Balanced Coarsening for Multilevel Hypergraph Partitioning via Wasserstein Discrepancy

We propose a balanced coarsening scheme for multilevel hypergraph partitioning. In addition, an initial partitioning algorithm is designed to improve the quality of k-way hypergraph partitioning. By assigning vertex weights through the LPT algorithm, we generate a prior hypergraph under a relaxed balance constraint. With the prior hypergraph, we have defined the Wasserstein discrepancy to coordinate the optimal transport of coarsening process. And the optimal transport matrix is solved by Sinkhorn algorithm. Our coarsening scheme fully takes into account the minimization of connectivity metric (objective function). For the initial partitioning stage, we define a normalized cut function induced by Fiedler vector, which is theoretically proved to be a concave function. Thereby, a three-point algorithm is designed to find the best cut under the balance constraint

The Magnetic Properties of 1111-type Diluted Magnetic Semiconductor (La1−x_{1-x}Bax_{x})(Zn1−x_{1-x}Mnx_{x})AsO in the Low Doping Regime

We investigated the magnetic properties of (La$_{1-x}$Ba$_{x}$)(Zn$_{1-x}$Mn$_{x}$)AsO with $x$ varying from 0.005 to 0.05 at an external magnetic field of 1000 Oe. For doping levels of $x$ $\leq$ 0.01, the system remains paramagnetic down to the lowest measurable temperature of 2 K. Only when the doping level increases to $x$ = 0.02 does the ferromagnetic ordering appear. Our analysis indicates that antiferromagnetic exchange interactions dominate for $x$ $\leq$ 0.01, as shown by the negative Weiss temperature fitted from the magnetization data. The Weiss temperature becomes positive, i.e., ferromagnetic coupling starts to dominate, for $x$ $\geq$ 0.02. The Mn-Mn spin interaction parameter $\mid$$2J/k_B$$\mid$ is estimated to be in the order of 10 K for both $x$ $\leq$ 0.01 (antiferromagnetic ordered state) and $x$ $\geq$ 0.02 (ferromagnetic ordered state). Our results unequivocally demonstrate the competition between ferromagnetic and antiferromagnetic exchange interactions in carrier-mediated ferromagnetic systems.Comment: 9 pages, 3 figure

Fuzzy Sparse Autoencoder Framework for Single Image Per Person Face Recognition

The issue of single sample per person (SSPP) face recognition has attracted more and more attention in recent years. Patch/local-based algorithm is one of the most popular categories to address the issue, as patch/local features are robust to face image variations. However, the global discriminative information is ignored in patch/local-based algorithm, which is crucial to recognize the nondiscriminative region of face images. To make the best of the advantage of both local information and global information, a novel two-layer local-to-global feature learning framework is proposed to address SSPP face recognition. In the first layer, the objective-oriented local features are learned by a patch-based fuzzy rough set feature selection strategy. The obtained local features are not only robust to the image variations, but also usable to preserve the discrimination ability of original patches. Global structural information is extracted from local features by a sparse autoencoder in the second layer, which reduces the negative effect of nondiscriminative regions. Besides, the proposed framework is a shallow network, which avoids the over-fitting caused by using multilayer network to address SSPP problem. The experimental results have shown that the proposed local-to-global feature learning framework can achieve superior performance than other state-of-the-art feature learning algorithms for SSPP face recognition

Combining hydrogen peroxide addition with sunlight regulation to control algal blooms

The concentration, light conditions during treatment, and the number of hydrogen peroxide (H2O2) additions as well as the H2O2 treatment combined with subsequent shading to control algal blooms were studied in the field (Lake Dianchi, China). The cyanobacterial stress and injury due to H2O2 were dose dependent, and the control effectiveness and degradation of H2O2 were better and faster under full light than under shading. However, H2O2 was only able to control a bloom for a short time, so it may have promoted the recovery of algae and allowed the biomass to rebound due to the growth of eukaryotic algae. A second addition of H2O2 at the same dose had no obvious effect on algal control in the short term, suggesting that a higher concentration or a delayed addition should be considered, but these alternative strategies are not recommended so that the integrity of the aquatic ecosystem is maintained and algal growth is not promoted. Moreover, shading (85%) after H2O2 addition significantly reduced the algal biomass during the enclosure test, no restoration was observed for nearly a month, and the proportion of eukaryotic algae declined. It can be inferred that algal blooms can be controlled by applying a high degree of shading after treatment with H2O2.</p

Four-Dimensional Higher-Order Chern Insulator and Its Acoustic Realization

We present a theoretical study and experimental realization of a system that is simultaneously a four-dimensional (4D) Chern insulator and a higher-order topological insulator (HOTI). The system sustains the coexistence of (4-1)-dimensional chiral topological hypersurface modes (THMs) and (4-2)-dimensional chiral topological surface modes (TSMs). Our study reveals that the THMs are protected by second Chern numbers, and the TSMs are protected by a topological invariant composed of two first Chern numbers, each belonging a Chern insulator existing in sub-dimensions. With the synthetic coordinates fixed, the THMs and TSMs respectively manifest as topological edge modes (TEMs) and topological corner modes (TCMs) in the real space, which are experimentally observed in a 2D acoustic lattice. These TCMs are not related to quantized polarizations, making them fundamentally distinctive from existing examples. We further show that our 4D topological system offers an effective way for the manipulation of the frequency, location, and the number of the TCMs, which is highly desirable for applications.Comment: Main text 19 pages, 6 figures. Supplemental materials 18 pages, 12 figure

Thickness effects on fibre-bridged fatigue delamination growth in composites

This paper provides an investigation on thickness effects on fibre-bridged fatigue delamination growth (FDG) in composite laminates. A modified Paris relation was employed to interpret experimental fatigue data. The results clearly demonstrated that both thickness and fibre bridging had negligible effects on FDG behaviors. Both energy principles and fractography analysis were subsequently performed to explore the physical reasons of this independence. It was found that the amount of energy release of a given crack growth was not only independent of fibre bridging, but also thickness. Fibre print was the dominant microscopic feature located on fracture surfaces, physically making the same energy dissipation during FDG. Furthermore, the present study provides extra evidence on the importance of using an appropriate similitude parameter in FDG studies. Particularly, the strain energy release rate (SERR) range applied around crack front was demonstrated as an appropriate similitude parameter for fibre-bridged FDG study

Thermoelastic Stresses Alleviation for Two-Dimensional Functionally Graded Cylinders Under Asymmetric Loading

Open Access via the Taylor and Francis Agreement Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Peer reviewedPublisher PD

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