Foreground detection is the first step in video surveillance system to detect moving objects. Robust Principal Components Analysis (RPCA) shows a nice framework to separate moving objects from the background. The background sequence is then modeled by a low rank subspace that can gradually change over time, while the moving foreground objects constitute the correlated sparse outliers. In this p...

Multidimensional data distributions can have complex topologies and variable local dimensions. To approximate complex data, we propose a new type of low-dimensional “principal object”: a principal cubic complex. This complex is a generalization of linear and non-linear principal manifolds and includes them as a particular case. To construct such an object, we combine a method of topological gra...

In this paper the phase centre of a pure mode, smooth wall, conical horn is studied. The method employed uses phase information obtained by aperture integration of the phase corrected mode field but differs from earlier presentations in first reducing the radiation integrals in terms of an identified family of functions prior to integration. The result is formulas for the principal plane radiat...

Design of blast resistant structures is an important subject in structural engineering, attracting the attention of governments, researchers, and engineers. Thus, given the benefits of optimization in engineering, development and assessment of optimization methods for optimum design of structures against blast is of great importance. In this research, multi-objective optimization of steel momen...

The largest eigenvalue λ1 of the adjacency matrix powerfully characterizes dynamic processes on networks, such as virus spread and synchronization. The minimization of the spectral radius by removing a set of links (or nodes) has been shown to be an NP-complete problem. So far, the best heuristic strategy is to remove links/nodes based on the principal eigenvector corresponding to the largest e...

in this paper, a new continuous ant colony optimization (caco) algorithm is proposed for optimal reservoir operation. the paper presents a new method of determining and setting a complete set of control parameters for any given problem, saving the user from a tedious trial and error based approach to determine them. the paper also proposes an elitist strategy for caco algorithm where best solut...

Simulation of the nonlinear mechanical response of materials with explicit representation of microstructural features is extremely challenging. These models typically involve a very large number of degrees of freedom, and are prone to convergence difficulties when searching for roots to nonlinear equilibrium equations. We focus on an idealized material model that is motivated by the microstruct...

Principal Component Analysis (PCA) is one of the most important unsupervised methods to handle high-dimensional data. However, due high computational complexity its eigen-decomposition solution, it hard apply PCA large-scale data with dimensionality, e.g., millions points variables. Meanwhile, squared L2-norm based objective makes sensitive outliers. In recent research, L1-norm maximization met...