Abstract: A method for processing a network delay or a jitter, includes receiving, by a first network function, at least one of a first delay and a first jitter sent by an application function (AF), in which the first delay is a delay of an application, and the first jitter is a jitter of the application.

Abstract: Embodiments may send input including a standardized attribute and an associated attribute value to a task-agnostic generative large language model (LLM). Embodiments may receive, from the task-agnostic generative LLM, a natural language description of the standardized attribute and associated attribute value. Embodiments may send the natural language description of the standardized attribute and associated attribute value to at least one embedding generator. Embodiments may receive, from the at least one embedding generator, at least one embedding of the natural language description.

Abstract: A personalized federated learning method for industrial Internet of Things targeting client needs is provided. The method includes: issuing, by a server, an initial model to each client as a local model, the local model including a shared layer and a personalized layer; for each client, freezing parameters of the personalized layer and locally training the shared layer based on local industrial data of the client using an orthogonality constraint loss; uploading the trained parameter of the shared layer of each client to the server for averaging and aggregation; sending the aggregated parameter to each client; updating the parameter of the shared layer of each client based on the aggregated parameter; repeating the training and parameter updating process of the shared layer until a count of iterations equals to a count of policy switching communications; training the shared layer and the personalized layer to obtain a trained local model of the client.

Abstract: A communication method and apparatus, and a network function are provided. The method includes: receiving, by a user plane function (UPF), a first message sent by a first network function, in which the first message is configured to request an update or termination of a subscription to a UPF event exposure service, the UPF event exposure service is a service that the UPF exposes information to the first network function; autonomously determining, by the UPF, to update or terminate the UPF event exposure service subscribed by the first network function; and sending, by the UPF, a second message to the first network function.

Abstract: Disclosed are an intelligent vibration isolator and a control method thereof.

Abstract: Embodiments may send input including a standardized attribute and an associated attribute value to a task-agnostic generative large language model (LLM). Embodiments may receive, from the task-agnostic generative LLM, a natural language description of the standardized attribute and associated attribute value. Embodiments may send the natural language description of the standardized attribute and associated attribute value to at least one embedding generator. Embodiments may receive, from the at least one embedding generator, at least one embedding of the natural language description.

Abstract: The present invention relates to a stable pharmaceutical composition of a receptor agonist, a preparation method therefor and the use thereof. In particular, the present invention discloses a pharmaceutical composition having a dual-receptor agonist as an active ingredient. The pharmaceutical composition comprises a dual-receptor agonist buffer solution, an osmotic pressure regulator and a pH regulator. The pharmaceutical composition of the present invention has good drug stability and safety, and the preparation method is simple and convenient, and suitable for industrial production.

Abstract: An information processing method and device, a device, and a readable storage medium are provided. The method includes: receiving first information sent by a base station and sending second information to the base station, or directly sending second information to a base station; wherein the first information includes at least one of following: network slice identification information, network slice selection assistance information, single network slice selection assistance information, broadcast indication or information of supporting a network slice group by the base station; the second information includes at least one of following: network slice identification information, network slice selection assistance information, single network slice selection assistance information, network slice group information, a network slice group identifier.

Abstract: An electric hammer includes a housing, an electric motor, an output assembly, an impact assembly, a mounting shaft, a clutch assembly, and a switching assembly. The mounting shaft is rotatable about a second axis. When the electric hammer is in the drill mode, a sleeve of the output assembly rotates. When the electric hammer is in the hammer drill mode, the sleeve rotates and an impact block of the impact assembly reciprocates in the sleeve. The switching assembly is configured to switch the clutch assembly between a first state and a second state and includes a switching element. The switching element includes a forced end and a drive end, the output assembly moving along a first axis drives the forced end to move, and the drive end is configured to drive the clutch assembly to be switched to the first state.

Abstract: Disclosed is a prediction method for tool remaining life of a numerical control machine tool based on a hybrid neural model, including: constructing a hybrid neural network model, specifically including the following steps: constructing sample data according to the sampling frequency of tool data; obtaining a first feature vector representing the tool life by utilizing a convolutional neural network and a long short-term memory network; generating working condition signals of sampling points into a second feature vector representing the tool life by utilizing an NFM neural network; and inputting a current working time of a tool and the acquired feature vectors into a multi-layer perceptron for fusion to predict the tool life.

Abstract: Disclosed is a prediction method for tool remaining life of a numerical control machine tool based on a hybrid neural model, including: constructing a hybrid neural network model, specifically including the following steps: constructing sample data according to the sampling frequency of tool data; obtaining a first feature vector representing the tool life by utilizing a convolutional neural network and a long short-term memory network; generating working condition signals of sampling points into a second feature vector representing the tool life by utilizing an NFM neural network; and inputting a current working time of a tool and the acquired feature vectors into a multi-layer perceptron for fusion to predict the tool life.

Abstract: A large-field-of-view high-resolution imaging device includes an imaging array formed by splicing and combining a plurality of imaging units and a CSI phosphor screen. Each imaging unit is formed by coupling an array of light cones in series and an enhanced CCD. The series light cone array is formed by connecting a large light cone and a small light cone in series such that a small end face of the large light cone is connected with a large end face of the small light cone, a large end face of the large light cone is attached to the CSI phosphor screen, and a small end face of the small light cone serves as an input window of an image enhancer. The enhanced CCD is formed by coupling the image enhancer and a CCD camera. A photosensitive screen of the CCD camera serves as an output window of the image enhancer.

Abstract: One or more computing devices, systems, and/or methods are provided. Event information associated with a plurality of events may be identified. The plurality of events may be associated with first entities corresponding to a first entity type and second entities associated with a second entity type. A first network profile associated with the first entities and the second entities may be generated based upon the event information. An iterative process may be performed to identify a coalition network associated with fraudulent activity. The iterative process may include analyzing the first network profile to identify a first set of entities, of the first entities, that are related to an entity of the second entities, and/or analyzing the first network profile to identify a second set of entities, of the second entities, that are related to the first set of entities. Multiple iterations may be performed to identify the coalition network.

Abstract: An electric hammer includes a housing, an electric motor, an output assembly, an impact assembly, a mounting shaft, a clutch assembly, and a switching assembly. The mounting shaft is rotatable about a second axis. When the electric hammer is in the drill mode, a sleeve of the output assembly rotates. When the electric hammer is in the hammer drill mode, the sleeve rotates and an impact block of the impact assembly reciprocates in the sleeve. The switching assembly is configured to switch the clutch assembly between a first state and a second state and includes a switching element. The switching element includes a forced end and a drive end, the output assembly moving along a first axis drives the forced end to move, and the drive end is configured to drive the clutch assembly to be switched to the first state.

Abstract: One or more computing devices, systems, and/or methods are provided. Event information associated with a plurality of events may be identified. The plurality of events may be associated with first entities corresponding to a first entity type and second entities associated with a second entity type. A first network profile associated with the first entities and the second entities may be generated based upon the event information. An iterative process may be performed to identify a coalition network associated with fraudulent activity. The iterative process may include analyzing the first network profile to identify a first set of entities, of the first entities, that are related to an entity of the second entities, and/or analyzing the first network profile to identify a second set of entities, of the second entities, that are related to the first set of entities. Multiple iterations may be performed to identify the coalition network.

Abstract: Disclosed is a chip for detection of basic electric leakage on a residual current protector. Basic electric leakage can be understood as an electric leakage signal which is generated during normal operation of an electrical appliance and cannot cause a residual current protector to trip out. The chip for detection of basic electric leakage includes a peak detection circuit, a 20 ms clock generator, a 60 ms delay circuit, a 2.5 V reference voltage module, a register module, a comparator module, a counter, a digital subtractor, an analog-to-digital converter (ADC) module, a digital-to-analog converter (DAC) module, an analog adder/analog subtractor, a selection circuit, and a circuit for delayed resetting. The present disclosure can identify and eliminate a basic electric leakage signal from an input electric leakage signal, and will not affect normal operation of a load during detection, determination, storage, and output of the electric leakage signal.