45results about How to "Optimize output" patented technology

A shift register and a shift register unit for diminishing clock coupling effect are introduced herein. Each stage shift register unit includes at least one pull-up driving module, a pull-up module, at least one pull-down module and a pull-down driving module. Before a waveform of either a first clock signal or a second clock signal employed by the pull-up module transits into a rising edge, the pull-down driving module employs a first periodic signal to turn on the pull-down module in advance for a specific period, and/or before the waveform of the first or second clock signal employed by the pull-up module transits into a falling edge, the pull-down driving module employs a second periodic signal to turn off the pull-down module in advance for a specific period. Accordingly, the pull-down module can gain a sufficient capability against the clock coupling effect so as to optimize the waveform outputted from the shift register unit.

A system and method for predicting future disturbance in MPC applications by segregating a transient part and a steady state value associated with the disturbance. A dynamic state space model that includes a variable disturbance prediction module can be utilized for analyzing a dynamic behavior of a physical process associated with a process model. The process model represents a dynamic behavior of the physical process being controlled and the dynamic state space model represents current deviations from the process model and future deviations over a predetermined prediction horizon. A predicted trajectory can be calculated as a response to the initial conditions estimated by a Kalman Filter for the process model extended by a disturbance model. The output of the dynamic state space model utilized for the disturbance prediction can be further provided as an estimated input to a MPC.

The invention discloses a medical knowledge base construction method based on a question-and-answer system, and relates to a medical knowledge base. The medical knowledge base construction technology based on the question-answering system mainly includes data processing, data analysis and an expert question-and-answer platform. Firstly, entity and correlation relations are extracted from clinical data by a hierarchical partitioning method at a data processing stage. Secondly, extracted results are analyzed by an association rule algorithm, entity correlation is mined, the mined entity correlation is matched with a medical dictionary, and correctly matched results are directly stored into the knowledge base. Finally, questions are automatically generated from entity correlation which cannot be confirmed by crowd-sourcing technology, the questions are submitted to an expert question-and-answer platform for answering the questions, and final results are selected from answers of experts by a majority voting algorithm and stored into the medical knowledge base.

The invention relates to a convolutional neural network road scene classification and road segmentation method. A dual-task joint structure model based on the convolutional neural network is established.and composed of an encoder and two decoders. Feature information sharing is achieved through end-to-end training.Classification of various road scenes such as urban roads, rural roads and highwaysis completed, road drivable areas in the scenes are segmented, and the dual goals of road scene classification and road area segmentation are achieved. Based on a convolutional neural network, scene classification and road extraction in road scene perception are combined. Real-time output is obtained through an end-to-end training mode, the functions of an intelligent driving assistance system areimproved, and an effective and reliable driving assistance function is provided. A mode of combining a full convolutional network and a conditional random field is adopted for a part extracted from adrivable area in the model, a high-resolution image optimization output result can be generated, and a relatively accurate segmentation effect is achieved.

The invention discloses a question answering method and device, computer equipment and a storage medium. The question answering method comprises the steps: obtaining input information of a user; recognizing named entities in the input information, and linking the named entities to candidate entities, corresponding to the named entities, in the Chinese knowledge graph, to form entity pairs, whereinthe entity pairs comprise the named entities and the candidate entities; matching candidate relations of candidate entities in the Chinese knowledge graph through a relation model; according to the entity pairs and the candidate relations, forming candidate triples, wherein the candidate triples comprise named entities, candidate entities and candidate relations; obtaining a sorting result corresponding to each candidate triple based on the learning sorting model; and querying the Chinese knowledge graph according to a sorting result to obtain an answer to the input information. According tothe question answering method, external resources can be effectively utilized, and a large amount of context information can be provided through text mining, and based on the learning sorting model, good answers can be obtained when question and answer corpus data are few.

A liquid ejection control apparatus which controls a liquid ejection mechanism having a plurality of nozzle groups made up of a plurality of nozzles for ejecting liquid, comprising: a usage ratio determination unit which determines a usage ratio between the plurality of nozzle groups when performing liquid ejection; a correction data generation unit which generates correction data corresponding to the determined usage ratio, by using respective correction data for correcting density of liquid ejection results corresponding respectively to a plurality of usage ratios between the nozzle groups; an image data correction unit which corrects prescribed image data on the basis of the generated correction data; and an ejection execution control unit which executes liquid ejection by driving the respective nozzle groups on the basis of the corrected image data and the determined usage ratio.

The invention discloses a distributed public verifiable random number generation method. A random number is generated through the cooperation of a participant, and the ciphertext is made public in the process of generating the random number so as to be verified. Unpredictability requires that the random number is private before being issued, but the public verifiability requires to discloses the information for verification, one of the main contributions of the patent is to solve the contradiction between two characters. Furthermore, the second contribution of the patent is that the trusted third party can be eliminated in the verifiable random number generation process; on one hand, the method can prevent single participant from knowing the random number result in advance, the security of the protocol is improved; on the other hand, the method is conductive to solving sing point of failure problem, and the robustness of the protocol is improved.

The invention provides a suction type SF6 gas leakage monitoring device and method. The device comprises an air outlet (1), an air inlet (2), an infrared light supply (3), a window piece I (4), a window piece II (5), a reference spectral filter (6), a measuring spectral filter (7), a dual channel infrared detector (8), a temperature probe(9), a signal conditioning module (10), an A/D (Analog/Digital) conversion module (11), a data processing module (12), a light source driving module (13), a device body (14), an end cover I (15) and an end cover II (16). The invention provides the suction type SF6 gas leakage monitoring device and method have the advantages that the suction type SF6 gas leakage monitoring device has a digital output and thermal compensation function and is simple and reliable, and the sensitivity is high. The method and the device can carry out ration monitoring on SF6 leaking so as to externally output a high-precision SF6 leaking concentration value, and the method and the device have the advantages that the monitoring accuracy is high, the method and the device are stable and reliable, the structure is compact, the volume is small and exquisite and the like.

The invention discloses an audio detection method for road tunnel traffic events. Audio data collected in a road tunnel is divided into frames, second-level long-term and short-term memory network models are utilized to improve the identification rate and robustness, specifically, 1), the first long-term and short-term memory network model A is utilized to optimize extracted audio features, and the attention mechanism is further introduced to improve robustness of the features; and 2), the second long-term and short-term memory network model B is utilized to weight the optimized and refined features, the output result is further optimized, so road tunnel traffic event detection has high timeliness and accuracy, and the method has good application prospects.

The invention provides a solder paste printing performance influence factor analysis method based on SMT big data, and solves the problems of incomplete analysis and low precision in solder paste printing performance influence factor analysis. The method comprises the following implementation steps: collecting solder paste printing parameters and performance indexes to construct a solder paste printing data set; Processing the data by using a Mahalanobis distance and a null value; Calculating correlation coefficients among the features, and filtering redundant features; Dividing training and testing sample sets; Randomly extracting a part of features and constructing a random forest model; Setting a model termination condition; Estimating a characteristic importance degree score accordingto the model mean square error increment, and performing sorting; and determining a subset of key impact factors. According to the method, the key influence factors of the SMT solder paste printing performance are mined through random forest feature selection in combination with the big data processing technology, the correlation between the performance indexes and the printing parameters is determined, the solder paste printing performance is optimized, and the circuit board printing quality is improved. The method is used for process optimization and solder paste printing performance improvement in the surface mounting technology solder paste printing process.

The invention discloses a CO2 gas concentration monitoring device and method with the automatic temperature and air pressure compensation. The CO2 gas concentration can be accurately detected in a relatively wide temperature range and a relatively wide air pressure range, and the device and the method are applied to monitoring the CO2 gas concentration in a low-temperature low-pressure environment. The CO2 gas concentration is monitored by adopting a dual-wavelength infrared monitoring principle and a suction structure, and the device has the advantages of adaptation to a low-temperature low-pressure environment, high precision, high reliability and the like. The interference caused by factors such as light source instability is eliminated by adopting a dual-channel infrared detector, the absorption length of infrared light is increased by adopting a reflector, the environment suitability of the device is enhanced by adopting a heating element and a heat preservation material, the receiving light intensity is enhanced and the automatic temperature and air pressure compensation and correction is performed by adopting a conical optical collector, and the CO2 gas monitoring precision is effectively improved.

There are provided a display apparatus, a display system and a display method. The display apparatus includes: a first input unit through which a first image signal having a first type is inputted; an image processing unit which processes the first image signal for display; a converting unit which converts the type of the first image signal into a second type different from the first type; and an output unit which outputs the first image signal converted into the second type to a next connected display apparatus.

The invention discloses a mid-point potential balance control system for a T-type three-level inverter based on neuron PI adaptive control. A voltage outer loop employs a neuron PI adaptive controller, and a current inner loop employs a traditional PI controller. The input of the voltage outer loop at the direct current side is a deviation value of two capacitor voltages to take as input of the PIadaptive controller, output of the voltage outer loop through the neuron PI adaptive controller is taken as input of the current inner loop, the difference of the input of the current inner loop andthe output of the voltage outer loop is subjected to the neuron PI adaptive controller to compare with a triangular wave to obtain mid-point potential balance control system for the T-type three-levelinverter with a balance circuit of complementary two-path PWM signal control. The voltage outer loop employs adaptive controller based on the neuron PI parameters to perform regulation of the parameters of the controller on line in real time. Compared to a traditional PI controller, the adaptive ability is high, the response speed is fast, and the output result of the voltage outer loop controller is better.

The invention discloses a lung lobe segmentation optimization method and system based on lung segmentation, and relates to the field of medical images. The method comprises the steps that 1, a first output result of a first lung automatic segmentation algorithm model and a second output result of a second lung lobe automatic segmentation algorithm model are obtained, and the precision of the first lung automatic segmentation algorithm model is larger than that of the second lung lobe automatic segmentation algorithm model; the method also includes: step 2, carrying out point multiplication on the first output result and the second output result to obtain an independent mask of each lung lobe; step 3, respectively acquiring the maximum connected domain matrix of the independent mask of each lung lobe; step 4, performing superposition processing on each maximum connected domain matrix to obtain first optimization data; and step 5, performing calculation and elimination processing on the first optimization data to obtain a final optimization result. The invention can achieve the effect of improving the prediction precision.

The invention discloses an ultra-precision lathe motion control method based on fuzzy PID self-tuning calculation, and relates to the technical field of ultra-precision cutting processing. The methodmainly comprises the following steps: acquiring preset position information and actual position information of a linear motion guide rail of a lathe as a controlled object; and calculating a control output quantity by adopting a fuzzy PID control algorithm according to the deviation value between the preset position and the actual position and the change rate of the deviation value, and inputtingthe control output quantity into a control system to control the linear motion guide rail to move. A discourse domain parameter self-tuning method is adopted in fuzzy PID control and introduced into the fuzzy PID control, autonomous learning can be achieved, the static and dynamic performance of the ultra-precision lathe guide rail control system is improved, and then the purpose of improving theultra-precision cutting machining precision is achieved.

The invention discloses a multi-parameter uncertainty analysis method based on a value set visualization technology. The multi-parameter uncertainty analysis method comprises the following steps: 1, constructing a value set function in a complex form based on a known analytical expression; 2, quickly drawing a corresponding value set graph and a parameter action arrow by utilizing a value set function; 3, selecting key parameters, and drawing a discrete value set and a parameter action arrow; and 4, completing multi-parameter uncertainty problem analysis according to the coverage range and themoving trend of the value set and the action arrows of the parameters. When solving the problem of multiple uncertain parameters, the multi-parameter uncertainty analysis method based on a value setvisualization technology, on the basis of a value set mapping mathematical theory and in combination with a value set rapid drawing skill, provides a visual expression image to clearly present the effect of each parameter on an output result, and corresponding analysis results can rapidly and visually reveal different influences of multiple parameters on the output result, and then optimal parameter configuration is found, and the output result is improved.

A pulse signal processing circuit includes an input control circuit, an optocoupler circuit and an output circuit, which are sequentially connected, wherein the input control circuit comprises a firstswitch tube,a second switch tube and a first resistor, the output terminals of the first switch tube and the second switch tube are grounded through the first resistor, the control terminal of the first switch tube is used as an input terminal for accessing the input pulse signal, the control terminal of the second switch tube is connected with a reference voltage, and the on-off of the optical coupling circuit is controlled by the on-off of the second switch tube; The output circuit includes a second resistor, one end of the second resistor serves as an output end of the output circuit, andthe other end of the second resistor is connected to both the second power supply unit and the optical coupling circuit and is grounded through the optical coupling circuit. By setting the reference voltage, the noise in the input pulse signal can be suppressed, so that the output of the circuit is not affected by the noise, so that the stable and noise-free pulse signal can be output.