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With an ever-increasing trend of cybercrimes and incidents due to software vulnerabilities and exposures, effective and proactive vulnerability management becomes imperative in modern organisations regardless large or small. Forecasting models leveraging rich historical vulnerability disclosure data undoubtedly provide important insights to inform the cyber community with the anticipated risks. In...
Proper determination of light use efficiency (LUE) is a prerequisite for LUE models to simulate gross primary productivity (GPP). This study was devoted to apply the photochemical reflectance index (PRI) to accurately track LUE variations for a sub-tropical coniferous forest using tower-based PRI and GPP measurements. To improve the ability of PRI to track LUE, a simple two-leaf approach is used to...
A time series is a sequence of observations collected over fixed sampling intervals. Several real-world dynamic processes can be modeled as a time series, such as stock price movements, exchange rates, temperatures, among others. As a special kind of data stream, a time series may present concept drift, which affects negatively time series analysis and forecasting. Explicit drift detection methods...
Vegetation index derived from remote sensing measurement servers as the significant reference for crop growing monitor and agricultural disaster forecasting. Vegetation index forecasting at long lead time and appropriate spatial scale is critical for decision making to mitigate the impacts from agricultural disaster. In previous studies, vegetation index forecasting has been studied and implemented...
Beichen district of Tianjin, located in the important node of Beijing-Tianjin golden corridor and high-tech industry area of Jingjintang region, has strong industrial foundations, while it is still faced with the problems that traditional industries account for high proportion of the industrial structure, inefficient use of industrial land, lack of enterprise innovation ability and shortage of resources,...
In [10] and [16], we proposed tools for simultaneous variable selection and parameter estimation in a functional linear model with a functional outcome and a large number of scalar predictor. We call these techniques Function-on-Scalar Lasso (FSL) and Adaptive Function-on-Scalar Lasso(AFSL). A scalar group lasso was used to fit the FSL and AFSL estimates. While this approach works well, we improve...
With the Geographic Information System (GIS) analytical tools and Remote Sensing technology, the main territory's Net Primary Productivity (NPP) in China from 2001 to 2010 is estimated based on CASA model. The analysis of the temporal and spatial variations in NPP shown that NPP in the southern regions shows increase trend after the first five years' decrease, in addition, the southern region of China...
Fraction of vegetation coverage (FVC), an important index to depict the conditions of land covered by vegetation, is increasingly used in monitoring grassland degradation in ecological researches. Hulunbuir Steppe is one of the best grasslands in China. So, in this study, we set Xinbaerhuyouqi, Xinbaerhuzuoqi, Chenbaerhuqi, and Ewenkezuzizhiqi as the study area. Pixel Decomposition Models was introduced...
Forest above ground biomass (AGB) retrieval by TomoSAR technology has been preliminary studied over the last two years. Recent experiments have demonstrated that the backscattered power in HV channel at 30-m layer have strong correlation with the forest AGB, and be successfully used to build the estimation model. However, much progress remains necessary to make the best of the vertical distribution...
The scale effects in earth science, which are related to various aspects in remote sensing monitoring, have become an international prosperous research area. As spatial heterogeneity of the earth system limits the transferring between different scale, it is necessary to study these spatial heterogeneity factors, and analyze their impact on NPP scale effect. Then we can introduce an approach to perform...
Statistical models built on historical data are often found to be effective in forecasting Indian summer monsoon. However, linear models are found to be inadequate, and non-linear models like neural networks provide better performance. In this article, we study the use of recurrent neural network for long range forecast of Indian monsoon at lead of one season. Recurrent network model the sequential...
In information services fuzzy concepts are frequently encountered because a customer or client asks a question about something which could be interpreted in many different ways, or, a document is transmitted of a type or meaning which cannot be easily allocated to a known type or category, or to a known procedure. It might take considerable inquiry to “place” the information, or establish in what...
Interbank Offered market (also called “Interbank Lending market”) and the stock market are important parts of China's financial market. This paper studies the relationship of Shanghai interbank offered rate (Interbank Offered Rate Shanghai, abbreviate “SHIBOR”) and stock market returns, which is benefit to grasp the change rules of them. It finds that the dynamic relationship between SHIBOR and stock...
With the production values of the secondary and tertiary industries and 18 industries, and the amount of energy consumption of 8 cities in Shandong peninsula urban agglomeration in 2014, The Theil index, data envelopment analysis, correlation analysis, stepwise multiple regression analysis and ArcGIS spatial analysis were applied to study the spatial patterns of the industrial development and energy...
The electric power distribution is considered as a monopoly public service, in which there cannot be direct competition, so it must be submitted to price and service quality regulation.
In order to solve the problem how to determine the quantitative relationship of characteristic factors caused by uncertainties, this paper describes the target case by characteristic factors in case-based reasoning, determines the initial weight according to the characteristic factor matrix, introduces Hebb learning rule to make a weight adjustment and applies the improved Euclidean distance to calculate...
There is a vast amount of neurobiological evidence supporting the role of dendritic processing in neural computation. However, most of the neuromorphic chips designed have overlooked these research findings. Here, we present a neuron model with multiple nonlinear spatially sensitive dendrites. Location-dependent processing occurs in multiple dendritic compartments, where sparse binary synapses are...
Fuzzy extractors and neural networks used for identification by handwriting dynamics should be used in tandem with another methods. Bayesian statistical inference networks or other networks able to consider a complete matrix of correlation coefficients may become a method that complete them. The paper proposes a simple correlation metric that takes into account correlation coefficients of biometric...
We consider the problem of estimating the intensity map of a spatially random phenomenon over a geographical area observed by a sensor network. The spatial phenomenon of interest is modeled using a Gaussian random field specified by its nonlinear mean and covariance functions. Our proposed algorithm includes two stages: a novel greedy sparse recovery algorithm to estimate the parameters of the mean...
A novel method to predict the viscosity of biodiesel blends as a simultaneous function of temperature and blend volume percent is proposed. The key advantage of the method is that, it requires only the viscosity data of pure blend components. The lower values of Standard Estimate of Error (SEE = 0.061 − 0.117) and Absolute Average Deviation (AAD = 1.98 − 4.23 %) suggest the predictive capability of...
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