Abstract: The disclosure provides an approach for on-demand application delivery. Embodiments include determining, by an application delivery component on a computing device, a user logon event. In response to the user logon event, embodiments include receiving, from an application management server separate from the computing device, shortcut information for a set of applications associated with the user and displaying, on the computing device, simulated shortcuts for the set of applications based on the shortcut information. Embodiments include receiving, at the computing device, user input selecting a simulated shortcut of the simulated shortcuts that corresponds to an application of the set of applications.

Abstract: Techniques to generate driving scenarios for autonomous vehicles characterize a path in a driving scenario according to metrics such as narrowness and effort. Nodes of the path are assigned a time for action to avoid collision from the node. The generated scenarios may be simulated in a computer.

Abstract: A system includes a memory and a processor. The memory stores a queue that includes a sequence of slots, each of which is configured to store a request. The processor receives, from a user device, a request for information. In response, the processor stores the request in an end slot of the queue. The processor collects values for parameters associated with the system. The processor determines, based on the request and the collected values for the parameters, an estimate of a time to generate a response to the request. Generating the response includes identifying an application for use in generating the response, generating, based on a set of videos of processes previously performed using the application, instructions for interfacing with the application to generate the response, and executing the instructions to interface with the application. The processor further transmits, to the user device, the estimate of the time.

Abstract: A system includes a memory and a processor coupled to the memory. The processor receives a user credential associated with a first user and authorizes an avatar of the first user to enter a virtual environment. When the first user is registered with a first entity, the processor obtains a user profile of the first user. Based on the user profile, the processor determines and indicates to the first user in the virtual environment that a first type of data file of the first user qualifies the first user to obtain a product or service for a first amount of data objects. The processor receives a selection of the product of service from the first user, receives a command to transfer the first amount of data objects from the first type of data file to a second data file, and transfers the first amount to the second data file.

Abstract: A representation of a first set of weights associated with a vehicle prior to a drive are received, the vehicle including a plurality of axles, a plurality of wheels attached to the plurality of axles, and a load. A warning is caused to be output in response to at least one weight from the first set of weights being outside a predetermined range. Longitudinal and lateral dynamics associated with the vehicle during the drive are determined. A second set of weights associated with at least one axle from the plurality of axles during the drive are determined. A determination is made if at least one remedial action should be performed based on the longitudinal dynamics, the lateral dynamics, and the second set of weights. In response to determining that the at least one remedial action should be performed, the at least one remedial action is caused to be performed.

Abstract: A device configured to identify automated process instructions for a network device. The automated process instructions include instructions for performing a series of actions on the network device. The device is further configured to identify a first time instance for executing the automated process instructions that does not occur within a time interval associated with a first system update for the network device and to execute the machine-executable code at the first time instance to perform the series of actions on the network device.

Abstract: Apparatus and methods for intelligently monitoring multiple bots for failure or predicted failure and notifying a user through a proximate Internet-of-Things (“IoT”) device are provided. A program may receive configuration files for each IoT device and access to monitor each bot. The program may monitor each bot through a resiliency scanner module. The program may generate a report about a failure or predicted failure of a bot. The program may activate a self-healing engine to attempt to heal the bot. The program may activate an event-stream engine. The event-stream engine may determine which IoT device to transmit a report and notify the user through that IoT device to the failure or predicted failure. The user may respond through the IoT device or another device.

Abstract: Aspects of the disclosure relate to upgrading an application within a simulated version of an enterprise system to detect and correct potential errors as a result of the upgrade. A computing platform may create a simulated version of the enterprise system by receiving metadata associated with the enterprise system, and converting the metadata into system parameters. Virtual parameters may be created by the computing system based on upgrading an application within the simulated version of the enterprise system. The computing system may determine errors caused by the application upgrade within the simulated version of the enterprise system based on differences between the system parameters and the virtual parameters. The computing platform may determine actions to correct the errors and input the results and feedback into an AI engine to further refine the accuracy and reliability of the computing platform over time.

Abstract: Apparatuses, systems, and techniques to perform collision-free motion generation (e.g., to operate a real-world or virtual robot). In at least one embodiment, at least a portion of the collision-free motion generation is performed in parallel.

Abstract: A system, e.g., a system on a chip (SoC) includes a first domain including a first processor configured to boot the system; a second domain including a processing subsystem having a second processor; and isolation circuitry between the first domain and the second domain During boot-up of the system, the first processor provides code to the second domain. When the code is executed by the second processor, it configures the processing subsystem as either a safety domain or as a general-purpose processing domain. The safety domain may an external safety domain or an internal safety domain.

Abstract: The present invention provides a novel reference standard, comprising of activated-quenched polysaccharide, for quantifying polysaccharide content in a vaccine composition using nephelometry. The invention also provides a method for preparing the activated-quenched polysaccharide, for use as a reference standard. Further, a nephelometry based method for quantifying the polysaccharides in a multivalent conjugate vaccine is also provided. The reference standard of the present invention, comprising of the activated-quenched polysaccharide, is stable and can be used for accurate quantification of polysaccharides through nephelometry.

Abstract: Embodiments of the disclosure provide memory circuit, a sense amplifier and associated method for reading a resistive state in a memory device. The sense amplifier includes a bit cell configurable to a high or low resistance state; a sensing circuit that detects a voltage drop across the bit cell in response to an applied read current during a read operation and generates a high or low logic output at an output node; and a pulse generation circuit that increases the applied read current with an injected current pulse when a low to high transition of the resistive state of the bit cell is detected.

Abstract: A method for user credential authentication includes receiving real-time logs from a blockchain network that is configured to perform an authentication process of a user. The real-time logs are normalized and bucketized to generate processed real-time logs, which are stored in a block and are added to a blockchain. The processed real-time logs are analyzed to identify the plurality of real-time behavioral patterns of the user. A first authentication score is determined by comparing a first real-time behavioral pattern to a respective first historical behavioral pattern. The first authentication score is compared to a first authentication score threshold, which corresponds to the first real-time behavioral pattern and the respective first historical behavioral pattern. In response to the first authentication score being less than the first authentication score threshold, a first instruction is sent to the blockchain network to temporarily stop the authentication process of the user.

Abstract: The present disclosure relates to methods and apparatus for sharing GPU hardware to generate bin visibility information concurrently for graphics processing. The apparatus can cause a processor to: store, in a GMEM, first data associated with a first graphics processing pass for a first frame of graphics data and second data associated with a second graphics processing pass for a second frame of graphics data. The apparatus can also cause a geometry processor to perform the first graphics processing pass using the first data and a second processor to concurrently perform the second graphics processing pass using the second data such that the first graphics processing pass and the second graphics processing path share the geometry processor. In some aspects, the apparatus can switch the geometry processor from being used for the first graphics processing pass to being used for the second graphics processing pass at a primitive batch boundary.

Abstract: In various examples, techniques for detecting occluded objects within an environment are described. For instance, systems and methods may receive training data representing images and ground truth data indicating whether the images are associated with occluded objects or whether the images are not associated with occluded objects. The systems and methods may then train a neural network to detect occluded objects using the training data and the ground truth data. After training, the systems and methods may use the neural network to detect occluded objects within an environment. For instance, while a vehicle is navigating, the vehicle may process sensor data using the neural network. The neural network may then output data indicating whether an object is located within the environment and occluded from view of the vehicle. In some examples, the neural network may further output additional information associated with the occluded object.

Abstract: A system includes a memory and a processor. The memory stores a set of videos each of which is associated with an application of a set of applications and depicts a process performed using the application. For each video, the processor generates metadata associated with the depicted process, and stores the metadata within a collection of metadata in the memory. The processor receives a request for information from a user. In response, the processor identifies an application of the set of applications for use in generating a response to the request. The processor generates, based on the collection of metadata, instructions for interfacing with the first application to generate the response. The processor executes the instructions to interface with the first application to generate the response, and transmits the response to the user.

Abstract: A system is disclosed. A node may include a resource. A lock manager may include storage for a data structure for a lock. The data structure may include a first identifier for the resource, a second identifier for an application, and a status for the lock.

Abstract: Certain aspects of the present disclosure provide techniques for dynamic configuration of demodulation reference signals (DMRSs). A method that may be performed by a base station (BS) includes receiving one or more uplink signals from at least one user equipment (UE); estimating a Doppler shift associated with the one or more uplink signals; determining a density of reference signals (RSs) within a slot for the at least one UE based, at least in part, on the estimated Doppler shift associated with the one or more uplink signals; and transmitting information to the at least one UE indicating an allocation of RS resources for the UE, wherein the allocation of the RS resources is based on the density of the RSs for the at least one UE.

Abstract: A device configured to identify automated process instructions for a network device. The automated process instructions include instructions for performing a series of actions on the network device. The device is further configured to identify a first time instance for executing the automated process instructions that does not occur within a time interval associated with a first system update for the network device and to execute the machine-executable code at the first time instance to perform the series of actions on the network device. The device is further configured to detect a second system update for the network device while executing the machine-executable code, to pause the execution of the machine-executable code at a breakpoint at a second time instance after detecting the second system update, and to resume execution of the machine-executable code after the breakpoint at a third time instance after the second system update is complete.

Abstract: A computer-implemented method of generating a security language query from a user input query includes receiving, at a computer system, an input security hunting user query indicating a user intention; selecting, using a trained machine learning model and based on the input security hunting query, an example user security hunting query and corresponding example security language query; generating, using the trained machine learning model, query metadata from the input security hunting query; generating a prompt, the prompt comprising: the input security hunting user query; the selected example user security hunting query and the corresponding example security language query; and the generated query metadata; inputting the prompt to a large language model; receiving a security language query from the large language model corresponding to the input security hunting query reflective of the user intention.