Abstract: This disclosure relates to method and system for providing a light weight secure communication for computing devices. In one example, the method includes generating a new encryption key based on a selected encryption key from among a plurality of encrypted keys and a current synchronized hash based on a set of pre-defined rules, generating an updated synchronized hash based on a message to be transmitted and the current synchronized hash using a pre-defined hash algorithm, encrypting the message to be transmitted using the new encryption key to generate an encrypted message, transmitting the encrypted message, and replacing the current synchronized hash with the updated synchronized hash. The set of pre-defined rules and the pre-defined hash algorithm are retrieved from a pre-installed library. Further, the current synchronized hash, the plurality of encryption keys, and the pre-installed library are synchronized between the first computing device and the second computing device.

Abstract: A method and a system of sharing an edge computing resource is disclosed. In an embodiment, the method may include receiving from one or more lessor edge computing resources, one or more first requests for presenting an availability of the one or more lessor edge computing resources, and receiving from a lessee edge computing resource, a second request for availing at least one lessor edge computing resource. The method may further include, upon receiving the second request, presenting the one or more first requests corresponding to the one or more lessor edge computing resources, to the lessee edge computing resource. The method may further include receiving from the lessee edge computing resource, a selection of a first request from the one or more first requests, and creating a connection between the lessee edge computing resource and the lessor edge computing resource corresponding to the received selection.

Abstract: A method and a device for associating sensors with entities within a stack is disclosed. In an embodiment, the method may include capturing at least one sensor parameter from each of a first plurality of sensors, wherein each of the first plurality of sensors is attached to an entity from a first plurality of entities placed within a stack. The method may further include determining a position of each of the first plurality of sensors relative to the stack, based on the associated at least one sensor parameter and a lookup table. The method may further include receiving an entity placement scheme within the stack, and associating each of the first plurality of sensors with one of the first plurality of entities within the stack to generate an association table, based on the position determined for each of the first plurality of sensors and the entity placement scheme.

Abstract: A method and system for summarizing content based on user preferences is disclosed. The method includes identifying a set of relevant objects from a set of objects based on a relevancy score corresponding to each of the set of objects extracted from a plurality of sentences. The method further includes generating a link graph between each of the plurality of sentences. The method further includes assigning a weight to each of the plurality of sentences based on a retention probability. The method further includes generating a summarized content from the plurality of sentences based on the user preferences, the link graph, and the weight associated with each of the plurality of sentences.

Abstract: The method of present disclosure relates to neural chip and optimizing operation of a neural chip. The method includes sensing current values of physical parameters indicating an environment. Sensed current values are stored in a memory unit. The memory unit also stores previously sensed values of physical parameters. The current values and the previously sensed values are compared by the neural chip. Based on the comparison, one or more actions are applied using the previously sensed values, for completing the task, if the current values and the previously sensed values are matched. In case there is no matching, the neural chip uses the current valises for applying the one or more actions. The neural chip learns from applying of the actions and updates itself accordingly.

Abstract: A system and method for identifying and subsequently modifying target sections within images is disclosed. The method includes receiving a user request that includes a target image and a user input, such that the user input includes an action corresponding to the target image. The method further includes extracting a plurality of target image attributes from the user input and comparing the plurality of target image attributes with a set of attributes within a pattern attribute table. The pattern attribute table includes mapping of each of the set of attributes to an associated set of activated neurons within a neural network. Comparing the plurality of target image further includes identifying a set of activated neurons mapped to the matching attribute as neuron activations corresponding to the plurality of target image attributes. The method includes identifying a target image section based on the set of activated neurons using a back-propagation technique.

Abstract: Systems and methods for dynamically testing product and process of production environment in virtual testing environment are disclosed. A testing system may retrieve production data related to each production activity corresponding to events executing in real-time. Each production activity is related to product and process of production environment. Further, testing system generates each scenario of production environment in virtual testing environment in real-time, based on sequencing of each event and creates, in the virtual testing environment, virtual process and virtual product corresponding to process and product of production environment, based on at least the events, generated scenarios, and historical data. Finally, testing system re-plays each production activity in virtual testing environment for testing virtual process and virtual product.

Abstract: A method and a system are described for detection of anomalies in surfaces, such as pipes. The method includes receiving an input comprising surface material type and plurality of frames of a real-time video stream associated with the surface. The method includes eliminating unwanted frames based on magnitude of 2-Dimensional optical flow vectors of the plurality of frames. The method includes identifying potential anomaly frames based on contours in a dense map created using a magnitude of displacement of each pixel of a frame. The method includes detecting in real-time anomalies in anomaly frames from potential anomaly frames based on trained models selected from a Model Mapping Table. The method includes classifying anomalies in the anomaly frames into anomaly classes using one or more deep learning techniques. The method includes generating a health report comprising anomalies in anomaly frames associated with the surface and providing health report to a user.

Abstract: A method and a systems of interchanging code-mixed words and uni-language words are described. In an embodiment, the method may include identifying two or more portions of a target word, wherein the target word is one of a code-mixed word and a uni-language word. The method may further include determining one or more equivalent words corresponding to at least one portion of the two or more portions, wherein the one or more equivalent words are in at least one predetermined target language. The method may further include selecting at least one equivalent word from the one or more equivalent words, based on a context of the target word within a sentence comprising the target word. The method may further include replacing the at least one portion of the two or more portions of the target word with the selected at least one equivalent word.

Abstract: The present invention discloses a method and a system for assisting user with product handling in a retail shopping. The method comprising identifying one or more products from a list of products that user intends to purchase, neighbouring products and orientations of the one or more products and the neighbouring products from a plurality of image frames and rack information, comparing the identified orientations with historic orientations of products and neighbouring products associated with the rack information, identifying at least one product from the one or more products and the neighbouring products that is improperly oriented based on comparison, determining product safety handling instructions of the identified at least one product and assisting the user in real-time with handling of the identified at least one product based on the product safety handling instructions.

Abstract: The present disclosure discloses method and a user intent identification system for identifying user intent from user statements. The user intent identification system receives input statement provided by a user from a Natural Language Understanding (NLU) engine. The input statement is processed to remove one or more irrelevant content. A plurality of features for each word in the processed input statement is extracted. The plurality of features comprises Parts of Speech (POS) label, dependency parse tree and word embeddings. The user intent determination system predicts class for each word in the processed input statement from a plurality of predefined classes using a neural network model. The neural network model predicts class for each word based on input vector generated for the each word based on the plurality of features. Thereafter, the user intent is identified based on class predicted for each word in processed input statement.

Abstract: Embodiment of the present disclosure discloses method and device for obtaining at least one influencing causal factor based on expert subjective judgement. Initially, first relative weightage values of plurality of predefined causal factors associated with each of one or more decision trees of classification in decision-making model is determined. Decision space is determined for classification based on first relative weightage values and base hypothesis associated with classification. The decision space is mapped with expert subjective judgment provided by expert user for classification. Error value associated with classification is determined based on mapping. Base hypothesis of classification is optimized such that optimized base hypothesis corresponds to minimum value of error value. Influencing causal factor from plurality of predefined causal factors are obtained by performing ensemble technique using optimized base hypothesis.

Abstract: Disclosed herein is method and system for prioritizing content for content processing by Multichannel Video Programming Distributors (MVPD). The system upon receiving multimedia content, determines premium quality vector for multimedia content. Further, system segments multimedia content into one or more segments and determines a complexity vector and social media vector for each segment. The complexity vector is identified based on scene transitions and complexity of scene in the segment. The social media vector is identified based on trend, popularity and viral nature of segment. The system assigns weightage to each segment using a machine learning model based on complexity vector, social media vector and premium quality vector. Based on weightage, system prioritizes segments for content processing. In this manner, present disclosure prioritizes content which needs to be first processed to reduce overall content processing time.

Abstract: The present invention relates to the field of dynamic content creation and management and more particularly to dynamically create and insert immersive promotional content in a multimedia. The multimedia requested by a user is procured from a media server (105) and the one or more objects present in the multimedia is determined. The content of the multimedia is analyzed, and a decision is taken to immerse the promotional content in the multimedia based on the analysis of the multimedia. Further, a promotional content is created in real time using the components present in the asset database (106) based on the personalized user profile. The created promotional content is overlaid and blended with a at least one object from the one or more objects in the multimedia. The created promotional content and the multimedia is joined to form a composite media and is streamed to the user device.

Abstract: This disclosure relates to method and system for managing security vulnerability in a host computer system. In an embodiment, the method may include receiving reputation data with respect to external network traffic data and receiving intrusion data with respect to host system data. The intrusion data may be generated by the host computer system based on the external network traffic data. The method may further include generating a plurality of test cases based on the reputation data and the intrusion data. The test cases, upon simulation, may provide information with respect to security vulnerability in the host computer system. The method may further include determining a set of implementable topologies for the host computer system, based on a simulation of each of the plurality of test cases, using a first artificial neural network (ANN) model to manage the security vulnerability.

Abstract: The present disclosure discloses method and a critical event managing system for managing time-critical events associated with critical devices. The critical event managing system identifies time-critical events from plurality of events based on predetermined factors related to the plurality of events. The plurality of events is determined from first procedural sequences identified from procedural narration by a practitioner and stored protocol manual. At least one of missed and incorrect events are determined based on comparison between reference and observed values associated with critical devices. A revised execution plan is provided iteratively based on historical data, data provided by practitioner, first procedural sequences, and metadata associated with plurality of parameters.

Abstract: This disclosure relates generally to a human machine interface (HMI) application, and more particularly to modular testing kits and testing framework for testing the HMI application. In one embodiment, a method for developing a modular testing kit for testing a modular component of the HMI application is disclosed. The method may include generating a plurality of test cases for testing the modular component based on a definition of each of a set of interfaces configured to implement the modular component on a target platform, developing the modular testing kit to execute the plurality of test cases by simulating each of the set of interfaces, and creating a test script for each of the plurality of test cases using the modular testing kit.

Abstract: A method and system for template-based dynamic network slicing is disclosed. The method includes creating a service requirement set associated with a service request based on a plurality of characteristics of the service request. The method includes identifying a network slice template hierarchy based on the service requirement set and selecting one of reusing one of at least one of existing network slice instance and creating a new network slice instance. The method includes instantiating a service associated with the service request using one of the at least one of existing network slice instances and the new network slice instance. The method further includes monitoring the service and one of the at least one of existing network slice instances and the new network slice instance. The method includes performing adaptation of at least one thresholds and at least one factor.

Abstract: The present disclosure relates to a method and system for predicting and mitigating failures in Virtual Desktop Infrastructure (VDI) systems. System logs is received from VDI systems. Error logs are segregated from the system logs. A prediction score is generated based on the error logs. A failure is predicted in VDI systems based on the prediction score and the error logs using a trained machine learning model. A response action associated with the predicted failure is determined. Training the machine learning model comprises receiving feature vectors associated with training error logs and one or more rules. Further, the training comprises determining a failure and a value based on the feature vectors and the one or more rules. Also, the training comprises determining a correlation between the one or more rules, the determined failure and the feature vectors.

Abstract: A method and driver assistance system for generating touch-based alerts to a driver in a vehicle is disclosed. The driver assistance system receives frames including the driver in vehicle and detects position of face of the driver in plurality of frames. Facial attributes of the driver are identified based on position of the face and one or more eye attributes of the driver are determined based on the identified one or more facial attributes. Based on the facial attributes and the one or more eye attribute sensory information is estimated from a plurality of sensory data. Further, information regarding haptic sensation is computed for the driver based on estimated sensory information and a position of hands of the driver received from a hand tracking device. Thereafter, an alert is generated using signals relating to the haptic sensation to the driver for taking one or more corrective measure.