Compressed sensing for image processing

Data compression technology is one of the effective measures to improve the wireless data transmission speed. The traditional data compression technology is based on Nyquist sampling law, and reduces its redundancy according to the characteristics of the data itself, so as to achieve the purpose of compression. The compressed sensing theory (CS) that has emerged in recent years is not subject to Nyquist sampling law. It uses non adaptive linear projection to maintain the original structure of the signal, and extracts as much information from as little data as possible by directly collecting compressed data. This dissertation expounds the basic principle of compressed sensing method, analyzes the CS theoretical framework and key technical problems, introduces the advantages of compressed sensing technology in wireless sensing, focuses on the latest progress in signal sparse transformation, observation matrix design and signal reconstruction algorithm, and discusses the existing difficult problems in the research. Using MATLAB software, based on the different Dictionary matrix selection, such as random matrix and discrete cosine transform (DCT) matrix, the high probability reconstruction of one-dimensional signal and twodimensional image is realized by diverse algorithms, like iteration soft threshold algorithm (IST), iteration hard threshold algorithm (IHT), and orthogonal matching pursuit algorithm (OMP). Comparing the reconstructed results with the original signal, the results show that as long as the sampling number m (much less than the sampling rate required by Nyquist theorem) can contain the useful information required by the image, CS algorithm can accurately reconstruct the image, and the reconstruction effect is also better. Moreover, some further discussion is also included, regarding the CS algorithm used in image inpainting and image denoising.Master of Science (Signal Processing

An Efficient High-Resolution Global–Local Network to Detect Lunar Features for Space Energy Discovery

Lunar craters and rilles are significant topographic features on the lunar surface that will play an essential role in future research on space energy resources and geological evolution. However, previous studies have shown low efficiency in detecting lunar impact craters and poor accuracy in detecting lunar rilles. There is no complete automated identification method for lunar features to explore space energy resources further. In this paper, we propose a new specific deep-learning method called high-resolution global–local networks (HR-GLNet) to explore craters and rilles and to discover space energy simultaneously. Based on the GLNet network, the ResNet structure in the global branch is replaced by HRNet, and the residual network and FPN are the local branches. Principal loss function and auxiliary loss function are used to aggregate global and local branches. In experiments, the model, combined with transfer learning methods, can accurately detect lunar craters, Mars craters, and lunar rilles. Compared with other networks, such as UNet, ERU-Net, HRNet, and GLNet, GL-HRNet has a higher accuracy (88.7 ± 8.9) and recall rate (80.1 ± 2.7) in lunar impact crater detection. In addition, the mean absolute error (MAE) of the GL-HRNet on global and local branches is 0.0612 and 0.0429, which are better than the GLNet in terms of segmentation accuracy and MAE. Finally, by analyzing the density distribution of lunar impact craters with a diameter of less than 5 km, it was found that: (i) small impact craters in a local area of the lunar north pole and highland (5°–85°E, 25°–50°S) show apparent high density, and (ii) the density of impact craters in the Orientale Basin is not significantly different from that in the surrounding areas, which is the direction for future geological research

Development of continuous V-shaped structure for high heat flux components of flat-type divertor

The continuous V-shaped structure with hypervapotron for divertor target can improve the cooling performance and detachment in the strike point area. The design and manufacture of this structure has been described in this work. The continuous V-shaped structure in a flat-type divertor is beneficial for divertor detachment because it has a deep slot that can trap neutral particles. The target cooled by hypervapotron is designed to sustain stationary heat flux up to ∼ 10 MW· m−2. The hypervapotron structure is directly connected at the root of the V configuration and expands the potential candidate area of the strike point for better adaptability to different plasma configurations. The simulation results demonstrate that temperature of the structure meets the allowance values of the materials because the strike point hits at the inner tip of V-shaped structure, i.e. the extreme point. The heat-sink composite panel used is made of CuCrZr and 316L stainless steel and is formed by explosive welding. The V-shaped structure is made by bending, machining, and brazing. Finally, three continuous V-shaped structure mockups were fabricated and tested to demonstrate the feasibility of engineering design

Shaping of Metal–Organic Frameworks: From Fluid to Shaped Bodies and Robust Foams

The applications of metal–organic frameworks (MOFs) toward industrial separation, catalysis, sensing, and some sophisticated devices are drastically affected by their intrinsic fragility and poor processability. Unlike organic polymers, MOF crystals are insoluble in any solvents and are usually not thermoplastic, which means traditional solvent- or melting-based processing techniques are not applicable for MOFs. Herein, a continuous phase transformation processing strategy is proposed for fabricating and shaping MOFs into processable fluids, shaped bodies, and even MOF foams that are capable of reversible transformation among these states. Based on this strategy, a cup-shaped Cu-MOF composite and hierarchically porous MOF foam were developed for highly efficient catalytic C–H oxidation (conv. 76% and sele. 93% for cup-shaped Cu-MOF composite and conv. 92% and sele. 97% for porous foam) with ease of recycling and dramatically improved kinetics. Furthermore, various MOF-based foams with low densities (<0.1 g cm^–3) and high MOF loadings (up to 80 wt %) were obtained via this protocol. Imparted with hierarchically porous structures and fully accessible MOFs uniformly distributed, these foams presented low energy penalty (pressure drop <20 Pa, at 500 mL min^–1) and showed potential applications as efficient membrane reactors

Enantioselective Effects of Metalaxyl Enantiomers in Adolescent Rat Metabolic Profiles Using NMR-Based Metabolomics

More than 30% of the registered pesticides are chiral with one or more chiral centers and exist as two or more enantiomers. The frequency of chiral chemicals and their environmental safety has been considered in their risk assessment in recent decades. Despite the fact that metabolic disturbance is an important sensitive molecular initiating event of toxicology effects, the potential mechanisms of how chiral compounds affect metabolism phenotypes in organisms remain unclear. As a typical chiral pesticide, metalaxyl is an acylalanine fungicide with systemic function. Although the fungicidal activity almost comes from the <i>R</i>-enantiomer, the toxicity of both enantiomers in animals and human beings is not yet clear. In this study, a nuclear magnetic resonance (NMR)-based metabolomics approach was adopted to evaluate the enantioselectivity in metabolic perturbations in adolescent rats. On the basis of multivariate statistical results, stable and evident metabolic profiles of the enantiomers were obtained. When rats were exposed to <i>R</i>-metalaxyl, the significantly perturbed metabolic pathways were biosynthesis of valine, leucine, and isoleucine, synthesis and degradation of ketone bodies, and metabolism of glycerolipid. In contrast, more significantly perturbed metabolic pathways were obtained when the rats were exposed to <i>S</i>-metalaxyl, including glycolysis, biosynthesis of valine, leucine, and isoleucine, metabolism of glycine, serine, and threonine, synthesis and degradation of ketone bodies, metabolism of glycerophospholipid and glycerolipid. These abnormal metabolic pathways were closely related to liver metabolism. These results offer more detailed information about the enantioselective metabolic effects of metalaxyl in adolescent development and provide data for the health risk assessment of metalaxyl at molecular level

Facile Fabrication of Multifunctional Metal–Organic Framework Hollow Tubes To Trap Pollutants

Pollutant treatment is critical in modern society and often requires tedious workup and expensive facilities. By virtue of structural diversity and tunability, metal–organic frameworks (MOFs) have shown promise in pollutant control. We herein report a powerful templated freeze-drying protocol for the fabrication of multifunctional MOF hollow tubular structures for both air and liquid contaminants filtration. Various hollow tube systems (e.g., “Janus”, “coaxial” and “cellular”) are produced. Specially, a multilayer coaxial MOF hollow tube is prepared for highly efficient capture of mixed inorganic–organic liquid contaminants with >94% filtration efficiency. Further, a “cellular” hollow tube with low pressure-drop (12 Pa, 10 cm s^–1) is applied in particulate matter filtration with high efficiency (>92%). Given the rich structural and functional diversities, this protocol might bring MOFs into industrial applications to remediate environmental problems