Clustering Based Large Margin Classification: A Scalable Approach using SOCP Formulation

This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture distributions, where each component of the mixture has a spherical covariance, the second order statistics of the components can be estimated efficiently using clustering algorithms like BIRCH. For each cluster, the second order moments are used to derive a second order cone constraint via a Chebyshev-Cantelli inequality. This constraint ensures that any data point in the cluster is classified correctly with a high probability. This leads to a large margin SOCP formulation whose size depends on the number of clusters rather than the number of training data points. Hence, the proposed formulation scales well for large datasets when compared to the state-of-the-art classifiers, Support Vector Machines (SVMs). Experiments on real world and synthetic datasets show that the proposed algorithm outperforms SVM solvers in terms of training time and achieves similar accuracies.

Spectral Finite Element Modeling of Complex Structures for Applications in Real-time Structural Health Monitoring

In this paper we discuss the recent progresses in spectral finite element modeling of complex structures and its application in real-time structural health monitoring system based on sensor-actuator network and near real-time computation of Damage Force Indicator (DFI) vector. A waveguide network formalism is developed by mapping the original variational problem into the variational problem involving product spaces of 1D waveguides. Numerical convergence is studied using a h()-refinement scheme, where is the wavelength of interest. Computational issues towards successful implementation of this method with SHM system are discussed.

Minimization of Constraint Violation in Fuzzy Multiobjective Programming

Fuzzy multiobjective programming for a deterministic case involves maximizing the minimum goal satisfaction level among conflicting goals of different stakeholders using Max-min approach. Uncertainty due to randomness in a fuzzy multiobjective programming may be addressed by modifying the constraints using probabilistic inequality (e.g., Chebyshev’s inequality) or by addition of new constraints using statistical moments (e.g., skewness). Such modifications may result in the reduction of the optimal value of the system performance. In the present study, a methodology is developed to allow some violation in the newly added and modified constraints, and then minimizing the violation of those constraints with the objective of maximizing the minimum goal satisfaction level. Fuzzy goal programming is used to solve the multiobjective model. The proposed methodology is demonstrated with an application in the field of Waste Load Allocation (WLA) in a river system.

Maximum rate of 3- and 4-real-symbol ML decodable unitary weight STBCs

It has been shown recently that the maximum rate of a 2-real-symbol (single-complex-symbol) maximum likelihood (ML) decodable, square space-time block codes (STBCs) with unitary weight matrices is 2a/2a complex symbols per channel use (cspcu) for 2a number of transmit antennas [1]. These STBCs are obtained from Unitary Weight Designs (UWDs). In this paper, we show that the maximum rates for 3- and 4-real-symbol (2-complex-symbol) ML decodable square STBCs from UWDs, for 2a transmit antennas, are 3(a-1)/2a and 4(a-1)/2a cspcu, respectively. STBCs achieving this maximum rate are constructed. A set of sufficient conditions on the signal set, required for these codes to achieve full-diversity are derived along with expressions for their coding gain.

Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.

Real-time density matrix renormalization group dynamics of spin and charge transport in push-pull polyenes and related systems

In this paper we investigate the effect of terminal substituents on the dynamics of spin and charge transport in donor-acceptor substituted polyenes [D-(CH)(x)-A] chains, also known as push-pull polyenes. We employ a long-range correlated model Hamiltonian for the D-(CH)(x)-A system, and time-dependent density matrix renormalization group technique for time propagating the wave packet obtained by injecting a hole at a terminal site, in the ground state of the system. Our studies reveal that the end groups do not affect spin and charge velocities in any significant way, but change the amount of charge transported. We have compared these push-pull systems with donor-acceptor substituted polymethine imine (PMI), D-(CHN)(x)-A, systems in which besides electron affinities, the nature of p(z) orbitals in conjugation also alternate from site to site. We note that spin and charge dynamics in the PMIs are very different from that observed in the case of push-pull polyenes, and within the time scale of our studies, transport of spin and charge leads to the formation of a ``quasi-static'' state.

Real source-sink pair

This work is concerned with the interaction of a source-sink pair. The main parameters of the problem are source and sink flow rates, the axial and lateral separations of the source and sink, and the angle between the axes of source and sink. Of concern is the percentage of source fluid that enters the sink as a function of these parameters. The experiments have been carried using the source nozzle diameter of 6 mm and the sink pipe diameter of two sizes: 10 mm and 20 mm. The Reynolds numbers of the source jet is about 3200. The main diagnostics are flow visualization using dye, laser induced fluorescence (LIF), particle streak photographs and particle image velocimetry (Ply). To obtain the removal effectiveness (that is percentage of source fluid that is going through the sink pipe), titration method is used. The sink diameter and the angle between source and the sink axes do not influence efficiencies as do the sink flow rate and the lateral separation. Data from experiments have been consolidated so that these results can be used for designing sinks for removal of heat and pollutants. (C) 2011 Elsevier Ltd. All rights reserved.

Optimal static voltage stability improvement using a numerically stable SLP algorithm, for real time applications

A numerically stable sequential Primal–Dual LP algorithm for the reactive power optimisation (RPO) is presented in this article. The algorithm minimises the voltage stability index C 2 [1] of all the load buses to improve the system static voltage stability. Real time requirements such as numerical stability, identification of the most effective subset of controllers for curtailing the number of controllers and their movement can be handled effectively by the proposed algorithm. The algorithm has a natural characteristic of selecting the most effective subset of controllers (and hence curtailing insignificant controllers) for improving the objective. Comparison with transmission loss minimisation objective indicates that the most effective subset of controllers and their solution identified by the static voltage stability improvement objective is not the same as that of the transmission loss minimisation objective. The proposed algorithm is suitable for real time application for the improvement of the system static voltage stability.

What is really real?

There has been substantial public debate recently on a host of issues such as climate change, genetically modified crops and nuclear power; a common theme running through these issues involves science and public policy. This note will be based broadly on three interlinked themes: growth of specialization in science, significant commercial interests pushing science and technology, and a checkered track record of the promises made and the broken-reality.

Real-time monitoring of critical nodes with minimal number of Phasor Measurement Units

This paper presents a method for placement of Phasor Measurement Units, ensuring the monitoring of vulnerable buses which are obtained based on transient stability analysis of the overall system. Real-time monitoring of phase angles across different nodes, which indicates the proximity to instability, the very purpose will be well defined if the PMUs are placed at buses which are more vulnerable. The issue is to identify the key buses where the PMUs should be placed when the transient stability prediction is taken into account considering various disturbances. Integer Linear Programming technique with equality and inequality constraints is used to find out the optimal placement set with key buses identified from transient stability analysis. Results on IEEE-14 bus system are presented to illustrate the proposed approach.

A Technique to Compute Smooth Amplitude, Phase, and Frequency Modulations From the Analytic Signal

Gabor's analytic signal (AS) is a unique complex signal corresponding to a real signal, but in general, it admits infinitely-many combinations of amplitude and frequency modulations (AM and FM, respectively). The standard approach is to enforce a non-negativity constraint on the AM, but this results in discontinuities in the corresponding phase modulation (PM), and hence, an FM with discontinuities particularly when the underlying AM-FM signal is over-modulated. In this letter, we analyze the phase discontinuities and propose a technique to compute smooth AM and FM from the AS, by relaxing the non-negativity constraint on the AM. The proposed technique is effective at handling over-modulated signals. We present simulation results to support the theoretical calculations.