Abstract: A system comprising a causal convolutional neural network to autoregressively generate a succession of values of a data item conditioned upon previously generated values of the data item. The system includes support memory for a set of support data patches each of which comprises an encoding of an example data item. A soft attention mechanism attends to one or more patches when generating the current item value. The soft attention mechanism determines a set of scores for the support data patches, for example in the form of a soft attention query vector dependent upon the previously generated values of the data item. The soft attention query vector is used to query the memory. When generating the value of the data item at a current iteration layers of the causal convolutional neural network are conditioned upon the support data patches weighted by the scores.

Abstract: Target data may be associated with a location requirement established by a data owner. A data access module may be used to attempt access to the target data. Location requirement and provenance metadata associated with the target data are obtained. The provenance metadata must be validated, and evidence only approved data access locations identified in the location requirement. A current location of a computing device attempting access to the target data must also meet the location requirement. The computing device is allowed to access the target data only in response to the current location and each location identified in the provenance metadata meeting the location requirement. The provenance metadata is updated to include a new record including the current data access location.

Abstract: A method, computer system, and a computer program product for semantic matching is provided. The present invention may include pre-processing and normalizing a job title. The present invention may include deconstructing the job title based on at least one semantic element. The present invention may include training a machine learning model. The present invention may include creating a contextual word representation of the job title using the at least one semantic element of the job title. The present invention may include computing a similarity score for each of the at least one semantic element of the job title. The present invention may lastly include applying a weight to the computed similarity score before making a final match assessment.

Abstract: A method and system to interpret sensor transmission patterns to analyze anomalies in a smart environment include obtaining a map of the smart environment, the map including an indication of obstructions and openings. The method includes determining an initial location of each sensor of a plurality of sensors in the smart environment. Each sensor emits a transmission after each detection. The method also includes identifying an initial transmission pattern associated with each sensor, and identifying a change in the initial transmission pattern of a sensor among the plurality of sensors. The change is interpreted to determine whether the change in the initial transmission pattern of the sensor among the plurality of sensors is due to movement or obstruction of the sensor. Action is taken based on a determination that the sensor among the plurality of sensors is obstructed or removed.

Abstract: A computer-implemented method, a computer program product, and a computer system for determining skill adjacencies using a machine learning model. A computer calculates first similarity scores between first skill vectors obtained from one or more training datasets and second similarity scores between the first skill vectors and skill category vectors pre-calculated from job requisitions, using both a reference corpus word embedding model and a target corpus word embedding model. The computer generates features extracted from the first similarity scores and the second similarity scores. Based on the features, the computer trains a machine learning model for classifying combinations of skills as adjacent and non-adjacent. The machine learning model is used to determine skill adjacencies between skills extracted from the job requisitions and skills extracted from resumes.

Abstract: A system and method for calculating and organizing a plurality of document objects with associated workflow objects for a plurality of user devices whereby a deadline calculator and an object manager calculate missing information based on historical records and corresponding rules and user settings. The plurality of user devices capable of managing, document object actions such as accept, deny, or pause document objects or actions, driven by pre-configured parameters and internal system rules related to single or ongoing deadlines and/or other triggers. A proximity manager to manage deadline triggers based on a plurality of rules based on date distances from computed deadlines.

Abstract: A node in a blockchain network may initiate a non-fungible token identity, establish a profile for the non-fungible token identity, receive reputation data related to the non-fungible token identity, determine, based on the reputation data, a reputation score, append the non-fungible token identity with the reputation score as a non-fungible token metadata tag, and upload the non-fungible token identity and the metadata tag to an ID repository.

Abstract: Provided are embodiments for a method, system, and computer program product for operating a certified information verification service. Some embodiments include receiving an article including one or more claims, and extracting the one or more claims from the article. The one or more claims are analyzed by the one or more information verification services, and a report for the article is generated based on the analysis.

Abstract: An electrical connector includes a receptacle connector having a tongue member with a surface extending between first and second tongue ends and having a shoulder extending from the surface adjacent to the second tongue end. The shoulder has a cross-sectional area within a receptacle opening size limit. The receptacle connector further includes a set of electrical contacts each extending through the shoulder between first and second contact ends on opposite sides of the shoulder. The electrical contacts at the first contact end are attached to the tongue surface at the first tongue end. The electrical contacts at the second contact end extend beyond the second tongue end. The receptacle connector further includes an electromagnetic interference (EMI) shielding bracket covering at least a portion of the set of electrical contacts between the first contact end and the shoulder. The disclosure further includes a method of making the electrical connector.

Abstract: A method, computer system, and a computer program product for semantic matching is provided. The present invention may include pre-processing and normalizing a job title. The present invention may include deconstructing the job title based on at least one semantic element. The present invention may include training a machine learning model. The present invention may include creating a contextual word representation of the job title using the at least one semantic element of the job title. The present invention may include computing a similarity score for each of the at least one semantic element of the job title. The present invention may lastly include applying a weight to the computed similarity score before making a final match assessment.

Abstract: This document describes techniques for placing instances on servers of a service provider environment. In an example embodiment, a system can determine that characteristics of a new virtual machine instance match a co-tenant policy of an existing virtual machine instance on a server and factor that information into a decision to place the virtual machine instance.

Abstract: A computer-implemented method, a computer program product, and a computer system for determining skill adjacencies using a machine learning model. A computer calculates first similarity scores between first skill vectors obtained from one or more training datasets and second similarity scores between the first skill vectors and skill category vectors pre-calculated from job requisitions, using both a reference corpus word embedding model and a target corpus word embedding model. The computer generates features extracted from the first similarity scores and the second similarity scores. Based on the features, the computer trains a machine learning model for classifying combinations of skills as adjacent and non-adjacent. The machine learning model is used to determine skill adjacencies between skills extracted from the job requisitions and skills extracted from resumes.

Abstract: Aspects of the disclosure provide for a system. In some examples, the system comprises a first sensor associated with first and second attributes and a second sensor associated with the second attribute and a third attribute. The system further comprises a processor communicatively coupled to the first and second sensors. The processor is configured to identify a number of activations of the first sensor within a time window, identify a number of activations of the second sensor within the time window, and construct a sensor vector identifying a number of first attribute activations based on the first number of activations of the first sensor, a number of second attribute activations based on the number of activations of the first sensor and the number of activations of the second sensor, and a number of third attribute activations based on the number of activations of the second sensor.

Abstract: A method and system to interpret sensor transmission patterns to analyze anomalies in a smart environment include obtaining a map of the smart environment, the map including an indication of obstructions and openings. The method includes determining an initial location of each sensor of a plurality of sensors in the smart environment. Each sensor emits a transmission after each detection. The method also includes identifying an initial transmission pattern associated with each sensor, and identifying a change in the initial transmission pattern of a sensor among the plurality of sensors. The change is interpreted to determine whether the change in the initial transmission pattern of the sensor among the plurality of sensors is due to movement or obstruction of the sensor. Action is taken based on a determination that the sensor among the plurality of sensors is obstructed or removed.

Abstract: Provided are embodiments for a method, system, and computer program product for operating a certified information verification service. Some embodiments include receiving an article including one or more claims, and extracting the one or more claims from the article. The one or more claims are analyzed by the one or more information verification services, and a report for the article is generated based on the analysis.

Abstract: This invention, through a computer or computer program (software code understood by a computer and displayed to a user through an interface), creates a systemized process and method of requesting, approving, exchanging, and managing documents—either in electronic or paper format—between multiple participants to a construction endeavor or related endeavor. The system, method, and process specifically enables the user(s) to request, approve, exchange, and manage said documents according to certain protocols and processes that are defined, guided, and controlled by user defined rules, user selected status, status indications automatically generated based on user data, status indications automatically generated based on aggregated data, rules based on user data, and/or rules based on aggregated data.

Abstract: A system is provided for inferring sensor topology in a structure. The system includes a receiver, a server communicatively coupled to the receiver and a sensor topology engine communicatively coupled to the receiver and the server. The receiver is configured to receive identification information that sensors have been and deployed throughout the structure to sense a presence of an operator and to receive sensor readings from the sensors and couple the sensor readings to the sensor topology engine. The sensor topology engine is further configured analyze the identification information and the sensor readings to infer zones of the multiple spaces in which the presence of the operator is sensed by at least one of the sensors, borders of each of the zones, and dead zones adjacent to one or more of the zones in which the presence of the operator is not sensed and build a topological graph.

Abstract: Techniques for determining whether data associated with an autonomous/non-autonomous operation of a manned/unmanned vehicle may be trusted. For example, a first set of data may be provided from a source external to a manned/unmanned vehicle. A second set of data may be accessed. This second set may be provided from a source internal or external to the manned/unmanned vehicle and may be associated with the same autonomous/non-autonomous operation. The two sets may be compared to determine whether the first set of data may be trusted or not. If untrusted, a corrective action may be performed.

Abstract: Described are techniques for outputting or suppressing output of network content to a user device based on content previously accessed by the user device. Correspondence between network content accessed by the user device and spoiler data determined from media content may indicate that the network content is associated with the media content. Content consumption data associated with the user device may indicate whether the user device has previously accessed the media content. The network content may be suppressed from output if the user device has not previously accessed the media content. The network content may be output to the user device if the media content has been accessed.