25results about How to "Avoid submersion" patented technology

The invention provides a gas diffusion electrode device for electrochemical lithium-mediated ammonia synthesis and an electrochemical ammonia synthesis method, and belongs to the technical field of electrochemical ammonia synthesis. The gas diffusion electrode device comprises a nitrogen runner, a sealing gasket, a working electrode, a catholyte chamber, a diaphragm, an anolyte chamber, an anode catalyst, a hydrogen runner and an electrolyte, the electrolyte comprises a lithium salt, an organic solvent, a proton shuttling agent and an interface additive. According to the invention, high nitrogen transmission is realized by adopting a circulating type gas diffusion electrode device, and a three-phase interface chemical environment of gas, electrolyte and the gas diffusion electrode is regulated and controlled by an interface additive, so that the ammonia production rate and the Faraday efficiency are remarkably improved, and continuous and efficient nitrogen reduction reaction is realized at normal temperature and normal pressure.

The invention discloses a converter valve partial discharge voiceprint signal extraction method and system, and the method comprises the steps: collecting a mixed voiceprint signal of a converter valve, carrying out the noise reduction of the mixed voiceprint signal, obtaining a noise reduction voiceprint signal, extracting an initial partial discharge voiceprint signal from the noise reduction voiceprint signal, carrying out the sparse representation of the initial partial discharge voiceprint signal, and obtaining a sparse representation result. A single source point is identified according to a sparse representation result, a hybrid matrix is estimated based on the single source point, a hybrid voiceprint signal is reconstructed by using the hybrid matrix, a final partial discharge voiceprint signal is obtained, and noise reduction processing can effectively improve the quality of the voiceprint signal and ensure the accuracy of subsequent extraction. A series of processing such as initial partial discharge voiceprint signal extraction, sparse representation, single source point recognition and hybrid matrix estimation can effectively prevent partial discharge voiceprint signals from being submerged in noise signals, so that the partial discharge voiceprint signals are extracted quickly and accurately.

The invention belongs to the technical field of material ultrasonic detection, and relates to a composite board interface defect classification and identification method and system based on echo feature fusion, and the method comprises the steps: extracting ultrasonic echo multi-dimensional acoustic features; calculating a local acoustic feature aliasing degree; combining the acoustic impedance value, the local acoustic feature aliasing degree and the sample scarcity degree to generate a dynamic acoustic cost weight; reconstructing a random forest model, and constructing a cost-sensitive voting factor by using an information gain index and a cost weight; inputting the multi-dimensional acoustic features of the to-be-detected composite board, and executing weighted summation to obtain a classification result; according to the method, the feature aliasing degree can be evaluated more accurately, the sample scarcity and acoustic characteristics are comprehensively considered, the importance of high-risk defect features in decision making is ensured, the misjudgment problem is effectively solved, and the accuracy and reliability of composite board interface defect classification and recognition are improved.

This application discloses an electronic atomized product and a method for determining its nicotine content. The nicotine content in this electronic atomized product is no higher than 500 ng / g, simulating the action and visual experience of smoking, assisting users in adapting to the transition phase without nicotine dependence, and aiding in smoking cessation. The method for determining the nicotine content in the electronic atomized product includes: ultrasonic extraction of the sample using ultrapure water; liquid chromatography separation using an alkaline aqueous phase (pH 9.22–10.76) and acetonitrile as the mobile phase; positive ion ionization using an electrospray ionization source; and detection of nicotine characteristic ions using a single quadrupole mass spectrometer in selected ion monitoring mode, achieving highly sensitive, highly selective, low-cost, stable, and reliable quantitative analysis of nicotine content.

The application relates to the field of semiconductor technology and discloses a microwave reflection photoconductance measurement system for wafer film carrier lifetime, which comprises a reconfigurable differential metasurface probe, which interacts with a wafer film to be measured in a near-field coupling mode; an optical excitation module, which performs pulsed light irradiation on the wafer film below a measurement area to generate non-equilibrium carriers; a dual-channel microwave transceiving module, which feeds microwave signals to the measurement area and a reference area; a closed-loop feedback control module, which receives the differential signal as input before the optical excitation module works; and a data acquisition and processing module, which collects transient changes of the differential signal after the optical excitation module works. The closed-loop feedback control module actively adjusts the microwave response of the reconfigurable probe reference area, the differential signal baseline is locked to zero before measurement, common-mode noise is suppressed, and the signal-to-noise ratio of the transient decay curve and the measurement accuracy are improved.

The application discloses a ship radiation noise line spectrum estimation method based on multi-snapshot sparse Bayesian learning, and belongs to the field of underwater acoustic signal processing; the method utilizes the sparse characteristics of the ship radiation noise line spectrum, that is, the line spectrum is not uniformly distributed in the whole frequency range, but is discrete and sparse, converts the line spectrum estimation problem into a sparse signal recovery problem, so as to solve the problems in the background technology, under the condition that the data sample length is limited and the sparsity is unknown, the Bayesian framework utilizes probability modeling to adaptively adjust the hyperparameters from the global optimization angle, can effectively reduce the sidelobe, realizes high resolution, reduces the background noise fluctuation variance through multiple observation snapshots statistical average, enhances the signal-to-noise ratio of the line spectrum output, and improves the line spectrum feature detection performance.

The present disclosure relates to a method, an apparatus, a computer program product and a system for event identification and notification. The method includes identifying an event based on at least one of a video and audio temporally aligned with the video; allocating event levels for the events based on a preset grading mode; and determining a notification mode for the event based on the event level.

The application claims a micro-expression recognition method based on spatio-temporal feature representation learning, aiming to solve the problems of spatial detail loss, temporal feature ambiguity and small sample overfitting in micro-expression recognition, belonging to the technical field of computer vision and pattern recognition. The method comprises the following steps: step 1. The application proposes an upsampling and position perception module, which restores high-resolution features and performs orthogonal decomposition on them to accurately locate the coordinates of high-frequency action units, so as to alleviate the loss of spatial details. Step 2. The application designs a motion difference fusion module, which highlights weak motion changes through explicit time difference and adaptive gating mechanism, and prevents them from being covered by deep semantic features. Step 3. The application designs a two-stage adaptive prototype contrast learning strategy, which compresses the intra-class variance and expands the inter-class boundary through focal loss preheating and orthogonal prototype alignment based on memory bank, to cope with the problems of small sample and class imbalance.

The invention relates to a video prediction model based on operator learning. The video prediction model comprises a coding layer, an operator layer and a decoding layer, the coding layer receives an externally input video, the video is a series of continuous picture sequences, gridding labeling is carried out on the video, and time information and the originally input picture sequences are fused; carrying out downsampling processing on the fused picture sequence, and sending a processing result to an operator layer; the operator layer adopts a self-adaptive Fourier neural operator to carry out Fourier transform on a result processed by the coding layer, and extracts spatial-temporal characteristics; and the decoding layer obtains a predicted picture sequence according to the spatial-temporal characteristics provided by the operator layer. According to the method, the application requirement of space-time flexibility of the prediction task can be met under the conditions of data missing, low input data frame rate and the like, and meanwhile, the precision in the video prediction task is relatively high.

The utility model discloses a frequency conversion circuit, a frequency conversion signal transmit-receive module and a passive wireless pressure sensor, belonging to the technical field of wireless monitoring, the passive wireless pressure sensor comprises a frequency conversion signal transmit-receive module, a pressure sensing module and a power supply module, the frequency conversion signal transmit-receive module comprises a first antenna, a circulator and a frequency conversion circuit, and the frequency conversion circuit converts the downlink radio-frequency signal into a frequency-converted uplink radio-frequency signal and transmits the frequency-converted uplink radio-frequency signal back. The frequency conversion circuit provided by the utility model has the characteristic of different frequencies of uplink and downlink radio frequency signals, avoids self-interference, improves the receiving sensitivity, expands the wireless communication distance, and improves the communication coverage capability of a reader.

The utility model relates to the technical field of fabricated buildings, in particular to an integral temporary steel bridge which comprises a base assembly arranged at the bottom of a riverbed, a supporting assembly connected with the two sides of the riverbed is arranged on the base assembly, and a bridge deck assembly is arranged on the supporting assembly. According to the integral temporary steel bridge, the clamping design of an original assembly type temporary steel bridge is changed, the bridge body is welded and connected in advance after the structure of the bridge body is simplified, the integrity of the temporary steel bridge is enhanced, and the requirement for large actual use load when the assembly type bridge is built on a temporary passing river channel is met; drainage holes are formed in the bridge floor in advance, the drainage effect of the bridge is improved, and the surface of the bridge body is prevented from being submerged by riverway water level rising; workers can arrange the guardrails on the bridge body according to actual needs, the bridge floor fixing steel is arranged, reinforced connection of the bridge floor is facilitated, the mounting vacancies are reserved in the bridge floor fixing steel to facilitate mounting of the guardrails in the later period, and the situation that the guardrails are welded in advance, and consequently the integral temporary steel bridge is inconvenient to transport is avoided.

The invention relates to an intelligent patrol method and system for a subway protection district, and the method comprises the steps: carrying out the preprocessing of a real-time image collected by an unmanned plane, carrying out the target detection of each frame of aerial photo in the preprocessed real-time image, and obtaining all target detection results; constructing an environment field corresponding to the moving target based on the bounding box of each moving target, performing environment feature extraction on the environment field, performing self feature extraction on each moving target, and combining the obtained self features with the target environment to generate final detection features; and matching the final detection features with known detection features in a database, carrying out duplicate removal on a target detection result according to a matching result, carrying out track prediction on the moving target, and generating alarm information according to an obtained track prediction result to give an alarm. Therefore, accurate duplicate removal and dynamic tracking of the moving target are realized, the accuracy and efficiency of patrol of the subway protection area are improved, and the safety of the subway protection area is improved.

The application provides a time sequence anomaly detection method based on block interpolation and gated window attention accumulation, and belongs to the field of unsupervised time sequence anomaly detection. The method comprises the following steps: step S1, feature dimension reduction and interpolation recovery; step S2, multi-level gated feature encoding; step S3, local topological correlation quantization; and step S4, joint optimization and product decision. The application overcomes the fragmentation of discrete space-time semantics, realizes lossless high-resolution point-by-point anomaly positioning, establishes a high-elasticity cross-layer memory fusion loop, breaks the deep network representation homogenization bottleneck, constructs an element-level pre-gated hard isolation mechanism, accurately eliminates the attention sinking caused by global disordered aggregation, and establishes a structured correlation anomaly measurement system, and completely breaks through the false alarm blind area caused by "over reconstruction".

This application relates to a method, apparatus, computer device, and storage medium for determining contextual hot words. The method includes: processing the speech to be recognized and candidate hot words in a candidate word list to determine the frame-level speech vector and the text semantic vector of each candidate hot word at each time step; performing temporal accumulation processing of boundary contributions on the frame-level speech vectors to determine an acoustic boundary sequence, wherein the acoustic boundaries in the acoustic boundary sequence are used to indicate the boundary positions of the frame-level speech vectors in the speech to be recognized; performing local alignment of the candidate hot words and the frame-level speech vectors on the acoustic boundary sequence according to the text lexical length of the candidate hot words to determine the acoustic vector group corresponding to the candidate hot words; and filtering each candidate hot word according to the text semantic vector of each candidate hot word and the frame-level speech vector of the acoustic vector group to obtain the contextual hot words of the speech to be recognized, thereby improving the accuracy of contextual hot word recognition.

The utility model discloses a rainwater collecting device for gardens, which comprises a pre-embedded part and a rainwater filtering structure, wherein the pre-embedded part comprises a pre-embedded shell, an overflow pipe fixedly installed on the front surface of the pre-embedded shell, and a water leakage cover plate clamped on the upper surface of the pre-embedded shell. The rainwater collecting device for gardens is characterized in that: firstly, the pre-embedded shell is pre-embedded by digging a foundation pit on one side of the garden close to a rainwater channel; then, a pull frame is clamped into the pre-embedded shell; when it rains, the rainwater in the garden will flow into the pull frame along the water leakage cover plate; then, the rainwater will sequentially pass through an intercepting assembly and a first filtering assembly to enter a pump body cavity; then, the water filtered in the pump body cavity is pumped into a water return cavity by a water pump; and the water is allowed to return to seep through a second filtering assembly from the bottom of a second filtering cavity, so that the water can be filtered again; and the filtered water can be stored in a clean water cavity, thus, the ground in the garden does not need to be excessively excavated, the objects in the garden are less damaged, and the rainwater collecting device has strong practicability.

The application discloses a super-deep buoyancy type large double-wall steel hanging box in severe sea conditions, which comprises A section wall body, B section buoyancy cabin and C section wall body which are rigidly connected in sequence from bottom to top, and watertight sealing structures are arranged between the sections. A construction method of the super-deep buoyancy type large double-wall steel hanging box in severe sea conditions comprises the following steps: S1, prefabrication and processing; S2, section assembly; S3, floating and positioning; S4, bed fixation; S5, tide adaptation debugging; S6, bottom sealing concrete construction; S7, buoyancy conversion; S8, completion detection. The application effectively resists the erosion of high-speed water flow in super-deep water area to the base; four groups of pressure sensors arranged at the bottom can monitor the base contact stress in real time, ensure that the steel hanging box is uniformly stressed after bed fixation, and significantly improve the anti-sliding and anti-inclination stability of the structure in severe sea conditions, and reduce the safety hidden danger caused by the base erosion.

The invention discloses a fire smoke detector and a smoke detection method, equipment and medium thereof, and relates to the technical field of fire smoke particle recognized.The method comprises the steps that scattering characteristics of scattering signals are simulated, the optimal scattering angle is found, and then the position of the fire smoke detector is adjusted according to the optimal scattering angle; the large-angle scattering signal intensity is prevented from being submerged by the small-angle scattering signal intensity; and obtaining the power value of each light emitting source, and comparing and judging the power ratio and a typical aerosol standard curve to distinguish burning particles from non-burning particles and balance the response sensitivity of black smoke and white smoke.

This application discloses a memory management method, related devices, and program products for a multi-agent interaction system, relating to the field of artificial intelligence technology. The method includes: responding to a user-initiated task command, calling a multi-agent ensemble to infer the task result, and feeding the task result back to the user; acquiring memory data generated by each agent in the multi-agent ensemble during the inference process; and storing the memory data of each agent hierarchically according to task memory level, dialogue memory level, and state memory level. A single task memory includes one or more rounds of dialogue memory related to a single task processed by the agent, and a single dialogue memory includes one or more state memories related to one round of dialogue by the agent. The state memory is used to record the state data of the model inference process called by the agent in one round of dialogue. This application provides more flexible memory data management, offering more flexible, accurate, and efficient context management and organization capabilities in human-machine and multi-agent collaboration processes.

The present application relates to the field of data acquisition, and relates to a power distribution system multi-data fusion acquisition method based on artificial intelligence. The present application acquires the values of high-frequency electrical parameters and low-frequency environmental parameters corresponding to each acquisition device in the power distribution system in real time, judges whether there is a transient mutation, if there is, obtains the trend consistency index with the adjacent acquisition device to judge whether the corresponding acquisition device is normal, if normal, prioritizes the abnormal parameters, and sequentially performs intelligent filtering processing on the tracking acquisition data of each abnormal parameter, when the fault characteristic signal is identified, the transient mutation value of each abnormal parameter is retained, otherwise, the corresponding transient mutation value is removed, the clock drift between each acquisition device is compensated using a unified time reference, the characteristic data stream referenced by high frequency and low frequency is generated respectively, and uploaded to the cloud analysis platform and mapped to each device node, so that the data acquisition is more accurate and reliable, and provides support for accurate analysis.

The invention relates to a fuel cell system for product management. According to one embodiment, there may be provided a fuel cell system for product management, including: a first fuel tank storing a cathode fuel; a second fuel tank storing anode fuel; a fuel cell stack that receives cathode fuel and anode fuel as reaction gases from the first fuel tank and the second fuel tank and generates electric energy; a purge valve that discharges a product generated by a reaction between a cathode fuel and an anode fuel from the fuel cell stack to the outside; and a control unit that controls the opening and closing operation of the purge valve on the basis of the concentration or internal humidity of the reaction gas in the fuel cell stack.

A metal plate electric appliance cabinet base structure comprises a metal plate electric appliance cabinet and a base, the bottom of the metal plate electric appliance cabinet is connected with a bottom plate, the bottom plate is installed on the base, the periphery of the bottom plate is provided with a set of supporting rods, one end of each supporting rod is rotationally connected with the bottom of the bottom plate, the bottom of the base is bent outwards to form a supporting edge, and the supporting edge is connected with an adjusting base. An adjusting groove is machined in the adjusting seat, the other end of the supporting rod extends into the adjusting groove, a plurality of adjusting holes are evenly distributed in the side face of the adjusting groove, and fixing pins are inserted into the adjusting holes to clamp the supporting rod so that the supporting rod can support the metal plate electric appliance cabinet on the bottom plate. Compared with the prior art, the base structure of the metal plate electric appliance cabinet has the advantages that the electric appliance cabinet and the base can be separated and lifted through the supporting rod structure, and the bottom of the electric appliance cabinet is prevented from being submerged.

The application discloses a traditional Chinese medicine formula effective component analysis system and method, and belongs to the technical field of traditional Chinese medicine analysis. The system comprises a data acquisition interface, a characteristic bin sampling module and an effective component content calculation module. The data acquisition interface acquires a mass spectrum response signal of a traditional Chinese medicine extract and converts the mass spectrum response signal into a digital chromatography-mass spectrum data matrix comprising a plurality of component detection points. The characteristic bin sampling module divides the plurality of component detection points into a plurality of characteristic bins based on chromatography retention time values and mass spectrum mass-to-charge ratio values in the data matrix, assigns corresponding characteristic bin identifiers, and generates a plurality of representative detection points. The effective component content calculation module determines the content or relative peak area ratio of a target effective component. The application can dynamically adjust the characteristic bin granularity, support multi-detection channel parallel sampling, and realize multi-component synchronous identification and quantification in combination with deep learning, and is suitable for efficient and accurate component analysis of a traditional Chinese medicine complex system.

The application discloses a supply chain inventory pledge dynamic risk control method and system based on multi-source data fusion, relates to the technical field of supply chain financial risk control, and comprises the following steps: separating a contract residual error tensor into a contract cooperative offset component, generating a local abnormality matrix, calculating a local abnormality amplitude and a continuous abnormality proportion, constructing a dynamic residual error state vector based on the product of the two, and generating a dynamic comprehensive risk value; the application extracts the contract cooperative offset component, generates a local abnormality matrix for the residual error after deducting the contract cooperative offset component, and constructs a dynamic residual error state vector in combination with the local abnormality amplitude and the continuous abnormality proportion, so that the dynamic comprehensive risk value reflects an abnormal state that deviates from the common change of the contract layer and continuously exists in time, avoids misidentifying contract layer synchronous fluctuations as batch local abnormalities, and also avoids submerging batch local continuous abnormalities in contract overall fluctuations, thereby improving the hierarchy, accuracy and interpretability of the risk identification result.

The invention discloses an image classification model training method and device, an image classification method and device, equipment and a medium. The method comprises the steps that an original image is acquired, an image description text corresponding to the original image, N attribute description texts and corresponding saliency areas are determined, and N is larger than 2; performing mask processing on each saliency region, and determining N region mask images; feature coding fusion is carried out on the original image, the N area mask images, the image description text and the N attribute description texts, and fusion coding features are determined; and performing model training based on the fused coding features, and determining a target classification model. According to the method, cross-modal feature code fusion is carried out on the whole image and a saliency region to obtain a fusion feature code capable of accurately representing the image, accurate training of a model is realized through the fusion feature code, and a target classification model with relatively high image category recognition accuracy is obtained. Therefore, image classification with high precision can be carried out according to the target classification model.

This invention relates to the field of wireless communication and signal processing technology, specifically to a shortwave spectrum high-efficiency sampling method and system based on compressed sensing. The method includes: acquiring power spectral density data across the entire frequency band using a low-speed scanning receiver; determining a set of strong interference frequency points; generating a binary null observation sequence; loading the binary null observation sequence onto an analog front-end mixer circuit to perform analog domain orthogonal mixing and integration processing on the input RF signal, outputting voltage sample values; calculating signal sparsity coefficients using a compressed sensing reconstruction algorithm; calculating the reconstruction residual based on the voltage sample values ​​and the signal sparsity coefficients; triggering a re-acquisition process of power spectral density data in response to the reconstruction residual exceeding a preset error threshold; and outputting the signal sparsity coefficients in response to the reconstruction residual being less than or equal to the preset error threshold. This invention solves the problems of limited dynamic range and weak signal overload, significantly improving the receiving sensitivity of weak signals under strong interference environments.