Abstract: A system processes images of documents, for example, identification documents. The system transforms an image of a document to generate an image that represent the document in a canonical form. For example, if the input image has a document that is tilted at an angle with respect to the sides of the image, the system modifies the orientation of the document to show the document having sides aligned with the sides of the image. The system stores user accounts that include user information including images. The system generates a graph of nodes that represent user accounts with edges determined based on similarity scores between user accounts. The system determines connected components of user accounts, such that each connected component represents user accounts that have a high likelihood of being duplicates.

Abstract: Backup data is leveraged to determine whether primary data has been encrypted by malware. The disclosed approach does not rely on recognizing particular malware instances or malware provenance, and thus can be applied to any body of data. Even a novel and previously unknown malware attack can be detected in this way. An illustrative data storage management system analyzes secondary copies it created over time, applies a multi-factor analysis to data recovered from the secondary copies and, based on the analysis, infers whether the primary data from which the secondary copies were created may be encrypted. The present approach uses successive versions of backup copies to find indicia of malware encryption, rather than trying to trace or identify the malware itself. Indicia of entropy correlate highly with encryption, such as encryption performed by malware attacks. Conversely, indicia of similarity correlate highly with lack of encryption of successive versions of documents.

Abstract: A data privacy system automatically determines quasi-identifiers in a database containing individuals' records. The data privacy system applies a machine learning model to the database, the model configured to classify each record in the database and output a measure of its confidence in its classification. The data privacy system determines, based on the measure of confidence, how important each attribute is to the model's classification. The data privacy system iteratively applies a machine learning model on a modified database that includes the highest ranked attributes to identify the quasi-identifiers in the records in the database. The data privacy system can use identified quasi-identifiers to determine if the database is susceptible to a membership inference attack, and in response to such a determination, can perform one or more data privacy operations on the database to reduce this risk.

Abstract: A data privacy system automatically determines quasi-identifiers in a database containing individuals' records. The data privacy system applies a machine learning model to the database, the model configured to classify each record in the database and output a measure of its confidence in its classification. The data privacy system determines, based on the measure of confidence, how important each attribute is to the model's classification. The data privacy system iteratively applies a machine learning model on a modified database that includes the highest ranked attributes to identify the quasi-identifiers in the records in the database. The data privacy system can use identified quasi-identifiers to determine if the database is susceptible to a membership inference attack, and in response to such a determination, can perform one or more data privacy operations on the database to reduce this risk.

Abstract: A battery pack assembly (100), the assembly (100) comprises: a plurality of cells (102a, 102b), each cell (102a, 102b) having a body portion extending between a first end having a first terminal and a second end having a second terminal, a first holding frame (101a) being configured to accommodate at least the first end of one or more of the plurality of cells (102a, 102b) and a second holding frame (101b) being configured to accommodate at least the second end of one or more of the plurality of cells (102a, 102b), an electrical control unit (103) configured to control the electrical output of the battery pack assembly (100), and a separator plate (104), wherein the separator plate (104) is located between the plurality of cells (102a, 102b) and the electrical control unit (103) and is secured to the first holding frame (101a) and the second holding frame (101b).

Abstract: An Integrated Circuit (IC) includes a storage element and control circuitry. The control circuitry is configured to select, responsively to a scan-enable control, between a functional-data input and a scan-data input to serve as an input to the storage element, to selectively disable toggling of an output of the storage element, responsively to a clock-enable control, by gating a clock signal provided to the storage element, and, while the clock-enable control indicates that the output of the storage element is to be disabled from toggling, to select the input of the storage element to be the scan-data input.

Abstract: A method of capping a metal layer includes performing a conversion process to reduce a metal oxide layer formed on a top surface of the metal layer and form a metal sulfide layer on the top surface of the metal layer, exposing the top surface of the metal layer to an oxidizing environment, and performing a removal process to remove the metal sulfide layer.

Abstract: Techniques are disclosed to identify if a current chamber being mapped is a target chamber that is desired to be mapped based on the relative position of the local activation time relative to QRS onset. Techniques are also disclosed whereby cardiac data can be labeled to indicate whether a beat was acquired while in the ventricle, or in the atrium.

Abstract: A method is provided for identifying changes in road geometry, comprising obtaining an image of an initial road geometry for a geographical area, obtaining an image of movement data for the geographical area, forming a composite image from at least the image of initial road geometry and the image of movement data and generating an image of road geometry corrections by applying a trained road geometry correction model to the composite image, wherein the image of road geometry corrections identifies one or more differences between the actual road geometry of the geographical area and the initial road geometry. A method of training a suitable road geometry correction model is also described.

Abstract: Methods and systems are provided for identifying a mid-sagittal plane (MSP) in a medical image. In one example, a method for an image processing system comprises obtaining an input volume acquired with an ultrasound imaging system, entering the input volume as input to a segmentation model trained to output a segmentation mask that identifies a segmented fetal head, a first segmented orbit, and a second segmented orbit, identifying a mid-sagittal plane (MSP) of the fetal head using the segmented first orbit and the segmented second orbit, visually displaying the MSP on the segmented fetal head, in response to determining the MSP is not an acquired plane, alerting a user of poor facial rendering or a possibility of poor facial rendering and prompting the user to reorient an ultrasound probe and reacquire the input volume, and displaying the input volume and/or saving the input volume in memory.

Abstract: There is provided a method for assigning an aerial cell to one or more user equipment (UEs) in a wireless communication system. The method includes establishing a data connection between one or more user equipments (UEs) and a terrestrial cell, receiving one or more feedback parameters from each of the one or more UEs via the data connection, and assigning an aerial cell to a first UE, among the one or more UEs, based on at least one of the one or more feedback parameters received from the first UE and a number of the one or more UEs present in a coverage area of the aerial cell, wherein the coverage area is part of a terrestrial coverage area of the terrestrial cell.

Abstract: An example method of managing tenant networks in a data center includes: obtaining, by tenant network topology discovery software executing in the data center, inventory data for a tenant network deployed in the data center from a network manager, the tenant network comprising a software-defined network managed by the network manager; generating, by the tenant network topology discovery software, a tenant network model based on the inventory data, the tenant network model including objects representing components of the tenant network and relationships between the components; storing, by the tenant network topology discovery software, the tenant network model in a database; and updating, by the tenant network topology discovery software, the tenant network model in response to monitoring the tenant network.

Abstract: Systems, computer program products, and methods are described herein for extraction of historical data in workflow automation platform architectures. The present disclosure is configured to introduce an advanced approach to historical data extraction from workflow automation platform architectures. At its core, it employs parallel processing, utilizing a multi-threaded asynchronous tool specifically designed within a workflow automation platform architecture framework. This ensures high performance and scalability, enabling easy extraction of large data volumes within designated system maintenance windows without impinging on system performance.

Abstract: A process includes operating a fuel injector to perform an injection of fuel, sensing a fluid hammer pressure of fuel in the injector generated in response to closing of an injector needle, determining at least one physical characteristic of the fuel in response to the fluid hammer pressure, and controlling operation of the fuel injection system in response to the at least one physical characteristic.

Abstract: An integrated circuit (IC), including a recording circuit and a clocking system, is provided. During a capture phase of an at-speed testing of the IC, the recording circuit records a number of clock pulses of a test clock signal and generates configuration data indicative of the recorded number of the clock pulses. The clocking system receives a reference clock signal and the configuration data and generates an at-speed clock signal. During the capture phase, the at-speed clock signal includes clock pulses that are extracted from the reference clock signal based on the configuration data. A count of the extracted clock pulses is equal to the recorded number of clock pulses of the test clock signal. The at-speed testing of the IC is enabled based on the at-speed clock signal.

Abstract: The disclosure provides an approach for gateway optimization. Embodiments include receiving, at a first gateway associated with a first tenant within a data center, a packet directed to a first public network address of an endpoint associated with a second tenant within the data center. Embodiments include performing, by the first gateway, network address translation (NAT) to translate the first public network address to a private network address of the endpoint. Embodiments include forwarding, by the first gateway, the packet to an edge gateway of the data center. Embodiments include forwarding, by the edge gateway, the packet to a second gateway associated with the second tenant within the data center without sending the packet to a public interface of the edge gateway. Embodiments include forwarding, by the second gateway, the packet to the endpoint.

Abstract: A seed camera disposed a first location is manually calibrated. A second camera, disposed at a second location, detects a physical marker based on predefined characteristics of the physical marker. The physical marker is located within an overlapping field of view between the seed camera and the second camera. The second camera is calibrated based on a combination of the physical location of the physical marker, the first location of the seed camera, the second location of the second camera, a first image of the physical marker generated with the seed camera, and a second image of the physical marker generated with the second camera.

Abstract: Some embodiments provide a novel method for configuring edge routers in a first network. The method configures on a first compute node of the first network (1) a first higher-level edge router and (2) a set of lower-level edge routers. Each lower-level edge router is configured for a different set of subnetworks defined in the first network and is connected to an external second network through the first higher-level edge router. The method detects a condition that requires a particular lower-level edge router for a particular subnetwork to be moved to another compute node. The method configures the particular lower-level edge router to operate on a second compute node below a second higher-level edge router operating on the second compute node to connect the particular lower-level edge router to the external second network.

Abstract: Artificial intelligence-based processing can be used to classify audio information received from an audio input unit. In an example, audio information can be received from a microphone configured to monitor an environment. A processor circuit can identify identifying one or more features of the audio information received from the microphone and use a first applied machine learning algorithm to analyze the one or more features and determine whether the audio information includes an indication of an abnormal event in the environment. In an example, the processor circuit can use a different second applied machine learning algorithm, such as a neural network-based deep learning algorithm, to analyze the same one or more features and classify the audio information as including an indication of a particular event type in the environment.

Abstract: Techniques are disclosed herein for managing ambiguous date mentions in natural language utterances in transforming natural language utterances to logical forms by encoding the uncertainties of the ambiguous date mentions and including the encoded uncertainties in the logical forms. In a training phase, training examples including natural language utterances, logical forms, and database schema information are automatically augmented and used to train a machine learning model to convert natural language utterances to logical form. In an inference phase, input database schema information is augmented and used by the trained machine learning model to convert an input natural language utterance to logical form.