Abstract: This disclosure relates to method and system for improving performance of an artificial neural network (ANN). The method may include generating a weight matrix comprising weights of neural nodes in a given layer for each layer of the ANN, determining a marginal contribution value of a given neural node for each neural node in the given layer with respect to other neural nodes in the given layer, executing an elimination decision for each neural node in each layer based on the corresponding marginal contribution value, determining a distributed surplus value of a given remaining neural node in a given layer based on the marginal contribution values of a coalition of remaining neural nodes in the given layer for each remaining neural node in each layer, and updating the weight matrix based on the distributed surplus value of each remaining neural node in each layer.

Abstract: Disclosed herein is a method and system for providing personalized content to a user. The method comprises categorizing original content to be provided to user into a plurality of data packets. The data packets include data of similar domain. The user is categorized into one of plurality of classes and a vocabulary of words suitable for the class is identified. The class is associated with a domain. The system identifies relevant content for the class. Thereafter, the system modifies the original content by either by inserting a new data packet or deleting a data packet. A target content is generated for the class based on vocabulary of words associated with class and modified original content. Thereafter, the target content is provided to the class by incorporating one or more features of a presenter for presenting the target content. The present disclosure enhances user experience by personalizing content for the user.

Abstract: A method and a system are described for context based clustering of one or more objects. The method comprises receiving, by the object clustering system, receiving, by an object clustering system, an object clustering request for one or more objects associated with a plurality of contextual parameters, where the plurality of contextual parameters comprises one or more physical attributes and one or more non-physical attributes. It further includes tagging the one or more non-physical attributes respectively to the one or more physical attributes. It further includes identifying a common context from the one or more physical attributes associated with the one or more objects based on the tagging. It further includes mapping the one or more physical attributes to the one or more objects based on the common context. It then includes clustering the one or more objects based on the mapping.

Abstract: The present invention discloses a method and a system for monitoring manufacturing operation workflow using Structural Similarity (SSIM) index based activity detection. The method comprising receiving video data corresponding to a manufacturing operation activity, extracting a plurality of video frames from the video data, measuring SSIM index for each video frame of the plurality of video frames with respect to next consecutive video frame of the plurality of video frames, comparing the SSIM index of the each video frame with the SSIM index of next consecutive video frame of the plurality of video frames to identify one or more local maxima, and determining at least one manufacturing operation activity based on the one or more local maxima using machine learning technique.

Abstract: A technique is provided for minimizing impact of a faulty node associated with an artificial network. The technique includes detecting a faulty node associated with the artificial neural network. The faulty node causes a faulty path in the artificial neural network. Further, a plurality of alternate paths are identified to reroute the faulty path. Based on the identified plurality of alternate paths, the faulty path is rerouted by assigning one or more weights associated with the faulty node to one or more nodes associated with the plurality of alternate paths.

Abstract: The present disclosure relates to an elevation detection system for an Autonomous Vehicle (AV) and a method for detecting elevation of surrounding of the AV. The elevation detection system includes an elevation sensor unit and a computation unit. The elevation sensor unit is configured to detect an elevation of a plurality of objects having a lower most elevation, in the surrounding of the AV to determine a boundary elevation of the road. The elevation sensor unit is vertically movable within a range of vertical positions. A Light Detection and Ranging (LIDAR) sensor unit is associated with the elevation sensor unit, to detect the surrounding of the AV, having a predefined Field of View (FoV). The computation unit determines a lower limit value of the FoV and provides it to the LIDAR sensor unit for accurately detecting obstacles in the road.

Abstract: The disclosure relates to system and method for facilitating designing of an Internet of Things (IoT) infrastructure for deploying an IoT application. The method includes determining a Manhattan distance between each of a plurality of existing requirements and a new requirement, identifying one or more of the plurality of existing requirements corresponding to a minimum Manhattan distance, determining a relevancy score for each of the one or more identified existing requirements based on a similarity between the each of the one or more identified existing requirements and the new requirement, and providing one or more IoT components and one or more IoT designs corresponding to a similar existing requirement for facilitating designing of the IoT infrastructure. The similar existing requirement comprises one of the one or more identified existing requirement with a maximum relevancy score.

Abstract: The disclosure relates to method and system for providing a MIMO transceiver in high speed mobility. The method includes dividing, by the wireless MIMO transmitter, transmission data into a plurality of transmit chains corresponding to an antenna. The method further includes generating for the plurality of transmit chains, a Circularly Pulse Shaped Orthogonal Time Frequency Space (CPS-OTFS) time frequency signal based on a first primary parameter. Value of the first primary parameter is determined based on a first predefined algorithm. The method further includes converting for the plurality of transmit chains, the CPS-OTFS time frequency signal to a CPS-OTFS time domain signal based on at least one of a plurality of secondary parameters. A first plurality of N-point Inverse Fast Fourier Transform (IFFT) are employed on the CPS-OTFS time frequency signal. The first plurality corresponds to the number of sub-carriers and N corresponds to a set of time symbols.

Abstract: Disclosed herein is a method and a source code generator for dynamically generating an executable source code for an application. Initially, user inputs related to requirements of an application are received from a user. Subsequently, an application flow corresponding to the application is identified and one or more source codes for the application flow are generated using at least one pre-trained code generation model. Further, one or more best-fit source codes for the application are determined based on similarities among each of the one or more source codes. Finally, the executable source code for the application is generated by validating the one or more best-fit source codes based on historical information related to the one or more executable source codes previously generated by the source code generator. In an embodiment, the present disclosure helps to reduce turnaround time and manual efforts required for developing an application.

Abstract: This disclosure relates to method and system for building ensemble models using competitive reinforcement learning (CRL). The method may include creating a plurality of clusters, each including a set of predictive models forming the ensemble model. For each of the plurality of clusters, the method may further include initializing each of the set of predictive models with random values for a set of first parameters to obtain a first accuracy score, categorizing each of the set of predictive models into a first associated category based on a first accuracy score, calculating a first reward for each of the set of predictive models based on the first associated category, and determining a set of second parameters for each of the set of predictive models using CRL to obtain a second accuracy score.

Abstract: The present invention discloses a method and a system for managing cache memory. The system comprising a processor is configured to receive datasets from one or more applications, segregate the received datasets into one or more data blocks, identify a checkpoint from previously created checkpoints stored in a virtual cache corresponding to the one or more data blocks, wherein the checkpoints are previously created based on frequency of repetition of each of the one or more data blocks and association between the each of the one or more data blocks, recall a sequence of previously stored data blocks from main memory based on the identified checkpoint, and send the sequence of previously stored data blocks to the one or more applications for execution, thereby managing cache memory.

Abstract: Embodiments of the present disclosure relate to generating velocity profiles for an autonomous vehicle (101). An ECU (107) of the autonomous vehicle (101) receives road information from one or more sensors (106) associated with the autonomous vehicle (101). One or more parameters related to smooth movement of the autonomous vehicle on the road is determined from the road information. Further, a first velocity profile is produced using an AI model and a second velocity profile is produced using a hierarchical model, based on the one or more parameters. Furthermore, one of the first and the second velocity profile is selected by comparing the first and the second velocity profiles. The selected velocity profile has a lower value of velocity value compared to the other velocity profile. The selected velocity profile is provided to the autonomous vehicle (101) for navigating on the road (102) smoothly.

Abstract: A method and system for determining lane change feasibility for autonomous vehicles is disclosed. The method includes the steps of tracking, in each frame, at least one neighboring vehicle from a plurality of neighboring vehicles in a current lane being used by the AV and in a plurality of adjacent lanes. The method further includes determining, in each frame, a set of kinematic parameters associated with each of the at least one neighboring vehicle, and assigning an occupancy state from a plurality of occupancy states to each of a plurality of voxels capturing a spatial information for each of the plurality of neighboring vehicles. The method may further includes determining an effective occupancy probability for each of the plurality of adjacent lanes, and determining feasibility of lane change for the AV to at least one adjacent lane from the plurality of adjacent lanes.

Abstract: System and method of providing real-time remote assistance to a user is disclosed. In one embodiment, an assistance system, upon receiving a request from the user, captures holographic information of one or more objects associated with a task to be performed by the user. The assistance system further transmits the holographic information to an expert, wherein the expert is identified based on one or more skills required to perform the task. Further, assistance system receives one or more brain signals associated with the expert while the expert is interacting with a virtual simulation of the one or more objects to perform the task. Further the assistance system provides real-time remote assistance to the user by generating execution commands for the user in real-time based on a plurality of features associated with performing the task extracted from the one or more brain signals received from the expert.

Abstract: The disclosure relates to method and system for correcting a clock skew in a slave device using a precision time protocol (PTP). The method includes determining an uplink delay and a downlink delay, based on at least two packet transactions in the PTP protocol and conducted between the slave device and a master device within a pre-defined accumulator time window. The method further includes determining a change in the uplink/downlink delay with respect to a reference uplink/downlink delay. The reference uplink/downlink delay correspond to a first pre-defined accumulator time window at a start of the slave device, or to a last pre-defined accumulator time window during a previous correction of the clock skew. The method further includes correcting the clock skew upon determining the change in the uplink delay to be about same in magnitude as and to be in opposite direction to the change in the downlink delay.

Abstract: The disclosure relates to an enhanced data security system and method thereof. In some embodiments, the method includes receiving the transactional credential dataset from a user application. The transactional credential dataset is provided by a user to the user application. The method further includes storing the transactional credential dataset in nodes of a graphical embedding storage model. The nodes further store historical credential datasets of the user. Further, the method includes determining a correlation among the historical credential datasets using an artificial neural network (ANN) model and detecting a pattern of the transactional credential dataset based on the correlation. The ANN model is trained based on credential datasets provided by users stored in the nodes of the graphical embedding storage model.

Abstract: Disclosed herein is a method and system for dynamically generating a secure navigation path for navigation of an autonomous vehicle. The method comprises detecting disproportional acceleration of the autonomous vehicle when the autonomous vehicle is navigating from a source point to a destination point based on a predefined trajectory plan. The method comprises determining direction values of the autonomous vehicle for reaching a secure path point in the predefined trajectory plan. Based on the determined direction values, distance values are determined. The method includes detecting position of the secure path point for navigation of the autonomous vehicle based on the determined direction values and the distance values. The present disclosure uses secure path point to realign the autonomous vehicle in the predefined trajectory plan to overcome the disproportional acceleration of the autonomous vehicle due to narrow roads, upward slope, or downward slope.

Abstract: A method and a system of selective encryption of a test dataset is disclosed. In an embodiment, the method may include determining a relevancy grade associated with each of a plurality of datapoints within a test dataset by comparing the test dataset with a common heat map, wherein the common heat map is generated using a plurality of training datasets. The method may further include calculating, based on the relevancy grade, an encryption level associated with each of the plurality of datapoints. The method may further include selectively encrypting at least one datapoint from the plurality of datapoints based on the encryption level associated with each of the plurality of datapoints. The at least one data point is rendered to a user after being decrypted.

Abstract: A method and system for allocating resources to containers includes receiving a plurality of resource allocation requests from a plurality of containers, receiving a preference of a container from each of the plurality of containers, determining a priority-sequence for the plurality of containers, allocating a first associated resource for an associated first time-period to each container of the plurality of containers, determining a current consumption of the first associated resource by each container of the plurality of containers during the associated first time-period, and allocating a second associated resource to each container of the plurality of containers based on the current consumption of the first associated resource by each container of the plurality of containers.

Abstract: The disclosure relates to method and system for performing optimized image search. The method includes receiving an input image and user requirements with respect to an image search, identifying a sub-section from various sub-sections of the input image based on semantic parameters corresponding to each sub-section and the user requirements, and determining an optimal resolution of the sub-section based on a pixel density of various image formats derived for the sub-section. The method further includes identifying an optimal set of layers from a plurality of layers of an Artificial Neural Network (ANN) based image search model for performing the image search based on the semantic parameters for the sub-section, the optimal resolution of the sub-section, and historical data, and performing the image search to identify a set of output images similar to the sub-section based on a modified ANN based image search model comprising the optimal set of layers.