Abstract: A hybrid storage device with three-level memory mapping is provided. An illustrative device comprises a primary storage device comprising a plurality of primary sub-blocks; a cache memory device comprising a plurality of cache sub-blocks implemented as a cache for the primary storage device; and a controller configured to map at least one portion of one or more primary sub-blocks of the primary storage device stored in the cache to a physical location in the cache memory device using at least one table identifying portions of the primary storage device that are cached in one or more of the cache sub-blocks of the cache memory device, wherein a size of the at least one table is independent of a capacity of the primary storage device.

Abstract: Embodiments are generally directed to systems, devices, methods, and techniques to control devices via a mobile device platform in a smart building system. Embodiments further include techniques to determine a device of the smart building system and an action to perform by the device. The techniques include establishing, a connection with a smart lock of the smart system, and communicating a request to perform the action to the smart lock of the smart system.

Abstract: A dynamically reconfigurable computational storage drive (CSD) that facilitates parallel data management functionality for a plurality of associated memory devices. The CSD includes an FPGA device that is dynamically reconfigurable during operation of the CSD to provide one or more data management functionality. The CSD interfaces with a plurality of storage controllers for parallel data management functionality applied to a corresponding plurality of memory devices. The CSD may be provided as a rack-mounted device or a storage appliance for dynamic provision of data management functionality to data in a storage system comprising the CSD.

Abstract: Embodiments are generally directed to systems, devices, methods, and techniques to control devices via a mobile device platform in a smart building system. Embodiments further include techniques to determine a device of the smart building system and an action to perform by the device. The techniques include establishing, a connection with a smart lock of the smart system, and communicating a request to perform the action to the smart lock of the smart system.

Abstract: Techniques are disclosed for explaining and visualizing an output of a machine learning system that detects cardiac arrhythmia in a patient. In one example, a computing device receives cardiac electrogram data sensed by a medical device. The computing device applies a machine learning model, trained using cardiac electrogram data for a plurality of patients, to the received cardiac electrogram data to determine, based on the machine learning model, that an episode of arrhythmia has occurred in the patient and a level of confidence in the determination that the episode of arrhythmia has occurred in the patient. In response to determining that the level of confidence is greater than a predetermined threshold, the computing device displays, to a user, a portion of the cardiac electrogram data, an indication that the episode of arrhythmia has occurred, and an indication of the level of confidence that the episode of arrhythmia has occurred.

Abstract: Systems and methods are disclosed herein for implementation of a vehicle command operation system that may use multi-modal technology to authenticate an occupant of the vehicle to authorize a command and receive natural language commands for vehicular operations. The system may utilize sensors to receive data indicative of a voice command from an occupant of the vehicle. The system may receive second sensor data to aid in the determination of the corresponding vehicular operation in response to the received command. The system may retrieve authentication data for the occupants of the vehicle. The system authenticates the occupant to authorize a vehicular operation command using a neural network based on at least one of the first sensor data, the second sensor data, and the authentication data. Responsive to the authentication, the system may authorize the operation to be performed in the vehicle based on the vehicular operation command.

Abstract: Techniques are described herein for improving performance of machine learning model(s) and thresholds utilized in determining whether automated assistant function(s) are to be initiated. A method includes: receiving, via one or more microphones of a client device, audio data that captures a spoken utterance of a user; processing the audio data using a machine learning model to generate a predicted output that indicates a probability of one or more hotwords being present in the audio data; determining that the predicted output satisfies a secondary threshold that is less indicative of the one or more hotwords being present in the audio data than is a primary threshold; in response to determining that the predicted output satisfies the secondary threshold, prompting the user to indicate whether or not the spoken utterance includes a hotword; receiving, from the user, a response to the prompting; and adjusting the primary threshold based on the response.

Abstract: In an embodiment, a processor may include an execution circuit to execute a plurality of instructions. The processor may also include a prediction circuit to: in response to a detection of a first target instruction in a program, identify a prediction data entry associated with a path history for the first target instruction, the identified prediction data entry to indicate an offset distance from the first target instruction to a predicted next taken branch of the program; and determine the predicted next taken branch of the program based on the offset distance indicated by the identified prediction data entry. Other embodiments are described and claimed.

Abstract: In an embodiment, a processor may include an execution circuit to execute a plurality of instructions, a cache, and a decode circuit. The decode circuit may be to: detect a branch instruction in a program, the branch instruction to cause execution to follow either a first path or a second path in the program; and in response to a determination that the branch instruction is a hard to predict (HTP) branch, cause first and second sets of instructions to be stored in the cache, where the first set of instructions is included in the first path, and where the second set of instructions is included in the second path. Other embodiments are described and claimed.

Abstract: A technique replicates an index of an operations log (oplog) from a primary node to a secondary node of a cluster in the event of failure. The oplog functions as a staging area to coalesce random write operations directed to a virtual disk (vdisk) stored on a backend storage tier. The oplog temporarily caches write data as well as metadata describing the write data. The metadata includes descriptors to the write data corresponding to offset ranges of the vdisk and are used to identify ranges of write data for the vdisk that are cached in the oplog. To facilitate fast lookup operations of whether write data is cached in the oplog, an oplog index provides a state of the latest data for offset ranges of the vdisk that enables fast failover of metadata used to construct the oplog index in memory without downtime or significant metadata replay.

Abstract: Aspects of call routing based on technical skills of users are discussed. Responses to a set of questions posed to a user are received to assess a technical skill level of the user. The user may be categorized in a category from among a plurality of categories based on the technical skill level and a decision may be provided to a route a call from the user to one of a human agent and a virtual agent based on the categorization.

Abstract: A neural network system leverages dual attention, specifically both spatial attention and channel attention, to jointly estimate heart rate and respiratory rate of a subject by processing images of the subject. A motion neural network receives images of the subject and estimates heart and breath rates of the subject using both spatial and channel domain attention masks to focus processing on particular feature data. An appearance neural network computes a spatial attention mask from the images of the subject and may indicate that features associated with the subject's face (as opposed to the subject's hair or shoulders) to accurately estimate the heart and/or breath rate. Channel-wise domain attention is learned during training and recalibrates channel-wise feature responses to select the most informative features for processing. The channel attention mask is learned during training and can be used for different subjects during deployment.

Abstract: In an exemplary technique for providing audio information, an input is received, and audio information responsive to the received input is provided using a speaker. While providing the audio information, an external sound is detected. If it is determined that the external sound is a communication of a first type, then the provision of the audio information is stopped. If it is determined that the external sound is a communication of a second type, then the provision of the audio information continues.

Abstract: Systems and methods for more accurate and robust determination of subject characteristics from an image of the subject. One or more machine learning models receive as input an image of a subject, and output both facial landmarks and associated confidence values. Confidence values represent the degrees to which portions of the subject's face corresponding to those landmarks are occluded, i.e., the amount of uncertainty in the position of each landmark location. These landmark points and their associated confidence values, and/or associated information, may then be input to another set of one or more machine learning models which may output any facial analysis quantity or quantities, such as the subject's gaze direction, head pose, drowsiness state, cognitive load, or distraction state.

Abstract: Disclosed is a midband dipole for use in a multiband antenna. The midband dipole has four folded dipoles, each of which is coupled to a decoupling circuit that has two capacitance points. The disclosed decoupling circuit configuration mitigates common mode resonance with nearby lowband dipoles, further preventing cross polarization in the midband.

Abstract: Techniques are disclosed for detecting arrhythmia episodes for a patient. A medical device may receive one or more sensor values indicative of motion of a patient. The medical device may determine, based at least in part on the one or more sensor values, an activity level of the patient. The medical device may determine a heart rate threshold for triggering detection of an arrhythmia episode based at least in part on the activity level of the patient. The medical device may determine whether to trigger detection of the arrhythmia episode for the patient based at least in part on comparing a heart rate of the patient with the heart rate threshold. The medical device may, in response to triggering detection of the arrhythmia episode, collect information associated with the arrhythmia episode.

Abstract: The invention relates to a method for analysing ribonucleic acid (RNA) interactions comprising: a) cross-linking base-paired nucleotides of at least one RNA molecule and/or at least one pair of RNA molecules using a tagged, reversible cross-linking agent (preferably tagged-psoralen) under ultraviolet irradiation; b) fragmenting the said cross-linked RNA molecule(s); c) using said tag to extract said cross-linked RNA fragment(s); d) ligating the said cross-linked RNA fragment(s) to produce cross-linked ligated RNA chimera(s); e) reversing the cross-linking of the said agent to the said RNA molecule(s); f) preparing a sequence library by sequencing the ligated RNA chimera molecule(s) or pair(s); and g) analysing the sequence library to determine RNA interactions. Also disclosed is a method of studying a subject by analysing RNA interactions and attributing them to a clinical picture, or a drug discovery method by attributing an efficacy score to the drug based upon determined RNA interactions.

Abstract: State information can be determined for a subject that is robust to different inputs or conditions. For drowsiness, facial landmarks can be determined from captured image data and used to determine a set of blink parameters. These parameters can be used, such as with a temporal network, to estimate a state (e.g., drowsiness) of the subject. To improve robustness, an eye state determination network can determine eye state from the image data, without reliance on intermediate landmarks, that can be used, such as with another temporal network, to estimate the state of the subject. A weighted combination of these values can be used to determine an overall state of the subject. To improve accuracy, individual behavior patterns and context information can be utilized to account for variations in the data due to subject variation or current context rather than changes in state.

Abstract: Examples of the present disclosure describe systems and methods for a windowing container that enables two or more windows associated with application(s) to be grouped within the container such that the windows may behave or function uniformly as a single window. For example, responsive to a request to group two windows, a container may be generated to include the windows arranged based on one or more rules and features enabling group functions associated with the container to be performed. When a group function is performed on the container, the function may be performed to each of the windows arranged therein as if they were a single window. As new windows are grouped within or existing windows are released from the container, the container and/or windows may be rearranged based on the rules. A state of the container may be stored to enable subsequent invocation of the container after closing.

Abstract: System for providing troubleshooting solutions for an electronic device is described. The system includes a query engine, that may receive a troubleshoot query from a user of the electronic device. The troubleshoot query indicates a device model of the electronic device and an issue with the electronic device. Further, the query engine may identify a context vector corresponding to the device model based on a mapping table and the device model. The context vector describes a relationship between the device model, a plurality of troubleshoot support documents, and functional features of the device model. Further, the system includes a machine learning engine to determine a troubleshooting solution for the issue based on the issue and the context vector corresponding to the device.