Abstract: Methods and systems are provided for exchanging electronic documents. An example method, and system implementing the method, can include receiving an exchange initiation request from an exchange creator, the exchange initiation request including a set of user identifiers; receiving a document submission request from a sender; storing the electronic document in a storage component when the sender is authenticated; receiving, from the sender, a recipient list for the electronic document, the recipient list indicating intended recipients of the electronic document; providing the intended recipients with access to the electronic document; and generating an exchange record for the electronic document, the exchange record providing a receipt confirmation indicating the electronic document was received and a receipt verification link to the exchange record stored in the storage component.

Abstract: Video sources and inertial sensors are attached to a weapon and to goggles. A computer receives video images from the weapon- and goggles-mounted sources and inertial data from the sensors. The computer calculates a location for an image from the weapon-mounted source within an image from the goggles-mounted source using the inertial sensor data. The sensor-based location is checked (and possibly adjusted) based on a comparison of the images. A database contains information about real-world objects in a field of view of the goggles-mounted source, and is used to generate icons or other graphics concerning such objects.

Abstract: Techniques are disclosed for for prioritizing a plurality of clusters. Prioritizing clusters may generally include identifying a scoring strategy for prioritizing the plurality of clusters. Each cluster is generated from a seed and stores a collection of data retrieved using the seed. For each cluster, elements of the collection of data stored by the cluster are evaluated according to the scoring strategy and a score is assigned to the cluster based on the evaluation. The clusters may be ranked according to the respective scores assigned to the plurality of clusters. The collection of data stored by each cluster may include financial data evaluated by the scoring strategy for a risk of fraud. The score assigned to each cluster may correspond to an amount at risk.

Abstract: Remote commissioning for an automation system enables a retailer to sell a new device to a customer pre-configured to work together with devices that are already a part of the user's automation system. Knowledge of how the devices are likely to be used at the automation system's location, a list of existing devices already installed and how they are configured, possible input from the customer, and the end user's current usage patterns are optionally used to configure the devices before they leave the store. Assisted local commissioning for an automation device enables an end user to commission devices themselves by simplifying the installation and commissioning process. The system uses a reference database of devices that includes information on how to commission the devices along with user-manual information and pictures for physical installation, and setup instructions so the system can walk a user through the process step by step.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

Abstract: A history preserving data pipeline computer system and method. In one aspect, the history preserving data pipeline system provides immutable and versioned datasets. Because datasets are immutable and versioned, the system makes it possible to determine the data in a dataset at a point in time in the past, even if that data is no longer in the current version of the dataset.

Abstract: Video sources and inertial sensors are attached to a weapon and to goggles. A computer receives video images from the weapon- and goggles-mounted sources and inertial data from the sensors. The computer calculates a location for an image from the weapon-mounted source within an image from the goggles-mounted source using the inertial sensor data. The sensor-based location is checked (and possibly adjusted) based on a comparison of the images. A database contains information about real-world objects in a field of view of the goggles-mounted source, and is used to generate icons or other graphics concerning such objects.

Abstract: A method executed by a computing device includes receiving a search criteria and location data from a user device in communication with the computing device, determining a user location based on the location data, and determining a geographical density of entities about the user location. The method optionally includes selecting one or more access mechanisms based on the search criteria and the geographical density. Each access mechanism, when executed by the user device, causes the user device to access a resource identified by the access mechanism. The method also optionally includes transmitting search results containing the one or more selected access mechanisms from the computing device to the user device.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyzes (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

Abstract: A sheet feeder comprises a feed deck for supporting a stack of sheets (65) to be fed. The feed deck may be formed by a bed of freely spinning rollers. A feed block (62) comprises a friction pad (66) that projects from the bottom of the feed block (62) towards a drive belt (42) to define a gate therebetween. The drive belt (42) frictionally engages the underside of a bottom sheet of the stack (65) and urges the sheet towards the gate. The feed block (62) comprises a front face (72) immediately upstream from the gate, which is inclined at a sharp angle to the feed direction. The friction pad (66) comprises a lower face that is substantially parallel to the feed direction and does not intersect the plane of the feed block front face (72).

Abstract: In various embodiments, systems, methods, and techniques are disclosed for generating a collection of clusters of related data from a seed. Seeds may be generated based on seed generation strategies or rules. Clusters may be generated by, for example, retrieving a seed, adding the seed to a first cluster, retrieving a clustering strategy or rules, and adding related data and/or data entities to the cluster based on the clustering strategy. Various cluster scores may be generated based on attributes of data in a given cluster. Further, cluster metascores may be generated based on various cluster scores associated with a cluster. Clusters may be ranked based on cluster metascores. Various embodiments may enable an analyst to discover various insights related to data clusters, and may be applicable to various tasks including, for example, tax fraud detection, beaconing malware detection, malware user-agent detection, and/or activity trend detection, among various others.

Abstract: In various embodiments, systems, methods, and techniques are disclosed for generating a collection of clusters of related data from a seed. Seeds may be generated based on seed generation strategies or rules. Clusters may be generated by, for example, retrieving a seed, adding the seed to a first cluster, retrieving a clustering strategy or rules, and adding related data and/or data entities to the cluster based on the clustering strategy. Various cluster scores may be generated based on attributes of data in a given cluster. Further, cluster metascores may be generated based on various cluster scores associated with a cluster. Clusters may be ranked based on cluster metascores. Various embodiments may enable an analyst to discover various insights related to data clusters, and may be applicable to various tasks including, for example, tax fraud detection, beaconing malware detection, malware user-agent detection, and/or activity trend detection, among various others.

Abstract: In various embodiments, systems, methods, and techniques are disclosed for generating a collection of clusters of related data from a seed. Seeds may be generated based on seed generation strategies or rules. Clusters may be generated by, for example, retrieving a seed, adding the seed to a first cluster, retrieving a clustering strategy or rules, and adding related data and/or data entities to the cluster based on the clustering strategy. Various cluster scores may be generated based on attributes of data in a given cluster. Further, cluster metascores may be generated based on various cluster scores associated with a cluster. Clusters may be ranked based on cluster metascores. Various embodiments may enable an analyst to discover various insights related to data clusters, and may be applicable to various tasks including, for example, tax fraud detection, beaconing malware detection, malware user-agent detection, and/or activity trend detection, among various others.

Abstract: In one embodiment, a search query is received from a computing device, the search query including one or more search terms. Based on the one or more search terms, one or more entities are identified from a set of multiple entities. Each of the one or more identified entities is associated with one or more application functionalities. In addition, a set of applications are identified based on the one or more search terms. Based at least on a type of at least one of the identified one or more entities, a determination is made that a particular application from the set of applications supports the at least one of the identified one or more entities. Thereafter, the applications in the set are ranked based in part on the determination that the particular application supports the at least one of the identified one or more entities.

Abstract: A fair scheduling system with methodology for fairly scheduling queries for execution by a database management system. The system obtains query jobs for execution by the database management system and cost estimates to execute the query jobs. The cost estimate can be a number of results the query is expected to return. Based on the cost estimates, the system causes the database management system to execute the query jobs as separately sub-query tasks in a round-robin fashion. By doing so, the execution latency of “low cost” query jobs that return few results is reduced when the query jobs are concurrently executed with “high cost” query jobs that return a large number of results.

Abstract: Techniques are disclosed for prioritizing a plurality of clusters. Prioritizing clusters may generally include identifying a scoring strategy for prioritizing the plurality of clusters. Each cluster is generated from a seed and stores a collection of data retrieved using the seed. For each cluster, elements of the collection of data stored by the cluster are evaluated according to the scoring strategy and a score is assigned to the cluster based on the evaluation. The clusters may be ranked according to the respective scores assigned to the plurality of clusters. The collection of data stored by each cluster may include financial data evaluated by the scoring strategy for a risk of fraud. The score assigned to each cluster may correspond to an amount at risk.

Abstract: A method includes receiving a search query froth a user device and identifying a plurality of function records included in a data store based on the received search query. Each of the function records includes an access mechanism specifying a state of an application, state information describing the state of the application, and location data including a coordinate and a perimeter. The coordinate defines the location of a place corresponding to the state information and the perimeter defines a geographic area surrounding the coordinate. The method also includes determining a search location and a score for the function record based on where the determined search location is located relative to the geographic area defined by the location data for each of the identified function records. The method also includes selecting access mechanisms from the function records based on the scores and transmitting the selected access mechanisms to the user device.

Abstract: A method includes receiving a search query from a user device, identifying a plurality of function records included in a data store based on the received search query, and determining a search location. Each function record includes an access mechanism specifying a state of an application, state information corresponding to the state of the application, and location data including a coordinate and a perimeter. The coordinate defines the location of a place corresponding to the state information and the perimeter defines a geographic area surrounding the coordinate. The method also includes determining whether the search location is located within the geographic area defined by the location data of the function record for each of the plurality of function records, selecting access mechanisms from function records that include location data defining a geographic area that includes the search location, and transmitting the selected access mechanisms to the user device.

Abstract: A method including receiving a search query containing one or more query terms from a remote device and determining one or more query parses based on the search query and a knowledge base. Each query parse indicates one or more entity types, wherein each entity type corresponds to a query term or a combination of query terms contained in the search query. The method further includes obtaining a set of app-specific rules, each app-specific rule respectively corresponding to a respective software application. The method further includes generating a set of unparameterized function identifiers based on the plurality of app-specific rules and the one or more query parses. For each of the set of unparameterized function identifiers, the method includes parameterizing the function identifier based on the query terms. The method further includes generating search results based on the parameterized function identifiers and transmitting the search results to the remote device.

Abstract: A deinterlacing apparatus includes a buffer to receive a plurality of consecutive fields of an interlaced video and a field combination module coupled to the buffer to deinterlace the interlaced video in accordance with cadence of the interlaced video. The deinterlacing apparatus also includes a cadence detection module to detect the cadence by (1) causing each of the fields to be combined with its preceding field into a frame and with its subsequent field into another frame to obtain a plurality of combined frames, (2) determining a comb factor of each of the combined frames to obtain a sequence of comb factors of the combined frames, and (3) determining if the sequence of comb factors of the combined frames follows a pre-determined repeating pattern. A cadence detection method is also described.