烧结工艺对硼泥玻璃陶瓷显微结构和性能的影响

以硼泥为主要原料对制备玻璃陶瓷工艺进行研究,实验中发现烧结温度和烧结时间对析晶相的成分影响较小,但玻璃陶瓷的表面形貌影响较大;当烧结温度高于析晶温度时,对晶体尺寸影响更大;根据不同烧结温度和烧结时间对玻璃陶瓷结构影响,找出适合的最佳烧结温度和烧结时间,其值为781℃,时间为4h。     

A Rough RBF Neural Network Based on Weighted Regularized Extreme Learning Machine

Adjusting parameters iteratively is a traditional way of training neural networks, and the Rough RBF Neural Networks (R-RBF-NN) follows the same idea. However, this idea has many disadvantages, for instance, the training accuracy and generalization accuracy etc. So how to change this condition is a hot topic in Academics. On the basis of Extreme Learning Machine (ELM), this paper proposes a Weighted Regularized Extreme Learning Machine (WRELM), taking into account both minimizing structured risk and weighted least-squares principle, to train R-RBF-NN. The traditional iterative training method is replaced by the minimal norm least-squares solution of general linear system. The method proposed in this paper, increasing controllability of the entire learning process and considering the structured risk and empirical risk, can improve the performance of learning and generalization. Experiments show that it can reach a very superior performance in both time and accuracy when WRELM trains the Rough RBF Neural Networks in pattern classification and function regression, especially in pattern classification, which can improve the generalization accuracy more than 3.36 % compared with ELM. Obviously, the performance of the method proposed in this paper is better than the traditional methods.     

Image super-resolution based on multi-space sparse representation

Sparse representation provides a new method of generating a super-resolution image from a single low resolution input image. An over-complete base for sparse representation is an essential part of such methods. However, discovering the over-complete base with efficient representation from a large amount of image patches is a difficult problem. In this paper, we propose a super-resolution construction based on multi-space sparse representation to efficiently solve the problem. In the representation, image patches are decomposed into a structure component and a texture component represented by the over-complete bases of their own spaces so that their high-level features can be captured by the bases. In the implementation, a prior knowledge about low resolution images generation is combined to the typical base construction for high construction quality. Experiment results demonstrate that the proposed method significantly improves the PSNR, SSIM and visual quality of reconstructed high-resolution image.     

Detecting and tracking dim small targets in infrared image sequences under complex backgrounds

This paper presents a unified framework for automatically detecting and tracking dim small targets in infrared (IR) image sequence under complex backgrounds. Firstly, the variance weighted information entropy (variance WIE) followed by a region growing technique is introduced to segment the candidate targets in a single-frame IR image after background suppression. Then the pipeline filter is used to verify the real targets. The position and the size of the detected target are then obtained to initialize the tracking algorithm. Secondly, we adopt an improved local binary pattern (LBP) scheme to represent the target texture feature and propose a joint gray-texture histogram method for a more distinctive and effective target representation. Finally, target tracking is accomplished by using the mean shift algorithm. Experimental results indicate that the proposed method can effectively detect the dim small targets under complex backgrounds and has better tracking performance compared with the gray histogram based tracking methods such as the mean shift and the particle filtering.     

Prediction-based realistic 3D model compression

The benefit of using the geometry image to represent an arbitrary 3D mesh is that the 3D mesh can be re-sampled as a completely regular structure and coded efficiently by common image compression methods. For geometry image-based 3D mesh compression, we need to code the normal-map images while coding geometry images to improve the subjective quality and realistic effects of the reconstructed model. In traditional methods, a geometry image and a normal-map image are coded independently. However a strong correlation exists between these two kinds of images, because both of them are generated from the same 3D mesh and share the same parameterization. In this paper we propose a predictive coding framework, in which the normal-map image is predicted based on the geometric correlation between them. Additionally we utilize the strong geometric correlation among three components of normal-map image to improve the predicting accuracy. The experimental results show the proposed coding framework improves the coding efficiency of normal-map image, meanwhile the realistic effect of a 3D mesh is significantly enhanced.     

凝胶注模成形技术的研究与发展

凝胶注模成形是一种近净尺寸成形工艺，是制备形状复杂、成分均匀和可靠性高的陶瓷材料的理想成形工艺。笔者阐述了凝胶注模成形工艺过程和成形原理，以及国内外的研究现状，指出了凝胶注模成形技术的未来发展方向。     

集成电路密封用高纯邻甲酚醛环氧树脂的制备

ECN树脂中的可水解氯含量是决定树脂质量的—个重要指标。本文研究了反应温度、ECH/OCN配比、反应时间和碱用量等因素的影响,取得了规律性的认识,并获得最佳配方,制备出高纯度的ECN树脂系列产品。     

二烷基二硫代氨基甲酸镉的合成及应用研究

合成了润滑油添加剂二戊基二硫代氨基甲酸镉,利用四球试验机研究了其在矿物基础油中的极压、抗磨性能,以及与二烷基二硫代磷酸锌(T202)有机硼酸酯和磷酸三苯酯添加剂之间的抗磨协同性能。结果表明,此添加剂体现出了较好的抗磨性能和承载能力,并且与两种硼酸酯都体现出了良好的抗磨协同性能。另外,通过箱热氧化试验简单评价了其抗氧化性能,结果表明,该添加剂具有良好的高温抗氧化性能。     

以职业能力为本位的高职动漫专业项目化课程的实践研究

为培养与动漫企业相对接的人才,我校动漫专业进行了以职业能力为本位的项目化课程的实践研究。以项目化课程开发理论为指导,树立"职业能力本位"的课程体系构建理念,合理选择项目化课程内容,并以动漫专业的核心课程为例,探讨项目化课程在高职教育教学改革中的适应性和应用价值。     

PE-UHMW挤出中空吹塑设备与工艺的研究

改型设计了改性超高相对分子质量聚乙烯的挤出中空吹塑设备，设计采用了专用的挤出螺杆、机筒、模头和模具，并研究改进了吹塑工艺及生产方法，从而克服了超高相对分子质量聚乙烯的加工难点，得到了合格的吹塑制品。