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Leaf area index (LAI) is an important biophysical vegetation variable in many models describing vegetation atmosphere interactions. This study presents a method to assimilation leaf area index(LAI) obtained by a simple downscaling technique into the World Food Studies(WOFOST) to improve simulation LAI in time series in plateau grasslands located in northeast of Qinghai province, China. Using the Sobol'...
Nitrogen is one of the most important nutrients in crop growth and development. To study the problem of spectral index setting of intelligent remote sensor for crop N prime inversion, and effectiveness of quantitative evaluation and other issues in different application requirements, with winter wheat for example to study the impact of quantitative model inversion of center wavelength, SNR and band...
Soil moisture is an effective variable for agricultural drought monitoring, and data assimilation is a useful tool to improve soil moisture estimates. In this study, we assimilated remotely sensed soil moisture (SM) and leaf area index (LAI) into DSSAT-CSM-Wheat crop growth model to estimate soil moisture. The results showed that compared to open-loop scenario, assimilating LAI independently could...
The rain-fed agriculture dominates the agricultural production in Northeast China, which leads to the drought risk for crops growing. To assess the yields and necessity of irrigation for maize in the Three Northeast Provinces of China, the calibrated and validated WOrld FOod STudies (WOFOST) model was used to estimate maize yieldss in the regional scale after it was optimized by assimilating leaf...
A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture...
Chlorophyll fluorescence is a common approach for understanding leaf photochemical and nonphotochemical processes nondestructively. Among all fluorescence parameters, the photosynthetic electron transport rate (ETR) is a useful indicator of the efficiency of carbon uptake. Traditionally, Pulse Amplitude Modulation (PAM) fluorometry was a key technique for measuring ETR, but it is not applicable for...
We present a new fault detection index, based on Multi-way Principal Component Analysis, which requires no selection of principal and residual spaces. This detection index is called Gaussian Time Error, since a Gaussian model is learned at each measurement instant. This index is used on real data from semiconductor processes to detect faults, providing a better detection than Square Prediction Error...
Recently probabilistic principal component analysis (PPCA) has been used for process monitoring and fault diagnosis, which can model the process noise and can handle the problem of missing data in the probabilistic framework. Nevertheless, the missing data samples are treated as principal components in conventional PPCA method, which causes the estimation accuracy is largely influenced by data missing...
Vehicle-mounted ground penetrating radar (GPR) is an effective and rapid tool to detect railway subgrade defects. However, the signal to noise ratio (SNR) of the raw GPR data on railway subgrade is much lower than that of other detection sites. The primary noises are caused by radar wave reflections from the rails and steel-concrete sleepers. However, the rail noise is always invariant since the rails...
In view of the current problems of system evaluation and decision support, an advanced theory of evaluation based on data station was proposed. The system effectiveness from different aspects was analyzed. For massive and non-structural characteristics a model of simulation data refinement and reconstruction processing was constructed, in order to meet different demands for system analysis a data...
Historical user activity is the key for building user profiles to predict the user behavior and affinities in many web applications such as targeting of online advertising and social recommendations. In these scenarios, the items recommended to users must match their profiles. However, user profiles are temporal, so, changes in a user's activity patterns are particularly useful for improved prediction...
With the expansion of semantic web, there is an increasing number of heterogeneous information data such as RDF. Nowadays, most of solutions operating RDF are centralized and have limitations of scalability. In this paper, we propose a method to solve the problem by storing and querying RDF data based on HBase and Hadoop. A storage model classified by class and predicate is used in HBase to support...
In order to mine the abnormal learning behavior of learner in virtual learning community and carry on personalized supervision and guidance, behavior filtering model based on the factor analysis of the behavior is constructed to solve the problem of the relationship between behavior factors in the learning behavior vector space model. In view of the disadvantage of neglecting local abnormal points...
Traditional classroom teaching is difficult to satisfy students' personalized learning. The main work of the thesis constructs knowledge point model which using relational model and constructs student model according to the students' interest characteristics, it uses improved k-means algorithm to analyze students' learning interest characteristics to dig out the interests of different students, and...
A Schema-less NoSQL system refers to solutions where users do not declare a database schema and, in fact, its management is moved to the application code. This paper presents a study that allows us to evaluate, to some extent, the data structuring impact. The decision of how to structure data in semi-structured databases has an enormous impact on data size, query performance and readability of the...
In this work a numerical model capable to predict the electromagnetic response of railway ballast aggregates under different physical conditions has been calibrated and validated by a simulation-based approach. The ballast model is based on the main physical and geometrical properties of its constituent material and it is generated by means of a random-sequential absorption (RSA) approach. A finite-difference...
Quality of Life (QoL) is a broad measure that captures the extent to which personal satisfaction with overall life circumstances is achieved. The transition to college can be a challenging event due to unique environment changes. So first-year students are special vulnerable to stress which has been associated with a variety of negative outcomes, including general and health-related QoL. Difficulties...
Numerous novel biomarkers are being considered as tools to enhance cardiovascular risk estimation. Statistical models can indicate how a biomarker influences movements between health states, and clinicians are interested in the impact they may have compared to traditional risk factors alone. Net reclassification indices (NRIs) have recently become popular statistics for measuring the prediction increment...
To protect cloud data against corruption, enabling data integrity checking along with error recovery becomes quite critical. Recently, regenerating code has caught researchers' attention due to low repair traffic while preserving fault tolerance. Existing integrity checking schemes for regenerating code storage only support static data and have high auditing cost, which are not suitable for practical...
This paper used the data of the Jiangsu Province, Henan Province and Guangxi Province from 1985 to 2009, as the representations of eastern, central and western parts of China, to study the influence of the development of rural finance on the rural income increase through the C-D production function model. The results showed that the effects were differed: both the rural finance scale and efficiency...
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