Abstract: In a method for improving converter and compiler operator granularity, a processor extracts an operator granularity from an artificial intelligence framework and an original model. A processor receives device characteristics from a target device. A processor outputs a converter granularity level to a converter based on the operator granularity and the device characteristics. A processor outputs a compiler granularity level to a compiler based on the operator granularity and the device characteristics.

Abstract: Systems and methods for determining control objective for electronic documents using models may include obtaining electronic documents and a control objectives library, determining a first set of summaries based on the electronic documents, extracting a set of embeddings from the control objectives library, and determining a set of control objectives based on the summaries and the embeddings. The method may also include determining control objective candidates based on the summaries and embeddings, ranking the control objective candidates based on a confidence score, filtering the control objective candidates based on the ranking, categorizing the control objectives candidates into a second and third set of control objectives, updating the control objectives library to include one or more control objectives from the third set of control objectives, and validating control objectives in the third set of control objectives based on a test plan and updating the control objectives library that pass validation.

Abstract: A metered-dose atomization module, an atomizer, a spray assembly and the use thereof. The metered-dose atomization module includes: a spray head in which an atomization cavity has a step surface; an atomization piece, including an annular brake and a microporous membrane attached to a side surface of the annular brake; rubber rings, including a first sealing ring and a second sealing ring, the first sealing ring and the second sealing ring being annular and arranged on two sides of the atomization piece respectively; and a pressing plate, the pressing plate being annular and fixed to the spray head, and being adapted to cooperate with the step surface to install the atomization piece and the rubber rings in the atomization cavity.

Abstract: Provided are a method and an apparatus for controlling an under-display camera, and the under-display camera structure. The method includes: when a camera is in a turned-on state, lamp beads close to a camera end are turned off and lamp beads far away from the camera are controlled to be in a lighting state, and light emitted by the second-type lamp beads forms a circle of light on the convex glass after being refracted by the convex glass; and when the camera is in a turned-off state, the plurality of lamp beads are controlled to be in a lighting state, and backlight for the convex glass after being refracted is provided by the convex glass. When the camera is turned on, the light emitted by the lamp beads far away from the camera forms a circle of light on the convex glass after being refracted by the convex glass.

Abstract: An inspiratory trigger atomizer for a patient with an airway disease, including: a main body including an atomization module and a nozzle connected thereto; an atomization driver; an air pressure sensor electrically connected to the driver, and a gas guide channel arranged in the main body, with a first end located in the nozzle and a second at a monitoring end of the sensor. The sensor acquires the air pressure in the nozzle that changes with the patient's breathing, identifies the inhalation state of the patient and generates a corresponding signal to trigger a main unit module to start the atomization driver. The atomizer has an extremely short inspiratory trigger response time, such that atomization can be quickly triggered after the patient inhales, and with atomization duration being 1.5 s, the patient can fully inhale a drug, so the atomizer can be applied to a wide range of people.

Abstract: Aspects of the invention include generating a plurality of predictions that each define a plurality of future inputs for a model. A deviation curve is generated by determining a distance between each prediction of the plurality of predictions and a respective known data point of a plurality of known data points. One or more points in the deviation curve are sampled and the sampled points are compared to a low threshold and a high threshold. A judgement is determined for each prediction to determine whether the respective prediction will be accepted or denied as an input to the model. The future inputs for the model are modified based on the judgments.

Abstract: Disclosed is a display panel, including a first display portion including a plurality of first pixel units, each of which includes a light-emitting element and a control element sequentially arranged in a thickness direction of the display panel, where the control element is configured to perform switching between a light-transmissive state and a light-shielding state under the control of an electric field, and the light-emitting element is configured to emit light under the control of a driving voltage. Further provided are a control method for the display panel, a control module for implementing the control method, and a display apparatus including the display panel.

Abstract: Provided are a flexible screen support device and an intelligent terminal. The flexible screen support device includes a bending plate, a connection rope, and a driving mechanism. The bending plate includes multiple support blocks hingedly connected in sequence. The width of the upper part of each support block gradually decreases to form a rotation gap between adjacent support blocks. One part of the connection rope penetrates through the upper parts of the multiple support blocks. The other part of the connection rope penetrates through the lower parts of the multiple support blocks. The driving mechanism is configured to pull the one part of the connection rope so that the upper parts of adjacent support blocks are in contact with one another to bend the bending plate. The intelligent terminal includes a flexible screen and the described flexible screen support device.

Abstract: A method, system, and computer program product for dependency-based software upgrading. The method may include determining respective dependency degrees between a plurality of software products based on property information related to a plurality of upgraded versions of the plurality of software products, a target software product depending on the plurality of software products. The method may also include dividing the plurality of software products into a plurality of groups of software products based on the respective dependency degrees. The method may also include determining a plurality of test scores associated with the plurality of groups, each test score indicating a performance enhancement degree of the target software product achieved by installing upgraded versions of at least one software product comprised in one of the plurality of groups. The method may also include determining a target upgrade solution for the target software product based on the plurality of test scores.

Abstract: A method determines corrected TRP or TIS of an AUT in a near-field test chamber, the AUT having a phase center offset from a rotation center of the test chamber. The method includes performing EIRP or EIS measurements of the AUT at first sampling grid points on a first closed-surface geometric shape centered at the rotation center; mapping second sampling grid points to the first closed-surface geometric shape to provide mapped sampling grid points on the first closed-surface geometric shape, where the second sampling grid points are on a second closed-surface geometric shape centered at the phase center of the AUT; determining estimated EIRPs or EISs at the mapped sampling grid points using the EIRP or EIS measurements; scaling the estimated EIRPs or EISs at the mapped sampling grid points to provide scaled EIRPs or EISs; and calculating the corrected TRP or TIS based on the scaled EIRPs or EISs.

Abstract: Disclosed herein are a method and system for evaluating the battery loss of a new energy vehicle. The method includes: Step 1, acquiring factory data of a vehicle, the initial charge electric quantity of the vehicle and the duration for full charge of the vehicle; Step 2, according to the factory data of the vehicle, calculating a theoretical duration for full charge of the vehicle at each of the electric quantity levels; and Step 3, forming a plurality of reference standards by dividing in the unit of time, making the plurality of reference standards correspond to a plurality of battery health levels, and determining the battery loss degree according to the range of the reference standard where the duration difference mean value falls. The battery loss is evaluated quantitatively by means of the decrement of the charge duration.

Abstract: A foldable terminal is disclosed, which may include a first storage rotation shaft, a second storage rotation and a flexible screen. One end of the flexible screen is connected and fixed to the first storage rotation shaft, and the other end of the flexible screen is connected and fixed to the second storage rotation shaft. And a portion of the flexible screen is wound around at least one of the first storage rotation shaft and the second storage rotation shaft. In response to the flexible screen being folded, the first storage rotation shaft is rotatable to release the flexible screen, and in response to the flexible screen being unfolded, the second storage rotation shaft is rotatable to roll up the flexible screen.

Abstract: Aspects of the invention include converting an artificial intelligence (AI) model generated in a first framework to a uniform exchange formatted model by engaging a master table to retrieve instructions for converting from the AI model to the uniform exchange formatted model in accordance with the first framework. The uniform exchange formatted model in compiled by engaging the master table to retrieve instructions for compiling the uniform exchange formatted model in accordance with the first framework. Data is received as an input to the compiled uniform exchange formatted model and an output is generated by engaging the master table to retrieve instructions for generating the output in accordance with the first framework.

Abstract: A computer-implemented method to estimate computing cost of database queries. The method includes receiving a query. The method also includes generating one or more access plans for the query. The method further includes dynamically generating a learning model based on each of the generated access plans. The method includes estimating, by the learning model and for each of the one or more access plans, a predicted cost to execute the query. The method includes selecting, based on the predicted cost, a first access path associated with a lowest cost of the predicted costs and executing the query according the selected access path.

Abstract: Provided herein are inter alia, unnatural amino acids based on fluorosulfonyloxybenzoyl-L-lysine FSK, proteins comprising unnatural amino acids, nanobodies comprising unnatural amino acids based on fluorosulfate-L-tyrosine FSY, meta-FSY and FFY within CDR1, CDR2, or CDR3, biomolecule conjugates, and methods of making the proteins and biomolecule conjugates.

Abstract: Aspects of the present disclosure involve, a customizable system and infrastructure which can receive privacy data from varying data sources for privacy scanning, containment, and reporting. In one embodiment, data received is scanned for privacy data extraction using various data connectors and decryption techniques. In another embodiment, the data extracted is transferred to a privacy scanning container where the data is analyzed by various deep learning models for the correct classification of the data. In some instances, the data extracted may be unstructured data deriving form emails, case memos, surveys, social media posts, and the like. Once the data is classified, the data may be stored or contained according to the classification of the data. Still in another embodiment, the classified data may be retrieved by an analytics container for use in reporting.

Abstract: A method determines corrected TRP or TIS of an AUT in a near-field test chamber, the AUT having a phase center offset from a rotation center of the test chamber. The method includes performing EIRP or EIS measurements of the AUT at first sampling grid points on a first closed-surface geometric shape centered at the rotation center; mapping second sampling grid points to the first closed-surface geometric shape to provide mapped sampling grid points on the first closed-surface geometric shape, where the second sampling grid points are on a second closed-surface geometric shape centered at the phase center of the AUT; determining estimated EIRPs or EISs at the mapped sampling grid points using the EIRP or EIS measurements; scaling the estimated EIRPs or EISs at the mapped sampling grid points to provide scaled EIRPs or EISs; and calculating the corrected TRP or TIS based on the scaled EIRPs or EISs.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: An approach to optimize performance for large scale inference models. Data in the form of images is received from sensors such as cameras. The data is processed to generate data tags associated with the context of the image and portion the images. Model tags are generated based on data characteristics or user input. The tags and their associated data are added to a time-based queue for delivery to the appropriate inference models. Based on the embedded delivery time and frequency, the portioned images are delivered to the appropriate inference models.

Abstract: A system is provided for measuring a power radiated pattern of an incident radio frequency (RF) signal indicating spatial distribution characteristics of a device under test (DUT). The system includes multiple antenna elements arranged in an array, where the antenna elements include antennas and diodes coupled to the antennas, respectively. Each antenna has a radar cross-section (RCS) that is too small for the antenna elements to operate in a reflect mode. Each diode is zero biased, such that the diodes receive the incident RF signal through the antennas to which the diodes are respectively coupled, and rectify the incident RF signal to DC voltages that are proportional to power of the incident RF signal, enabling the antenna elements to operate in a detect mode.