Abstract: A method of reducing power consumption of a first wireless communication device is described. A charge level of a battery associated with the first wireless communication device is monitored. A wireless communication session between the first wireless communication device and a second wireless communication device is maintained. Based at least in part on the charge level of the battery being within a low battery threshold range, a wireless signal strength associated with the wireless communication session is monitored. Based at least in part on the wireless signal strength reaching a power saving threshold that is above a minimum connection threshold for maintaining the wireless communication session, a power saving action associated with a wireless interface that supports the wireless communication session is performed.

Abstract: Methods, systems, and devices for data management are described. A data management system (DMS) may determine to generate a backup instance of an application that includes multiple user accounts. The DMS may identify a time window for generation of the backup instance based on a set of backup parameters associated with the application. The DMS may calculate respective runtime durations for the user accounts based on respective quantities of data objects in the user accounts and respective backup job types associated with the data objects. The DMS may determine respective values of a semaphore parameter based on the respective runtime durations and the time window, where the semaphore parameter defines a threshold quantity of data objects to be processed in parallel. The DMS may generate the backup instance of the application based on processing the user accounts in accordance with the respective values of the semaphore parameter.

Abstract: A computer implemented method of generating a machine learning model for interpreting host phage response data comprising receiving datasets and labels for a host phage response, training a machine learning model and using this model to estimate the efficacy of a test phage in inhibiting growth of a test bacteria.

Abstract: A method of reducing power consumption of a first wireless communication device is described. A charge level of a battery associated with the first wireless communication device is monitored. A wireless communication session between the first wireless communication device and a second wireless communication device is maintained. Based at least in part on the charge level of the battery being within a low battery threshold range, a wireless signal strength associated with the wireless communication session is monitored. Based at least in part on the wireless signal strength reaching a power saving threshold that is above a minimum connection threshold for maintaining the wireless communication session, a power saving action associated with a wireless interface that supports the wireless communication session is performed.

Abstract: A method, apparatus, system for batter material screening is disclosed. First, microstructure generation parameters for a plurality of microstructures are received, where the microstructure generation parameters include microstructure characteristics. Microstructure statistics are generated using a first artificial intelligence (“AI”) model, where the received microstructure generation parameters are inputs for the first AI model. Microstructure properties are predicted using a second AI model for the microstructures based on the generated microstructure statistics, the received microstructure generation parameters, and battery cell characteristics. It is determined whether at least one of the microstructures is within a predefined energy profile range based on the predicted microstructure properties.

Abstract: In one embodiment, a method is provided. The method includes receiving, at an input of a first machine learning model, first input data representing an environment. The method also includes determining, by the first machine learning model, a set of objects within the environment based on the first input data. The method further includes determining, by a second machine learning model, a set of behaviors for a second set of objects. An input of the second machine learning model is coupled to a set of intermediate layers of the first machine learning model. Determining the set of objects and determining the set of behaviors for the second set of objects is performed at least partially simultaneously.

Abstract: Certain aspects involve using a set of machine learning modeling models for predicting attempts to tamper with records using a fraudulent dispute. A tampering prediction system receives a request from a target entity to modify event data for a historical event, including information about the target entity and the event. The system generates a first score by applying a first set of machine learning models to the information from the request and information about the target entity obtained from a database. They system computes a second score by applying a second machine learning model to event data retrieved from the database. The second machine learning model has been trained using labeled training data and is augmented with a model that has been trained using unlabeled training data. The system generates an overall score for the request based on the first score and the second score.

Abstract: A method, apparatus, system for batter material screening is disclosed. First, microstructure generation parameters for a plurality of microstructures are received, where the microstructure generation parameters include microstructure characteristics. Microstructure statistics are generated using a first artificial intelligence (“AI”) model, where the received microstructure generation parameters are inputs for the first AI model. Microstructure properties are predicted using a second AI model for the microstructures based on the generated microstructure statistics, the received microstructure generation parameters, and battery cell characteristics. It is determined whether at least one of the microstructures is within a predefined energy profile range based on the predicted microstructure properties.

Abstract: A client device may obtain a first measurement corresponding to a serving WLAN access point that uses a first channel. The client device may also obtain a second measurement corresponding to a target WLAN access point that uses a second channel. To facilitate intelligent wireless channel selection, the client device may weight at least one of the first measurement and the second measurement based on channel selection settings to obtain at least one weighted measurement. The client device may determine whether to roam from the serving WLAN access point to the target WLAN access point based on the at least one weighted measurement.

Abstract: Systems and methods for annotated data collection in an electronic messaging platform. One example system includes a machine learning database and an electronic processor communicatively coupled to the machine learning database. The electronic processor is configured to receive a plurality of electronic messages. The electronic processor is configured to select a sample message set from the plurality of electronic messages. The electronic processor is configured to add an actionable message to each electronic message of the sample message set. The electronic processor is configured to receive an actionable message selection from an electronic messaging client. The actionable message selection includes a user label indication and a message identifier. The electronic processor is configured to store the actionable message selection in the machine learning database.

Abstract: A method of controlling wireless communication performance in an electronic device includes accessing data containing material properties relating to a plurality of materials, transmitting a first test signal on a first transmission channel with a first antenna at a first location in the electronic device, receiving the first test signal on the first transmission channel with a second antenna at a second location in the electronic device, determining a housing material of the electronic device based on a measured attenuation of the first test signal received by the second antenna based upon the data containing transmission properties relating to a plurality of materials, and adjusting a transmission power of one of the first antenna and the second antenna based upon the material properties of the housing material.

Abstract: A method and system for exporting a 3D object in an application to a file having a 3D file format is disclosed. The method includes a receiving a request for exporting a 3D object in an application to a file having a 3D file format where the 3D object includes a plurality of components. Upon receiving the request, the components are examined to determine if any of them are a 2D text component. When it is determined that at least one of the components is a 2D text component, a database may be referenced to identify a text character that corresponds to the 2D text component, before replacing the 2D text component with a corresponding 3D model in the file.

Abstract: Approaches are described to improve database performance by implementing a RLE decompression function at a low level within a general-purpose processor or an external block. Specifically, embodiments of a hardware implementation of an instruction for RLE decompression are disclosed. The described approaches improve performance by supporting the RLE decompression function within a processor and/or external block. Specifically, a RLE decompression hardware implementation is disclosed that produces a 64-bit RLE decompression result, with an example embodiment performing the task in two pipelined execution stages with a throughput of one per cycle. According to embodiments, hardware organization of narrow-width shifters operating in parallel, controlled by computed shift counts, is used to perform the decompression.

Abstract: A client device may obtain a first measurement corresponding to a serving WLAN access point that uses a first channel. The client device may also obtain a second measurement corresponding to a target WLAN access point that uses a second channel. To facilitate intelligent wireless channel selection, the client device may weight at least one of the first measurement and the second measurement based on channel selection settings to obtain at least one weighted measurement. The client device may determine whether to roam from the serving WLAN access point to the target WLAN access point based on the at least one weighted measurement.

Abstract: The present invention is related to detecting location of a navigation device using sensor data analysis, where the sensor is coupled to the navigation device. A hierarchical algorithm is used for making a series of decisions regarding the location of the navigation device, with each decision corresponding to a class among a plurality of classes related to the possible motion modes and/or precise location of the device, including the location of the device with respect to a person's body. By accurately identifying the device location, the hierarchical algorithm facilitates in providing relevant contextual information, thereby enhancing situational awareness.

Abstract: Approaches are described to improve database performance by implementing a RLE decompression function at a low level within a general-purpose processor or an external block. Specifically, embodiments of a hardware implementation of an instruction for RLE decompression are disclosed. The described approaches improve performance by supporting the RLE decompression function within a processor and/or external block. Specifically, a RLE decompression hardware implementation is disclosed that produces a 64-bit RLE decompression result, with an example embodiment performing the task in two pipelined execution stages with a throughput of one per cycle. According to embodiments, hardware organization of narrow-width shifters operating in parallel, controlled by computed shift counts, is used to perform the decompression.

Abstract: A method, system, and computer program product for implementing automated worklists are provided. The method includes generating a worklist, which further includes retrieving a worklist template corresponding to the worklist and, via a first query, selecting a listing of members and attributes to be populated in the worklist, the attributes include a status indicator of an action item specified for each of the members of the worklist. The worklist generation also includes building a worklist member table with results of the first query and, via a second query, and using attributes of the worklist member table, identifying up-to-date values of one or more worklist member attributes, and outputting results of the second query to the worklist. The method also includes presenting the worklist to a corresponding assignee. For each of the members in the worklist, the status indicator is editable to update a status of the member.

Abstract: The present invention is related to detecting location of a navigation device using sensor data analysis, where the sensor is coupled to the navigation device. A hierarchical algorithm is used for making a series of decisions regarding the location of the navigation device, with each decision corresponding to a class among a plurality of classes related to the possible motion modes and/or precise location of the device, including the location of the device with respect to a person's body. By accurately identifying the device location, the hierarchical algorithm facilitates in providing relevant contextual information, thereby enhancing situational awareness.

Abstract: A method, system, and computer program product for implementing automated worklists are provided. The method includes generating a worklist, which further includes retrieving a worklist template corresponding to the worklist and, via a first query, selecting a listing of members and attributes to be populated in the worklist, the attributes include a status indicator of an action item specified for each of the members of the worklist. The worklist generation also includes building a worklist member table with results of the first query and, via a second query, and using attributes of the worklist member table, identifying up-to-date values of one or more worklist member attributes, and outputting results of the second query to the worklist. The method also includes presenting the worklist to a corresponding assignee. For each of the members in the worklist, the status indicator is editable to update a status of the member.