Methods for local page writes via pre-staging buffers for resilient buffer pool extensions are performed by computing systems. Compute nodes in database systems insert, update, and query data pages maintained in storage nodes. Data pages cached locally by compute node buffer pools are provided to buffer pool extensions on local disks as pre-copies via staging buffers that store data pages prior to local disk storage. Encryption of data pages occurs at the staging buffers, which allows a less restrictive update latching during the copy process, with page metadata being updated in buffer pool extensions page tables with in-progress states indicating it is not yet written to local disk. When stage buffers are filled, data pages are written to buffer pool extensions and metadata is updated in page tables to indicate available/valid states. Data pages in staging buffers can be read and updated prior to writing to the local disk.
Examples are disclosed that relate to fairly ordering financial market trades received from different market participant computers via a cloud computing network. In one example, a plurality of trades generated by a plurality of market participant computers are received. The trades are generated based at least on a financial market data point received by the plurality of market participant computers. Each trade is tagged with a delivery clock time stamp that tracks time in relation to financial market events that occur at a corresponding market participant computer. The trades are ordered based on the delivery clock time stamps and sent to a central exchange server computer. The central exchange server computer processes the trades.
The description relates to resource aware object detection for encoded video streams that can identify frames of the video stream that include an object of interest, such as a human, without decoding the frames.
H04N 19/177 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a group of pictures [GOP]
H04N 19/169 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
Techniques for identifying an exposed credential that, if used, would provide access to a resource are disclosed. The techniques enable the resource to remain online while (i) a new credential is allocated for the resource, (ii) the resource is transitioned to using the new credential instead of the exposed credential, and (iii) the exposed credential is attempted to be invalidated. A credential is accessed. This credential is suspected of being in an exposed state. The credential is accessible from within an artifact and is determined to be in the exposed state. A new credential is generated. This new credential is designed to replace the exposed credential. An instruction is transmitted to the resource to cause it to transition from using the exposed credential to using the new credential. The exposed credential is then invalidated.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
Using a language model attention matrix to facilitate a “code radar” source code navigation experience that highlights related source code locations. A computer system identifies a first source code location within source code that is displayed at a code editor user interface (UI). From a set of mappings generated based on a language model attention matrix, the computer system identifies a second source code location as being related to the first source code location. Concurrent with presenting the first source code location in the code editor UI, the computer system presents a related source code navigation experience, which includes both (i) presenting the second source code location in the code editor UI, and (ii) presenting a visual indication that the second source code location is related to the first source code location. Some embodiments include generating the set of mappings based on a language model attention matrix.
Systems are methods are used for facilitating identify anonymization by using controlled masking and encryption of user identifiers, such as UUIDs. A system that manages a UUID converts the UUID into a set of one or more different unique versions of the UUID for one or more corresponding different partner system(s) by removing and replacing masked portions of the UUID and by selectively encrypting the non-masked portions of the UUID. New masked portions added to the new version(s) of the UUID identify different corresponding partner(s) and/or rules to be applied by the different partner(s) when handling the different unique version(s) of the UUID(s). Partner systems that receive the new versions of the UUID identify and utilize the new masked portions to deterministically control decrypting and/or other processing of the new version of the UUID.
Embodiments detect cyberattack campaigns against multiple cloud tenants by analyzing activity data to find sharing anomalies. Data that appears benign in a single tenant's activities may indicate an attack when the same or similar data is also found for additional tenants. Attack detection may depend on activity time frames, on how similar certain activities of different tenants are to one another, on how unusual it is for different tenants to share an activity, and on other factors. Sharing anomaly analysis may utilize hypergeometric probabilities or other statistical measures. Detection avoidance attempts using digital entity randomization are revealed and thwarted. Authorized vendors may be recognized, mooting anomalousness. Although data from multiple tenants is analyzed together for sharing anomalies while monitoring for attacks, tenant confidentiality and privacy are respected through technical and legal mechanisms. Mitigation is performed in response to an attack indication.
Examples are disclosed that relate to generating expressive avatars using multi-modal three-dimensional face modeling and tracking. One example includes a computer system comprising a processor coupled to a storage system that stores instructions. Upon execution by the processor, the instructions cause the processor to receive initialization data describing an initial state of a facial model. The instructions further cause the processor to receive a plurality of multi-modal data signals. The instructions further cause the processor to perform a fitting process using the initialization data and the plurality of multi-modal data signals. The instructions further cause the processor to determine a set of parameters based on the fitting process, wherein the determined set of parameters describes an updated state of the facial model.
Systems and methods for generating a shared collaborative channel for collaboration are provided. In particular, a computing device may receive a request, from an originating member of an organization, to create the shared collaborative channel, the request including an invitee to be added to the shared collaborative channel. In response to receipt of the request, the computing device may provision a substrate group by creating a container associate with the shared collaborative channel including a substrate database associated with the shared collaborative channel, generate an invitation including a custom link to the shared collaborative channel for the invitee, and determine whether the invitee belongs to an originating collaboration team associated with the originating member based on the substrate database. If the invitee belongs to the originating collaboration team, the computing device may further update the substrate group to add the invitee as a new member of the shared collaborative channel.
Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.
A click-to-script service enables developers of big-data job scripts to quickly see the underlying script operations from optimized execution plans. Once a big-data job is received, the disclosed examples compile it and generate tokens that are associated with each operation of the big-data job. These tokens include may include the file name of the job, the line number of the operation, and/or an Abstract Syntax Tree (AST) node for the given operations. An original execution plan is optimized into an optimized execution plan, and the tokens for the original operations of the job script are assigned to the optimized operations of the optimized execution plan. The optimized execution plan is graphically displayed in an interactive manner such that users may view the optimized execution plan and click on its optimized operations to find the original operations of the job script.
Techniques for separating an image into a forward sweeping image and a backward sweeping image are disclosed. A lookup table maps MEMS projection positions on a display with corresponding pixel positions in an image generated by a camera facing the display. The lookup table is used to associate a first set of pixel positions in the image with a forward scanning sweep of the MEMS system. The lookup table is also used to associate a second set of pixel positions in the image with a backward scanning sweep of the MEMS system. The first and second sets of pixel positions are used to generate the forward sweeping image and the backward sweeping image, respectively. These images can then be used to calibrate the MEMS system to compensate for bi-phase.
H04N 9/31 - Projection devices for colour picture display
G02B 26/08 - Optical devices or arrangements for the control of light using movable or deformable optical elements for controlling the direction of light
A virtual network provider system supports a virtual network including virtual machines that are each assigned to an underlay address of an underlay addressing scheme. The virtual network provider system further includes multiple routing domains each defined to include a different subset of the virtual machines. Each of the routing domains is assigned to a range of overlay addresses of an overlay addressing scheme. For each routing domain, the assigned range of overlay addresses is allocated among the subset of the virtual machines in the routing domain. The system further includes a virtual network host configured to use addresses of the overlay addressing scheme to selectively route messages between endpoints on select pairs of the virtual machines assigned to a same routing domain of the plurality of routing domains.
This document relates to training and employing a quality estimation model. One example includes a method or technique that can be performed on a computing device. The method or technique can include providing degraded audio signals to one or more packet loss concealment models, and obtaining enhanced audio signals output by the one or more packet loss concealment models. The method or technique can also include obtaining quality labels for the enhanced audio signals and training a quality estimation model to estimate audio signal quality based at least on the enhanced audio signals and the quality labels.
G10L 25/60 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for measuring the quality of voice signals
G10L 19/005 - Correction of errors induced by the transmission channel, if related to the coding algorithm
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
G10L 25/69 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for evaluating synthetic or decoded voice signals
15.
IDENTIFYING AND CONSENTING TO PERMISSIONS FOR WORKFLOW AND CODE EXECUTION
The present invention extends to methods, systems, and computer program products for identifying and consenting to permissions for workflow and code execution. Aspects of the invention can be used to automatically scan a workflow or code definition to identify (potentially all) the actions/triggers a workflow or program intends to perform on behalf of a user. The user is shown the actions/triggers the workflow or program intends to perform (e.g., at a user interface) before consent to perform the actions/triggers is granted. As such, a user is aware of intended actions/triggers of a workflow or program before granting consent. Further, since actions/triggers are identified from the workflow or code definition (and not formulated by an author), permission requests better align with permissions that workflow or program functionality actually uses during execution.
G06F 12/0891 - Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches using clearing, invalidating or resetting means
G06F 21/51 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems at application loading time, e.g. accepting, rejecting, starting or inhibiting executable software based on integrity or source reliability
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
The present disclosure relates to systems, methods, and computer-readable media for identifying a variety of events that occur within a gaming session and generating event reports based on the identified events. For example, a gaming service (e.g., a cloud gaming server) can leverage content analysis and event recognizer services on a cloud computing system to detect one or more in-game events based on gaming content (e.g., video content, audio content, controller inputs) that is delivered to a client system. Systems described herein can train and implement event recognizers trained to track various in-game events across multiple gaming applications. Based on the tracked events, the systems described herein can generate event reports for events, individual users, and groups of users of the cloud computing system.
A63F 13/77 - Game security or game management aspects involving data related to game devices or game servers, e.g. configuration data, software version or amount of memory
A63F 13/75 - Enforcing rules, e.g. detecting foul play or generating lists of cheating players
A foldable computing device comprises a first frame rotatably coupled to a second frame. The second frame comprises a push-to-open mechanism comprising an actuator and a power switch located for actuation by the actuator. A detection mechanism detects a displaced position of the actuator that corresponds to releasing the foldable computing device from a closed configuration. Actuation of the power switch is detected and used with detection of the displaced position of the actuator to control an operating state of the computing device.
Embodiments of the present disclosure include techniques for machine language processing. In one embodiment, the present disclosure includes configuring functional modules on a machine learning processor to execute a plurality of machine learning (ML) operations during a plurality of time segments. During the time segments, a first portion of the ML operations execute serially and at least one other ML operation executes during at least a majority of the time of each of the time segments. Serial ML operations may be processed simultaneously with the at least one other ML operation.
Indirect time-of-flight camera systems for operating in multiple optical channels using active modulated light and accompanying methods of operation are provided. In one aspect, the indirect time-of-flight camera system includes first and second modulatable laser sources outputting light of different wavelengths for illuminating a target environment. The camera system further includes a wavelength-selective reflective element designed to reflect the light of a first wavelength and to transmit the light of a second wavelength. The camera system further includes a controller comprising instructions executable to control the camera system to, in a first time period, activate the first modulatable laser source and deactivate the second modulatable laser source, and in a second time period, deactivate the first modulatable laser source and activate the second modulatable laser source. The camera system further includes a photosensor for receiving the light outputted by the first and second modulatable laser sources.
Methods and systems cause display of email messages of a user on a screen of a computing system based on scores associated with the email messages. An email ranking system may have assigned the scores to the email messages. The scores are based on actions that other recipients of the email messages have taken with respect to the email messages. In calculating the scores, the actions of the other recipients may receive different weights based on how closely connected a recipient is to the user and a type of connection the recipient has to the user. A network graph may indicate how closely connected the recipient is to the user and the type of connection the recipient has to the user.
Examples are disclosed that relate to applying haptic output to a touch-sensitive input device. One example provides a touch-sensitive input device comprising a body, a haptic feedback mechanism within the body, a sensor subsystem, a logic processor, and a memory. The memory stores instructions executable by the processor to receive from the sensor subsystem sensor data indicating locations along the body of a plurality of contact points between a user hand and the body, based at least in part on the sensor data, determine a touch profile of the user hand applied to the body, based at least in part on the touch profile of the user hand, determine a selected haptic output to be applied to the body, and cause a drive signal to be transmitted to the haptic feedback mechanism to apply the selected haptic output to the body.
G06F 3/038 - Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
G06F 3/0354 - Pointing devices displaced or positioned by the user; Accessories therefor with detection of 2D relative movements between the device, or an operating part thereof, and a plane or surface, e.g. 2D mice, trackballs, pens or pucks
22.
TRANSFORMER-BASED TEXT ENCODER FOR PASSAGE RETRIEVAL
A computing system includes a logic subsystem and a storage subsystem holding instructions executable by the logic subsystem to implement a transformer-based text encoder. The transformer-based text encoder includes a plurality of transformer blocks previously-trained to apply encoding operations to computer-readable text representations of input text strings, the computer-readable text representations including computer-readable question representations of input text questions, and computer-readable passage representations of input text passages. The plurality of transformer blocks include a shared transformer block trained for both the computer-readable question representations and the computer-readable passage representations and a specialized transformer block including two or more input-specific subnetworks, and a routing function to select an input-specific subnetwork of the two or more input-specific subnetworks for each of the computer-readable text representations.
A computer implemented method includes receiving first firmware information at a hosting environment identifying that a user has selected user-controlled firmware for user virtual machines to be hosted on the hosting environment. A copy of the user-controlled firmware is obtained and a user virtual machine is deployed that includes the user-controlled firmware. The user-controlled firmware is locked against changes by the hosting environment absent receiving permission from the user.
A system provisioning resources of a processing unit. The system predicts a performance impact on a workload attributable to a performance constraint of the processing unit for the workload according to a resource model, wherein the workload includes a query and the resource model characterizes attainable compute bandwidth, attainable memory bandwidth, and arithmetic intensity based on peak compute bandwidth and peak memory bandwidth of the processing unit. The system determines a resource allocation of the processing unit, based on the predicted performance impact and instructs the processing unit to allocate the resources for processing the workload based on the determined resource allocation.
A systematic mechanism for visualizing functions or capabilities that an application has. One or more user experience objects are generated corresponding to an application. An application definition is obtained for that application, and then multiple user experience templates are identified based on that application definition. Information from the application definition is then used to populate at least one of the user experience templates to generate at least one object experience object. The user may then review visualizations of the user experience objects to determine the general capabilities of the application, and thereby determine whether to install or open the application, and how best to use the application.
Techniques for (i) using contextual information associated with an exposed credential to identify a resource that could be accessed using the exposed credential, (ii) identifying a responsible entity of that resource, and (iii) alerting the responsible entity about the exposed credential are disclosed. A credential is determined to be in an exposed state. The exposed credential, if used, could potentially provide an actor access to a resource, despite the fact that the actor should not have access to the resource. The exposed credential is analyzed to determine a context. Based on that context, the resource is identified. A responsible entity associated with the resource is identified. An alert is then sent to that entity.
Techniques for mitigating loss of vaporized working fluid in a two-phase immersion cooling system may be implemented using one or more supplemental condensers that facilitate condensation of vaporized working fluid when the immersion tank is open, and one or more vapor collection points that are in fluid communication with at least one supplemental condenser. One or more fluid displacement devices may be configured to create suction pressure at the one or more vapor collection points. One or more vents may be positioned in the door. The one or more vents may be configured to permit movement of air from outside the immersion tank into an interior portion of the immersion tank without permitting loss of vaporized working fluid. A directional blowing device may be configured to blow a gaseous substance against a computing device in a downward direction as the computing device is being pulled upward out of the immersion tank.
A general methodology is presented for optimizing a value at risk (VaR) associated with an allocation of objects (i.e., a strategy) having variable performance and loss characteristics. For purposes of illustration, investment strategies prescribing a portfolio of items from a set of candidates with unknown and generally correlated joint losses are discussed. The framework is based on approximating the VaR using nonparametric estimates of the portfolio loss density and, using mathematical insights, an efficient approach to computing the VaR gradient with respect to the strategy. The approach also allows inclusion of constraints on the strategy (e.g. a maximum fraction per item) and allows the VaR optimization problem to be solved using optimization techniques such as sequential quadratic programming.
The present disclosure relates to utilizing a hierarchical network communication system to efficiently manage and monitor a controlled hierarchical network. In particular, the hierarchical network communication system utilizes gateway services embedded among various architecture levels of a controlled hierarchical network to facilitate secure communications between levels of the hierarchical network as well as with an authorized external computing device or computing system. In various instances, the gateway service includes various components and elements that facilitate inter-network level communication as well as remote management, including monitoring, configuring, and upgrading components and resources at each level of the controlled hierarchical network. Indeed, the hierarchical network communication system facilitates the remote management of a controlled hierarchical network while upholding the strict security and communication protocols required for networks adhering to the Purdue Reference Architecture Model, ISA-95 standards, and ISA-99 standards.
The description relates to accelerator architectures for deep learning models. One example can obtain a deep learning training script associated with a deep learning model and extract an operator graph from the training script. The example can split the operator graph into first and second portions of a heterogeneous pipeline and tune a first accelerator core for the first portion of the heterogeneous pipeline and a second accelerator core for the second portion of the heterogeneous pipeline. The example can also generate a hardware architecture that includes the first accelerator core and the second accelerator core arranged to collectively accomplish the deep learning model.
Transparently providing a virtualization feature to an unenlightened guest operating system (OS). A guest partition, corresponding to a virtual machine, is divided into a first guest privilege context and a second guest privilege context. A compatibility component executes within the first guest privilege context, while a guest OS executes within the second guest privilege context. The compatibility component is configured to intercept input/output (I/O) operations associated with the guest operating OS. Based on the compatibility component intercepting an I/O operation associated with the guest OS, the compatibility component processes the I/O operation using a virtualization feature that is unsupported by the guest OS. Examples of the virtualization feature include accelerated access to a hardware device and virtual machine guest confidentiality.
Aspects of the present disclosure relate to systems and methods for sorting one or more files hosted by a collaborative application. In one aspect, one or more activity signals associated with one or more files hosted by the collaborative application may be received from a substrate. An activity-based sort order may be determined using at least a combination of the one or more activity signals. The activity-based sort order may be applied to sort the one or more files hosted by the collaborative application for display in a user interface to an activity object of the collaborative application.
Authentication request notifications are selectively suppressed, reducing notification fatigue and susceptibility to social engineering attacks. Authentication request notifications may be suppressed by not presenting a push notification on the user's phone. The authentication request may still be accessed and approved by manually opening the authenticator app. Notifications may be suppressed based on an estimation that the person attempting to login is not who they say they are. This estimation may be based on applying heuristics and/or machine learning models to the context of the login attempt, such as the IP address that originated the login request, time of day, recent user actions, patterns of previous logins, etc. One heuristic determines that the user has repeatedly ignored notifications caused by a particular IP address. Machine learning models generate a risk score from the login context, and notifications may be suppressed if the risk score exceeds a threshold.
Embodiments of the present disclosure include techniques for machine language processing. In one embodiment, the present disclosure include commands with data structures comprising fields describing multi-dimensional data and fields describing synchronization. Large volumes of data may be processed and automatically synchronized by execution of a single command.
A method of responding to a thermal management capacity reduction in a datacenter includes obtaining (236) process allocations assigned to a plurality of electronic devices in the datacenter and determining (238) a process priority list based on the process allocations assigned to the plurality of electronic devices. The method further includes monitoring (240) at least one cooling sensor configured to measure a thermal management capacity of a cooling system of the plurality of electronic devices and, in response to detecting a reduction in thermal management capacity, reducing (242) power delivery to at least one electronic device of the plurality of electronic devices based at least partially on the process priority list.
The present disclosure relates to systems, methods, and computer-readable media for extending functionality of unstructured data storage function (UDSF) nodes in supporting features and functionality of services and applications that are accessible via a core network. The systems described herein include a UDSF node having a UDSF data management system that enables network functions to interact with and modify data resources separately maintained by the UDSF node(s). A network function may selectively target discrete sets of blocks of data on records to access without accessing entire records and without issuing redundance application programming interface (API) calls to the USDF node(s). the UDSF node may be implemented in a core network to enhance network functions in fifth generation (5G) and beyond communication environments.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
G06F 3/06 - Digital input from, or digital output to, record carriers
37.
DEVICES, SYSTEMS, AND METHODS FOR A COOLING SYSTEM
A cooling system may include a tank filled with a first cooling fluid. The cooling system may include a container including a chamber, the chamber receiving a heat-generating component, the container being sealed, the container being at least partially submerged in the first cooling fluid in the tank, the container including a second cooling fluid.
Described herein is a technique to facilitate filtering during candidate retrieval stage performed by an information retrieval system that utilizes embedding models. An aNN indexing structure is created for each end-user, and in some instances, each activity type. This allows a single request for candidate content items to invoke a single process to obtain content items that satisfy the filtering criteria (e.g., in this case, the in-network requirement) from the separate per-end-user indexes.
An end-to-end service delivery system provides customers representing mobile network and enterprise operators with an online repository for services that are created from virtual network functions, and which are available from multiple service creators and operable across infrastructure underlying the customer's software-defined networking-based mobile network including diverse private, public, and hybrid cloud platforms. The network functions delivery system provides a user interface (UI) exposing a catalog of differentiated services of varying types. When the customer selects a service from the catalog, the service delivery system uses an installation engine to deploy the selected service on the customer's mobile network. The system provides a lifecycle management and orchestration engine that orchestrates the deployed service on an end-to-end basis across domains and network platforms. The service delivery system troubleshoots the service installation if deployment problems arise and notifies the customer of issues through the UI to provide recommendations and solutions.
H04L 41/40 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using virtualisation of network functions or resources, e.g. SDN or NFV entities
H04L 43/55 - Testing of service level quality, e.g. simulating service usage
40.
Neural network categorization accuracy with categorical graph neural networks
Neural network-based categorization can be improved by incorporating graph neural networks that operate on a graph representing the taxonomy of the categories into which a given input is to be categorized by the neural network based-categorization. The output of a graph neural network, operating on a graph representing the taxonomy of categories, can be combined with the output of a neural network operating upon the input to be categorized, such as through an interaction of multidimensional output data, such as a dot product of output vectors. In such a manner, information conveying the explicit relationships between categories, as defined by the taxonomy, can be incorporated into the categorization. To recapture information, incorporate new information, or reemphasize information a second neural network can also operate upon the input to be categorized, with the output of such a second neural network being merged with the output of the interaction.
Systems and methods for using a generative artificial intelligence (AI) model to generate a suggested draft reply to a selected message. A message generation system and method are described that use inferred context to improve the suggested draft reply message for the user. Various message data and additional context are obtained and included in a prompt provided to the AI model to improve suggested content. In some examples, the message data and additional context include a message thread history and previously sent messages, profile information of the sender and recipient(s) of the selected message, known relationship information between the sender and the user, etc. For instance, the user's preferred communication style and talking points can be inferred based on the profile data, relationship data, and the user's past communications with similar participants and used to tailor the suggested draft reply to the user.
G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
G06F 40/40 - Processing or translation of natural language
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
A technique uses a graph neural network (GNN) to determine whether a particular entity under consideration is engaging in abusive network-related activity over a computing network in collaboration with other entities. In some applications, the particular entity is part of a bot attack aimed at fraudulently engaging with advertisements. The technique trains the GNN by performing machine learning on a training set that includes a plurality of nodes, edges, and node labels. In forming the training set, the technique associates a feature set with each node in the training set that describes the network activity exhibited by that node's entity. The technique then connects each pair of nodes in the training set with an edge if the feature sets of the pair satisfy a prescribed test for similarity. The technique assigns labels to at least some nodes to convey whether the nodes are associated abusive network-related activity.
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
A computing system is provided, including a processor and memory storing instructions that cause the processor to execute a domain name service (DNS) log analyzer configured to identify a container identifier associated with a DNS request and a destination IP address associated with a DNS response to the DNS request, using one or more DNS logs, a fleet management system record analyzer configured to identify a first service associated with the container identifier and a second service associated with the destination IP address, using one or more fleet management system logs, and a dependency map generator configured to generate a service-to-service dependency map between the identified first service and the identified second service.
The techniques disclosed herein enable systems to translate three-dimensional experiences into user accessible experiences to improve accessibility for users with disabilities. Namely, the discussed system enables users with disabilities to create and personalize objects for use in the three-dimensional experience. This is accomplished by translating and grouping components from a three-dimensional space to form an intuitive and logical hierarchy. The grouped components are then organized into an accessible user interface which a user with disabilities can navigate using simplified inputs and assistive technologies. In this way, users with disabilities can be empowered to personalize their user experience and understand a three-dimensional space in a layered, well-defined format.
G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
G06F 3/04815 - Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
H04S 7/00 - Indicating arrangements; Control arrangements, e.g. balance control
45.
INTEROPERABILITY FOR TRANSLATING AND TRAVERSING 3D EXPERIENCES IN AN ACCESSIBILITY ENVIRONMENT
The techniques disclosed herein enable systems to translate three-dimensional experiences into user accessible experiences to improve accessibility for users with disabilities. This is accomplished by extracting components from a three-dimensional environment such as user avatars and furniture. The components are organized into component groups based on shared attributes. The component groups are subsequently organized into a flow hierarchy. The flow hierarchy is then presented to the user in an accessibility environment that enables interoperability with various accessibility tools such as screen readers, simplified keyboard inputs, and the like. Selecting a component group, and subsequently, a component through the accessibility environment accordingly invokes functionality within the three-dimensional environment. In this way, users with disabilities are empowered to fully interact with three-dimensional experiences.
G06F 3/04815 - Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
46.
PROVIDING RECENT EVENT INFORMATION FOR WEB SEARCH QUERIES
An electronic device may identify one or more search queries occurring frequently in a query log during a temporal period and maintain, for each of the one or more search queries, a frequency count of the search query occurring in the query log. The device may identify, a plurality of uniform resource locators (URLs) and match, one or more URLs of the plurality of URLs based on text of the URLs. The device may generate a news event profile for each search query and add each of the matching URLs into a respective news event profile. The device may receive a query from a user and identify, a matching news event profile. The device causes URLs of the matching news event profile and one or more related search queries from the first group of search queries to be presented to the user.
A set of geometric shapes to be applied by a machine learning model to objects identified in image data is defined. A learning rate of the machine learning model is updated in response to external events. The machine learning model is used to estimate spatial parameters for each of the objects identified in the image data. The spatial parameters are estimated by fitting the objects to the set of geometric shapes. Updates to the spatial parameters are temporally integrated. A spatial estimate of the objects identified in the image data is generated.
This document relates to performing live video stream analytics on edge devices. One example determines resources available to the system, and a video analytics configuration is selected that distributes work between edge devices and cloud devices in a cascading manner, where edge device processing is prioritized over cloud processing in order to conserve resources. This example can dynamically modify the allocation of processing depending on changing conditions, such as network availability.
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06V 20/40 - Scenes; Scene-specific elements in video content
Techniques for correcting an overlay misalignment between an external camera image and a system camera image are disclosed. A first system camera image and a first external camera image are acquired. A first visual alignment is performed between those two images to produce an overlaid image. Some of the content in the overlaid image is surrounded by a bounding element. A position of the bounding element is modified based on movements of the system camera and/or the external camera. In response to performing a second visual alignment using new images, an update vector is computed. Relative movement between the two cameras is determined. Based on the movement and based on the update vector, the bounding element is progressively transitioned to a corrected position in the overlaid image. A speed by which the bounding element is progressively transitioned is proportional to the amount of movement.
Physical layouts of Majorana-based qubits for implementations of pentagonal tilings are described. An example quantum device comprises a set of tetrons for enabling Majorana-based qubits. The set of tetrons is arranged in a lattice to allow pentagonal tilings associated with the set of tetrons. The vertices of the pentagonal tilings relate to the qubits and single qubit operations, and the edges of the pentagonal tilings (connecting different vertices) relate to 2-qubit operations acting on a pair of qubits connected by a given edge. As an example, the 1-qubit Pauli measurements relate to the operations performed on the vertices associated with the pentagonal tilings and the 2-qubit measurements relate to the operations performed along the edges of the pentagonal tilings.
A method for automatically identifying a root cause of customer dissatisfaction with a software product and creating feedback items to improve the software product includes collecting engagement data pertaining to interactions between a customer and a flow of visual elements presented by the software product and detecting a trigger event indicating that the customer is dissatisfied with the software product. In response to the trigger event and based at least in part on the engagement data, a potential deficiency of the software product is automatically identified and a repair ticket is generated for a development team. The repair ticket identifies the potential deficiency of the software product.
The present disclosure relates to methods and systems for automatically providing a suggestion to delay sending a message that is being composed by a user to send to a chat participant using a chat feature of an application. The suggestion is sent in response to determining that one or more trigger conditions occurred. The suggestion includes a scheduled time to send the message. The methods and systems send the delayed message at the scheduled time.
A method of encoding video streams includes, at an encoding device, receiving a first video stream frame from a first server device at the encoding device at a first receipt time; receiving a second video stream frame from a second server device at the encoding device at a second receipt time; encoding the first video stream frame with the encoding device; determining a delay duration based at least partially on a first encoding duration of the first video stream frame and the second receipt time; and transmitting a delay instruction based at least partially on the delay duration to the second server device.
H04N 19/42 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals - characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
H04N 19/136 - Incoming video signal characteristics or properties
H04N 19/172 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
H04N 19/40 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video transcoding, i.e. partial or full decoding of a coded input stream followed by re-encoding of the decoded output stream
54.
SYSTEM FOR DETECTING LATERAL MOVEMENT COMPUTING ATTACKS
A method may include receiving from a first computing device, metadata that includes a suspected malicious activity indicator and a device identifier associated with the indicator; receiving, from a second computing device, log activity data; matching the device identifier included in the metadata to a device identifier in the log activity data; and based on the matching, transmitting an alert identifying the second computing device as a source of the suspected malicious activity.
Some embodiments help manage cybersecurity insider risk. An authorized user influence pillar value is based on an influence signal representing the user's actual or potential influence in a computing environment. An authorized user access pillar value is based on an access signal representing the user's actual or potential access to resources. An impact risk value is calculated as a weighted combination of the pillar values. In response, an embodiment automatically adjusts a cybersecurity characteristic, such as a security risk score, security group membership, threat detection mechanism, or alert threshold. In some cases, impact risk is also based on a cumulative potential exfiltration anomaly access signal. In some cases, impact risk is based on one or more values which represent user public visibility, user social network influence, brand damage risk, resource mission criticality, access request response speed or success rate, or a known cybersecurity attack.
A computing system including a quantum computing device and a classical computing device. The computing system computes an estimated unitary matrix over a plurality of iterations that each include, at a processor, computing a current-iteration exponent, a current-iteration error parameter, and a conjugate transpose of a current-iteration estimate of the unitary matrix. Each iteration further includes transmitting the current-iteration exponent, the current-iteration error parameter, and the conjugate transpose to the quantum computing device. At the quantum computing device, each iteration further includes computing a process tomography result and outputting the process tomography result to the classical computing device. At the processor, each iteration further includes computing a distance measure between the current-iteration estimate and the process tomography result, and, when the distance measure is below a predefined constant, updating the current-iteration estimate. The computing system outputs, as the estimated unitary matrix, the updated current-iteration estimate computed in a final iteration.
Embodiments described herein enable at least one of a plurality of entities to access data protected by a security policy in response to validating respective digital access requests from the entities. The respective digital access requests are received, each comprising a proof. For each request, an encrypted secret share is obtained from a respective ledger database. Each request is validated based at least on the respective encrypted secret share and the proof, without decrypting the respective encrypted secret share. In response to validating all of the requests, a verification that an access criteria of a security policy is met is made. If so, at least one of the entities is provided with access to data protected by the security policy. In an aspect, embodiments enable a blind subpoena to be performed. In another aspect, embodiments enable the at least one entity to access the data for an isolated purpose.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
A display system includes an integrated laser and modulator device and a display assembly. The integrated laser and modulator device includes a laser component configured to facilitate light emission responsive to applied current and a modulator component configured to selectively modulate light responsive to applied signal. The modulator component is integrally coupled to the laser component via a bridging structure that intervenes between the laser component and the modulator component. At least a portion of the bridging structure facilitates power reflectivity into a laser cavity of the laser component. The bridging structure facilitates transmission of light emitted by the laser component into the modulator component for modulation by the modulator component to provide modulated light. The display assembly is configured to direct the modulated light provided by the integrated laser and modulator device to illuminate pixels to form an image.
G02F 1/17 - Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour based on variable-absorption elements not provided for in groups
G09G 3/02 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes by tracing or scanning a light beam on a screen
A computing system is described, where the computing system includes a processor and memory storing instructions that, when executed by the processor, cause the processor to perform several acts. The acts include receiving a query from an application executing on a client computing device that is in network communication with the computing system. The acts also include searching a computer-readable index of items based upon the query, identifying an item based upon the searching of the computer-readable index, transmitting the query to a computer-implemented model, and obtaining content generated by the computer-implemented model, where the computer-implemented model generated the content based upon the query. The acts further include returning at least one of the item or the content to the client computing device for presentment by way of the application executing on the client computing device.
A method of and system for automatically generating an ink note object is carried out by detecting receipt of a digital ink input on a user interface (UI) screen, the UI screen being displayed by an application and being associated with at least one of a document, a page or an event. Once digital ink input is detected, the digital ink input is captured. Additionally, contextual data associated with the digital ink input is collected, the contextual data being related to at least one of the document, the page, the event, and a user providing the digital ink input. An ink note object is then generated and stored for the digital ink input, the ink note object including the captured digital ink input and the contextual data, and the ink note object being an entity that is separate from the document, the page and the even.
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation
61.
INFERRING AND CONTEXTUALIZING A STRANGER ON AN ENTERPRISE PLATFORM
Systems and methods for inferring and contextualizing a stranger on an enterprise platform are provided. The method includes generating a familiarity score between a user and an individual. Based on the generated familiarity score, the individual is determined to be a stranger to the user and a contextualized summary of the stranger is generated. The generated contextualized summary of the stranger is presented to the user in response to an upcoming interaction between the user and the stranger or a detected interaction between the user and the stranger.
Systems and methods for identifying and evicting idle sessions include training a machine learning model as a session classifying model to learn rules for classifying active sessions between clients and the cloud-based service. The session classifying model is trained to receive a plurality of parameters pertaining to the document associated with an active session as input and to apply the rules to the plurality of parameters to determine a classification for the active session and to provide an output indicative of the classification for the active session. The session classifying model is then utilized in the cloud-based service to classify the active sessions. The active sessions classified as idle sessions may then be evicted from the cloud-based service.
Clouds in a satellite image are replaced with a prediction of what was occluded by those clouds. The cloudy portion of the image is interpolated from a series of satellite images taken over time, some of which are cloud-free in the target image's cloudy portion. In some configurations, clouds are removed taking into account each pixel's availability—a measure of certainty that a pixel is cloud-free. Furthermore, these images may have been taken under different amounts of illumination, making it difficult to determine whether a difference between two images is due to a change in illumination or a change to the location. The effect of illumination on each image is removed before interpolating the cloudy portion of the image. In some configurations, removing the effect of illumination also takes into account pixel availability.
G06V 10/60 - Extraction of image or video features relating to illumination properties, e.g. using a reflectance or lighting model
G06T 7/90 - Determination of colour characteristics
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/26 - Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
G06V 10/56 - Extraction of image or video features relating to colour
G06V 10/74 - Image or video pattern matching; Proximity measures in feature spaces
Methods for evaluating quantum computing circuits in view of the resource costs of a quantum algorithm are described. A processor-implemented method for performing an evaluation of a polynomial corresponding to an input is provided. The method includes determining a polynomial interpolation for a set of sub-intervals corresponding to the input. The method further includes constructing a quantum circuit for performing, in parallel, polynomial evaluation corresponding to each of the set of sub-intervals.
Systems, methods, and software are disclosed herein that allow multiple values to be stored and referenced individually in a spreadsheet or table cell. In an implementation, an application identifies a format of a cell in a spreadsheet with a format having multiple data points. The application receives multiple values corresponding to the multiple data points and stores each value of the multiple values in the cell as a separately referenceable value with respect to each other value of the multiple values. In some implementations, formulas in other cells or sub-routines can reference an individual one of the values in the cell.
A failure recommendation system for a command line interface (CLI) uses machine learning to predict the most likely command to correct an unsuccessful or failed attempt to perform an intended operation using the CLI. The failure recommendation system is based on a conditional probability model trained on failure-success pairs of commands from CLI telemetry data to learn the most likely command to remediate a failure. The conditional probability model predicts the most likely command based on a failure type and the failed command. The failure type is identified through a failure type classifier and is used to select the most likely command to remediate a failure from the different events that may lead to a failure.
Systems and methods directed to generating a predicted quality metric are provided. Telemetry data may be received from a from a first group of devices executing first software. A quality metric for the first software may be generated based on the first telemetry data. Telemetry data from a second group of devices may be received, where the second group of devices is different from the first group of devices. Covariates impacting the quality metric based on features included in the first telemetry data and the second telemetry data may be identified, and a coarsened exact matching process may be performed utilizing the identified covariates to generate a predicted quality metric for the first software based on the second group of devices.
In some examples, matrix based bot implementation may include obtaining, for a plurality of bots that are used to respond to a query, a matrix that includes entries including a plurality of scenarios, a plurality of questions corresponding to the plurality of scenarios, and a plurality of responses. Each response may correspond to a specified question. A plurality of scripts may be generated based on an analysis of the matrix. Each script may include at least one question followed by at least one response, and further followed by at least one scenario. For each script, a closest pre-existing script may be identified based on a comparison of the script to pre-existing scripts. For each script, a modification to the matrix may be generated based on a difference in the script from the closest pre-existing script. The bots may be utilized to respond to the query based on the modified matrix.
A document re-finding system generates embeddings for concept clips provided by a user, the concept clips defining a concept for searching for content of interest to the user in a plurality of documents previously seen by the user. The re-finding system determines semantic relationships between the concept and document clips, related to respective document among the plurality of documents, based on the concept embedding and embeddings generated for the document clips. A graphical user interface depicting the semantic relationships is rendered to the user and is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.
Systems are provided for improving computer security systems that are based on user risk scores. These systems can be used to improve both the accuracy and usability of the user risk scores by applying multiple tiers of machine learning to different the user risk profile components used to generate the user risk scores and in such a manner as to dynamically generate and modify the corresponding user risk scores.
Example aspects include techniques for query processing over deep neural network runtimes. These techniques include receiving a query including a query operator and a trainable user defined function (UDF). In addition, the techniques include determining a query representation based on the query, and determining, for performing the query in a neural network runtime, an initial neural network program based on the query representation, the initial neural network program including a differentiable operators corresponding to the query operator. and executing the neural network program in the neural network runtime over the neural network data structure to generate a query result. Further, the techniques include training the initial neural network program via the neural network runtime to determine a trained neural network program, and executing the trained neural network program in the neural network runtime to generate inference information.
The techniques disclosed herein enable a realistic, inclusive sense of physical presence for videoconference participants that is comparable to in-person communication. Multiple users are simultaneously provided with an immersive experience without the need for head-mounted displays or other wearable technology. Specifically, a real-time three-dimensional model of a scene at the remote end of the videoconference is received. At the same time, the location and perspective of each local participant is determined. Each local participant is then individually provided with a spatially correct stereoscopic view of the model. The sense of physical presence is created by changing what each local participant sees in response to a change in their perspective. The sense of physical presence is enhanced by enabling direct eye contact, clear communication of emotional state and other non-verbal cues, and a shared visual experience and audio ambience across locations.
Systems, methods, and computer-readable storage devices are disclosed for simulated choral audio chatter in communication systems. One method including: receiving audio data from each of a plurality of users participating in a first group of a plurality of groups for an event using a communication system; generating first simulated choral audio chatter based on the audio data received from each of the plurality of users in the first group; and providing the generated first simulated choral audio data to at least one user of a plurality of users of the event.
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
A rainbow artifact mitigation system includes an angular dependent filter configured to receive light and to transmit light according to one or more angular transmission functions. The one or more angular transmission functions define light transmission as a function of incident angle for the angular dependent filter, The angular dependent filter is configured to at least partially mitigate transmission of light for at least some incident angles above 40°. The angular dependent filter comprises a plurality of nanostructures, and the nanostructures of the plurality of nanostructures are arranged in an array with one or more sub-wavelength periods. The one or more angular transmission functions comprise at least two different angular transmission functions for different regions of the angular dependent filter.
Techniques for using transfer learning to address label data shortage in seniority modeling for an online service are disclosed herein. In some embodiments, a computer-implemented method comprises training an initialized neural network using training examples comprising profile data and labels for the profile data, where each label comprises a standardized position title, and the training of the initialized neural network forms a pre-trained neural network. Next, the computer system may train the pre-trained neural network using training examples comprising profile data and labels for the profile data, where the labels comprise a position seniority, and the training of the pre-trained neural network forms a fine-tuned neural network. The computer system may then compute the position seniority for a user based on profile data of the user using the fine-tuned neural network, and use the position seniority of the user in an application of an online service.
An access control system is disclosed for controlling access to a resource. A request is received by a location attribute policy (LAP) server to access an encrypted resource. The LAP server accesses a resource policy that identifies requirements for granting access to the encrypted resource, such as a list of attributes of the requestor that are required and a dynamic attribute requirement of the requestor. The LAP server receives a cryptographic proof from the computing device that the requestor possesses the attributes and validates the proof based at least on information obtained from a trusted ledger. Once the proof is validated, the LAP server provides a shared secret associated with the dynamic attribute requirement to a decryption algorithm. The decryption algorithm uses the dynamic attribute shared secret in combination with one or more attribute shared secrets from the requestor to generate a decryption key for the encrypted resource.
The automated generation of an emphasis image (such as a cropped image) that is based on an input image. The input image is fed to a machine-learned model that is trained to label portions of images. That machine-learned model then outputs an identification of multiple portions of images, along with potentially labels of each of those identified portions. The label identifies a property of the corresponding identified portion. As an example, one portion might be labelled as irrelevant, another might be labelled as a name, another might be labelled as a comment, and so forth. That output is accessed and the generated label is used to determine an emphasis bounding box. The emphasis bounding box is then applied to the input image to generate an emphasis image. As an example, the emphasis image may be a cropped image of the input image.
Techniques are described herein that are capable of providing privacy-preserving rules-based targeting using machine learning. Ranks are assigned to entities using a machine learning model. Values of each targetable feature associated with the respective entities are ordered. For each targetable feature, the entities are sorted among bins based on the values of the feature associated with the respective entities. For each targetable feature, a bin is selected from the bins that are associated with the feature based on the selected bin including more entities having respective ranks that are within a designated range than each of the other bins that are associated with the feature. A targeting rule is established, indicating a prerequisite for targeting an entity. The prerequisite indicating that the value of each targetable feature associated with the entity is included in a respective interval associated with the selected bin for the feature.
A touch-screen display device comprises a series of column electrodes and a series of row electrodes, with an electronic display layer arranged behind the series of column electrodes and behind the series of row electrodes. The series of row electrodes crosses the series of column electrodes such that the electrical impedance at each crossing of a row and column electrode is responsive to the proximity of a touch input to that crossing. A row-drive circuit is configured to apply an excitation signal to a selected row electrode and to concurrently apply a compensation signal to one or more other row electrodes, the compensation signal being out of phase with respect to the excitation signal. A column-sense circuit is configured to sense a column signal from the series of column electrodes and to provide a corresponding column output.
An enhanced user experience is disclosed herein that provides for gesture-based configuring of pivot tables. In various implementations, a pivot table includes query areas associated with fields of a data table being summarized by the pivot table. Gestures made with respect to an area of the pivot table drive changes in the association of the fields of the data table with the query areas of the pivot table. As user input is received with respect to an area of the pivot table, relevant fields are identified, and new associations are made between the query areas and the fields. The pivot table may then be updated accordingly based on the new associations.
G06F 40/18 - Editing, e.g. inserting or deleting using ruled lines of spreadsheets
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
Systems are provided for logging transactions in heterogeneous networks that include a combination of one or more instrumented components and one or more non-instrumented components. The instrumented components are configured to generate impersonated log records for the non-instrumented components involved in the transaction processing hand-offs with the instrumented components. The impersonated log records are persisted with other log records that are generated by the instrumented components in a transaction log that is maintained by a central logging system to reflect a complete flow of the transaction processing performed on the object, including the flow through the non-instrumented component(s).
H04L 41/0631 - Management of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
H04L 43/04 - Processing captured monitoring data, e.g. for logfile generation
A display pose of a client computing device is computed in a hybrid manner using both the client computing device and a server. Using the client computing device, an initial pose of the client computing device at an initial time is computed. A prospective pose at a target time is predicted using the client computing device. The prospective pose is sent along with auxiliary data from the client computing device to the server and a display pose of the client computing device at a display time is computed. The display pose is computed using the prospective pose and the auxiliary data.
A system provides dynamically controlled participation allocations for communication sessions. A system can create a queue for participants of a communication session, such as an online meeting. The queue can be generated for a communication session having an intended format that allows participants to individually speak in succession, such as a Question and Answer (Q&A) session. The system manages a user interface (UI) of the communication session displaying a timer that changes dynamically for each participant indicating a total time for his or her questions or comments based on an amount of time left for the meeting to end. The system displays, augments, and associates a timer for each participant indicating a total time for his or her questions or comments, which is based on an amount of time left for the meeting to end, number of users providing a “hand raise” input, and history of participation for each participant.
H04L 65/1093 - In-session procedures by removing participants
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
In various examples there is a method performed by a controller in Kubernetes cluster. The method comprises: identifying a job to be completed by the cluster, from a plurality of jobs. In response to identifying a job to be completed by the cluster, determining at least one sidecar container associated with the job. In response to identifying a job to be completed by the cluster, determining that the job has been completed by querying a Kubernetes control plane of the cluster. In response to determining that the job has been completed, triggering termination of the sidecar container.
Generally discussed herein are devices, systems, and methods for digital signature generation security. A method can include generating, by a first device, a first random number, in generating a signature for a communication, masking, using the first random number, only a private key, a hash of the communication, or a combination thereof, and providing the signature with the communication to a second device.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
86.
DETERMINATIONS OF MODIFICATIONS IN OBJECTS HAVING NESTED CHILD OBJECTS
According to examples, an apparatus may include a processor and a memory on which is stored instructions that may cause the processor to determine that information has been inputted into an object, the object including a child object nested within the object. The instructions may also cause the processor to generate a child-object hash value based on contents of the child object, generate a hash value for the object based on contents of the object, the contents of the object including the child-object hash value, and determine whether the generated hash value differs from a stored hash value, the stored hash value corresponding to contents of the object without the inputted information. The instructions may also cause the processor to, based on a determination that the generated hash value differs from the stored hash value, save the object including the child object nested within the object.
G06F 9/451 - Execution arrangements for user interfaces
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 16/215 - Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
H04L 9/06 - Arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
87.
END-TO-END SECURE COMMUNICATIONS FOR PRIVILEGED 5G NETWORK TRAFFIC
Software-defined networking and network function virtualization constructs are leveraged across diverse portions of 5G network infrastructure including radio access network, mobile core, and wide area network to enable a security property to be implemented for a network slice from end-to-end to provide for strong logical and/or physical isolation of slice traffic from other network traffic. One or more network slice controllers are implemented in the 5G network that are interoperable as separate elements, or under centralized control, to enable the underlying diverse network infrastructure to be abstracted and virtualized so that infrastructure properties can be mapped across infrastructure types for the end-to-end slice. Network resources may be dynamically allocated based on real-time traffic demands to instantiate the end-to-end network slices on a customized basis to meet particular quality of service parameters for various traffic types, including privileged traffic that may be prioritized when resources become scarce and network congestion occurs.
A system for adding persistence to SPAD imagery is configurable to capture, using a SPAD array, a plurality of image frames. The system is configurable to capture, using an IMU, pose data associated with the plurality of image frames. The pose data includes at least respective pose data associated with each of the plurality of image frames. The system is configurable to determine a persistence term based on the pose data. The system is also configurable to generate a composite image based on the plurality of image frames, the respective pose data associated with each of the plurality of image frames, and the persistence term. The persistence term defines a contribution of each of the plurality of image frames to the composite image.
G09F 9/33 - Indicating arrangements for variable information in which the information is built-up on a support by selection or combination of individual elements in which the desired character or characters are formed by combining individual elements being semiconductor devices, e.g. diodes
G06T 7/207 - Analysis of motion for motion estimation over a hierarchy of resolutions
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/75 - Image or video pattern matching; Proximity measures in feature spaces using context analysis; Selection of dictionaries
H01L 31/107 - Devices sensitive to infrared, visible or ultraviolet radiation characterised by only one potential barrier or surface barrier the potential barrier working in avalanche mode, e.g. avalanche photodiode
An automated tuning service is used to automatically tune, or modify, the operational parameters of a large-scale cloud infrastructure. The tuning service performs automated and fully data/model-driven configuration based from learning various real-time performance of the cloud infrastructure. Such performance is identified through monitoring various telemetric data of the cloud infrastructure. The tuning service leverages a mix of domain knowledge and principled data-science to capture the essence of our cluster dynamic behavior in a collection of descriptive machine learning (ML) models. The ML models power automated optimization procedures for parameter tuning, and inform administrators in most tactical and strategical engineering/capacity decisions (such as hardware and datacenter design, software investments, etc.). Rich “observational” models (models collected without modifying the system) are combined with judicious use of “fighting” (testing in production), allowing the tuning service to automatically configure operational parameters of a large cloud infrastructure for a broad range of applications.
Examples are disclosed that relate to using natural language processing (NLP) to determine a recipe for a chemical synthesis described in a text to create a life cycle inventory (LCI). One example provides a method comprising receiving an input of a text from a publication comprising a description of a chemical product, and analyzing the text using NLP to determine a recipe for the chemical synthesis, the recipe comprising and action and action metadata, the action metadata comprising a reactant. The method further discloses obtaining LCI information for the reactant, determining an energy utilized for the action, and creating an estimate of an environmental impact for the product.
Example solutions for voice biometrics for anonymous identification and personalization capture an audio signal containing voice signal from a speaker. A plurality of unlabeled voiceprints are stored that are each associated with an anonymous label. The speaker's voice signal is recognized as matching one of the unlabeled voiceprints, enabling identification of the associated anonymous label. Historical information associated with the identified anonymous label is used to generate an alert specific to the speaker. Example practical applications include leveraging a customer relations management (CRM) interaction record to provide a personalized experience to the speaker and providing a warning to a user that the speaker is on a watchlist. These and other practical applications are possible, even though the speaker's identity may be unknown, and the speaker has not enrolled in a voice biometric system. Solutions for generating the unlabeled voiceprints are also disclosed.
G10L 17/06 - Decision making techniques; Pattern matching strategies
G10L 17/02 - Preprocessing operations, e.g. segment selection; Pattern representation or modelling, e.g. based on linear discriminant analysis [LDA] or principal components; Feature selection or extraction
A subset of data that includes a feature may be selected from a dataset. Parameters from the selected subset of data are determined and an extreme value theory (EVT) algorithm is implemented to determine a probability value for the feature based at least in part on the determined parameters. Based on the determined probability value for the feature, an outlier score is generated for the feature. Based on the outlier score being above a threshold, the subset is identified as anomalous.
The present disclosure relates to methods and systems for providing a neural graphical model. The methods and systems generate a neural view of the neural graphical model for a domain. The input data is generated from the domain and includes generic input data. The input data also includes a combination of different data types of input data. The neural view of the neural graphical model represents the functions of the different features of the domain using a neural network. The functions are learned for the features of the domain using a dependency structure of an input graph for the input data and the neural network. The methods and systems use the neural graphical model to perform inference tasks. The methods and systems also use the neural graphical model to perform sampling tasks.
In an example embodiment, a blending model is presented based on a linear programming approach. The blending model produces a slate of sponsored and non-sponsored pieces of content for display in a graphical user interface, with the ordering and placement of the sponsored and non-sponsored pieces of content selected in order to maximize an objective function. Such an approach can fine tune each piece of content using content-level parameters and holistically examine global constraints and opportunities. It establishes a robust optimization framework that can adapt to content and domain changes without requiring tuning through online experiments.
A workload management system includes a workload management tool configured to generate a workload context associated with a workload generated based on interactions of a user with workload initiation controls presented within a user interface (UI) of a client application. The workload context includes instructions for transmitting the workload context from a main browser session to a first background browser session; executing the workload within the first background session; and for configuring a first event handler within the main session to wait for a first event generated within the first background session in association with execution of the workload and, in response to receipt of the first event, transmit the client application an instruction to present workload status information in the user interface.
A data processing system implements obtaining, at a file services platform, first mapping information by mapping files, folders, or a combination thereof stored on each of a plurality of client devices associated with a first user. The data processing system further implements synchronizing the first mapping information with the plurality of client devices, receiving a first request for a first file from a first client device of the plurality of client devices, where the first file stored locally on a second client device of the plurality of client devices. The data processing system further implements requesting that the second client device upload an instance of the first file to the file services platform; receiving the instance of the first file from the second client device; and causing the first client device to download the instance of the first file from the file services platform to the first client device.
A first data connector for communicating data with a second data connector includes a data communication interface including adjacent radiofrequency antenna elements, wherein a plurality of the adjacent radiofrequency antenna elements forms a radiofrequency data antenna array and another radiofrequency antenna element of the adjacent radiofrequency antenna elements forms a radiofrequency control channel antenna element, each radiofrequency antenna element of the radiofrequency data antenna array being configured to communicate a subchannel signal of the data to a corresponding radiofrequency data antenna element of a data communication interface of the second data connector bidirectionally. The radiofrequency control channel antenna element is configured to manage data communications through the radiofrequency data antenna array. An attachment interface is positioned on the first data connector and configured to removably attach the first data connector to the second data connector.
H04B 7/24 - Radio transmission systems, i.e. using radiation field for communication between two or more posts
H01Q 1/22 - Supports; Mounting means by structural association with other equipment or articles
H01Q 21/08 - Arrays of individually energised antenna units similarly polarised and spaced apart the units being spaced along, or adjacent to, a rectilinear path
H04B 1/38 - Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
98.
SYSTEM AND METHOD FOR DETERMINING CRITICAL SEQUENCES OF ACTIONS CAUSING PREDETERMINED EVENTS DURING APPLICATION OPERATIONS
A system and method to collect an actions list of action sequences in an application leading to a predetermined resulting event, create pairs of the action sequences, apply a fitting alignment to the action sequence pairs to create fitted action sequence pairs, wherein non-matching data between fitted action sequences of each pair is replaced with gaps to ensure that the first and second fitted action sequences are of equal length and are aligned with one another with the gaps being located at index positions the fitted action sequences corresponding to index positions of non-matching data, and delete data, for each of the fitted action sequence pairs, corresponding to the gaps to create a critical sequence of actions for each of the fitted action sequence pairs representing, respectively, common actions of the fitted action sequences of each of the fitted action sequence pairs leading to the predetermined resulting event.
A technique facilitates interaction among meeting participants for a purpose of verifying meeting attendance. The technique includes the operations of: using a programmatic interface to query a data structure to discover first information regarding meetings that a user is scheduled to attend; using the programmatic interface to query the data structure to discover second information regarding participants of a particular meeting; generating a likelihood measure, based on the second information, that specifies a likelihood that the particular meeting will take place; displaying the first information, second information, and a representation of the likelihood measure in a user interface presentation; generating and presenting a graphical control that invites the user to take a computer-implemented action pertaining to the particular meeting; and, in response to activation of the graphical control, performing the computer-implemented action. In some cases, the action involves sending an electronic message to at least one meeting participant.
The techniques disclosed herein enable a guest operating system (OS) to access and use a media processing component configured on a host OS. The guest OS provides, via an API, a request to create an instance of the media processing component (e.g., a codec, an encryption/decryption component, a DRM component). In association with the request, the guest OS allocates space in memory for media data that is to be processed by the instance of the media processing component configured on the host OS. The guest OS stores the input media data in the allocated memory and provides, via the API, reference(s) to locations of the allocated memory. The reference(s) to the locations of the allocated memory enable the host OS to retrieve the input media data and process the input media data using the instance of the media processing component configured on the host OS.
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