21results about How to "Easy diagnosis" patented technology

The application relates to the technical field of Internet of Things data processing, and discloses a local reasoning and abnormality detection method for a wireless sensor network, which comprises the following steps: constructing a hypergraph model according to a sensor node set in the sensor network and corresponding association relations, and defining an energy function; applying a sensitivity constraint to the potential function, so that the potential function satisfies a bounded difference condition; determining a constraint range of coupling strength and a truncation order m; performing local deterministic approximate reasoning to obtain a conditional edge probability of a target sensor node; calculating an abnormality score of the target sensor node, and performing abnormality detection. In the wireless sensor network, a hypergraph Gibbs model with a sensitivity constraint is constructed, and based on strong spatial mixing ensured by theory, the application realizes the probability reasoning of a deterministic error bound only by relying on a limited-step local communication, so that the explainable abnormality detection and positioning are completed on a resource-limited edge device.

This invention relates to solenoid valve fault diagnosis technology and discloses an automotive intelligent chassis electronic control system and its control circuit. The system includes a first fault diagnosis circuit and a second fault diagnosis circuit, each comprising a voltage acquisition unit, a voltage divider circuit, and a protection circuit. The protection circuit protects the fault diagnosis circuit, the voltage divider circuit divides the voltage output by the solenoid valve, and the voltage acquisition unit acquires the divided voltage. The voltage of the solenoid valve is acquired in real time using the voltage acquisition unit, and the state of the solenoid valve is determined based on the acquired voltage. This invention diagnoses faults in the solenoid valves of the automotive intelligent chassis electronic control system without requiring a driving solenoid valve. Each solenoid valve diagnosis requires only one port resource, making the diagnostic method simple and low-cost.

The application provides a plasma exosome mRNA biomarker and application thereof in construction of a gastric cancer diagnosis model, and relates to the technical field of biological medicine.The application first discovers that plasma exosome mRNA MORC3 is significantly enriched in plasma of gastric cancer patients, indicating that the plasma exosome mRNA MORC3 is expected to be used as a biomarker for gastric cancer diagnosis and as a target gene for treatment of gastric cancer.We take the plasma exosome mRNA MORC3 as a target marker to construct a diagnosis model and a corresponding diagnosis system for gastric cancer.The diagnosis model provided by the application shows high sensitivity and specificity in distinguishing gastric cancer patients from healthy people, displays good diagnosis efficiency, and can effectively identify gastric cancer patients, thereby providing an effective auxiliary tool for clinical diagnosis.The application provides a new choice for a molecular marker for gastric cancer diagnosis, overcomes the low sensitivity of existing cancer markers when used for gastric cancer diagnosis, and provides a new method for early screening and diagnosis of gastric cancer.

This invention discloses a method and apparatus for detecting and diagnosing energy storage devices based on multi-model fusion and AI collaboration. The method starts a portable host, drives the detection modules to perform self-tests, initializes the AI ​​processing module, and establishes a connection by scanning surrounding devices using the communication module. Voice commands control each detection module to collect multi-dimensional raw data. Each diagnostic model quantitatively calculates and outputs single-dimensional diagnostic results and confidence levels. A weighted fusion of these results using a self-built core fusion model yields a comprehensive diagnostic value, determining the fault level and type to generate a comprehensive diagnostic result. Protocols are parsed as needed to generate adaptation code, supplementing the collection of auxiliary data. The optimal operation and maintenance solution is selected based on the comprehensive diagnostic result using formula calculations, outputs the solution, and drives its execution. Data is simultaneously uploaded to the cloud. Finally, model parameters and weight coefficients are updated based on the device's operating data after fault handling, improving subsequent diagnostic accuracy. This invention solves the problems of difficult cross-manufacturer interface adaptation and inefficient operation in extreme environments found in existing technologies.

The present application relates to the technical field of magnetic resonance imaging, in particular to a magnetic resonance human liver electrical property imaging method, comprising the following steps: step S1, acquiring a magnetic resonance image; step S2, calculating fat content distribution; step S3, segmenting a human liver tissue image; step S4, establishing a function model of human liver fat content and electrical property; and step S5, calculating human liver electrical property distribution. The present application provides a magnetic resonance human liver electrical property imaging method, which obtains a high-accuracy liver electrical property distribution image through a reasonable fat content acquisition route and based on the relationship between fat content and electrical property, and is beneficial to clinical liver examination and diagnosis, and solves the problem of reduced imaging accuracy of the human liver in traditional electrical property technology due to the principle defect.

This application provides a configuration method and related apparatus. During the configuration of AOP and TrustZone, it is necessary to first query the configuration status of TrustZone. Upon confirming that TrustZone configuration is complete, it can also be confirmed that xPU is enabled. Then, when xPU is enabled, the configuration parameters of AOP are read through xPU to complete the AOP configuration. This application adjusts the timing during the configuration process, placing the step of reading the AOP configuration parameters through xPU after querying the TrustZone configuration status. This avoids system crashes caused by calling xPU when it is not enabled, improving the success rate of internal system environment configuration and enhancing user experience.

An electric sound stethoscope with double-channel compatible and collection switch relates to the field of medical auscultation, which is configured with double-channel compatible and convenient collection switch, analyzes and compares sound and sound wave pattern functions, and outputs two high-definition loudspeaker work of audio amplifier modules in two ways to connect two audio boxes, which is a new innovation for diagnosing heart and lung diseases. The excellent electric sound quality presents the extremely distinctive creative color of the system. The system includes electronic or traditional auscultation head to collect sound signals, and the sound signals are converted into electric sound signals by a microphone. The auscultation includes collecting heart and lung sound, and independently setting a microphone channel or a microphone wired socket interface with a convenient switch, forming the electric sound signal of the heart and lung auscultation collected by the convenient switch and the auscultation method to suppress howling. The electric sound signal enters the functional module circuit for processing through the appropriate transmission mode, amplifies the electric sound signal to drive the loudspeaker to broadcast and listen to the auscultation.

The application discloses a knowledge-based temporal convolution neural network (KB-TGCN) blast furnace fault diagnosis method. The method can solve the space-time dependence and sample imbalance problem of the blast furnace ironmaking process. First, the calculated variables that can further reflect the process state are calculated by using the variables directly detected by the sensor. Then, the knowledge-based graph structure is constructed according to the spatial position and calculation relationship of the variables. Subsequently, a one-dimensional time information extraction module is embedded in the graph convolutional neural network. Therefore, the TGCN can capture time information while maintaining the original spatial relationship. By using the knowledge-based graph structure, the KB-TGCN can fully mine the spatial information of different blast furnace positions. In addition, the method uses a focal loss function with an adaptive balance factor instead of a traditional cross-entropy loss function to overcome the sample imbalance problem.

This invention provides a magnetic resonance imaging (MRI) apparatus and its control method. In contrast-enhanced MRI, it improves the ability to depict tissues reached by the contrast agent and shortens the overall imaging time. The imaging unit of the MRI apparatus is equipped with a gradient echo pulse sequence for acquiring T1-emphasis images containing fat-suppressing pulses. The control unit performs the following control: the imaging unit repeats the pulse sequence for a given time from the time the contrast agent is administered to the subject, generating images of multiple phases at different arrival locations of the contrast agent. At this time, starting from the phase about to reach the target tissue, a preparatory pulse is added before the pulse sequence to suppress signals from the contrast agent present outside the target tissue (cells).

A method for segmenting and 3D visualization of chest CT images, belonging to the field of medical image processing and computer-aided diagnosis technology, comprises the following steps: S1, importing and standardizing preprocessing of medical image data; S2, segmenting of multiple tissue images of the thoracic cavity based on a hybrid strategy; S3, dual-mode 3D geometric reconstruction; and S4, interactive 3D visualization and rendering. Through these steps, this invention directly achieves accurate segmentation of multiple tissues and dual-mode 3D reconstruction of surfaces and volumes without relying on high-end hardware or complex manual operations, thus improving image analysis efficiency.

This application provides a circuit and system for voltage information diagnosis and self-calibration. By adding resistors R1 and R2 in series, the total cell voltage is divided, reducing the sampling point voltage Vsample to the measurement range of the analog-to-digital converter (ADC) of the microcontroller (MCU). The MCU accumulates and calculates the total voltage Vafe by sampling the voltages of each cell from the analog front-end (AFE). Based on the Vafe data from the AFE, the total cell voltage Vmcu is automatically calibrated to obtain the calibrated total cell voltage Vcalib. Simultaneously, the MCU compares the calibrated total cell voltage Vcalib with the Vafe voltage in real time to obtain the deviation value Vdiag. When the deviation value Vdiag exceeds a set threshold, fault diagnosis is triggered, indicating an abnormality in the cell voltage sampling function, and a safety protection mechanism is activated to meet functional safety requirements. This circuit, through reasonable hardware design, voltage protection, cell total voltage calibration, and fault diagnosis mechanism, not only improves the accuracy of system measurements but also achieves self-calibration and fault diagnosis, making it suitable for applications with high stability requirements.

The present application belongs to the field of biology and chemistry, and relates to a method for visual detection of porcine pseudorabies virus (PRV) by using a CRISPR / Cas12a system. ‑ / TK ‑ The present application discloses a crRNA for differentiating a CRISPR / Cas12a-based visual porcine pseudorabies wild strain and gE ‑ / TK ‑ gene deletion vaccine strain, and corresponding primers and probes. The differential diagnosis method of the present application comprises the following steps: step one, extraction of a virus genome; step two, amplification of the extracted virus genome by using a constant temperature amplification primer through a constant temperature amplification technology; and step three, use of the amplified product for Cas12a detection. The method of the present application is simple to operate and has superior sensitivity and specificity.

The application discloses a kind of general data exchange systems based on configurable label structure, it is related to the technical field of data processing and information integration, including parameter module for establishing the identity authentication mechanism of exchange party;Business document module is used to establish data structure definition based on preset exchange demand;Document logic module is used for logical analysis and code decoupling to data structure definition, generates tokenization language script code and execution instruction, constructs execution matrix, realizes the mapping of database physical field and memory logic variable;Standard adaptation module is used to compare and check the generated data content, and the verification result is fed back to the parameter module to correct the exchange rule and parameter configuration.The application implements more intelligent logic separation strategy through structured insight, cooperatively controls data reading, writing and transmission, and realizes complete decoupling of business logic and program code using nested label structure, optimizes the flexibility, universality and maintenance efficiency of data exchange.

The application provides a blood vessel information prediction method and device, equipment and a storage medium, and relates to the technical field of biomedicine. The method comprises the following steps: obtaining to-be-predicted data; inputting the to-be-predicted data into a prediction model to obtain blood vessel information of a target blood vessel; wherein the prediction model is obtained through the following steps: obtaining a training data set and a corresponding physical model, wherein the training data set comprises historical physiological signals and corresponding blood pressure waveform data or blood flow rate waveform data; determining a loss function of a to-be-trained neural network based on the physical model; and performing neural network training according to the loss function and the training data set to obtain the prediction model. The implementation of the application can predict blood vessel information by using physiological signals, improve the acquisition efficiency of blood pressure and blood flow rate related data, facilitate long-time acquisition of the data, and promote the promotion of cardiovascular disease diagnosis and prevention in daily life.

This invention discloses a time-series graph modeling method and apparatus that integrates multi-parameter data analysis. The method includes: acquiring multi-source information from a converter transformer, including operating condition data and multi-source sensor data; transforming the multi-source information into corresponding semantic feature vectors using a word vector model; performing linear transformations on each semantic feature vector and the concatenated feature vector obtained by splicing the semantic features to transform the multi-source information into a common feature space; processing the feature values ​​of each semantic feature vector after linear transformation using a knowledge graph technology based on the adaptive change of adjacency matrix weights with node features to obtain a knowledge graph corresponding to the multi-source information at different times; and processing the knowledge graph corresponding to the multi-source information at different times using a time-series graph attention neural network to analyze the changing patterns of the multi-source information.

The embodiment of the invention relates to an artificial neural network processing method and system for providing semiconductor device parameters. A method includes providing a set of measured characteristic curve values for a semiconductor device having a control node and a current flow path through between a first current node and a second current node, the values including a measured current value through the current flow path, the current value is a function of a voltage value across the first and second current nodes, a set of control voltage levels is applied at the control node, an artificial neural network processing pipeline is applied to the set of measured characteristic curve values to obtain a set of reconstructed physical parameter values for the semiconductor device, a reconstructed characteristic curve value of the semiconductor device is calculated based on the reconstructed physical parameter value and the set of device modeling equations, a comparison of the reconstructed characteristic curve value and the measured characteristic curve value is performed, and an indicator of a variation of the physical value of the semiconductor device is provided.

This invention proposes an adaptive feature clustering-based method for diagnosing coupled faults in industrial machinery under low-labeled sample conditions. It relates to the field of intelligent fault diagnosis for industrial equipment and addresses the technical problems of existing fault diagnosis methods, such as high dependence on labeled data, poor multi-source signal feature fusion, insufficient deep feature mining of coupled faults, and weak adaptability to complex operating conditions. First, heterogeneous kernel density adaptive normalization is performed on multi-sensor signals. Then, three-dimensional weighted primary and secondary features are adaptively mined to generate pre-trained weights. A diagnostic clustering model is constructed through iterative fusion of channel attention to complete fault identification. Finally, the model is optimized, and the source and evolution of the fault are quantified. This invention is suitable for low-labeled industrial scenarios, provides high accuracy in coupled fault diagnosis, exhibits strong robustness under conditions such as sample imbalance and limited channels, can quantify the source of faults, reveal evolution patterns, and provide accurate operation and maintenance suggestions. It also has good scalability and is easy to implement in engineering.

A kind of desktop expandable table, it includes first guide rail and second guide rail of symmetrical distribution front and back, the bottom of first guide rail and second guide rail is provided with several cross beams, the bottom of cross beam is equipped with support part;It also includes first tabletop and second tabletop of opposite installation, the bottom of first tabletop and second tabletop is equipped with first sliding frame and second sliding frame respectively, first sliding frame and second sliding frame are slidably installed in first guide rail and second guide rail in front and back two sides, so that first tabletop and second tabletop can be moved relative to first guide rail and second guide rail;It also includes lifting tabletop installed between first tabletop and second tabletop.The beneficial effects of the utility model are: the utility model discards the linkage mechanism of complex connecting rod, gear or cam etc. in prior art, and innovatively uses the direct sliding cooperation mode of guide column and 7-shaped guide groove to realize the lifting and support of lifting tabletop.

This invention relates to the application of urinary FLRT2 protein in the preparation of IgA nephropathy biomarkers, belonging to the field of materials science involving specific methods for the study or analysis of proteins, peptides, or amino acids. The application refers to the use of urinary FLRT2 protein as a biomarker in the preparation of predictive models for IgA nephropathy, in the preparation of online diagnostic systems for IgA nephropathy, and in the preparation of reagent kits for the detection of IgA nephropathy. This invention has the following advantages: 1. Achieves high-precision non-invasive diagnosis; 2. Overcomes the limitations of the "black box" and provides interpretable decision support; 3. Completes clinical translation and provides real-time online tools; 4. Verifies the unique added value of FLRT2 biomarkers; 5. Possesses strong generalization ability and robustness; 6. Provides a potentially efficient and low-cost screening pathway.

The present application relates to a kind of protein markers for diagnosing postmenopausal osteoporosis and its application, belong to biological medicine technical field.The present application is screened, and it is found that NADH dehydrogenase 1 beta subcomplex subunit 4, NADH dehydrogenase 1 beta subcomplex subunit 5, NADH dehydrogenase 1 beta subcomplex subunit 6, NADH dehydrogenase 1, NADH dehydrogenase 1 alpha subcomplex subunit 8, cytochrome c oxidase subunit 7C, cytochrome c oxidase subunit 5A and cytochrome c oxidase subunit 7A2 can be used alone or in combination in the diagnosis test of postmenopausal osteoporosis, to accurately evaluate the PMOP state of subject.Further, the combination of NDUB5 and NDUA8 two protein markers shows excellent diagnostic sensitivity and specificity, which is helpful for early diagnosis of PMOP, screening of high-risk population of fracture and precise prevention and treatment.

The application of the biomarker combination in the preparation of a drug for fulminant myocarditis belongs to the field of drugs. The application is characterized in that the biomarker combination comprises Siglec-5; the biomarker combination is further selected from the group consisting of sST2, PAI-1, Siglec-5, CD163, CD40, P-Cadherin, CD14, CTLA4. The application finds that the expression of the biomarker in the plasma of a patient with fulminant myocarditis is increased, and confirms the role of the biomarker as a drug target in relieving and / or improving fulminant myocarditis. The level of the biomarker can be controlled by a drug, the diagnosis and subsequent treatment of the disease can be more intensified, and the biomarker has great application value in clinical practice.