Abstract: Technologies are shown for selecting a provider to service a client service request using a consensus protocol and creating a block on a blockchain to service the client service request. In accordance with some aspects, a first miner receives parameters of each proposal transaction from a plurality of proposal transactions for servicing a client service request. The parameters of at least one proposal transaction from the plurality of proposal transactions is received from a second miner. The first miner uses a selection algorithm to select a first proposal transaction from the plurality of proposal transactions based on the parameters of each proposal transaction. The first miner appends a block to a blockchain based on the first proposal transaction.

Abstract: Features related to systems and methods for automated generation of a machine learning model based in part on a pretrained model are described. The pretrained model is used as a starting point to augment and retrain according to client specifications. The identification of an appropriate pretrained model is based on the client specifications such as model inputs, model outputs, and similarities between the data used to train the models.

Abstract: Memory cell sensing by charge sharing between two sense nodes is disclosed. A first sense node and a second sense node are pre-charged and the second node is discharged initiating charge sharing between the first sense node and the second sense node that results in an improved sense margin. Sensing circuitry disclosed herein may include one or more pre-charge circuits, sense enable circuits, and charge-sharing circuits. The increased sense margin achieved by sensing circuitry disclosed herein provides better noise immunity and more accurate sensing results.

Abstract: A remote control system, in which an operator remotely operates a robot having an end effector that is capable of gripping and manipulating an object, includes an acquisition part acquiring information on a state of the operator operating the robot; an end effector capable of performing multiple types of gripping methods; a gripping method table in which the gripping methods are stored; and a gripping method selector selecting the gripping method from the gripping method table based on a joint flexion angle of the operator obtained from operator information of the acquisition part.

Abstract: A method for source attribution comprises receiving measurements of a chemical species at a spatially distributed sensor array for a given set of spatially positioned emission sources in a physical environment using a dispersion model. Based on the received measurements, a concentration field is mapped from the emission sources to the sensor array using a forward operator. For each emission source, a likelihood data set is evaluated at least by fitting an emission rate of the chemical species using a regression model based on the mapped concentration field and real-world, runtime measurements from the sensor array. A posterior data set is evaluated based at least on the evaluated likelihood data set and historical data for the physical environment. For each sensor of the sensor array, estimated emission rates and contribution rankings for emission sources are determined and output based on the evaluation of the posterior data set.

Abstract: A method of tiled rendering of an image for display is provided which comprises receiving an image comprising one or more three dimensional (3D) objects and executing a visibility pass for determining locations of primitives of the image. The method also comprises executing, concurrently with the executing of the visibility pass, front end geometry processing of one of the primitives determined, from the visibility pass, to be in a first one of a plurality of tiles of the image and executing, concurrently with the executing of the visibility pass, back end processing of the one primitive in the first tile.

Abstract: A system for generating a 4D representation of a scene in motion given a sinogram collected from the scene while in motion. The system generates, based on scene parameters, an initial 3D representation of the scene indicating linear attenuation coefficients (LACs) of voxels of the scene. The system generates, based on motion parameters, a 4D motion field indicating motion of the scene. The system generates, based on the initial 3D representation and the 4D motion field, a 4D representation of the scene that is a sequence of 3D representations having LACs. The system generates a synthesized sinogram of the scene from the generated 4D representation. The system adjusts the scene parameters and the motion parameters based on differences between the collected sinogram and the synthesized sinogram. The processing is repeated until the differences satisfy a termination criterion.

Abstract: A processor includes a task scheduling unit and a compute unit coupled to the task scheduling unit. The task scheduling unit performs a task dependency assessment of a task dependency graph and task data requirements that correspond to each task of the plurality of tasks. Based on the task dependency assessment, the task scheduling unit schedules a first task of the plurality of tasks and a second proxy object of a plurality of proxy objects specified by the task data requirements such that a memory transfer of the second proxy object of the plurality of proxy objects occurs while the first task is being executed.

Abstract: Various embodiments of methods for detecting anomalous activity in a computer network are disclosed. A method includes a computer system receiving an indication of a current session establishing a secure channel to a computing device within a network. The computer system evaluates information relating to the current session, as well as information relating to one or more other sessions. Using this information, the computing system performs monitoring to detect the presence of anomalous lateral movement within the network, for example based on detecting multiple user credentials. Based on the evaluating performed, the computer system generates a score for the current session and reports whether the score is indicative of anomalous lateral movement.

Abstract: Systems and methods for units of work based on business objectives are disclosed. Exemplary implementations may: manage environment state information maintaining a collaboration environment configured to facilitate interaction by users, the environment state information defining units of work and business objectives associated with the units of work; obtain progress information, the progress information for individual business objectives conveying progress toward fulfillment of the individual business objectives; update objective records for the business objectives based on the progress information so that the progress of the business objectives is maintained by the objective records; and/or perform other operations.

Abstract: A superconducting device includes two nodes and a Josephson junction coupled between the two nodes, wherein the Josephson junction is characterized by a superconducting phase difference, ?, wherein the superconducting device has a potential that varies as a function of the superconducting phase difference, ?, and has a single potential well. The potential has a non-zero cubic term and quartic term is zero. The Josephson junction may be a single small Josephson junction. The superconducting device may include a superconducting ring connected between the two nodes. The superconducting ring may include a first ring portion with a plurality of large Josephson junctions connected in series. The superconducting ring may also include a second ring portion that includes the single small Josephson junction in parallel with the plurality of large Josephson junctions between the two nodes.

Abstract: A system for classifying a target image with segments having attributes is provided. The system generates a graph for the target image that includes vertices representing segments of the image and edges representing relationships between the connected vertices. For each vertex, the system generates a subgraph that includes the vertex as a home vertex and neighboring vertices representing segments of the target image within a neighborhood of the segment represented by the home vertex. The system applies an autoencoder to each subgraph to generate latent variables to represent the subgraph. The system applies a machine learning algorithm to a feature vector comprising a universal image representation of the target image that is derived from the generated latent variables of the subgraphs to generate a classification for the target image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying user behavior as anomalous. One of the methods includes obtaining user behavior data representing behavior of a user in a subject system. An initial model is generated from training data, the initial model having first characteristic features of the training data. A resampling model is generated from the training data and from multiple instances of the first representation for a test time period. A difference between the initial model and the resampling model is computed. The user behavior in the test time period is classified as anomalous based on the difference between the initial model and the resampling model.

Abstract: A method, apparatus and computer program product are provided for warping a perspective image into the ground plane using a homography transformation to estimate a bird's eye view in real time. Methods may include: receiving first sensor data from a first vehicle traveling along a road segment in an environment, where the first sensor data includes perspective image data of the environment, and where the first sensor data includes a location and a heading; retrieving a satellite image associated with the location and heading; applying a deep neural network to regress a bird's eye view image from the perspective image data; applying a Generative Adversarial Network (GAN) to the regressed bird's eye view image using the satellite image as a target of the GAN to obtain a stabilized bird's eye view image; and deriving values of a homography matrix between the sensor data and the established bird's eye view image.

Abstract: Multi-component modules (MCMs) including configurable electromagnetic interference (EMI) shield structures, and related methods are disclosed. An EMI shield enclosing an IC or another electrical component in an MCM can protect other components within the MCM from EMI generated by the enclosed component. The EMI shield also protects the enclosed component from the EMI generated by other electrical components. An EMI shield with side-wall structures, in which vertical conductors supported by a wall medium electrically couple a lid of the EMI shield to a ground layer in a substrate, provides configurable EMI protection in an MCM. The EMI shield may also be employed to increase heat dissipation. The side-wall structures of the EMI shield are disposed on one or more sides of an electrical component and are configurable to provide a desired level of EMI isolation.

Abstract: A method for the detection of multi-killchain alerts is disclosed. The method includes receiving, by a computer system, a plurality of alerts indicative of activity within a computer network, wherein a given alert specifies one or more events having attributes, and extracting attributes from events included in the plurality of alerts. The method further includes determining attribute similarity for pairs of events based on whether a given pair of events has common values for one or more attributes and whether attribute values of the given pair of events indicates lateral movement within computers of the computer network. Linked pairs are then identified based on the determined attribute similarity and added to a graph data structure. The method further includes the computer system analyzing the graph data structure to find clusters of events relating to a security attack.

Abstract: Systems, computer program products, and methods are described herein for secure channel selection for multi-factor authentication using non-fungible electronic resources.

Abstract: Systems, computer program products, and methods are described herein for implementing a data driven channel for query executions using quantum computing. The present invention is configured to receive, from a user input device, a query; parse, using a query processing engine, the query; determine a classical execution plan based on at least parsing the query; convert, using a query optimization engine, the classical execution plan into a quantum execution plan; initiate a query execution engine on the quantum execution plan; determine, using the query execution engine, a quantum circuit design for execution of the quantum execution plan; execute, using the query execution engine, the quantum execution plan; generate a query result based on at least executing the quantum execution plan; and transmit control signals configured to cause the user input device to display the query result.

Abstract: A processor includes a task scheduling unit and a compute unit coupled to the task scheduling unit. The task scheduling unit performs a task dependency assessment of a task dependency graph and task data requirements that correspond to each task of the plurality of tasks. Based on the task dependency assessment, the task scheduling unit schedules a first task of the plurality of tasks and a second proxy object of a plurality of proxy objects specified by the task data requirements such that a memory transfer of the second proxy object of the plurality of proxy objects occurs while the first task is being executed.

Abstract: Methods, computer readable media, and devices to automatically construct kill-chain from security alerts are disclosed. One method may include collecting a plurality of security alerts, receiving a selection of a high severity security alert associated with a node and a user from among the plurality of security alerts, creating a security narrative for the high severity security alert by providing a set of historical security alerts to a deep learning architecture, the set including security alerts selected based on a relation to the node and the user, and identifying a subset of the set of historical security alerts, including security alerts relevant to the high severity security alert, in a reverse time order by the deep learning architecture, and providing the security narrative as part of a response to the high severity security alert.