Abstract: This disclosure relates generally to data processing, and more particularly, to methods and systems for determining an equipment operation based on historical data. In one embodiment, a hardware processor-implemented method for facilitating an operation of a device is provided. The method comprises: receiving an indication of an operation problem for a first device; acquiring historical operation data of a plurality of devices including the first device, the historical operation data including structured data and unstructured data; determining at least a list of first entities and a list of second entities based on the structured data; determining a set of entity associations, each entity association including at least one of the first entities and at least one of the second entities; determining one or more relationships between each of the entity associations; and determining, based on the one or more determined relationships, an operation solution to solve the operation problem.

Abstract: A method and a system are provided for facilitating operation of an electronic device. The method comprises receiving a semi-structured dataset comprising one or more entities, wherein the semi-structured dataset corresponds to at least an indication of an operation problem associated with an electronic device. The method comprises extracting one or more unique classes associated with one or more entities from the semi-structured dataset. The method comprises creating one or more n-grams representative of a relationship between the one or more entities and the one or more unique classes. The method comprises generating a hypothesis associated with the one or more entities based on a first set of entities from the one or more entities using one or more n-grams, wherein the generated hypothesis corresponds to an operation solution to solve the operation problem associated with the electronic device.

Abstract: A method and a system are provided for facilitating operation of an electronic device. The method comprises receiving a semi-structured dataset comprising one or more entities, wherein the semi-structured dataset corresponds to at least an indication of an operation problem associated with an electronic device. The method comprises extracting one or more unique classes associated with one or more entities from the semi-structured dataset. The method comprises creating one or more n-grams representative of a relationship between the one or more entities and the one or more unique classes. The method comprises generating a hypothesis associated with the one or more entities based on a first set of entities from the one or more entities using one or more n-grams, wherein the generated hypothesis corresponds to an operation solution to solve the operation problem associated with the electronic device.

Abstract: This disclosure relates generally to data processing, and more particularly, to methods and systems for determining an equipment operation based on historical data. In one embodiment, a hardware processor-implemented method for facilitating an operation of a device is provided. The method comprises: receiving an indication of an operation problem for a first device; acquiring historical operation data of a plurality of devices including the first device, the historical operation data including structured data and unstructured data; determining at least a list of first entities and a list of second entities based on the structured data; determining a set of entity associations, each entity association including at least one of the first entities and at least one of the second entities; determining one or more relationships between each of the entity associations; and determining, based on the one or more determined relationships, an operation solution to solve the operation problem.

Abstract: A method, non-transitory computer readable medium, and an image analysis computing device that retrieves, based on a captured version of an object in a received image, training images which display related versions of the object and items of data related to the related versions of the object of the training images. Keypoints which are invariant to changes in scale and rotation in the captured version of the object in the received image and in the related versions of the object in the training images are determined. Changes to the object in the received image based on any of the determined keypoints in the related version of the object which do not match the determined keypoints in the captured version of the object are identified. The identified changes in the captured version of the object in the received image are provided.

Abstract: The present disclosure discloses a method and a device for monitoring life of automobile oil. The method comprising, receiving, by an oil life indication device, a video from an imaging unit communicatively coupled to the oil life indication device, where the video displays spreading of the automobile oil over a slope surface. The method comprises extracting a plurality of image frames from the video, determining one or more parameter values for at least one quality factors of the automobile oil and comparing the one or more parameter values with predefined threshold values to estimate life of the automobile oil.

Abstract: The present disclosure relates to a method and a system for recognizing characters. In one embodiment, the input image comprising one or more characters to be recognized is received and processed to extract one or more nodes and edges of each character in the input image. Using the extracted nodes and edges, a graphical representation and adjacency matrix of each character is generated and compared with a predetermined graphical representation and adjacency matrix to determine a match. Based on the comparison, a matching probability is determined based on which one or more characters in the input image is recognized and displayed as output. The proposed recognition method and system recognizes character with more accuracy and speed. Further, the present disclosure is simple, cost-effective and reduces the complexity involved in automatic recognition of characters.

Abstract: The present disclosure relates to a method and a system for recognizing characters. In one embodiment, the input image comprising one or more characters to be recognized is received and processed to extract one or more nodes and edges of each character in the input image. Using the extracted nodes and edges, a graphical representation and adjacency matrix of each character is generated and compared with a predetermined graphical representation and adjacency matrix to determine a match. Based on the comparison, a matching probability is determined based on which one or more characters in the input image is recognized and displayed as output. The proposed recognition method and system recognizes character with more accuracy and speed. Further, the present disclosure is simple, cost-effective and reduces the complexity involved in automatic recognition of characters.

Abstract: Systems and methods for recognizing alphanumeric characters are described. In one implementation, the method for recognizing alphanumeric characters comprises receiving features for each of the alphanumeric characters to be recognized. The features comprises at least one of number of lines, length of lines, number of arcs, length of arcs, number of loops, length of loops, number of junctions, junction positions, or total length of lines, arcs, and loops. Further, the method comprises creating a vector for each of the alphanumeric characters based on the features. Further, the method comprises comparing the vector with a reference vector obtained from a reference database. Further, the method comprises determining an array of probabilities for each of the alphanumeric characters based on the comparison. Further, the method comprises recognizing the alphanumeric characters based on the array of probabilities.

Abstract: A method, non-transitory computer readable medium, and an image analysis computing device that retrieves, based on a captured version of an object in a received image, training images which display related versions of the object and items of data related to the related versions of the object of the training images. Keypoints which are invariant to changes in scale and rotation in the captured version of the object in the received image and in the related versions of the object in the training images are determined. Changes to the object in the received image based on any of the determined keypoints in the related version of the object which do not match the determined keypoints in the captured version of the object are identified. The identified changes in the captured version of the object in the received image are provided.

Abstract: This disclosure relates to methods and systems for determining user attributes. In one embodiment, a method performed by an electronic device for determining user attributes receiving a touch input is disclosed, the method comprising: determining one or more sets of touch parameters based on the touch input, each set associated with a user attribute; identifying, for each of the one or more sets of touch parameters, an associated set of stored touch parameters from among a plurality of stored touch parameters based on a predefined criterion of match between the set of touch parameters and the plurality of stored touch parameters; determining, for each of the one or more sets of touch parameters, the associated user attribute based on the associated set of stored touch parameters; and providing the determined user attribute associated with each of the one or more sets of touch parameters.