Factors affecting the occurrence and transport of atmospheric organochlorines in the china sea and the northern Indian and South East atlantic oceans

Organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) are reported in 97 air samples collected on board the RV Polarstern in November 2007 from the equator to Cape Town, South Africa and the MV Oceanic II (The Scholar Ship) in January-March 2008 from Shanghai, China to Cape Verde in the Central Atlantic Ocean. The atmospheric concentrations were higher close to the coast and lower in remote regions of the Indian and South Atlantic Ocean. Groups of samples were selected in the South China Sea, Indian Ocean and South Atlantic Ocean where the relative wind direction matched the trajectory of the ship, thus all the samples had the same input of sources upwind. In these three regions the concentrations of OCPs and PCBs declined during atmospheric transport following first order kinetics. These sets of measurements provided estimates of field derived residence times (FDRTs) for individual compounds. These values were compared with predicted atmospheric residence times (PARTs) computed using a model of long-range atmospheric transport potential of POPs. The FDRTs are 5-10 times longer for the more volatile PCB congeners and TC, CC, p,p'-DDT and p,p'-DDE than the respective PARTs, while they are similar to PARTs for the less volatile compounds. Possible causes of discrepancies between PARTs and FDRTs are discussed, and revolatilization from the ocean surface seems to be the main cause for the higher values of FDRTs of the more volatile compounds in comparison with the respective PARTs.     

Modified Generalized Autocorrelation based Estimator for time delays in multipath environment - A tradeoff in estimator performance and number of multipath

In this paper, the existing Generalized Autocorrelation based Estimator (GAE) has been modified for estimation of time delays in multipath environment in the presence of uncorrelated noise. Here the multipath propagation output signal is modeled as a superposition of the delayed, attenuated, and filtered versions of the stationary Gaussian stochastic input signal. Accuracy Percentage (AP) performance measure has been used to characterize the performance of the estimators. The modified GAE performance has been compared, obtained both analytically and via simulation, with AP_CRLB the equivalent CRLB expressed in AP. Simulation results show that the performance of the proposed estimator improves with the increase in SNR but deteriorates with the increase in number of multipath.     

Feedback linearization based control of a rotational hydraulic drive

The technique of feedback linearization is used to design controllers for displacement, velocity and differential pressure control of a rotational hydraulic drive. The controllers, which take into account the square-root nonlinearity in the system's dynamics, are implemented on an experimental test bench and results of performance evaluation tests are presented. The objective of this research is twofold: firstly, to present a unified method for tracking control of displacement, velocity and differential pressure; and secondly, to experimentally address the issue of whether the system can be modeled with sufficient accuracy to effectively cancel out the nonlinearities in a real-world system.     

Improving neural machine translation for low-resource Indian languages using rule-based feature extraction

Neural Computing and Applications - Languages help to unite the world socially, culturally and technologically. Different natives communicate in different languages; there is a tremendous...     

Effect of Nano Particle Deposition on Mechanical Properties of Friction Stir Welded Dissimilar Aluminium Alloys by Taguchi Technique

Improving the mechanical properties while joining of dissimilar alloys by FSW has been a choice of research during the past decade. Hence, an attempt has been made in the present research to join dissimilar Al alloys (AA5052 and AA6063) by addition of Copper nanoparticles in the weld joint. A 5T NC FSW machine has been employed to perform the desired task. To achieve optimum values of the process parameters, an optimization study has been carried out using Taguchi technique. The results obtained from the optimization studies and experimental investigations match very well proving the efficacy of the study. The results from the investigation show an improvement in mechanical properties when Cu nanoparticles are deposited which are further supported by microstructure and EDX analysis.     

Entropy-based dual-portal-to-3-DCT registration incorporating pixel correlation

For patient setup verification in external beam radiotherapy (EBRT) of prostate cancer, we developed an information theoretic registration framework, called the minimax entropy registration framework, to simultaneously and iteratively segment portal images and register them to three-dimensional (3-D) computed tomography (CT) image data. The registration framework has two steps, the max step and the min step, and evaluates appropriate entropies to estimate segmentations of the portal images and to find the transformation parameters. In the initial version of the algorithm (Bansal et al. 1999), we assumed image pixels to be independently distributed, an assumption not true in general. Thus, to better segment the portal images and to improve the accuracy of the estimated registration parameters, in this initial formulation of the problem, the correlation among pixel intensities is modeled using a one-dimensional Markov random process. Line processes are incorporated into the model to improve the estimation of segmentation of the portal images. In the max step, the principle of maximum entropy is invoked to estimate the probability distribution on the segmentations. The estimated distribution is then incorporated into the min step to estimate the registration parameters. Performance of the proposed framework is evaluated and compared to that of a mutual information-based registration algorithm using both simulated and real patient data. In the proposed registration framework, registration of the 3-D CT image and the portal images is guided by an estimated segmentation of the pelvic bone. However, as the prostate can move with respect to the pelvic structure, further localization of the prostate using ultrasound image data is required, an issue to be further explored in future.     

Deep feature extraction and classification of breast ultrasound images

Controlled despeckling (structure/edges/feature preservation with smoothing the homogeneous areas) is a desired pre-processing step for the design of computer-aided diagnostic (CAD) systems using ultrasound images as the presence of speckle noise masks diagnostically important information making interpretation difficult even for experienced radiologist. For efficiently classifying the breast tumors, the conventional CAD system designs use hand-crafted features. However, these features are not robust to the variations in size, shape and orientation of the tumors resulting in lower sensitivity. Thus deep feature extraction and classification of breast ultrasound images have recently gained attention from research community. The deep networks come with an advantage of directly learning the representative features from the images. However, these networks are difficult to train from scratch if the representative training data is small in size. Therefore transfer learning approach for deep feature extraction and classification of medical images has been widely used. In the present work the performance of four pre-trained convolutional neural networks VGG-19, SqueezeNet, ResNet-18 and GoogLeNet has been evaluated for differentiating between benign and malignant tumor types. From the results of the experiments, it is noted that CAD system design using GoogLeNet architecture for deep feature extraction followed by correlation based feature selection and fuzzy feature selection using ANFC-LH yields highest accuracy of 98.0% with individual class accuracy value of 100% and 96% for benign and malignant classes respectively. For differentiating between the breast tumors, the proposed CAD system design can be utilized in routine clinical environment.