A scalable architecture for geometric correction of multi-projector display systems

Multi-projector displays allow the realization of large and immersive projection environments by allowing the tiling of projections from multiple projectors. Such tiled displays require real time geometrical warping of the content that is being projected from each projector. This geometrical warping is a computationally intensive operation and is typically applied using high-end graphics processing units (GPUs) that are able to process a defined number of projector channels. Furthermore, this limits the applicability of such multi-projector display systems only to the content that is being generated using desktop based systems. In this paper we propose a platform independent FPGA based scalable hardware architecture for geometric correction of projected content that allows addition of each projector channel at a fractional increase in logic area. The proposed scheme provides real time correction of HD quality video streams and thus enables the use of this technology for embedded and standalone devices.     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.     

一种基于Spark的不确定数据集频繁模式挖掘算法

如何在海量不确定数据集中提高频繁模式挖掘性能是目前研究的热点.传统算法大多是以期望、概率或者权重等单一指标为数据项集支持度，在大数据背景下，同时考虑概率和权重支持度的算法难以兼顾其执行效率.为此，本文提出一种基于Spark的不确定数据集频繁模式挖掘算法（UWEFP），首先，为了同时兼顾数据项的概率和权重，计算一项集的最大概率权重值并进行剪枝；然后，为了减少对数据集的多次扫描，结合Spark框架的优点，设计了一种具有FP-tree特征的新颖的UWEFP-tree结构进行模式树的构建及挖掘；最后在Spark环境下，以UCI数据集进行实验验证.实验结果表明本文的方法在保证挖掘结果的同时，提高了效率.     

带参数的一阶脉冲微分方程边值问题

利用上下解和单调迭代法。讨论了带参数的一阶脉冲微分方程。获得了单边Lipschitz条件下这类方程边值问题的解的存在性。     

基于Vague集的鱼雷研制阶段年度投资分配模型

鱼雷的研制费用在鱼雷整个寿命周期费用中所占比系不大，但研制阶段决定了鱼雷寿命周期费用的绝大部分，闪此对鱼雷研制费用的研究可供鱼雷武器管理和决策者作经费计划综合平衡时参考。文章基于Vague集，提出了Vague集模糊熵的构造方法，进而提出了运用Vague集模糊熵进行鱼雷研制阶段年度投资强度分配的新模型。实例表明，该方法具有实用价值。     

A new distributed approximation algorithm for constructing minimum connected dominating set in wireless ad hoc networks

In recent years, constructing a virtual backbone by nodes in a connected dominating set (CDS) has been proposed to improve the performance of ad hoc wireless networks. In general, a dominating set satisfies that every vertex in the graph is either in the set or adjacent to a vertex in the set. A CDS is a dominating set that also induces a connected sub‐graph. However, finding the minimum connected dominating set (MCDS) is a well‐known NP‐hard problem in graph theory. Approximation algorithms for MCDS have been proposed in the literature. Most of these algorithms suffer from a poor approximation ratio, and from high time complexity and message complexity. In this paper, we present a new distributed approximation algorithm that constructs a MCDS for wireless ad hoc networks based on a maximal independent set (MIS). Our algorithm, which is fully localized, has a constant approximation ratio, and O(n) time and O(n) message complexity. In this algorithm, each node only requires the knowledge of its one‐hop neighbours and there is only one shortest path connecting two dominators that are at most three hops away. We not only give theoretical performance analysis for our algorithm, but also conduct extensive simulation to compare our algorithm with other algorithms in the literature. Simulation results and theoretical analysis show that our algorithm has better efficiency and performance than others. Copyright © 2005 John Wiley & Sons, Ltd.     

Examining a dimensional representation of depression and anxiety disorders' comorbidity in psychiatric outpatients with item response modeling.

The current study replicated, in a sample of 2,300 outpatients seeking psychiatric treatment, a previous study (R. F. Krueger & M. S. Finger, 2001) that implemented an item response theory approach for modeling the comorbidity of common mood and anxiety disorders as indicators along the continuum of a shared latent factor (internalizing). The 5 disorders examined were major depressive disorder, social phobia, panic disorder/agoraphobia, specific phobia, and generalized anxiety disorder. The findings were consistent with the prior research. First, a confirmatory factor analysis yielded sufficient evidence for a nonspecific factor underlying the 5 diagnostic indicators. Second, a 2-parameter logistic item response model showed that the diagnoses were represented in the upper half of the internalizing continuum, and each was a strongly discriminating indicator of the factor. Third, the internalizing factor was significantly associated with 3 indexes of social burden: poorer social functioning, time missed from work, and lifetime hospitalizations. Rather than the categorical system of presumably discrete disorders presented in DSM-IV, these 5 mood and anxiety disorders may be alternatively viewed as higher end indicators of a common factor associated with social cost. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

任意曲线透视投影的逆变换

透视曲线的逆变换是透视图象三维逆变换的重要基础。本文在给出透视投影逆变换基本方程的基础上，分别提出了圆、椭圆、二次曲线、任意平面曲线的透视投影逆变换的解析方法或计算机反求方法。同时给出灭点信息不足明图象的透视参数的准确反求方法。     

扇形束投影域重建—再投影迭代法

本文所提出的投影域重建——再投影迭代算法可以恢复不完整的扇形束投影数据,从而实现从有限的投影数据重建图象。这种算法把滤波——反投影图象重建过程和再投影的过程纳入一个公式,仅在投影域上估算未知的投影数据,因此避免了重建过程和反投影过程中的插值运算,改善了收敛性,提高了计算精度,缩短了运算时间。模拟实验表明:即使有70％的投影数据丢失,经过两次迭代就能以令人满意的精度恢复丢失的投影数据。     

Category Norms as a Function of Culture and Age: Comparisons of Item Responses to 105 Categories by American and Chinese Adults.

Understanding how aging influences cognition across different cultures has been hindered by a lack of standardized, cross-referenced verbal stimuli. This study introduces a database of such item-level stimuli for both younger and older adults, in China and the United States, and makes 3 distinct contributions. First, the authors specify which item categories generalize across age and/or cultural groups, rigorously quantifying differences among them. Second, they introduce novel, powerful methods to measure between-group differences in freely generated ranked data, the rank-ordered logit model and Hellinger Affinity. Finally, a broad archive of tested, cross-linguistic stimuli is now freely available to researchers: data, similarity measures, and all stimulus materials for 105 categories and 4 culture-by-age groups, comprising over 10,000 fully translated unique item responses. (PsycINFO Database Record (c) 2010 APA, all rights reserved)