Abstract: A vehicle, among other things, may use predicted rates of change in vehicle speed based on past driving data of a particular user to allocate resources within the vehicle, to recreate the behavior of particular user in an automated driving system, or to accurately predict a capability of the vehicle.

Abstract: Certain aspects of the present disclosure provide techniques for performing machine learning computations in a compute in memory (CIM) array comprising a plurality of bit cells, including: determining that a sparsity of input data to a machine learning model exceeds an input data sparsity threshold; disabling one or more bit cells in the CIM array based on the sparsity of the input data prior to processing the input data; processing the input data with bit cells not disabled in the CIM array to generate an output value; applying a compensation to the output value based on the sparsity to generate a compensated output value; and outputting the compensated output value.

Abstract: A wireless device may receive packets according to a protocol, such as Bluetooth, and may rapidly react to receive an interfering RF packet instead of dropping the first RF packet and the interfering RF packet, to decrease message delay due to collisions in high device density environments. When a received signal strength indicator (RSSI) difference between the interfering RF packet and the first RF packet exceeds a threshold, the device may detect the interfering packet and resync a portion of its circuitry to lock on to and receive the interfering packet. The wireless receiver may detect the interfering RF packet by detecting one or more of: a specific resync byte sequence, an increase in RSSI, or a phase shift. Additionally, a wireless device may add the specific resync byte sequence to an RF packet of a standard protocol.

Abstract: A computer-implemented method is disclosed. The method includes obtaining, by a de-duplication server, a candidate pair of a plurality of digitally stored documents from a document database. Text elements are identified from each digitally stored document in the candidate pair in response, and the text elements are stored as document extraction attributes. The method then automatically computes and stores relative positional differences of the text elements between each digitally stored document of the candidate pair and a document similarity score based on the relative positional differences. The relative positional differences are compared with a similarity function to form a difference similarity vector for the candidate pair. The difference similarity vector comprises components corresponding to each relative positional difference. The components of the difference similarity vector are aggregated to determine a final score for the candidate pair.

Abstract: A control system is provided that may include a first sensor configured to detect a vehicle system. The control system may also include one or more processors in communication with the first sensor. The one or more processors may be configured to receive communication related to entry of the vehicle system into an area, and operate the first sensor to begin monitoring the vehicle system in response to entry of vehicle system into the area. The one or more processors may also be configured to record movement data related to the vehicle system, and determine movement of the vehicle system within the area based on the movement data.

Abstract: Apparatus and methods are provided for CSI enhancement for multi-TRP coherent joint transmission. A user equipment (UE) receives signals from a plurality of transmission and reception points (TRPs). The UE determines, based on the signals, multiple TRP (multi-TRP) coherent joint transmission (CJT) channel state information (CSI) report information for a codebook based on a spatial basis selection matrix, a combination coefficient matrix, and a frequency basis selection matrix. The spatial basis selection matrix is layer common, polarization common, and TRP independent. The UE reports, to one or more of the plurality of TRPs, the multi-TRP CJT CSI report information.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately enhancing optical character recognition with a machine learning approach for determining words from reverse text, vertical text, and atypically-sized text. For example, the disclosed systems segment a digital image into text regions and non-text regions utilizing an object detection machine learning model. Within the text regions, the disclosed systems can determine reverse text glyphs, vertical text glyphs, and/or atypically-sized text glyphs utilizing an edge based adaptive binarization model. Additionally, the disclosed systems can utilize respective modification techniques to manipulate reverse text glyphs, vertical text glyphs, and/or atypically-sized glyphs for analysis by an optical character recognition model.

Abstract: An information handling system includes a storage and a basic input/output system (BIOS). The BIOS load and boot the base root file system. The BIOS determine a requested capability for the information handling system. The BIOS download an external root file system for the requested capability. The BIOS overlay the external root file system on the base root file system. The BIOS determine a job associated with the requested capability is completed. Based on the job being completed, the BIOS delete the external root file system.

Abstract: The present invention relates to a stable oral liquid pharmaceutical composition of celecoxib or pharmaceutically acceptable salts thereof. The celecoxib present in the compositions as described herein do not show any precipitation when subjected in Fasted-State Simulated Gastric Fluid (FaSSGF) at pH 2.0, temperature of 37° C.±0.5° C. and under stirring at a speed of 50 rpm at least for 60 minutes. It also relates to the process of preparing and method of using said composition of celecoxib.

Abstract: Systems and methods for allocating optimal supply chain resources based on order data are disclosed. In some embodiments, a disclosed method includes: receiving, from a computing device, an allocation request associated with an order; determining a customer node associated with the order, wherein the customer node is in a supply chain network; determining, based on the order and the customer node, a sub-network of the supply chain network; determining, based on cost information associated with the sub-network, at least one path from at least one source node to the customer node in the sub-network; generating supply chain allocation data for the order based on the at least one path; and transmitting the supply chain allocation data to the computing device.

Abstract: Methods, devices, and systems for placing dental auxiliaries on teeth and/or removing dental auxiliaries from teeth are provided. In some embodiments, a device for removing a dental auxiliary from a tooth includes: a first elongate member having a proximal end and a distal end; a second elongate member having a proximal end and a distal end, where the first and second elongate members are pivotally coupled to each other; a scraper at the distal end of the second elongate member, where the scraper is configured to apply force to the dental auxiliary to remove the dental auxiliary from the tooth; and a pair of sidewalls configured to capture debris resulting from the removal of the dental auxiliary from the tooth.

Abstract: The present subject matter describes performing radio resource management (RRM) measurements by a WTRU in a 3GPP networks. The method comprise defining at-least one of: a) a channel condition threshold, b) a WTRU mobility threshold, and c) a measurement-reliability threshold. A first sub-set of reference-signal samples are measured out of a set of reference-signal samples based on sensing at least one of current channel conditions and mobility-conditions. A reliability-parameter associated with the first sub-set of measured samples is checked.

Abstract: The invention features methods for the identification of genomic aberrations in circulating tumor cells (CTCs) isolated from peripheral blood. In various embodiments of the disclosure, the methods involve isolation of a small number of purified circulating multiple myeloma cells, purification of genomic DNA from the cells, and sequencing of the genomic DNA.

Abstract: A system includes an array of sensors configured to capture data about an environment for vehicular traffic. The array of sensors is disposed at a non-vehicular location. The system also includes one or more computing devices that include one or more processors. The one or more processors are configured to process the captured data about the environment to detect one or more road users in the environment and/or to detect information about traffic signage in the environment. The one or more processors are also configured to transmit, in real-time, an indication of the one or more detected road users and/or the detected information about the traffic signage in the environment to a vehicle.

Abstract: A control system for a machine includes one or more component controllers for one or more components of the machine. The control system also includes a supervisory controller, connected to the one or more component controllers, and having at least one supervisory processor configured to perform operations comprising receiving supervisory system inputs, including at least one of a machine component status input, a key switch input, a directional input, or an operator presence input, from an operator of the machine, requesting and receiving, from each of the one or more component controllers, a status of the one or more components, and, upon receiving an indication that a status of a component, of the one or more components, is faulted, disabling the faulted component, and disabling any other components, of the one or more components, that require the faulted component for operation.

Abstract: Virtual memory pooling, including identifying GPUs of respective IHSs, wherein each of the GPUs is associated with a respective internal memory allocation; partitioning, for each GPU, the internal memory allocation associated with the GPU into a first memory allocation and a second memory allocation; allocating, for each GPU, the first memory allocation of the internal memory allocation associated with the GPU as accessible only by the associated GPU; pooling, for each GPU, the second memory allocation of the internal memory allocation associated with the GPU to define a virtual memory pool, the virtual memory pool accessible by each GPU; processing, at a first GPU, a computational task, including: accessing the first memory allocation associated with the first GPU; determining that processing of the computational task exceeds a capacity of the first memory allocation of the first GPU and in response, requesting access to the virtual memory pool.

Abstract: Aspects of the technology evaluate a client device query to identify an IP address-based estimated location of a mobile device. One or more candidate wireless stations are selected in accordance with the IP-based estimated location and a location-relevant response to the query is also generated in accordance with the IP-based location. This information is transmitted to the mobile device. The mobile device compares the received information about the candidate wireless stations against one or more actual wireless stations with which the mobile device is in communication. Log information is generated as a result of the comparison. The log information is anonymized and transmitted to the network without user ID or other client-identifiable information included in the log. The received log information is then used to validate the initial estimated location. Aggregation of log information from multiple devices may be used in the validation process.

Abstract: Certain aspects of the present disclosure provide techniques for performing machine learning computations in a compute in memory (CIM) array comprising a plurality of bit cells, including: determining that a sparsity of input data to a machine learning model exceeds an input data sparsity threshold; disabling one or more bit cells in the CIM array based on the sparsity of the input data prior to processing the input data; processing the input data with bit cells not disabled in the CIM array to generate an output value; applying a compensation to the output value based on the sparsity to generate a compensated output value; and outputting the compensated output value.

Abstract: Systems, computer program products, and methods are described herein for a decentralized machine learning source code generation framework via a holochain network. The present invention is configured to receive a predetermined code criteria, receive a new code segment from an editor on an endpoint device, retrieve characteristics of the new code segment, determine, using a trained machine learning model, at least one subsequent code segment, based on at least the characteristics of the new code segment, determine, using an evaluation engine, at least one score of the subsequent code segment, wherein the at least one score is associated with the predetermined code criteria, and transmit to the editor of the endpoint device for displaying a predetermined number of the at least one subsequent code segments above a predetermined threshold of the at least one score.

Abstract: A method of monitoring a fluid level in a power unit relies on a neural network model. The model is used to predict lateral acceleration during air ingestion events. These predictions are compared to measured values of lateral acceleration. When the measured values and the predicted values are not well correlated, a controller takes corrective action.