Abstract: In computing, an unresolved problem of high manual effort required for mapping data attributes between the source and the target systems involved in process of the data transformation. This disclosure relates to method of auto-mapping of a plurality of source data attributes and a plurality of target data attributes associated with one or more applications based on similarity of a metadata information is provided. The processor implemented method include processing, a corresponding source table to a target table based on similarity associated with a table name; determining, a candidate source data attributes for at least one target data attribute based on similarity associated with a data attribute name; computing, a weighted score of each of the candidate source data attributes for corresponding at least one target data attribute; and mapping, the weighted score to determine an association of a final data attribute.

Abstract: The disclosure generally relates to methods and systems for ensuring the on-time delivery (OTD) of a product by a manufacturing company. According to the present disclosure, a part persona for each part is generated using a data model, by placing the part as an central entity and the one or more influencing factors of each part that affect the OTD of the product are captured in the part persona. A trained intent and OTD prediction model is built and used to predict an initial intent and an initial OTD for each part, based on the corresponding part persona. Further, the trained intent and OTD prediction model is used to predict a successive intent and a successive OTD for each part, based on the conversations and the events. Hence the OTD of the product is accurately predicted and which is useful to ensuring the OTD of the product.

Abstract: The fine-grained variations in product images are usually due to slight variations in text, size, and color of the package. Both marginal variations in image content and illumination poses an important challenge in product classification. This disclosure relates to a system and method for fine-grained classification of similar-looking products utilizing object-level and part-level information. The system simultaneously captures an object-level and part-level information of the product. The object-level classification score of the product is estimated with the trained RC-Net, a deep supervised convolutional autoencoder. For annotation-free modelling of part-level information of the product the discriminative part-proposal of the product is identified around the BRISK key points. An ordered sequence of the discriminative part-proposals and the product image, encoded using stacked convolutional LSTM network, estimates the part-level classification score.

Abstract: This disclosure relates generally to relates to the field of estimation of remaining useful life (RUL) in lithium based batteries, and, more particularly, to estimation of remaining useful life in lithium based batteries based on coupled estimation of a state of charge (SOC) and a state of health (SOH) during charging/discharging in constant current (CC) and constant voltage (CV) modes. The disclosed RUL estimation technique considers the inter-dependency of SOC-SOH and influence of internal-external parameters/factors during the coupled estimation of SOC-SOH. The coupled estimation of SOC and SOH is based on a reduced order physics based modelling technique and considers the influence real time environment obtained using real-time dynamic data obtained by several sensors during the coupled estimation of SOC-SOH.

Abstract: This disclosure relates generally to systems and methods for masking and unmasking of sensitive data. The present systems and methods solve the problems of consistency of the data masking, by using a random index and a masked index with use of regular expression concept. An additional random key produce different masked data versions, however the original form of the sensitive data is achieved with any masked data version. Plurality of masked data versions are generated by masking the sensitive input dataset, where the plurality of masked data versions comprises same format of the sensitive input dataset. The generated masked data versions are secured and hard to predict the original form of the sensitive input dataset by authorized or unauthorized environments. Also, the present method consume less processing time, as the masking process and the unmasking process make operations on the indexes rather than with the original dataset.

Abstract: A system and method for estimating blood pressure (BP) using photoplethysmogram (PPG) has been explained. The PPG is captured from a PPG sensor (102). For preparing training model, a pulse oximeter is used for capturing PPG. For testing, a smartphone camera is used for capturing the PPG signal. A plurality of features are extracted from the preprocessed PPG signal. A BP distribution is then generated using the plurality of features and the training model. The BP distribution is part of a set of BP distributions generated from different subjects. Finally, a post-processing methodology have been used to reject inconsistent data out of the set of BP distributions and BP value is estimated only for the remaining BP distributions and a statistical average is provided as the blood pressure estimate.

Abstract: This disclosure relates generally to method and system for enhancing Quality of experience (QoE) for rendering live interactive videos in real-time. The conventional methods utilize an additional field in packet header to determine which packet sequences were lost, so that the receiver could request a retransmission. Due to unpredictable delay and loss, the receiver may not get the end-of-frame packet which has been sent using best-effort. The disclosed method and system introduced an additional indicator to identify an expected maximum number of packets transmitted for each frame, and further determine the distribution of loss so that the rendering unit can intelligently decide on whether to allow the frame to display, or to drop it without using any additional retransmission or error-concealment strategy, thereby enhancing the QoE of reception at the receiver.

Abstract: Electrical utilities offer incentives to customers to reduce consumption during periods of demand-supply mismatch. A building's participation in demand response (DR) depends both on its ability (due to building constraints), and its willingness (a function of incentive) to reduce electricity. Customers prefer a large incentive whereas a utility would want to minimize the revenue outflow to achieve a target reduction. Systems and methods of the present disclosure identify optimal incentive from the utility's perspective reflecting this trade-off. A model is built to estimate the demand response potential (DRP) of a building for a given incentive offered by the utility. The models for individual buildings are used to characterize the behavior of an ensemble of buildings. The utility may then decide optimum incentives that should be offered to achieve a target DR, using the associated DRP.

Abstract: This disclosure relates generally to method and system for determining myocardial ischemia severity based on hemodynamic parameters estimation. Many patients suffer from myocardial ischemia due to narrowing of coronary artery resulting poor oxygen supply in cardiac muscles. The method includes receiving Electrophysiology (EP) signal from a simulated heart surface model to generate a single lead ECG template. The method further estimates hemodynamic parameters using a hemodynamic module based on the single lead ECG template and then estimates cardiac pressure-volume loop variables. The myocardial ischemia severity of the heart surface model is determined which includes one of moderate ischemia, severe ischemia and silent ischemia. Here, the cardiac source module is coupled with the hemodynamic module to determine cardiac transmembrane potential (TMP) of the heart surface model through contractility function.

Abstract: This disclosure relates to a method and system for regime-based process optimization of various assets of industrial manufacturing and process plants or units. Operating regimes of assets are identified and a regime similarity score of each asset is computed from regime sequences of integrated industrial data and compared with a given threshold to identify regimes of operation. Operating regimes are matched with regimes of regime database and industrial assets and similar operating regimes are group together. Process optimization is carried out for each group of industrial assets to identify optimum settings in order to maximize output or minimize loss/cost considering process and equipment constraints. Anomalies are analyzed in the unmatched operating regimes and a diagnosis is carried out to identify the root cause for any detected anomalies. Remaining useful life of components in the assets with unmatched operating regimes is estimated to ensure component reliability and to prevent failure.

Abstract: Authentication is a key procedure in information systems. Conventional biometric authentication system is based on a trusted third-party server which is not secure. The present disclosure provides a privacy preserving multifactor biometric authentication for authenticating a client without the third-party authentication server. The server receives a plurality of encrypted biometric features from the client, encrypted using Fully Homomorphic Encryption. Further, the server evaluates the plurality of encrypted biometric features to obtain a client identifier value and a plurality of encrypted resultant values. The server encrypts each of the plurality of resultant values based on a time based nonce and the client identifier value. The encrypted authentication tags and the corresponding resultant values are aggregated by the server and transmitted to the client. The client decrypts the resultant value and the authentication tag and transmits to the server.

Abstract: Conventionally, manufacturing of molded parts using composite materials has led to poor dimensional accuracy and tensile strength due to improper curing thus resulting in rejection or early/premature failure of composite part. Embodiments of the present disclosure provide simulation-based systems and methods for manufacturing/generating molded parts using reinforced composite materials. The optimized cure cycle is computed for a given component without carrying out numerous experiments. The present disclosure implements multiscale method and surrogate modeling in virtual testing for more accurate and faster manufacturing of molded parts. Process parameters for specified qualities (e.g., minimum residual stresses, minimum deformation, etc.) required for a part are determined along with least process manufacturing time. The resulting optimized time dependent cure cycle for each thermal zone of the heated mold is transferred to a master controller (e.g.

Abstract: The present subject matter discloses a method for application data synchronization through a communication network. The method includes receiving application data from at least one user device, formatting the application data based on at least one formatting parameter to generate a data file, where the formatting parameter is indicative of a format of the data file, and transmitting the data file to at least one target syncing device through protocols based on Push Email Synchronization.

Abstract: Most of the prior art references that generate animations fail to determine and consider head movement data. The prior art references which consider the head movement data for generating the animations rely on a sample video to generate/determine the head movements data, which, as a result, fail to capture changing head motions throughout course of a speech given by a subject in an actual whole length video. The disclosure herein generally relates to generating facial animations, and, more particularly, to a method and system for generating the facial animations from speech signal of a subject. The system determines the head movement, lip movements, and eyeball movements, of the subject, by processing a speech signal collected as input, and uses the head movement, lip movements, and eyeball movements, to generate an animation.

Abstract: The present disclosure provides methods and systems for automated identification of agro-climatic zones. The methods deal with receiving parameters pertaining to ambience and soil from various external systems for a geographical region via one or more interaction methods. The parameters may be raw data or derived from raw data, homogenized and stored in a generic and hierarchical format for easy consumption. Inference is drawn from the parameters and associated attributes by comparing with historic attributes available in a knowledge base module for a corresponding agro-climatic zone. Inferences may also be made from parameters available in encoded form such as images, videos and ontological knowledge. Based on the comparison, a score is generated that reflects the degree of compliance with pre-defined agro-climatic zones.

Abstract: This disclosure relates generally to speech signal processing, and more particularly to method and system for improving recognition of disordered speech. In one embodiment, a method and a system for identifying extent of deviation in speech utterances of a user from a normal level, caused due to such impairments are provided. The system further makes appropriate modifications to generate utterances pertaining to healthy speech. This data may be fed as input to the speech recognition systems, as those systems can interpret the corrected data.

Abstract: This disclosure relates generally to methods and systems for generating a textual summary from a tabular data. During the textual summary generation using conventional end-to-end neural network-based techniques, a numeric data present in the tables is encoded via textual embeddings. However, the textual embeddings cannot reliably encode information about numeric concepts and relationships. The methods and systems generate the textual summary from the tabular data, by incorporating rank information for different records present in the tabular data. Then, a two-stage encoder-decoder network is used to learn correlations between the rank information and the probability of including the records based on the rank information, to obtain the textual summary generation model. The textual summary generation model identifies the content selection having the records present in the tables to be included in the textual summary and generates the textual summary from the identified content selection.

Abstract: Existing methods of automated testing of web service APIs require additional tools to extract API related details and configuration files to create test cases. The method and system disclosed herein taps annotations present in code of web service APIs to extract API related details and creates test cases using the extracted data. The method disclosed herein describes an approach to identify resource classes related to a plurality of web service APIs using built-in annotations in code of web application under test. Further, the identified resource classes are scanned to extract API related details (metadata) using built-in annotations and annotations given by a developer. Further, the extracted metadata is forwarded to a test engine server which generates a plurality of test cases using the extracted metadata. Further, the plurality of web service APIs are tested using the generated test cases.

Abstract: This disclosure relates to multi-sensor fusion using Transform Learning (TL) that provides a compact representation of data in many scenarios as compared to Dictionary Learning (DL) and Deep network models that may be computationally intensive and complex. A two-stage approach for better modeling of sensor data is provided, wherein in the first stage, representation of the individual sensor time series is learnt using dedicated transforms and their associated coefficients and in the second stage, all the representations are fused together using a fusing (common) transform and its associated coefficients to effectively capture correlation between the different sensor representations for deriving an inference. The method and system of the present disclosure can find application in areas employing multiple sensors that are mostly heterogeneous in nature.

Abstract: This disclosure relates generally to production of stable and uniformly dispersed nanoparticles. Convention methods of nanoparticle production includes a two-step approach that utilizes additives or surface modifiers. The disclosed method avoids using any additives/surface modifiers owing to the environmental and economic implications. The method includes employing process conditions in a reaction to manipulate electrostatic double layer repulsive forces among nanoparticles to impart the dispersion stability of nanoparticles. The reaction includes pouring pH modifier dropwise into metal precursor solution with vigorous stirring forming metal hydroxide solution, while maintain ranges for concentration of metal precursor solution about 0.15M to 0.75 M, pH about 9 to 12, ionic conductivity about 50 to 200 mS/cm, stirring speed about 800 to 1200 rpm, aging time 6 to 24 hours. The metal hydroxide solution is heated with temperature maintained in range of 100 to 400° C.