Signal subspace approach in localization of sound source in shallow water

A new algorithm based on signal subspace approach is proposed for localizing a sound source in shallow water. In the first instance we assumed an ideal channel with plane parallel boundaries and known reflection properties. The sound source is assumed to emit a broadband stationary stochastic signal. The algorithm takes into account the spatial distribution of all images and reflection characteristics of the sea bottom. It is shown that both range and depth of a source can be measured accurately with the help of a vertical array of sensors. For good results the number of sensors should be greater than the number of significant images; however, localization is possible even with a smaller array but at the cost of higher side lobes. Next, we allowed the channel to be stochastically perturbed; this resulted in random phase errors in the reflection coefficients. The most singular effect of the phase errors is to introduce into the spectral matrix an extra term which may be looked upon as a signal generated coloured noise. It is shown through computer simulations that the signal peak height is reduced considerably as a consequence of random phase errors.

Flux Partitioning of Species Approach in Binary Interdiffusion Process

Validation of the flux partitioning of species model has been illustrated. Various combinations of inequality expression for the fluxes of species A and B in two successively grown hypothetical intermetallic phases in the interdiffusion zone have been considered within the constraints of this concept. Furthermore, ratio of intrinsic diffusivities of the species A and B in those two phases has been correlated in four different cases. Moreover, complete and or partial validation or invalidation of this model with respect to both the species, has been proven theoretically and also discussed with the Co-Si system as an example.

Nonthermal plasma approach in direct methanol synthesis from CH4

Direct methanol synthesis from CH4 and O2 has been experimentally studied using pulsed discharge plasma in concentric-cylinder-type reactors. The methanol production becomes efficient with an increase in the average electric field strength of the reactor. A combination of the pulsed discharge and catalysts was tested and was proved to be effective in increasing both the production and selectivity of methanol. In the present stage, about 2% of CH4 can be converted into other hydrocarbons, and a methanol yield of around 0.5% and selectivity of 38% can be obtained when a catalyst of V2O5+SiO2 is combined with the pulsed discharge plasma

Nonthermal plasma approach in direct methanol synthesis from CH4

Conversion of hydrocarbon fuels to methanol promoted their efficient utilization as methanol can easily be converted to hydrogen gas, which has higher available energy. In this regard, nonthermal plasma approach using electrical discharges is gaining significance to improve the conversion process of methanol. The efficiency of this nonthermal plasma chemical reaction is affected by various chemical and electrical parameters. This paper presents some important results of the parametric study carried out in methanol synthesis with the aim of reducing energy losses associated with the conventional method. The parameters include the concentration of the reactants, corona electrode configurations, gas mixtures, etc. Further, an attempt was made to study the combined effect of catalysts and electrical discharges on methanol synthesis. Main emphasis was laid on the electrical aspects like electric field, power transfer efficiency, etc. The gas analysis was carried out under carefully maintained laboratory conditions

Enhanced viability of probiotic Saccharomyces boulardii encapsulated by layer-by-layer approach in pH responsive chitosan-dextran sulfate polyelectrolytes

Saccharomyces boulardii was encapsulated by layer-by-layer technique (LbL) using oppositely charged polyelectrolytes, chitosan and dextran sulfate to protect from degradation during its gastrointestinal transit. The protective effect of the coating was evaluated by checking viability after subjecting the coated cells to lyophilisation and simulated gastrointestinal conditions. During lyophilization, coated S. boulardii was found to have an enhanced viability of 7.74 +/- 2.00 log CFU/100 mg (5.62 x 10(6) +/- 2.12 CFU/100 mg) and 5.53 +/- 1.85 log CFU/100 mg (3.46 x 10(5) 1.73 CFU/100 mg) for uncoated cells. On sequential treatment with simulated gastric and intestinal juice, the coated cells had a viability of 4.59 +/- 1.52 log CFU/100 mg (3.8 x 104 +/- 1.52 CFU/100 mg) while only 1.90 +/- 0.80 log CFU/100 mg (0.79 x 102 +/- 0.81 CFU/100 mg) of uncoated cells survived. Confocal studies displayed the selective permeability of the coated cells which plays a significant role in maintaining the integrity and viability of the yeast cells. This clearly indicates that LbL is an efficient protective encapsulation technique and it could be potentially used for improving therapeutic applications of yeast. (C) 2014 Elsevier Ltd. All rights reserved.

Quality Assurance and Assessment in Technical Education System: A Web Based Approach

Engineering education quality embraces the activities through which a technical institution satisfies itself that the quality of education it provides and standards it has set are appropriate and are being maintained. There is a need to develop a standardised approach to most aspects of quality assurance for engineering programmes which is sufficiently well defined to be accepted for all assessments.We have designed a Technical Educational Quality Assurance and Assessment (TEQ-AA) System, which makes use of the information on the web and analyzes the standards of the institution. With the standards as anchors for definition, the institution is clearer about its present in order to plan better for its future and enhancing the level of educational quality.The system has been tested and implemented on the technical educational Institutions in the Karnataka State which usually host their web pages for commercially advertising their technical education programs and their Institution objectives, policies, etc., for commercialization and for better reach-out to the students and faculty. This helps in assisting the students in selecting an institution for study and to assist in employment.

3D shape extraction of human face in presence of facial hair: A profilometric approach

The increasing use of 3D modeling of Human Face in Face Recognition systems, User Interfaces, Graphics, Gaming and the like has made it an area of active study. Majority of the 3D sensors rely on color coded light projection for 3D estimation. Such systems fail to generate any response in regions covered by Facial Hair (like beard, mustache), and hence generate holes in the model which have to be filled manually later on. We propose the use of wavelet transform based analysis to extract the 3D model of Human Faces from a sinusoidal white light fringe projected image. Our method requires only a single image as input. The method is robust to texture variations on the face due to space-frequency localization property of the wavelet transform. It can generate models to pixel level refinement as the phase is estimated for each pixel by a continuous wavelet transform. In cases of sparse Facial Hair, the shape distortions due to hairs can be filtered out, yielding an estimate for the underlying face. We use a low-pass filtering approach to estimate the face texture from the same image. We demonstrate the method on several Human Faces both with and without Facial Hairs. Unseen views of the face are generated by texture mapping on different rotations of the obtained 3D structure. To the best of our knowledge, this is the first attempt to estimate 3D for Human Faces in presence of Facial hair structures like beard and mustache without generating holes in those areas.

The Indian-Institute-Of-Science - 8 Decades Of An Interdisciplinary Center

The Indian Institute of Science at Bangalore is probably the oldest institute in India, established with a donation from the great industrial visionary Jamsetji Tata over eight decades ago. It has gradually become a key centre of scientific and engineering research and higher education. From its very inception the institute had an interdisciplinary approach to research and teaching.

Human Action Recognition in Compressed Domain using PBL-McRBFN Approach

Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.