LZW Based Distance Measures for Spoken Language Identification

We present a new approach to spoken language modeling for language identification (LID) using the Lempel-Ziv-Welch (LZW) algorithm. The LZW technique is applicable to any kind of tokenization of the speech signal. Because of the efficiency of LZW algorithm to obtain variable length symbol strings in the training data, the LZW codebook captures the essentials of a language effectively. We develop two new deterministic measures for LID based on the LZW algorithm namely: (i) Compression ratio score (LZW-CR) and (ii) weighted discriminant score (LZW-WDS). To assess these measures, we consider error-free tokenization of speech as well as artificially induced noise in the tokenization. It is shown that for a 6 language LID task of OGI-TS database with clean tokenization, the new model (LZW-WDS) performs slightly better than the conventional bigram model. For noisy tokenization, which is the more realistic case, LZW-WDS significantly outperforms the bigram technique

Helium Gas Purity Monitor based on Low Frequency Acoustic Resonance

Monitoring gas purity is an important aspect of gas recovery stations where air is usually one of the major impurities. Purity monitors of Katherometric type ate commercially available for this purpose. Alternatively, we discuss here a helium gas purity monitor based on acoustic resonance of a cavity at audio frequencies. It measures the purity by monitoring the resonant frequency of a cylindrical cavity filled with the gas under test and excited by conventional telephone transducers fixed at the ends. The use of the latter simplifies the design considerably. The paper discusses the details of the resonant cavity and the electronic circuit along with temperature compensation. The unit has been calibrated with helium gas of known purities. The unit has a response time of the order of 10 minutes and measures the gas purity to an accuracy of 0.02%. The unit has been installed in our helium recovery system and is found to perform satisfactorily.

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.

On the sensitivity of elastic waves due to structural damages:Time-frequency based indexing method

Time-frequency analysis of various simulated and experimental signals due to elastic wave scattering from damage are performed using wavelet transform (WT) and Hilbert-Huang transform (HHT) and their performances are compared in context of quantifying the damages. Spectral finite element method is employed for numerical simulation of wave scattering. An analytical study is carried out to study the effects of higher-order damage parameters on the reflected wave from a damage. Based on this study, error bounds are computed for the signals in the spectral and also on the time-frequency domains. It is shown how such an error bound can provide all estimate of error in the modelling of wave propagation in structure with damage. Measures of damage based on WT and HHT is derived to quantify the damage information hidden in the signal. The aim of this study is to obtain detailed insights into the problem of (1) identifying localised damages (2) dispersion of multifrequency non-stationary signals after they interact with various types of damage and (3) quantifying the damages. Sensitivity analysis of the signal due to scattered wave based on time-frequency representation helps to correlate the variation of damage index measures with respect to the damage parameters like damage size and material degradation factors.

Inter-helical Interactions in Membrane Proteins: Analysis Based on the Local Backbone Geometry and the Side Chain Interactions

The availability of a significant number of the Structures of helical membrane proteins has prompted us to investigate the mode of helix-helix packing. In the present study, we have considered a dataset of alpha-helical membrane proteins representing Structures solved from all the known superfamilies. We have described the geometry of all the helical residues in terms of local coordinate axis at the backbone level. Significant inter-helical interactions have been considered as contacts by weighing the number of atom-atom contacts, including all the side-chain atoms. Such a definition of local axis and the contact criterion has allowed us to investigate the inter-helical interaction in a systematic and quantitative manner. We show that a single parameter (designated as alpha), which is derived from the parameters representing the Mutual orientation of local axes, is able to accurately Capture the details of helix-helix interaction. The analysis has been carried Out by dividing the dataset into parallel, anti-parallel, and perpendicular orientation of helices. The study indicates that a specific range of alpha value is preferred for interactions among the anti-parallel helices. Such a preference is also seen among interacting residues of parallel helices, however to a lesser extent. No such preference is seen in the case of perpendicular helices, the contacts that arise mainly due to the interaction Of Surface helices with the end of the trans-membrane helices. The Study Supports the prevailing view that the anti-parallel helices are well packed. However, the interactions between helices of parallel orientation are non-trivial. The packing in alpha-helical membrane proteins, which is systematically and rigorously investigated in this study, may prove to be useful in modeling of helical membrane proteins.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Automatic Road Extraction using High Resolution Satellite Image Based on Texture Progressive Analysis and Normalized Cut Method

In this paper the approach for automatic road extraction for an urban region using structural, spectral and geometric characteristics of roads has been presented. Roads have been extracted based on two levels: Pre-processing and road extraction methods. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, parking lots, vegetation regions and other open spaces). The road segments are then extracted using Texture Progressive Analysis (TPA) and Normalized cut algorithm. The TPA technique uses binary segmentation based on three levels of texture statistical evaluation to extract road segments where as, Normalizedcut method for road extraction is a graph based method that generates optimal partition of road segments. The performance evaluation (quality measures) for road extraction using TPA and normalized cut method is compared. Thus the experimental result show that normalized cut method is efficient in extracting road segments in urban region from high resolution satellite image.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Genetic characterization of Indian type O FMD virus 3A region in context with host cell preference

The 3A region of foot-and-mouth disease virus has been implicated in host range and virulence. For example, amino acid deletions in the porcinophilic strain (O/TAW/97) at 93-102 aa of the 153 codons long 3A protein have been recognized as the determinant of species specificity. In the present study, 18 type 0 FMDV isolates from India were adapted in different cell culture systems and the 3A sequence was analyzed. These isolates had complete 3A coding sequence (153 aa) and did not exhibit growth restriction in cells based on species of origin. The 3A region was found to be highly conserved at N-terminal half (1-75 aa) but exhibited variability or substitutions towards C-terminal region (80-153). Moreover the amino acid substitutions were more frequent in recent Indian buffalo isolates but none of the Indian isolates showed deletion in 3A protein, which may be the reason for the absence of host specificity in vitro. Further inclusive analysis of 3A region will reveal interesting facts about the variability of FMD virus 3A region in an endemic environment. (C) 2010 Elsevier B.V. All rights reserved.

A Cache coherence protocol for MIN-based multiprocessors

In this paper we present a cache coherence protocol for multistage interconnection network (MIN)-based multiprocessors with two distinct private caches: private-blocks caches (PCache) containing blocks private to a process and shared-blocks caches (SCache) containing data accessible by all processes. The architecture is extended by a coherence control bus connecting all shared-block cache controllers. Timing problems due to variable transit delays through the MIN are dealt with by introducing Transient states in the proposed cache coherence protocol. The impact of the coherence protocol on system performance is evaluated through a performance study of three phases. Assuming homogeneity of all nodes, a single-node queuing model (phase 3) is developed to analyze system performance. This model is solved for processor and coherence bus utilizations using the mean value analysis (MVA) technique with shared-blocks steady state probabilities (phase 1) and communication delays (phase 2) as input parameters. The performance of our system is compared to that of a system with an equivalent-sized unified cache and with a multiprocessor implementing a directory-based coherence protocol. System performance measures are verified through simulation.

Characterization and Acceptor Preference of a Soluble Meningococcal Group C Polysialyltransferase

Vaccines against Neisseria meningitidis group C are based on its alpha-2,9-linked polysialic acid capsular polysaccharide. This polysialic acid expressed on the surface of N. meningitidis and in the absence of specific antibody serves to evade host defense mechanisms. The polysialyltransferase (PST) that forms the group C polysialic acid (NmC PST) is located in the cytoplasmic membrane. Until recently, detailed characterization of bacterial polysialyltransferases has been hampered by a lack of availability of soluble enzyme preparations. We have constructed chimeras of the group C polysialyltransferase that catalyzes the formation alpha-2,9-polysialic acid as a soluble enzyme. We used site-directed mutagenesis to determine the region of the enzyme necessary for synthesis of the alpha-2,9 linkage. A chimera of NmB and NmC PSTs containing only amino acids 1 to 107 of the NmB polysialyltransferase catalyzed the synthesis of alpha-2,8-polysialic acid. The NmC polysialyltransferase requires an exogenous acceptor for catalytic activity. While it requires a minimum of a disialylated oligosaccharide to catalyze transfer, it can form high-molecular-weight alpha-2,9-polysialic acid in a nonprocessive fashion when initiated with an alpha-2,8-polysialic acid acceptor. De novo synthesis in vivo requires an endogenous acceptor. We attempted to reconstitute de novo activity of the soluble group C polysialyltransferase with membrane components. We found that an acapsular mutant with a defect in the polysialyltransferase produces outer membrane vesicles containing an acceptor for the alpha-2,9-polysialyltransferase. This acceptor is an amphipathic molecule and can be elongated to produce polysialic acid that is reactive with group C-specific antibody.

S-nets: A Petri net based model for performance evaluation of real-time scheduling algorithms

A new class of nets, called S-nets, is introduced for the performance analysis of scheduling algorithms used in real-time systems Deterministic timed Petri nets do not adequately model the scheduling of resources encountered in real-time systems, and need to be augmented with resource places and signal places, and a scheduler block, to facilitate the modeling of scheduling algorithms. The tokens are colored, and the transition firing rules are suitably modified. Further, the concept of transition folding is used, to get intuitively simple models of multiframe real-time systems. Two generic performance measures, called �load index� and �balance index,� which characterize the resource utilization and the uniformity of workload distribution, respectively, are defined. The utility of S-nets for evaluating heuristic-based scheduling schemes is illustrated by considering three heuristics for real-time scheduling. S-nets are useful in tuning the hardware configuration and the underlying scheduling policy, so that the system utilization is maximized, and the workload distribution among the computing resources is balanced.

Stochastic differential games: Occupation measure based approach

A new approach based on occupation measures is introduced for studying stochastic differential games. For two-person zero-sum games, the existence of values and optimal strategies for both players is established for various payoff criteria. ForN-person games, the existence of equilibria in Markov strategies is established for various cases.

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.