Abstract: A system, method, and computer-readable storage medium are disclosed that execute machine vision operations to categorize a locality. At least one embodiment accesses a map image of a locality, where the map image includes geographical artefacts corresponding to entities within the locality; analyzes the map image to detect the entities in the locality using the geographical artefacts; assigns entity classes to detected entities in the locality; assigns a locality score to the locality based on entity classes included in the locality; retrieves street view images for one or more of the detected entities in the locality; and analyzes street view images of the detected entities to assign one or more further classifications to the detected entities. Other embodiments include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the method.

Abstract: A mobile device running a software application is configured to provide initial location data to a server when it is first turned on, or reaches a predetermined movement status. The server determines, based on the initial location data, geo data including a set of geo-fences near the mobile device and a region including areas defined by the set of geo-fences, and provides the geo data to the mobile device. The mobile device is further configured to collect its locations when the mobile device is within any of the set of geo-fences and to provide the collected locations to the server. The mobile device is further configured to track its movement status after it has been outside the region and, in response to having reached a predetermined movement status, obtain updated geo data including a new region and a new set of geo-fences from the server. The software application enables efficient tracking of mobile device locations and reduces power consumption.

Abstract: A system, method, and computer-readable medium for performing a system failure repair operation, comprising: receiving information regarding symptoms related to a faulty device; storing the information with other historical information regarding the symptoms; receiving additional information as the faulty device is diagnosed; indicating whether a repair recommendation is provided for the faulty device; and using the stored information, historical information, and additional information to provide a repair recommendation if indicating shows no repair recommendation.

Abstract: An apparatus comprises a processing device configured to receive a query to extract information from a document, and to perform two or more iterations of utilizing a machine learning-based information extraction model to extract portions of unstructured text data from the document. In each iteration, a portion of the unstructured text data extracted from the document and an associated relevance score are output. In a first iteration, the query and document are input while in subsequent iterations the query and modified versions of the document are input, the modified versions having previously-extracted portions of the unstructured text data removed therefrom. The processing device is also configured to generate a response to the query comprising a subset of the portions of the unstructured text data extracted from the document determined to have associated relevance scores exceeding a threshold relevance score and at least a threshold level of similarity to the query.

Abstract: A method includes obtaining information regarding a given asset to be repaired, providing the information regarding the given asset to an encoder of a deep learning model, and receiving, from a decoder of the deep learning model, a recommendation for a troubleshooting action to be performed on the given asset. The method also includes performing the recommended troubleshooting action on the given asset, determining whether the recommended troubleshooting action results in a successful repair of the given asset and, responsive to determining that the recommended troubleshooting action does not result in a successful repair of the given asset, augmenting the information regarding the given asset based at least in part on an output vocabulary of the decoder corresponding to the recommended troubleshooting action. The method further includes repeating the providing, receiving, performing and determining steps utilizing the augmented information regarding the given asset.

Abstract: A method of purifying a plurality of metal oxide particles produced from a synthesis process comprising the step of washing a plurality of metal oxide particles in a first solvent composition comprising of at least one aliphatic ether, and at least one flocculant. In one embodiment, the plurality of metal oxide particles are iron oxide particles produced from a thermal decomposition synthesis process between an iron-oleate complex and oleic acid in 1-octadecene, wherein the first solvent composition comprises a 1:1 (vol/vol) ratio of an aliphatic ether in the form of diethyl ether and a flocculant in the form of methanol. The washed iron oxide particles are further washed in a second solvent composition comprising a 1:1 (vol/vol) ratio of hexane and ethanol, and then finally dispersed in hexane. The resulting iron oxide particles find use as a contrast agent for magnetic resonance imaging (MRI) or as magnetic particles in magnetic separation, magnetism-directed targeting or magnetism-induced heating.

Abstract: A system, method, and computer-readable medium for performing a product query operation, comprising: receiving user input from a user; identifying keywords contained within the user input; comparing keywords to vector representations of words and also to a document vector representation of product specifications in a backend product repository, each vector representation of a word being associated with a particular query type; identifying component details based upon the comparing; and, providing a list of products corresponding to the component details to the user in real time.

Abstract: An apparatus includes at least one processing device configured to obtain information regarding a given asset to be repaired, to generate a recommended troubleshooting action to be performed on the given asset, and to provide the recommended troubleshooting action and the obtained information regarding the given asset as input to an encoder of a machine learning model implementing an attention mechanism. The at least one processing device is also configured to receive, from a decoder of the machine learning model, a predicted success of the recommended troubleshooting action. The at least one processing device is further configured to determine whether the predicted success of the recommended troubleshooting action meets designated criteria, to perform the recommended troubleshooting action responsive to the predicted success meeting the designated criteria, and, to modify the recommended troubleshooting action responsive to the predicted success not meeting the designated criteria.

Abstract: An apparatus includes at least one processing device configured to obtain information regarding a given asset to be repaired, to generate a recommended troubleshooting action to be performed on the given asset, and to provide the recommended troubleshooting action and the obtained information regarding the given asset as input to an encoder of a machine learning model implementing an attention mechanism. The at least one processing device is also configured to receive, from a decoder of the machine learning model, a predicted success of the recommended troubleshooting action. The at least one processing device is further configured to determine whether the predicted success of the recommended troubleshooting action meets designated criteria, to perform the recommended troubleshooting action responsive to the predicted success meeting the designated criteria, and, to modify the recommended troubleshooting action responsive to the predicted success not meeting the designated criteria.

Abstract: At least one embodiment is directed to a computer-implemented method for using machine vision to categorize a locality to conduct product positioning analyses, the method including: generating locality profile scores for each locality of a plurality of localities using deep learning networks, where the locality profile score includes distributions of entity classes within the locality; extracting a set of entities having the same entity class from a group of localities; retrieving historical purchasing data for the entity set; and generating a sequence of products likely to be purchased by a target entity as a function of: the similarity of purchasing characteristics of the target entity with respect to other entities, product sequences found in product purchase of other entities, and entity profile weights extracted from the locality profile scores of other entities that have purchased one or more of the same products as the target entity.

Abstract: At least one embodiment of the disclosed system is directed to computer-implemented method for using machine vision to categorize a locality to conduct lead mining analyses. Embodiments of the method may include: generating locality profile scores and economic categorization for each locality of a plurality of localities, the locality profile score for each locality being derived through neural network analyses of map images of the locality, the economic categorization being derived through neural network analyses of images of entities within the locality; and generating a lead score for each entity in the locality group as a function of the locality profile score for the locality in which the entity is located, the economic categorization of the locality in which the entity is located, and campaign vehicles used in the locality in which the entity is located.

Abstract: A system, method, and computer-readable storage medium are disclosed that execute machine vision operations to categorize a locality. At least one embodiment accesses a map image of a locality, where the map image includes geographical artefacts corresponding to entities within the locality; analyzes the map image to detect the entities in the locality using the geographical artefacts; assigns entity classes to detected entities in the locality; assigns a locality score to the locality based on entity classes included in the locality; retrieves street view images for one or more of the detected entities in the locality; and analyzes street view images of the detected entities to assign one or more further classifications to the detected entities. Other embodiments include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the method.

Abstract: A system, method, and computer-readable storage medium are disclosed that execute machine vision operations to categorize a locality. At least one embodiment accesses a map image of a locality, where the map image includes geographical artefacts corresponding to entities within the locality; analyzes the map image to detect the entities in the locality using the geographical artefacts; assigns entity classes to detected entities in the locality; assigns a locality score to the locality based on entity classes included in the locality; retrieves street view images for one or more of the detected entities in the locality; and analyzes street view images of the detected entities to assign one or more further classifications to the detected entities. Other embodiments include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the method.

Abstract: A mobile device running a software application is configured to provide initial location data to a server when it is first turned on, or reaches a predetermined movement status. The server determines, based on the initial location data, geo data including a set of geo-fences near the mobile device and a region including areas defined by the set of geo-fences, and provides the geo data to the mobile device. The mobile device is further configured to collect its locations when the mobile device is within any of the set of geo-fences and to provide the collected locations to the server. The mobile device is further configured to track its movement status after it has been outside the region and, in response to having reached a predetermined movement status, obtain updated geo data including a new region and a new set of geo-fences from the server. The software application enables efficient tracking of mobile device locations and reduces power consumption.

Abstract: A system, method, and computer-readable medium are disclosed for management of a distributed ledger technology customer loyalty program, by establishing a distributed ledger technology network of customer and entity nodes. The entity nodes support products and/or services purchased by customers, providing a distributed ledger technology platform accessible by the nodes. Transactions between nodes go through the distributed ledger technology platform. A distributed ledger technology ledger which tracks the transactions. Coins/credits are provided to customers based on their transactions.

Abstract: A method includes obtaining information regarding a given asset to be repaired, providing the information regarding the given asset to an encoder of a deep learning model, and receiving, from a decoder of the deep learning model, a recommendation for a troubleshooting action to be performed on the given asset. The method also includes performing the recommended troubleshooting action on the given asset, determining whether the recommended troubleshooting action results in a successful repair of the given asset and, responsive to determining that the recommended troubleshooting action does not result in a successful repair of the given asset, augmenting the information regarding the given asset based at least in part on an output vocabulary of the decoder corresponding to the recommended troubleshooting action. The method further includes repeating the providing, receiving, performing and determining steps utilizing the augmented information regarding the given asset.

Abstract: A system, method, and computer-readable medium for performing a system failure repair operation, comprising: receiving information regarding symptoms related to a faulty device; storing the information with other historical information regarding the symptoms; receiving additional information as the faulty device is diagnosed; indicating whether a repair recommendation is provided for the faulty device; and using the stored information, historical information, and additional information to provide a repair recommendation if indicating shows no repair recommendation.

Abstract: A system, method, and computer-readable medium for performing a workload classification and analysis operation. The workload classification and analysis operation includes performing the steps of receiving workload data from a data source; generating a neural network model from the workload data; defining a plurality of workload signatures, the plurality of workload signatures defining a particular type of workload; identifying particular workloads using the plurality of workload signatures; and, providing information regarding the particular workloads to a user.

Abstract: A mobile device running a software application is configured to provide initial location data to a server when it is first turned on, or achieves a predetermined movement status. The server determines, based on the initial location data, geo data including a set of areas of interest (AOIs) near the mobile device and a region including the set of AOIs, and provides the geo data to the mobile device. The mobile device is further configured to track its locations when the mobile device is within any of the set of AOIs and to provide the tracked locations to the server. The mobile device is further configured to track its movement status after it has been outside the region, and, in response to a predetermined movement status being detected for a predetermined amount of time, obtain updated geo data including a new region and a new set of AOIs from the server. The software application enables efficient tracking of mobile device locations and reduces power consumption.

Abstract: A system, method, and computer-readable medium for performing a workload classification and analysis operation. The workload classification and analysis operation includes performing the steps of receiving workload data from a data source; generating a neural network model from the workload data; defining a plurality of workload signatures, the plurality of workload signatures defining a particular type of workload; identifying particular workloads using the plurality of workload signatures; and, providing information regarding the particular workloads to a user.