循环冷却水零排污运行方案的研究

对循环冷却水系统零排污的技术可行性、经济性等进行了讨论，并针对大庆炼化公司循环冷却水系统零排污方案的实施加以详细描述，对实施过程中存在的问题予以了详细说明。     

基于数据密度的半监督自训练分类算法

在实际的分类任务中,无标记样本数量充足而有标记样本数量稀少的情况经常出现,目前处理这种情况的常用方法是半监督自训练分类算法。提出了一种基于数据密度的半监督自训练分类算法,该算法首先依据数据的密度对数据集进行划分,从而确定数据的空间结构;然后再按照数据的空间结构对分类器进行自训练的迭代,最终得到一个新的分类器。在UCI中6个数据集上的实验结果表明,与三种监督学习算法以及其分别对应的自训练版本相比,提出的算法分类效果更好。     

不同粒径可膨胀石墨无卤阻燃高密度硬质聚氨酯泡沫塑料研究

采用高速混合破碎机对可膨胀石墨（EG）进行处理，制得不同粒径的EG。考察了不同粒径EG填充的硬质聚氨酯泡沫塑料（RPUF）的微观形态，研究了EG对于RPUF燃烧行为的影响。结果表明：EG的粒径越小，其在聚氨酯体系中的分散就越困难；20％未经处理的EG粒子（EG0）填充的RPUF氧指数为39．5％，比未填充的RPUF氧指数提高了近一倍，而经过13min破碎的EG粒子（EG13）其氧指数仅为23．5％，与纯RPUF的氧指数在同一水平；水平垂直燃烧结果可进一步验证氧指数结果，当EGO填充量超过10％时，RPUF燃烧已经达到了V-0级，而RPUF／EG13因其阻燃性能较差只能用水平燃烧分级。由此可见，EGO可有效提高RPUF的阻燃性能，而EG13对RPUF的燃烧性能几乎没有影响；研究同时提出了不同粒径EG无卤阻燃高密度硬质聚氨酯泡沫塑料的阻燃机理。     

HEGM: A hierarchical elastic graph matching for hand gesture recognition

A hierarchical scheme for elastic graph matching applied to hand gesture recognition is proposed. The proposed algorithm exploits the relative discriminatory capabilities of visual features scattered on the images, assigning the corresponding weights to each feature. A boosting algorithm is used to determine the structure of the hierarchy of a given graph. The graph is expressed by annotating the nodes of interest over the target object to form a bunch graph. Three annotation techniques, manual, semi-automatic, and automatic annotation are used to determine the position of the nodes. The scheme and the annotation approaches are applied to explore the hand gesture recognition performance. A number of filter banks are applied to hand gestures images to investigate the effect of using different feature representation approaches. Experimental results show that the hierarchical elastic graph matching (HEGM) approach classified the hand posture with a gesture recognition accuracy of 99.85% when visual features were extracted by utilizing the Histogram of Oriented Gradient (HOG) representation. The results also provide the performance measures from the aspect of recognition accuracy to matching benefits, node positions correlation and consistency on three annotation approaches, showing that the semi-automatic annotation method is more efficient and accurate than the other two methods.     

3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

Gravity optimised particle filter for hand tracking

This paper presents a gravity optimised particle filter (GOPF) where the magnitude of the gravitational force for every particle is proportional to its weight. GOPF attracts nearby particles and replicates new particles as if moving the particles towards the peak of the likelihood distribution, improving the sampling efficiency. GOPF is incorporated into a technique for hand features tracking. A fast approach to hand features detection and labelling using convexity defects is also presented. Experimental results show that GOPF outperforms the standard particle filter and its variants, as well as state-of-the-art CamShift guided particle filter using a significantly reduced number of particles.     

A GPU-based parallel method for evolutionary tree construction

Evolutionary trees are widely applied in various applications to show the inferred evolutionary relationships among species or entities. Neighbor-Joining is one solution for data-intensive and time-consuming evolutionary tree construction, with polynomial time complexity. However, its performance becomes poorer with the growth of massive datasets. Graphics Processing Units (GPUs) have brought about new opportunities for these time-consuming applications. Based on its high efficiency, a GPU-based parallel Neighbor-Joining method is proposed, and two efficient parallel mechanisms, data segmentation with asynchronous processing and the minimal chain model with bitonic sort, are put forward to speed up the processing. The experimental results show that an average speedup of 25.1 is achieved and even approximately 30 can be obtained with a sequence dataset ranging from 16,000 to 25,000. Moreover, the proposed parallel mechanisms can be effectively exploited in some other high performance applications.     

Robust passive autofocus system for mobile phone camera applications

A robust autofocus system is a ubiquitous function in today’s mobile phone camera applications. However, due to the power consumption and size requirements, it is difficult for the autofocus function to be implemented into the design of mobile phone cameras. This paper presents a passive autofocus system with low computational complexity. This system uses a novel contrast measurement to determine degree of image sharpness, which can better reflect the information about image discontinuities. In order to gauge the performance of this measurement, a modified peak search strategy is used in the experiments. The experimental results from several typical image sequences validate the effectiveness of the proposed method.     

A Non-Line-of-Sight mitigation localization algorithm for sensor networks using clustering analysis

Non-Line-of-Sight propagation of wireless signal has an impact on measured distances in range-based localization and will bias the final localization results. A new localization algorithm is proposed in this paper to mitigate Non-Line-of-Sight errors when there are more than enough anchor nodes deployed around the node to be located. This algorithm utilizes multi-round clustering analysis to filter the pre-located estimators which derive from all possible subsets of measured distances. In each round, the method density-based spatial clustering of applications with noise is adopted. Simulations show that the proposed algorithm can effectively improve localization accuracy not only when the measured distances with Non-Line-of-Sight error are minor but also under the condition that all of them suffer random Non-Line-of-Sight error.     

Runtime home mapping for effective memory resource usage

In tiled Chip Multiprocessors (CMPs) last-level cache (LLC) banks are usually shared but distributed among the tiles. A static mapping of cache blocks to the LLC banks leads to poor efficiency since a block may be mapped away from the tiles actually accessing it. Dynamic policies either rely on the static mapping of blocks to a set of banks (D-NUCA) or rely on the OS to dynamically load pages to statically mapped addresses (first-touch).