Fuzzy superpixels for polarimetric SAR images classification

Superpixels technique has drawn much attention in computer vision applications. Each superpixels algorithm has its own advantages. Selecting a more appropriate superpixels algorithm for a specific application can improve the performance of the application. In the last few years, superpixels are widely used in polarimetric synthetic aperture radar (PolSAR) image classification. However, no superpixel algorithm is especially designed for image classification. It is believed that both mixed superpixels and pure superpixels exist in an image.Nevertheless, mixed superpixels have negative effects on classification accuracy. Thus, it is necessary to generate superpixels containing as few mixed superpixels as possible for image classification. In this paper, first, a novel superpixels concept, named fuzzy superpixels, is proposed for reducing the generation of mixed superpixels.In fuzzy superpixels ,not al lpixels are assigned to a corresponding superpixel. We would rather ignore the pixels than assigning them to improper superpixels. Second,a new algorithm, named FuzzyS(FS),is proposed to generate fuzzy superpixels for PolSAR image classification. Three PolSAR images are used to verify the effect of the proposed FS algorithm. Experimental results demonstrate the superiority of the proposed FS algorithm over several state-of-the-art superpixels algorithms

Research on the development law of karst caves on water conducting fractures under the influence of mining in Southwest Karst Mining Areas

Southwest Guizhou mining area is a typical karst development mining area in China. Under the influence of mining, the height of karst roof water conducting cracks is abnormally developed. During the rainy season, atmospheric precipitation is extremely easy to enter the underground working face through ultra-high water conducting channels, causing water inrush disasters at the working face, seriously affecting the normal production of the mine. Therefore, based on the analysis of the occurrence characteristics of karst caves in Xintian Coal Mine, the development rules of karst roof water conducting fracture zones during mining were studied by means of on-site measurement, indoor simulation, and theoretical analysis. The development mechanism of ultra-high water conducting fractures was revealed. The results show that: ①The roof karst caves in the study area have obvious zonation phenomenon from top to bottom in the layers such as the surface, the Yulongshan section, and the Changxing Formation. The surface water holes develop along the gullies, and the karst caves in the upper and middle parts of the strong aquifer in the Yulongshan section develop, presenting different forms of beads. The Changxing Formation only locally hosts karst caves with smaller diameters; ② Karst caves in karst aquifers have an important impact on water conducting fractures. Without karst caves, the development height of water conducting fractures is 43.1 m, and the fracture mining ratio is 14.4. Under karst caves, the development of water conducting fractures is abnormal, with a height of 173.1 m, and a fracture mining ratio of 57.7, which communicates with the strong limestone aquifer in the Yulong Mountain section; ③ Karst roof water conducting fissures consist of two parts: mining upward fissures and karst cave instability downward fissures. Under the influence of mining, karst caves become unstable under the combined action of concentrated stress and mining additional stress, and are prone to form downward fissures, which communicate with mining upward fissures, ultimately forming a special ultra-high water conducting fissure in southwestern Guizhou mining area

Fruit quality assessment based on mineral elements and juice properties in nine citrus cultivars

IntroductionCitrus fruit is considered a superfood due to its multiple nutritional functions and health benefits. Quantitative analysis of the numerous quality characteristics of citrus fruit is required to promote its sustainable production and industrial utilization. However, little information is available on the comprehensive quality assessment of various fruit quality indicators in different citrus cultivars.MethodsA total of nine different fresh citrus fruits containing seeds were collected as the experimental materials. The objectives of this study were: (i) to determine the morphological and juice properties of citrus fruits, (ii) to measure the mineral elements in the peel, pulp, and seeds, and (iii) to evaluate the fruit quality index (FQI) using the integrated quality index (IQI) and the Nemoro quality index (NQI) methods.ResultsThere were significant differences in fruit quality characteristics, including morphological, mineral, and juice quality, among the investigated citrus cultivars. The proportion of pulp biomass was the highest, followed by that of peel and seeds. N and Cu had the highest and lowest concentrations, respectively, among the measured elements across all citrus fruits, and the amounts of N, P, Mg, Cu, and Zn in seeds, K and Al in pulp, and Ca, Fe, and Mn in peel were the highest, dramatically affecting the accumulation of minerals in the whole fruit and their distribution in various fruit parts. Additionally, Ningmeng fruits had the highest vitamin C and titratable acidity (TA) but the lowest total soluble solids (TSS) and total phenolic (TP) contents, resulting in the lowest TSS/TA and pH values. In contrast, Jinju fruits had the highest TSS and TP contents. Based on the mineral element and juice quality parameters, principal component analysis showed that the citrus fruits were well separated into four groups, and the dendrogram also showed four clusters with different distances. The FQI range based on the IQI method (FQIIQI) and NQI method (FQINQI) was 0.382-0.590 and 0.106-0.245, respectively, and a positive relationship between FQIIQI and FQINQI was observed.ConclusionOur results highlight the great differences in mineral and juice characteristics among fruit parts, which mediated fruit quality. The strategy of fruit quality assessment using the FQI can be expanded for targeted utilization in the citrus industry

Complex-Valued Multi-Scale Fully Convolutional Network with Stacked-Dilated Convolution for PolSAR Image Classification

Polarimetric synthetic aperture radar (PolSAR) image classification is a pixel-wise issue, which has become increasingly prevalent in recent years. As a variant of the Convolutional Neural Network (CNN), the Fully Convolutional Network (FCN), which is designed for pixel-to-pixel tasks, has obtained enormous success in semantic segmentation. Therefore, effectively using the FCN model combined with polarimetric characteristics for PolSAR image classification is quite promising. This paper proposes a novel FCN model by adopting complex-valued domain stacked-dilated convolution (CV-SDFCN). Firstly, a stacked-dilated convolution layer with different dilation rates is constructed to capture multi-scale features of PolSAR image; meanwhile, the sharing weight is employed to reduce the calculation burden. Unfortunately, the labeled training samples of PolSAR image are usually limited. Then, the encoder–decoder structure of the original FCN is reconstructed with a U-net model. Finally, in view of the significance of the phase information for PolSAR images, the proposed model is trained in the complex-valued domain rather than the real-valued domain. The experiment results show that the classification performance of the proposed method is better than several state-of-the-art PolSAR image classification methods

Chaos Moth Flame Algorithm for Multi-Objective Dynamic Economic Dispatch Integrating with Plug-In Electric Vehicles

Dynamic economic dispatch (DED) plays an important role in the operation and control of power systems. The integration of DED with space and time makes it a complex and challenging problem in optimal decision making. By connecting plug-in electric vehicles (PEVs) to the grid (V2G), the fluctuations in the grid can be mitigated, and the benefits of balancing peaks and filling valleys can be realized. However, the complexity of DED has increased with the emergence of the penetration of plug-in electric vehicles. This paper proposes a model that takes into account the day-ahead, hourly-based scheduling of power systems and the impact of PEVs. To solve the model, an improved chaos moth flame optimization algorithm (CMFO) is introduced. This algorithm has a faster convergence rate and better global optimization capabilities due to the incorporation of chaotic mapping. The feasibility of the proposed CMFO is validated through numerical experiments on benchmark functions and various generation units of different sizes. The results demonstrate the superiority of CMFO compared with other commonly used swarm intelligence algorithms

Repression of recA Induction by RecX Is Independent of the RecA Protein in Deinococcus radiodurans▿

Besides inhibiting RecA activity at the protein level, Deinococcus radiodurans RecX can suppress RecA induction at the transcriptional level. The regulation of RecX on recA induction is independent of RecA activity, and its N terminus is involved in this process