To evaluate and improve the real-time performance of Ethernet for plant automation（EPA） industrial Ethernet,the real-time performance of EPA periodic data transmission was theoretically and experimentally studied.By...To evaluate and improve the real-time performance of Ethernet for plant automation（EPA） industrial Ethernet,the real-time performance of EPA periodic data transmission was theoretically and experimentally studied.By analyzing information transmission regularity and EPA deterministic scheduling mechanism,periodic messages were categorized as different modes according to their entering-queue time.The scheduling characteristics and delivery time of each mode and their interacting relations were studied,during which the models of real-time performance of periodic information transmission in EPA system were established.On this basis,an experimental platform is developed to test the delivery time of periodic messages transmission in EPA system.According to the analysis and the experiment,the main factors that limit the real-time performance of EPA periodic data transmission and the improvement methods were proposed.展开更多
In this paper, we study the large time behavior of solutions of the parabolic semilinear equation δtu-div（a（x）△↓u） = -｜u｜^αu in （0,∞） × R^N, where α 〉 0 is constant and a∈ Cb^1（R^N） is a symmetr...In this paper, we study the large time behavior of solutions of the parabolic semilinear equation δtu-div（a（x）△↓u） = -｜u｜^αu in （0,∞） × R^N, where α 〉 0 is constant and a∈ Cb^1（R^N） is a symmetric periodic matrix satisfying some ellipticity assumptions.Considering an integrable initial data u0 and α ∈ （2/N, 3/N）, we prove that the large time behavior of solutions is given by the solution U（t, x） of the homogenized linear problem δtU-div（a^h△↓U）=0,U（0） = C, where a^h is the homogenized matrix of a（x）, C is a positive constant and δ is the Dirac measure at 0.展开更多
自动驾驶与仿真场景中遍布带周期特征的数据,其环面拓扑让常规聚类算法容易把簇割断,效率也随之下滑。针对这一痛点,文章提出周期性聚类(Periodic-Density-Based Spatial Clustering of Applications with Noise,P-DBSCAN)。该算法用最...自动驾驶与仿真场景中遍布带周期特征的数据,其环面拓扑让常规聚类算法容易把簇割断,效率也随之下滑。针对这一痛点,文章提出周期性聚类(Periodic-Density-Based Spatial Clustering of Applications with Noise,P-DBSCAN)。该算法用最短环绕距离精确定义周期邻域,经验证可消除簇的错误分割,同时维持近线性时间复杂度,为海量周期数据提供了既精准又高效的解析手段。展开更多
The advent of the era of big data has caused paradigm changes in translation studies,and the combination of big data technology and thinking with translation studies has further interdisciplinaryized translation studi...The advent of the era of big data has caused paradigm changes in translation studies,and the combination of big data technology and thinking with translation studies has further interdisciplinaryized translation studies and presented characteristics such as quantification,expansion of research horizon and scale.Scholars should pay attention to the prospect of translation studies while paying attention to corpus translation studies:the shift of research in text patterns;the spatial turn of and media integration of translation studies.In the process of translatology research in the era of big data,the limitations of digital technology and big data research are also noted.展开更多
We use wavelet transform to analyze the daily relative sunspot number series over solar cycles 10-23. The characteristics of some of the periods shorter than - 600-day are discussed. The results exhibit not only the v...We use wavelet transform to analyze the daily relative sunspot number series over solar cycles 10-23. The characteristics of some of the periods shorter than - 600-day are discussed. The results exhibit not only the variation of some short periods in the 14 solar cycles but also the characteristics and differences around solar peaks and valley years. The short periodic components with larger amplitude such as ～27, ～ 150 and ～360-day are obvious in some solar cycles, all of them are time-variable, also their lengths and amplitudes are variable and intermittent in time. The variable characteristics of the periods are rather different in different solar cycles.展开更多
In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors(i.e., seasons, pollut...In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors(i.e., seasons, pollution periods and airflow directions), through a case study in Beijing from 2013 to 2016. The results showed that the annual mean concentrations(MC) of PM_(2.5), SO_2, NO_2 and CO had decreased with annual mean ratios of 7.5%, 28.6%, 4.6%and 15.5% from 2013 to 2016, respectively. Among seasons, the MC in winter contributed the largest fractions(25.8%～46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation(IMCV) of PM_(2.5) and NO2. For different pollution periods, gradually increase of frequency of S-1(PM_(2.5), 0～ 75 μg/m^3) made S-1 become the largest contributor(28.8%) to the MC of PM_(2.5) in 2016, it had a negative contribution(-13.1%) to the IMCV of PM_(2.5); obvious decreases of frequencies of heavily polluted and severely polluted dominated(44.7% and 39.5%) the IMCV of PM_(2.5). For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease(22.5%～62.5%), and those decrease contributed most to the IMCV of PM_(2.5)(143.3%),SO2(72.0%), NO_2(55.5%) and CO(190.3%); the west airflow had negative influences to the IMCV of PM_(2.5), NO_2 and CO. The framework is helpful for further analysis and utilization of the large amounts of monitoring data; and the analysis results can provide scientific supports for the formulation or adjustment of further air pollution mitigation policy.展开更多
基金Supported by the National High Technology Research and Development Program of China (2006AA040301-4,2007AA041301-6)
文摘To evaluate and improve the real-time performance of Ethernet for plant automation（EPA） industrial Ethernet,the real-time performance of EPA periodic data transmission was theoretically and experimentally studied.By analyzing information transmission regularity and EPA deterministic scheduling mechanism,periodic messages were categorized as different modes according to their entering-queue time.The scheduling characteristics and delivery time of each mode and their interacting relations were studied,during which the models of real-time performance of periodic information transmission in EPA system were established.On this basis,an experimental platform is developed to test the delivery time of periodic messages transmission in EPA system.According to the analysis and the experiment,the main factors that limit the real-time performance of EPA periodic data transmission and the improvement methods were proposed.
基金Supported by CNPq-Conselho Nacional de Desenvolvimento Cient'fico e Tecnológico
文摘In this paper, we study the large time behavior of solutions of the parabolic semilinear equation δtu-div（a（x）△↓u） = -｜u｜^αu in （0,∞） × R^N, where α 〉 0 is constant and a∈ Cb^1（R^N） is a symmetric periodic matrix satisfying some ellipticity assumptions.Considering an integrable initial data u0 and α ∈ （2/N, 3/N）, we prove that the large time behavior of solutions is given by the solution U（t, x） of the homogenized linear problem δtU-div（a^h△↓U）=0,U（0） = C, where a^h is the homogenized matrix of a（x）, C is a positive constant and δ is the Dirac measure at 0.
文摘自动驾驶与仿真场景中遍布带周期特征的数据,其环面拓扑让常规聚类算法容易把簇割断,效率也随之下滑。针对这一痛点,文章提出周期性聚类(Periodic-Density-Based Spatial Clustering of Applications with Noise,P-DBSCAN)。该算法用最短环绕距离精确定义周期邻域,经验证可消除簇的错误分割,同时维持近线性时间复杂度,为海量周期数据提供了既精准又高效的解析手段。
文摘The advent of the era of big data has caused paradigm changes in translation studies,and the combination of big data technology and thinking with translation studies has further interdisciplinaryized translation studies and presented characteristics such as quantification,expansion of research horizon and scale.Scholars should pay attention to the prospect of translation studies while paying attention to corpus translation studies:the shift of research in text patterns;the spatial turn of and media integration of translation studies.In the process of translatology research in the era of big data,the limitations of digital technology and big data research are also noted.
基金Supported by the National Natural Science Foundation of China.
文摘We use wavelet transform to analyze the daily relative sunspot number series over solar cycles 10-23. The characteristics of some of the periods shorter than - 600-day are discussed. The results exhibit not only the variation of some short periods in the 14 solar cycles but also the characteristics and differences around solar peaks and valley years. The short periodic components with larger amplitude such as ～27, ～ 150 and ～360-day are obvious in some solar cycles, all of them are time-variable, also their lengths and amplitudes are variable and intermittent in time. The variable characteristics of the periods are rather different in different solar cycles.
基金financially supported by the National Key R&D Program of China(2017YFC 0209905)the Natural Sciences Foundation of China(No.51878012,51638001)+1 种基金the project supported by Beijing Municipal Education Commission of Science and Technology(No.KM201610005019)the New Talent Program of Beijing University of Technology(No.2017-RX(1)-10)
文摘In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors(i.e., seasons, pollution periods and airflow directions), through a case study in Beijing from 2013 to 2016. The results showed that the annual mean concentrations(MC) of PM_(2.5), SO_2, NO_2 and CO had decreased with annual mean ratios of 7.5%, 28.6%, 4.6%and 15.5% from 2013 to 2016, respectively. Among seasons, the MC in winter contributed the largest fractions(25.8%～46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation(IMCV) of PM_(2.5) and NO2. For different pollution periods, gradually increase of frequency of S-1(PM_(2.5), 0～ 75 μg/m^3) made S-1 become the largest contributor(28.8%) to the MC of PM_(2.5) in 2016, it had a negative contribution(-13.1%) to the IMCV of PM_(2.5); obvious decreases of frequencies of heavily polluted and severely polluted dominated(44.7% and 39.5%) the IMCV of PM_(2.5). For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease(22.5%～62.5%), and those decrease contributed most to the IMCV of PM_(2.5)(143.3%),SO2(72.0%), NO_2(55.5%) and CO(190.3%); the west airflow had negative influences to the IMCV of PM_(2.5), NO_2 and CO. The framework is helpful for further analysis and utilization of the large amounts of monitoring data; and the analysis results can provide scientific supports for the formulation or adjustment of further air pollution mitigation policy.
