In this paper, we give a characterization of the set of curves that may be approached by trajectories of a smooth control-a ne nonlinear system, in the topology of uniform convergence. This characterization is in terms of the drift vector field and the distribution spanned by the Lie algebra generated by the control vector fields. The characterization is valid on open sets where this distributi...

in the last two decade the use of aerial laser scanner (als) or lidar (light detection and ranging) sensor in geomatics engineering and surveying application has augmented significantly . the main reason of the mentioned phenomenon is the reliability and accuracy of the data obtained by lidar sensors. the output of lidar is unclassified 3d point cloud. classification of the lidar point clouds i...

in this paper we have proposed an approach for emotion detection in implicit texts. we have introduced a combinational system based on three subsystems. each one analyzes input data from a different aspect and produces an emotion label as output. the first subsystem is a machine learning method. the second one is a statistical approach based on vector space model (vsm) and the last one is a key...

classification ensemble, which uses the weighed polling of outputs, is the art of combining a set of basic classifiers for generating high-performance, robust and more stable results. this study aims to improve the results of identifying the persian handwritten letters using error correcting output coding (ecoc) ensemble method. furthermore, the feature selection is used to reduce the costs of ...

a robust and reliable quantitative structure-property relationship (qspr) study was established to forecast the melting points (mps)  of a diverse and long set including 250 drug-like compounds. based on the calculated descriptors by dragon software package, to detect homogeneities and to split the whole dataset into training and test sets, a principal component analysis (pca) approach was used...

In this paper, a generalized recurrent neural network is proposed for solving -insensitive support vector regression ( -ISVR). The -ISVR is first formulated as a convex non-smooth programming problem, and then a generalize recurrent neural network with lower model complexity is designed for training the support vector machine. Furthermore, simulation results are given to demonstrate the effecti...

Smooth convex minimization over the unit trace-norm ball is an important optimization problem in machine learning, signal processing, statistics, and other fields that underlies many tasks which one wishes to recover a low-rank matrix given certain measurements. While first-order methods for enjoy optimal convergence rates, they require worst-case compute full-rank SVD on each iteration, order ...

Understanding human activities and object affordances are two very important skills, especially for personal robots which operate in human environments. In this work, we consider the problem of extracting a descriptive labeling of the sequence of sub-activities being performed by a human, and more importantly, of their interactions with the objects in the form of associated affordances. Given a...

Computer Aided Diagnosis (CADx) systems are designed to assist doctors in medical image interpretation. However, a CADx is often thought of as a "black box" whose diagnostic decision is not intelligible to a radiologist. Therefore, a system that uses semantic image interpretation, and mimics human image analysis, has clear benefits. We propose a new method for automatic textual description of m...