Performance of global look-up table strategy in digital image correlation with cubic B-spline interpolation and bicubic interpolation

Global look-up table strategy proposed recently has been proven to be an efficient method to accelerate the interpolation, which is the most time-consuming part in the iterative sub-pixel digital image correlation （DIC） algorithms. In this paper, a global look-up table strategy with cubic B-spline interpolation is developed for the DIC method based on the inverse compositional Gauss-Newton （IC-GN） algorithm. The performance of this strategy, including accuracy, precision, and computation efficiency, is evaluated through a theoretical and experimental study, using the one with widely employed bicubic interpolation as a benchmark. The global look-up table strategy with cubic B-spline interpolation improves significantly the accuracy of the IC-GN algorithm-based DIC method compared with the one using the bicubic interpolation, at a trivial price of computation efficiency.

An extended input-output table for environmental and resources accounting

Environmentally Extended Input-Output(EEIO)tables have become a powerful element in supporting information-based environmental and economic policies.National-and provincial-level 10 tables are currently published by the National Bureau of Statistics of the People's Republic of China according to well-defined conventions.However,county-level 10tables are not provided as a rule by official statistics organizations.This paper conducts an overview of compiling EEIO tables for environmental and resources accounting at the county level and then answers several questions:First,what kind of data should be prepared for the compilation of county-level EEIO tables?Second,how can we set up comprehensive EEIO tables at the county level?Third,regarding the survey methods and the indirect modeling,which one should be chosen to build EEIO tables at the county level?Finally,what policy questions could such a table answer?EEIO tables at the county level can be used to predict the economic impacts of environmental policies and to perform trend and scenario analysis.

A Stable Analytical Solution Method for Car-Like Robot Trajectory Tracking and Optimization

In this paper, the car-like robot kinematic model trajectory tracking and control problem is revisited by exploring an optimal analytical solution which guarantees the global exponential stability of the tracking error. The problem is formulated in the form of tracking error optimization in which the quadratic errors of the position, velocity, and acceleration are minimized subject to the rear-wheel car-like robot kinematic model. The input-output linearization technique is employed to transform the nonlinear problem into a linear formulation. By using the variational approach, the analytical solution is obtained, which is guaranteed to be globally exponentially stable and is also appropriate for real-time applications. The simulation results demonstrate the validity of the proposed mechanism in generating an optimal trajectory and control inputs by evaluating the proposed method in an eight-shape tracking scenario.

面向SW26010Pro处理器的全局符号重定位优化

申威异构众核处理器运算核心访问主存的延迟很大,程序中应尽量避免运算核心代码访问主存的操作.全局偏移表存放程序中全局变量和函数的地址,不适合保存在珍稀的运算核心局部存储空间中,并且其访问模式通常比较离散,因而也不适合对其做Cache预取,访问全局偏移表引入的访问主存操作对程序性能影响较大.本文针对异构众核程序静态链接与动态链接的使用场景,分析链接器relaxation优化的使用限制,通过“gp基地址+扩展偏移”的方法实现避免访问主存操作的全局符号重定位优化.实验结果表明,该重定位优化方法能够以增加少量代码为代价,在运算核心代码调用函数与访问全局变量时有效避免访问全局偏移表引入的访问主存的操作,提高众核程序的运行性能.

Exploring the Dynamics of Industrial Convergence Among RCEP Member Countries: An Empirical Study

The evolving dynamics of industrial convergence among the member countries of the Regional Comprehensive Economic Partnership(RCEP)framework have emerged as a significant subject that merits in-depth consideration and analysis.This study initially employs multi-regional input-output(MRIO)data and the social network analysis(SNA)method to delineate the levels and variation trends of this industrial convergence across the RCEP member countries.It then delves into the positive effects of this convergence phenomenon on the trade and investment fields of the member countries.The research findings indicate:(a)In 2006 and 2015,before the implementation of the RCEP,the RCEP member countries displayed a relatively close industrial convergence.The convergence levels exhibited a general upward trend on both the supply and the demand sides,but there were significant disparities in the levels of industrial convergence among the member countries.Furthermore,while the convergence in the three economic sectors showed an increasing trend,the development was uneven across the board.(b)Since the implementation of the RCEP,the trade ties among the member countries within the region have strengthened significantly,and the interplay between the countries’industrial and supply chains has been characterized by high-quality collaboration and demonstrated remarkable resilience.In addition,the convergence in the investment fields of the RCEP member countries and their respective industries has unleashed a wave of positive synergies.These findings offer valuable insights that can serve as a robust foundation for formulating effective policies to advance the growth and prosperity of the RCEP region.

基于响应面法的电动振动台垂直扩展台面优化

针对电动振动台垂直扩展台面一阶垂向共振频率较低的问题,以某垂直扩展台面为研究对象,采用有限元软件建立垂直扩展台面的有限元模型,以空心圆柱内圆半径、裙边高度、裙边至台面中心距离和台面底部安装半径作为优化参数,通过不同的试验设计分别构造响应面拟合的输入矩阵和验证矩阵,最后采用全局响应面法对垂直扩展台面的结构参数进行优化。结果表明,优化后的垂直扩展台面一阶垂向共振频率由2132.98Hz提升至2185.21Hz,从而验证了该优化方法的有效性。该方法对其他台面的优化设计具有一定的参考意义。

基于GlobalMapper的教学三维电子沙盘制作研究

文章利用Global Mapper软件,以新疆天池为例,介绍了如何利用公开免费的地理信息制作三维电子沙盘的简单方法。

Parameterless Pruning Algorithms for Similarity-Weight Network and Its Application in Extracting the Backbone of Global Value Chain

Purpose:With the availability and utilization of Inter-Country Input-Output(ICIO)tables,it is possible to construct quantitative indices to assess its impact on the Global Value Chain(GVC).For the sake of visualization,ICIO networks with tremendous low-weight edges are too dense to show the substantial structure.These redundant edges,inevitably make the network data full of noise and eventually exert negative effects on Social Network Analysis(SNA).In this case,we need a method to filter such edges and obtain a sparser network with only the meaningful connections.Design/methodology/approach:In this paper,we propose two parameterless pruning algorithms from the global and local perspectives respectively,then the performance of them is examined using the ICIO table from different databases.Findings:The Searching Paths(SP)method extracts the strongest association paths from the global perspective,while Filtering Edges(FE)method captures the key links according to the local weight ratio.The results show that the FE method can basically include the SP method and become the best solution for the ICIO networks.Research limitations:There are still two limitations in this research.One is that the computational complexity may increase rapidly while processing the large-scale networks,so the proposed method should be further improved.The other is that much more empirical networks should be introduced to testify the scientificity and practicability of our methodology.Practical implications:The network pruning methods we proposed will promote the analysis of the ICIO network,in terms of community detection,link prediction,and spatial econometrics,etc.Also,they can be applied to many other complex networks with similar characteristics.Originality/value:This paper improves the existing research from two aspects,namely,considering the heterogeneity of weights and avoiding the interference of parameters.Therefore,it provides a new idea for the research of network backbone extraction.

Cumulative Tariff Cost Rate and Structure in the Global Value Chain:A Theoretical and Empirical Study

This paper constructs a more unified measurement framework from the perspective of the Leontief inverse matrix and Ghosh inverse matrix(Ghosh).At the same time,referring to the four-term decomposition method of Leontief inverse matrix in Muradov(2016),this paper analyzes the structural decomposition of the cumulative tariff cost rate.Results show that(1)Overall,from 2000 to 2017,China's cumulative tariff cost rate,direct tariff cost rate,and multi-stage tariff cost rate all showed a downward trend,and the decline was greater than that of other countries(regions).China has strictly fulflled its WTO accession commitments and has greatly reduced the tariff rate on imported intermediate goods.(2)With China's deep participation in the global value chain,the amplification effect of China's tariffs has increased from 2.57 in 2000 to 3.17 in 2017,and there is a certain degree of"amplification effect"(above 1.5)in tariffs in all countries in the world.(3)From the perspective of the contribution rate of various countries in the world,China contributes the most to the global cumulative tariff cost rate,which is due to the complexity of the global production network structure,rather than the excessively high tariff rate imposed by China on imported intermediate goods.In terms of policy implications,if China did not take the initiative to reduce tariffs,the structural changes in the global production network would lead to a larger global cumulative tariff cost rate.

生产性服务业投入与全球价值链位势攀升——基于中国省份制造业面板数据的实证研究

文章基于2014—2020年中国30个省份面板数据,运用引力模型实证检验生产性服务业投入对制造业全球价值链位势的影响,并从二者细分维度进行全面分析。结果表明:生产性服务业投入可显著提升制造业全球价值链位势;从生产性服务业投入类型来看,运输业投入、信息业投入与金融业投入均对制造业全球价值链位势提升具有显著驱动作用;从制造业技术含量高低来看,生产性服务业投入有利于中技术制造业全球价值链位势提升,但对低技术、高技术制造业全球价值链位势提升具有负向抑制作用;从控制变量来看,资本密集程度、企业存续年限、技术水平与劳动生产效率均对制造业全球价值链位势提升具有促进作用。对此,可通过打造示范发展先行区、深化高技术制造业改革、加强信息技术应用水平,为建设制造强国、强化国际竞争力有效赋能。

物联网异构数据库分层访问算法仿真

由于用户及信息量过大,导致物联网异构数据访问时常出现访问结果残缺和数据库访问不完全问题,影响使用者体验感,于是提出DAS模型下物联网异构数据分层访问算法。利用二元时间序列描述异构数据库,得到数据语义状态及特征文本,分析异构分层数据库结构,计算访问信号同时得出多维矢量空间。建立带有三种机构的数据库策略分层,在DAS模型帮助下通过二值独立检索词汇与异构数据库间共现频率,得出数据的相似度。获取大量局部关联表,并将其综合生成全局关联表,综合获取用户想要的内容,实现物联网异构数据分层访问。实验结果表明,所提算法的分层成功概率高和访问命中率高,且访问延时短,给用户带来极佳的使用体验。

Estimation of regional physical imports and exports of EW-MFA in China using monetary input-output tables

Given the statistical gaps in material flow among provinces in China, a method was introduced to estimate regional physical imports and exports （RPIE）, which includes international and interregional imports/ exports. This method uses provincial monetary input- output tables （MIOT） and international trade statistics. A coefficient matrix representing correlations between monetary value and physical mass for years 2000-2009 was obtained based on a detailed commodity classification and 22 material production sectors in MIOT. With the coefficient matrix as reference, RPIE was measured. Pilot calculation of both regional physical trade balance and domestic material consumption, as well as a brief analysis of these methods, were conducted using 2002 data.

Measuring I/O-Production in Digital Economy

According to OECD standards(United Nations,2008),“productivity is commonly defined as a ratio of a volume measure of output to a volume measure of input use”.This ratio indicates how efficiently production inputs,such as labour and capital,are being used in an economy to produce a given level of outputs.Productivity stays aside the main aggregates of national accounts,as the national income(a proxy of GDP),the total output and the circulating capital.Assume the existence of a Leontief-type national Input-Output Table with the vector of total output and the vector of intermediate inputs,situated on its right and lower border.In this paper a measure of capital productivity is proposed.It is called the productiveness,and results from the solution of a boundary value problem,elaborated for Input-Output Tables,involving the vector of total output and the vector of intermediate inputs.

Water consumption and biodiversity:Responses to global emergency events

Given that it was a once-in-a-century emergency event,the confinement measures related to the coronavirus disease 2019(COVID-19)pandemic caused diverse disruptions and changes in life and work patterns.These changes significantly affected water consumption both during and after the pandemic,with direct and indirect consequences on biodiversity.However,there has been a lack of holistic evaluation of these responses.Here,we propose a novel framework to study the impacts of this unique global emergency event by embedding an environmentally extended supply-constrained global multi-regional input-output model(MRIO)into the drivers-pressure-state-impact-response(DPSIR)framework.This framework allowed us to develop scenarios related to COVID-19 confinement measures to quantify country-sector-specific changes in freshwater consumption and the associated changes in biodiversity for the period of 2020-2025.The results suggest progressively diminishing impacts due to the implementation of COVID-19 vaccines and the socio-economic system’s self-adjustment to the new normal.In 2020,the confinement measures were estimated to decrease global water consumption by about 5.7% on average across all scenarios when compared with the baseline level with no confinement measures.Further,such a decrease is estimated to lead to a reduction of around 5% in the related pressure on biodiversity.Given the interdependencies and interactions across global supply chains,even those countries and sectors that were not directly affected by the COVID-19 shocks experienced significant impacts:Our results indicate that the supply chain propagations contributed to 79% of the total estimated decrease in water consumption and 84%of the reduction in biodiversity loss on average.Our study demonstrates that the MRIO-enhanced DSPIR framework can help quantify resource pressures and the resultant environmental impacts across supply chains when facing a global emergency event.Further,we recommend the development of more locally based water conservation measures—to mitigate the effects of trade disruptions—and the explicit inclusion of water resources in post-pandemic recovery schemes.In addition,innovations that help conserve natural resources are essential for maintaining environmental gains in the post-pandemic world.

Using Fundamental Economic Structures to Estimate Chinese Regional Input-Output Tables

The estimation of regional input-output tables is well discussed in the literature and a large variety of methods exist. In this paper we will use the concept of fundamental economic structure （FES） to estimate the matrix of intermediate deliveries for some ＂missing＂ region（s）. Furthermore, the estimates will be compared with the estimates obtained from ＂traditional＂ estimating techniques, including regionalization on the basis of the national table, and borrowing coefficients from similar regions. The results show FES is very helpful for compiling regional tables of China.

大数据环境下多决策表的区间值全局近似约简

在电力大数据中,很多具体的应用如负荷预测、故障诊断都需要依据一段时间内的数据变化来判断所属类别,对某一条数据进行类别判定是毫无意义的.基于此,将区间值粗糙集引入到大数据分类问题中,分别从代数观和信息观提出了基于属性依赖度和基于互信息的区间值启发式约简相关定义和性质证明,并给出相应算法,丰富和发展了区间值粗糙集理论,同时为大数据的分析研究提供了思路.针对大数据的分布式存储架构,又提出了多决策表的区间值全局约简概念和性质证明,进一步给出多决策表的区间值全局约简算法.为了使得算法在实际应用中取得更好的效果,将近似约简概念引入所提的3种算法中,通过对2012上半年某电厂一台600MW的机组运行数据进行稳态判定,验证所提算法的有效性.实验结果表明,所提的3种算法均能在保持较高分类准确率的条件下从对象和属性个数两方面对数据集进行大幅度缩减,从而为大数据的进一步分析处理提供支撑.

青藏高原高寒湿地温室气体释放对水位变化的响应

为了探究水位变化对青藏高原高寒湿地温室气体释放的影响,以高原东部若尔盖典型高寒湿地为研究对象,采用"中型实验生态系"的技术手段,研究了两种不同水位情形[稳定水位(SW,0cm)和波动水位(DW,从0cm下降到45cm,再复原到0cm)]对高寒湿地二氧化碳(CO_2)、甲烷(CH_4)和氧化亚氮(N_2O)三种温室气体释放的影响。结果表明,1)高寒湿地水位变化对土壤(0~10cm)可溶性有机碳(DOC)没有显著影响;水位从0cm下降到45cm,再复原到0cm,对铵态氮(NH_4^+-N)和硝态氮(NO_3^--N)的转化起到了促进作用;2)水位变化对高寒湿地CO_2释放影响不显著,SW和DW处理下CO_2累积释放量分别为235.2和209.7g/m^2;3)水位变化对CH4释放有显著影响,CH4累积释放量从SW处理的1.79g/m^2下降到DW处理的0.86g/m^2,下降了52.18%;4)水位波动处理抑制了N_2O的释放,其在SW和DW条件下的累积释放量分别是6.72和-7.36mg/m^2;5)高寒湿地土壤温度在10℃以上,CO_2和CH_4释放量与其呈显著正相关性,水位下降提高了CO_2和CH4释放与温度的拟合度。

一种基于名誉的P2P网络信任管理模型

由于P2P系统的开放、匿名等特点,节点间的信任关系往往很难通过客观的信任关系建立。本文构建了一种基于实体间交易历史和推荐的信任模型,提出了依据历史交易记录来计算直接信任值的方法,定义了信任推荐和信任聚合两种运算,运用分布式哈希表来处理信任值的存储和查询,并给出了信任咨询和更新的算法。实验表明,该模型可以提供较可靠的信任推荐服务,同时能较好地消除诋毁、恶意推荐等安全问题。

利用查找表的动态载波环路增益控制算法

传统的全球卫星导航接收机,由于跟踪环路带宽是固定的,很难在环路动态性和噪声抑制方面达到平衡。针对该问题,本文提出了一种利用查找表的动态载波环路增益控制算法。该算法根据载体运动场景,以二级等差数列对环路增益调节量变化范围进行非均匀量化,建立环路的增益调节量查找表,实现对环路增益和带宽的动态调节。通过Matlab软件接收机进行了测试,测试结果表明:该算法有较好的动态适应性,能显著减少瞬态信号带来的误差跟踪时间,并能有效抑制噪声,在环路动态性和噪声抑制方面达到了较好的平衡。

一种基于垂直分布的多决策表全局属性核求解算法

针对分布式环境下粗糙集理论研究的重要性,引入全局决策表和局部决策表的概念,并提出一种基于垂直分布的多决策表全局属性核求解算法.该算法可充分利用求得的局部不一致对象和局部差别矩阵,有效提高垂直分布的多决策表全局属性核求解效率.分析结果表明本文算法是有效的,可行的.