Abstract: Disclosed is a reconfigurable parallel 3-Dimensional (3-D) convolution engine for performing 3-D Convolution and parallel feature map extraction on an image. The reconfigurable parallel 3-D convolution engine further comprises a plurality of CNN reconfigurable engines configured to perform 3-D convolution, in parallel, to process a plurality of feature maps, a kernel memory space, present in each instance of CNN reconfigurable engine, capable for holding a set of parameters associated to a network layer having each operational instance of CNN reconfigurable engine, and at least one memory controller, an Input Feature Map Memory (FMM) cluster and an Output FMM cluster.

Abstract: The present disclosure relates to system(s) and method(s) for building an ARIMA based Time Series prediction/forecast model for Key Performance Indicators (KPIs) and Performance Management (PM) counters in a telecommunication network. The system receives historical data, for a predefined period, associated with a prediction/forecast model. The system further pre-processes the historical data in order to evaluate statistical characteristics of stationarity of the historical data. Based on the evaluation, the system stationarizes the data first by backfilling anomalies and missing data and then applying techniques associated with differencing, moving averages and auto-correlation. The system further builds the Time Series based prediction/forecast model using the data using ACF and PACF correlation functions.

Abstract: Disclosed is a method and system for verifying a regex sanitizer and a validator. The method comprises verifying of at least one of a regex sanitizer and a validator by applying the regex sanitizer and a validator over multiple predefined tainted inputs. An output obtained after applying at least one of the regex sanitizer is checked for one of a tainted output or a non-tainted output. The at least one of the regex sanitizer and validator may be qualified as a valid regex sanitizer and validator based upon the checking. The valid regex sanitizer may be tagged with a validation signature. The valid regex sanitizer is used for checking the tainted input in the user's input.

Abstract: Method and system for determining a conversation system from a multi-conversation system using Artificial Intelligence (AI) is provided. The method includes receiving a user query associated with a domain and creating a hierarchical tree comprising a root node and a child node using a first pre-trained machine learning model. The method further includes traversing the hierarchical tree for a path between root node and one leaf child node to identify a topic hierarchy. The path is associated with a confidence score corresponding to mapping between user query and match data of nodes in the path. The method further includes determining a conversation system from the multi-conversation system for outputting data to answer the user query corresponding to one leaf child node of one path with a highest confidence score.

Abstract: Disclosed is a convolution operator system comprising a Convolution Neural Network (CNN) reconfigurable engine including a plurality of Mini Parallel Rolling Engines (MPREs) for performing a convolution operation concurrently on an image. An input router receives image data. A controller allocates image data to computing blocks through a set of data flow control blocks. Each computing block produces a convolution output corresponding to each row of the image. The controller allocates a plurality of group having one or more computing blocks to generate a set of convolution output. Further, a pipeline adder aggregates the set of convolution output to produce an aggregated convolution output. An output router transmits either the convolution output or the aggregated convolution output for performing subsequent convolution operation to generate a convolution result for the image data.

Abstract: The invention relates to method and system for classifying faces of a Boundary Representation (B-Rep) model using Artificial Intelligence (AI). The method includes extracting topological information corresponding to each of a plurality of data points of a B-Rep model of a product; determining a set of parameters based on the topological information corresponding to each of the plurality of data points; transforming the set of parameters corresponding to each of the plurality of data points of the B-Rep model into a tabular format to obtain a parametric data table; and assigning each of the plurality of faces of the B-Rep model a category from a plurality of categories based on the parametric data table using an AI model.

Abstract: A method and system for determining collaboration between employees is disclosed. In some embodiments, the method includes receiving a plurality of collaboration parameters associated with a set of employees. The method further includes creating a plurality of employee nodes associated with the set of employees in a hierarchical tree, based on the plurality of collaboration parameters and a first pre-trained machine learning model. The method further includes generating a plurality of vector embeddings associated with the plurality of employee nodes, based on the first pre-trained machine learning model. The method further includes determining a degree of collaboration between at least two employees from the set of employees based on one or more vector embeddings from the generated plurality of embeddings.

Abstract: The present disclosure relates to system(s) and method(s) for tuning an analytical model. The system builds a global analytical model based on modelling data received from a user. Further, the system analyses a target eco-system to identify a set of target eco-system parameters. The system further selects a sub-set of model parameters, corresponding to the set of target eco-system parameters, from a set of model parameters. Further, the system generates a local analytical model based on updating the global analytical model, based on the sub-set of model parameters and one or more PMML wrappers. The system further deploys the local analytical model at each node, from a set of nodes, associated with the target eco-system. Further, the system gathers test results from each node based on executing the local analytical model. The system further tunes the sub-set of model parameters associated with the local analytical model using federated learning algorithms.

Abstract: An Aircraft Passenger Compliance Monitoring System (APCMS) for automating compliance monitoring for passengers onboard an aircraft is disclosed. In some embodiments, the APCMS includes an onboard server, an onboard network communicatively coupled to the onboard server, and an aircraft passenger compliance monitoring application communicatively coupled to the onboard server and the onboard network. The aircraft passenger compliance monitoring application is configured to receive passenger information related to each of a plurality of passengers. The aircraft passenger compliance monitoring application is further configured to perform a set of monitoring processes from a plurality of monitoring processes on the passenger related information received for each of the plurality of passengers. The aircraft passenger compliance monitoring application is further configured to generate a compliance measure in response to performing the set of monitoring processes.

Abstract: This disclosure relates to method and system for identifying common requirements from applications. The method includes receiving a plurality of requirements from a plurality of applications. For at least two of the plurality of requirements, the method further includes determining a similarity index through each of a set of analysis techniques. For at least two of the plurality of requirements, the method further includes calculating a final similarity index based on the similarity index determined through each of a set of analysis techniques. The method further includes generating a similarity matrix for the plurality of requirements based on the final similarity index. The method further includes generating a hierarchical cluster tree for the plurality of requirements based on the final similarity index corresponding to each of the plurality of requirements.

Abstract: The invention relates to method and system for automatic identification of a primary manufacturing process (PMP) from a three-dimensional (3D) model of a product. The method includes generating a plurality of images corresponding to a plurality of views of the product based on the 3D model of the product; determining a plurality of confidence score vectors, based on the plurality of images, using a first Artificial Neural Network (ANN) model; determining an aggregate confidence score vector, representing a pre-defined PMP category with maximum frequency, based on the plurality of confidence score vectors; extracting a set of manufacturing parameters associated with the product, based on the 3D model of the product; and identifying the PMP based on the aggregate confidence score vector and the set of manufacturing parameters, using a second ANN model.

Abstract: This disclosure relates to system and method for managing an insect swarm using a plurality of drones. The method includes detecting an insect swarm. The method may further include tracking a movement of the insect swarm. The method further includes communicating, with remaining of the plurality of drones, to dynamically align in a position based on the tracking so as to make a drone formation. The method further includes magnetizing, by at least some of the plurality of drones, one or more drone couplers for electromagnetically coupling the at least some of the plurality of drones with each other as per the drone formation. The method further includes casting, by each of the plurality of drones, a net to trap insects in the insect swarm. The method further includes supplying, by each of the plurality of drones, a high voltage to the net to decapacitate the insects.

Abstract: This disclosure relates to method and system for generating and rendering a customized dashboard. The method includes initiating a schema-less dashboard canvas through a frontend application that invokes a server-less library. The method further includes integrating a set of widgets selected by a user, from the plurality of native widgets and from the plurality of third-party widgets, with the schema-less dashboard canvas using the server-less library. The method further includes generating metadata for each of the set of widgets based on a corresponding configuration performed by the user. The method further includes associating the metadata with a user account of the user for subsequent rendering of the customized dashboard for the user.

Abstract: The present disclosure relates to a system and a method for processing distributed data files. The processor executes instructions to receive a set of instructions from a primary device, wherein the set of instructions comprises verification rules, validators, primary transformers and structure query transformers; generate processed data files by processing the distributed data files. The distributed data files are processed by performing at least one of: executing one of the verification rules, the validators and the primary transformers on the distributed data files; and transforming the distributed data files by executing the structure query transformers. The execution of the structured query transformers comprises steps of generating a dependency graph based upon dependencies between the structure query transformers; and determining a sequence of execution of the structured query transformers based upon the dependency graph; and transfer the processed data files to a data warehouse.

Abstract: Disclosed is a system (102) for executing a test case. The system (102) comprises a memory (206) and a processor (202). The system (102) receives a test file in a predefined format. The test file comprises a test case comprising one or more test steps, test data and one or more expected results for execution. Further, each test step from the one or more test steps indicates an action to be performed for executing the test case. The system (102) generates one or more tokens by classifying text associated with the one or more test steps. The system (102) generates an output template associated with the test case based on analysing the one or more tokens. The system (102) executes the test case based on one or more controls associated with the test case in the output template. The one or more controls are dynamically identified from the output template.

Abstract: The present disclosure relates to a system and method for controlling data interception in a communication network. One or more requests from a user for accessing one or more microservices are received through an Application Programming Interface (API). Information associated with one or more requests is the detected and requests are classified as secured microservice request and non-secured microservice request. The information is detected through predefined rules. Authentication token is then issued for secured microservice based on the detecting. The authentication token stores information detected by the detector in a geo storage system. The one or more requests are then routed according to the authentication token towards one or more corresponding microservices of the one or more microservices.

Abstract: The present disclosure relates to system(s) and method(s) for verifying data loading requirements of an avionics unit. The system receives a request for data loading. The request comprises file data, and data loading requirements associated with the avionics unit. Further, the system obtains target file from a repository based on an analysis of the request. The system further generates valid data set and invalid data set in the target file based on an analysis of the data loading requirements. Upon generation, the system verifies predefined data loading requirements of the avionics unit using the invalid data set from the target file.

Abstract: Systems and methods for data security using a blockchain ledger. The system receives request associated with a product from a user. The system further obtains data associated with the product upon receiving the request. Further, the system analyses the data to using predefined parameters identify valid data and invalid data. Upon identification, the system uploads the valid data in the blockchain ledger. Further, the valid data may be displayed to the user through a channel, associated with the user, in the blockchain ledger, thereby providing the data security.

Abstract: Disclosed is a method and system for joining datasets in a distributed computing environment. The system comprises a memory 206 and a processor 202. The processor 202 identifies a skewed dataset from two or more datasets to be joined. The processor 202 identifies a replication parameter from a configuration file. The processor 202 then assigns a randomly assigned machine number to each chunk of the skewed dataset owned by the nodes/machines involved in the join operation. The processor 202 forms copies of the non-skewed dataset equal to the replication parameter and adds the copy number to each sample of the copy of the non-skewed dataset formed. Further, the processor 202 merges each non-skewed dataset into the final copy of the non-skewed dataset, forming a single non skewed dataset. The processor 202 then repeats these steps for all the non-skewed datasets involved in the join operation resulting in generation of merged copies of all the non-skewed datasets and then performs the joining operation.

Abstract: Disclosed is a method and system for assessing the authenticity of a communication. The method comprises receiving data of the communication by the processor between one or more participants. Further, extracting one or more features by the processor from the data by using data extraction techniques. Further, comparing the one or more features by the processor with predefined threshold features stored in a feature repository. Further, generating, one or more authenticity attributes by using one or more trained Artificial Intelligence (AI) models applied over the one or more features, along with results of the comparing. Each of the one or more authenticity attributes generates a recommendation output, providing the authenticity of the communication.