SPSA Based Feature Relevance Estimation For Video Retrieval

With the availability of a huge amount of video data on various sources, efficient video retrieval tools are increasingly in demand. Video being a multi-modal data, the perceptions of ``relevance'' between the user provided query video (in case of Query-By-Example type of video search) and retrieved video clips are subjective in nature. We present an efficient video retrieval method that takes user's feedback on the relevance of retrieved videos and iteratively reformulates the input query feature vectors (QFV) for improved video retrieval. The QFV reformulation is done by a simple, but powerful feature weight optimization method based on Simultaneous Perturbation Stochastic Approximation (SPSA) technique. A video retrieval system with video indexing, searching and relevance feedback (RF) phases is built for demonstrating the performance of the proposed method. The query and database videos are indexed using the conventional video features like color, texture, etc. However, we use the comprehensive and novel methods of feature representations, and a spatio-temporal distance measure to retrieve the top M videos that are similar to the query. In feedback phase, the user activated iterative on the previously retrieved videos is used to reformulate the QFV weights (measure of importance) that reflect the user's preference, automatically. It is our observation that a few iterations of such feedback are generally sufficient for retrieving the desired video clips. The novel application of SPSA based RF for user-oriented feature weights optimization makes the proposed method to be distinct from the existing ones. The experimental results show that the proposed RF based video retrieval exhibit good performance.

Prediction of Ultimate Capacity of Laterally Loaded Piles in Clay: A Relevance Vector Machine Approach

This study investigates the potential of Relevance Vector Machine (RVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. RVM is a sparse approximate Bayesian kernel method. It can be seen as a probabilistic version of support vector machine. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. RVM model outperforms the two other models based on root-mean-square-error (RMSE) and mean-absolute-error (MAE) performance criteria. It also stimates the prediction variance. The results presented in this paper clearly highlight that the RVM is a robust tool for prediction Of ultimate capacity of laterally loaded piles in clay.

Microbial aspects of acid generation and bioremediation with relevance to indian mining

The role of Acidithiobacillus group of bacteria in acid generation and heavy metal dissolution was studied with relevance to some Indian mines. Microorganisms implicated in acid generation such as Acidithiobacillus Acidithicibacillus thiooxidans and Leptospirillum ferrooxidans were isolated from abandoned mines, waste rocks and tailing dumps. Arsenite oxidizing Thiomonas and Bacillus group of bacteria were isolated and their ability to oxidize As (111) to As (V) established. Mine isolated Sulfate reducing bacteria were used to remove dissolved copper, zinc, iron and arsenic from solutions.

The generalized anomeric effect in the 1,3-thiazolidines: Evidence forboth sulphur and nitrogen as electron donors. Crystal structures of various N-acylthiazolidines including mercury(II) complexes. Possible relevance to penicillin action

Evidence for the generalized anomeric effect (GAE) in the N-acyl-1,3-thiazolidines, an important structural motif in the penicillins, was sought in the crystal structures of N-(4-nitrobenzoyl)-1,3-thiazolidine and its (2:1) complex with mercuric chloride, N-acetyl-2-phenyl-1,3-thiazolidine, and the (2:1) complex of N-benzoyl-1,3-thiazolidine with mercuric bromide. An inverse relationship was generally observed between the. C-2-N and C-2-S bond lengths of the thiazolidine ring, supporting the existence of the GAE. (Maximal bond length changes were similar to 0.04 angstrom for C-2-N-3, S-1-C-2, and similar to 0.08 angstrom for N-3-C-6.) Comparison with N-acylpyrrolidines and tetrahydrothiophenes indicates that both the nitrogen-to-sulphur and sulphur-to-nitrogen GAE's operate simultaneously in the 1,3-thiazolidines, the former being dominant. (This is analogous to the normal and exo-anomeric effects in pyranoses, and also leads to an interesting application of Baldwin's rules.) The nitrogen-to-sulphur GAE is generally enhanced in the mercury(II) complexes (presumably via coordination at the sulphur); a 'competition' between the GAE and the amide resonance of the N-acyl moiety is apparent. There is evidence for a 'push-pull' charge transfer between the thiazolidine moieties in the mercury(II) complexes, and for a 'back-donation' of charge from the bromine atoms to the thiazolidine moieties in the HgBr2 complex. (The sulphur atom appears to be sp(2) hybridised in the mercury(II) complexes, possibly for stereoelectronic reasons.) These results are apparently relevant to the mode of action of the penicillins. (c) 2006 Elsevier B.V. All rights reserved.

Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

Positional dependence of material flow in friction stir welding: analysis of joint line remnant and its relevance to dissimilar metal welding

Understanding material flow in friction stir welding is important for production of sound dissimilar metal welding that control the intermixing of two alloys being welded and consequent formation of new constituents which influences the weld properties. In the present experimental investigation material flow patterns are visualised using dissimilar and similar aluminium alloys using a simple innovative ,experiment. The experimental results reveal that only a portion of material transported from the leading edge undergoes chaotic flow and the remaining is deposited systematically in the trailing edge of the weld. Using this information it is shown that the formation of a friction stir welding defect, joint line remnant, does not occur only when the weld interface is on the advancing side. The material flow visualisation study has been utilised to analyse the mechanism of weld formation and its usefulness in improving fatigue properties and for dissimilar metal welds.

A neural network based CBIR system using STI features and relevance feedback

Multimedia mining primarily involves, information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the Internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution(STI). Content Based Image Retrieval(CBIR) is an efficient retrieval of relevant images from large databases based on features extracted from the image. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The paper proposes a CBIR System named STIRF (Shape, Texture, Intensity-distribution with Relevance Feedback) that uses a neural network for nonlinear combination of the heterogenous STI features. Further the system is self-adaptable to different applications and users based upon relevance feedback. Prior to retrieval of relevant images, each feature is first clustered independent of the other in its own space and this helps in matching of similar images. Testing the system on a database of images with varied contents and intensive backgrounds showed good results with most relevant images being retrieved for a image query. The system showed better and more robust performance compared to existing CBIR systems

New evidences on Tau-DNA interactions and relevance to neurodegeneration

Tau is mainly distributed in cytoplasm and also found to be localized in the nucleus. There is limited data on DNA binding potential of Tau.We provide novel evidence on nicking of DNA by Tau. Tau nicks the supercoiled DNA leading to open circular and linear forms. The metal ion magnesium (a co-factor for endonuclease) enhanced the Tau DNA nicking ability, while an endonuclease specific inhibitor,aurinetricarboxylic acid (ATA) inhibited the Tau DNA nicking ability Further, we also evidenced that Tau induces B-C-A mixed conformational transition in DNA and also changes DNA stability. Tau-scDNA complex is more sensitive to DNAse I digestion indicating stability changes in DNA caused by Tau. These findings indicate that Tau alters DNA helicity and integrity and also nicks the DNA. The relevance of these novel intriguing findings regarding the role Tau in neuronal dysfunction is discussed. (C) 2010 Elsevier Ltd. All rights reserved.

Interaction of A beta peptide (1-40) with amino acid aluminium complexes: relevance to Alzheimer's disease

A beta (39-43 aminoacid residues) is the principal peptide component of amyloid deposits in Alzheimer's disease (AD). A beta peptide is derived from the amyloid precursor protein (APP) in which mutations give rise to many forms of familial AD. Aluminium is reported to play a key role in inducing conformational change in the synthetic beta-amyloid peptide (1-40)from alpha-helix to beta-pleated sheet, leading to aggregation and fibrillar formation. We have studied the interaction of amino acid-Al complexes such as D-Asp-Al and L-Glu-Al with A beta(1-40) in TFE/buffer (70% TFE and 30% H2O v/v pH 6.7) mixture using CD spectroscopy. The interaction of either of these amino acid complexes with A beta(1-40) results in loss of alpha-helical content and the peptide is more unstructured compared to free Al3+ in the solution. Our data strongly support the idea, that the Al3+ in the form of aminoacid-Al complexes is more effective in inducing random coil conformation in the A beta peptide than the free Al3+ present in the solution.

An XPS study on oxidation states of Pt and its alloys with Co and Cr and its relevance to electroreduction of oxygen

Cathodic reduction of oxygen in fuel cells is known to be enhanced on platinum alloys in relation to the platinum metal. The higher performance of the platinum alloys is as a result of the improved oxygen-reduction kinetics on the alloys but there is hardly any increase in the electrode platinum-surface-areas for the platinum alloys as compared to the platinum metal, and thus the higher performance is solely due to the enhanced electrocatalytic activity of the alloys as compared to the platinum metal. The present X-ray photoelectron spectroscopic (XPS) study on carbon-supported Pt, Pt–Co and Pt–Co–Cr electrocatalysts suggests the presence of a relatively lower Pt-oxide content on the alloys. The X-ray powder diffraction patterns for these electrocatalysts show that while the carbon-supported platinum electrocatalyst has a face-centered cubic (fcc) phase, carbon-supported Pt–Co and Pt–Co–Cr electrocatalysts exhibit a face-centered tetragonal (fct) phase. But, Pt electrocatalyst has a lower particle-size and, hence, a higher dispersion. Previous studies have shown higher activities on the Pt-alloys than on Pt, and have attributed it to changes in the electronic and structural characteristics of Pt. These changes can be correlated with the lower oxidation-state of Pt sites, as found in this study.

Curcumin-glucoside, A Novel Synthetic Derivative of Curcumin, Inhibits alpha-Synuclein Oligomer Formation: Relevance to Parkinson's Disease

alpha-Synuclein aggregation is centrally implicated in Parkinson's disease (PD). It involves multi-step nucleated polymerization process via the formation of dimers, soluble toxic oligomers and insoluble fibrils. In the present study, we synthesized a novel compound viz., Curcumin-glucoside (Curc-gluc), a modified form of curcumin and studied its anti-aggregating potential with alpha-synuclein. Under aggregating conditions in vitro, Curc-gluc prevents oligomer formation as well as inhibits fibril formation indicating favorable stoichiometry for inhibition. The binding efficacies of Curc-gluc to both alpha-synuclein monomeric and oligomeric forms were characterized by micro-calorimetry. It was observed that titration of Curc-gluc with alpha-synuclein monomer yielded very low heat values with low binding while, in case of oligomers, Curc-gluc showed significant binding. Addition of Curc-gluc inhibited aggregation in a dose-dependent manner and enhanced alpha-synuclein solubility, which propose that Curc-gluc solubilizes the oligomeric form by disintegrating preformed fibrils and this is a novel observation. Overall, the data suggest that Curc-gluc binds to alpha-synuclein oligomeric form and prevents further fibrillization of alpha-synuclein; this might aid the development of disease modifying agents in preventing or treating PD.