Tata Consultancy Services Patente

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A method and system for determining a speed of a vehicle based on a GPS speed captured from a Global Positioning System (GPS). A capturing module (212) captures GPS speed V x and a horizontal accuracy value corresponding to a time stamp T x . A speed modification module (214) modifies the GPS speed V x corresponding to the time stamp T x . A speed correcting module (216) corrects the GPS speed V x corresponding to the time stamp T x . The GPS speed may be corrected by filtering an error in the GPS speed by using a Slope dependent averaging (SDA) filter in order to obtain a first corrected speed V x '. Further, the first corrected speed is corrected by selecting one of a centre weight (CW) filter and an edge weight (EW) filter, based upon a pre-defined condition, in order to obtain a second corrected speed V x " indicating the speed of the vehicle.

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A method and system for in-silico testing of actives on human skin is described. The present invention discloses a micro and macroscopic level model of the skins upper protective layer Stratum-Corneum. The invention presents a multi-scale modeling framework for the calculation of diffusion and release profile of different actives like drugs, particles and cosmetics through developed skin model using molecular dynamics simulations and computational fluid dynamics approach. The systems consist of a molecular model of the skin's upper layer stratum corneum and permeate molecules. The system also consists of a macroscopic transport model of stratum corneum. The transport model is used to generate the release profile of the active molecule.

A system and method for creating and maintaining a unique data repository (102) comprising a matching process based on a set of predefined matching conditions and thereon performing an action type corresponding to the outcome of matching process. The present disclosure provides for real time data de-duplication and updating of the unique data repository to obtain a unified view of unique and matching records.

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Existing software defect text categorization approaches are based on use of supervised/semi-supervised machine learning techniques, which may require significant amount of labeled training data for each class in order to train the classifier model leading to significant amount of human effort, resulting in an expensive process. Embodiments of the present disclosure provide systems and methods for circumventing the problem of dependency on labeled training data and features derived from source code by performing concept based classification of software defect reports. In the present disclosure, semantic similarity between the defect category/type labels and the software defect report(s) is computed and represented in a concept space spanned by corpus of documents obtained from one or more knowledge bases, and distribution of similarity values are obtained. These similarity values are compared with a dynamically generated threshold, and based on the comparison, the software defect reports are classified into software defect categories.

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Method and system for user authentication are described. The method comprises receiving an authentication code from an application server (108) seeking authentication of the user. Further, a private key of the user is computed in real time based on a user identity (ID) of the user and a master secret key of the PKG. The method further comprises, ascertaining a verification code based on the private key of the user and a verification timestamp, wherein the verification timestamp indicates a time at which the ascertaining of the verification code was initiated. Further, the authentication code is compared with the verification code. Further, the method comprises authenticating the user based on the comparison.

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Methods and systems for masking data columns in a database are described herein. The method describes obtaining a masking template. Further the method describes associating the masking template (124) with at least one rule and selecting columns based on the at least one rule. The method further describes identifying at least one column from the selected columns for applying masking setup and initiating masking setup on the at least one column based on the masking template (124).

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Systems and methods for analyzing community structures within a plurality of environmental samples are described herein. The method includes obtaining taxa data corresponding to taxonomic groups within the plurality of the environmental samples. Based on the taxa data, an abundance value for each of the taxonomic groups with respect to each of the plurality of environmental samples is determined. Further, based on abundance values, an interaction factor for each pair of the taxonomic groups in the plurality of environmental samples is computed. The interaction factor is indicative of a degree of interaction between a pair of taxonomic groups from among the taxonomic groups. Based in part on interaction factors and abundance values, the plurality of the environmental samples is clustered.

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Disclosed is an interworking gateway facilitating to-and-fro communication between a first subscriber and a second subscriber. The first subscriber is on a Global System for Mobile Communications Railway (GSM-R) network and the second subscriber is on a Terrestrial Trunked Radio (TETRA) network. In one aspect, the interworking gateway receives a plurality of ISUP messages from the first subscriber. The plurality of ISUP messages are based on an ISUP protocol. Upon receiving an ISUP message, of the plurality ISUP messages, the interworking gateway selects an ISI message, from the plurality ISI messages, equivalent to the ISUP message based on a pre-defined mapping to facilitate the to-and-fro communication. The to-and-fro communication is facilitated by at least one of a Point-to-Point Call (PtP), a Voice Group Call Service (VGCS), and a Voice Broadcast Service (VBS) between the first subscriber and the second subscriber in a vendor independent approach.

Systems and methods for test data generation are described. In one implementation, the method includes receiving seed data (118-1) having one or more characteristics. Further, the method includes obtaining a selection criterion indicating a selected portion of the seed data (118-1) to be transformed. Based on the selection criterion, the seed data (118-1) is transformed for at least a plurality of iterations to generate test data (118-2). The test data (118-2) comprise a plurality of data sets including a primary data set (120-1) generated in a first iteration and a secondary data set (120-2) generated in each subsequent iteration. The primary data set (120-1) includes transformed data corresponding to the selected portion of the seed data (118-1) and non-transformed data corresponding to a remaining portion of the seed data (118-1) and each secondary data set (120-2) includes transformed data corresponding to the selected portion of the seed data (118-1).