Scene-Level Geographic Image Classification Based on a Covariance Descriptor Using Supervised Collaborative Kernel Coding

Scene-level geographic image classification has been a very challenging problem and has become a research focus in recent years. This paper develops a supervised collaborative kernel coding method based on a covariance descriptor (covd) for scene-level geographic image classification. First, covd is introduced in the feature extraction process and, then, is transformed to a Euclidean feature by a supervised collaborative kernel coding model. Furthermore, we develop an iterative optimization framework to solve this model. Comprehensive evaluations on public high-resolution aerial image dataset and comparisons with state-of-the-art methods show the superiority and effectiveness of our approach

Numerical Investigation of Fracture Compressibility and Uncertainty on Water-Loss and Production Performance in Tight Oil Reservoirs

Multi-stage hydraulic fracturing along with horizontal wells are widely used to create complex fracture networks in tight oil reservoirs. Analysis of field flowback data shows that most of the fracturing fluids are contained in a complex fracture network, and fracture-closure is the main driving mechanism during early clean up. At present, the related fracture parameters cannot be accurately obtained, so it is necessary to study the impacts of fracture compressibility and uncertainty on water-loss and the subsequent production performance. A series of mechanistic models are established by considering stress-dependent porosity and permeability. The impacts of fracture uncertainties, such as natural fracture density, proppant distribution, and natural fracture heterogeneity on flowback and productivity are quantitatively assessed. Results indicate that considering fracture closure during flowback can promote water imbibition into the matrix and delay the oil breakthrough time compared with ignoring fracture closure. With the increase of natural fracture density, oil breakthrough time is advanced, and more water is retained underground. When natural fractures connected with hydraulic fractures are propped, well productivity will be enhanced, but proppant embedment can cause a loss of oil production. Additionally, the fracture network with more heterogeneity will lead to the lower flowback rate, which presents an insight in the role of fractures in water-loss

Distributed Attitude Consensus for Multiple Rigid Spacecraft under Jointly Connected Switching Topologies

We study the distributed leader-following attitude consensus problem for multiple rigid spacecraft with a single leader under jointly connected switching topologies. Two cases are considered, where the first case is with a static leader and the second case is with a dynamic leader. By constructing an auxiliary vector and a distributed observer for each follower spacecraft, the controllers are designed to drive all the attitudes of the follower spacecraft to the leader’s, respectively, for both of the two cases, though there are some time intervals in which the communication topology is not connected. The whole system is proved to be stable by using common Lyapunov function method. Finally, the theoretical result is illustrated by numerical simulations

Bilateral Filter Regularized L2 Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing

Hyperspectral unmixing (HU) is one of the most active hyperspectral image (HSI) processing research fields, which aims to identify the materials and their corresponding proportions in each HSI pixel. The extensions of the nonnegative matrix factorization (NMF) have been proved effective for HU, which usually uses the sparsity of abundances and the correlation between the pixels to alleviate the non-convex problem. However, the commonly used L 1 / 2 sparse constraint will introduce an additional local minima because of the non-convexity, and the correlation between the pixels is not fully utilized because of the separation of the spatial and structural information. To overcome these limitations, a novel bilateral filter regularized L 2 sparse NMF is proposed for HU. Firstly, the L 2 -norm is utilized in order to improve the sparsity of the abundance matrix. Secondly, a bilateral filter regularizer is adopted so as to explore both the spatial information and the manifold structure of the abundance maps. In addition, NeNMF is used to solve the object function in order to improve the convergence rate. The results of the simulated and real data experiments have demonstrated the advantage of the proposed method

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008-2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion.

BACKGROUND:Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. METHODS:The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. RESULTS:The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. CONCLUSION:We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables

Case Study on the Effect of Acidizing on the Rock Properties of the Mahu Conglomerate Reservoir

The development of the Mahu tight reservoir has adopted horizontal wells with staged fracturing. In the fracturing, there is a problem of a high fracturing pressure. Acid treatment is often used to lower the fracturing pressure on site. At present, the impact of this acid treatment on the physical parameters of the rocks of the reservoir in the Mahu region has not been systematically studied. Aiming to solve this problem, this paper conducted an experimental study on how acid dissolution affects the physical properties of the Mahu conglomerate, including its porosity, permeability, triaxial rock mechanical parameters, tensile strength, and mineral composition. First, the experimental scheme was designed. Next, a series of experiments were conducted. Finally, the experiment results were analyzed comparatively before and after acidizing. The acid composition, concentration, and contact time were the main factors for the analysis, based on which the acid system and related parameters were recommended. This study showed that the Mahu conglomerate exhibited brittle plasticity characteristics under stress. The carbonate content in this region was low, while the feldspar content was high, so it was necessary to use mud acid to effectively dissolve feldspar, clay, and other silicates. After acidizing, the porosity was 200% of the original value. The permeability increased by up to 14 times. The tensile strength decreased significantly by up to 84%. The value of Young’s modulus of the rock decreased by up to 63.6%. The value of Poisson’s ratio was reduced by up to 40.7%. A combination of 6% HF + 15% HCl is recommended, with an effective acid treatment time of over 60 min for the Mahu conglomerate. Acidizing could significantly change the mechanical properties and permeability of the rock of the Mahu conglomerate reservoir, thus effectively reducing the formation fracturing pressure. This research provides technical support for Mahu acid dipping in horizontal well fracturing

A Modified Shape Model Incorporating Continuous Accumulated Growing Degree Days for Phenology Detection of Early Rice

Using a shape model (SM) is a typical method to determine the phenological phases of crops with long-time-series satellite remote sensing data. The average AGDD-based shape model (AAGDD-SM) takes temperature into account compared to SM, however, the commonly used daily average temperature is not sufficient to determine the exact AGDD owing to the possibly significant changes in temperatures throughout the day. In this paper, a modified shape model was proposed for the better estimation of phenological dates and it is incorporated into the continuous AGDD (CAGDD) which was calculated based on temperatures from a continuous 24 h within a day, different from the calendar day or the average AGDD indicators. In this study, the CAGDD replaced the abscissa of the NDVI growth curve over a 5-year period (2014 to 2018, excluding 2015) for a test site of early rice in Jiangxi province of China. Four key phenological phases, including the reviving, tillering, heading and anthesis phases, were selected and determined with reference to the field-observed phenological data. The results show that compared with the AAGDD-SM, the method proposed in this paper has basically improved the prediction of each phenological period. For those cases where the average temperature is lower than the minimum temperatures (K1) but the effective accumulated temperature is not zero, more accurate AGDD can be calculated according to the method in this paper