Abstract: An apparatus for a high-intensity focused ultrasound (HIFU) generation device includes: an ultrasonic radiation frame comprising at least one coupling hole formed therein; at least one transducer holder inserted into the at least one coupling hole, wherein the at least one transducer holder is detachably coupled to the ultrasonic radiation frame; and at least one transducer mounted in the at least one transducer holder. At least a part of a side surface of a respective transducer holder of a respective transducer holder comprises an opening formed therein.

Abstract: A display substrate, including: a base substrate; a plurality of gate lines and a plurality of data lines that intersect to surround a plurality of pixels; wherein each pixel includes a first thin film transistor, a second thin film transistor and a pixel electrode. A first electrode of the first thin film transistor is electrically connected to a pixel conductive layer of the pixel electrode, a second electrode of the first thin film transistor is electrically connected to a first electrode of the second thin film transistor, and a second electrode of the second thin film transistor is electrically connected to the data line. An orthographic projection of a combination of the second electrode of the first thin film transistor and the first electrode of the second thin film transistor on the base substrate at least partially overlaps with an orthographic projection of the pixel conductive layer on the base substrate.

Abstract: Methods and systems for managing data processing systems are disclosed. A data processing system may include and depend on the operation of hardware and/or software components. Inference models may be implemented to predict future system infrastructure outcomes (e.g., component failures) using information recorded in logs that reflect the operation of the components. However, the models may be complex “black boxes” and may generate critical outcome predictions for downstream consumers without explanations of how the predictions are determined, resulting in downstream consumers having low confidence in the predictions. Therefore, hidden knowledge (e.g., structured knowledge attributes) of the models may be extracted and/or used to understand the underlying processes that the models use to predict the system infrastructure outcomes.

Abstract: A high-intensity focused ultrasound generator according to the present invention has a plurality of transducers mounted to respective transducer holders and the transducer holders detachably coupled to an ultrasonic radiation frame, and thus allows easy replacement and repair of the transducers in a separate manner, and further, by sealing between the inner surface of the transducer holder and the transducer by means of the adhesion of a flexible glue, leakage may be prevented, and the front surface of the transducer is not blocked by the glue, and thus loss of ultrasonic energy generated forward from the front surface of the transducer may be prevented and efficiency may be enhanced.

Abstract: Image processing is described. An example method includes generating a feature extraction layer portion of an image classification model based on a deep neural network (DNN) model, and extracting features of a group of images by using the feature extraction layer portion. The method further includes training an output layer portion of the image classification model according to the features of training images in the group of images and classification labels of the training images. The method further includes generating the image classification model by combining the feature extraction layer portion and the output layer portion. Embodiments of the present disclosure implement a lightweight artificial intelligence (AI) solution on a storage system. An expanded storage system can facilitate the generation of AI applications and assist in training an image classification model more quickly, and the obtained image classification model can also produce high accuracy on a small training set.

Abstract: Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for recognizing object regions in an image. The method includes detecting edges in an image based on pixels in the image. The method further includes segmenting the image into a plurality of semantic regions based on semantics of objects in the image. The method further includes recognizing, based on the edges and the plurality of semantic regions, object regions covering the objects. In this way, the positions of objects including graphic elements in the image and the tags of the objects can be automatically recognized, thus improving the efficiency of subsequent processing of the image.

Abstract: Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for generating images. The method includes acquiring a descriptive text for describing image content of a target image, determining position prior information, and generating the target image based on the descriptive text and position prior information. According to the method of the embodiments of the present disclosure, a target image that can be used for rare data simulation in rare scenarios can be generated by means of an input descriptive text. In addition, the method allows for position perception editing and operation, and can control, based on position prior information, a direction and a position of an object generated in the target image, thereby effectively and diversely generating images. Moreover, the method provided in the present disclosure is based on object types in each subdivided image block, thus making position perception more accurate.

Abstract: Methods and systems for managing data processing systems are disclosed. A data processing system may include and depend on the operation of hardware and/or software components. To manage the operation of the data processing system, a data processing system manager may obtain logs for components of the data processing system. Inference models may be implemented to predict likely future component failures (e.g., failure sequences) and their associated times-to-failures using information recorded in the logs. The failure sequences may be presented as an acyclic graph that associates component failures, their times-to-failure, and related actions. The probable failure sequences may be analyzed to identify sets of actions. The sets of actions may be optimized based on deviations detected during executing the sets of actions to optimize operational goals (e.g., maximizing system lifetime, minimizing system costs), and/or reduce the likelihood of the data processing system becoming impaired.

Abstract: Methods and systems for managing display of a website to a user are disclosed. Data processing systems operating the website may perform operator actions that increase the likelihood of achieving operational goals, such as presenting relevant content to the user to increase view time and/or user retention. To identify appropriate operator actions, logs (e.g., historical browsing data) may be obtained for various users of the website. The logs may record user actions, operator actions, and/or other information that describes historical and/or current user browsing activity. Inference models may be implemented to predict probable user actions, and associated user action information based on the log information. The predictions may be presented as an acyclic graph that associates the operator actions, user actions, and user action information. The graph may be analyzed to identify operator actions that may maximize user retention and/or increase the likelihood of meeting other operational goals.

Abstract: Methods and systems for managing data processing systems are disclosed. A data processing system may include and depend on the operation of hardware and/or software components. To manage the operation of the data processing system, a data processing system manager may obtain logs for components of the data processing system. The logs may record information that describe and reflect the historical and/or current operation of these components. Inference models may be implemented to predict likely future component failures (e.g., a predicted mean time to first failure (MTFF) of the components) using information recorded in the logs and component specification information from component vendors. The likely future component failures may be analyzed to reduce the likelihood of the data processing system becoming impaired.

Abstract: Embodiments disclosed herein relate to a method, an electronic device, and a computer program product for data anonymization. The method includes: performing classification on data by a classifier to obtain data types of the data. The method further includes: performing anonymization on the data by a first anonymization model to obtain first anonymized data. The method further includes: determining, based on the data types, using an anonymizer whether re-anonymization needs to be performed on the first anonymized data. The method further includes: performing, based on a determination that the re-anonymization needs to be performed, the re-anonymization on the first anonymized data by a second anonymization model to obtain second anonymized data. Accordingly, anonymization processing may be performed on data using different anonymization models for different types of data to obtain the final anonymized data and to ensure that no data leakage occurs.

Abstract: Methods and systems for managing data processing systems are disclosed. A data processing system may include and depend on the operation of hardware and/or software components. To manage the operation of the data processing system, a data processing system manager may obtain logs for components of the data processing system. The logs may record actions (e.g., user actions) and other information that describes and reflects the historical and/or current operation of these components. Inference models may be implemented to predict likely future component failures (e.g., failure sequences) and their associated times-to-failures using information recorded in the logs. The failure sequences may be presented as an acyclic graph that associates component failures, their times-to-failure, and related actions. The probable failure sequences may be analyzed to identify sets of actions that optimize operational goals (e.g.

Abstract: Methods and systems for managing display of a website to a user are disclosed. Data processing systems operating the website may perform operator actions that increase the likelihood of achieving operational goals, such as presenting relevant content to the user to increase view time and/or user retention. To identify appropriate operator actions, logs (e.g., historical browsing data) may be obtained for various users of the website. The logs may record user actions, operator actions, and/or other information that describes historical and/or current user browsing activity. Inference models may be implemented to predict probable user actions, and associated user action information based on the log information. The predictions may be presented as an acyclic graph that associates the operator actions, user actions, and user action information. The graph may be analyzed to identify operator actions that may maximize user retention and/or increase the likelihood of meeting other operational goals.

Abstract: Methods and systems for managing data processing systems based on indications of a failure are disclosed. A data processing system may include and depend on the operation of hardware and/or software components. To manage the operation of the data processing system, a data processing system manager may obtain logs for components of the data processing system that reflect the historical and/or current operation of these components. Inference models may be implemented to predict future system infrastructure issues (e.g., future component failures) using information recorded in the logs. The inference models may also predict times-to-failures associated with the future failures by assigning attribution scores to portions of logs. Further analysis of attribution scores may be performed to generate health scores for the data processing system, providing additional information for the determination of remedial actions that may reduce the likelihood of the data processing system becoming impaired.

Abstract: Reference voltage circuits and methods for designing the same are provided. The reference voltage circuit includes: a reference core unit configured to output a reference voltage; a main amplification unit connected to the reference core unit and configured to form feedback to the reference core unit; and a feedforward amplification unit connected to the main amplification unit and configured to form feedforward to the main amplification unit. The reference core unit, the main amplification unit, and the feedforward amplification unit form a third-order negative feedback loop to improve a power supply rejection ratio of the reference voltage.

Abstract: Methods and systems for managing data processing systems are disclosed. A data processing system may include hardware and/or software components. The operation of the data processing system may depend on the operation of these components. To manage the operation of the data processing system, a system may include a data processing system manager. The data processing system manager may obtain logs for components of the data processing system reflecting the historical operation of these components and use the log to predict the future operation of the data processing system, identify similar operation of other data processing systems, and/or for other purposes. Based on the predictions, the data processing system manager may take action to reduce the likelihood of the data processing system becoming impaired.

Abstract: This disclosure provides systems, methods, and media for creating a data graph database from various unstructured and unstructured data items for use by various services. The method comprises the operations of identifying unstructured data items in data subjects; recognizing regions of interest (ROIs) in the unstructured data items; and extracting the ROIs from the unstructured data items. The method further comprises encoding the extracted ROIs into ROI vectors; creating a data graph to represent the data subjects, the data items, and the ROI vectors; and storing the data graph into a graph database. The various embodiments can manage data items of different data formats together rather than separately, thus creating a data management system for managing data across data formats. The data management system can also store structured data items into the graph database, thus complementing the existing ETL procedure for structured data items.

Abstract: The present disclosure provides a polysilicon resistor, a method for manufacturing the same, and a successive approximation register analog-to-digital converter.

Abstract: An efficient cut blasting method for medium-length holes in deep high-stress rock roadway is disclosed. The method may comprise steps of carrying out a crustal stress blasting test on the free face of the in-situ rock roadway to be excavated, and obtaining a distribution state of cracks under a synergistic action of crustal stress, explosion stress waves and clamping force of surrounding rock of a rock mass in the stratum where the in-situ rock roadway to be excavated is located; arranging a cutting hole net on the free face of the rock roadway to be excavated according to a distribution state of the cracks; performing cut blasting based on the cutting hole net.

Abstract: File annotation is described. An example method includes: processing files to be annotated by using an annotation model to determine a first performance of the annotation model, the first performance being associated with the confidence of a model annotation result generated by the annotation model; if the first performance is lower than a predetermined threshold, determining a group of target files from the files based at least on the confidence of the model annotation result; acquiring truth-value annotation information of the group of target files for retraining the annotation model; and if a second performance of the retrained annotation model is higher than or equal to the predetermined threshold, determining annotation information for at least some of the files by using the retrained annotation model. Based on this approach, automatic annotation of files can be realized with less truth-value annotation information, thereby reducing annotation costs.