3D image retrieval based on differential geometry and co-occurrence matrix

3D image retrieval approach is a challenging problem in the research of content-based image retrieval. In this paper, a novel retrieval approach combined differential geometry and co-occurrence matrix is presented. Firstly, Gaussian curvature and mean curvature are utilized to represent the inherent characteristic of spatial surface, and then we use co-occurrence matrix to store the shape information of 3D images. Secondly, normalization process is applied to the co-occurrence matrix and the invariants independence of the translation, scaling, and rotation transforms are proved. In comparison with the recent methods, experiments indicate a lower computation complexity and a better retrieval rate to 3D images with slight different shape characteristic.     

Memristor-based chaotic neural networks for associative memory

In chaotic neural networks, the rich dynamic behaviors are generated from the contributions of spatio-temporal summation, continuous output function, and refractoriness. However, a large number of spatio-temporal summations in turn make the physical implementation of a chaotic neural network impractical. This paper proposes and investigates a memristor-based chaotic neural network model, which adequately utilizes the memristor with unique memory ability to realize the spatio-temporal summations in a simple way. Furthermore, the associative memory capabilities of the proposed memristor-based chaotic neural network have been demonstrated by conventional methods, including separation of superimposed pattern, many-to-many associations, and successive learning. Thanks to the nanometer scale size and automatic memory ability of the memristors, the proposed scheme is expected to greatly simplify the structure of chaotic neural network and promote the hardware implementation of chaotic neural networks.     

Dynamic watermarking scheme for quantum images based on Hadamard transform

In this paper, a novel watermarking scheme for quantum images based on Hadamard transform is proposed. In the new scheme, a unitary transform controlled by a classical binary key is implemented on quantum image. Then, we utilize a dynamic vector, instead of a fixed parameter as in other previous schemes, to control the embedding process. The dynamic embedding vector is decided by both the carrier quantum image and the watermark image, which is only known by the authorized owner. The proposed scheme is analyzed from visual quality, computational complexity, and payload capacity. Analysis and results show that the proposed scheme has better visual quality under a higher embedding capacity and lower complexity compared with other schemes proposed recently.     

量子图像处理问题综述

量子图像处理问题将是量子计算机时代媒体信息处理的一个主要问题。量子图像处理包括一般的处理问题和安全方面的处理问题。本文介绍和分析了量子图像表示方式和处理等问题的最新研究成果。首先给出了目前量子图像处理的一般架构,然后介绍了目前流行的量子图像表示方法、并根据不同的量子图像处理目的对现有的处理算法进行了分类和分析,最后总结并展望了量子图像处理领域的未来发展方向。     

新型可见光固化口腔正畸粘合剂研制

介绍了一种新型可见光固化正畸粘合剂的组成、性能及正畸粘接的工艺。此粘合剂由一种单组分液体底胶和单组分糊剂组成。与化学固化粘合剂相比,其操作使用方便,固化时间短。这种新型粘合剂的粘接强度完全满足了正畸粘合剂的要求。     

二氢茉莉酮酸甲酯的合成进展

二氢茉莉酮酸甲酯是一种重要的合成香料,目前尚未见有直接从天然产物中提取的产业化文献报道,其香气独特优异,性质稳定,对其合成方法的研究一直是化学工作者们的科研热点。本文对其合成方法的研究进行了综述。     

低挥发分煤在新型干法窑生产中的应用

对劣质煤、低挥发分煤的燃烧特性分析,工艺设备分析,提出预分解窑烧劣质煤、低挥发分煤的可能性、必要性,为我公司烧劣质煤、无烟煤打下了基础。     

无卤阻燃EPDM胶料的性能预测

用回归分析法对EPDM胶料的阻燃性和物理机械性能进行研究并预测胶料的性能．结果表明：无卤阻燃EPDM胶料的阻燃性随氢氧化铝用量和硼酸锌用量增加而提高，物理机械性能则有所下降，建立的数学模型能较好地拟合胶料各项性能与氢氧化铝用量和硼酸锌用量之间的关系，能够准确地预测含不同氯氧化铝用量和硼酸锌用量胶料的性能。     

填充母料及其他常用塑料母料

塑料母料对推动塑料工业的迅猛发展起了很大作用，其主要特点是：可以简化生产工艺过程：原料混合方便，混炼质量均匀，提高生产效率及制品性能指标；减少粉尘飞扬及对设备的磨损；降低制品在换色时清洗螺杆的用料量；延长原料储存的保质期等。