131 results about "Small data" patented technology

The invention relates to a dynamic adjust gyroscope life forecasting method based on gray model. By data collection of vibration effective value, random drift and environmental temperature parameter which are preprocessed using radial neural networks, influence of environmental temperature on vibration effective value and random drift is eliminated and random drift and effective value just related to time are obtained by subtracting drift constant value term, then trend term of vibration effective value and random drift are extracted by using wavelet transformation and gray model are built separately for their trend term. The smaller data in two values of life predicted of dynamic adjust gyroscope unless two predicted values exceeding performance parameter limitation when dynamic adjust gyroscope is considered losing effect. The invention uses performance parameter of life probative period of product to predict its life, showing discipline of performance parameter and life of dynamic adjust gyroscope. It is easy and convenient economical and reliable.

This application provides a data transmission method and a terminal device. The terminal device includes a primary subscriber identity module (SIM) card and a secondary SIM card. When the primary SIM card detects that a specified event is started, the terminal device obtains remaining duration corresponding to the secondary SIM card. The terminal device determines first preset duration corresponding to the specified event. When the remaining duration is less than the first preset duration, the terminal device sends preset signaling to a network device through small data transmission. According to this application, it may be determined, based on a currently started event, whether to transmit the preset signaling through small data transmission.

The present disclosure provides a vehicle-mounted cabin driving integrated image processing system and a vehicle. The system comprises a driving domain image signal input module, a cabin domain image signal input module, a driving domain image signal processing module, a cabin domain image signal processing module and a memory. The driving domain image signal input module is used for storing driving domain image signals to the memory. The cabin domain image signal input module is used for storing cabin domain image signals to the memory. The driving domain image signal processing module is used for reading driving domain image signals from the memory and processing to obtain driving domain images, and storing the driving domain images to the memory. The cabin domain image signal processing module is used for reading cabin domain image signals from the memory and processing to obtain cabin domain images, and storing the cabin domain images to the memory. The system occupies less space, has shorter data transmission delay, lower cost, avoids data transmission interference caused by too long lines, and data transmission errors caused by line faults.

The present application belongs to the technical field of AI. Disclosed are a method for determining a output result of a model and a related apparatus. The method comprises: acquiring first input information of a network model; if the first input information hits a first intermediate operation result in a key-value cache, performing dimension-increasing processing on the first intermediate operation result by means of the network model to obtain a first key-value pair; and, on the basis of the first key-value pair, determining a first output result by means of the network model, the first output result being an output result corresponding to the first input information. The data volume of the first intermediate operation result is less than the data volume of the first key-value pair, that is, the key-value cache in the present application has a smaller data volume and occupies less storage space. Using intermediate operation results with a smaller data volume can increase the data loading speed of key-value caches and reduce the occupation of video memory by data loading, thereby accelerating reasoning and enhancing the overall operation performance of devices.

A data transmission processing method and apparatus, and a device are provided. The method includes: obtaining configuration information for small data transmission, where the configuration information includes: a quantity N of uplink transmission resources, and N is greater than 1; and determining whether to trigger small data transmission based on the configuration information.

This application discloses a method and apparatus for intelligent driving data trajectory repair based on segmented point cloud registration, relating to the field of autonomous driving technology. The method includes the following steps: dividing the data segment to be repaired into multiple smaller data segments; registering each frame of point cloud data in a smaller data segment with the first frame of point cloud data in that smaller data segment to obtain a data segment repaired within the segment; and registering the point cloud data of adjacent data segments repaired within the segment on the time axis to obtain point cloud data repaired between segments. Through partial-to-global joint trajectory correction, data repair can be achieved without relying on additional hardware upgrades or external auxiliary data. This significantly improves global trajectory consistency and repair success rate, efficiently repairing trajectory deviations in existing data, avoiding data resource waste, and adapting to the repair needs of newly added data, thus greatly reducing data processing costs.

Fire alarm device (1) with at least one fire alarm arrangement (2), wherein the at least one fire alarm arrangement (2) comprises at least one fire detector (3) for detecting a fire and at least one processing unit, in particular at least one image processing unit (4), wherein the at least one fire detector (3) and the at least one processing unit, in particular the at least one image processing unit (4), provide data, with a communication device (5), wherein the at least one fire alarm arrangement (2) is connectable or connected to the communication device (5) for transmitting the provided data, wherein the at least one fire alarm assembly (2) and the communication device (5) each have at least one wired bus connection (7), wherein the at least one fire alarm assembly (2) and the communication device (5) can be connected to each other via a wired bus connection (8) by means of the at least one wired bus connection (7), wherein the at least one fire alarm arrangement (2) for transmitting the data additionally has at least one wireless connection port (9), wherein the communication device (5) comprises a further wireless connection port (9), wherein the wireless connection ports (9) of the at least one fire alarm arrangement (2) and the communication device (5) are connectable or connected to each other for the transmission of data via a wireless network unit (10), where the data with a small data size are allocated to the wired bus connection (8) for transmission at low data rates, wherein the data with a large data size is assigned to the wireless network unit (10) for transmission at high data rates, wherein the fire alarm device (1) comprises at least one repeater (11), wherein the wireless transmission of the data between the wireless connection terminals (9) of the communication device (5) and the at least one fire alarm arrangement (2) is carried out indirectly via the at least one repeater (11).

Methods and systems for ultrasound imaging are provided. In one example, a method includes receiving, with a wireless handheld probe assembly, ultrasound signals of a region of interest; generating, within the wireless handheld probe assembly, a plurality of received digital signals based on the received ultrasound signals; generating each of a larger data set and a smaller data set from the plurality of received digital signals; transmitting the smaller data set from the wireless handheld probe assembly to a hub via a lower bandwidth wireless connection; transmitting the larger data set from the wireless handheld probe assembly to the hub via a higher bandwidth wireless connection; generating, at the hub, a low resolution image from the smaller data set and a high resolution image from the larger data set; and transmitting the low resolution image from the hub to a first display and the high resolution image from the hub to an electronic device.

Embodiments herein relate to, for example, a method performed by UE (10) for handling communication in the wireless communications network 1. The UE initiates a random access procedure for small data transmissions; and monitors for a message using a Type4-PDCCH CSS, or a USS, wherein the Type4-PDCCH CSS and / or the USS uses a radio resource set separated or partly overlapping a legacy radio resource set for a legacy CSS.

A data transmission method, wherein when small data arrives, user equipment (UE) in a radio resource control inactive state RRC_INACTIVE can establish a communication with a base station without entering an RRC connected state, so as to perform small data transmission (SDT). An RNAU timer for controlling a periodic radio access network (RAN) based notification area update is set for the base station. For the SDT, an SDT timer for SDT small data transmission is set. A small data transmission data radio bearer (DRB) is configured for the user equipment. When an RRC resume procedure is triggered by arrival of data at the DRB, a high layer triggering small data transmission, or the like, the user equipment starts the SDT timer.

The present application relates to a kind of pneumonia detection model training method, specifically to a kind of hierarchical topology pneumonia detection model based on collaborative learning system and method.It overcomes the difficulty of existing pneumonia detection model training system, low efficiency and the problem that local detection node cannot achieve optimal detection performance.First, each node uses local pneumonia data to pre-train respective pneumonia detection model locally, then, center node is based on the feedback data of local model to build hierarchical topology collaborative learning system;After that, each cluster node and child node uses local pneumonia data to train respective pneumonia detection model locally;Finally, collaborative training is carried out, including intra-cluster collaborative training and inter-cluster collaborative training;Intra-cluster collaborative training includes cluster node aggregation training and child node random interactive training.The present application has small data transmission, storage and calculation pressure, and is easy to implement;At the same time, different client is provided with different model parameters, so that each hospital detection node achieves local detection performance maximization.

This application provides a data transmission method, apparatus, readable storage medium, and system. In this method, cell reselection is performed in the RRC inactive state. When the SDT process is triggered, uplink data, including SDT data and authentication parameters, is sent to a first network device in the currently camped cell on the first CG-SDT resource. The authentication parameters are used by the first network device for legitimacy authentication based on the root key. The first CG-SDT resource and authentication parameters are configured by a second network device. The first CG-SDT resource includes a set of resource blocks in the CG-SDT resource pool configured for the RNA, which includes both the first and second network devices. This allows the first network device to perform small-data processing of the SDT process without needing to obtain the terminal device's context information from the second network device, thereby enabling CG-SDT to support cell reselection.

Techniques are disclosed for providing an avatar personalized for a specific person based on known data from a relatively large population of individuals and a relatively small data sample of the specific person. Auto-encoder neural networks are used in a novel manner to capture latent-variable representations of facial models. Once such models are developed, a very limited data sample of a specific person may be used in combination with convolutional-neural-networks or statistical filters, and driven by audio / visual input during real-time operations, to generate a realistic avatar of the specific individual's face. In some embodiments, conditional variables may be encoded (e.g. gender, age, body-mass-index, ethnicity, emotional state). In other embodiments, different portions of a face may be modeled separately and combined at run-time (e.g., face, tongue and lips). Models in accordance with this disclosure may be used to generate resolution independent output.

A method for a user equipment (UE) to monitor a physical downlink control channel (PDCCH) is provided. When the method includes, receiving, from a base station (BS), a radio resource control (RRC) release message when the UE is in an RRC_CONNECTED state, wherein the RRC release message includes a small data transmission (SDT) configuration. After receiving the RRC release message, the method transitions the UE from the RRC_CONNECTED state to an RRC_INACTIVE state in response to the received RRC release message. Then, the method initiates an SDT procedure according to the SDT configuration. The method further determines whether a search space set associated with an SDT search space is received from the BS. The method monitors the PDCCH by monitoring the search space set when the search space set is received from the BS in the SDT procedure.

A user equipment (UE) and a method for small data transmission (SDT) are provided. The method includes initiating an SDT procedure while the UE is in a Radio Resource Control (RRC) Inactive (RRC_INACTIVE) state; initiating a random access (RA) procedure before the SDT procedure is terminated; and determining whether to include a Cell-Radio Network Temporary Identifier (C-RNTI) Medium Access Control (MAC) Control Element (CE) in an uplink (UL) message during the RA procedure based on at least one condition. The at least one condition includes whether the SDT procedure corresponds to a Configured Grant (CG)-SDT procedure. The UL message is a message 3 (Msg3) in a case that the RA procedure is a 4-step RA procedure. The UL message is a message A (MsgA) in a case that the RA procedure is a 2-step RA procedure.

Examples of implementation of this disclosure relate to computer-readable devices, methods, apparatus, and storage media for configuring small data transmission. In these examples, an idle mobility metric is determined. Based on this metric, one of the following procedures is selected: a small data transmission procedure or a connection establishment procedure. Subsequently, the selected data transmission procedure is initiated.

This specification provides a control method and apparatus for a cell mechanical property measurement and sorting system. Based on this method, the control module first controls a camera to acquire target images of the target cells in a matching manner according to the operating parameters of the first interdigital transducer, obtaining relatively good target images. Then, the control module performs a basic first processing on the target images, with relatively small data processing volume, to quickly obtain the first processing result. Based on the first processing result, the second interdigital transducer is controlled to perform corresponding cell sorting processing. Simultaneously, the target images are sent to a computer device via a PCIe interface, utilizing the computer device's data processing resources to perform a more refined second processing on the target images, with a relatively larger data processing volume, obtaining the second processing result. This effectively reduces system latency and efficiently and accurately controls the corresponding modules in the system to cooperate in completing the cell sorting process.

This paper relates to a generator set control method and device based on multi-timescale features. The higher-level scale provides guidance information to the lower-level scale; the weekly plan provides the unit start-up and shutdown status for the day-ahead plan, and the day-ahead plan provides the basic output points of the units for the intraday plan. At the weekly scale, the constraints of unit timing coupling can be ignored, and a dataset is generated by feeding back from the lower-level scale to the higher-level scale. This results in smaller data dimensionality and lower computational cost for data generation. Then, based on a neural network, the start-up and shutdown status of the units is predicted, and reliable start-up and shutdown statuses are selected and passed down, eliminating the need for feasibility remedial measures for start-up and shutdown statuses and reducing computational complexity. At the day-ahead and intraday scales, the start-up and shutdown statuses of the units determined by the higher-level time scale are used to identify more redundant constraints and accelerate the solution speed. This paper utilizes the features of different time scales to solve the unit combination problem, which can accelerate the solution speed while ensuring solution quality, and the solution speed is more stable.

A data transmission method performed by a terminal device includes: performing, in response to arrival of first data at the terminal device during a small data transmission (SDT) procedure, sending a first data arrival indication through uplink SDT, thereby causing the terminal device to enter a connected state; and sending, by the terminal device in the connected state, the first data; where the SDT procedure is a data transmission procedure of the terminal device in an inactive state, and the first data includes data not supporting transmission in the SDT procedure; the first data arrival indication is used for notifying a network device that the first data arrives at the terminal device, and the uplink SDT is uplink data transmission in the SDT procedure.

The application discloses an inline small data transmission method and system based on an NVMe command queue, and belongs to the field of electronic digital data processing. The application aims at the problem that the PRP / SGL mechanism in the existing NVMe protocol takes 4KB physical pages as the minimum transmission granularity, leading to bandwidth amplification and redundant direct memory access operation in the small data scene. The submission queue is expanded into a mixed transmission channel of commands and data. When the effective load is less than or equal to a preset threshold, the host side segments the data, constructs an NVMe command containing a combined command type code, and writes the command and the data segment as a continuous 64-byte entry into the submission queue in sequence. The solid state disk controller sequentially reads the submission queue, identifies the inline transmission mode according to the combined command type code, directly extracts the data segment or triggers the direct memory access engine to perform multi-source aggregation transmission. The application eliminates redundant direct memory access transactions, improves the high-speed peripheral component interconnect link bandwidth utilization, and reduces the small data transmission delay.

This invention relates to a time-delay integration direct time-of-flight (DToF) LiDAR sensor and its processing method. Based on an area-array scanning operation, it completes quantization and readout within each short transit time, thus increasing the frame rate. The sensor's readout circuit employs a successive TDC (Time-of-Flight Difference) approach to approximate the histogram peak value, significantly reducing the amount of data generated by quantization. This reduces both the area overhead of the internal storage circuitry and the amount of data read out. Simultaneously, the system uses a coarse-quantization followed by a fine-quantization method, improving the quantization accuracy of the histogram TDC at a lower clock frequency. Benefiting from coarse quantization generating only one sign bit per stage, the TDI-DToF-LiDAR sensor exhibits a smaller data volume, higher frame rate, and smaller storage circuitry area overhead compared to traditional DToF-LiDAR sensors. Furthermore, the coarse-quantization + fine-quantization approach allows for high quantization accuracy without requiring a high-frequency clock input.

Embodiments of the present application are directed to a method and apparatus for small data transmission. In an embodiment of the present application, the method includes: selecting a channel access priority class (CAPC) for small data transmission (SDT) based on a rule if the CAPC for SDT is not indicated by a base station; and performing SDT based on the CAPC for the SDT.

Provided in the present disclosure are a random access reporting method and a user equipment. The random access reporting method includes: initiating, by a user equipment (UE), a small data transmission (SDT) procedure; determining, by the UE, that the SDT procedure is completed or a random access (RA) procedure in the SDT procedure is completed; and storing, by the UE, SDT information in an RA report, wherein the SDT information includes at least one of the following information: first information, used to indicate whether the SDT procedure is successfully completed; and second information, used to indicate whether the RA procedure in the SDT procedure is successfully completed.

The application discloses a point cloud information processing method, device and equipment and a storage medium, and comprises the following steps: acquiring current point cloud frame data, wherein the current point cloud frame data comprises three-dimensional coordinate information of a plurality of point clouds; performing two-dimensional space mapping processing on the three-dimensional coordinate information of the plurality of point clouds to obtain a current depth image corresponding to the current point cloud frame data; comparing the current depth image with a previous depth image to obtain a frame difference image, wherein the previous depth image is a depth image corresponding to previous point cloud frame data adjacent to the current point cloud frame data; determining a target sending image from the current depth image and the frame difference image with smaller data quantity; and sending the target sending image to an image rendering module. The application can effectively reduce the data quantity of point cloud data, facilitate the storage and sending of point cloud data, and ensure real-time transmission of point cloud data.

The application discloses a small-data-driven observer, a multiphase motor predictive control system and method, and the multiphase motor predictive control system comprises a sampling module and a small-data-driven observer, the observer comprises a neural network module and a neural network weight adjustment rhythm module; the neural network module comprises a plurality of neurons, and the neural network module calculates a current k time point current error compensation prediction value through the weight of each neuron according to the feedback value of each phase current of the multiphase motor at the current k time point; the neural network weight adjustment rhythm module calculates an optimal weight adjustment increment of the neural network module at k+1 time point according to the output value and the observation state of the observer at k time point, updates the weight matrix of the neural network module at k time point based on the optimal weight adjustment increment, and obtains the neural network weight matrix at k+1 time point. The application independently updates the network weight matrix, and improves the stability and observation accuracy of the observer at different working points of the multiphase motor.