Abstract: An LDPC decoder receives channel information and performs a bit flipping algorithm to correct unsatisfied checks with respect to a parity matrix H. The threshold condition for determining whether to flip a bit is a function of the channel information itself. A threshold Thk used to evaluate the threshold condition may vary between iterations based on the number of iterations, number of bits flipped in the previous iteration, and number of unsatisfied checks. A threshold Thki may be calculated for each bit position. Thki and the threshold condition may be a function of whether bit position i was flipped in a previous iteration. A binning approach for parameters of the threshold condition may be used to reduce hardware complexity.

Abstract: An integrated clock gate (ICG) includes an OR-AND-INVERT gate to receive a first enable and a second enable; a first inverter coupled to the output of the OR-AND-INVERT; a first NAND gate coupled to the output of the first inverter; a second NAND gate coupled to the output of the OR-AND-INVERT; and a second inverter to provide a clock which is gated based on logic values of the first enable and/or the second enable, wherein an output of the second inverter is received as input by the OR-AND-INVERT-gate. The ICG circuit reduces capacitance of input clk pin, which translates to lower switching power when clock is gated and reduction in dynamic power of clock network, since buffers in clock tree driving the ICG cells can be downsized. The ICG cell has the smallest transistor count (and area) when compared to existing ICG cell topologies.

Abstract: An illustrative method for performing a risk scenario assessment and remediation may include identifying, based on posture data associated with a compute environment, one or more compute resources deployed in the compute environment that are configured to be connected to a network, accessing runtime workload data associated with the one or more compute resources representative of network activity for the one or more compute resources, and performing, based on the posture data and the runtime workload data, a remediation operation associated with the one or more compute resources.

Abstract: A multi-universal subscriber identity module (MUSIM) user equipment (UE) is configured to operate in an Radio Resource Control (RRC) inactive state with a first network associated with the first SIM, operate in an RRC connected state with a second network associated with the second SIM, receive a page from the first network, determine that a priority of at least one operation being performed between the UE and the second network is higher than a priority of the page and send a BUSY indication to the first network in response to the page.

Abstract: Memory calibration with a margin check is disclosed. A memory subsystem includes a memory and a memory controller coupled to the memory. The memory controller includes a calibration circuit configured to perform, during an initialization process, horizontal memory calibrations for ones of a plurality of performance states and to determine and store, in a storage circuit, information indicative of a set of differences between calibration results for pairs of the plurality of performance states. The memory controller is further configured to, subsequent to the initialization process and in response to a change from a first one of the plurality of performance states to a second one of the plurality of performance states set initial memory parameters for the second performance state based on the set of differences. Thereafter, operation begins in the second performance state without performing an initial horizontal calibration.

Abstract: A computer-implemented method that includes monitoring execution of program code by first and second processor components. A computing system detects that a trigger condition is satisfied by: i) identifying an operand in a portion of the program code; or ii) determining that a current time of a clock of the computing system indicates a predefined time value. The operand and the predefined time value are used to initiate trace events. When the trigger condition is satisfied the system initiates trace events that generate trace data identifying respective hardware events occurring across the computing system. The system uses the trace data to generate a correlated set of trace data. The correlated trace data indicates a time ordered sequence of the respective hardware events. The system uses the correlated set of trace data to analyze performance of the executing program code.

Abstract: A machine-learning model (MLM) is trained to identify a given item identifier for an item and shelf dimensions of an empty space associated with the item from training images of a shelf. After training, real-time images of the shelf are provided as input to the MLM and the output provided by the MLM includes empty space identifiers, dimensions or pixel coordinates for each empty space identifier, and an item identifier for each empty space identifier. A quantity of each item identifier is determined based on known shelf dimensions that the corresponding item should occupy on a fully stocked shelf and based on the corresponding empty space dimensions for the empty space associated with the item. A real-time report is sent to store personnel and/or published on a website monitored by the store personnel. The report identifies the items, the shelves, and restocking item quantities that need restocked in the store.

Abstract: In an example, a wireless battery management system includes one or more sets of battery cells. The wireless battery management system includes a primary node configured to broadcast a downlink packet in a first superframe. The wireless battery management system also includes a first secondary node coupled to a first set of battery cells. The first secondary node is configured to receive the downlink packet and transmit a first uplink packet to the primary node during the first superframe. The wireless battery management system includes a second secondary node coupled to a second set of battery cells. The second secondary node is configured to receive the first uplink packet from the first secondary node in the first superframe. The second secondary node is also configured to transmit a second uplink packet to the primary node during a second superframe.

Abstract: A battery management system (BMS) is presented herein. The BMS has a master node. The master node includes a master transceiver and a controller communicably coupled to the master transceiver. The BMS has a plurality (n) of slave nodes. Each slave node of the n slave nodes includes a slave transceiver for communicably coupling to at least one battery monitor. The controller of the BMS is configured to direct the master transceiver to establish a communications network with the n slave nodes. To establish the communications network, the controller is also configured to respectively assign each of the n slave nodes to non-overlapping time slots of a superframe. The controller is further configured to direct the master transceiver to consecutively receive uplink (UL) transmissions from the n slave nodes in the non-overlapping time slots of the superframe.

Abstract: A method for channel switching by a secondary node. The method includes: receiving, from a primary node, a downlink transmission, measuring one or more statistics about the downlink transmission, determining, from the downlink transmission, an uplink interval, transmitting, to the primary node during the uplink interval, the measured one or more statistics about the downlink transmission, receiving, from the primary node, an indication of a set of useable channels, determining, based on the set of useable channels and at least one of the primary node or the secondary node, a next channel from the set of useable channels, and switching to the next channel based on a switch indication from the primary node.

Abstract: Apparatus and methods for deploying a web application including a plurality of binary objects. The methods may include isolating from the plurality of class files a class file in which a run-time behavior occurs. The methods may include updating the class file to produce a modified class file that does not have the behavior. The methods may include testing performance of the modified class file. The methods may include storing the class file in a dynamic configuration database. The methods may include recognizing the modified class file as being modified. The methods may include, using a cron job processor, reading the metadata. The methods may include compiling the modified class file into binary code. The methods may include executing the binary code instead of a different binary code that corresponds to the class file in which the run-time behavior occurs.

Abstract: An authentication system supports multi-factor authentication (MFA) when authenticating the identity of a user. A challenge-response portion of the authentication process is delegated to an MFA device—a secondary device within control of the user, but separate from the primary login device that the user is using when initiating the authentication. Communications between the MFA device and the login device are conducted using a short-range wireless communication protocol (e.g., Bluetooth™ or NFC), so that the two devices must be in close physical proximity to each other.

Abstract: Disclosed herein is a time-based leaderboard that ranks users based on a length of time each user has controlled or possessed a given digital object. The leaderboard includes customization options for purposes of user identification and identity connected to social network objects. The leaderboard further uses a staking feature where users provide their digital objects to universal wallets to hold for a predetermined period based on smart contract limitations. Staking improves leaderboard position. The leaderboard further enables expression and displayed of staked digital objects despite the user no longer having actual possession of the digital object. A digital object generator builds unique digital objects based on the user specific input. The unique digital objects are part of a graphic presentation to users.

Abstract: The present disclosure describes systems and methods for information retrieval. Embodiments of the disclosure provide a color embedding network trained using machine learning techniques to generate embedded color representations for color terms included in a text search query. For example, techniques described herein are used to represent color text in a same space as color embeddings (e.g., an embedding space created by determining a histogram of LAB based colors in a three-dimensional (3D) space). Further, techniques are described for indexing color palettes for all the searchable images in the search space. Accordingly, color terms in a text query are directly converted into a color palette and an image search system can return one or more search images with corresponding color palettes that are relevant to (e.g., within a threshold distance from) the color palette of the text query.

Abstract: A memory subsystem and method for performing calibrations therein is disclosed. A memory subsystem includes a memory controller coupled to a memory by a plurality of signal paths. The memory controller is configured to perform an initial calibration to determine respective eye patterns corresponding to the ones of the plurality of signal paths. For a subsequent calibration, updated eye patterns are determined for a subset of the plurality of signal paths. Remaining ones of the plurality of signal paths (not included in the subset), are not active during the subsequent calibrations. Updated eye patterns for the remaining ones of the plurality of signal paths are determined based on information obtained during the initial calibration and information from signal paths in the subset designated proxies for the remaining ones of the plurality of signal paths.

Abstract: A method for determining a placement for machine learning model operations across multiple hardware devices is described.

Abstract: A user equipment (UE) configured to operate in a radio resource control (RRC) connected state with a network cell, receive an RRC message to release or suspend the RRC connected state, the RRC message including an indication for a tracking reference signal (TRS) or channel state information reference signal (CSI-RS) configuration to use during an RRC inactive or idle state, enter the RRC inactive or idle state and apply the TRS or CSI-RS configuration for performing timing and frequency error estimation for decoding downlink control information.

Abstract: A user equipment (UE) receives an indication that a secondary cell group (SCG) state is to be changed from an activated state to a deactivated state, when the SCG is in the deactivated state, identifies a SCG failure based on downlink timing associated with the SCG and reports the SCG failure to a primary node.

Abstract: Embodiments of the technology described herein, provide improved visual search results by combining a visual similarity and a textual similarity between images. In an embodiment, the visual similarity is quantified as a visual similarity score and the textual similarity is quantified as a textual similarity score. The textual similarity is determined based on text, such as a title, associated with the image. The overall similarity of two images is quantified as a weighted combination of the textual similarity score and the visual similarity score. In an embodiment, the weighting between the textual similarity score and the visual similarity score is user configurable through a control on the search interface. In one embodiment, the aggregate similarity score is the sum of a weighted visual similarity score and a weighted textual similarity score.

Abstract: Systems and methods for training a neural network to predict states of a robotics device are disclosed. Robotics data is received for a robotics device, including indications of a set of components, a digital simulation of the robotics device, and measurement data received from a sensor associated with the robotics device. The set of components includes an actuator and a structural element. A training dataset is generated using the received robotics data. Generating the training dataset includes comparing the measurement data with simulated measurement data based on the digital simulation. A neural network is trained using the generated training dataset to modify the digital simulation of the robotics device to predict a state of the robotics device, such as a position, motion, electrical quantity, or other. When trained, the neural network is applied to predict states of the robotics device or a different robotics device.