Abstract: A method of acquiring an image, an apparatus of acquiring an image and a method of detecting a defect are provided, which relate to a field of image acquisition and processing. The method includes: capturing an image of a target object with lighting of a shadowless light source, where the image contains first and second regions of the target object which have different surface heights from each other; calculating N feature values of the image according to a relative positional relationship between the first and second regions; determining a displacement correction value of the shadowless light source according to the N feature values, in response to the N feature values not meeting a predetermined condition; and adjusting a position of the shadowless light source according to the displacement correction value to re-capture the image and re-calculate the N feature values until the N feature values meet the predetermined condition.

Abstract: Disclosed herein are embodiments of a method of training a machine learning prediction model for use in an open loop transfer function estimator of a hearing aid. The method uses simulation data representing sound from a known, simulated acoustic environment of the hearing aid, the simulation data including a feedback path transfer function representative of an impulse response of a feedback path of the hearing aid.

Abstract: Provided is a method of training an image recognition model, the model is configured to detect a defect region in an image of a display substrate, the display substrate includes a display area and a connection area, and the method includes: acquiring a first training sample including images of n display substrates; dividing each of the images of n display substrates into a first sub image and a second sub image, the first sub image is an image of a display area, and the second sub image is an image of a connection area; inputting the first training sample into the image recognition model, the first training sample includes the first sub image and the second sub image; and adjusting at least one feature parameter of the image recognition model to reduce a difference between an output value of the model and a training value of the first training sample.

Abstract: The present disclosure relates to an organosilica membrane with a porous intermediate layer and a method for preparing the same. The method includes: treating carbon nanotubes with an acid, washing, and drying to obtain carboxylated carbon nanotubes (COOH-CNTs); adding water to the COOH-CNTs and a SiO2—ZrO2 sol, and mixing uniformly to obtain a COOH-CNTs/SiO2—ZrO2 sol; coating the COOH-CNTs/SiO2—ZrO2 sol onto a tubular ceramic support, and calcining to obtain a ceramic support with a porous intermediate layer; and coating an organosilica sol onto the ceramic support with the porous intermediate layer, and performing a heat treatment to form a separation layer, thereby obtaining the organosilica membrane.

Abstract: A method for controlling a robot. The method includes performing demonstrations and descriptor images for the demonstrations from a point of view of the robot of the object; selecting a set of feature points, wherein the feature points are selected by searching an optimum of an objective function which rewards selected feature points being visible in the descriptor images; training a robot control model using the demonstrations and controlling the robot for a control scene with the object by determining a descriptor image of the object, locating the selected set of feature points in the descriptor image of the object; determining Euclidean coordinates of the located feature points; estimating a pose from the determined Euclidean coordinates; and controlling the robot to handle the object by means of the robot control model with the estimated pose.

Abstract: A method of detecting a sudden change in a feedback/echo path of a hearing aid is based on a gradient of an adaptive filter comprising an adaptive algorithm configured to estimate the feedback/echo path. The method may comprise comparing a smoothed and processed version of the gradient values over time to a threshold value. A hearing aid configured to detect a sudden change in a feedback/echo path is furthermore provided.

Abstract: A hearing aid comprises a forward path comprising a) an input transducer for converting sound (x(n), v(n)) in an environment around the hearing aid to an electric input signal (y(n)) representing said sound; b) a hearing aid processor for processing said electric input signal (y(n)), or a signal originating therefrom (e(n)), and to provide a processed signal (u(n)) based thereon; c) an output transducer for converting said processed signal (u(n)), or a signal originating therefrom (ua(n)), to acoustic stimuli presented to said eardrum of the user. The hearing aid further comprises d) a feedback control system for attenuating or cancelling feedback propagated via a feedback path (H) from an electric input signal to said output transducer to an electric output from said input transducer.

Abstract: A preparation method for a CDK4/6 inhibitor for a compound of formula (I):5-fluoro-4-(3-isopropyl-2-methyl-2H-indazol-5-yl)-N-(5-(piperazin-1-yl) pyrazol-2-yl)pyrimidine-2-amine. The preparation method has cheap and readily available starting materials and reagents, greatly simplified total reaction steps, shortened reaction time, improved total yield and a high purity of the key intermediate and final product, being suitable for industrial production.

Abstract: Disclosed herein are embodiments of methods, performed by an electronic device, for training a machine learning (ML) model for use in a feedback control system of a hearing aid. The method can include executing a plurality of training iterations using training data including a training input signal and a training processed signal. Each training iteration of the plurality of training iterations can include updating the ML model based on a target data and an estimate of the training feedback path transfer function. Embodiments of the ML model includes, in the following order, a convolutional layer, a first fully connected (FC) layer, and a long-short term memory (LSTM) layer.

Abstract: A method for controlling a robot device. The method includes providing a selection model and executing multiple instances of a task, including, in each execution, when a function of the robot device needs to be selected to perform the task instance, checking whether the selection model provides a selection of a function and, if yes, controlling the robot device to perform the function selected by the selection model and if no, receiving user input indicating a selection of a function, selecting a function according to the selection indicated by the user input, controlling the robot device to perform the function selected according to the selection indicated by the user input and training the selection model according to the selection indicated by the user input.

Abstract: A hearing aid includes an input unit, an output unit, a signal processing unit connected to said input unit and output unit, where the input unit, the signal processing unit and the output unit are forming part of a forward path of the hearing aid, where the signal processing unit is configured to apply a forward gain to the at least one electric input signal or a signal originating therefrom. The hearing aid further includes a feedback control unit configured to reduce a risk of howl due to acoustic, electrical, and/or mechanical feedback of an external feedback path from the output unit to the input unit of said hearing aid, where the hearing aid is configured to receive motion data characterising movement and/or acceleration and/or orientation and/or position of the hearing aid to control processing.

Abstract: Disclosed herein are embodiments of a method of training a machine learning prediction model for use in an open loop transfer function estimator of a hearing aid. The method uses simulation data representing sound from a known, simulated acoustic environment of the hearing aid, the simulation data including a feedback path transfer function representative of an impulse response of a feedback path of the hearing aid.

Abstract: The present disclosure discloses a preparation method of an organosilica/ceramic composite membrane with a gradient pore structure. The preparation method comprises: (1) selecting a porous ceramic material as a membrane support layer; (2) gradually replacing a solvent with water to prepare zirconium colloidal sols with different particle sizes, and successively coating the prepared zirconium colloidal sols onto a ceramic support from large to small so as to form a membrane transition layer with a gradient pore structure; and (3) catalytically synthesizing an organosilica polymeric sol using hydrochloric acid, coating the prepared organosilica sol onto the preheated transition layer through ultrasonic thermal spraying to undergo heat treatment, so as to prepare the organosilica/ceramic composite membrane with the gradient pore structure. According to the present disclosure, the transition layer with the gradient pore structure is prepared by using the zirconium colloidal sols with different particle sizes.

Abstract: A curved substrate bubble detection method includes: providing, by a first light source and a second light source, parallel light incident to a to-be-tested substrate in different incident directions; obtaining, by a linear array camera, a first image including image information of a first side edge of the to-be-tested substrate; determining location information of a defect region of the to-be-tested substrate according to the first image, and generating a second image including image information of the defect region; binarizing the second image, and determining that the to-be-tested substrate has a bubble defect if there are at least two bright spots in an obtained binarized image, and a distance between any two first bright spots of at least two first bright spots is less than a first preset value. A curved substrate bubble detection system is also disclosed.

Abstract: Disclosed herein are embodiments of a hearing aid configured to be worn by a user. The hearing aid can include a user interface allowing the user to control functionality of the hearing aid, and a feedback sensor for repeatedly providing a feedback signal indicative of a current estimate of feedback from an output transducer to an input transducer of the hearing aid, wherein the user interface is based on changes to the current estimate of the feedback path, e.g. provided by the user.

Abstract: Disclosed are a crystalline form of a five-membered N heterocyclic compound, particularly, a crystalline form of a compound as represented by formula I, and an application of the crystalline form in preparation of a medication for preventing or treating a disease benefiting from inhibition of capsid protein assembly.

Abstract: A hearing aid configured to be worn by a user, the hearing aid comprising a user interface allowing the user to control functionality of the hearing aid, and a feedback sensor for repeatedly providing a feedback signal indicative of a current estimate of feedback from an output transducer to an input transducer of the hearing aid, wherein the user interface is based on changes to the current estimate of the feedback path, e.g. provided by the user. A method of operating a hearing aid is further disclosed. Thereby an alternative user interface for a hearing aid may be provided. The invention may e.g. be used in hearing aids or headsets, or a combination thereof.

Abstract: Disclosed by the present application is a crystalline form of a capsid protein assembly inhibitor containing an N hetero five-membered ring; specifically disclosed is the crystalline form of the compound of formula I; also comprised is an the application of said crystalline form in the preparation of a drug for preventing or treating diseases benefiting from the inhibition of capsid protein assembly.