A method and system of providing assistance during an operation performed on an equipment by a smart assistance device. A first set of image frames and a second set of image frames corresponding to forward steps and reverse steps respectively performed during the operation are received from an imaging device. Parts of the equipment are detected in each of first set of image frames and tagged. The smart assistance device detects parts of the equipment present in an image frame for each of the second set of the image frames. A discrepancy is determined in the reverse steps by comparing the parts of the equipment present in the frame of the second set of the image frames with the parts tagged in the corresponding first image frame of the first set of image frames. A notification and recommendation is provided to correct the discrepancy.
G06T 7/50 - Récupération de la profondeur ou de la forme
G06V 20/70 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène Étiquetage du contenu de scène, p.ex. en tirant des représentations syntaxiques ou sémantiques
2.
MANAGING PATCHED GLOBAL ASSEMBLY CACHE (GAC) METHOD FOR WEBSITES RUNNING IN A .NET FRAMEWORK ENVIRONMENT
The invention relates to method and system for managing patched Global assembly cache methods for websites running in .NET framework environment. The method includes initiating a second domain when a website hosted on web-server is loaded for first-time; creating a copy of each of the one or more .NET modules for reverse patching; creating a runner method to call the copy of each of the one or more .NET modules; creating a patched method corresponding to each of the one or more .NET modules in the second domain; calling, in run-time, the patched method in second domain upon encountering the corresponding .NET module. Further, calling patched method includes calling the runner method via reflection in run-time. Calling the runner method includes calling the copy of the corresponding .NET module via reverse patching in run-time. The method further includes monitoring, in real-time, behaviour of the patched method in the second domain.
A method and system for performing cloud vendor arbitrage using AI is disclosed. The method includes receiving each of a plurality of metrices for each of a set of components associated with an application and infrastructure deployment, and creating one or more feature vectors corresponding to each of the plurality of metrices. The one or more feature vectors are created based on corresponding one or more first pre-trained machine learning models. The method further includes predicting a metric value corresponding to each of plurality of metrices, based on assessing of the one or more feature vectors using corresponding one or more first pre-trained machine learning models and performing cloud vendor arbitrage by computing prices for each of the set of components from price data received from each of a plurality of cloud vendors. The method further includes determining a cloud preference from at least one of plurality of cloud vendors.
The invention relates to method and system for intoxication examination of an operator for operating an asset. The method includes receiving input data corresponding to the operator prior to operating the asset from one of an asset or a client device; determining an intoxication score of the operator based on the input data using a Machine Learning (ML) model; determining permissibility of operating an asset for the operator through a plurality of predefined rules using the ML model; assigning the asset to the operator when the asset operation is determined to be permissible for the operator; transmitting authorization information to the assigned asset; authorizing, by the asset, the operator to operate the asset based on the authorization information; upon authorization, monitoring in real-time, the operator during the asset operation from real-time video data of the operator to check for compliance of the asset operation with the conditions of operation.
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
G06V 20/52 - Activités de surveillance ou de suivi, p.ex. pour la reconnaissance d’objets suspects
5.
METHOD AND SYSTEM FOR FEATURE EXTRACTION USING RECONFIGURABLE CONVOLUTIONAL CLUSTER ENGINE IN IMAGE SENSOR PIPELINE
The invention relates to method and system for feature extraction from an input image from a plurality of images in an image sensor pipeline. The method includes determining a number of logical convolutional operations to be performed, within a reconfigurable convolutional cluster engine, based on a size of an input feature map corresponding to the input image; performing a set of concurrent row wise convolutions on the input feature map, based on the number of logical convolutional operations; performing at least one of a maximum pooling or an average pooling operation on the set of corresponding convolution output through one or more pooling elements to generate a set of pooling output; and generating an output feature map based on the set of pooling output.
G06V 10/77 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source
G06T 5/30 - Erosion ou dilatation, p.ex. amincissement
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
6.
METHOD AND SYSTEM FOR PATCHING WEBSITES RUNNING IN A .NET FRAMEWORK ENVIRONMENT
The invention relates to method and system for patching websites running in a .NET framework environment. The method includes initiating second domain when website hosted on web-server is loaded for first-time. The website includes set of .NET modules, and one or more of the set of .NET modules are of interest. The method further includes creating patched method corresponding to each of the one or more of the set of .NET modules in the second domain by inserting preconfigured tracking code that calls the .NET module in the website via reflection. The method further includes calling, in real-time, the patched method in the second domain upon encountering the corresponding .NET module; monitoring, in real-time, behaviour of the patched method in the second domain; generating notification when the website is unloaded. The second domain is updated with information corresponding to unavailability of the unloaded website upon generating the notification.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
A method for transmitting media content from a cloud content delivery network (CCDN) to a plurality of in-flight wireless media servers (WMSs) is disclosed. In some embodiments, the method includes receiving, by each of the plurality of in-flight WMSs, position data with respect to at least one of a movement, an altitude, or a geo-spatial location of an aircraft; identifying, by the plurality of in-flight WMSs, one or more elevated in-flight WMSs for receiving the media content. The method for identifying further includes determining a respective content-reception state of each of the plurality of in-flight WMSs; determining a respective content-reception suitability score for each of the plurality of in-flight WMSs; and identifying the one or more elevated in-flight WMSs. The method further includes receiving, by each of the one or more elevated in-flights WMSs, the media content from a suitable CCDN server in the CCDN.
H04N 21/214 - Plate-forme spécialisée de serveur, p.ex. serveur situé dans un avion, un hôtel ou un hôpital
H04N 21/231 - Opération de stockage de contenu, p.ex. mise en mémoire cache de films pour stockage à court terme, réplication de données sur plusieurs serveurs, ou établissement de priorité des données pour l'effacement
8.
METHOD AND SYSTEM FOR ACCESSING USER RELEVANT MULTIMEDIA CONTENT WITHIN MULTIMEDIA FILES
A method for generating a temporal token file to enable access to selective multimedia content within a multimedia file is disclosed. In some embodiments, the method includes identifying a plurality of multimedia content present within the multimedia file. The method further includes generating a token file for each of the plurality of multimedia content. To generate the token file, the method includes retrieving a plurality of snippets from each of the plurality of multimedia content; and annotating each of the plurality of snippets with a textual token. The method further includes extracting a timestamp associated with each of the plurality of snippets. The method further includes generating the temporal token file associated with each of the plurality of multimedia content based on the token file and the timestamp extracted for each of the plurality of snippets.
G06V 20/70 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène Étiquetage du contenu de scène, p.ex. en tirant des représentations syntaxiques ou sémantiques
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04N 21/466 - Procédé d'apprentissage pour la gestion intelligente, p.ex. apprentissage des préférences d'utilisateurs pour recommander des films
H04N 21/845 - Structuration du contenu, p.ex. décomposition du contenu en segments temporels
H04N 21/8547 - Création de contenu impliquant des marquages temporels pour synchroniser le contenu
9.
SYSTEM AND METHOD FOR MANAGING AN INSECT SWARM USING DRONES
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.
A01M 5/00 - Capture des insectes dans les champs, jardins ou forêts, au moyen d'appareillages mobiles
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
G05D 1/10 - Commande de la position ou du cap dans les trois dimensions simultanément
A01M 29/16 - CAPTURE OU PIÉGEAGE DES ANIMAUX OU ÉPOUVANTAILS; APPAREILS DE DESTRUCTION D'ANIMAUX OU DE PLANTES NUISIBLES Épouvantails ou dispositifs répulsifs, p.ex. pour oiseaux utilisant des ondes sonores
G05D 1/12 - Commande pour la recherche d'un objectif
10.
SYSTEM AND METHOD FOR MANAGING AN INSECT SWARM USING DRONES
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.
A01M 5/00 - Capture des insectes dans les champs, jardins ou forêts, au moyen d'appareillages mobiles
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
G05D 1/10 - Commande de la position ou du cap dans les trois dimensions simultanément
A01M 29/16 - CAPTURE OU PIÉGEAGE DES ANIMAUX OU ÉPOUVANTAILS; APPAREILS DE DESTRUCTION D'ANIMAUX OU DE PLANTES NUISIBLES Épouvantails ou dispositifs répulsifs, p.ex. pour oiseaux utilisant des ondes sonores
G05D 1/12 - Commande pour la recherche d'un objectif
11.
METHOD AND SYSTEM FOR GENERATING TIGHTEST REVOLVE ENVELOPE FOR COMPUTER-AIDED DESIGN (CAD) MODEL
This disclosure relates to method and system for generating tightest revolve envelope for a Boundary representation (B-rep) Computer-Aided Design (CAD) model. The method includes receiving a 2-dimensional (2D) point cloud within an XY-plane corresponding to each of a plurality of faces of the B-rep CAD model within an XYZ-space. The method further includes, for each of the plurality of faces, determining a concave hull shape for the 2D point cloud through a concave hull algorithm. The method further includes combining the concave hull shape corresponding to each of the plurality of faces of the B-rep CAD model through at least one of a Boolean operation and a stitching operation to obtain a tightest revolve profile of the B-rep CAD model. The method further includes revolving the tightest revolve profile about X-axis of the XYZ-space to obtain a tightest revolve envelope corresponding to the B-rep CAD model.
A staircase mobility system is disclosed. The system includes a docking assembly that is configured to dock or undock with a dockable seat assembly. The docking assembly includes support rods configured to engage or disengage with the dockable seat assembly when docked or undocked, respectively. Further, the system includes a drive assembly coupled to the docking assembly. The drive assembly includes a motor that is configured to drive the docking assembly along a guide rail in a forward or reverse direction, and to operate the docking assembly to dock or undock with the dockable seat assembly.
B66B 9/08 - Genres ou types d'ascenseurs installés dans les bâtiments ou édifices ou adjoints à ceux-ci inclinés, p.ex. desservant des hauts fourneaux combinés à des escaliers, p.ex. pour transporter des personnes infirmes
13.
METHOD AND SYSTEM OF IDENTIFYING A WELDMENT FEATURE
The disclosure relates to method and system for identifying a weldment feature. The method may include extracting a plurality of wire bodies from a sheet-metal model, and identifying from the plurality of wire bodies, a set of wire bodies associated with a face of the sheet-metal model. The method may further include generating one or more potential weldment features from the set of wire-bodies. Each of the one or more potential weldment features may be analyzed with respect to the face of the sheet-metal model. The method may further include identifying from the one or more potential weldment features, at least one related pair of weldment features. Weldment features of each related pair may include one of a contacting relationship and crossing relationship with each other.
The disclosure relates to method and system for intelligently managing time and attendance of a user in an establishment. The method includes recording, by a custom wearable device, a set of evaluation parameters associated with the user; receiving, by an intelligent Access Point Network (IAPN), the set of evaluation parameters from the custom wearable device; computing, by a distance calculator, a distance of the custom wearable device from the IAPN; determining, by an intelligent monitoring subsystem, a valid usage of the custom wearable device based on the set of evaluation parameters using a first trained machine learning model; determining one of a valid presence or a valid movement of the custom wearable device based on the set of evaluation parameters and the distance using a second trained machine learning model; and generating an alert in response to determination of at least one the valid usage or the valid presence.
The invention relates to method and system for automatically identifying tube elements in a Boundary Representation (B-Rep)-based Computer Aided Design (CAD) model of a tube. The method includes extracting information corresponding to the B-Rep-based CAD model of the tube; validating geometrical features of the B-Rep based CAD model of the tube based on the extracted information; classifying each of a plurality of faces of the tube into one of a set of face types; determining one or more regions on the tube using a set of connected top faces of the tube; generating a plurality of primary tube elements and a set of secondary tube elements based on shapes of the plurality of regions; determining a plurality of element parameters for each of the plurality of tube elements of the tube; and determining a plurality of tube parameters for the tube based on the plurality of element parameters.
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.
G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
17.
Method and system for classifying faces of boundary representation (B-Rep) models using artificial intelligence
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.
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo
G06V 10/46 - Descripteurs pour la forme, descripteurs liés au contour ou aux points, p.ex. transformation de caractéristiques visuelles invariante à l’échelle [SIFT] ou sacs de mots [BoW]; Caractéristiques régionales saillantes
G06V 10/778 - Apprentissage de profils actif, p.ex. apprentissage en ligne des caractéristiques d’images ou de vidéos
18.
METHOD AND SYSTEM FOR EVALUATING LUMINANCE IN AUGMENTED REALITY (AR) APPLICATIONS
The disclosure relates to method and system for evaluating luminance in Augmented Reality (AR) applications. The method includes receiving a plurality of video frames corresponding to an AR object in a real-world environment at a current camera angle; for each of the plurality of video frames, subtracting the set of AR object pixels from the set of environment pixels in a frame; calculating mean luminance value corresponding to the set of AR object pixels in each of the at least one of the plurality of blocks in the frame and corresponding to each of the plurality of blocks of the grid in the real-world environment through a light sensor; comparing mean luminance value for each of the plurality of blocks of the grid with mean luminance value corresponding to the set of AR object pixels; and evaluating luminance of AR object at the current location in the AR application.
G06T 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie
G06T 19/20 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie Édition d'images tridimensionnelles [3D], p.ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 10/60 - Extraction de caractéristiques d’images ou de vidéos relative aux propriétés luminescentes, p.ex. utilisant un modèle de réflectance ou d’éclairage
G06V 10/74 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques
19.
METHOD AND SYSTEM FOR PERFORMING DATALOAD PROTOCOL OPERATION TESTING IN AN AVIONICS UNIT
A method for performing dataload protocol operation testing in an avionics Line Replaceable UNIT (LRU) is disclosed. In some embodiments, the method includes sending a request to initiate transfer of a dataload sequence from an external data loader to a target hardware. The method further includes receiving an acceptance status from the target hardware to initiate transfer of the dataload sequence based on at least one of the valid or invalid dataload sequence request or response. The method further includes determining, based on the invalid dataload sequence request or response, occurrence of one or more failure scenarios associated with at least one of: the transmission of the dataload sequence; and the receiving of the acceptance status from the target hardware on different stages of dataload operation.
This disclosure relates to method and system for optimally fitting shapes in a 2-Dimensional (2D) sheet. The method includes receiving discretized geometric data corresponding to a 2D shape; generating a pair of copies of the 2D shape including a first copy and a second copy using the discretized geometric data; determining an optimal arrangement of the first copy and the second copy on the 2D sheet to obtain an optimally arranged pair; generating first copy of the optimally arranged pair and second copy of the optimally arranged pair; determining a pair combination with a minimum distance between the first copy and the second copy; calculating a maximum number of repetitions possible for the pair combination on the 2D sheet based on sheet dimensions and a set of pair combination parameters; and identifying an optimal pair combination from a plurality of pair combinations based on the maximum number of repetitions.
A method and system for automating analysis of log data files is disclosed. In some embodiments, the method includes pre-processing a log data file to generate a transformed log data file. The method further includes analyzing the transformed log data file to detect one or more of a plurality of anomalies in the transformed log data file; performing a predictive analysis for the one or more of the plurality of anomalies detected in the transformed log data file. The method further includes generating a report based on the predictive analysis performed for each of the one or more of the plurality of anomalies; receiving a feedback from an end-user based on the report generated for each of the one or more of the plurality of anomalies; and updating a database based on the feedback from the end-user for each of the one or more of the plurality of anomalies.
The invention relates to method and system for extracting and classifying manufacturing features from a three-dimensional (3D) model of a product. The method includes generating graph corresponding to product based on 3D model of product. The graph includes nodes corresponding to faces of the product and links corresponding to edges of product. The graph generation includes determining adjacency attribute matrix from the 3D model. The method further includes assigning scores to each of links; determining a cumulative score for each of links; extracting sub-graphs from graph by discarding one or more links from links; extracting node parameters and edge parameters from 3D model of product; determining node feature vector based on node parameters and edge feature vector based on edge parameters; and determining a type of manufacturing feature based on corresponding node feature vector and edge feature vector using a Graph Neural Network (GNN) model.
A method and system for evaluating performance of operation resources using Artificial Intelligence (AI) is disclosed. In some embodiments, the method includes receiving, each of a plurality of performance parameters associated with a set of operation resources. The method further includes determining a set of features for each of the plurality of performance parameters. The method further includes creating one or more feature vectors corresponding to each of the plurality of performance parameters. The one or more feature vectors are created based on a first pre-trained machine learning model. The method further includes assessing the one or more feature vectors, based on the first pre-trained machine learning model and classifying the set of operation resources into one of a set of performance categories based on the assessing of the one or more feature vectors. The method further includes evaluating performance of at least one of the set of operation resources.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
A method and system for providing profile-based data and visualization access through a semantic domain layer is disclosed. In some embodiments, the method includes receiving a user request to access data. The method further includes determining a user profile from a plurality of user profiles associated with the user. The method further includes extracting a first access level from a first set of access levels associated with the user profile. The method further includes mapping the user profile with a domain object from a plurality of domain objects, based on a second access level from the first set of access levels associated with the domain object. The method further includes selectively rendering at least a portion of the data requested in the user request to the user, in response to mapping the user profile with the domain object.
The invention relates to method and system for providing visual explanations for image analytics decisions. The method includes extracting a set of local features from each of a plurality of image instances using a deep learning (DL) model; determining a feature list by aggregating the set of local features from each of the plurality of image instances; generating a two-dimensional (2D) pixel map based on the feature list; superimposing the 2D pixel map of aggregated features on each of the plurality of image instances; and providing a visual explanation for an image analytics decision on one or more of the plurality of image instances based on superimposition.
G06V 10/22 - Prétraitement de l’image par la sélection d’une région spécifique contenant ou référençant une forme; Localisation ou traitement de régions spécifiques visant à guider la détection ou la reconnaissance
The invention relates to method and system for enhancing computer network security. The method includes receiving a plurality of requests from client devices to avail a plurality of responses from services running on servers; determining a URL pattern for each of the plurality of requests based on URL associated with that request; determining a request data signature for each of the plurality of requests or a response data signature for each of the plurality of responses based on a set of request parameters associated with that request or based on a set of response parameters associated with that response, respectively, using a first machine learning model; and determining an authenticity of each of the plurality of requests based on the URL pattern and the data signature associated with that request, or an authenticity of each of the plurality of responses based on the data signature associated with that response.
A staircase mobility system is disclosed. The system includes a docking assembly that is configured to dock or undock with a dockable seat assembly. The docking assembly includes support rods configured to engage or disengage with the dockable seat assembly when docked or undocked, respectively. Further, the docking assembly includes dock connecters are disposed along the support rods. The dock connecters are configured to communicatively connect or disconnect with the dockable seat assembly when docked or undocked, respectively. Further, the system includes a drive assembly coupled to the docking assembly. The drive assembly includes a motor that is configured to drive the docking assembly along a guide rail in a forward or reverse direction, and to operate the docking assembly to dock or undock with the dockable seat assembly.
B66B 9/08 - Genres ou types d'ascenseurs installés dans les bâtiments ou édifices ou adjoints à ceux-ci inclinés, p.ex. desservant des hauts fourneaux combinés à des escaliers, p.ex. pour transporter des personnes infirmes
28.
SYSTEM AND METHOD FOR RECORDING, ORGANIZING, AND TRACING EVENTS
A method and system for recording, organizing, and tracing events is disclosed. In some embodiments, the method includes obtaining real-time video data captured using a video capturing equipment. The real-time video data comprises a plurality of sequential image frames and audio data associated with each of a plurality of events. The method further includes extracting first timestamp data and first text data from each of the plurality of sequential image frames, extracting second timestamp data and second text data from the audio data, generating text data associated with each of the plurality of events based on the first timestamp data, the first text data, the second timestamp data, and the second text data, storing the generated text data for subsequent audit, and discarding the real-time video data associated with each of the plurality of events.
G06F 16/38 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/34 - Navigation; Visualisation à cet effet
G06F 40/40 - Traitement ou traduction du langage naturel
29.
METHOD AND SYSTEM FOR MANAGING ITEMS IN WAREHOUSES THROUGH DISTRIBUTED LEDGER
This disclosure relates to method and system for managing items in warehouses through distributed ledger. The method includes sending a request from a first warehouse to each of a plurality of warehouses to add an item to an Enterprise Resource Planning (ERP) system associated with each of the plurality of warehouses and to a distributed ledger. For each of the plurality of warehouses, the method further includes checking whether the item exists in an ERP system associated with a warehouse based on the metadata of the item within the request from the first warehouse. The method further includes receiving a response to the request from each of the plurality of warehouses based on the checking. The method further includes managing the item in the ERP system associated with each of the plurality of warehouses and the distributed ledger based on the response received from each of the plurality of warehouses.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
G06Q 10/08 - Logistique, p.ex. entreposage, chargement ou distribution; Gestion d’inventaires ou de stocks
G06F 16/215 - Amélioration de la qualité des données; Nettoyage des données, p.ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
30.
Aircraft passenger compliance monitoring system and method thereof
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.
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.
G05B 13/02 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
G05B 19/4097 - Commande numérique (CN), c.à d. machines fonctionnant automatiquement, en particulier machines-outils, p.ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'u caractérisée par l'utilisation de données de conception pour commander des machines à commande numérique [CN], p.ex. conception et fabrication assistées par ordinateur CFAO
32.
System and method for designing artificial intelligence (AI) based hierarchical multi-conversation system
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.
A method and system for evaluating performance of developers using Artificial Intelligence (AI) is disclosed. In some embodiments, the method includes receiving, each of a plurality of performance parameters associated with a set of developers. The method further includes creating one or more feature vectors corresponding to each of the plurality of performance parameters, based on one or more features determined for each of the plurality of performance parameters. The method further includes assessing the one or more feature vectors, based on the first pre-trained machine learning model. The method further includes classifying the set of developers into one of a set of performance categories based on the assessing of the one or more feature vectors. The method further includes evaluating the performance of at least one of the set of developers, based on an associated category in the set of performance categories, in response to the classifying.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
The disclosure relates to method and system recommending tuning of parameters to generate a data analytics model. The method includes identifying at a data pre-processing stage a pre-processing subset from an associated set of predefined pre-processing methods for a predefined objective. The method includes identifying at a feature selection stage a feature subset from an associated set of predefined feature selection methods for the predefined objective. The method includes identifying at a model training stage a training subset from an associated set of predefined model training methods for the predefined objective. The method further includes generating a plurality of data analytics tuples and selecting a data analytics tuple from the plurality of data analytics tuples. An output result of the data analytics tuple includes highest ranked results for the predefined objective.
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p.ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
35.
Method and system for determining collaboration between employees using artificial intelligence (AI)
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.
Method and system for identifying an empty region in a label and placing a content thereon is provided. The method includes processing an image of the label to extract label attribute and the content to retrieve content attribute. Label attribute includes at least one of dimensions of the label, at least one pre-existing content on the label, dimensions associated with pre-existing content, and location of pre-existing content on the label. The content attribute includes a type of content, dimensions of content, a preferred label location associated with content. The method further includes determining at least one empty region within the label, based on extracted label attribute and the retrieved content attribute. Each of the at least one empty region may be configured to accommodate the content. The method further includes inserting the content into one of the at least one empty region based on a predefined rule.
G06V 10/75 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexte; Sélection des dictionnaires
37.
METHOD AND SYSTEM FOR IDENTIFYING PERSONALLY IDENTIFIABLE INFORMATION (PII) THROUGH SECRET PATTERNS
This disclosure relates to method and system for identifying Personally Identifiable Information (PII) through secret patterns. The method includes receiving user data from at least one data source through a plurality of communication channels. The user data includes PII and non-PII. The user data is associated with a user. The PII includes a plurality of personal identifiers. The method further includes identifying the PII in user data through a predictive model. The method further includes generating a secret pattern based on the PII identified through the predictive model. The secret pattern is an identifiable label. The method further includes adding the secret pattern to each of the plurality of personal identifiers in PII. The method further includes identifying each of the plurality of personal identifiers through the secret pattern in real-time, when user data is transmitted from the at least one data source to at least one data destination.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
G06F 21/79 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du stockage de données dans les supports de stockage à semi-conducteurs, p.ex. les mémoires adressables directement
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
38.
Method and system for identifying common requirements from applications
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.
A half rate bang—bang phase detector for high-speed Analog Clock and Data Recovery (CDR) is disclosed. In some embodiments, the half rate bang—bang phase detector includes a first set of flip flops. Each of the first set of flip flops is configured to receive an input data sampled at each of a four phases of a Voltage Controlled Oscillator (VCO) clock. The half rate bang—bang phase detector includes a first set of logic gates configured to generate a set of four exclusive—OR (XOR) outputs. The half rate bang—bang phase detector includes a second set of flip flops configured to generate a set of clean XOR outputs. The half rate bang—bang phase detector includes a second set of logic gates configured to generate a set of final outputs based on the set of clean XOR outputs.
H03L 7/091 - Commande automatique de fréquence ou de phase; Synchronisation utilisant un signal de référence qui est appliqué à une boucle verrouillée en fréquence ou en phase - Détails de la boucle verrouillée en phase concernant principalement l'agencement de détection de phase ou de fréquence y compris le filtrage ou l'amplification de son signal de sortie le détecteur de phase ou de fréquence utilisant un dispositif d'échantillonnage
H03L 7/08 - Commande automatique de fréquence ou de phase; Synchronisation utilisant un signal de référence qui est appliqué à une boucle verrouillée en fréquence ou en phase - Détails de la boucle verrouillée en phase
H03K 19/21 - Circuits OU EXCLUSIF, c. à d. donnant un signal de sortie si un signal n'existe qu'à une seule entrée; Circuits à COÏNCIDENCES, c. à d. ne donnant un signal de sortie que si tous les signaux d'entrée sont identiques
H03L 7/099 - Commande automatique de fréquence ou de phase; Synchronisation utilisant un signal de référence qui est appliqué à une boucle verrouillée en fréquence ou en phase - Détails de la boucle verrouillée en phase concernant principalement l'oscillateur commandé de la boucle
H04L 7/00 - Dispositions pour synchroniser le récepteur avec l'émetteur
40.
System and method for automating software development life cycle
The invention relates to system and method for automating software development life cycle. In some embodiments, the method includes receiving a plurality of code snippets being utilized for developing a software application from a plurality of sources in a software development life cycle, generating a plurality of embedding vectors corresponding to the plurality of code snippets, and generating a high-level feature vector corresponding to each of the plurality of code snippets based on the corresponding embedding vector using a deep learning model. The method further includes generating a final merged code comprising a final sequence of code lines by combining the sequence of code lines corresponding to the plurality of code snippets using the deep learning model. The deep learning model is trained to generate the high-level feature vector and arrange the sequence of code lines based on historical data from the software development life cycle.
Disclosed is a method and system for classifying elements of a product. The method comprises identifying elements of the product. Thereupon, features of the one or more elements are determined, using a feature recognition technique. The features correspond to manufacturing operations required for manufacturing the elements, and include sheet metal operations, turn operations, injection moulding operations, and machining operations. The manufacturing operations are determined in a priority order with the sheet metal operation having a highest priority and the machining operation having a least priority.
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.
G06F 16/904 - Navigation; Visualisation à cet effet
G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/9035 - Filtrage basé sur des données supplémentaires, p.ex. sur des profils d'utilisateurs ou de groupes
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport utilisant des icônes
43.
METHOD AND SYSTEM FOR INTEGRATING FIELD PROGRAMMABLE ANALOG ARRAY WITH ARTIFICIAL INTELLIGENCE
A method and system for integrating Field Programmable Analog Array (FPAA) with Artificial Intelligence (AI) is disclosed. In some embodiments, the method includes automatically creating, by an AI model, a function by auto connecting a first set of computation elements from a plurality of computational elements in an FPAA, in response to receiving an input. The method further includes receiving a feedback comprising a first accuracy level associated with the output. The method further includes automatically adjusting at least one of a plurality of control parameters to modify the function to generate an adjusted output corresponding to the input, based on the first accuracy level associated with the output.
G06F 7/57 - Unités arithmétiques et logiques [UAL], c. à d. dispositions ou dispositifs pour accomplir plusieurs des opérations couvertes par les groupes ou pour accomplir des opérations logiques
G06F 30/367 - Vérification de la conception, p.ex. par simulation, programme de simulation avec emphase de circuit intégré [SPICE], méthodes directes ou de relaxation
44.
System and method for managing an insect swarm using drones
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.
A01M 5/00 - Capture des insectes dans les champs, jardins ou forêts, au moyen d'appareillages mobiles
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
G05D 1/10 - Commande de la position ou du cap dans les trois dimensions simultanément
A01M 29/16 - CAPTURE OU PIÉGEAGE DES ANIMAUX OU ÉPOUVANTAILS; APPAREILS DE DESTRUCTION D'ANIMAUX OU DE PLANTES NUISIBLES Épouvantails ou dispositifs répulsifs, p.ex. pour oiseaux utilisant des ondes sonores
G05D 1/12 - Commande pour la recherche d'un objectif
B64U 101/00 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques
Disclosed is a method and system for processing skewed datasets. The processor 202 is configured to capture a broadcast size of non-skewed datasets to be loaded onto a memory associated with one or more nodes in a distributed system. The skewed dataset is identified from two or more datasets to be joined. Each of the non-skewed dataset is divided into a plurality of non-skewed data chunks at the node and each of the non-skewed data chunk is broadcasted to one or more nodes having the skewed dataset. The joining operation is then performed between each of the skewed dataset and the non-skewed data chunk till all the non-skewed data chunks are consumed in the join operation. Resultant joined dataset is then collected as a single joined dataset from the nodes involved in the joining operation.
A food processing device configured to process a food product stored in a pod is disclosed. The food processing device may further include a drive assembly. The drive assembly may include a drive motor configured to move linearly in the vertical direction, and a linear actuator coupled to the drive motor. The linear actuator may cause the drive motor to move linearly in the vertical direction. The drive assembly may further include a drive shaft coupled to the drive motor. The drive shaft may be configured to engage or disengage with the top shaft of the pod owing to the linear movement of the drive motor in vertical direction. Upon engaging with the tops shaft of the pod, the drive shaft may be further configured to impart rotary motion to the top shaft.
A47J 31/44 - Eléments ou parties constitutives des appareils à préparer des boissons
A47J 31/40 - Appareils à préparer des boissons avec des moyens de distribution pour ajouter une quantité mesurée d'ingrédients, p.ex. du café, de l'eau, du sucre, du cacao, du lait, du thé
A47J 31/46 - Becs verseurs, pompes, soupapes de vidange ou dispositifs analogues pour le transport de liquides
A47J 31/52 - Mécanismes commandés par un réveil-matin pour les appareils à préparer le café ou le thé
A47J 31/56 - Bouilloires à commande de la température
A47J 43/044 - Machines de ménage non prévues ailleurs, p.ex. pour moudre, mélanger, agiter, pétrir, émulsionner, fouetter ou battre les aliments, p.ex. actionnées par moteur à outils actionnés du côté du haut
A device, system, and method for creating air capsules enclosing passengers in vehicles is disclosed. The device for creating air capsules enclosing passengers in vehicles includes an attachment portion. The attachment portion is removably attached to a gasper within a vehicle and receives airflow from an outlet port of the gasper. The device further includes a diffuser portion integrated with the attachment portion. The diffuser portion is configured to intake the airflow from the attachment portion. Further, the diffuser portion includes a flow control portion configured to generate at least one airflow stream from the airflow. A first airflow stream of the at least one airflow stream creates an air capsule configured to enclose a passenger in the vehicle.
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.
G06F 16/20 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet de données structurées, p.ex. de données relationnelles
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
G06F 16/21 - Conception, administration ou maintenance des bases de données
49.
SYSTEM AND METHOD FOR PROVIDING VISUAL GUIDANCE IN A MEDICAL SURGERY
Disclosed is a method for providing visual guidance in a medical surgery. The method comprises registering, within a virtual assistance device having a combination of a virtual medical implant, an Intra-Medullary (IM) nail model and a virtual insertion handle model, each of a physical IM nail implant and a physical insertion handle. Further, a physical drill gun is registered within the virtual assistance device having a drill gun model. Further, coordinates of the one or more holes on the physical IM nail implant are registered within the virtual assistance device. The physical IM nail is inserted into a target. The virtual impression of the physical drill gun is aligned over the one or more holes based on the coordinates. Further, one or more surgical steps are performed by the physical drill gun based on the aligning.
A61B 34/20 - Systèmes de navigation chirurgicale; Dispositifs pour le suivi ou le guidage d'instruments chirurgicaux, p.ex. pour la stéréotaxie sans cadre
A61B 34/00 - Chirurgie assistée par ordinateur; Manipulateurs ou robots spécialement adaptés à l’utilisation en chirurgie
A61B 34/10 - Planification, simulation ou modélisation assistées par ordinateur d’opérations chirurgicales
A61B 90/90 - Moyens d’identification pour les patients ou les instruments, p.ex. étiquettes
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
Disclosed is a sterile cover (100) for a Mixed Reality (MR) device (101). The sterile cover (100) may comprise a first case (102) arranged for covering a front side of the MR device (101). The first case (102) may comprise a hard case with an embedded clear layer (114) for covering a glass area of the front side of the MR device (101). The sterile cover (100) may further comprise a second case (104). The second case (104) may be arranged for covering a headband side of the MR device (101). The second case (104) may comprise a stretchable case for allowing a flexible adjustment of the headband side of the MR device (101) within the second case (104).
A61B 90/00 - Instruments, outillage ou accessoires spécialement adaptés à la chirurgie ou au diagnostic non couverts par l'un des groupes , p.ex. pour le traitement de la luxation ou pour la protection de bords de blessures
A61B 90/50 - Supports pour instruments chirurgicaux, p.ex. bras articulés
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.
G06F 18/40 - Dispositions logicielles spécialement adaptées à la reconnaissance des formes, p.ex. interfaces utilisateur ou boîtes à outils à cet effet
G06V 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06F 18/213 - Extraction de caractéristiques, p.ex. en transformant l'espace des caractéristiques; Synthétisations; Mappages, p.ex. procédés de sous-espace
A Convolution Multiply and Accumulate-Xtended (CMAC-X) system (102) for performing a convolution operation with functional safety mechanism is disclosed. The CMAC-X system (102) receives image data pertaining to an image. The image data comprises a set of feature matrix, a kernel size and depth information. Further, the CMAC-X system (102) generates a convoluted data based on convolution operation for each feature matrix, The CMAC-X system (102) performs an accumulation of the convoluted data to generate accumulated data, when the convolution operation for each feature matrix is performed. The CMAC-X system (102) further performs an addition of a predefined value to the accumulated data to generate added data. Further, the CMAC-X system (102) filters the added data. Further, the CMAC-X system (102) comprises a functional safety unit to verify a functionality of the CMAC-X system (102), thereby performing the convolution operation of the image with functional safety mechanism.
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.
The invention relates to method and system for generating a Bill of Materials (BOM) for a product. In some embodiments, the method includes acquiring information associated with a component of the product using communicatively connected information recording instruments. The information may include measurement parameters recorded using communicatively connected measuring instruments. The method further includes automatically populating a set of data fields from among a plurality of data fields in a graphic user interface (GUI) based on the acquired information and a shape of the component, receiving a validation command from the user via the GUI, and storing the plurality of data fields as one of a plurality of records in a BOM database for the product upon receiving the validation command. The shape of the component may be selected by a user from a list of pre-defined shapes or may be identified based on an image of the component.
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.
G06N 3/063 - Réalisation physique, c. à d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone utilisant des moyens électroniques
G06V 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06F 18/213 - Extraction de caractéristiques, p.ex. en transformant l'espace des caractéristiques; Synthétisations; Mappages, p.ex. procédés de sous-espace
56.
Method and system for managing user access to multimedia content for online conferences using metadata
A method and system for managing user access to a multimedia content for an online conference using metadata is disclosed. In some embodiments, the method includes identifying a plurality of contexts for each of a plurality of conference data streams extracted from the multimedia content. The method further includes generating a plurality of metadata types based on the plurality of contexts associated with each of the plurality of conference data streams, providing a plurality of options corresponding to the plurality of metadata types to a user for accessing a section of interest in the plurality of conference data streams, receiving at least one selected option from the plurality of options by the user and validating the user access to one or more of the plurality of conference data streams based on the at least one selected option and access rights associated with the user.
H04L 65/402 - Prise en charge des services ou des applications dans laquelle les services impliquent une session principale en temps réel et une ou plusieurs sessions parallèles additionnelles non-temps-réel, p.ex. le téléchargement d’un fichier lors d’une session FTP parallèle, l’introduction d’un courriel ou d
G06F 16/48 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
H04L 65/4053 - Dispositions pour la communication multipartite, p.ex. pour les conférences sans commande de la prise de parole
H04L 65/1089 - Procédures en session en supprimant des médias
57.
Decomposing a monolithic application into one or more micro services
The present disclosure relates to system(s) and method(s) for decomposing a monolithic application into one or more micro services. The method identifies a subset of functionalities, from a set of functionalities associated with the monolithic application. The method further determines a number of micro services based on a functionality priority, a functionality complexity score, and a functionality predefined complexity score associated with each functionality. Further, the method generates one or more groups of methods from a plurality of methods associated with the subset of functionalities. Further, the method decomposes the monolithic application into the one or more micro services based on the one or more groups of methods, and the number of micro services.
Disclosed is a method and system for generating test scripts. The method comprises receiving at least one of a video and/or an audio captured during manual testing of a Device Under Test (DUT) comprising an output unit or a Graphical User Interface (GUI) based application. At least one of the video and/or the audio is processed for generating a test script for the DUT or the GUI based application. Generation of the test script may include allowing a user to pause at least one of the video and/or the audio at a particular time frame. Using a script generator user interface, input events corresponding to the particular time frame are received. A type of validation is selected for the output unit of the DUT or the GUI based application, and inputs are provided for the validation. The validation is device specific and performed using during runtime test execution.
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.
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.
G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
61.
SYSTEM AND METHOD FOR GENERATING AN OMNI-CHANNEL SUPPORT PLATFORM
The present disclosure relates to system(s) and method(s) for generating an Omni-channel support platform. The method comprises integrating a multi-channel support system with a blockchain framework. Further, the method comprises generating an Omni-channel support platform based on the integration. The Omni-channel support platform comprises an Omni-channel support block for a user from a set of users. The Omni-channel support block comprises a support ledger and a support smart contract for the user. The Omni-channel support block further comprises capturing transaction data associated with the user from the multiple support channels. Further, the Omni-channel support block comprises recommending one or more resolutions to each user upon based on a support request.
H04L 9/06 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p.ex. système DES
G06Q 20/12 - Architectures de paiement spécialement adaptées aux systèmes de commerce électronique
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.
Disclosed is a system (102) for determining a location of an explosive device. The system (102) detects an explosive device using one or more devices (204) based on one or more nano-explosive detection sensors (206) associated with the one or more devices (204). The system (102) further identifies a type, a quantity and a signal strength associated with the explosive device. The system (102) computes a distance between the explosive device and the one or more devices (204). The system (102) determines explosive device co-ordinates based on the computed distance and device co-ordinates associated with each device (204). The system (102) receives a data packet comprising data associated with the explosive device from the one or more devices (204). The system (102) determines a location of the explosive device based on an analysis of the data packet received from the one or more devices (204).
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.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
G06Q 30/0202 - Prédictions ou prévisions du marché pour les activités commerciales
The present disclosure relates to a system (102) for assigning dynamic operation of devices in a communication network (106). The system (102) receives one or more behavioral attributes and one or more contextual attributes associated with one or more devices (232) in a communication network (106). The system (102) further determines one or more clusters (234) associated with each device from the one or more devices (232). The system (102) further determines, dynamically, one or more network slices, from a set of network slices associated with the one or more clusters (234). The system (102) further determines, dynamically, one or more analytics models associated with the one or more clusters (234). The system (102) further assigns dynamic operation of the one or more clusters (234) based on the one or more contextual attributes, the one or more network slices and the one or more analytics models.
Disclosed is a system for providing an inference associated with delays in processing input data packet(s) by a Design Under Verification (DUV)/System Under Verification (SUV) characterized by maintaining timing information of the input data packet(s) is disclosed. To provide an inference, initially, an input data packet is processed by a DUV or SUV. Simultaneously, an expected data packet corresponding to the input data packet is predicted and a Unique Identifier is assigned to the expected data packet corresponding to the input data packet that entered into the DUV/SUV. After assigning the Unique Identifier, the plurality of data fields pertaining to the Unique Identifier are populated in an array of Packet Timing Entries based on a Delay Identifier (ID) and a Delay Mode. The plurality of data fields may then be used for reporting various delay statistics and operational behaviour of DUV/SUV.
The present disclosure relates to system(s) and method(s) for generating a version associated with a section in a document. The system receives user inputs corresponding to line boundaries associated with the document. Based on the user inputs, the system generates a set of sections and a set of section tags associated with the set of sections. The system further generates one or more versions associated with each section tag when the section associated with the section tag is modified. Upon generation of the one or more versions, the system may store the one or more versions independent of the document.
G06F 16/38 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
Disclosed method for generating synthetic data for minority classes in a very large dataset comprises grouping samples stored on several devices, into different groups. A pivot is identified to be used as a reference for grouping the samples into bins. The samples are assigned to a bin, based on a closest pivot. The samples are regrouped into different groups, based on identities of the bins, and each of the groups is distributed to the several devices. Samples belonging to majority class and minority classes for which synthetic data is not being generated are removed from each of the different groups. Samples of each of these groups are arranged in different M-Trees to facilitate identification of K-nearest neighbours for each sample within each of the different groups to generate K pairs of nearest neighbours. Finally, synthetic samples are generated for the K pairs of nearest neighbours by creating random samples.
G06F 17/00 - TRAITEMENT ÉLECTRIQUE DE DONNÉES NUMÉRIQUES Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
G06F 16/22 - Indexation; Structures de données à cet effet; Structures de stockage
69.
System and method to perform control testing to mitigate risks in an organization
The present disclosure relates to system(s) and method(s) to perform control testing to mitigate risks in an organization. The system may extract sentences from control documents, and may classify the sentences into one of questions and non-questions, based on at least one of active learning and pro-active learning. Interpretations of the questions may thereafter be generated. Relevant documents related to each of the interpretations of the questions may be identified and extracted, from repositories. Artificial Intelligence (AI) may be used to identify the relevant documents. A cognitive master may be implemented to organize meetings between control testers and process owners for discussing over effectiveness of design and implementation test of test plans to mitigate the risks.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
Disclosed is a system for generating Clinical trial protocol design document with selection of a Patient and an Investigator for a clinical trial process. The system inputs meaningful information derived from the raw data, a pre-Drafted protocol, a regulatory authorities' protocol curated by regulatory authorities, and a pre-stored dataset, present in a repository. A Clinical trial protocol design document is drafted by generating a case frame upon extracting data in form of a key value into a standard document. Each key value is validated and a prediction score is computed based on overlapping of the interim Clinical trial protocol design template with the pre-Drafted protocol and the regulatory authorities' protocol to determine whether the interim Clinical trial protocol design document is approved or rejected. A Clinical trial protocol design document is generated when the interim Clinical trial protocol design document is approved.
G16H 10/20 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des essais ou des questionnaires cliniques électroniques
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
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.
G06F 11/07 - Réaction à l'apparition d'un défaut, p.ex. tolérance de certains défauts
G01C 23/00 - Instruments combinés indiquant plus d’une valeur de navigation, p.ex. pour l’aviation; Dispositifs de mesure combinés pour mesurer plusieurs variables du mouvement, p.ex. la distance, la vitesse ou l’accélération
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.
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06F 11/07 - Réaction à l'apparition d'un défaut, p.ex. tolérance de certains défauts
H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité
73.
SYSTEM AND METHOD FOR GENERATING A PREDICTIVE MODEL
The present disclosure relates to a system(s) and method(s) for generating a predictive model, the method comprises receiving data and extracting one or more predicator features from the data based on a feature selection methodology. In one example, the feature selection methodology comprises computing a degree connectedness for each of the plurality of features using a modified mutual information technique and a Pearson co-efficient and identifying the one or more predicator features on a comparison of degree of connectedness and a predefined threshold. Further, the method comprises identifying a data type associated with the data, and generating a predictive model to be applied on the data based on the data type and the one or more predicator features.
Disclosed is a system for allowing secure access to a microservice. An Application Programming Interface (API) gateway receives a request comprising a Uniform Resource Locator (URL) associated to the microservice. A set of input parameters indicating information about the user device and the microservice is identified from the URL. The system performs validation of input parameters, extraction of request patterns, tracking of IP address, and detection of user credentials to provide output parameters. A decision tree comprising rules is generated by using a supervised machine learning technique on the output parameters. Further, the API gateway creates a stateless identity token to encrypt the request. The stateless identity token is created based on the user credentials and at least one rule applicable to the request. Once the stateless identity token is created, the stateless identity token is verified to allow the secure access to the microservice.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06N 5/02 - Représentation de la connaissance; Représentation symbolique
Disclosed is a system for profiling one or more nodes based on a hybrid Key Performance Indicator (KPI). Initially, a flag indicating an issue with a KPI is received. A set of Performance Management (PM) counters undergoing periodic changes in performance beyond a predefined threshold by using machine learning based statistical techniques is identified. The set of PM counters may comprise a set event based of PM counters and a set of protocol based PM counters. A hybrid KPI is created based on combination of the set event based of PM counters and the set of protocol based PM counters. One or more nodes are profiled by comparing the hybrid KPI associated to the node with hybrid KPI corresponding to each of the one or more nodes.
Disclosed is a system for profiling one or more nodes based on a hybrid Key Performance Indicator (KPI). Initially, a flag indicating an issue with a KPI is received. A set of Configuration Management (CM) may be changed or identified by SME. Deviation in magnitude of each CM parameters from a predefined CM magnitude is computed to determine a changed CM parameter with deviation magnitude higher than deviation magnitude of remaining CM parameters. A set of Performance Management (PM) counters is identified by comparing magnitude of each PM with a predefined threshold value or using machine learning or statistical techniques. A hybrid KPI is created based on combination of the changed CM parameters and a subset of PM counters. One or more nodes are profiled by comparing the hybrid KPI associated to the node with hybrid KPI corresponding to each of the one or more nodes.
Disclosed is a reconfigurable convolution engine for performing a convolution operation on an image. A data receiving module receives image data. A determination module determines a kernel size based on the image data, clock speed associated to the convolution engine and number of available on-chip resources. An allocation module allocates a plurality of instances based on the kernel size. Each instance of the plurality of instances further comprises a set of computing blocks operating concurrently. Each computing block is configured to perform convolution operation on the feature map of the image. An aggregation module aggregates the convolution output of each computing block for each instance of the plurality of instances to produce a convolution result for the image.
Disclosed is a convolution operator system for performing a convolution operation concurrently on an image. An input router receives image data. A controller allocates image data to a set of computing blocks based on the size of the image data and number of available computing 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.
G06V 10/75 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexte; Sélection des dictionnaires
79.
System and method for performing a convolution operation
A Convolution Multiply and Accumulate (CMAC) system for performing a convolution operation is disclosed. The CMAC system receives image data pertaining to an image. The image data comprises a set of feature matrix, a kernel size and depth information. Further, the CMAC system generates a convoluted data based on convolution operation for each feature matrix. The CMAC system performs an accumulation of the convoluted data to generate accumulated data, when the convolution operation for each feature matrix is performed. The CMAC system further performs an addition of a predefined value to the accumulated data to generate added data. Further, the CMAC system filters the added data to provide a convolution result for the image, thereby performing the convolution operation of the image.
The present disclosure relates to system(s) and method(s) for predicting a Key Performance Indicator (KPI) in a telecommunication network is illustrated. The system is configured to monitor a set of counters and a Key Performance Indicator corresponding to a telecommunication network. The set of counters and the Key Performance Indicator (KPI) are monitored for a predefined time interval to gather sample data. The system is configured to analyze the sample data using a data analysis technique in order to identify a subset of counters, from the set of counters, influencing the KPI and a correlation coefficient associated with each counter from the subset of counters, wherein the correlation coefficient associated with each counter is identified after normalizing the subset of counters. The system is configured to apply regression on the subset of counters and the KPI in order to build a correlation equation between the subset of counters and the KPI.
The embodiments herein relate to operational data analysis (ODA) and, more particularly to automate operational data analysis and generate the analysis report for various products using a web-based multi-tenant product intelligence framework. The system allows the user to configure a data collection process, define schema structure, select a data storage for storing the collected data, select or create a data formatting algorithm, and generate a data report to perform the ODA process. Based on the ODA report, appropriate decisions can be taken by an organization.
G06F 16/30 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet de données textuelles non structurées
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06N 5/04 - Modèles d’inférence ou de raisonnement
A system for facilitating authentication of a user based on a polygonal image includes a registration module registering a user by selecting a password artifact comprising a first polygon and a first image from a set of images. The first polygon includes a plurality of grids. The registration module slices the first image to derive a set of sub first images based on the grids and derives a first image pattern by aligning a sub image on each of the grids in accordance with a preference defined by the user. The authentication module authenticates the user by displaying a plurality of password artifacts comprising a plurality of polygons and a plurality of images and derives a second image pattern upon aligning a sub image of a set of sub second images, created by slicing a second image, on each of a plurality of grids associated to the second polygon.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06F 21/36 - Authentification de l’utilisateur par représentation graphique ou iconique
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
83.
System and method for managing content using generic content management interface
A system and method for providing a unified solution to transmit data from one or more devices/OEMs to one or more storage providers. The system analyzes the metadata of a device, which is sending the request, and identifies an appropriate storage provider for storing the data. Further, the system can convert device specific data format and an API set used for transmitting the data to a storage specific data format and a generic API set. The generic API set can be used to transmit data to one or more storage providers. Additionally, the system supports an extendable interface to initiate a request from the device.
The present disclosure relates to system(s) and method(s) for multi-level amplitude modulation and demodulation. The system accepts a frame delimiter signal, when a comparator is triggered upon receiving the frame delimiter signal from a transmitter. Further, the system receives modulated data associated with a data frame from the transmitter. In one aspect, the modulated data may be generated by modulation of the data frame using a set of three amplitude levels. Upon receiving the modulated data, the system demodulates the modulated data to retrieve the data frame along with the frame delimiter signal, which can be used for successive digital logic elements for enhanced performance.
H04L 27/04 - Circuits de modulation; Circuits émetteurs
H04L 25/49 - Circuits d'émission; Circuits de réception à au moins trois niveaux d'amplitude
H04L 7/033 - Commande de vitesse ou de phase au moyen des signaux de code reçus, les signaux ne contenant aucune information de synchronisation particulière en utilisant les transitions du signal reçu pour commander la phase de moyens générateurs du signal de synchronisation, p.ex. en utilisant une boucle verrouillée en phase
H04L 27/06 - Circuits de démodulation; Circuits récepteurs
Disclosed is a system for removing bugs present in a software code. A determination module determines a usage pattern of a software code by using an Artificial Neural Network (ANN) technique. A comparison module compares the usage pattern with a set of pre-stored usage patterns of software applications similar to the software code. An execution module executes a set of test suites, on the software code, associated to at least one software application of the software applications, when a usage pattern of the at least one software application is matched with the usage pattern of the software code. An identification module identifies a code snippet comprising the bug. A recommendation module recommends a code patch, corresponding to the code snippet, from a ranked list of code patches determined by a Deep RNN technique. Further, a replacement module replaces the code snippet with the code patch thereby removing the bug.
The present disclosure relates to system(s) and method(s) for assisting a user to resolve a hardware issue and a software issue. The system identifies, a target cluster, associated with a new ticket received from the user, from the set of clusters. Further, the system recommends one or more runbook scripts, from a runbook repository, associated with the new ticket. The system further identifies a new runbook script, corresponding to the new ticket, from a set of external repositories. Further, the system executes at least one of the one or more runbook scripts or the new runbook script, associated with the new ticket. The system further generates a document based on the execution of the one or more runbook scripts or the new runbook script, thereby assisting the user to resolve a target issue.
G06F 11/22 - Détection ou localisation du matériel d'ordinateur défectueux en effectuant des tests pendant les opérations d'attente ou pendant les temps morts, p.ex. essais de mise en route
Disclosed is a system for facilitating reusability of a code snippet during development of a software application. Initially, a plurality of tokens is extracted, by using an Artificial Intelligence (AI) based syntactic analysis, from a sequence of lines of code entered by a developer. Further, each token of the plurality of tokens is converted into a vector by using a neural word embedding technique. Subsequently, a context of the plurality of tokens is determined by using a deep autoencoder neural network technique. Furthermore, at least one code snippet is recommended from a plurality of code snippets corresponding to the context. To do so, the context is compared with a plurality of contexts by using a Deep Recurrent Neural Network (Deep RNN) technique. Upon comparison, a confidence score is computed for each code snippet. Finally, the at least one code snippet is selected based on the confidence score.
A reconfigurable convolution engine for performing a convolution operation on an image is disclosed. A data receiving module receives image data. A determination module determines a kernel size based on the image data, clock speed associated to the convolution engine and available on-chip resources. A generation module generates a plurality of instances based on the kernel size. A configuration module configures an adder engine comprising a plurality of adders configured to operate in a pipelined structure and in parallel with the plurality of instances. An execution module executes the convolution operation on each of the plurality of instances and the adder engine. A filtering module filters an output of the convolution operation by using a filter function configured to operate on a predefined threshold function.
G06F 17/17 - Opérations mathématiques complexes Évaluation de fonctions par des procédés d'approximation, p.ex. par interpolation ou extrapolation, par lissage ou par le procédé des moindres carrés
The present disclosure relates to system(s) and method(s) for generating a score for a runbook or a script. The system receives a ticket and a ticket description. The system further identifies a set of policies based on an analysis of historical data, the ticket and the ticket description. Further, the system determines a set of functions based on an analysis of the set of policies using a neural network technique and an Inverse Reinforcement Learning technique. Furthermore, the system recommends a runbook or a script based on the set of functions, the ticket and the ticket description. The runbook or the script is further executed to resolve the ticket. Based on the execution, the system records a script success or a script failure. The system further generates a score for the runbook or the script based on the script success or the script failure.
The present disclosure relates to system(s) and method(s) for generating a controlled static electricity in a propensity medium. The system receives an input signal indicating a target static electricity to be generated in the propensity medium, and a DC voltage from a power source. Furthermore, the system converts the DC voltage into an AC voltage. Furthermore, the system multiplies the AC voltage using a voltage multiplier to generate a static electricity. The voltage multiplier comprises a plurality of a set of capacitors and diodes. The system further measures the static electricity. Further, the system compares the static electricity and the target static electricity. Based on the comparison, the system configures the voltage multiplier by modifying at least one set of capacitors and diodes. Further, the system generates the controlled static electricity in the propensity medium based on the configuration of the voltage multiplier.
H02N 13/00 - Embrayages ou dispositifs de maintien utilisant l'attraction électrostatique, p.ex. utilisant l'effet Johnson-Rahbek
G01D 15/28 - Moyens de maintien pour surfaces d'enregistrement; Moyens de guidage pour surfaces d'enregistrement; Moyens d'échange pour surfaces d'enregistrement
91.
System and method for automatically summarizing documents pertaining to a predefined domain
Disclosed is a system for automatically summarizing documents pertaining to a predefined domain. A document finder module enables a web crawler to crawl web resources in order to find a plurality of documents. A keyword determination module determines a set of keywords from the plurality of documents and a rank associated to each keyword of the set of keywords. A clustering module clusters the plurality of documents into one or more clusters. A score computation module identifies a subset of the set of keywords for each cluster upon computing a similarity score, corresponding to each keyword, for each cluster. A summary generation module generates a summary for each cluster based on presence of one or more keywords, of the subset, in each document classified in the cluster.
Disclosed is a system and method for automatically diagnosing an error by performing failure analysis of functional simulation pertaining to a Design Under Verification (DUV) or System Under Verification (SUV). A prediction unit generates a set of expected output packets upon processing a set of input packets' copy. A comparison unit compares an actual output packet, from the set of actual output packets, with an expected output packet, from the set of expected output packets, corresponding to the actual output packet. When there is a mismatch, the actual output packet is compared with at least one subsequent expected output packet until the match is found. The diagnosing unit automatically diagnoses at least one of a packet drop error, an ordering error, an error in routing, by performing a systematic failure analysis and reports a diagnostic information and/or default diagnostic information associated with the error.
G06F 30/3323 - Vérification de la conception, p.ex. simulation fonctionnelle ou vérification du modèle utilisant des méthodes formelles, p.ex. vérification de l’équivalence ou vérification des propriétés
Disclosed is a system for performing User Interface (UI) verification of a Device Under Test (DUT). Before performing the UI verification, a set of corner markers is positioned at corners of a display frame associated to the DUT. Once the set of corner markers are positioned, an image receiving module receives a DUT image, captured by an image capturing unit, of the UI pertaining to a DUT. A skew correction module for correcting orientation of the DUT image by determining an orientation correction factor. A file configuration module for storing the orientation correction factor in a pre-configuration file when the DUT image is occupying the content greater than the predefined threshold percentage. In one aspect, the orientation correction factor may be referred while testing a UI of the DUT.
The present disclosure relates to system(s) and method(s) for generating a functional simulation's progress report simultaneously when the simulation is in progress. The system comprises a testbench and a DUV/SUV connected to the testbench. The testbench generates a set of input data/packets in order to simulate and verify the DUV/SUV. The system is configured to identify one or more components, from a set of components in the testbench. Furthermore, the system receives one or more current progress messages from the one or more components and identifies one or more component Lock-Up conditions based on the processing of the one or more current progress messages and one or more previous progress messages. Further, the system executes one or more actions to resolve the one or more component Lock-Up conditions. Furthermore, the system generates a simulation progress report, simultaneously at runtime, during the simulation.
G06F 30/3323 - Vérification de la conception, p.ex. simulation fonctionnelle ou vérification du modèle utilisant des méthodes formelles, p.ex. vérification de l’équivalence ou vérification des propriétés
G06F 111/20 - CAO de configuration, p.ex. conception par assemblage ou positionnement de modules sélectionnés à partir de bibliothèques de modules préconçus
95.
System and method for delegating access of sensitive information
Disclosed is a system for delegating access of sensitive information by a user device to a requestor device through a central server. A receiving module receives a first token Identification (ID) generated by the user device in an offline mode and a request, comprising a second token ID, from the requestor device. A validation module validates the request by comparing the first token ID and the second token ID. An identification module identifies a subset of the sensitive information based on a profile of the requestor, when the first token ID is matched with the second token ID. A watermarking module watermarks the subset of the sensitive information with a set of variables to generate watermarked sensitive information. Upon generating the watermarked sensitive information, the access delegation module delegates the access of the watermarked sensitive information to the requestor device.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06F 21/33 - Authentification de l’utilisateur par certificats
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
The present disclosure relates to system(s) and method(s) for interactively controlling the course of a functional simulation of DUV/SUV. The system comprises a testbench and the DUV/SUV connected to the testbench. The testbench generates a set of input data/packets as a stimulus to be processed by the DUV/SUV. The set of input data/packets is generated to simulate and verify the DUV/SUV. Further, the testbench identifies a pre-defined event at runtime during the simulation. Upon identification of the event, the testbench is configured to pause the simulation and transmit a notification message to a user indicating the occurrence of the event. Further, the testbench waits for a pre-defined time interval to receive one or more user inputs. The testbench further generates new stimulus based on the one or more user inputs and resumes the paused simulation with the new stimulus, thereby controlling the course of the functional simulation.
The present disclosure relates to system(s) and method(s) for deploying a data analytics model in a target environment. The system records a set of data pre-processing stages, associated with the data analytics model. The set of data pre-processing stages may comprise receiving raw data, executing a set of ETL functions on the raw data, and executing a set of algorithms on the raw data. Further, the system generates the data analytics model based on the set of algorithms. Furthermore, the system generates a scoring engine workflow, associated with the data analytics model, based on the set of data pre-processing stages. The scoring engine workflow comprises one or more ETL functions and one or more algorithms. Further, the system deploys the data analytics model and the scoring engine workflow in the target environment. The scoring engine workflow enables pre-processing of production data in the target environment.
An embodiment of the invention may include a method, computer program product, and system for detecting email messages sent from an automated mailing system. The embodiment may include analyzing email metadata of a user to detect an indication of automation. The embodiment may include identifying any email messages sent corresponding to the pattern of automation. The embodiment may include performing an action in response to the identified email messages.
H04L 51/42 - Aspects liés aux boîtes aux lettres, p.ex. synchronisation des boîtes aux lettres
H04L 51/00 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p.ex. courriel
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p.ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p.ex. des réponses automatiques ou des messages générés par un agent conversationnel
G06F 16/335 - Filtrage basé sur des données supplémentaires, p.ex. sur des profils d’utilisateurs ou de groupes
99.
Rule based IPv4 to IPv6 migration assisting framework
A method and system for rule based Internet Protocol version 4 (IPv4) to Internet Protocol version 6 (IPv6) migration assisting framework is disclosed. The method provides guidance and assistance for migrating a product, a system or the like to IPv6. The method views across the complete development life cycle, not restricting only to the impacted code base of the system artifacts. The method scans the system artifacts for IPv4 dependency detection and then provides IPv4 Dependency Removal Effort Estimation (IDRE). The IPv4 dependency detection is based on predefined Meta-rules constructed with respect to the context of product. The IDRE combines Analysis Effort (AE) and Project Execution Effort (PEE) to provide a user and/or the organization order of magnitude estimate based on the assessment of IPv4 dependencies, level of coupling with IPv4 dependencies against different parts of the system artifacts.
Disclosed is a system for debugging the network environment under regression testing. Initially, a data receiving module receives data pertaining to the network environment. An extraction module extracts a plurality of features by using a parser. An identification module identifies an error as a Problem Report (PR) or a False Failure (FF) based on classification of a test case execution log and a similarity confidence. The test case execution log may be classified based on comparison of a predefined pattern with an error pattern of the test case execution log. A generation module may generate second test case based on the plurality of features, a predefined set of instructions and the error pattern associated with the test case execution log by using a K-means and a Nearest Neighbour algorithm. A debugging module debugs the network environment based on execution of a test case.
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