Abstract: The disclosure relates to an electronic apparatus for recognizing user voice and a method of recognizing, by the electronic apparatus, the user voice. According to an embodiment, the method of recognizing the user voice includes obtaining an audio signal segmented into a plurality of frame units, determining an energy component for each filter bank by applying a filter bank distributed according to a preset scale to a frequency spectrum of the audio signal segmented into the frame units, smoothing the determined energy component for each filter bank, extracting a feature vector of the audio signal based on the smoothed energy component for each filter bank, and recognizing the user voice in the audio signal by inputting the extracted feature vector to a voice recognition model.

Abstract: Systems and methods include responsive to a user initiating a session with a resource, determining a master fingerprint of a device associated with the user; collecting, at predefined time intervals, one or more additional fingerprints during the session; comparing the one or more additional fingerprints with the master fingerprint; and performing one or more actions based on the comparing.

Abstract: Certain example embodiments relate to a method for selecting wireless ridelity (Wi-Fi) channel for mitigating and/or reducing interference, wherein the method may detect the presence of nearby access points and determine the number of access points by an access point detector module. The method may determine the minimum value of received signal strength indicator (RSSI) by the access point detector module, and may determine the congestion information from the nearby devices by a peer congestion observer module. Furthermore, the method may calculate at least one weighted parameter and select a preferred channel to create a hotspot for communication by a channel selector module.

Abstract: Techniques for presenting a search result with an improved user interface. A computer system can receive, from a user device, a request for a content item. Additionally, the system can select, based on the request, a first content item from a plurality of content items. The first content item can be associated with an organization image and an organization name of an organization. Moreover, the system can process, using one or more machine-learned model, the organization image to determine whether the organization image is acceptable to be presented in the search result. Subsequently, the system can transmit, to the user device, the first content item and the organization image to be presented in the search result.

Abstract: A method for AI-driven augmented reality mentoring includes determining semantic features of objects in at least one captured scene, determining 3D positional information of the objects, combining information regarding the identified objects with respective 3D positional information to determine at least one intermediate representation, completing the determined intermediate representation using machine learning to include additional objects or positional information of the objects not identifiable from the at least one captured scene, determining at least one task to be performed and determining steps to be performed using a knowledge database, generating at least one visual representation relating to the determined steps for performing the at least one task, determining a correct position for displaying the at least one visual representation, and displaying the at least one visual representation on the see-through display in the determined correct position as an augmented overlay to the view of the at least

Abstract: The system can include a set of joints, a controller, and a model engine; and can optionally include a support structure and an end effector. Joints can include: a motor, a transmission mechanism, an input sensor, and an output sensor. The system can enable articulation of the plurality of joints.

Abstract: Disclosed are systems, apparatuses, processes, and computer-readable media to provide haptic feedback in electronic devices based on contextual awareness. A method of processing image data includes receiving at least one image of a patient; providing the image of the patient to a trained model for segmenting the image; and processing the image based on a multi-stage trained model to segment the image into a plurality of segmented images that are separated based on plaque components.

Abstract: A method of and system for human interactions with a computer user interface using neurological signals from the frontal part of the human brain, also known as the prefrontal cortex. In one embodiment, the system comprised a brain-computer interface system and a method of filtering, processing and analyzing neurological signals over a specific period of time to trigger, activate or control on-demand a computer user interface without the need of any preliminary brain state recording nor traditionally-required external stimulus.

Abstract: A method for aborting a command for PCIe based NVMe SSD includes receiving an abort command in an Admin submission queue to abort a target command present in an I/O submission queue of host or in an I/O queue of the NVMe SSD and updating a tail doorbell of NVMe doorbell registers of the NVMe SSD after receiving the abort command. The abort command includes a slot of the target command to be aborted. Thereafter, the method includes placing the abort command into an Admin queue of the NVMe SSD and executing the abort command using the slot of the target command to be aborted by updating an I/O completion queue of the host with the target command to be aborted. The method further includes updating a head doorbell of the doorbell registers of the NVMe SSD and updating the abort command in an Admin completion queue of the host.

Abstract: Generally, the present disclosure is directed to user interface understanding. More particularly, the present disclosure relates to training and utilization of machine-learned models for user interface prediction and/or generation. A machine-learned interface prediction model can be pre-trained using a variety of pre-training tasks for eventual downstream task training and utilization (e.g., interface prediction, interface generation, etc.).

Abstract: The present disclosure relates to a method of producing metallurgical coke from a combination of non-coking and non-metallic carbon-based microwave susceptor. The method is energy efficient, economical, and environmentally friendly. The present disclosure also relates to metallurgical coke having improved coke quality, such as improved coke strength after reaction.

Abstract: A vehicle includes a primary axle powered by an actuator and a secondary axle powered by a motor and including a wheel and a clutch selectively coupling the wheel to the motor via mating components. A controller is electrically connected to the clutch and the motor. The controller is programmed to, in response to an engagement of the clutch being unsuccessful within a first duration of time, command a series of speeds to the motor based on wheel speed and an alternating offset that changes between positive and negative signs at predefined periods so that relative speeds between the mating components oscillate due to the alternating offset to jiggle the clutch into engagement.

Abstract: The present disclosure relates to synthetic biology and, in particular, the bioproduction of bakuchiol, and engineered enzymes for producing the same.

Abstract: Generally, the present disclosure is directed to user interface understanding. More particularly, the present disclosure relates to training and utilization of machine-learned models for user interface prediction and/or generation. A machine-learned interface prediction model can be pre-trained using a variety of pre-training tasks for eventual downstream task training and utilization (e.g., interface prediction, interface generation, etc.).

Abstract: A method includes receiving data indicating a plurality of dimensions of a manufactured device. The method further includes providing the data to a trained machine learning model. The method further includes receiving, from the trained machine learning model, a synthetic microscopy image associated with the manufactured device, wherein the synthetic microscopy image is generated in view of the first data. The method further includes performing at least one of (i) outputting the synthetic microscopy image to a display or (ii) performing one or more operations on the synthetic microscopy image.

Abstract: An analytics system identifies interventions for individual samples from a set of samples with a mixture of interventions. Given a causal graph, a set of baseline samples, and a set of samples with interventions, a set of intervention tuples is determined that represents the mixture of interventions for the set of samples with interventions. Each intervention tuple in the set of intervention tuples identifies an intervention and a mixing coefficient representing a percentage of samples with the intervention. An iterative process is used in which a set of intervention tuples is determined for N variables and then lifted to a set of intervention tuples for N+1 variables until all variables from the causal graph have been considered, providing a final set of intervention tuples. The final set of intervention tuples is used to match individual samples from the set of samples with interventions to interventions.

Abstract: A method for aborting a command in PCIe based NVMe SSD includes receiving an abort command in an Admin submission queue to abort a target command present in an I/O submission queue of host or in an I/O queue of the NVMe SSD and updating a tail doorbell of NVMe doorbell registers of the NVMe SSD after receiving the abort command. The abort command includes a slot of the target command to be aborted. Thereafter, the method includes placing the abort command into an Admin queue of the NVMe SSD and executing the abort command using the slot of the target command to be aborted by updating an I/O completion queue of the host with the target command to be aborted. The method further includes updating a head doorbell of the doorbell registers of the NVMe SSD and updating the abort command in an Admin completion queue of the host.

Abstract: The invention relates to methods of diagnosing, prognosing, or monitoring or staging the progression of non-alcoholic fatty liver disease (NAFLD) using biomarkers. The invention also relates to a method of scoring to determine the severity of NAFLD, and a method of treating NAFLD.

Abstract: A method includes determining a plurality of features of a first original image of a first product that are expected to be different for one or more products to be produced via manufacturing parameters of a manufacturing process compared to the first product. The method further includes adjusting one or more of the plurality of features of the first original image to generate a first synthetic image. The method further includes providing a plurality of images including the first original image and the first synthetic image to train a machine learning model to generate a trained machine learning model configured to generate output associated with updating the manufacturing parameters of the manufacturing process.

Abstract: A method includes: receiving, by a storage device from a core in a host, a request to provide exclusive resource to a command of a predefined submission queue of a non-volatile memory (NVM) set in the storage device, wherein the request pertains to operating the NVM set in a deterministic state; generating a virtual NVM set identifier for a virtual NVM set based on a predefined mapping of the predefined submission queue and the NVM set; determining a storage controller associated with the NVM set based on a predefined mapping of the predefined submission queue, the NVM set, and the virtual NVM set identifier; enabling at least one core to operate in a Predictable Latency Mode; and operating the storage controller and the NVM set in the deterministic state by allocating predetermined resources to execute the command and return data with a predictable latency.