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The Method-of-Moment (MoM) discretization of the Electric-Field Integral Equation (EFIE) for a transversal electric (TE) illuminating plane wave impinging on an infinitely long cylinder (2D-object) traditionally requires continuous piecewise linear basis functions. These basis functions are particularly convenient in the numerical implementation because they reduce the degree of the Kernel singularity...
The traditional discretizations of the electric-field integral equation (EFIE) impose the continuity of the normal component current across the edges in the meshing. These edgeoriented schemes become awkward in the analysis of composite objects or of closed conductors meshed with nonconformal meshes. In this context, the nonconforming expansion of the current with facet-oriented schemes, like the...
The adaptive cross approximation algorithm is invoked for the fast construction of the method-of-moment matrix involving source basis functions for the currents and a set of auxiliary test functions that samples the radiated electromagnetic (EM) field. Once the adaptive cross approximation coupling matrix is constructed, the far and near fields from a source current are obtained directly through a...
In this paper we explore ways to address the issue of dataset bias in person re-identification by using data augmentation to increase the variability of the available datasets, and we introduce a novel data augmentation method for re-identification based on changing the image background. We show that use of data augmentation can improve the cross-dataset generalisation of convolutional network based...
In this paper, a global algorithm for human action, facial and gesture recognition is presented. The proposed algorithm depends on the extraction of multiple transform domain features and Canonical Correlation Analysis (CCA) for features fusion and classification. The proposed algorithm achieved the best reported results for facial and facial expression recognition. Excellent comparable results were...
FID is the original fuzzy decision tree, first introduced almost twenty years ago, that sparked a huge variety of hybrid algorithms merging approximate reasoning, fuzzy systems, and mainstream classification algorithms. With the continued interest, this paper describes a newly released update 3.5. One important new addition is a module that can be used to study the effect of noise and missing values...
Electromyografic signals offer insights into understanding the intent and extent of motion of the musculoskeletal system. This information could be utilized in developing controllers for applications such as prostheses and orthosis, and in general assistive technology. This paper presents a myoelectric based interface to control five discrete upper limb motions involving the shoulder and elbow joint...
When binary tree SVM is used for multi-class fault diagnosis, inner-class distance or between-class distance is always used to decide the classification hierarchy, but these methods cannot take the comprehensive separability information between classes into account, which leads to decrease the accuracy of fault diagnosis easily, so an improved binary tree SVM method is proposed. Combining the separability...
A face recognition algorithm based on a newly developed Transform Domain Mutual Principal Component Analysis (TD-2D-MuPCA) approach is proposed. In this approach, the spatial facial two-dimensional images (2D) and their division into horizontal, vertical and diagonal sub-images halves are generated. The sub-image halves are processed using non-overlapping and overlapping windows. Each face and its...
Support Vector Machines (SVMs) were primarily designed for 2-class classification. But they have been extended for N-class classification also based on the requirement of multiclasses in the practical applications. Although N-class classification using SVM has considerable research attention, getting minimum number of classifiers at the time of training and testing is still a continuing research....
The widely known classifier chains method for multi-label classification, which is based on the binary relevance (BR) method, overcomes the disadvantages of BR and achieves higher predictive performance, but still retains important advantages of BR, most importantly low time complexity. Nevertheless, despite its advantages, it is clear that a randomly arranged chain can be poorly ordered. We overcome...
Along with the development of technology at this era, the need of Internet access service as a media of communication is increasing. This increasing led to anomalies in network traffic. These anomalies, can occur because of a Distributed Denial of Service (DDoS) that deliberately. The impact of an anomaly is to make the user cannot access the internet service. If left alone, these anomalies can be...
Method-of-moment (MoM) implementations of the Electric-field Integral Equation (EFIE) in the scattering analysis of infinitely long (2D) or arbitrarily shaped (3D) conductors have traditionally required, respectively, piecewise-continuous or divergence-conforming basis functions. Recently, nonconforming EFIE-discretizations, with no imposed interelement continuity of current, have been developed by...
An efficient explicit marching on in time (MOT) scheme for solving the magnetic field volume integral equation is proposed. The MOT system is cast in the form of an ordinary differential equation and is integrated in time using a PE(CE)m multistep scheme. At each time step, a system with a Gram matrix is solved for the predicted/corrected field expansion coefficients. Depending on the type of spatial...
Recent attention has been devoted to the development of nonconforming method-of-moment (MoM) implementations of the Electric-Field Integral Equation (EFIE), which provide current solutions with no continuity constraints between neighboring facets. These schemes rely on the testing of the fields over small volumetric domains attached to the surface triangulation, inside the body under analysis. In...
Remote sensing has much to gain from citizen sensing. This is particularly evident in relation to the provision of ground reference data for use in the training and testing stages of supervised image classification analyses used to generate thematic maps from remotely sensed data. Citizens are able to provide data over large geographical areas inexpensively, addressing potential problems connected...
In this paper, the combination of FMIR-MoM with barycentric subdivision-based quadrature is utilized to analyze the Wideband RCS of the PEC objects. By using the FMIR-MoM, the electromagnetic properties over a wide frequency band can be quickly obtained. In this method, smaller frequency band division is not needed while it is required in the interpolation techniques. The memory requirement is comparable...
EEG based biometric system can be used for authentication, with advantages like confidentiality retention and forgery prevention. Signals which are taken from maximum brain regions show some sort of unique information that can be used for extracting the subject dependent pattern. This paper presents an approach to find the relationships among signals generated in different brain regions which give...
A number of papers has presented a pattern recognition method for Parkinson's Disease (PD) detection. However, the literatures only able to classify subjects as either healthy of suffering from PD. This paper presents a pattern recognition method for multi stage classification of PD utilizing voice features. 22 features are obtained from University of California-Irvine (UCI) data repository. These...
This paper presents a novel method based on sparse representation classification (SRC) and random dimensionality reduction projection (RDRP) to classify electric power system fault types in real time. Each testing fault sample is firstly represented as an overcomplete sparse linear combination of training fault samples. Then RDRP is applied to extract fault features with reduced dimensionality and...
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