球形全景图像的自动拼接

近年来,球形全景的虚拟现实方法开始发展起来.在已有的球形全景图像拼接方法中,基本上都是"半自动"的拼接方法,需要很多人工操作,效率低下、成本高昂.提出一种球面自寻匹配的拼接算法.该算法通过把多幅图像映射到一个合适的球面上,自动调整每幅图像的插入点,使得重合位置的差值图像灰度累积平均值最小,然后球面的图像反映射成平面形式,最终得到拼合图像.该算法可使程序实现完全自动化,使人工操作降至最低,从而降低全景图像的制作成本.     

Q-learning based heterogenous network self-optimization for reconfigurable network with CPC assistance

With the irreversible trend of the convergence and cooperation among heterogeneous networks, there emerge some important issues for network evolution. One of them is to reconfigure network elements such as cellular base stations (BSs) or access points (APs) of wireless local area networks (WLANs) according to the real-time network environment, in order to maximize the cooperation gain of different networks. In this paper, we consider cognitive pilot channel (CPC) as an assistant to enable cooperation among heterogeneous networks. Based on the widely used reinforcement learning algorithm, this paper has proposed the heterogeneous network self-optimization algorithm (HNSA) to solve the adaptation problem in reconfigurable systems. In the algorithm, distributed agents perform reinforcement learning, and make decisions cooperatively with the help of CPC in order to reduce the system blocking rate and improve network revenue. Finally our simulation proves the anticipated goal is achieved.     

NAND Flash的驱动程序设计

以三星公司K9F2808UOB为例,设计了NAND Flash与S3C2410的接口电路,介绍了NAND Flash在ARM嵌入式系统中的设计与实现方法,并在U-Boot上进行了验证。所设计的驱动易于移植,可简化嵌入式系统开发。     

Learning Image-Text Associations

Web information fusion can be defined as the problem of collating and tracking information related to specific topics on the World Wide Web. Whereas most existing work on Web information fusion has focused on text-based multidocument summarization, this paper concerns the topic of image and text association, a cornerstone of cross-media Web information fusion. Specifically, we present two learning methods for discovering the underlying associations between images and texts based on small training data sets. The first method based on vague transformation measures the information similarity between the visual features and the textual features through a set of predefined domain-specific information categories. Another method uses a neural network to learn direct mapping between the visual and textual features by automatically and incrementally summarizing the associated features into a set of information templates. Despite their distinct approaches, our experimental results on a terrorist domain document set show that both methods are capable of learning associations between images and texts from a small training data set.     

基于XML中间件的分布式异构数据库的数据分片策略研究

主要研究XML中间件的分布式异构数据库的数据分片策略,以便能够并行处理XML查询。为了描述XML数据分片,提出了对象树、子树的概念,将一棵XML数据树分割成对象树和子树,对象树在各个站点上复制,子树标签化后均匀分片到各个站点上。为了实现用户数据分片查询工作量的均衡,对最大树深的子树采用减治法策略,减治法策略后的子树又分配到一个新的站点上。基于这一思想,提出并实现其算法。实验结果证明：在分布式异构数据库的检索、查询和访问中,基于对象树、子树的数据分片算法的性能要比PSPIB算法性能优越。     

幽门螺杆菌TNF-α诱导蛋白的生物信息学分析

肿瘤坏死因子诱导蛋白Tipα是幽门螺杆菌特有的一个膜相关蛋白.它可以激活核因子κB,并诱导多种细胞因子和趋化因子的表达,导致胃炎和随后的肿瘤发生.它是幽门螺杆菌和胃癌发生之间的关键分子.本文利用生物信息学工具分析Tipα序列,预测其信号肽、跨膜区、疏水性、二级结构、三级结构等性质.结果:Tipα具有一段信号肽、脂蛋白信号肽酶切位点及脂盒模体.另外该蛋白没有跨膜区,可能是一个外周膜蛋白.Tipα的三级结构说明,该蛋白形成了一个致密的球状结构,Tipα的二级结构以α螺旋为主.     

气象雷达通用测试台的设计与实现

采用自动测试和综合仿真技术,解决了对雷达的多路被测信号的选择和陀螺平台的模拟等问题,适用于部分气象雷达的故障检测和性能测试,实现对雷达天线、收发机和显示器的自动测试;采用高灵敏度温度传感器、过压过流检测等多种保护措施,满足被测雷达对电源的特殊要求;其智能化程度高,操作简便,实用,可以减少维修检测的人为误差,对于提高飞行安全具有及其重要的意义,因此推广应用前景好,经济效益明显,填补了国内气象雷达检测设备的空白。     

TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data

Statistical analysis of air mass back trajectories combined with long-term ambient air pollution measurements are useful tools for source identification. Using these methods, the geographic information system (GIS) based software, TrajStat, was developed to view, query, and cluster the trajectories and compute the potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analyses when measurement data are included.     

A Simplified Neural Network for Linear Matrix Inequality Problems

A simplified neural network model is proposed to solve a class of linear matrix inequality problems. The stability and solvability of the proposed neural network are analyzed and discussed theoretically. In comparison with the previous neural network models (Lin and Huang, Neural Process Lett 11:153–169, 2000; Lin et al., IEEE Trans Neural Netw 11:1078–1092, 2000), the simplified one is composed of two layers rather than three layers, and the neuron array in each layer is triangular rather than square. The proposed approach can therefore reduce the complexity of the neural network architecture. In addition, the simplified neural network can also be extended to solve multiple linear matrix inequalities with specific constraints, which enlarges the application domain of the proposed approach. Finally, examples are given to illustrate the effectiveness and efficiency of the simplified neural network.