Optimization and regularization of complex task decomposition for blind removal of multi-factor degradation

Most existing image restoration methods based on deep neural networks are developed for images which only degraded by a single degradation mode and imaging under an ideal condition. They cannot be directly used to restore the images degraded by multi-factor coupling. A complex task decomposition regularization optimization strategy (TDROS) is proposed to solve the problem. The restoration of images degraded by multi-factor coupling is a complex task that can be solved by separating these multiple factors, that is, breaking the complex task into numbers of simpler tasks to make the entire complex problem be overcome more easily. Motivated by this idea, the TDROS decomposes the complex task of image restoration into two sub-task: the potential task constrained by regularization and the main task for reconstructing high-definition images. In TDROS, the front of the neural network is focused on the restoration of images degraded by additive noise, while the other part of the network is focused mainly on the restoration of images degraded by blur. We applied the TDROS to an 11-layer convolutional neural network (CNN) and compared it with initial CNNs from the aspects of restoration accuracy and generalization ability. Based on these results, we used TDROS to design a novel network model for the restoration of atmospheric turbulence-degraded images. The experimental results demonstrate that the proposed TDROS can improve the generalization ability of the existing network more effectively than current popular methods, offering a better solution for the problem of severely degraded image restoration. Moreover, the TDROS concept provides a flexible framework for low-level visual complex tasks and can be easily incorporated into existing CNNs.     

蛇纹石酸浸提镁残渣制备硅酸锂及其性能研究

以蛇纹石酸浸提镁残渣为硅源,碳酸锂为锂源,通过高温固相反应合成了硅酸锂高温固碳材料,探究了煅烧时间、气氛以及物料配比对合成材料高温固碳性能的影响。采用热重-差热综合热分析仪(TG-DTG)研究了蛇纹石酸浸提镁残渣型硅酸锂的CO2吸收性能,并通过扫描电子显微镜(SEM)与X射线衍射仪(XRD)对合成材料的微观形貌与结构特征进行了表征。结果表明:蛇纹石酸浸提镁残渣型硅酸锂具有较好的CO2吸收性能,吸收量可达26.66%;与市售Si O2为硅源相比,蛇纹石酸浸提镁残渣型硅酸锂材料煅烧合成时间缩短,高温固碳性能更优。     

耐火材料声发射源信号的盲反卷恢复

声发射信号是表征材料内部损伤状态的重要指标。由于源信号无法直接获取,研究的通常是传播一段距离后已失真的信号,这对材料损伤状态的准确判断带来了影响。为了降低传播路径对声发射源信号的衰减和失真带来的不利影响,假设声发射信号在耐火材料的传递路径为线性系统,对传递通道的冲击响应函数进行了估计,并设计了反卷滤波器。与实验结果对比发现,该方法很好的辨识了传递通道未知的系统,并能一定程度地恢复声发射源信号,为材料损伤状态的准确判断提供参考。     

金川矿区龙首矿长距离独头掘进通风系统改造研究

为制定适合于长距离独头掘进巷道的通风方案,提高长距离掘进的供风效能,以龙首矿西一采区辅助斜坡道为实验基础,通过对原有通风系统进行测试并分析存在的问题,设计钻孔通风方案及风库中转优化布置方案。结果表明：钻孔通风采用2×37 KW的风机配备刚性风筒能使工作面平均风速提高至0.29 m/s以上,该套掘进通风系统调整方案共需投资约11.63万元。风库中转通风系统采用2×11 KW的风机,当风库转移至距离硐口约249 m处,风库中转效率达到最高,单趟风筒工作面风量能够达到1.11 m3/s,采用双趟风筒时工作面风量能够达到2.22 m3/s。方案实施后,与预期的通风效果基本相符。     

基于CCAE的药筒抽壳性能的影响因素分析研究

为了解决大口径火炮药筒在射击时存在卡壳或者抽壳困难的问题,采用药筒划分不同区域的办法,对不同钢材、不同温度以及同一钢材不同材料参数这3种工况进行有限元仿真计算。结果表明药筒口部和药筒斜肩部抽壳力的占比较多;不同钢材对药筒抽壳力有一定的影响,其中30#钢相比20#钢、45#钢而言更容易抽壳;依据实验要求更换钢材材料参数,计算得出的抽壳力相比修改参数之前下降约50%左右,效果十分显著;温度升高对应的抽壳力也就越大,温度对抽壳的影响不可忽视。因此,在设计中应合理地在不同分区采用不同材料,确保更换材料参数可以降低药筒口部和药筒斜肩部的抽壳力,同时降低药筒温度,从而顺利抽壳。     

Blind Source Separation of Instantaneous Mixture of Delayed Sources Using High‐Order Taylor Approximation

This paper deals with the problem of blind source separation (BSS), where observed signals are a mixture of delayed sources. In reference to a previous work, when the delay time is small such that the first‐order Taylor approximation holds, delayed observations are transformed into an instantaneous mixture of original sources and their derivatives, for which an extended second‐order blind identification (SOBI) approach is used to recover sources. Inspired by the results of this previous work, we propose to generalize its first‐order Taylor approximation to suit higher‐order approximations in the case of a large delay time based on a similar version of its extended SOBI. Compared to SOBI and its extended version for a first‐order Taylor approximation, our method is more efficient in terms of separation quality when the delay time is large. Simulation results verify the performance of our approach under different time delays and signal‐to‐noise ratio conditions, respectively.     

Web考试系统自动组卷策略的设计与实现

组卷策略是Web考试系统的重点和难点,合理设置试题库和组卷参数以及合适的组卷算法是关键,论文介绍了一种基于随机抽取法＋分类分段法进行组卷的设计思想及其实现过程。     

Blind quality assessment for screen content images via convolutional neural network

With the wide propagation of cloud and mobile computing, screen content images (SCIs) have become more indispensable in our daily lives. Compared to natural scene images (NSIs), SCIs possess many particular characteristics, like mixed contents, extremely sharp edges, and text graphics. Consequently, more challenges occur in the feature extraction, which is used to reflect the distortion, during the quality assessment of SCIs. Recently, some convolutional neural network (CNN) models have been designed by automatically learning feature to evaluate the quality. In this paper, we develop a novel blind quality assessment method for SCIs via the CNN. First, compared with existing CNN-based methods, the proposed method avoids the disadvantage of training with image patches, and it is the pioneering attempt that takes the entire image as inputs. Second, instead of the image gray value, the original image is decomposed into two portions, i.e., the predicted and unpredicted portions, according to the internal generative mechanism (IGM) theory as the input of CNN. Through the CNN, all features of the image are learned automatically from beginning to end, and the network finally outputs the predicted score. Since existing SCI database is too small, to fully train the network, we collected 30000 SCIs and employed a high-accuracy full-reference quality assessment metric of SCI to compute scores as the training labels. Experimental results on SIQAD database demonstrate that the proposed method is comparable to reference-based SCI quality assessment metrics and is superior to the state-of-the-art NSI quality assessment metrics.     

Variable-dimensional vector modulation for perceptual-based DWT blind audio watermarking with adjustable payload capacity

A variable-dimensional vector modulation (VDVM) scheme is introduced to maximize the efficiency of the norm-space DWT-based blind audio watermarking technique. This flexible scheme allows the watermarking algorithm to reach a balance between robustness and capacity, while the imperceptivity is always ensured. The imperfection of applying quantization index modulation in the open-loop case has been rectified. The effectiveness of the proposed scheme is proven using the perceptual evaluation of audio quality (PEAQ) and bit error rates of recovered watermarks under various signal processing attacks. Experimental results show that the proposed VDVM scheme is comparable to other recently developed methods in robustness and imperceptivity even at a capacity as high as 301.46 bps. Such a capacity can be further doubled by halving the dimension of the involved DWT vector, while the robustness is still maintained at a satisfactory level.     

任意层互连生产技术研究

任意层互连（ELIC）是最高阶的高密度连接（HDI）制程，它可以比传统线路在层数相同的情况下，增加约30%层间互连；随着移动通讯产品功能需求的增加，ELIC技术被大举应用在智能手机及平面电脑等产品上。高阶ELIC线路板的生产不但流程长，且生产难度较大。本文对ELIC板的制作难点进行了分析，并提出相应的解决方法和生产注意事项，为ELIC工艺产业化提供必要的参考依据。