基于LBSN动态异构网络的时间感知兴趣点推荐

随着基于位置社交网络(Location-Based Social Network,LBSN)的快速发展,兴趣点(Point-Of-Interest,POI)推荐可以帮助人们发现有趣的并吸引人的位置。针对签到数据的稀疏性和用户兴趣的动态性等挑战性问题,提出了基于LBSN动态异构网络的时间感知兴趣点推荐算法。在LBSN异构网络模式中增加会话节点类型。通过动态元路径,在用户和兴趣点语义关系之间有效地融入时间信息、位置信息和社交信息等。设置了用户-兴趣点之间的动态元路径集,并提出了动态路径实例的偏好度计算方法。采用矩阵分解模型对不同动态偏好矩阵进行矩阵分解。根据不同动态元路径的用户特征矩阵和兴趣点特征矩阵,获取用户在目标时间访问兴趣点的推荐列表。实验结果表明,与其他兴趣点推荐方法相比,所提方法在兴趣点推荐精确度上取得了较好的推荐结果,具有良好的应用前景。     

Weighted preliminary-summation-based principal component analysis for non-Gaussian processes

For industrial chemical process, preliminary-summation-based principal component analysis (PS-PCA), an amended PCA method was recently provided for coping with both Gaussian and non-Gaussian characteristics. By summing the training and monitoring data respectively, PS-PCA is capable of resolving the issue of non-Gaussian processes and achieves higher fault detection rate than the traditional PCA. However, in the PS-PCA summation operation, all data samples are regarded as the same weight, which results in the fault information of newly-samples may be diluted, leading to significant detection delays. To address this challenge, in this paper, we propose a novel weighted PS-PCA (WPS-PCA) method that employs an exponential weighting scheme to put more emphasis on recent information. Subsequently, a mathematical argument demonstrates that when the number of variables is enough plentiful, the obtained summation combined with the generalized central limit theorem conforms to approximately a Gaussian distribution. The kurtosis relationships indicate this conversion will bring out well-pleasing feasibility for conventional PCA. Ultimately, the proposed technique verifies detection performance using the Tennessee Eastman process, which is compared with the existing PCA and PS-PCA schemes, in terms of the fault detection time and fault detection rate. The simulation studies reveal that the proposed method is efficient and superior.     

Methods for constructing analytic phase function for small spherical particle polydispersions

Two ways of constructing analytic phase function for a polydispersion of small spherical non-absorbing particles have been investigated. First one is a straightforward procedure emanating from the implementation of single particle scattering input into the defined polydisperse phase function. This results in an analytic phase function in terms of moments of the distribution. The second approach is a new strategy, based on the Lagrange mean value theorem. A clear understanding of the relationship between these two approaches has been developed. The efficacy and accuracy of the scattering phase functions is illustrated by applying it to a power-law size distributed sphere ensemble.     

基于多尺度结构特征的快速异源图像匹配

针对异源图像提出一种基于多尺度密集结构特征的快速匹配算法。算法首先利用Gabor滤波器逐像素提取图像中的结构响应,再根据主方向响应对多尺度结构特征融合,然后使用快速傅里叶变换在频域计算各特征分量图像之间的卷积,最后将卷积生成的系数矩阵求和计算出图像之间的相似性并选择相似性最大位置作为匹配结果输出。本文算法能有效适应异源图像间的非线性灰度变化和噪声干扰问题。测试使用可见光、红外、雷达图像组成的异源图像数据集对本文算法和现有算法进行测试比较,结果表明:本文算法的平均误匹配率最低,并且计算速度有明显优势。     

Levelized cost of energy definition – An economic paradox

Using mean value theorem for integrals we show that the well-known LCOE definition is incorrect.     

On robustness in the gap metric and coprime factor uncertainty for LTV systems

In this paper, we study the problem of robust stabilization for discrete linear time-varying (LTV) systems subject to time-varying normalized coprime factor uncertainty. Operator theoretic results which generalize similar results known to hold for linear time-invariant (infinite-dimensional) systems are developed. In particular, we compute an upper bound for the maximal achievable stability margin under TV normalized coprime factor uncertainty in terms of the norm of an operator with a time-varying Hankel structure. We point to a necessary and sufficient condition which guarantees compactness of the TV Hankel operator, and in which case singular values and vectors can be used to compute the time-varying stability margin and TV controller.     

Thermoelastic influence functions and solution to a locally mixed BVP for a strip

This article presents in closed form new influence functions for displacements and stresses to a boundary value problems (BVP) of thermoelasticity within a strip, caused by a unit point heat source. We also obtain the respective new integration formula of Green’s type, which directly determines the thermal stresses in the form of integrals of the products between specified internal heat sources, temperature, or heat flux prescribed on boundary and derived thermoelastic influence functions (kernels). The general Green’s type integral formula permits to derive new solution to one particular BVP of thermoelasticity for a strip in the form of elementary functions. Graphical representation of thermal stresses, created by an internal point heat source and by a boundary temperature, is included.     

一类分数阶微积分的中值定理及应用

Riemann-Liouville分数阶微积分算子是一类带有一个函数的分数阶微积分算子的特殊情形，以Riemann-Liouville分数阶微积分算子的积分中值定理和微分中值定理为基础，我们得到了一类带有一个函数的分数阶微积分算子的积分中值定理和微分中值定理，并给出其在计算方面的一些应用。