Abstract: A method for performing operation optimization through virtual simulation, the method comprising generating, by a processor, human digital profiles associated with a plurality of persons; performing, by the processor, virtual simulation using the human digital profiles as input to a first model; generating, by the processor, performance prediction as output from the first model; and performing operation optimization based on the performance prediction.

Abstract: Disclosed is a method for establishing a 3D medical image segmentation model based on masked modeling and application thereof includes: establishing a semi-supervised learning network, wherein a student network includes an encoding module for extracting latent features and a segmentation decoder that predicts segmentation results, a teacher network includes an encoding module and a segmentation decoder that are structurally consistent with the student network; training the semi-supervised learning network, wherein during training, two random masking operations are performed on each image, and the image is input to the two networks respectively; optimizing and updating the weight of the student network, and transferring the updated weight to the teacher network, wherein the training loss function includes prototype representation loss, which is used to characterize the difference between the prototypes extracted and generated by the two networks; the student network may further include a reconstruction decoder

Abstract: Disclosed herein are methods of producing a hypoimmune cell and methods of mediating localized immune tolerance.

Abstract: Methods, systems, and computer-readable storage media for generating a detection prompt at least partially based on unstructured data determined from one or more of a query entity and a target entity, determining an unstructured data pattern vector that is representative of an output of a LLM that is responsive to the detection prompt, providing a data pattern metric based on the unstructured data pattern vector, generating an explanation prompt at least partially based on the inference result, determining a correctness result that is representative of a correctness of the inference result using explanation text that is generated by the LLM, in response to determining that there is a threshold decrease in accuracy at least partially based on the correctness result, automatically executing one of fine-tuning of the ML model and re-training of the ML model to provide an adapted ML model.

Abstract: An input/output (I/O) interface is described. The I/O interface includes an I/O terminal, a gate component, and an anti-electrostatic discharge apparatus. The gate component controls reading of data from the I/O terminal. The gate component includes a first switch component, where an input end of the first switch component is connected to the I/O terminal. The anti-electrostatic discharge apparatus is configured to increase a breakdown voltage at the first switch component.

Abstract: Provided is a yarn spindle packaging system, a control method thereof, an electronic device and a storage medium, relating to technical field of chemical fiber intellectualization.

Abstract: Methods, systems, and computer-readable storage media for training a global matching ML model using a set of enterprise data associated with a set of enterprises, receiving a subset of enterprise data associated with an enterprise that is absent from the set of enterprises, fine tuning the global matching ML model using the subset of enterprise data to provide a fine-tuned matching ML model. deploying the fine-tuned matching ML model for inference, receiving feedback to one or more inference results generated by the fine-tuned matching ML model, receiving synthetic data from a LLM system in response to at least a portion of the feedback, and fine tuning one or more of the global matching ML model and the fine-tuned ML model using the synthetic data.

Abstract: The present invention discloses an electrical connector, which is used to be electrically connected to a chip module. The electrical connector includes: a base; a plurality of terminals, provided in the base; a pickup cover, covered above the base, and abutting downward against the base; and at least one counterweight block, positioned in at least one of the base and the pickup cover. The counterweight block does not interfere with the terminals. The electrical connector in the present invention is provided with the counterweight blocks and utilizes the counterweight blocks to increase the weight for pressing the base, thus resolving the issue of the warping of the base due to heat and reducing the ill soldering of the terminals when the electrical connector is soldered to a circuit board.

Abstract: Embodiments are described for a code generating system comprising a memory and at least one processor coupled to the memory. The at least one processor is configured to receive an instruction to generate a source code and retrieve the code profile from a profile manager. The instruction include a user description and information of a code profile. The at least one processor is further configured to generate a first command by combining the user description and the code profile and transmit the first command to an artificial intelligence (AI) proxy. Finally, the at least one processor is configured to receive the source code from the AI proxy and transmit the source code to a user device.

Abstract: Methods, systems, and computer-readable storage media for receiving, by an entity matching ML model, a query and target pair including a query entity and a target entity, providing, by the entity matching ML model, a query-target prediction by processing the query entity and the target entity, the query-target prediction indicating a match type between the query entity and the target entity, generating a prompt by populating a prompt template with at least a portion of the query-target prediction, inputting the prompt into a large language model (LLM), and receiving, from the LLM, an explanation that is responsive to the prompt and that describes one or more reasons for the query-target prediction output by the entity matching ML model.

Abstract: Methods, systems, and computer-readable storage media for receiving a real data table, providing a synthetic structured table based on the real data table, providing a sampled data table comprising a sub-set of real data of the real data table, transmitting a prompt to a LLM system, the prompt being generated based on the real data table and the synthetic structured data table, receiving synthetic unstructured data from the LLM system, providing an aggregate synthetic table that includes at least a portion of the synthetic unstructured data, and training a ML model using the aggregate synthetic table.

Abstract: The present disclosure provides a coordinated multiple access method for multi-cell ground-to-air data transmission, and belongs to the technical field of wireless communication. The method comprises the following steps: S1, constructing a model of a coordinated multiple access system for multi-cell ground-to-air data transmission; S2, calculating a transmission rate of an aircraft, and constructing a multi-cell airspace and power domain resource allocation optimization problem by taking maximizing a system transmission rate as an optimization objective; S3, constructing a Markov decision process model; S4, solving the optimization problem using a multi-agent deep reinforcement learning algorithm. The system transmission rate is maximized under the condition that the aircraft can decode the signal correctly and satisfy the constraint of minimum transmission rate, thereby realizing ground-to-air high-speed data transmission.

Abstract: Methods, systems, and computer-readable storage media for providing, for a set of ML models, a set of training metrics determined using test data during a training phase, providing, for a production-use ML model, a set of inference metrics based on predictions generated by the production-use ML model, generating, by a prompt generator, a set of few-shot examples using the set of training metrics and the set of inference metrics, inputting, by the prompt generator, the set of few-shot examples to a LLM as prompts, transmitting, to the LLM a query, displaying, to a user, a recommendation that is received from the LLM and responsive to the query, receiving input from a user indicating a user-selected ML model responsive to the recommendation, and deploying a user-selected ML model to an inference runtime for production use.

Abstract: Disclosed is a label printer and a control method thereof. The label printer includes a paper cartridge configured to hold a label roll paper unit including a tube core and a continuous paper, wherein the tube core is provided with an RFID tag; an RFID reader configured to read information stored on the RFID tag; and a controller configured to detect whether the RFID reader reads the stored information of the RFID tag when the label roll paper unit is in an initial position, and if the RFID reader is unable to read the stored information of the RFID tag, the controller controls the label roll paper unit to rotate and drive the RFID tag to rotate, and controls the RFID reader to continuously read the RFID tag during rotating until the RFID reader is able to read the stored information.

Abstract: An optical-path calibration module is provided. The optical-path calibration module defines a first light inlet, a second light inlet, and a first light outlet, and a first light-splitting device is disposed in the optical-path calibration module. The first light inlet is configured to receive a calibration beam of a calibration light-source or be closed. The second light inlet is configured to receive a target-light-source beam or the calibration beam from the calibration light-source. The first light outlet is configured to emit a detection beam to a photoelectric sensor. An angle of 45° is defined between the first light-splitting device and each of the first light inlet and the second light inlet.

Abstract: A female connector includes a female body, first terminals provided at intervals in a lateral direction and second terminals provided at intervals in a longitudinal direction perpendicular to the lateral direction. The first and second terminals are fixed to the female body and intersect with each other to define multiple cavities, allowing heat dissipation. Each first terminal includes first elastic arms. Each second terminal includes second elastic arms. Each of the first and second elastic arms is provided with two arms and a connecting arm connecting them. Each of the two arms has a contact portion. For a first elastic arm and a second elastic arm facing a same cavity, the two contact portions of the first elastic arm are exposed to two adjacent cavities in the lateral direction, and the two contact portions of the second elastic arm are exposed to two adjacent cavities in the longitudinal direction.

Abstract: This application relates to a method and apparatus for processing a security service, and to a device, a storage medium, and a program product related to the technical field of network security. The method includes: receiving a Honeypot service deployment request transmitted by a first device of a network content provider, the Honeypot service deployment request being configured to indicate a probe service type and a Honeypot service type; establishing, based on the Honeypot service type, a Honeypot service in a cloud corresponding to target network content, the target network content being network content provided by the network content provider; and establishing, based on the probe service type, a probe service of the network content provider. In this disclosure, a Honeypot service of the network content provider may be automatically created in the cloud, thereby improves deployment efficiency of a Honeypot system.

Abstract: Methods, systems, and computer-readable storage media for receiving a query from a digital assistant of an enterprise system, retrieving data that is responsive to the query from a data management system, inputting a first few-shot prompt to a LLM, and determining, in response to the first few-shot prompt, that a graphical representation of the data is to be generated, and in response: inputting a second few-shot prompt and a third few-shot prompt to the LLM, receiving code from the LLM responsive to the third few-shot prompt, and executing the code to render the graphical representation with the digital assistant.

Abstract: Embodiments of this application provide a power control method, a communication apparatus, and a communication system. The method includes: determining whether a first condition is met, where the first condition includes that a time-frequency resource for sending a first beam and a time-frequency resource for sending a second beam overlap, a ratio of interference of the first beam to the second beam to noise floor of a receiver is greater than a first threshold, and a ratio of interference of the second beam to the first beam to the noise floor of the receiver is greater than the first threshold; and reducing transmit power of the first beam and transmit power of the second beam when the first condition is met.