Identification of Active Sources in Single-Channel Convolutive Mixtures Using Known Source Models

We address the problem of identifying the constituent sources in a single-sensor mixture signal consisting of contributions from multiple simultaneously active sources. We propose a generic framework for mixture signal analysis based on a latent variable approach. The basic idea of the approach is to detect known sources represented as stochastic models, in a single-channel mixture signal without performing signal separation. A given mixture signal is modeled as a convex combination of known source models and the weights of the models are estimated using the mixture signal. We show experimentally that these weights indicate the presence/absence of the respective sources. The performance of the proposed approach is illustrated through mixture speech data in a reverberant enclosure. For the task of identifying the constituent speakers using data from a single microphone, the proposed approach is able to identify the dominant source with up to 8 simultaneously active background sources in a room with RT60 = 250 ms, using models obtained from clean speech data for a Source to Interference Ratio (SIR) greater than 2 dB.

Scalable multi-dimensional user intent identification using tree structured distributions

The problem of identifying user intent has received considerable attention in recent years, particularly in the context of improving the search experience via query contextualization. Intent can be characterized by multiple dimensions, which are often not observed from query words alone. Accurate identification of Intent from query words remains a challenging problem primarily because it is extremely difficult to discover these dimensions. The problem is often significantly compounded due to lack of representative training sample. We present a generic, extensible framework for learning the multi-dimensional representation of user intent from the query words. The approach models the latent relationships between facets using tree structured distribution which leads to an efficient and convergent algorithm, FastQ, for identifying the multi-faceted intent of users based on just the query words. We also incorporated WordNet to extend the system capabilities to queries which contain words that do not appear in the training data. Empirical results show that FastQ yields accurate identification of intent when compared to a gold standard.

Mobile agent based TCP attacker identification in MANET using the traffic history (MAITH)

TCP attacks are the major problem faced by Mobile Ad hoc Networks (MANETs) due to its limited network and host resources. Attacker traceback is a promising solution which allows a victim to identify the exact location of the attacker and hence enables the victim to take proper countermeasure near attack origins, for forensics and to discourage attackers from launching the attacks. However, attacker traceback in MANET is a challenging problem due to dynamic network topology, limited network and host resources such as memory, bandwidth and battery life. We introduce a novel method of TCP attacker Identification in MANET using the Traffic History - MAITH. Based on the comprehensive evaluation based on simulations, we showed that MAITH can successfully track down the attacker under diverse mobile multi-hop network environment with low communication, computation, and memory overhead.

Multiple transmitter localization and communication footprint identification using sparse reconstruction techniques

This paper considers the problem of identifying the footprints of communication of multiple transmitters in a given geographical area. To do this, a number of sensors are deployed at arbitrary but known locations in the area, and their individual decisions regarding the presence or absence of the transmitters' signal are combined at a fusion center to reconstruct the spatial spectral usage map. One straightforward scheme to construct this map is to query each of the sensors and cluster the sensors that detect the primary's signal. However, using the fact that a typical transmitter footprint map is a sparse image, two novel compressive sensing based schemes are proposed, which require significantly fewer number of transmissions compared to the querying scheme. A key feature of the proposed schemes is that the measurement matrix is constructed from a pseudo-random binary phase shift applied to the decision of each sensor prior to transmission. The measurement matrix is thus a binary ensemble which satisfies the restricted isometry property. The number of measurements needed for accurate footprint reconstruction is determined using compressive sampling theory. The three schemes are compared through simulations in terms of a performance measure that quantifies the accuracy of the reconstructed spatial spectral usage map. It is found that the proposed sparse reconstruction technique-based schemes significantly outperform the round-robin scheme.

Identification of coherent synchronous generators in a multi- machine power system using support vector clustering

This paper illustrates the application of a new technique, based on Support Vector Clustering (SVC) for the direct identification of coherent synchronous generators in a large interconnected Multi-Machine Power Systems. The clustering is based on coherency measures, obtained from the time domain responses of the generators following system disturbances. The proposed clustering algorithm could be integrated into a wide-area measurement system that enables fast identification of coherent clusters of generators for the construction of dynamic equivalent models. An application of the proposed method is demonstrated on a practical 15 generators 72-bus system, an equivalent of Indian Southern grid in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations on coherency are also investigated.

Identification of mycobacterial lectins from genomic data

Sixty-four sequences containing lectin domains with homologs of known three-dimensional structure were identified through a search of mycobacterial genomes. They appear to belong to the -prism II, the C-type, the Microcystis virdis (MV), and the -trefoil lectin folds. The first three always occur in conjunction with the LysM, the PI-PLC, and the -grasp domains, respectively while mycobacterial -trefoil lectins are unaccompanied by any other domain. Thirty heparin binding hemagglutinins (HBHA), already annotated, have also been included in the study although they have no homologs of known three-dimensional structure. The biological role of HBHA has been well characterized. A comparison between the sequences of the lectin from pathogenic and nonpathogenic mycobacteria provides insights into the carbohydrate binding region of the molecule, but the structure of the molecule is yet to be determined. A reasonable picture of the structural features of other mycobacterial proteins containing one or the other of the four lectin domains can be gleaned through the examination of homologs proteins, although the structure of none of them is available. Their biological role is also yet to be elucidated. The work presented here is among the first steps towards exploring the almost unexplored area of the structural biology of mycobacterial lectins. Proteins 2013. (c) 2012 Wiley Periodicals, Inc.

Damage identification of beam-like structures with contiguous and distributed damage

Structural health monitoring of existing infrastructure is currently an active field of research, where elaborate experimental programs and advanced analytical methods are used in identifying the current state of health of critical structures. Change of static deflection as the indicator of damage is the simplest tool in a structural health monitoring scenario of bridges that is least exploited in damage identification strategies. In this paper, some simple and elegant equations based on loss of symmetry due to damage are derived and presented for identification of damage in a bridge girder modeled as a simply supported beam using changes in static deflections and dynamic parameters. A single contiguous and distributed damage, typical of reinforced or prestressed concrete structures, is assumed for the structure. The methodology is extended for a base-line-free as well as base-line-inclusive measurement. Measurement strategy involves application of loads only at two symmetric points one at a time and deflection measurements at those symmetric points as well as at the midspan of the beam. A laboratory-based experiment is used to validate the approach. Copyright (c) 2012 John Wiley & Sons, Ltd.

Variance-Reduced Particle Filters for Structural System Identification Problems

A few variance reduction schemes are proposed within the broad framework of a particle filter as applied to the problem of structural system identification. Whereas the first scheme uses a directional descent step, possibly of the Newton or quasi-Newton type, within the prediction stage of the filter, the second relies on replacing the more conventional Monte Carlo simulation involving pseudorandom sequence with one using quasi-random sequences along with a Brownian bridge discretization while representing the process noise terms. As evidenced through the derivations and subsequent numerical work on the identification of a shear frame, the combined effect of the proposed approaches in yielding variance-reduced estimates of the model parameters appears to be quite noticeable. DOI: 10.1061/(ASCE)EM.1943-7889.0000480. (C) 2013 American Society of Civil Engineers.

Identification of source of heavy metal contamination in a site - a case study

Accidental spills and improper disposal of industrial effluent/sludge containing heavy metals onto the open land or into subsurface result in soil and water contamination. Detailed investigations are carried out to identify the source of contamination of heavy metals in an industrial suburb near Bangalore in India. Detailed investigation of ground water and subsurface soil analysis for various heavy metals has been carried out. Ground water samples were collected in the entire area through the cluster of borewells. Subsurface soil samples were collected from near borewells which were found to contain heavy metals. Water samples and soils samples (after acid digestion) were analysed as per APHO-standard method of analysis. While the results of Zn, Ni and Cd showed that they are within allowable limits in the soil, the ground water and soils in the site have concentration of Cr+6 far exceeding the allowable limits (up to 832 mg/kg). Considering the topography of the area, ground water movement and results of chromium concentration in the borewells and subsurface it was possible to identify the origin, zone of contamination and the migration path of Cr+6. The results indicated that the predominant mechanism of migration of Cr+6 is by diffusion.

Identification of prospective locations for generation expansion with least augmentation of network

With ever increasing demand for electric energy, additional generation and associated transmission facilities has to be planned and executed. In order to augment existing transmission facilities, proper planning and selective decisions are to be made whereas keeping in mind the interests of several parties who are directly or indirectly involved. Common trend is to plan optimal generation expansion over the planning period in order to meet the projected demand with minimum cost capacity addition along with a pre-specified reliability margin. Generation expansion at certain locations need new transmission network which involves serious problems such as getting right of way, environmental clearance etc. In this study, an approach to the citing of additional generation facilities in a given system with minimum or no expansion in the transmission facility is attempted using the network connectivity and the concept of electrical distance for projected load demand. The proposed approach is suitable for large interconnected systems with multiple utilities. Sample illustration on real life system is presented in order to show how this approach improves the overall performance on the operation of the system with specified performance parameters.

Assay development for identifying inhibitors of the mycobacterial FadD32 activity

FadD32, a fatty acyl-AMP ligase (FAAL32) involved in the biosynthesis of mycolic acids, major and specific lipid components of the mycobacterial cell envelope, is essential for the survival of Mycobacterium tuberculosis, the causative agent of tuberculosis. The protein catalyzes the conversion of fatty acid to acyl-adenylate (acyl-AMP) in the presence of adenosine triphosphate and is conserved in all the mycobacterial species sequenced so far, thus representing a promising target for the development of novel antituberculous drugs. Here, we describe the optimization of the protein purification procedure and the development of a high-throughput screening assay for FadD32 activity. This spectrophotometric assay measuring the release of inorganic phosphate was optimized using the Mycobacterium smegmatis FadD32 as a surrogate enzyme. We describe the use of Tm (melting temperature) shift assay, which measures the modulation of FadD32 thermal stability, as a tool for the identification of potential ligands and for validation of compounds as inhibitors. Screening of a selected library of compounds led to the identification of five novel classes of inhibitors.

Identification of an exported heat shock protein 70 in Plasmodium falciparum

Host cell remodelling is a hallmark of malaria pathogenesis. It involves protein folding, unfolding and trafficking events and thus participation of chaperones such as Hsp70s and Hsp40s is well speculated. Until recently, only Hsp40s were thought to be the sole representative of the parasite chaperones in the exportome. However, based on the re-annotated Plasmodium falciparum genome sequence, a putative candidate for exported Hsp70 has been reported, which otherwise was known to be a pseudogene. We raised a specific antiserum against a C-terminal peptide uniquely present in PfHsp70-x. Immunoblotting and immunofluorescence-based approaches in combination with sub-cellular fractionation by saponin and streptolysin-O have been taken to determine the expression and localization of PfHsp70-x in infected erythrocyte. The re-annotated sequence of PfHsp70-x reveals it to be a functional protein with an endoplasmic reticulum signal peptide. It gets maximally expressed at the schizont stage of intra-erythrocytic life cycle. Majority of the protein localizes to the parasitophorous vacuole and some of it gets exported to the erythrocyte compartment where it associates with Maurer's clefts. The identification of an exported parasite Hsp70 chaperone presents us with the fact that the parasite has evolved customized chaperones which might be playing crucial roles in aspects of trafficking and host cell remodelling.

Synthon identification in co-crystals and polymorphs with IR spectroscopy. Primary amides as a case study

IR spectroscopy has been widely employed to distinguish between different crystal forms such as polymorphs, clathrates, hydrates and co-crystals. IR has been used to monitor co-crystal formation and single synthon detection. In this work, we have developed a strategy to identify multiple supramolecular synthons in polymorphs and co-crystals with this technique. The identification of multiple synthons in co-crystals with IR is difficult for several reasons. In this paper, a four step method involving well assigned IR spectral markers that correspond to bonds in a synthon is used. IR spectra of three forms of the co-crystal system, 4-hydroxybenzoic acid: 4,4'-bipyridine (2 : 1), show clear differences that may be attributed to differences in the synthon combinations existing in the forms (synthon polymorphism). These differences were picked out from the three IR spectra and the bands analysed and assigned to synthons. Our method first identifies IR marker bands corresponding to (covalent) bonds in known/model crystals and then the markers are mapped in known co-crystals having single synthons. Thereafter, the IR markers are queried in known co-crystals with multiple synthons. Finally they are queried in unknown co-crystals with multiple synthons. In the last part of the study, the N-H stretching absorptions of primary amides that crystallize with the amide dimers linked in a ladder like chain show two specific absorptions which are used as marker absorptions and all variations of this band structure have been used to provide details on the environment around the dimer. The extended dimer can accordingly be easily distinguished from the isolated dimer.

A novel filtering framework through Girsanov correction for the identification of nonlinear dynamical systems

Using a Girsanov change of measures, we propose novel variations within a particle-filtering algorithm, as applied to the inverse problem of state and parameter estimations of nonlinear dynamical systems of engineering interest, toward weakly correcting for the linearization or integration errors that almost invariably occur whilst numerically propagating the process dynamics, typically governed by nonlinear stochastic differential equations (SDEs). Specifically, the correction for linearization, provided by the likelihood or the Radon-Nikodym derivative, is incorporated within the evolving flow in two steps. Once the likelihood, an exponential martingale, is split into a product of two factors, correction owing to the first factor is implemented via rejection sampling in the first step. The second factor, which is directly computable, is accounted for via two different schemes, one employing resampling and the other using a gain-weighted innovation term added to the drift field of the process dynamics thereby overcoming the problem of sample dispersion posed by resampling. The proposed strategies, employed as add-ons to existing particle filters, the bootstrap and auxiliary SIR filters in this work, are found to non-trivially improve the convergence and accuracy of the estimates and also yield reduced mean square errors of such estimates vis-a-vis those obtained through the parent-filtering schemes.

Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.