Abstract: Some embodiments provide a two-tier DNS (Domain Name System) service for processing DNS requests. In some embodiments, the two-tier DNS service deploys first and second tiers of service machines, with the second-tier having several groups of service machines each of which is configured to resolve DNS requests for a different set of domain names than the other second-tier group(s). Each service machine in the first-tier is configured to identify the second-tier group responsible for each particular DNS request that the service machine receives for each particular domain name, and to forward the particular DNS request to the second-tier group that it identifies for the particular DNS request. The first-tier DNS service in some embodiments has only one group of service machines. Each first or second service machine group in some embodiments can have one or more service machines, and can be scaled up or down to add or remove service machines to the group (e.g., through an active/active layer 3 scaleout with BGP).

Abstract: Described herein are methods and a system device management of multiple tools or consoles in a data center, where the consoles control devices in the data center. The consoles are identified with unique identifiers. A capability list of devices in the data center, a provider policy as to the multiple consoles, and a grant matrix as to device capability and consoles is used by a baseboard management controller of a device to determine control of a console over the device.

Abstract: Methods, apparatuses, systems, and computer program products are disclosed for generating content for presentation at a collaborative content interface based on a captured content source.

Abstract: Embodiments described herein relate to systems and methods for automatically generating content for a generative content interface of a collaboration platform. The system may perform an intent analysis on a natural language user input to the generative content interface to determine an intent confidence score with respect to each of a set of request classifiers, the set of request classifiers comprising a first request classifier associated with a request for an action, a second request classifier associated with a request for information, and a third request classifier associated with a request for a contact. Based on the intent confidence scores of the request classifiers, the system may select a content store in which to search for content to satisfy a user's query.

Abstract: Some embodiments provide a two-tier DNS (Domain Name System) service for processing DNS requests. In some embodiments, the two-tier DNS service deploys first and second tiers of service machines, with the second-tier having several groups of service machines each of which is configured to resolve DNS requests for a different set of domain names than the other second-tier group(s). Each service machine in the first-tier is configured to identify the second-tier group responsible for each particular DNS request that the service machine receives for each particular domain name, and to forward the particular DNS request to the second-tier group that it identifies for the particular DNS request. The first-tier DNS service in some embodiments has only one group of service machines. Each first or second service machine group in some embodiments can have one or more service machines, and can be scaled up or down to add or remove service machines to the group (e.g., through an active/active layer 3 scaleout with BGP).

Abstract: Certain aspects of the present disclosure provide techniques for dynamic adjustment of adaptive reception diversity (ARD). An example method, performed at a user equipment (UE), generally includes receiving configuration information configuring the UE with first resources for receiving at least one downlink signal and second resources for transmitting at least one uplink signal, detecting a conflict between the first resources and the second resources, and dynamically adjusting an adaptive reception diversity (ARD) mode if one or more conditions are met after detecting the conflict.

Abstract: Methods, apparatuses, or computer program products provide for generating a service risk analysis score data object. A service risk analysis request associated with an unreleased code object is received. One or more service risk analysis attributes are extracted using a service risk analysis layer based at least in part on the unreleased code object. A service risk analysis score data object is generated using a service risk analysis machine learning model based at least in part on the one or more service risk analysis attributes. The service risk analysis score data object is output.

Abstract: Various embodiments include methods and devices for implementing scaling memory frequency configuration by a computing device. Embodiments may include comparing at least a memory refresh rate, a memory size, at least one use case bandwidth of transmission between the memory and a system on chip (SoC), and a use case latency of transmission between the memory and the SoC with at least one stored memory refresh rate, at least one stored memory size, at least one stored use case bandwidth of transmission between the memory and the SoC, and at least one stored use case latency of transmission between the memory and the SoC, selecting a memory frequency based on a result of the comparison, and configuring the memory for the memory frequency. Some embodiments may include issuing an alarm indicating changing the use for the memory to be able to achieve a use case parameter.

Abstract: The present disclosure provides systems and techniques for dynamically providing a visualization of predicted flight information on a navigation display. An example technique includes presenting a window comprising a plurality of flight parameters on the navigation display. An indication of at least one first flight parameter selected from the plurality of flight parameters is obtained. A first position associated with the flight plan that is selected on the navigation display is detected. In response to the detection, a first value of the at least one first flight parameter at the first position is predicted and displayed on the navigation display.

Abstract: A system and a method include a control unit configured to receive data regarding an aircraft, and determine, based on the data, one or more economy speeds for the aircraft to fly between a departure airport and an arrival airport.

Abstract: Systems and methods provide techniques for more effective and efficient predictive monitoring of a software application framework. In response, embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to enable effective and efficient predictive monitoring of a software application framework using incident signatures for the software application that are generated by using a natural language processing machine learning framework, a structured data processing machine learning model, a feature combination machine learning model, and a clustering machine learning model.

Abstract: Apparatuses and methods of operating a flexible and optimized power management unit (PMU) for multiple power supply scenarios are described. One integrated circuit includes a first terminal to couple to an unregulated power supply, a second terminal to couple to a regulated power supply, a first regulator, and a second regulator. The first regulator outputs a first supply voltage in a first configuration, and the second regulator outputs a second supply voltage in a second configuration. The first and second regulators do not operate concurrently.

Abstract: Various embodiments include methods and devices for implementing scaling memory frequency configuration by a computing device. Embodiments may include comparing at least a memory refresh rate, a memory size, at least one use case bandwidth of transmission between the memory and a system on chip (SoC), and a use case latency of transmission between the memory and the SoC with at least one stored memory refresh rate, at least one stored memory size, at least one stored use case bandwidth of transmission between the memory and the SoC, and at least one stored use case latency of transmission between the memory and the SoC, selecting a memory frequency based on a result of the comparison, and configuring the memory for the memory frequency. Some embodiments may include issuing an alarm indicating changing the use for the memory to be able to achieve a use case parameter.

Abstract: A method of synchronously executing input/output operations (IOs) for a plurality of applications using a storage device with a file system includes the steps of: receiving a first write IO including an instruction to write first data at a first address of the file system; determining that, within a first range of the file system comprising the first address, there are no pending unmap IOs for deallocating storage space of the storage device from files of the plurality of applications; after determining that there are no pending unmap IOs within the first range, locking the first range to prevent incoming unmap IOs from deallocating storage space within the first range from the files of the plurality of applications; after locking the first range, writing the first data to the storage device at the first address; and after writing the first data, unlocking the first range.

Abstract: A method of optimizing ground operations at an airport. The method includes receiving input information regarding the airport where the input information at least includes turnaround process information for aircraft at the airport. An allocation of ground resources and manpower is determined at the airport with a ground resource and manpower model based on the input information. The allocation of ground resources and manpower determined by the ground resource and manpower model with a machine learning model are iteratively optimized until an optimized allocation of ground recourse and manpower is generated that reduces idling of at least one of ground resources or manpower at the airport. A report is generated based on the optimized allocation of ground resources and manpower.

Abstract: Aspects relate to random access channel procedures. In some examples, if a user equipment (UE) has not successfully received a random access channel (RACH) downlink message prior to the end of a random access window for a first RACH attempt, the UE may elect to proceed with a second RACH attempt. For example, the UE may determine whether there are any remaining downlink symbols available during the random access window to receive the RACH downlink message. If not, the UE may retransmit a physical RACH (PRACH) preamble.

Abstract: Systems and methods provide techniques for more effective and efficient predictive monitoring of a software application framework. In response, embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to enable effective and efficient predictive monitoring of a software application framework using incident signatures for the software application that are generated by using a natural language processing machine learning framework, a structured data processing machine learning model, a feature combination machine learning model, and a clustering machine learning model.

Abstract: A UE may obtain an indication of a first subset of PRACH resources in a set of PRACH resources, the first subset of PRACH resources having a set of channel metrics that is greater than or equal to a first threshold value, select a first PRACH resource from the first subset of PRACH resources based on a first set of channel metrics of the first PRACH resource or a first RO associated with the first PRACH resource, and transmit a RACH message to a network node in the first RO. The UE may evaluate the multiple qualifying SSBs/CSI-RSs and select one SSB/CSI-RS among the qualifying SSBs/CSI-RSs based on a scheduling opportunity of the associated ROs and a power usage on the UE side.

Abstract: Various embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to accurately and concisely generate one or more action item logs of one or more document data objects. For example, certain embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to generate an action item log of a document data object comprising one or more semantically complete or incomplete units of text data, by generating content segmentation units, determining action item presence predictions, generating action item sets from each content segmentation unit within a candidate action item subset, aggregating the action item sets to create an action item log, and storing the action item log.

Abstract: Disclosed is a controller for controlling brake action of an aircraft based on a current runway condition of the runway. The controller receives an expected condition of the runway and expected brake action for the aircraft from air traffic control, or other entity. The controller sends actual measured brake pressure applied by the aircraft while landing, along with sensor data from sensors on the aircraft configured to detect contaminants such as fluid or ice on the runway to a machine learning model. The machine learning model is configured to output a predicted brake action for the aircraft and predicted runway condition. The controller compares the expected brake action and expected runway condition to the predicted brake action and predicted runway condition. If there is any discrepancy, the controller sends the predicted brake action and runway condition to air traffic control to update the expected brake action and expected runway condition.