Analysis of Water Body Segmentation from Landsat Imagery using Deep Neural Network

Wireless Personal Communications - The water body segmentation is precious for assessing its role in ecosystem services with the circumstances of climate change and global warming. The accurate...     

Multi-agent based collaborative fault detection and identification in chemical processes

Fault detection and identification (FDI) has received significant attention in literature. Popular methods for FDI include principal component analysis, neural-networks, and signal processing methods. However, each of these methods inherit certain strengths and shortcomings. A method that works well under one circumstance might not work well under another when different features of the underlying process come to the fore. In this paper, we show that a collaborative FDI approach that combines the strengths of various heterogeneous FDI methods is able to maximize diagnostic performance. A multi-agent framework is proposed to realize such collaboration in practice where different FDI methods, i.e: principal component analysis, self-organizing maps, non-parametric approaches, or neural-networks are combined. Since the results produced by different FDI agents might be in conflict, we use decision fusion methods to combine FDI results. Two different methods – voting-based fusion and Bayesian probability fusion are studied here. Most monitoring and fault diagnosis algorithms are computationally complex, but their results are often needed in real-time. One advantage of the multi-agent framework is that it provides an efficient means for speeding up the execution time of the various FDI methods through seamless deployment in a large-scale grid. The proposed multi-agent approach is illustrated through fault diagnosis of the startup of a lab-scale distillation unit and the Tennessee Eastman Challenge problem. Extensive testing of the proposed method shows that combining diagnostic classifiers of different types can significantly improve diagnostic performance.     

Harnessing defocus blur to recover high-resolution information in shape-from-focus technique

Traditional shape-from-focus (SFF) uses focus as the singular cue to derive the shape profile of a 3D object from a sequence of images. However, the stack of low-resolution (LR) observations is space-variantly blurred because of the finite depth of field of the camera. The authors propose to exploit the defocus information in the stack of LR images to obtain a super-resolved image as well as a high-resolution (HR) depth map of the underlying 3D object. Appropriate observation models are used to describe the image formation process in SFF. Local spatial dependencies of the intensities of pixels and their depth values are accounted for by modelling the HR image and the HR structure as independent Markov random fields. Taking as input the LR images from the stack and the LR depth map, the authors first obtain the super-resolved image of the 3D specimen and use it subsequently to reconstruct a HR depth profile of the object.     

Enhanced bioactivity of ZnO nanoparticles—an antimicrobial study

In this study, we investigate the antibacterial activity of ZnO nanoparticles with various particle sizes. ZnO was prepared by the base hydrolysis of zinc acetate in a 2-propanol medium and also by a precipitation method using Zn(NO₃)₂ and NaOH. The products were characterized by x-ray diffraction (XRD) analysis, transmission electron microscopy (TEM) and photoluminescence (PL) spectroscopy. Bacteriological tests such as minimum inhibitory concentration (MIC) and disk diffusion were performed in Luria-Bertani and nutrient agar media on solid agar plates and in liquid broth systems using different concentrations of ZnO by a standard microbial method for the first time. Our bacteriological study showed the enhanced biocidal activity of ZnO nanoparticles compared with bulk ZnO in repeated experiments. This demonstrated that the bactericidal efficacy of ZnO nanoparticles increases with decreasing particle size. It is proposed that both the abrasiveness and the surface oxygen species of ZnO nanoparticles promote the biocidal properties of ZnO nanoparticles.     

MIPS32?74KTM内核系列的微架构优势

1.简介 　　MIPS科技的MIPS32 74KTM内核系列采用全新的超标量、无序流水线架构,可通过可合成的方法实现优化的性能. 　　……     

Pole assignment with output feedback

For pole assignment with output feedback, appropriate partitioning of the coefficient matrix of the system numerator transfer function matrix leads to simplified design equations to solve for the vectors of the unity rank output feedback matrix. This concept is applied to derive the pole placement equations for the proportional-derivative output feedback dynamic compensator. The simplicity of the design procedure is illustrated with a numerical example.     

Aluminium as anode in primary alkaline batteries. Influence of additives on the corrosion and anodic behaviour of 2S aluminium in alkaline citrate solution

The inhibitive effects of various additives on the corrosion of 2S aluminium in 4N NaOH containing calcium oxide and sodium citrate (base electrolyte) have been examined by studying the self corrosion, anodic polarization and anode efficiency of 2S aluminium in solutions containing different additives. It has been found that among the different additives investigated, those forming anions in solution act favourably.     

Purification and properties of sulfite oxidase from human liver

Sulfite oxidase has been purified to near homogeneity from human liver. Properties of the molecule have been investigated and compared to those of the rat liver enzyme which has been isolated in a pure form. Both proteins exist as dimeric molecules with one molybdenum and one cytochrome b5-type heme per sub-unit. The human enzyme has a slightly larger subunit molecular weight (61,100 vs. 57,200 daltons) and is a more negatively charged molecule. Decreased reactivity of the human enzyme with various electron acceptors suggests the presence of nonfunctional molybdenum centers in a portion of the molecules isolated. Human liver sulfite oxidase cross-reacts strongly with antibody prepared against the rat liver enzyme. Human enzyme activity is precipitated by antibody at concentrations about twofold greater than required for comparable complexation of rat sulfite oxidase.