Cramer-Rao bounds for source localization in shallow ocean with generalized Gaussian noise

Localization of underwater acoustic sources is a problem of great interest in the area of ocean acoustics. There exist several algorithms for source localization based on array signal processing.It is of interest to know the theoretical performance limits of these estimators. In this paper we develop expressions for the Cramer-Rao-Bound (CRB) on the variance of direction-of-arrival(DOA) and range-depth estimators of underwater acoustic sources in a shallow range-independent ocean for the case of generalized Gaussian noise. We then study the performance of some of the popular source localization techniques,through simulations, for DOA/range-depth estimation of underwater acoustic sources in shallow ocean by comparing the variance of the estimators with the corresponding CRBs.

High-temperature deformation processing maps for a NiTiCu shape memory alloy

The properties of widely used Ni-Ti-based shape memory alloys (SMAs) are highly sensitive to the underlying microstructure. Hence, controlling the evolution of microstructure during high-temperature deformation becomes important. In this article, the ``processing maps'' approach is utilized to identify the combination of temperature and strain rate for thermomechanical processing of a Ni(42)Ti(50)Cu(8) SMA. Uniaxial compression experiments were conducted in the temperature range of 800-1050 degrees C and at strain rate range of 10(-3) and 10(2) s(-1). Two-dimensional power dissipation efficiency and instability maps have been generated and various deformation mechanisms, which operate in different temperature and strain rate regimes, were identified with the aid of the maps and complementary microstructural analysis of the deformed specimens. Results show that the safe window for industrial processing of this alloy is in the range of 800-850 degrees C and at 0.1 s(-1), which leads to grain refinement and strain-free grains. Regions of the instability were identified, which result in strained microstructure, which in turn can affect the performance of the SMA.

Long term stability studies of particle storage rings using polynomial Maps

Long-term stability studies of particle storage rings can not be carried out using conventional numerical integration algorithms. We require symplectic integration algorithms which are both fast and accurate. In this paper, we study a symplectic integration method wherein the sym-plectic map representing the Hamiltonian system is refactorized using polynomial symplectic maps. This method is used to perform long term integration on a particle storage ring.

Uncertainty visualization using HDR volume rendering

In this paper, we explore a novel idea of using high dynamic range (HDR) technology for uncertainty visualization. We focus on scalar volumetric data sets where every data point is associated with scalar uncertainty. We design a transfer function that maps each data point to a color in HDR space. The luminance component of the color is exploited to capture uncertainty. We modify existing tone mapping techniques and suitably integrate them with volume ray casting to obtain a low dynamic range (LDR) image. The resulting image is displayed on a conventional 8-bits-per-channel display device. The usage of HDR mapping reveals fine details in uncertainty distribution and enables the users to interactively study the data in the context of corresponding uncertainty information. We demonstrate the utility of our method and evaluate the results using data sets from ocean modeling.

Processes of 30-90 days sea surface temperature variability in the northern Indian Ocean during boreal summer

During summer, the northern Indian Ocean exhibits significant atmospheric intraseasonal variability associated with active and break phases of the monsoon in the 30-90 days band. In this paper, we investigate mechanisms of the Sea Surface Temperature (SST) signature of this atmospheric variability, using a combination of observational datasets and Ocean General Circulation Model sensitivity experiments. In addition to the previously-reported intraseasonal SST signature in the Bay of Bengal, observations show clear SST signals in the Arabian Sea related to the active/break cycle of the monsoon. As the atmospheric intraseasonal oscillation moves northward, SST variations appear first at the southern tip of India (day 0), then in the Somali upwelling region (day 10), northern Bay of Bengal (day 19) and finally in the Oman upwelling region (day 23). The Bay of Bengal and Oman signals are most clearly associated with the monsoon active/break index, whereas the relationship with signals near Somali upwelling and the southern tip of India is weaker. In agreement with previous studies, we find that heat flux variations drive most of the intraseasonal SST variability in the Bay of Bengal, both in our model (regression coefficient, 0.9, against similar to 0.25 for wind stress) and in observations (0.8 regression coefficient); similar to 60% of the heat flux variation is due do shortwave radiation and similar to 40% due to latent heat flux. On the other hand, both observations and model results indicate a prominent role of dynamical oceanic processes in the Arabian Sea. Wind-stress variations force about 70-100% of SST intraseasonal variations in the Arabian Sea, through modulation of oceanic processes (entrainment, mixing, Ekman pumping, lateral advection). Our similar to 100 km resolution model suggests that internal oceanic variability (i.e. eddies) contributes substantially to intraseasonal variability at small-scale in the Somali upwelling region, but does not contribute to large-scale intraseasonal SST variability due to its small spatial scale and random phase relation to the active-break monsoon cycle. The effect of oceanic eddies; however, remains to be explored at a higher spatial resolution.

Estimation of heavy rainfall during cyclonic storms from microwave observations using nonlinear approach over Indian Ocean

In this study, an effort has been made to study heavy rainfall events during cyclonic storms over Indian Ocean. This estimate is based on microwave observations from tropical rainfall measuring mission (TRMM) Microwave Imager (TMI). Regional scattering index (SI) developed for Indian region based on measurements at 19-, 21- and 85-GHz brightness temperature and polarization corrected temperature (PCT) at 85 GHz have been utilized in this study. These PCT and SI are collocated against Precipitation Radar (PR) onboard TRMM to establish a relationship between rainfall rate, PCT and SI. The retrieval technique using both linear and nonlinear regressions has been developed utilizing SI, PCT and the combination of SI and PCT. The results have been compared with the observations from PR. It was found that a nonlinear algorithm using combination of SI and PCT is more accurate than linear algorithm or nonlinear algorithm using either SI or PCT. Statistical comparison with PR exhibits the correlation coefficients (CC) of 0.68, 0.66 and 0.70, and root mean square error (RMSE) of 1.78, 1.96 and 1.68 mm/h from the observations of SI, PCT and combination of SI and PCT respectively using linear regressions. When nonlinear regression is used, the CC of 0.73, 0.71, 0.79 and RMSE of 1.64, 1.95, 1.54 mm/h are observed from the observations of SI, PCT and combination of SI and PCT, respectively. The error statistics for high rain events (above 10 mm/h) shows the CC of 0.58, 0.59, 0.60 and RMSE of 5.07, 5.47, 5.03 mm/h from the observations of SI, PCT and combination of SI and PCT, respectively, using linear regression, and on the other hand, use of nonlinear regression yields the CC of 0.66, 0.64, 0.71 and RMSE of 4.68, 5.78 and 4.02 mm/h from the observations of SI, PCT and combined SI and PCT, respectively.

A spring-mass-lever model, stiffness and inertia maps for single-input, single-output compliant mechanisms

A spring-mass-lever (SML) model is introduced in this paper for a single-input-single-output compliant mechanism to capture its static and dynamic behavior. The SML model is a reduced-order model, and its five parameters provide physical insight and quantify the stiffness and inertia(1) at the input and output ports as well as the transformation of force and displacement between the input and output. The model parameters can be determined with reasonable accuracy without performing dynamic or modal analysis. The paper describes two uses of the SML model: computationally efficient analysis of a system of which the compliant mechanism is a part; and design of compliant mechanisms for the given user-specifications. During design, the SML model enables determining the feasible parameter space of user-specified requirements, assessing the suitability of a compliant mechanism to meet the user-specifications and also selecting and/or re-designing compliant mechanisms from an existing database. Manufacturing constraints, material choice, and other practical considerations are incorporated into this methodology. A micromachined accelerometer and a valve mechanism are used as examples to show the effectiveness of the SML model in analysis and design. (C) 2012 Published by Elsevier Ltd.

Signatures of Indian ocean Dipole and El Nino-Southern Oscillation events in sea level variations in the Bay of Bengal

We investigate the impact of the Indian Ocean Dipole (IOD) and El Nino and the Southern Oscillation (ENSO) on sea level variations in the North Indian Ocean during 1957-2008. Using tide-gauge and altimeter data, we show that IOD and ENSO leave characteristic signatures in the sea level anomalies (SLAs) in the Bay of Bengal. During a positive IOD event, negative SLAs are observed during April-December, with the SLAs decreasing continuously to a peak during September-November. During El Nino, negative SLAs are observed twice (April-December and November-July), with a relaxation between the two peaks. SLA signatures during negative IOD and La Nina events are much weaker. We use a linear, continuously stratified model of the Indian Ocean to simulate their sea level patterns of IOD and ENSO events. We then separate solutions into parts that correspond to specific processes: coastal alongshore winds, remote forcing from the equator via reflected Rossby waves, and direct forcing by interior winds within the bay. During pure IOD events, the SLAs are forced both from the equator and by direct wind forcing. During ENSO events, they are primarily equatorially forced, with only a minor contribution from direct wind forcing. Using a lead/lag covariance analysis between the Nino-3.4 SST index and Indian Ocean wind stress, we derive a composite wind field for a typical El Nino event: the resulting solution has two negative SLA peaks. The IOD and ENSO signatures are not evident off the west coast of India.

Functional maps within a single neuron

Narayanan R, Johnston D. Functional maps within a single neuron. J Neurophysiol 108: 2343-2351, 2012. First published August 29, 2012; doi:10.1152/jn.00530.2012.-The presence and plasticity of dendritic ion channels are well established. However, the literature is divided on what specific roles these dendritic ion channels play in neuronal information processing, and there is no consensus on why neuronal dendrites should express diverse ion channels with different expression profiles. In this review, we present a case for viewing dendritic information processing through the lens of the sensory map literature, where functional gradients within neurons are considered as maps on the neuronal topograph. Under such a framework, drawing analogies from the sensory map literature, we postulate that the formation of intraneuronal functional maps is driven by the twin objectives of efficiently encoding inputs that impinge along different dendritic locations and of retaining homeostasis in the face of changes that are required in the coding process. In arriving at this postulate, we relate intraneuronal map physiology to the vast literature on sensory maps and argue that such a metaphorical association provides a fresh conceptual framework for analyzing and understanding single-neuron information encoding. We also describe instances where the metaphor presents specific directions for research on intraneuronal maps, derived from analogous pursuits in the sensory map literature. We suggest that this perspective offers a thesis for why neurons should express and alter ion channels in their dendrites and provides a framework under which active dendrites could be related to neural coding, learning theory, and homeostasis.

MAPS: midline analysis and propagation of segmentation

Scenic word images undergo degradations due to motion blur, uneven illumination, shadows and defocussing, which lead to difficulty in segmentation. As a result, the recognition results reported on the scenic word image datasets of ICDAR have been low. We introduce a novel technique, where we choose the middle row of the image as a sub-image and segment it first. Then, the labels from this segmented sub-image are used to propagate labels to other pixels in the image. This approach, which is unique and distinct from the existing methods, results in improved segmentation. Bayesian classification and Max-flow methods have been independently used for label propagation. This midline based approach limits the impact of degradations that happens to the image. The segmented text image is recognized using the trial version of Omnipage OCR. We have tested our method on ICDAR 2003 and ICDAR 2011 datasets. Our word recognition results of 64.5% and 71.6% are better than those of methods in the literature and also methods that competed in the Robust reading competition. Our method makes an implicit assumption that degradation is not present in the middle row.

The Indian Ocean forecast system

In order to meet the ever growing demand for the prediction of oceanographic parametres in the Indian Ocean for a variety of applications, the Indian National Centre for Ocean Information Services (INCOIS) has recently set-up an operational ocean forecast system, viz. the Indian Ocean Forecast System (INDOFOS). This fully automated system, based on a state-of-the-art ocean general circulation model issues six-hourly forecasts of the sea-surface temperature, surface currents and depths of the mixed layer and the thermocline up to five-days of lead time. A brief account of INDOFOS and a statistical validation of the forecasts of these parametres using in situ and remote sensing data are presented in this article. The accuracy of the sea-surface temperature forecasts by the system is high in the Bay of Bengal and the Arabian Sea, whereas it is moderate in the equatorial Indian Ocean. On the other hand, the accuracy of the depth of the thermocline and the isothermal layers and surface current forecasts are higher near the equatorial region, while it is relatively lower in the Bay of Bengal.

Predicting the extremes of Indian summer monsoon rainfall with coupled ocean-atmosphere models

An analysis of the retrospective predictions by seven coupled ocean atmosphere models from major forecasting centres of Europe and USA, aimed at assessing their ability in predicting the interannual variation of the Indian summer monsoon rainfall (ISMR), particularly the extremes (i.e. droughts and excess rainfall seasons) is presented in this article. On the whole, the skill in prediction of extremes is not bad since most of the models are able to predict the sign of the ISMR anomaly for a majority of the extremes. There is a remarkable coherence between the models in successes and failures of the predictions, with all the models generating loud false alarms for the normal monsoon season of 1997 and the excess monsoon season of 1983. It is well known that the El Nino and Southern Oscillation (ENSO) and the Equatorial Indian Ocean Oscillation (EQUINOO) play an important role in the interannual variation of ISMR and particularly the extremes. The prediction of the phases of these modes and their link with the monsoon has also been assessed. It is found that models are able to simulate ENSO-monsoon link realistically, whereas the EQUINOO-ISMR link is simulated realistically by only one model the ECMWF model. Furthermore, it is found that in most models this link is opposite to the observed, with the predicted ISMR being negatively (instead of positively) correlated with the rainfall over the western equatorial Indian Ocean and positively (instead of negatively) correlated with the rainfall over the eastern equatorial Indian Ocean. Analysis of the seasons for which the predictions of almost all the models have large errors has suggested the facets of ENSO and EQUINOO and the links with the monsoon that need to be improved for improving monsoon predictions by these models.

Yanai waves in the western equatorial Indian Ocean

Observations and models have shown the presence of intraseasonal fluctuations in 20-30-day and 10-20-day bands in the equatorial Indian Ocean west of 60 degrees E (WEIO). Their spatial and temporal structures characterize them as Yanai waves, which we label low-frequency (LFYW) and high-frequency (HFYW) Yanai waves, respectively. We explore the dynamics of these intraseasonal signals, using an ocean general circulation model (Modular Ocean Model) and a linear, continuously stratified model. Yanai waves are forced by the meridional wind tau(y) everywhere in the WEIO most strongly during the monsoon seasons. They are forced both directly in the interior ocean and by reflection of the interior response from the western boundary; interference between the interior and boundary responses results in a complex surface pattern that propagates eastward and has nodes. Yanai waves are also forced by instabilities primarily during June/July in a region offshore from the western boundary (52-55 degrees E). At that time, eddies, generated by barotropic instability of the Southern Gyre, are advected southward to the equator. There, they generate a westward-propagating, cross-equatorial flow field, v(eq), with a wave number/frequency spectrum that fits the dispersion relation of a number of Yanai waves, and these waves are efficiently excited. Typically, Yanai waves associated with several baroclinic modes are excited by both wind and eddy forcing; and typically, they superpose to create beams that carry energy vertically and eastward along ray paths. The same processes generate LFYWs and HFYWs, and hence, their responses are similar; differences are traceable to the property that HFYWs have longer wavelengths than LFYWs for each baroclinic mode.

Estimating wind stress at the ocean surface from scatterometer observations

Wind stress is the most important ocean forcing for driving tropical surface currents. Stress can be estimated from scatterometer-reported wind measurements at 10 m that have been extrapolated to the surface, assuming a neutrally stable atmosphere and no surface current. Scatterometer calibration is designed to account for the assumption of neutral stability; however, the assumption of a particular sea state and negligible current often introduces an error in wind stress estimations. Since the fundamental scatterometer measurement is of the surface radar backscatter (sigma-0) which is related to surface roughness and, thus, stress, we develop a method to estimate wind stress directly from the scatterometer measurements of sigma-0 and their associated azimuth angle and incidence angle using a neural network approach. We compare the results with in situ estimations and observe that the wind stress estimations from this approach are more accurate compared with those obtained from the conventional estimations using 10-m-height wind measurements.

Dynamics of the Indian-Ocean oxygen minimum zones

In the Indian Ocean, mid-depth oxygen minimum zones (OMZs) occur in the Arabian Sea and the Bay of Bengal. The lower part of the Arabian-Sea OMZ (ASOMZ; below 400 m) intensifies northward across the basin; in contrast, its upper part (above 400 m) is located in the central/eastern basin, well east of the most productive regions along the western boundary. The Bay-of-Bengal OMZ (BBOMZ), although strong, is weaker than the ASOMZ. To investigate the processes that maintain the Indian-Ocean OMZs, we obtain a suite of solutions to a coupled biological/physical model. Its physical component is a variable-density, 6 1/2-layer model, in which each layer corresponds to a distinct dynamical regime or water-mass type. Its biological component has six compartments: nutrients, phytoplankton, zooplankton, two size classes of detritus, and oxygen. Because the model grid is non-eddy resolving (0.5 degrees), the biological model also includes a parameterization of enhanced mixing based on the eddy kinetic energy derived from satellite observations. To explore further the impact of local processes on OMZs, we also obtain analytic solutions to a one-dimensional, simplified version of the biological model. Our control run is able to simulate basic features of the oxygen, nutrient, and phytoplankton fields throughout the Indian Ocean. The model OMZs result from a balance, or lack thereof, between a sink of oxygen by remineralization and subsurface oxygen sources due primarily to northward spreading of oxygenated water from the Southern Hemisphere, with a contribution from Persian-Gulf water in the northern Arabian Sea. The northward intensification of the lower ASOMZ results mostly from horizontal mixing since advection is weak in its depth range. The eastward shift of the upper ASOMZ is due primarily to enhanced advection and vertical eddy mixing in the western Arabian Sea, which spread oxygenated waters both horizontally and vertically. Advection carries small detritus from the western boundary into the central/eastern Arabian Sea, where it provides an additional source of remineralization that drives the ASOMZ to suboxic levels. The model BBOMZ is weaker than the ASOMZ because the Bay lacks a remote source of detritus from the western boundary. Although detritus has a prominent annual cycle, the model OMZs do not because there is not enough time for significant remineralization to occur.