Constrained linear filter and its relation to singular optimal control

This paper presents an analysis of an optimal linear filter in the presence of constraints on the moan squared values of the estimates from the viewpoint of singular optimal control. The singular arc has been shown to satisfy the generalized Legcndrc-Clebseh condition and Jacobson's condition. Both the cases of white measurement noise and coloured measurement noise are considered. The constrained estimate is shown to be a linear transformation of the unconstrained Kalman estimate.

Studies on transport phenomena during solidification of an aluminum alloy in the presence of linear electromagnetic stirring

Numerical and experimental studies on transport phenomena during solidification of an aluminum alloy in the presence of linear electromagnetic stirring are performed. The alloy is electromagnetically stirred to produce semisolid slurry in a cylindrical graphite mould placed in the annulus of a linear electromagnetic stirrer. The mould is cooled at the bottom, such that solidification progresses from the bottom to the top of the cylindrical mould. A numerical model is developed for simulating the transport phenomena associated with the solidification process using a set of single-phase governing equations of mass. momentum, energy. and species conservation. The viscosity variation of the slurry, used in the model, is determined experimentally using a rotary viscometer. The set of governing equations is solved using a pressure-based finite volume technique, along with an enthalpy based phase change algorithm. The numerical study involves prediction of temperature, velocity, species and solid fraction distribution in the mould. Corresponding solidification experiments are performed, with time-temperature history recorded at key locations. The microstructures at various temperature measurement locations in the solidified billet are analyzed. The numerical predictions of temperature variations are in good agreement with experiments, and the predicted flow field evolution correlates well with the microstructures observed at various locations.

A semi-analytical particle filter for identification of nonlinear oscillators

Particle filters find important applications in the problems of state and parameter estimations of dynamical systems of engineering interest. Since a typical filtering algorithm involves Monte Carlo simulations of the process equations, sample variance of the estimator is inversely proportional to the number of particles. The sample variance may be reduced if one uses a Rao-Blackwell marginalization of states and performs analytical computations as much as possible. In this work, we propose a semi-analytical particle filter, requiring no Rao-Blackwell marginalization, for state and parameter estimations of nonlinear dynamical systems with additively Gaussian process/observation noises. Through local linearizations of the nonlinear drift fields in the process/observation equations via explicit Ito-Taylor expansions, the given nonlinear system is transformed into an ensemble of locally linearized systems. Using the most recent observation, conditionally Gaussian posterior density functions of the linearized systems are analytically obtained through the Kalman filter. This information is further exploited within the particle filter algorithm for obtaining samples from the optimal posterior density of the states. The potential of the method in state/parameter estimations is demonstrated through numerical illustrations for a few nonlinear oscillators. The proposed filter is found to yield estimates with reduced sample variance and improved accuracy vis-a-vis results from a form of sequential importance sampling filter.

Opioid dependence: Brain structure and function : a magnetic resonance imaging, neuropsychological, and electromagnetic study

Background: Opiod dependence is a chronic severe brain disorder associated with enormous health and social problems. The relapse back to opioid abuse is very high especially in early abstinence, but neuropsychological and neurophysiological deficits during opioid abuse or soon after cessation of opioids are scarcely investigated. Also the structural brain changes and their correlations with the length of opioid abuse or abuse onset age are not known. In this study the cognitive functions, neural basis of cognitive dysfunction, and brain structural changes was studied in opioid-dependent patients and in age and sex matched healthy controls. Materials and methods: All subjects participating in the study, 23 opioid dependents of whom, 15 were also benzodiazepine and five cannabis co-dependent and 18 healthy age and sex matched controls went through Structured Clinical Interviews (SCID) to obtain DSM-IV axis I and II diagnosis and to exclude psychiatric illness not related to opioid dependence or personality disorders. Simultaneous magnetoencephalography (MEG) and electroencephalography (EEG) measurements were done on 21 opioid-dependent individuals on the day of hospitalization for withdrawal therapy. The neural basis of auditory processing was studied and pre-attentive attention and sensory memory were investigated. During the withdrawal 15 opioid-dependent patients participated in neuropsychological tests, measuring fluid intelligence, attention and working memory, verbal and visual memory, and executive functions. Fifteen healthy subjects served as controls for the MEG-EEG measurements and neuropsychological assessment. The brain magnetic resonance imaging (MRI) was obtained from 17 patients after approximately two weeks abstinence, and from 17 controls. The areas of different brain structures and the absolute and relative volumes of cerebrum, cerebral white and gray matter, and cerebrospinal fluid (CSF) spaces were measured and the Sylvian fissure ratio (SFR) and bifrontal ratio were calculated. Also correlation between the cerebral measures and neuropsychological performance was done. Results: MEG-EEG measurements showed that compared to controls the opioid-dependent patients had delayed mismatch negativity (MMN) response to novel sounds in the EEG and P3am on the contralateral hemisphere to the stimulated ear in MEG. The equivalent current dipole (ECD) of N1m response was stronger in patients with benzodiazepine co-dependence than those without benzodiazepine co-dependence or controls. In early abstinence the opioid dependents performed poorer than the controls in tests measuring attention and working memory, executive function and fluid intelligence. Test results of the Culture Fair Intelligence Test (CFIT), testing fluid intelligence, and Paced Auditory Serial Addition Test (PASAT), measuring attention and working memory correlated positively with the days of abstinence. MRI measurements showed that the relative volume of CSF was significantly larger in opioid dependents, which could also be seen in visual analysis. Also Sylvian fissures, expressed by SFR were wider in patients, which correlated negatively with the age of opioid abuse onset. In controls the relative gray matter volume had a positive correlation with composite cognitive performance, but this correlation was not found in opioid dependents in early abstinence. Conclusions: Opioid dependents had wide Sylvian fissures and CSF spaces indicating frontotemporal atrophy. Dilatation of Sylvian fissures correlated with the abuse onset age. During early withdrawal cognitive performance of opioid dependents was impaired. While intoxicated the pre-attentive attention to novel stimulus was delayed and benzodiazepine co-dependence impaired sound detection. All these changes point to disturbances on frontotemporal areas.

A Kalman filter based strategy for linear structural system identification based on multiple static and dynamic test data

The problem of identification of stiffness, mass and damping properties of linear structural systems, based on multiple sets of measurement data originating from static and dynamic tests is considered. A strategy, within the framework of Kalman filter based dynamic state estimation, is proposed to tackle this problem. The static tests consists of measurement of response of the structure to slowly moving loads, and to static loads whose magnitude are varied incrementally; the dynamic tests involve measurement of a few elements of the frequency response function (FRF) matrix. These measurements are taken to be contaminated by additive Gaussian noise. An artificial independent variable τ, that simultaneously parameterizes the point of application of the moving load, the magnitude of the incrementally varied static load and the driving frequency in the FRFs, is introduced. The state vector is taken to consist of system parameters to be identified. The fact that these parameters are independent of the variable τ is taken to constitute the set of ‘process’ equations. The measurement equations are derived based on the mechanics of the problem and, quantities, such as displacements and/or strains, are taken to be measured. A recursive algorithm that employs a linearization strategy based on Neumann’s expansion of structural static and dynamic stiffness matrices, and, which provides posterior estimates of the mean and covariance of the unknown system parameters, is developed. The satisfactory performance of the proposed approach is illustrated by considering the problem of the identification of the dynamic properties of an inhomogeneous beam and the axial rigidities of members of a truss structure.

Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

Robust joint precoder/receive filter designs for multiuser MIMO downlink

In this paper, we consider robust joint linear precoder/receive filter designs for multiuser multi-input multi-output (MIMO) downlink that minimize the sum mean square error (SMSE) in the presence of imperfect channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas, and each user terminal is equipped with one or more receive antennas. We consider a stochastic error (SE) model and a norm-bounded error (NBE) model for the CSIT error. In the case of CSIT error following SE model, we compute the desired downlink precoder/receive filter matrices by solving the simpler uplink problem by exploiting the uplink-downlink duality for the MSE region. In the case of the CSIT error following the NBE model, we consider the worst-case SMSE as the objective function, and propose an iterative algorithm for the robust transceiver design. The robustness of the proposed algorithms to imperfections in CSIT is illustrated through simulations.

Citizens breaking out of filter bubbles: Urban screens as civic media

Social media platforms risk polarising public opinions by employing proprietary algorithms that produce filter bubbles and echo chambers. As a result, the ability of citizens and communities to engage in robust debate in the public sphere is diminished. In response, this paper highlights the capacity of urban interfaces, such as pervasive displays, to counteract this trend by exposing citizens to the socio-cultural diversity of the city. Engagement with different ideas, networks and communities is crucial to both innovation and the functioning of democracy. We discuss examples of urban interfaces designed to play a key role in fostering this engagement. Based on an analysis of works empirically-grounded in field observations and design research, we call for a theoretical framework that positions pervasive displays and other urban interfaces as civic media. We argue that when designed for more than wayfinding, advertisement or television broadcasts, urban screens as civic media can rectify some of the pitfalls of social media by allowing the polarised user to break out of their filter bubble and embrace the cultural diversity and richness of the city.

Electromagnetic signatures of lightning near the HF frequency band

The dissertation deals with remote narrowband measurements of the electromagnetic radiation emitted by lightning flashes. A lightning flash consists of a number of sub-processes. The return stroke, which transfers electrical charge from the thundercloud to to the ground, is electromagnetically an impulsive wideband process; that is, it emits radiation at most frequencies in the electromagnetic spectrum, but its duration is only some tens of microseconds. Before and after the return stroke, multiple sub-processes redistribute electrical charges within the thundercloud. These sub-processes can last for tens to hundreds of milliseconds, many orders of magnitude longer than the return stroke. Each sub-process causes radiation with specific time-domain characteristics, having maxima at different frequencies. Thus, if the radiation is measured at a single narrow frequency band, it is difficult to identify the sub-processes, and some sub-processes can be missed altogether. However, narrowband detectors are simple to design and miniaturize. In particular, near the High Frequency band (High Frequency, 3 MHz to 30 MHz), ordinary shortwave radios can, in principle, be used as detectors. This dissertation utilizes a prototype detector which is essentially a handheld AM radio receiver. Measurements were made in Scandinavia, and several independent data sources were used to identify lightning sub-processes, as well as the distance to each individual flash. It is shown that multiple sub-processes radiate strongly near the HF band. The return stroke usually radiates intensely, but it cannot be reliably identified from the time-domain signal alone. This means that a narrowband measurement is best used to characterize the energy of the radiation integrated over the whole flash, without attempting to identify individual processes. The dissertation analyzes the conditions under which this integrated energy can be used to estimate the distance to the flash. It is shown that flash-by-flash variations are large, but the integrated energy is very sensitive to changes in the distance, dropping as approximately the inverse cube root of the distance. Flashes can, in principle, be detected at distances of more than 100 km, but since the ground conductivity can vary, ranging accuracy drops dramatically at distances larger than 20 km. These limitations mean that individual flashes cannot be ranged accurately using a single narrowband detector, and the useful range is limited to 30 kilometers at the most. Nevertheless, simple statistical corrections are developed, which enable an accurate estimate of the distance to the closest edge of an active storm cell, as well as the approach speed. The results of the dissertation could therefore have practical applications in real-time short-range lightning detection and warning systems.

Single-resolution and multiresolution extended-Kalman-filter-based reconstruction approaches to optical refraction tomography

The problem of reconstruction of a refractive-index distribution (RID) in optical refraction tomography (ORT) with optical path-length difference (OPD) data is solved using two adaptive-estimation-based extended-Kalman-filter (EKF) approaches. First, a basic single-resolution EKF (SR-EKF) is applied to a state variable model describing the tomographic process, to estimate the RID of an optically transparent refracting object from noisy OPD data. The initialization of the biases and covariances corresponding to the state and measurement noise is discussed. The state and measurement noise biases and covariances are adaptively estimated. An EKF is then applied to the wavelet-transformed state variable model to yield a wavelet-based multiresolution EKF (MR-EKF) solution approach. To numerically validate the adaptive EKF approaches, we evaluate them with benchmark studies of standard stationary cases, where comparative results with commonly used efficient deterministic approaches can be obtained. Detailed reconstruction studies for the SR-EKF and two versions of the MR-EKF (with Haar and Daubechies-4 wavelets) compare well with those obtained from a typically used variant of the (deterministic) algebraic reconstruction technique, the average correction per projection method, thus establishing the capability of the EKF for ORT. To the best of our knowledge, the present work contains unique reconstruction studies encompassing the use of EKF for ORT in single-resolution and multiresolution formulations, and also in the use of adaptive estimation of the EKF's noise covariances. (C) 2010 Optical Society of America

Effect of process parameters on transport phenomena during solidification in the presence of electromagnetic stirring

In the present work, a numerical study is performed to predict the effect of process parameters on transport phenomena during solidification of aluminium alloy A356 in the presence of electromagnetic stirring. A set of single-phase governing equations of mass, momentum, energy and species conservation is used to represent the solidification process and the associated fluid flow, heat and mass transfer. In the model, the electromagnetic forces are incorporated using an analytical solution of Maxwell equation in the momentum conservation equations and the slurry rheology during solidification is represented using an experimentally determined variable viscosity function. Finally, the set of governing equations is solved for various process conditions using a pressure based finite volume technique, along with an enthalpy based phase change algorithm. In present work, the effect of stirring intensity and cooling rate are considered. It is found that increasing stirring intensity results in increase of slurry velocity and corresponding increase in the fraction of solid in the slurry. In addition, the increasing stirring intensity results uniform distribution of species and fraction of solid in the slurry. It is also found from the simulation that the distribution of solid fraction and species is dependent on cooling rate conditions. At low cooling rate, the fragmentation of dendrites from the solid/liquid interface is more.

Design of a compact wideband bandpass filter

This article presents the analysis and design of a compact multi-layer layer, high selectivity wideband bandpass filter using stub loaded and `U' shaped resonators over a slotted bottom ground plane. While the resonators with folded open circuit stub loadings create the desired bandpass characteristics. the IT shaped resonators reduce the size of filter. The slotted bottom ground plane is used to enhance the coupling to achieve the desired bandwidth. The proposed filter has been analyzed using circuit model, and the results were verified through full wave simulations and measurements. The fabricated filter is compact and measures a size of 18 mm x 25 mm x 1.6 MM. (C) 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52: 1387-1389, 2010: Published online in Wiley InterScience (www.interscience.wiley.com).

Instability of Coupled Longitudinal and Transverse Electromagnetic Modes of Wave‐Propagation in Bounded Streaming Plasmas

The instability of coupled longitudinal and transverse electromagnetic modes associated with long wavelengths is studied in bounded streaming plasmas. The main conclusions are as follows: (i) For long waves for which O (k 2)=0, in the absence of relative streaming motion of electrons and ions and aωp/c<0.66, the whole spectrum of harmonic waves is excited due to finite temperature and boundary effects consisting of two subseries. One of these subseries can be identified with Tonks-Dattner resonance oscillations for the electrons, and arises primarily due to the electrons with frequencies greater than the electrostatic plasma frequency corresponding to the electron density in the midplane in the undisturbed state. The other series arises primarily due to ion motion. When aωp/c>0.66, in addition to the above spectrum of harmonic waves, the system admits an infinite number of growing and decaying waves. The instability associated with these modes is found to arise due to the interaction of the waves inside the plasma with the external electromagnetic field. (ii) For modes with comparatively shorter wavelengths for which O (k3)=0, the coupling due to finite temperature sets in, and it is found that the two series of harmonic waves obtained in (i) deriving energy from the transverse modes also become unstable. Thus, for these wavelengths the system admits three sets of growing and decaying modes, first two for all values of aωp/c and the third for (aωp/c) > 0.66. (iii) The presence of streaming velocities introduces various other coupling mechanisms, and we find that even for the wavelengths for which O (k2)=0, we get three sets of growing and decaying waves. The numerical values for the growth rates show that the streaming velocities enhance the growth rates of instability significantly.