Model Based Target Tracking in a Wireless Network of Passive Infrared Sensor Nodes

We consider the problem of tracking an intruder in a plane region by using a wireless sensor network comprising motes equipped with passive infrared (PIR) sensors deployed over the region. An input-output model for the PIR sensor and a method to estimate the angular speed of the target from the sensor output are proposed. With the measurement model so obtained, we study the centralized and decentralized tracking performance using the extended Kalman filter.

A Kushner-Stratonovich Monte Carlo filter applied to nonlinear dynamical system identification

A Monte Carlo filter, based on the idea of averaging over characteristics and fashioned after a particle-based time-discretized approximation to the Kushner-Stratonovich (KS) nonlinear filtering equation, is proposed. A key aspect of the new filter is the gain-like additive update, designed to approximate the innovation integral in the KS equation and implemented through an annealing-type iterative procedure, which is aimed at rendering the innovation (observation prediction mismatch) for a given time-step to a zero-mean Brownian increment corresponding to the measurement noise. This may be contrasted with the weight-based multiplicative updates in most particle filters that are known to precipitate the numerical problem of weight collapse within a finite-ensemble setting. A study to estimate the a-priori error bounds in the proposed scheme is undertaken. The numerical evidence, presently gathered from the assessed performance of the proposed and a few other competing filters on a class of nonlinear dynamic system identification and target tracking problems, is suggestive of the remarkably improved convergence and accuracy of the new filter. (C) 2013 Elsevier B.V. All rights reserved.

An Algorithm for Tracking a Maneuvering Target in Clutter

We consider the problem of tracking a maneuvering target in clutter. In such an environment, missed detections and false alarms make it impossible to decide, with certainty, the origin of received echoes. Processing radar returns in cluttered environments consists of three functions: 1) target detection and plot formation, 2) plot-to-track association, and 3) track updating. Two inadequacies of the present approaches are 1) Optimization of detection characteristics have not been considered and 2) features that can be used in the plot-to-track correlation process are restricted to a specific class. This paper presents a new approach to overcome these limitations. This approach facilitates tracking of a maneuvering target in clutter and improves tracking performance for weak targets.

Orthogonal biofunctionalization of magnetic nanoparticles via ``clickable'' poly(ethylene glycol) silanes: a ``universal ligand'' strategy to design stealth and target-specific nanocarriers

The present work demonstrates a novel strategy to synthesize orthogonally bio-engineered magnetonanohybrids (MNPs) through the design of versatile, biocompatible linkers whose structure includes: (i) a robust anchor to bind with metal-oxide surfaces; (ii) tailored surface groups to act as spacers and (iii) a general method to implement orthogonal functionalizations of the substrate via ``click chemistry''. Ligands that possess the synthetic generality of features (i)-(iii) are categorized as ``universal ligands''. Herein, we report the synthesis of a novel, azido-terminated poly(ethylene glycol) (PEG) silane that can easily self-assemble on MNPs through hetero-condensation between surface hydroxyl groups and the silane end of the ligand, and simultaneously provide multiple clickable sites for high density, chemoselective bio-conjugation. To establish the universal-ligand-strategy, we clicked alkyl-functionalized folate onto the surface of PEGylated MNPs. By further integrating a near-infrared fluorescent (NIRF) marker (Alexa-Fluor 647) with MNPs, we demonstrated their folate-receptor mediated internalization inside cancer cells and subsequent translocation into lysosomes and mitochondria. Ex vivo NIRF imaging established that the azido-PEG-silane developed in course of the study can effectively reduce the sequestration of MNPs by macrophage organs (viz. liver and spleen). These folate-PEG-MNPs were not only stealth and noncytotoxic but their dual optical and magnetic properties aided in tracking their whereabouts through combined magnetic resonance and optical imaging. Together, these results provided a strong motivation for the future use of the ``universal ligand'' strategy towards development of ``smart'' nanohybrids for theragnostic applications.

Fragment-based real-time object tracking: a sparse representation approach

Real-time object tracking is a critical task in many computer vision applications. Achieving rapid and robust tracking while handling changes in object pose and size, varying illumination and partial occlusion, is a challenging task given the limited amount of computational resources. In this paper we propose a real-time object tracker in l(1) framework addressing these issues. In the proposed approach, dictionaries containing templates of overlapping object fragments are created. The candidate fragments are sparsely represented in the dictionary fragment space by solving the l(1) regularized least squares problem. The non zero coefficients indicate the relative motion between the target and candidate fragments along with a fidelity measure. The final object motion is obtained by fusing the reliable motion information. The dictionary is updated based on the object likelihood map. The proposed tracking algorithm is tested on various challenging videos and found to outperform earlier approach.

Eigen-profiles of spatio-temporal fragments for adaptive region-based tracking

We propose a novel space-time descriptor for region-based tracking which is very concise and efficient. The regions represented by covariance matrices within a temporal fragment, are used to estimate this space-time descriptor which we call the Eigenprofiles(EP). EP so obtained is used in estimating the Covariance Matrix of features over spatio-temporal fragments. The Second Order Statistics of spatio-temporal fragments form our target model which can be adapted for variations across the video. The model being concise also allows the use of multiple spatially overlapping fragments to represent the target. We demonstrate good tracking results on very challenging datasets, shot under insufficient illumination conditions.

Robust tracking with interest points: A sparse representation approach

Visual tracking is an important task in various computer vision applications including visual surveillance, human computer interaction, event detection, video indexing and retrieval. Recent state of the art sparse representation (SR) based trackers show better robustness than many of the other existing trackers. One of the issues with these SR trackers is low execution speed. The particle filter framework is one of the major aspects responsible for slow execution, and is common to most of the existing SR trackers. In this paper,(1) we propose a robust interest point based tracker in l(1) minimization framework that runs at real-time with performance comparable to the state of the art trackers. In the proposed tracker, the target dictionary is obtained from the patches around target interest points. Next, the interest points from the candidate window of the current frame are obtained. The correspondence between target and candidate points is obtained via solving the proposed l(1) minimization problem. In order to prune the noisy matches, a robust matching criterion is proposed, where only the reliable candidate points that mutually match with target and candidate dictionary elements are considered for tracking. The object is localized by measuring the displacement of these interest points. The reliable candidate patches are used for updating the target dictionary. The performance and accuracy of the proposed tracker is benchmarked with several complex video sequences. The tracker is found to be considerably fast as compared to the reported state of the art trackers. The proposed tracker is further evaluated for various local patch sizes, number of interest points and regularization parameters. The performance of the tracker for various challenges including illumination change, occlusion, and background clutter has been quantified with a benchmark dataset containing 50 videos. (C) 2014 Elsevier B.V. All rights reserved.

Studies on the target conditioning for deposition of $LiCoO_{2}$ films

Deposition of good quality thin films of Lithium Cobalt Oxide (LiCoO2), by sputtering is preceded by target conditioning, which dictates the surface composition, morphology and electrochemical performance of the deposited film. Sputtering from a Virgin target surface, results in films with excess of the more reactive elements. The concentration of these reactive elements in the films decreases until the system reaches a steady state after sufficient sputtering from the target. This paper discusses the deposition kinetics in terms of target conditioning of LiCoO2. The composition, morphology and texturing of deposited film during various hours of sputtering were analyzed using X-ray photoelectron Spectroscopy (XPS) and Field Emission Scanning electron microscopy (FESEM). The compositional stability is not observed in the films formed during the initial hours or Sputtering from the fresh target, which becomes stable after several hours of sputtering. The Li and Co concentration in the Films deposited subsequently is found to be varying and possible causes are discussed. After the compositional stability is reached, electrochemical analysis of LiCoO2 thin films was performed, which shows a discharge capacity of 129 mu Ah/cm(2).

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

Studies on the Tracking and Erosion Resistance of RTV Silicone Rubber Nanocomposite

One of the problems associated with outdoor polymeric insulators is tracking and erosion of the weathershed which can directly influence the reliability of the power system. Flame retardants are added to the base material to enhance its tracking and erosion resistance. Hydroxide fillers are regarded as the best flame retardants. This paper deals with studies related to nano - sized magnesium dihydroxide (MDH) and micron-sized Alumina Trihydrate (ATH) fillers as flame retardants in RTV silicone rubber. Tracking and erosion resistance studies were carried out on MDH and ATH silicone rubber composites using an inclined plane tracking and erosion (IPT) resistance tester. The MDH filled (5% by wt) composites performed much better than ATH composites in terms of eroded mass, depth of erosion, width and length of erosion. The eroded mass of MDH composite is 49.8 % that of ATH composite which can be attributed to high surface area and higher thermal stability of MDH nanofillers.

New approach to improved detection and tracking performance in track-while-scan radars. Part 1: Introduction and review

The paper presents a new approach to improve the detection and tracking performance of a track-while-scan (TWS) radar. The contribution consists of three parts. In Part 1 the scope of various papers in this field is reviewed. In Part 2, a new approach for integrating the detection and tracking functions is presented. It shows how a priori information from the TWS computer can be used to improve detection. A new multitarget tracking algorithm has also been developed. It is specifically oriented towards solving the combinatorial problems in multitarget tracking. In Part 3, analytical derivations are presented for quantitatively assessing, a priori, the performance of a track-while-scan radar system (true track initiation, false track initiation, true track continuation and false track deletion characteristics). Simulation results are also shown.

New approach to improved detection and tracking performance in track-while-scan radars. Part 3: Performance prediction, optimisation and testing

The paper presents, in three parts, a new approach to improve the detection and tracking performance of a track-while-scan radar. Part 1 presents a review of the current status of the subject. Part 2 details the new approach. It shows how a priori information provided by the tracker can be used to improve detection. It also presents a new multitarget tracking algorithm. In the present Part, analytical derivations are presented for assessing, a priori, the performance of the TWS radar system. True track initiation, false track initiation, true track continuation and false track deletion characteristics have been studied. It indicates how the various thresholds can be chosen by the designer to optimise performance. Simulation results are also presented.

New approach to improved detection and tracking performance in track-while-scan radars. Part 2: Detection, track nitiation and association

he paper presents, in three parts, a new approach to improve the detection and tracking performance of a track-while-scan (TWS) radar. Part 1 presents a review of current status. In this part, Part 2, it is shown how the detection can be improved by utilising information from tracker. A new multitarget tracking algorithm, capable of tracking manoeuvring targets in clutter, is then presented. The algorithm is specifically tailored so that the solution to the combinatorial problem presented in a companion paper can be applied. The implementation aspects are discussed and a multiprocessor architecture identified to realise the full potential of the algorithm. Part 3 presents analytical derivations for quantitative assessment of the performance of the TWS radar system. It also shows how the performance can be optimised.

Incidence factors of the tracking systems used in parabolic-cylindrical concentrators

Several orientation and tracking systems employed in parabolic-cylindrical concentrators for focusing the direct solar radiation on the absorber tubes are analyzed from the technical and economic points of view. Case one, where the incidence factor was a function of declination and hour angle, showed that the maximum variations of incident factor from morning to noon was 0.5 at zero angle of declination. Case two, where the incidence factor was a function of declination, hour angle and latitude, showed the maximum variation of the incidence factor to be 0.128, which occurred during noon at the latitude of 30 degrees, corresponding to a change of declination from 0 to 23.5 degrees. In case three, the incidence factor, a function of declination only, showed that the maximum variation of the incidence factor corresponding to the change in declination from 0 to 23.5 degree was 0.0758. It is concluded that system three is the most efficient from the technical and economic point of view.