基于CMFS-MIC特征选择的跳频电台个体识别方法

针对跳频电台细微特征集中存在冗余特征等导致电台识别时存在计算量大、识别准确率低等问题,提出了一种基于CMFS-MIC特征选择的跳频电台个体识别方法。首先计算采集到的各个跳频电台信号样本的细微特征集,然后采用关联信息熵度量特征子集的组合效应,兼顾考虑特征间的关联关系和冗余关系对各个特征进行降序排序。在此基础上,采用最大信息系数度量的近似马尔可夫毯方法删除冗余特征,实现对特征子集进行优化和降维。最后,设计了投票组合分类器实现对4部跳频电台信号的识别。仿真结果表明,本文算法具有更高的分选识别率。     

Evaporative Heat Transfer of Annular Two-phase Flow of Air-water in a Small Vertical Tube

The evaporative heat transfer of the non-boiling annular two-phase flow of air-water in a small vertical tube with uniform wall heat flux was studied both theoretically and experimentally. A simplified two-phase flow boundary layer model was used to calculate the thickness of the water film attached to the wall, and from the liquid film thickness the evaporative heat transfer coefficients of the annular two-phase flow were obtained. Theoretical equations and semi-theoretical equations were proposed for predicting the evaporative heat transfer of the annular two-phase flow of air-water in a small vertical tube. The semi-theoretical prediction agrees well with the experimental data. The mechanism of the heat transfer enhancement is the evaporation of the thin liquid film attached on the wall.     

强化单螺杆挤出机内层流混合的方法

综述了单螺杆挤出机内聚合物熔体层流混合机理的研究进展，对提高混合的措施进行了分析总结，指出了进一步强化混合效果的方法。     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.     

Multi-resolution feature fusion for face recognition

For face recognition, image features are first extracted and then matched to those features in a gallery set. The amount of information and the effectiveness of the features used will determine the recognition performance. In this paper, we propose a novel face recognition approach using information about face images at higher and lower resolutions so as to enhance the information content of the features that are extracted and combined at different resolutions. As the features from different resolutions should closely correlate with each other, we employ the cascaded generalized canonical correlation analysis (GCCA) to fuse the information to form a single feature vector for face recognition. To improve the performance and efficiency, we also employ “Gabor-feature hallucination”, which predicts the high-resolution (HR) Gabor features from the Gabor features of a face image directly by local linear regression. We also extend the algorithm to low-resolution (LR) face recognition, in which the medium-resolution (MR) and HR Gabor features of a LR input image are estimated directly. The LR Gabor features and the predicted MR and HR Gabor features are then fused using GCCA for LR face recognition. Our algorithm can avoid having to perform the interpolation/super-resolution of face images and having to extract HR Gabor features. Experimental results show that the proposed methods have a superior recognition rate and are more efficient than traditional methods.     

大冶硫酸四系列干吸塔结构特点

以干燥塔为例，介绍大冶公司硫酸四系列干吸塔的结构特点。除捕沫层简体及出气管为316L不锈钢外，其余塔体均为碳钢内衬瓷砖结构。塔底为球形底，中心排酸。采用槽管式分酸器，分酸点密度为43个/m^2，设可调闸板以保证各槽酸量均匀；闸板外设置带孔板的分布板，以消除进口酸的冲击，保证槽内酸液面平稳。比较了该塔与常规塔的不同之处，强调了设备节点的优化设计。     

提高30m~3聚合釜生产能力

介绍了提高聚合釜生产能力的措施,改变聚合水油比,由原来的1.77降低到1.70,增加投料系数0.16;采用新助剂和密闭投料等新工艺,缩短聚合反应周期2.7h。使30m3聚合釜生产能力从5kt/a提高到6.5kt/a。     

Skeleton-enhanced line drawings for 3D models

We present a novel line drawing approach for 3D models by introducing their skeleton information into the rendering process. Based on the silhouettes of the input 3D models, we first extract feature lines in geometric regions by utilizing their curvature, torsion and view-dependent information. Then, the skeletons of the models are extracted by our newly developed skeleton extraction algorithm. After that, we draw the skeleton-guided lines from non-geometric regions through the skeleton information. These lines are combined with the feature lines to render the final line drawing result using the line optimization. Experimental results show that our algorithm can render line drawings more effectively with enhanced skeletons. The resulting artistic effects can capture the local geometries as well as the global skeletons of the input 3D models.     

高效节能换热器在氮肥工业中的应用

描述了新型折流杆换热器的强化传热和降低壳层压力降的原理 ,它与传统折流板换热器相比 ,传热效率高 ,材料及能耗小。介绍了这种新型换热器在合成氨变换工段和尿素装置中的应用情况及所起的节能降耗作用 ,指出该高效节能换热器在设计和生产中的关键技术。