A Convolutional Neural Network with Parallel Multi-Scale Spatial Pooling to Detect Temporal Changes in SAR Images

In synthetic aperture radar (SAR) image change detection, it is quite challenging to exploit the changing information from the noisy difference image subject to the speckle. In this paper, we propose a multi-scale spatial pooling (MSSP) network to exploit the changed information from the noisy difference image. Being different from the traditional convolutional network with only mono-scale pooling kernels, in the proposed method, multi-scale pooling kernels are equipped in a convolutional network to exploit the spatial context information on changed regions from the difference image. Furthermore, to verify the generalization of the proposed method, we apply our proposed method to the cross-dataset bitemporal SAR image change detection, where the MSSP network (MSSP-Net) is trained on a dataset and then applied to an unknown testing dataset. We compare the proposed method with other state-of-arts and the comparisons are performed on four challenging datasets of bitemporal SAR images. Experimental results demonstrate that our proposed method obtains comparable results with S-PCA-Net on YR-A and YR-B dataset and outperforms other state-of-art methods, especially on the Sendai-A and Sendai-B datasets with more complex scenes. More important, MSSP-Net is more efficient than S-PCA-Net and convolutional neural networks (CNN) with less executing time in both training and testing phases

Excellent performance of Pt-C/TiO2 for methanol oxidation:contribution of mesopores and partially coated carbon

Partial deposition of carbon onto mesoporous TiO2 (C/TiO2) were prepared as supporting substrate for Pt catalyst development. Carbon deposition is achieved by in-situ carbonization of furfuryl alcohol. The hybrid catalysts were characterized by XRD, Raman, SEM and TEM and exhibited outstanding catalytic activity and stability in methanol oxidation reaction. The heterogeneous carbon coated on mesoporous TiO2 fibers provided excellent electrical conductivity and strong interfacial interaction between TiO2 support and Pt metal nanoparticles. Methanol oxidation reaction results showed that the activity of Pt-C/TiO2 is 3.0 and 1.5 times higher than that of Pt-TiO2 and Pt-C, respectively. In addition, the Pt-C/TiO2 exhibited a 6.7 times enhanced stability compared with Pt-C after 2000 cycles. The synergistic effect of C/TiO2 is responsible for the enhanced activity of Pt-C/TiO2, and its excellent durability could be ascribed to the strong interfacial interaction between Pt nanoparticles and C/TiO2 support

Hyperspectral Band Selection Using Improved Classification Map

Although it is a powerful feature selection algorithm, the wrapper method is rarely used for hyperspectral band selection. Its accuracy is restricted by the number of labeled training samples and collecting such label information for hyperspectral image is time consuming and expensive. Benefited from the local smoothness of hyperspectral images, a simple yet effective semisupervised wrapper method is proposed, where the edge preserved filtering is exploited to improve the pixel-wised classification map and this in turn can be used to assess the quality of band set. The property of the proposed method lies in using the information of abundant unlabeled samples and valued labeled samples simultaneously. The effectiveness of the proposed method is illustrated with five real hyperspectral data sets. Compared with other wrapper methods, the proposed method shows consistently better performance

Deconvolution Filtering for Nonlinear Stochastic Systems with Randomly Occurring Sensor Delays via Probability-Dependent Method

This paper deals with a robust H∞ deconvolution filtering problem for discrete-time nonlinear stochastic systems with randomly occurring sensor delays. The delayed measurements are assumed to occur in a random way characterized by a random variable sequence following the Bernoulli distribution with time-varying probability. The purpose is to design an H∞ deconvolution filter such that, for all the admissible randomly occurring sensor delays, nonlinear disturbances, and external noises, the input signal distorted by the transmission channel could be recovered to a specified extent. By utilizing the constructed Lyapunov functional relying on the time-varying probability parameters, the desired sufficient criteria are derived. The proposed H∞ deconvolution filter parameters include not only the fixed gains obtained by solving a convex optimization problem but also the online measurable time-varying probability. When the time-varying sensor delays occur randomly with a time-varying probability sequence, the proposed gain-scheduled filtering algorithm is very effective. The obtained design algorithm is finally verified in the light of simulation examples

Novel mesoporous TiO2(B) whisker-supported sulfated solid superacid with unique acid characteristics and catalytic performances

Mesoporous TiO2(B) whisker was firstly applied as a support for synthesizing the novel sulfated solid superacid (SO42−/TiO2(B)). According to NH3-TPD, TG and Py-IR characterization results, it was found that the similar amount of sulfate group on TiO2(B) and anatase showed significantly different acid characteristics and catalytic performances. The total acid amount of SO42−/TiO2(B) was about 1.8 times as anatase-supported sulfated solid superacid (SO42−/Anatase). Simultaneously, the SO42−/TiO2(B) possessed higher percentage of Brønsted acid and more weak-medium acid strength than SO42−/Anatase. These acidic properties endowed SO42−/TiO2(B) with the increased esterification reaction rate and decreased alkylation byproduct selectivity compared with that of SO42−/Anatase. Structure-performance analysis exhibited that there were more bridged bidentate sulfate groups coordinated to the TiO2(B) in SO42−/TiO2(B), which could induce more Ti cations than that of the chelating one. This was the key factor to be responsible for the unique acid characteristics of SO42−/TiO2(B). The present work provides a novel solid superacid and might open a strategy to mediate the acid characteristic for sulfated solid superacid

Control mechanism of the migration of heavy metal ions from gangue backfill bodies in mined-out areas

In the process of solid backfill mining, the leaching of heavy metal ions from the gangue backfill body in the mined-out area can pose potential risk of polluting water resources in the mine. Accordingly, based on the environment of the gangue backfill body, the migration model of heavy metal ions from the gangue backfill body was established to reveal the pollution mechanism of water resources by the gangue backfill body in the mined-out area. The main factors that affect the migration of heavy metal ions were analyzed, and prevention and control techniques for the leaching and migration of heavy metal ions from gangue backfill bodies were proposed. Research showed that the heavy metal ions in gangue backfill bodies were subjected to the coupled action of seepage, concentration, and stress and then driven by water head pressure and gravitational potential energy to migrate downward along the pore channels in the floor, during which mine water served as the carrier. The migration distance of heavy metal ions increased with time. According to the migration rate, the migration process can be subdivided into three phases: the rapid migration phase (0–50 years), the slow migration phase (50–125 years), and the stable phase (125–200 years). It was concluded that the leaching concentration of heavy metal ions, the particle size of gangue, the permeability of floor strata, and the burial depth of coal seams were the main influencing factors of the migration of heavy metal ions. From the two perspectives of heavy metal ion leaching and migration, prevention and control techniques for the leaching and migration of heavy metal ions from gangue backfill bodies were proposed to protect water resources in mining area. The present study is of great significance to realizing utilization of solid waste in mines and protecting the ecological environment