Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Enhanced photoreactivity of MOFs by intercalating interlayer bands via simultaneous ?NCO and ?SCu modification

Herein, we propose a novel method to enhance the photoreactivity of an MOF catalyst by grafting isocyanate bonds ( NCO) and sulfhydryl-complexed copper ( SCu) onto ZIF-8 (NIF-SCu). The grafting process intercalated interlayer bands between the conduction and valence bands of ZIF-8, thereby providing a “ladder” for facile electron transition. The extreme improvement in the photoreactivity of NIF-SCu could be attributed to the enhancement in light responses in the range of 350–450 nm by  NCO groups and the widening of the visible light range of the MOF by  SCu groups. The formation of staggered energy levels in NIF-SCu could also narrow the band gap, lower the resistance, and facilitate the transfer of photogenerated carriers, thereby generating electrons with strong reduction potential in the  SCu conduction band. This study provides a new strategy for improving or even endowing the photoactivity of environmental functional materials with wide bandgaps.     

Stabilization of 6H-Hexagonal SrMnO3 Polymorph by Al2O3 insertion

We demonstrate the structural evolution of polymorphic phases in Al₂O₃-inserted SrMnO₃ ceramics synthesized by solid state reaction. While the 4H-hexagonal phase is predominant in pure SrMnO₃ ceramics, a small amount of 6H-hexagonal polymorph is identified in addition to the primary 4H-hexagonal SrMnO₃ and the secondary hexagonal SrAl₂O₄ phases in the as-sintered ceramics, evidenced by x-ray diffraction and subsequent Rietveld refinement analyses. The existence of the 6H-hexagonal SrMnO₃ phase is corroborated using Raman spectroscopy. The chemical compositions and electronic structures of the Al₂O₃-inserted SrMnO₃ compounds are also examined using energy dispersive spectroscopy and x-ray photoelectron spectroscopy, respectively. The first-principles calculations reveal that there is no clear difference between the total energies of 4H- and 6H-hexagonal polymorphs regardless of the presence/absence of Sr and oxygen vacancies. Possible origins are discussed with the estimation of actual strain based on the refined lattice parameter of 6H SrMnO₃.     

Damage evolution in polymer due to exposure to high-pressure hydrogen gas

The use of hydrogen as a fuel is increasing exponentially, and the most economical way to store and transport hydrogen for fuel use is as a high-pressure gas. Polymers are widely used for hydrogen distribution and storage systems because they are chemically inert towards hydrogen. However, when exposed to high-pressure hydrogen, some hydrogen diffuses through polymers and occupies the preexisting cavities inside the material. Upon depressurization, the hydrogen trapped inside polymer cavities can cause blistering or cracking by expanding these cavities. A continuum mechanics–based deformation model was deployed to predict the stress distribution and damage propagation while the polymer undergoes depressurization after high-pressure hydrogen exposure. The effects of cavity size, cavity location, and pressure inside the cavity on damage initiation and evolution inside the polymer were studied. The stress and damage evolution in the presence of multiple cavities was also studied, because interaction among cavities alters the damage and stress field. It was found that all these factors significantly change the stress state in the polymer, resulting in different paths for damage propagation. The effect of adding carbon black filler particles and plasticizer on the damage was also studied. It was found that damage tolerance of the polymer increases drastically with the addition of carbon black fillers, but decreases with the addition of the plasticizer.     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.