53results about How to "Fast and effective comprehensive detection" patented technology

The invention discloses a method and a system for detecting LDoS attack data flow in a cloud environment. The method comprises the steps of simulating various attacks with network simulation softwareand extracting corresponding network traffic; sampling and classifying the data packets that arrive and lose on the server; extracting the average number of packets, source IP growth rate, wavelet features and congestion participation in a given period of data stream from the sample; analyzing the eigenvalues and establishing the random forest classification model, testing the established random forest model with normal data stream and abnormal data stream, calculating the corresponding information entropy for each feature classification, adjusting the threshold value of eigenvalues accordingto the information entropy, so as to achieve the best classification effect; according to the stochastic forest classification model, designing and deploying the LDoS attack data flow detection systemon the cloud server to detect and process all kinds of LDoS attack data flow in real time. The invention has the advantages of low energy consumption, high detection rate and low false alarm rate, and has high practical value.

The invention discloses a terahertz security imaging system based on a vector network analyzer, which includes a signal generation and acquisition device, an analog front end, a scanning drive device, a signal and data processing device; the vector network analyzer is used as the signal generation and acquisition device, Through the analog front-end, the step frequency signal of the X-band is up-converted to the terahertz band to radiate to the space to be inspected, and then the target echo signal of the terahertz-band is down-converted to the X-band through the analog front-end for signal processing; the main control computer is used for signal processing. The scanning drive device, signal and data processing device are controlled, and the user can adjust the corresponding scanning parameters according to the actual situation to achieve optimal detection, which improves the efficiency of the security inspection system; Such substances have good penetrability, and can effectively detect hidden items in packages and human clothing, with high resolution and accuracy.

The embodiment of the invention discloses a Webshell detection method and device, a computer device, and a readable storage medium for quickly and effectively realizing the detection of Webshell. The method of the embodiment comprises a step of obtaining an access log which comprises Http request information initialized by a browser to a Web service system, data request information initialized by the Web service system to a database system based on the Http request information, data response information fed by the database system to the Web service system based on the data request information, and Http response information fed by the Web service system to the browser based on the data response information, a step of extracting the Http response information from the access log, a step of detecting whether the Http response information comprises sensitive information of the database system or not, and a step of determining a condition that the Http response information points at the Webshell.

The invention discloses a kit for identifying a new coronavirus by applying a mass spectrum system and a use method of the kit. The kit comprises the following components: a U9 buffer solution, a U1 buffer solution and a sodium acetate buffer solution. The using method of the kit comprises the following steps: S1, activating a metalloprotein chip target plate; S2, pretreating a serum sample; S3, extracting protein in the serum sample by using the metalloprotein chip target plate; and S4, acquiring and processing a spectrogram by using an MALDI-TOF mass spectrum system, and analyzing the read spectrogram by using software. Therefore, the kit is high in sensitivity, good in accuracy, simple and convenient to operate, short in consumed time and very suitable for clinical diagnosis.

The invention provides equipment and a method for detecting an object based on a multiscale comparison characteristic. The equipment for detecting the object comprises an input unit, a learning machine based on the multiscale comparison characteristic, a sorter loading unit and a detecting unit; the input unit is used for inputting a detected image; the learning machine is used for extracting the multiscale comparison characteristic of a training sample related with the object, and processing the extracted characteristic by using statistical learning; the sorter loading unit is used for constructing a sorter according to a statistical learning processed result of the learning machine based on the multiscale comparison characteristic; and the detecting unit is used for detecting the object of the detected image input by the input unit by using the sorter constructed by the sorter loading unit, wherein the multiscale comparison characteristic is used for instructing comparison relation relative to a specific image attribute among a plurality of relevant rectangular regions under different scales in the image.

The invention relates to a surface mounting device having an automatic material checking function. The surface mounting device is provided with a plurality of material grooves into which material trays can be arranged. Radio frequency (RF) identification readers are arranged corresponding to the positions of the material grooves and comparison modules are built in the RF identification readers. RF identification tags are provided for the material trays, the tags of the material trays are read by the RF identification readers, and the information about the material trays stored in the tags is output. The comparison modules judge whether the material trays that are arranged into the material grooves are ones of the corresponding material grooves according to the information about the material trays, and output error signals when judging that an error occurs. When in use, the surface mounting device detects whether the right material trays are arranged into the material grooves quickly, simultaneously can save the labor and time costs caused by element detection, and further improves the surface mounting efficiency.

The invention provides a method for generating a pump station unit fault diagnosis system. The method comprises the following steps: collecting fault data of the pump station unit; extracting featurevectors from the collected data information, and selecting an optimal feature vector from the extracted feature vectors; carrying out permutation and combination on the optimal feature vector and a machine learning model through a genetic algorithm, and selecting the optimal combination of the feature vector and the machine learning model; combining the optimal feature vector with a machine learning model to form a diagnosis model for testing; and diagnosing the fault of the pump station unit by using the successfully tested diagnosis model. According to the invention, a genetic algorithm in the field of computer science artificial intelligence is adopted for automatic permutation and combination, the optimal feature vector and machine learning model combination is selected, manual processing and selection are not needed, cost is low, the period is short, and the pump station unit diagnosis system formed through the generation method can rapidly and effectively detect faults of the pump station unit.

The invention discloses automatic screw thread detection equipment. The equipment comprises a work table provided with a platform, a detection device used for detecting the qualification degree of screw threads, a clamping device for clamping a product above the platform, as well as a positioning device for axially positioning the non-detection end of the product, wherein the detection device is provided with a screw thread detection gauge capable of being connected with the thread end of the product, a motor driving the screw thread detection gauge to rotate circumferentially, a translation cylinder driving the screw thread detection gauge to axially move, a clutch connected between the motor and the screw thread detection gauge and capable of realizing connection or separation according to torsion force, as well as a displacement detector capable of detecting the displacement of the screw thread detection gauge. The automatic screw thread detection equipment has the benefit as follows: the thread section can be rapidly, effectively and comprehensively detected.

The invention relates to artificial intelligence, and provides a network security detection method and device, computer equipment and a storage medium. The method comprises the steps of obtaining a training set of a target network; determining an attack vector confronting a preset source network on the training set; determining a disturbance vector corresponding to the attack vector; constructinga generative network; training the generation network; taking an output vector of an encoder in the trained generative network as an embedded vector, and calculating the attack vector of the target network in a space where the embedded vector is located to obtain a third attack vector; and inputting the attack vector of the target network into the target network so as to detect the target network.In addition, the invention also relates to a blockchain technology, and the attack vector of the target network can be stored in the blockchain node. According to the invention, the detection accuracy and the search efficiency in the attack technology based on the black box can be improved.

The invention provides a power source control device for an indoor illuminating lamp. The power source control device comprises an input rectifying module, a main control module and an output rectifying module. The input rectifying module and the output rectifying module are respectively connected with the main control module, and the input rectifying module is used for filtering and rectifying an input power source. The main control module is used for detecting and controlling the working state of a power source of the indoor illuminating lamp. The output rectifying module is used for filtering and rectifying an output power source and adjusting the voltage of the output power source, and the main control module is used for detecting the working environment temperature of the indoor illuminating lamp in real time through a temperature detecting unit. When the working environment temperature is higher than a preset temperature value, output current of the power source is reduced. When the working environment temperature is higher than the preset temperature value, derating control over the power source of the indoor illuminating lamp is automatically performed, meanwhile, the service life, safety performance and normal working of the indoor illuminating lamp are guaranteed, and the defect that the indoor illuminating lamp is burned out due to over temperature or flickers is avoided.

The invention discloses a full-automatic AOI particle indentation detection machine. The detection machine comprises a particle indentation detection unit which detects an LCM bound with an IC, and an independent IC corner-chipping edge-chipping detection camera (8) is arranged on the particle indentation detection unit in a matched mode; the particle indentation detection unit is used for conducting indentation detection on the LCM, an FPC detects a certain period of interval time in the process of IC detection, the IC corner-chipping edge-chipping detection camera (8) which is arranged on a blanking conveying arm (6) is moved to the portion above the LMC and takes a picture of the IC, an image is acquired and processed, and whether or not corner-chipping and edge-chipping exits in the IC which is bound on the LMC is judged. According to the full-automatic AOI particle indentation detection machine, when the particle indentation detection unit conducts indentation detection on the LMC, the detection of corner-chipping and edge-chipping of the IC which is bound on the LMC can be completed, compared with the manual sampling, the cost is lowered, the qualification rate is improved, the unnecessary cost waste is avoided, and the production benefit is improved.

The invention provides hybridoma cells capable of secreting substances resisting PEDV (porcine epidemic diarrhea virus) monoclonal antibodies, a monoclonal antibody and an application. The hybridoma cells are respectively named as 4A11 and 3H7, are preserved in the China Center for Type Culture Collection, in Wuhan University, Wuhan, China on 13 June 2018, with the preservation numbers being CCTCCNO:C2018123 and CCTCC NO:C2018122. The hybridoma cell strains 4A11 and 3H7 can secrete monoclonal antibodies resisting porcine epidemic diarrhea viruses at a high yield, and ascites indirect-ELISA titer can reach 10<-6>. The porcine epidemic diarrhea virus detection test paper is also established by using the monoclonal antibody as a core, so that the porcine epidemic diarrhea viruses can be highly-specifically, accurately and sensitively detected, the operation is simple and convenient, effective and rapid site fast detection can be realized, and material support and technical support are provided for detection, diagnosis and scientific guidance on prevention and control of the porcine epidemic diarrhea viruses in China.

The invention discloses primers and a method for detecting fusarium graminearum with high resistance to carbendazim. The base sequences of the primers are as follows: the base sequence of the forward primer is 5'-TTG CAA TTG CAA ATT TCA ACG TG-3'; the base sequence of the reverse primer is 5'-CGT TAT CGA TAC AGA AGG TAA-3', or 5'-CGT TAT CGA TAC AGA AGG TTA-3'. The invention provides two groups of primers, PCR augmentation is performed through any one of the primers so as to detect the fusarium graminearum which has high resistance to carbendazim, and the specificities of the primers are high; in addition, the method disclosed by the invention can quickly and accurately detect the fusarium graminearum with the high resistance to carbendazim, the whole process only costs about two hours, and the operation is fast and accurate.

The invention relates to a device for testing based on ATE and belongs to the technical field of computer power supply detection. The device comprises a rack, a machine table which is arranged at the top of the rack, a test connection sub-seat which is mounted at the top of the machine table, a test connection female seat which is mounted at the top of the machine table, and an integrated circuit automatic detection machine which is mounted at the top of the machine table, wherein a primary interface and a secondary interface are led out of the integrated circuit automatic detection machine, the primary interface is electrically connected with the test connection female seat, the secondary interface is electrically connected with the test connection sub-seat, and when the integrated circuit automatic detection machine is used for testing, the test connection female seat is matched with a computer power supply socket end, and the test connection sub-seat is matched with a computer power supply lead end. In order to improve detection efficiency of a computer power supply, the invention provides a device for testing based on ATE.

The invention discloses an intelligent extinguishment control system which comprises a power supply system, a system control unit, a signal receiving unit, a storage unit, a signal output unit, a fault diagnosis unit and a driving control unit. According to the invention, through the fault diagnosis unit additionally arranged in the system, the self fault diagnosis of circuits and unit modules can be realized, the system faults can be fast and effectively detected, located and isolated, the system reliability can be improved, the maintenance cost can be lowered, and the maintenance efficiency can be improved.

The invention belongs to the technical field of logistics, and discloses a visual and active interaction-based detection and correction method for a packing box segmentation error. Carrying out regionextraction based on a target detection model result; performing Suspected error segmentation detection based on a two-dimensional visual algorithm; performing Error segmentation judgment based on anactive interactive strategy; Correcting error segmentation and calculating a correct grabbing position; based on Two-dimensional vision-based algorithm, the possible problems of under-segmentation andover-segmentation of the prediction result of the target detection model are pre-judged; a gripper of the robot to perform trial gripping is guided on the target, the size and position change of thebox body are tracked, detecting whether the comparison result is matched with a prior segmentation result or not, if yes, continuing to complete gripping on the target, and if not, performing correction on error segmentation. The visual-based interactive strategy can effectively correct the packaging box which is wrongly segmented, the risk that the packaging box is broken down is avoided, and therobustness of the robot for accurately grabbing the packaging box is greatly improved.

The invention provides a gearbox fault detection method and system based on vibration signal distribution characteristic recognition, and particularly relates to the technical field of data mode recognition. The method comprises the steps of collecting vibration signals generated by a gearbox in real time in the automobile driving process, and establishing a data set to be tested; constructing a fault detection model based on the established to-be-detected data set and a preset sample data set reflecting the normal working state of the gearbox; fitting and analyzing the distribution structuresof the sample data set and the to-be-detected data set by taking the data distribution characteristics as measurement based on the constructed fault detection model, and performing fault detection onthe gearbox by identifying an abnormal data mode in the to-be-detected data set; and outputting a diagnosis result of the gearbox fault type based on the identification of the abnormal data mode distribution characteristics. Based on the scheme provided by the invention, the fault generated by the gearbox in the working state in real time can be rapidly detected, and the robustness is relativelyhigh in a complex working environment influenced by multiple vibration sources.

The present invention provides a method and application for monitoring mRNA Poly(A) tail length, and relates to the field of biotechnology. The method for monitoring mRNA Poly(A) tail length provided by the invention includes measuring ATP consumption in mRNA tailing reaction Quantity and / or PPi generation yields mRNA Poly(A) tailed length. This method is applicable to any type of mRNA, has wide applicability, and can effectively replace complex detection methods such as capillary electrophoresis used in the prior art to quickly and effectively detect the tail length of mRNA, making the detection simpler and more efficient. Moreover, the relationship between ATP consumption and mRNA tail length is used to monitor the mRNA Poly(A) tail length, and the result is more intuitive and accurate. At the same time, the detection of ATP consumption does not require expensive instruments, and the detection cost is low.

The invention provides an organism detection device and an organism detection method through which the shape of an organism and pressure generated by the organism can be quickly, effectively and simultaneously detected. The organism detection device comprises a support panel, a shape scanning module and a pressure detection module; the shape scanning module is configured to scan the organism located on the support plate to generate first detection information about the shape of the organism; the pressure detection module is arranged on the support panel and configured to measure the pressure on the support panel while the shape scanning module scans the organism to generate second detection information about the pressure of the first face of the organism, wherein the first face of the organism makes contact with the support panel.

The invention discloses a calixarene-rhodamine supramolecular co-assembly and its preparation method and application. Its molecular formula is C 112 h 103 o 51 N 2 S 12 , can be used as a fluorescent probe to detect Fe in aqueous solution 3+ and Pb 2+ . The supramolecular co-assembly of the invention can be used as a fluorescent detection reagent for iron ions and palladium ions in aqueous solution, and has the advantages of rapid and effective detection, good selectivity, high sensitivity, low detection cost and low requirements for equipment.

The invention discloses a cable parameter detection device and a cable parameter detection method, and relates to the technical field of cable detection; the device includes a support, an angle detection mechanism and an information processing mechanism; the angle detection mechanism includes an angle detection part, a detection rod and a follower The angle detection part has a fixed end and a detection end, the fixed end is fixedly connected to the support; the first end of the detection rod is connected to the support in rotation, and the first end of the detection rod is connected to the detection end; the follower is movably arranged on the The cable is connected to the second end of the detection rod and can move with the cable; the angle detection part is used to detect the angle between the detection rod and the horizontal direction in real time during the movement of the follower with the cable; the information processing mechanism and the angle detection mechanism The electric connection is used to determine the cable outlet angle of the cable according to the detection value of the angle detection part. The device can quickly detect the cable outlet angle to ensure the cable laying effect and the safety and stability of the cable itself, thereby prolonging the service life of the cable.

The invention discloses a full-automatic garbage classification treatment separation line and process. The separation line comprises a crusher, a water washing tank, a dryer, a smashing machine, a magnetic separator, a winnowing machine and a gasifier; the crusher is provided with two outlets, wherein one outlet is connected with the smashing machine and the magnetic separator in sequence, and the other outlet is connected with the water washing tank, the dryer, the winnowing machine and the gasifier in sequence; the magnetic separator is provided with two outlets, wherein one outlet can output coarse materials for producing fertilizers, and the other outlet can output fine materials for recovery; materials floating on the water surface in the water washing tank can be conveyed into the drying furnace, and the rest materials are filtered for fertilizer production; and the winnowing machine is provided with two outlets, wherein one outlet can output light materials for granulation, and the other outlet is connected with an inlet of the gasifier. The separation line has the beneficial effects of: capability of effectively recycling different components in garbage and reduction of energy consumption and pollution in the treatment process.

The invention discloses an anchor cable supporting force detection device and method. The detection device comprises a pressure gauge, a counter-force cover and an anchor cable tensioning machine tool. A to-be-tested anchor cable, an anchor cable tray and an anchor cable lock are surrounded and protected through the counter-force cover; the recoil force of an anchor cable drawing device acts on the counter-force cover, the situation that the detection result cannot truly reflect the actual supporting force of the anchor cable due to the influence of the recoil force is avoided, and the supporting force of the anchor cable can be rapidly and effectively detected while the normal drawing of the anchor cable is guaranteed; meanwhile, the pressure gauge is used for providing a judgment value for detecting the anchor cable supporting force; the tensioning of the anchor cable is stopped immediately when the numerical value of the pressure gauge changes, the anchoring structure of the to-be-detected anchor cable is not damaged to cause failure of the anchor cable while the supporting force is detected, the supporting force of the anchor cable can be detected quickly and effectively, and reliable data support is provided for the stable control of a roadway surrounding rock.

The invention discloses a calixarene-rhodamine supramolecular co-assembly as well as a preparation method and application thereof, the molecular formula of the calixarene-rhodamine supramolecular co-assembly is C112H103O51N2S12, and the calixarene-rhodamine supramolecular co-assembly can be used as a fluorescent probe for detecting Fe < 3 + > and Pb < 2 + > and the supramolecular co-assembly disclosed by the invention can be used as a fluorescence detection reagent for iron ions and palladium ions in an aqueous solution, and has the advantages of rapidness and effectiveness in detection, good selectivity, high sensitivity, low detection cost and low requirements on equipment.

The invention discloses a bearing detection method based on a convolutional neural network. The method includes the following steps: generating a one-dimensional vibration signal based on a convolutional neural network based on the vibration acceleration signal of the bearing, and converting the one-dimensional vibration signal according to the time sequence and ratio It is divided into training set, verification set and test set in turn, and the convolutional neural network visualization structure based on Grad-CAM is established, and the Grad-CAM graph corresponding to the input sample of the convolutional neural network is obtained through ReLU function activation. In the Grad-CAM Dimensions of the vibration signal sampled on the graph, different activation thresholds are set in the value range of Grad-CAM, and the coordinates corresponding to the activation area of ​​Grad-CAM are used as the index to mark the activation of the original signal after passing through the convolutional neural network, and the neural network is established. Connections between network regions and target categories.