32results about How to "Guaranteed randomness" patented technology

The invention provides a virtual resource acquisition method and device, equipment and a storage medium, and belongs to the technical field of human-computer interaction. According to the method, a virtual prop configured with a plurality of sub-props is provided, the sub-props are first-class sub-props or second-class sub-props, the first-class sub-props correspond to virtual resources, and the second-class sub-props are used for improving at least one of the risk level of failure of obtaining the virtual resources and the resource level of the virtual resources obtained by the first-class sub-props. When the virtual props are used, the first type of sub-props and the second type of sub-props are possibly selected, the virtual resources can be obtained by selecting the first type of sub-props, and the virtual resources fail to be obtained by selecting the second type of sub-props, and due to the uncertainty, the randomness of obtaining the virtual resources is ensured; moreover, the method has an opportunity to obtain the virtual resources of a high resource level while bearing the high risk of failure, thereby enhancing the interestingness and gaming performance, and facilitating the promotion of the interaction based on the virtual prop.

The invention discloses a multi-cloud data possession proving method, and relates to the field of cloud computing and data security. The method aims at solving the problems that in the multi-cloud storage environment, the data integrity verification efficiency is low, abnormity positioning is difficult, and damaged data is difficult to automatically repair. According to the method, a plurality of storage positions are intelligently distributed for data blocks through a dynamic weight model, and data fingerprints associated with multiple clouds are constructed; during verification, data block risk scores and random selection are fused to generate a challenge set, and each cloud service party calculates local response based on stored data blocks and fingerprints; the verifier aggregates all the responses, compares the responses with an expected value through a consistency verification function, and outputs a comprehensive verification result; if it is judged that the data are not completely held, an exception positioning and repairing mechanism is triggered. According to the method, efficient verification, accurate positioning and autonomous recovery of the integrity of the multi-cloud data are realized, and the reliability and security of cross-cloud storage of the data are remarkably improved.

The invention relates to the field of microbiological examination laboratory equipment, and discloses a drying and disinfecting device and method for a specimen glass slide for microbiological examination. The device comprises a machine shell, a motor and a controller, the detachable rotating shaft is in transmission connection with the driving motor; the support frame is detachably arranged on the detachable rotating shaft and forms a plurality of mounting surfaces; the glass slide mounting plate is detachably mounted on the mounting surface, and a plurality of glass slide mounting stations are arranged on the glass slide mounting plate; the drying module comprises a drying lamp; the disinfection module comprises an ultraviolet disinfection lamp; and the control module is electrically connected with the driving motor, the drying module and the disinfection module and is used for executing a drying program and a disinfection program. The problems that in an existing glass slide processing method, the drying capacity and uniformity are difficult to consider at the same time, the drying process is uncontrollable, and low efficiency and safety risks are caused by separation of the drying process and the disinfection process are effectively solved.

The invention discloses a power grid new energy station power generation method and system considering spatial correlation. The method comprises the following steps: calculating correlation coefficients of any two different new energy stations based on a power change sequence; calculating the distance between stations by using the correlation coefficient, and carrying out clustering based on the distance to form a plurality of station groups; and for each station group, constructing a correlation coefficient matrix, and generating a new new energy station power change sequence through Cholesky decomposition. According to the invention, through the improved correlation analysis method, correlation characteristics between new energy units are accurately quantified; an optimized clustering algorithm is utilized to classify highly-correlated units into one group, so that the spatial dimension of a sample is remarkably reduced; a random generation method based on an advanced statistical model is adopted to generate a new energy power sequence with real randomness and correlation, so that the randomness of new energy power output is kept, and a correlation structure between units is ensured.

This invention provides an automatic obstacle avoidance seismic acquisition source random optimization design method, which includes: Step 1: Determining the physical location points of the acquisition sources according to actual conditions; Step 2: Calculating the number of sources corresponding to obstacles based on actual surface conditions; Step 3: Selecting optimization operators and determining the length and number of random sampling groups; Step 4: Generating multiple random sampling matrices with the constraint of not placing sources at obstacle locations; Step 5: Selecting the data reconstruction transformation space and calculating the correlation coefficient of the random sampling matrices; Step 6: Finding the random sampling matrix with the smallest correlation coefficient, which is the location of the seismic source. This automatic obstacle avoidance seismic acquisition source random optimization design method fully considers surface obstacle conditions, reduces the number of sources, and ensures high-precision seismic data reconstruction, achieving the goal of cost reduction and efficiency improvement in oil and gas exploration.

The invention relates to the technical field of tail gas detection, in particular to a sulfonic acid processing sulfonation tail gas detection sampling device which is characterized in that a three-way valve is arranged on the upper side of a cyclone separator, a sampling mechanism is arranged on the upper side of the three-way valve, and a docking mechanism is arranged on the sampling mechanism; according to the invention, the sampling assembly in the sampling mechanism is matched with the docking mechanism, so that sulfonated tail gas needing to be circulated and discharged in advance in the sampling process can be collected and flows back to the conveying pipe communicated with the electrostatic demister, and a plurality of sampling points at different positions can be arranged in the same section of sulfonated tail gas flow; therefore, synchronous multi-point random sampling on the same section of sulfonated tail gas flow can be realized; according to the invention, the butt-joint assembly in the butt-joint mechanism is matched with the quick-mounting assembly in the sampling mechanism, so that the gas collecting bag can be quickly sealed and mounted to a point position needing to be sampled so as to sample sulfonated tail gas.

The invention is suitable for the technical field of plant disease detection, and particularly relates to a plant leaf disease detection method based on a convolutional neural network, and the method comprises the steps: obtaining a plant planting region map; constructing a training data set based on the disease and pest database, constructing a convolutional neural network, and obtaining a disease and pest recognition model; and constructing a virtual boundary in a plane coordinate system, performing variation processing, performing light virtual reflection, determining the position of a sampling point, collecting a to-be-detected image at the sampling point, performing pre-screening, obtaining a pre-screened image, replacing invalid pixels, sending the image to a pest recognition model for recognition, and generating a recognition result. According to the method, the light propagation process is simulated in the virtual boundary by constructing the virtual boundary, so that the flight path of the unmanned aerial vehicle is simulated, the sampling points are extracted from the flight path, the randomness of the sampling points is ensured, and the data transmission quantity is greatly reduced and the data transmission efficiency is improved by performing hierarchical screening and transmission on the images.

The invention relates to a feed additive sampling inspection system and a using method thereof, and belongs to the technical field of feed additive sampling inspection, the feed additive sampling inspection system comprises a scattering box body, a conveying box body, a sample collecting frame, a sample storage box and a sample bottle, and the scattering box body is fixedly communicated with a feed additive feeding valve and a communicating pipe. According to the feed additive sampling inspection device, the feed additive sampling inspection device is communicated with the discharge port of the feed additive production line, feed additives discharged from the discharge port can be dispersed, the discharged feed additives can be uniformly dispersed, so that the uniformity of sampling inspection samples is guaranteed, multiple groups of feed conveying channels are arranged, the feed additives in the multiple groups of feed conveying channels can be sampled in sequence, and the sampling inspection efficiency is improved. The sample collecting assembly is arranged, multiple sets of sampling inspection samples can be sequentially collected, workers can take out the multiple sets of sampling inspection samples for subsequent inspection, the randomness and uniformity of the samples can be guaranteed in the whole sampling inspection process, the whole outer wall environment of the sampling inspection mode does not make contact with produced feed additives, and better safety is achieved.

The invention belongs to the technical field of stirrers, and particularly relates to a concentric double-shaft stirrer which comprises a console, a moving frame and a stirring component, the moving frame is arranged at the top of the console, and the stirring component is arranged on the inner wall of the moving frame; the axis stirrer is provided with a hollow connecting shaft, a floating sliding disc, a deflection stirring plate and a compression sleeve. According to the device, mixed liquid in the containing cylinder is synchronously stirred through the axis stirrer in the middle and the stirring rotating arms on the two sides, and the axis stirrer in the middle can control the floating sliding disc to slide up and down under the driving action of the drainage net cover, so that the actual rotating point position of deflection stirring is changed; therefore, when actual stirring work is carried out, a one-way vortex is difficult to form at the central part of liquid, so that the problem that the liquid gathered at the axis part is easy to polymerize to cause insufficient stirring is avoided.

The utility model discloses a sampling box for food inspection and detection, which comprises a box body, a rotating rod is vertically arranged at the center in the box body, a plurality of rows of threaded blind holes are longitudinally formed in the side surface of the rotating rod, a first connecting rod is screwed in the upper end hole of each row of threaded blind holes, and a first jacket and a second jacket are mounted at the outer end of each first connecting rod; third connecting rods are connected into lower end holes of each row of threaded blind holes in a threaded mode, first bottom supports and second bottom supports are installed at the outer ends of the third connecting rods, a first arc-shaped groove and a second arc-shaped groove are formed in the upper surface of a box cover arranged at the upper end of the box body, and an output shaft of a gear motor installed in the center of the upper surface of the box cover is connected with a rotating rod. Compared with the prior art, the test tube box has the beneficial effects that test tubes are fixed in the first clamping sleeve and the first bottom support as well as the second clamping sleeve and the second bottom support, and then the rotating rod is driven by the speed reducing motor to be connected, so that a plurality of sample test tubes rotate in the box body, and then sampling detection is performed through the first arc-shaped groove and the second arc-shaped groove.

The invention relates to a special digital speckle preparation tool and method for measuring a deformation field of a ship model, and the tool comprises a housing, a first installation pedestal and a second installation pedestal which are vertically distributed at an interval in the housing, and a speckle preparation assembly, a primer preparation assembly, a pose sensing control assembly and a high-pressure gas supply assembly are installed in the housing. Power supply battery packs are arranged on the left and right sides of the rear part of the shell, a high-pressure air hose is connected to the tail part of the shell, and a top plate is arranged on the top surface of the shell; the speckle preparation work can be conveniently completed, the problems that existing speckle preparation tools and methods are low in preparation efficiency, poor in randomness of speckles, inconsistent in size, poor in applicability of large-scale complex structures, large in measurement noise and the like are effectively solved, and harmony and unification of speckle patterns between regular distribution and random characteristics are achieved. And the application of the DIC measurement technology in the field of high-precision deformation field measurement of the ship structure model is promoted.

The invention relates to a texture processing area segmentation method and device, computer equipment and a storage medium. The method comprises the following steps: binarizing a texture grey-scale image based on a multi-level grey-scale range to obtain a multi-level binary image; randomly selecting seed points from a connected domain in the binary image; segmenting the connected domain based on the seed points to obtain segmented regions; determining a first mapping region where the segmentation region is mapped to the surface of the three-dimensional object; determining a first pose of the three-dimensional object when the center of a seed triangular patch corresponding to the seed point in the first mapping area is vertically penetrated by a central ray in the laser processing range; if the first mapping area is matched with the laser processing range when the three-dimensional object is in the first pose, determining that the first mapping area is a texture processing area, and determining that the first pose is a corresponding processing pose; otherwise, the first mapping area is segmented into a texture machining area matched with the laser machining range, and the corresponding machining pose is determined. By adopting the method, the texture processing quality can be improved.

The invention discloses an encryption method and device for stable-control high-real-time 2M communication. The encryption method comprises the steps that a sending end and a receiving end of 2M communication construct the same random key generation module; the sending end generates timestamps according to the synchronous clock and sends the timestamps to the receiving end, and the two ends generate seed signals based on the timestamps to serve as the initial state of the key generation module; the sending end encrypts a message by using a key output by the key generation module, and the receiving end decrypts the message by using the output key; and in a key generation module state updating stage, the sending end randomly generates an updating sequence number and sends the updating sequence number to the receiving end in a hidden manner, and when the frame sequence of messages processed by the two ends reaches the updating sequence number, the state of the random seed signal updating module associated with the stability control service is synchronously updated. According to the invention, the FPGA is utilized to construct the key generation module to encrypt and decrypt the message, the time overhead is low, and the high real-time requirement of stable control 2M communication is met; and the module state is randomly updated, the periodicity of key generation is eliminated, and the encryption security is greatly enhanced.

The invention provides a battery charging and discharging data self-adaptive sampling method and system in the technical field of battery detection. The method comprises the following steps: step S1, setting a DOC interval threshold value d, an input length threshold value input size, a sampling initial electric quantity starsoc and a sampling cut-off electric quantity endsoc; s2, acquiring charge and discharge data with the length of L, and verifying the charge and discharge data based on the DOC interval threshold value d and an input length threshold value input size; s3, cutting the charging and discharging data based on the sampling initial electric quantity starsoc and the sampling cut-off electric quantity endsoc to obtain a plurality of pieces of first charging and discharging sub-data; s4, on the basis of the input length threshold value input size, each piece of first charging and discharging sub-data is verified; and S5, performing dynamic down-sampling on each first charging and discharging sub-data, and outputting a sampling result. The method has the advantages that the diversity of battery charging and discharging data sampling is greatly improved, and time sequence characteristics are reserved.

The invention provides a security authentication method of a medical internet of things system and related equipment, which can improve the security of data transmission between a reader-writer and tag equipment. The method comprises the following steps: sending target request information to label equipment, so that the label equipment returns a target response message; the target response message is sent to the server, so that the server searches the corresponding target label content and returns the target label content; generating first challenge information according to the character string and the target label content; the first challenge information is sent to the tag equipment, so that the tag equipment verifies the identity of the reader-writer according to the first challenge information, and second challenge information is generated and returned according to the first challenge information when the verification is passed; verifying whether the tag device is legal according to the second challenge information; and if the local challenge information is legal, generating update challenge information and sending the update challenge information to the tag equipment, so that the tag equipment is matched with the local challenge information, and determining that the reader-writer and the tag equipment pass authentication when the tag equipment is matched with the local challenge information.

The application provides a smart city-based Internet of Things device encryption transmission method and system, which comprises the following steps: obtaining the unique serial code of the Internet of Things device; performing multiplication with the Internet of Things device serial code, the IP address of the server, the current timestamp and the function related to UUID to generate two prime numbers with a product greater than 1024 bits, and one of the two prime numbers is greater than or equal to twice the other prime number; generating the RSA public key pair and private key pair corresponding to the Internet of Things device according to the obtained two prime numbers and giving the Internet of Things device a unique device ID; when data is transmitted, the Internet of Things device adopts the RSA public key pair to encrypt the plaintext to obtain a first-level ciphertext, and then performs symmetric encryption based on the device ID and the serial code to form a two-section encryption ciphertext; the platform verifies the device ID, performs symmetric decryption on the ciphertext based on the device ID and the serial code to obtain a first-level ciphertext, and adopts the RSA private key pair to decrypt the first-level ciphertext again to obtain the plaintext.

This invention provides a high-precision modeling method for porous metallic materials based on a stochastic algorithm and its application in simulating the electrothermal-mechanical properties of materials. It relates to the field of artificial intelligence algorithm technology. The method includes: reconstructing and optimizing an initial reconstruction model of the porous metallic material based on a stochastic algorithm to obtain a three-dimensional reconstruction model; performing slice analysis on the three-dimensional reconstruction model and determining whether the analysis results meet the accuracy error standard; if they do, outputting the three-dimensional reconstruction model. By reconstructing and optimizing the initial model, the three-dimensional structure of porous materials can be accurately simulated, achieving high-precision modeling of porous metallic materials. Generating and growing pore seeds using a stochastic algorithm ensures the randomness and realism of the model. The setting of the accuracy error standard further improves the reliability of the model, ensuring the accuracy of porosity and pore size. This effectively solves the error problem in the modeling process of porous metallic materials, providing a solid foundation for high-precision simulation and material performance prediction.

The invention relates to a training partner ping-pong robot system for human health and an execution method, and belongs to the technical field of human health and artificial intelligence crossing. The method comprises the following steps: 1, generating a random seed value at the current moment; 2, respectively setting a preset position and a transmitting angle; 3, simultaneously opening a transmitting tube valve and a visual module; 4, a booster arranged in the launching tube is triggered to push out the table tennis balls; 5, ball hitting waiting time is calculated to serve as the interval time between ball serving of the launching module and ball hitting of the mechanical arm; 6, obtaining a target site; 7, calculating to obtain the hitting force; 8, moving the mechanical arm to the target site to hit the ball; 9, repeatedly executing the step 4 to the step 8 to obtain a single-round hitting force set; 10, circularly executing the step 9 to obtain a multi-round ball hitting force mean value; the ball hitting force mean value is used for adjusting the ball hitting force of next training in real time; the technical problems of enabling the robot to simulate circular ball hitting and adjusting the ball hitting force in real time are solved.

The invention discloses a novel adeno-associated virus variant library for gene and cell therapy as well as construction and application of the novel adeno-associated virus variant library, and belongs to the field of biological medicines. Through high-throughput sequencing and gene editing, an AAV variant library containing a large number of mutants is constructed, the construction efficiency is improved, the diversity of the mutants is ensured, the cap gene of AAV is modified by the variant library through a site-directed mutagenesis technology, the transduction efficiency of human immune cells is improved, the limitation of an existing AAV modification method is overcome, and the AAV mutant library has good application prospects. The constructed novel AAV variant library has higher packaging efficiency, lower cytotoxicity and better adaptability, and provides more choices for development of gene therapy drugs; the screened novel AAV6 variant P482L has remarkable advantages in the aspects of transduction efficiency, safety and the like, and becomes a potential candidate vector in the field of gene therapy; the invention not only accelerates the progress of new drug research and development, but also provides a new tool and method for treating hereditary diseases, tumors and the like, and promotes the development of the field of gene therapy.

This invention relates to the field of product packaging technology and discloses a method for random packaging of equal-quantity products based on virtual workstation mapping, comprising the following steps: S1, generating multiple non-repeating random combination sequences according to the capacity N of the product packaging unit; S2, creating virtual workstations that move synchronously with the physical packaging units in the virtual space of the packaging conveyor line; S3, sequentially setting at least N work areas along the packaging conveyor line, each work area being configured with a robotic arm; configuring a control instruction set for each virtual workstation; S4, each time a virtual workstation passes through a work area, the robotic arm of that work area performs a product gripping and placing operation, placing the product on the fixed physical position of the physical packaging unit corresponding to that coordinate; S5, after a virtual workstation has traversed all work areas, it enters the packaging workstation for sealing. This invention has the beneficial effects of flexible scheduling and more uniform random product distribution.

The invention discloses a construction method of an unsupervised semantic segmentation model, and an image semantic segmentation method and device, and belongs to the technical field of image processing. Based on a prior principle that similar samples appear in groups, potential similar features of image block features of each image block in the whole image are searched by utilizing mutual attention weights between every two image blocks in intra-batch images obtained by a ViT network; segmenting head features, output by a segmenting head, of all image blocks of the in-batch images are aggregated on the basis of mutual attention weights between every two processed image blocks, segmenting head aggregation features of all the image blocks of the in-batch images are obtained and further input into a projection head, and corresponding projection aggregation features are obtained; through a feature aggregation mode, the feature expression ability of a segmentation head and a projection head is improved, sufficient expression is given to strong semantics appearing in a large probability, meanwhile, sufficient expression is given to weak semantics appearing in a small probability, and then image semantic segmentation is finely and accurately achieved.

This utility model discloses an anti-cheating starting device that can randomly shuffle balls, relating to the field of game equipment technology. It includes a top plate, a ball-dropping and replacing mechanism mounted on the upper part of the top plate, a mechanical starting mechanism mounted on the ball-dropping and replacing mechanism, an anti-cheating transparent cover on the top of the top plate, a sealed box mounted on the bottom of the top plate, and a ball-topping mechanism mounted on the bottom of the sealed box. This design utilizes the ball-dropping and replacing mechanism to shuffle the balls, the mechanical starting mechanism to seal and start the game, the anti-cheating transparent cover for protection, and the ball-topping mechanism to lift the balls to the ball-dropping and replacing mechanism. This device achieves multiple random shuffling of the balls through the coordinated action of the ball-dropping and replacing mechanism and the ball tray inside the sealed box, ensuring the randomness of the starting game. The mechanical starting mechanism, combined with the anti-cheating transparent cover, prevents the balls from being observed. The cooperation of these mechanisms achieves automated operation, improving the stability, reliability, and fairness of the game.

The invention relates to the technical field of intelligent bid evaluation, in particular to a technical bid and dark bid electronic review method based on multi-dimensional dynamic dislocation sequencing, and the method comprises the steps: obtaining review data of a bid invitation project, the review data comprising scoring point information, bidding unit information and review expert information; for the first scoring point, randomly sorting all bidding units and all review experts; according to the sequence of the scoring points, performing random sorting operation of all the bidding units and all the review experts on each following scoring point until all the scoring points complete the random sorting operation; and reviewing each scoring point based on the randomly sorted bidding units and reviewing experts. The identity recognition possibility in the review process can be eliminated to the maximum extent, human factor interference is reduced, independent review of each judge is achieved, and therefore the fairness in the review process is guaranteed.

This invention discloses a key exchange method, apparatus, and storage medium based on a modular lattice. The key exchange method includes: Party A generating a random number seed, obtaining a compressed public key, and sending it to Party B; Party B using the random number seed to obtain the compressed public key; recovering data from the received compressed public key from Party A and calculating a temporary key; processing the temporary key using a segmented signal function to obtain a signal value; using the signal value to coordinate the temporary key to obtain a shared temporary key, thereby generating a verification tag and deriving the final key; Party A recovering data from the received compressed public key from Party B, recalculating the verification tag, and comparing them; only when a match is successful, the final key is derived using the same method. This ensures the randomness of the data and the ability to detect tampering with the data received by Party A, thus achieving higher security. This invention significantly reduces the failure probability while improving security.

The present invention provides a route planning method and a computer-readable medium, the method comprising obtaining boundary vertices of a plot to be operated to obtain an initial boundary; preprocessing the boundary vertices to obtain target boundary vertices, and connecting the target boundary vertices to determine the target boundary; performing an initial number of sampling point distribution planning operations within the target boundary, and effectively determining the initial number of sampling points to determine the number of effective sampling points to obtain a target number of effective sampling points and their distribution within the initial boundary, wherein the target number is less than or equal to the initial number; and performing route planning based on the effective sampling points and their distribution to obtain an operating route within the initial boundary. The present invention solves the problems of large computing power consumption of operating routes, a large number of ineffective operating routes, and safety of operating routes in the prior art.

The invention relates to a random sampling method for powdery raw materials transported by a tank truck, which comprises the following steps: S1, a driver swipes a card, and a system automatically acquires vehicle and cargo information; s2, the unloading duration S is determined; s3, determining sampling times n; s4, the raw and auxiliary material remote sampling system randomly generates sampling parameters of the vehicle: a sampling interval lower limit C, a sampling delay interval A and a sampling interval array [B1, B2,..., Bn-1]; s5, unloading is started, and after the sampling delay time interval A, the sampling machine starts sampling for the first time; after the first-time sampling is completed, the sampling machine starts second-time sampling after a sampling interval B1; and the rest can be done in the same manner until the sampling interval is Bn-1, and then the nth sampling is completed. Through the method, the randomness of the sampling interval is ensured, more comprehensive cargo quality data can be obtained, and the selective sampling risk is avoided. Meanwhile, a sampling delay parameter is introduced, so that the pollution of residues in an unloading pipeline to the sample is avoided, the irregularity of first sampling is ensured, and the representativeness of the sample is ensured.

The invention discloses a security control method for realizing large model computing power center data gridding, and relates to the technical field of data security, and the method comprises the steps: firstly determining computing power center data, obtaining a sensitivity index, an access frequency and a data size of the computing power center data, generating an optimal total number of blocks, and carrying out the blocking processing of the data, thereby obtaining a data block sequence; analyzing pre-stored physical location hash values and logic partitions of the data blocks, constructing quantized grid coordinates and carrying out gridding storage; meanwhile, the cross-region access frequency is monitored in real time, and a fusing mechanism is triggered to interrupt access if the cross-region access frequency exceeds the limit; and after fusing, adding offset to the quantized grid coordinates of the related data block sequence, regenerating and storing, and clearing the data block at the original storage position to ensure the safe storage and access control of the large model computing power center data.

The invention relates to the technical field of science popularization instruments, in particular to a probability distribution science popularization device which comprises a base, a falling mechanism, an adjusting mechanism, a triggering mechanism, a recycling mechanism, a display mechanism and a control mechanism. A falling mechanism is fixedly mounted on the base; an adjusting mechanism is fixedly mounted in the falling mechanism; a trigger mechanism is fixedly mounted in the base; a recycling mechanism is fixedly installed on the base and located on one side of the falling mechanism. A display mechanism is fixedly mounted on the base; the falling mechanism, the adjusting mechanism, the triggering mechanism, the recycling mechanism and the display mechanism are electrically connected with the control mechanism, and the problems that in an existing probability distribution demonstration device, the occurrence probability of an event cannot be changed, and the occurrence process of other probability events cannot be observed are solved; the occurrence probability of the event can be changed, and the occurrence process of other probability events can be observed.

The invention discloses a sequence password randomness detection method and system based on deep learning, and belongs to the technical field of information security. The method comprises the following steps: transforming input and output of a sequence password to be detected; constructing a data set and dividing the data set into a training data set and a test data set; training the deep learning model by using the training data set to obtain a trained detection model; and detecting the randomness of the sequence password to be detected by using the test data set and the trained detection model. According to the invention, the randomness detection effect of the sequence password can be improved.

The present invention discloses an integrated circuit scan chain diagnosis method and system based on artificial neural network. The method first injects two random faults, stuck at‑0 and stuck at‑1, into each scan trigger in the integrated circuit scan chain, wherein a random cycle of the fault is obtained by generating a random number through a linear feedback shift register; then automatic test vector generation is performed to obtain a pattern report containing fault information and a corresponding simulation log; finally, an integer fault vector and a label vector are obtained through the pattern report and the simulation log, and the integer fault vector and the label vector are input into the artificial neural network for training and verification, and the fault position in the integrated circuit scan chain is obtained by predicting the trained artificial neural network. The present invention generates random cycle faults, eliminates abnormal data, uses an artificial neural network model, effectively reduces the risk of human misjudgment and missed detection, and realizes accurate prediction.