific and technological advancements,consistently advance ecological restoration and management,and elevate the quality of green development to a higher level.

Calculating the shading reduction coefficient of photovoltaic system efficiency using the anisotropic sky scattering model

The front-row shading reduction coefficient is a key parameter used to calculate the system efficiency of a photovoltaic(PV)power station.Based on the Hay anisotropic sky scattering model,the variation rule of solar radiation intensity on the surface of the PV array during the shaded period is simulated,combined with the voltage-current characteristics of the PV modules,and the shadow occlusion operating mode of the PV array is modeled.A method for calculating the loss coefficient of front shadow occlusion based on the division of the PV cell string unit and Hay anisotropic sky scattering model is proposed.This algorithm can accurately evaluate the degree of influence of the PV array layout,wiring mode,array spacing,PV module specifications,and solar radiation on PV power station system efficiency.It provides a basis for optimizing the PV array layout,reducing system loss,and improving PV system efficiency.

Evaluation and Influencing Factors of Urban Renewal Efficiency Based on SBM Model:A Case Study of the First Batch of Pilot Cities for Urban Renewal

China is already in the second half of the urbanization process,which means that the urbanization path in China needs to shift from“large-scale expansion development”in the past to“comprehensive and refined operation”.To explore how to efficiently carry out urban renewal work,from the perspective of urban renewal efficiency,the first batch of pilot cities for urban renewal released by the Ministry of Housing and Urban Development in 2021 are selected as the objects.And the SBM model and Malmquist index are used to calculate and analyze their urban renewal efficiency.The results indicate that among the 20 pilot cities,Beijing,Tangshan,Suzhou,Tongling,and Jingdezhen are of high grade,and Hohhot,Xiamen,Huangshi,and Yinchuan are of medium grade,while the rest of the cities are of low grade.The regression results of the Tobit model indicate that population density,real estate investment,and regional economic development level are the main influencing factors of urban renewal.Finally,constructive suggestions are proposed for urban renewal from four aspects:concept,technology,real estate,and policy.

Low organic matter abundance and highly efficient hydrocarbon generation of saline source rock in the Qaidam Basin,NW China

The geochemical analysis and experimental simulation are comprehensively used to systematically study the hydrocarbon generation material,organic matter enrichment and hydrocarbon generation model of Paleogene source rock in the Western Qaidam Depression,Qaidam Basin,NW China.Three main factors result in low TOC values of saline lacustrine source rock of the Qaidam Basin:relatively poor nutrient supply inhibits the algal bloom,too fast deposition rate causes the dilution of organic matter,and high organic matter conversion efficiency causes the low residual organic carbon.For this type of hydrogen-rich organic matter,due to the reduction of organic carbon during hydrocarbon generation,TOC needs to be restored based on maturity before evaluating organic matter abundance.The hydrocarbon generation of saline lacustrine source rocks of the Qaidam Basin is from two parts:soluble organic matter and insoluble organic matter.The soluble organic matter is inherited from organisms and preserved in saline lacustrine basins.It generates hydrocarbons during low-maturity stage,and the formed hydrocarbons are rich in complex compounds such as NOS,and undergo secondary cracking to form light components in the later stage;the hydrocarbon generation model of insoluble organic matter conforms to the traditional“Tissot”model,with an oil generation peak corresponding to Ro of 1.0%.

How Does Urban Shrinkage Affect Land Use Efficiency?A Case Study of Shrinking Cities in Northeast China

The effect of urban shrinkage has gradually become a new topic.Theoretically,urban shrinkage may exert great influence on land use efficiency(LUE)through various urban subsystems,but there is currently limited research examining these pathways.Using the Super-SBM-Undesirable model and the Structural Equation Model(SEM),this study calculates the LUE of shrinking cities in Northeast China and simulates the process of urban shrinkage affecting LUE.To quantify the process of urban shrinkage affecting LUE,three mediation variables,namely the economy,public services,and innovation,are used as latent variables to apply SEM.The results show that urban shrinkage will affect LUE through a direct path and indirect paths.In the direct path,urban shrinkage leads to an improvement in LUE.In the indirect paths,the economy and innovation will transmit the negative effect of urban shrinkage on LUE,while public services will reverse this effect.An important contribution of this study is that it quantifies the paths of urban shrinkage affecting LUE,thereby expanding the understanding of urban shrinkage effect and laying a foundation for the sustainable development of shrinking cities.

Maximum initial primary wave model for low-Froude-number reservoir landslides based on wave theory

The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking the Shuipingzi 1#landslide that occurred in the Baihetan Reservoir area of the Jinsha River in China as an engineering example,this study established a large-scale physical model(with dimensions of 30 m×29 m×3.5 m at a scale of 1:150)and conducted scaled experiments on 3D landslide-induced impulse waves.During the process in which a sliding mass displaced and compressed a body of water to generate waves,the maximum initial wave amplitude was found to be positively correlated with the sliding velocity and the volume of the landslide.With the increase in the water depth,the wave amplitude initially increased and then decreased.The duration of pressure exertion by the sliding mass at its maximum velocity directly correlated with an elevated wave amplitude.Based on the theories of low-amplitude waves and energy conservation,while considering the energy conversion efficiency,a predictive model for the initial wave amplitude was derived.This model could fit and validate the functions of wavelength and wave velocity.The accuracy of the initial wave amplitude was verified using physical experiment data,with a prediction accuracy for the maximum initial wave amplitude reaching 90%.The conversion efficiency(η)directly determined the accuracy of the estimation formula.Under clear conditions for landslide-induced impulse wave generation,estimating the value ofηthrough analogy cases was feasible.This study has derived the landslide-induced impulse waves amplitude prediction formula from the standpoints of wave theory and energy conservation,with greater consideration given to the intrinsic characteristics in the formation process of landslide-induced impulse waves,thereby enhancing the applicability and extensibility of the formula.This can facilitate the development of empirical estimation methods for landslide-induced impulse waves toward universality.

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.

Are cities greener because of innovation?Independent innovation policy and green economic efficiency

The national independent innovation demonstration zone(NIIDZ)is an independent innovation policy that plays a crucial role in implementing strategies.Given the importance of the NIIDZ,this study uses panel data of 278 prefecture-level cities in China from 2006 to 2020 and empirically examines the effect and internal mechanism of the NIIDZ on green economic efficiency(GEE)using the difference-in-difference model(DID).The results show that the NIIDZ effectively enhances the growth of GEE,and the results remain valid through several robustness tests,such as year-by-year propensity score matching.The transmission mechanism suggests that the NIIDZ indirectly drives GEE by accelerating scientific and technological investment,promoting talent concentration,and optimizing the industrial structure.Moreover,heterogeneity analysis reveals that the promotion effect of the NIIDZ on GEE is more prominent in the eastern region and high green development level areas.The study’s findings can serve as a reference for China to further utilize the policy effectiveness of the NIIDZ and accelerate the high-quality development of the green economy in the future.

DPAL-BERT:A Faster and Lighter Question Answering Model

Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems.However,with the constant evolution of algorithms,data,and computing power,the increasing size and complexity of these models have led to increased training costs and reduced efficiency.This study aims to minimize the inference time of such models while maintaining computational performance.It also proposes a novel Distillation model for PAL-BERT(DPAL-BERT),specifically,employs knowledge distillation,using the PAL-BERT model as the teacher model to train two student models:DPAL-BERT-Bi and DPAL-BERTC.This research enhances the dataset through techniques such as masking,replacement,and n-gram sampling to optimize knowledge transfer.The experimental results showed that the distilled models greatly outperform models trained from scratch.In addition,although the distilled models exhibit a slight decrease in performance compared to PAL-BERT,they significantly reduce inference time to just 0.25%of the original.This demonstrates the effectiveness of the proposed approach in balancing model performance and efficiency.

The heterogeneous impact of China-Europe railway express on the efficiency of logistics industry in node cities

Purpose-The spatiotemporal compression effect of China-Europe Railway Express(CR-Express)can reduce the filow costs of resources between China's node cities.Additionally,it can break through the limitations of low-added-value marine products,significantly impacting the logistics industry efficiency.However,there are few literature verifying and analyzing its heterogeneity.This study explores the impact of CR-Express on the efficiency of logistics industry in node cities and analyzes the heterogeneity.Design/methodology/approach-First,this study uses panel data to measure the efficiency of node city logistics industry.Secondiy,this study discusses the impact of the opening of CR-Express on the efficiency of logistics industry in node cities based on the multi-period differential model.Finally,according to the node city difference,the sample city experimental group is grouped for heterogeneity analysis.Findings-The results show that CR-Express can promote the urban logistics industry efficiency,with an average effect of 4.55%.According to the urban characteristics classification,the heterogeneity analysis shows that the efficiency improvement effect of logistics industry in inland cities is more obvious.The improvement effect of node cities and central cities in central and western China is stronger,especially in the sample of megacities and type I big cities.Compared with non-value chain industrial products,the CR-Express has significant promotion effects on the logistics efficiency of the cities where main goods are value chain products.Originality/value-Under the background of double cycle development,this paper can provide a scientific basis for the investment benefit evaluation of CR-Express construction and the follow-up route planning.

High Yield and Efficient Cultivation Techniques of Rice under Rice- fish Intergrowth Model in Chengdu

The integrated planting and breeding of paddy fields is a kind of eco-planting and breeding mode which makes rice and aquatic animals benefit from each other,greatly reducing the harm of rice pests and diseases,using less or even no fertilizers or pesticides,greatly reducing the agricultural non-point source pollution,thus achieving the " multiple use of water,multiple harvests in one field,grain and fishing winwin,ecological and high efficient use. " In this paper,the high yield and efficient cultivation techniques of rice under the rice-fish intergrowth model in Chengdu was introduced from the aspects of selecting good paddy fields for fishing,using appropriate rice varieties,soaking disinfection,timely sowing and nurturing strong seedlings,reasonable close planting,reasonable fertilization,scientific water management,scientific pest control and rice harvests.

A Study of the Impact of the Digital Economy on the Efficiency of Urban Green Economy--Based on the Yangtze River Delta City Cluster

This paper adopts the non-expected output-super-efficiency SBM(Slacks-Based Model)model and principal component analysis to calculate the green economy efficiency and the digital economy level of 27 prefecture-level cities in China’s Yangtze River Delta urban agglomeration between 2011 and 2019,respectively,and examines the impact of the digital economy on the green economy efficiency by using benchmark regression and mechanism analysis.The findings show that,first,the digital economy has a significant contribution to the green economic efficiency of cities,and this conclusion still holds after robustness tests such as replacing explanatory and interpreted variables and introducing province-fixed effects.Second,through the mechanism test,it is found that the digital economy can indirectly promote urban green economic efficiency through the positive mechanism effect of promoting industrial structure upgrading.

Efficient Energy-Aware Resource Management Model(EEARMM)Based Dynamic VM Migration

In cloud environment,an efficient resource management establishes the allocation of computational resources of cloud service providers to the requests of users for meeting the user’s demands.The proficient resource management and work allocation determines the accomplishment of the cloud infrastructure.However,it is very difficult to persuade the objectives of the Cloud Service Providers(CSPs)and end users in an impulsive cloud domain with random changes of workloads,huge resource availability and complicated service policies to handle them,With that note,this paper attempts to present an Efficient Energy-Aware Resource Management Model(EEARMM)that works in a decentralized manner.Moreover,the model involves in reducing the number of migrations by definite workload management for efficient resource utilization.That is,it makes an effort to reduce the amount of physical devices utilized for load balancing with certain resource and energy consumption management of every machine.The Estimation Model Algorithm(EMA)is given for determining the virtual machine migration.Further,VM-Selection Algorithm(SA)is also provided for choosing the appropriate VM to migrate for resource management.By the incorporation of these algorithms,overloading of VM instances can be avoided and energy efficiency can be improved considerably.The performance evaluation and comparative analysis,based on the dynamic workloads in different factors provides evidence to the efficiency,feasibility and scalability of the proposed model in cloud domain with high rate of resources and workload management.

Efficient model building in active appearance model for rotated face

This paper proposes the efficient model building in active appearance model(AAM) for the rotated face.Finding an exact region of the face is generally difficult due to different shapes and viewpoints.Unlike many papers about the fitting method of AAM,this paper treats how images are chosen for fitting of the rotated face in modelling process.To solve this problem,databases of facial rotation and expression are selected and models are built using Procrustes method and principal component analysis(PCA).These models are applied in fitting methods like basic AAM fitting,inverse compositional alignment(ICA),project-out ICA,normalization ICA,robust normalization inverse compositional algorithm(RNIC)and efficient robust normalization algorithm(ERN).RNIC and ERN can fit the rotated face in images efficiently.The efficiency of model building is checked using sequence images made by ourselves.