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A temporal framework for building up of healthy soils PERSPECTIVE

《农业科学与工程前沿（英文）》 2024年 第11卷 第2期   页码 292-296 doi: 10.15302/J-FASE-2024561

摘要：

A temporal framework for building up of healthy soils

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A hybrid spatial-temporal deep learning prediction model of industrial methanol-to-olefins process

《化学科学与工程前沿（英文）》 2024年 第18卷 第4期 doi: 10.1007/s11705-024-2403-7

摘要： Methanol-to-olefins, as a promising non-oil pathway for the synthesis of light olefins, has been successfully industrialized. The accurate prediction of process variables can yield significant benefits for advanced process control and optimization. The challenge of this task is underscored by the failure of traditional methods in capturing the complex characteristics of industrial processes, such as high nonlinearities, dynamics, and data distribution shift caused by diverse operating conditions. In this paper, we propose a novel hybrid spatial-temporal deep learning prediction model to address these issues. Firstly, a unique data normalization technique called reversible instance normalization is employed to solve the problem of different data distributions. Subsequently, convolutional neural network integrated with the self-attention mechanism are utilized to extract the temporal patterns. Meanwhile, a multi-graph convolutional network is leveraged to model the spatial interactions. Afterward, the extracted temporal and spatial features are fused as input into a fully connected neural network to complete the prediction. Finally, the outputs are denormalized to obtain the ultimate results. The monitoring results of the dynamic trends of process variables in an actual industrial methanol-to-olefins process demonstrate that our model not only achieves superior prediction performance but also can reveal complex spatial-temporal relationships using the learned attention matrices and adjacency matrices, making the model more interpretable. Lastly, this model is deployed onto an end-to-end Industrial Internet Platform, which achieves effective practical results.

关键词： methanol-to-olefins     process variables prediction     spatial-temporal     self-attention mechanism     graph convolutional network    

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Spatio-temporal characteristics of genotoxicity in the Yangtze River under the background of COVID-19

《环境科学与工程前沿（英文）》 2024年 第18卷 第11期 doi: 10.1007/s11783-024-1900-8

摘要：

● Genotoxicity was higher in upper Yangtze River than that in the lower reaches.

关键词： Yangtze River     COVID-19     Genotoxicity     Spatio-temporal characteristics    

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Realtime prediction of hard rock TBM advance rate using temporal convolutional network (TCN) with tunnel

Zaobao LIU; Yongchen WANG; Long LI; Xingli FANG; Junze WANG

《结构与土木工程前沿（英文）》 2022年 第16卷 第4期   页码 401-413 doi: 10.1007/s11709-022-0823-3

摘要： Real-time dynamic adjustment of the tunnel bore machine (TBM) advance rate according to the rock-machine interaction parameters is of great significance to the adaptability of TBM and its efficiency in construction. This paper proposes a real-time predictive model of TBM advance rate using the temporal convolutional network (TCN), based on TBM construction big data. The prediction model was built using an experimental database, containing 235 data sets, established from the construction data from the Jilin Water-Diversion Tunnel Project in China. The TBM operating parameters, including total thrust, cutterhead rotation, cutterhead torque and penetration rate, are selected as the input parameters of the model. The TCN model is found outperforming the recurrent neural network (RNN) and long short-term memory (LSTM) model in predicting the TBM advance rate with much smaller values of mean absolute percentage error than the latter two. The penetration rate and cutterhead torque of the current moment have significant influence on the TBM advance rate of the next moment. On the contrary, the influence of the cutterhead rotation and total thrust is moderate. The work provides a new concept of real-time prediction of the TBM performance for highly efficient tunnel construction.

关键词： hard rock tunnel     tunnel bore machine advance rate prediction     temporal convolutional networks     soft computing     construction big data    

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Spatio-temporal variations of water quality in Yuqiao Reservoir Basin, North China

Yuan XU,Ruqin XIE,Yuqiu WANG,Jian SHA

《环境科学与工程前沿（英文）》 2015年 第9卷 第4期   页码 649-664 doi: 10.1007/s11783-014-0702-9

摘要： Fuzzy comprehensive assessment and multivariate statistical techniques including cluster analysis, discriminant analysis, principal component analysis, and factor analysis were applied to analyze the water quality status of Yuqiao Reservoir Basin, North China, for assessing its spatio-temporal variations and identifying potential pollution sources. In this paper, we considered data for 14 water quality parameters collected during 1990–2004 at 7 water quality monitoring sites. The results of fuzzy comprehensive assessment revealed that water quality in Yuqiao Reservoir Basin showed a downtrend from 1990 to 2001 with fluctuation, and a slowly upward trend after 2001. The major water quality belonged to Class III and IV. Besides, hierarchical cluster analysis divided 7 monitoring sites into two groups (Group A and B), and 12 months into three periods (low-flow (LF), normal-flow (NF), and high-flow (HF) period). Temp, pH, SS, T-har, DO, NO -N and TP were identified as significant variables affecting spatial variations, and Temp, pH and NO -N were identified as significant variables affecting temporal variations by discriminant analysis. Factor analysis identified four latent pollution sources for water quality variations: nutrient pollution, organic pollution, inorganic pollution, and natural pollution. Moreover, for Group A regions, pollution inputs mainly came from domestic wastewater and industrial sewage. For Group B regions, it is more likely that water pollution resulted from the combined effects of domestic wastewater, hospital wastewater, agriculture runoff, and fishpond discharge, as well as the incoming water from upstream.

关键词： Fuzzy comprehensive assessment     multivariate statistical analysis     water quality    

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Temporal trend of mortality from major cancers in Xuanwei, China

null

《医学前沿（英文）》 2015年 第9卷 第4期   页码 487-495 doi: 10.1007/s11684-015-0413-z

摘要：

Although a number of studies have examined the etiology of lung cancer in Xuanwei County, China, other types of cancer in this county have not been reported systematically. This study aimed to investigate the temporal trend of eight major cancers in Xuanwei County using data from three mortality surveys (1973–1975, 1990–1992, and 2004–2005). The Chinese population in 1990 was used as a standard population to calculate age-standardized mortality rates. Cancers of lung, liver, breast, brain, esophagus, leukemia, rectum, and stomach were identified as the leading cancers in this county in terms of mortality rate. During the three time periods, lung cancer remained as the most common type of cancer. The mortality rates for all other types of cancer were lower than those of the national average, but an increasing trend was observed for all the cancers, particularly from 1990–1992 to 2004–2005. The temporal trend could be partly explained by changes in risk factors, but it also may be due to the improvement in cancer diagnosis and screening. Further epidemiological studies are warranted to systematically examine the underlying reasons for the temporal trend of the major cancers in Xuanwei County.

关键词： cancer     mortality     Xuanwei     temporal trend    

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The temporal changes of the concentration level of typical toxic organics in the river sediments around

Qiang Li, Xiong Xu, Yaoyao Fang, Ruiyang Xiao, Donghong Wang, Wenjue Zhong

《环境科学与工程前沿（英文）》 2018年 第12卷 第6期 doi: 10.1007/s11783-018-1054-7

摘要：

The current situation of typical organics in the sediments around Beijing was unclear.

56 kinds of typical toxic organics were detected in this article.

Historical data was compared with the data in this study.

The change of different organics in the sediments around Beijing was concluded.

关键词： Organic compounds     Endocrine disrupters     Sediments     Concentration     Temporal changes    

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Spatial and Temporal Distribution of PM

Xiao-hong Chen,Xiang-bo Tang

《工程管理前沿（英文）》 2016年 第3卷 第2期   页码 171-181 doi: 10.15302/J-FEM-2016017

摘要： Utilizing the initial hourly monitoring data of PM concentrations at 23 monitoring sites across the Chang-Zhu-Tan city cluster between January 2013 and February 2014 that released in Real-time Air Quality Reporting System in Hunan Province, this paper draws diagrams and analyzes the change rule of the pollutants concentration over time. In addition, this paper studies the regional distribution of PM seasonal pollution in the vicinity of the monitoring sites using ArcGIS geographic information system with the Kriging interpolation method. On this basis, this paper puts forward some effective control strategies to cope with regional PM pollution combined with the information of industry distribution and development status in the Chang-Zhu-Tan city cluster.

关键词： PM2.5     spatial and temporal distribution     ArcGIS     the chang-Zhu-Tan city cluster    

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The effect of texture and irrigation on the soil moisture vertical-temporal variability in an urban artificial

Xiaofeng ZHANG,Xu ZHANG,Guanghe LI

《环境科学与工程前沿（英文）》 2015年 第9卷 第2期   页码 269-278 doi: 10.1007/s11783-014-0672-y

摘要： Soil moisture variability in natural landscapes has been widely studied; however, less attention has been paid to its variability in the urban landscapes with respect to the possible influence of texture stratification and irrigation management. Therefore, a case study was carried out in the Beijing Olympic Forest Park to continuously monitor the soil in three typical profiles from 26 April to 11 November 2010. The texture stratification significantly affected the vertical distribution of moisture in the non-irrigated profile where moisture was mostly below field capacity. In the profile where irrigation was sufficient to maintain moisture above field capacity, gravity flow led to increased moisture with depth and thus eliminated the influence of texture. In the non-irrigated sites, the upper layer (above 80 cm) exhibited long-term moisture persistence with the time scale approximating the average rainfall interval. However, a coarse-textured layer weakened the influence of rainfall, and a fine-textured layer weakened the influence of evapotranspiration, both of which resulted in random noise-like moisture series in the deeper layers. At the irrigated site, frequent irrigation neutralized the influence of evapotranspiration in the upper layer (above 60 cm) and overshadowed the influence of rainfall in the deeper layer. As a result, the moisture level in the upper layer also behaved as a random noise-like series; whereas due to deep transpiration, the moisture of the deep layer had a persistence time-scale longer than a month, consistent with characteristic time-scales found for deep transpiration.

关键词： moisture vertical distribution     moisture temporal variation     texture stratification     irrigation     meteorological forcing     urban landscape    

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CLIMATE-CHANGE-INDUCED TEMPORAL VARIATION IN PRECIPITATION INCREASES NITROGEN LOSSES FROM INTENSIVE CROPPING

《农业科学与工程前沿（英文）》 2022年 第9卷 第3期   页码 457-464 doi: 10.15302/J-FASE-2022452

摘要：

● A simple model was used to evaluate how increasing temporal variability in precipitation influences crop yields and nitrogen losses.

关键词： crop yield     fertilizer timing     nitrogen loss     precipitation variability     toy model    

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空中交通延误传播动力学的时空网络视角 Article

Qing Cai, Sameer Alam, Vu N. Duong

《工程（英文）》 2021年 第7卷 第4期   页码 452-464 doi: 10.1016/j.eng.2020.05.027

摘要：

由于日益增长的空中交通需求与有限的空域容量之间的不平衡，空中交通出现了难以解决的延误。由于空中交通与复杂的航空运输系统有关，延误可以在这些系统中被放大和传播，从而导致所谓的延迟传播的紧急行为。对延误传播动力学的理解与现代空中交通管理有着密切的关系。本文提出了一种复杂的网络延迟传播动力学观点。具体来说，我们利用以机场为节点的时空网络对空中交通场景进行建模。为了建立节点间的动态边缘，我们提出了一种时延传播方法，并将其应用于给定的空中交通调度集合。基于所构建的时空网络，提出了三个指标（幅度、严重性和速度）来衡量延迟传播动态。为了验证该方法的有效性，我们对东南亚地区（SAR）和美国的国内航班进行了案例研究。实验表明，美国交通延误传播影响的航班数和传播延迟量的传播幅度分别是SAR的5倍和10倍。实验进一步表明，美国交通的传播速度比SAR快8倍。延迟传播动态显示，SAR约6个枢纽机场存在明显的传播延误，而美国的情况则更为严重，相应数量在16个左右。本工作为跟踪空中交通延误的演变提供了有力的工具。

关键词： 空中交通     运输系统     时延传播动力学     时空网络    

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Forecasting measured responses of structures using temporal deep learning and dual attention

《结构与土木工程前沿（英文）》 2024年 第18卷 第6期   页码 832-850 doi: 10.1007/s11709-024-1092-0

摘要： The objective of this study is to develop a novel and efficient model for forecasting the nonlinear behavior of structures in response to time-varying random excitation. The key idea is to design a deep learning architecture to leverage the relationships, between external excitations and structure’s vibration signals, and between historical values and future values, within multiple time-series data. The proposed method consists of two main steps: the first step applies a global attention mechanism to combine multiple-measured time series and time-varying excitation into a weighted time series before feeding it to a temporal architecture; the second step utilizes a self-attention mechanism followed by a fully connected layer to predict multi-step future values. The viability of the proposed method is demonstrated via two case studies involving synthetic data from a three-dimensional (3D) reinforced concrete structure and experimental data from an 18-story steel frame. Furthermore, comparison and robustness studies are carried out, showing that the proposed method outperforms conventional methods and maintains high performance in the presence of noise with an amplitude of less than 10%.

关键词： structural dynamic     time-varying excitation     deep learning     signal processing     response forecasting    

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Assessment of temporal and spatial variations in water quality using multivariate statistical methods

Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG

《环境科学与工程前沿（英文）》 2014年 第8卷 第6期   页码 895-904 doi: 10.1007/s11783-014-0736-z

摘要： This study evaluated the temporal and spatial variations of water quality data sets for the Xin'anjiang River through the use of multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), correlation analysis, and principal component analysis (PCA). The water samples, measured by ten parameters, were collected every month for three years (2008–2010) from eight sampling stations located along the river. The hierarchical CA classified the 12 months into three periods (First, Second and Third Period) and the eight sampling sites into three groups (Groups 1, 2 and 3) based on seasonal differences and various pollution levels caused by physicochemical properties and anthropogenic activities. DA identified three significant parameters (temperature, pH and ) to distinguish temporal groups with close to 76% correct assignment. The DA also discovered five parameters (temperature, electricity conductivity, total nitrogen, chemical oxygen demand and total phosphorus) for spatial variation analysis, with 80.56% correct assignment. The non–parametric correlation coefficient (Spearman R) explained the relationship between the water quality parameters and the basin characteristics, and the GIS made the results visual and direct. The PCA identified four PCs for Groups 1 and 2, and three PCs for Group 3. These PCs captured 68.94%, 67.48% and 70.35% of the total variance of Groups 1, 2 and 3, respectively. Although natural pollution affects the Xin'anjiang River, the main sources of pollution included agricultural activities, industrial waste, and domestic wastewater.

关键词： Xin'anjiang River     multivariable statistical analysis     temporal variation     spatial variation     water quality    

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An investigation based on the temporal-spatial distributions of idle vehicles

《工程管理前沿（英文）》 doi: 10.1007/s42524-024-3109-8

摘要： Does e-hailing perform better than on-street searching? An investigation based on the temporal-spatial distributions of idle vehicles
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Machine learning for detecting mesial temporal lobe epilepsy by structural and functional neuroimaging

Baiwan Zhou, Dongmei An, Fenglai Xiao, Running Niu, Wenbin Li, Wei Li, Xin Tong, Graham J Kemp, Dong Zhou, Qiyong Gong, Du Lei

《医学前沿（英文）》 2020年 第14卷 第5期   页码 630-641 doi: 10.1007/s11684-019-0718-4

摘要： Mesial temporal lobe epilepsy (mTLE), the most common type of focal epilepsy, is associated with functional and structural brain alterations. Machine learning (ML) techniques have been successfully used in discriminating mTLE from healthy controls. However, either functional or structural neuroimaging data are mostly used separately as input, and the opportunity to combine both has not been exploited yet. We conducted a multimodal ML study based on functional and structural neuroimaging measures. We enrolled 37 patients with left mTLE, 37 patients with right mTLE, and 74 healthy controls and trained a support vector ML model to distinguish them by using each measure and the combinations of the measures. For each single measure, we obtained a mean accuracy of 74% and 69% for discriminating left mTLE and right mTLE from controls, respectively, and 64% when all patients were combined. We achieved an accuracy of 78% by integrating functional data and 79% by integrating structural data for left mTLE, and the highest accuracy of 84% was obtained when all functional and structural measures were combined. These findings suggest that combining multimodal measures within a single model is a promising direction for improving the classification of individual patients with mTLE.

关键词： mesial temporal lobe epilepsy     functional magnetic resonance imaging     structural magnetic resonance imaging     machine learning     support vector machine    

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标题 作者 时间 类型 操作

A temporal framework for building up of healthy soils

期刊论文

A hybrid spatial-temporal deep learning prediction model of industrial methanol-to-olefins process

期刊论文

Spatio-temporal characteristics of genotoxicity in the Yangtze River under the background of COVID-19

期刊论文

Realtime prediction of hard rock TBM advance rate using temporal convolutional network (TCN) with tunnel

Zaobao LIU; Yongchen WANG; Long LI; Xingli FANG; Junze WANG

期刊论文

Spatio-temporal variations of water quality in Yuqiao Reservoir Basin, North China

Yuan XU,Ruqin XIE,Yuqiu WANG,Jian SHA

期刊论文

Temporal trend of mortality from major cancers in Xuanwei, China

null

期刊论文

The temporal changes of the concentration level of typical toxic organics in the river sediments around

Qiang Li, Xiong Xu, Yaoyao Fang, Ruiyang Xiao, Donghong Wang, Wenjue Zhong

期刊论文

Spatial and Temporal Distribution of PM

Xiao-hong Chen,Xiang-bo Tang

期刊论文

The effect of texture and irrigation on the soil moisture vertical-temporal variability in an urban artificial

Xiaofeng ZHANG,Xu ZHANG,Guanghe LI

期刊论文

CLIMATE-CHANGE-INDUCED TEMPORAL VARIATION IN PRECIPITATION INCREASES NITROGEN LOSSES FROM INTENSIVE CROPPING

期刊论文

空中交通延误传播动力学的时空网络视角

Qing Cai, Sameer Alam, Vu N. Duong

期刊论文

Forecasting measured responses of structures using temporal deep learning and dual attention

期刊论文

Assessment of temporal and spatial variations in water quality using multivariate statistical methods

Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG

期刊论文

An investigation based on the temporal-spatial distributions of idle vehicles

期刊论文

Machine learning for detecting mesial temporal lobe epilepsy by structural and functional neuroimaging

Baiwan Zhou, Dongmei An, Fenglai Xiao, Running Niu, Wenbin Li, Wei Li, Xin Tong, Graham J Kemp, Dong Zhou, Qiyong Gong, Du Lei

期刊论文