41 results about "Block detection" patented technology

The present disclosure relates to a pump failure prediction method and apparatus, the pump failure prediction apparatus including at least one processor, a storage device communicatively connected with the processor and storing program code running in the processor, and a communicator communicatively connected with the processor, wherein the program code comprises a data acquisition module and an exception detection module, and the exception detection module detects three exceptions. And inputting the real-time data into a first model in which the historical data has been supervised and learned before a fault occurs, so as to obtain a first anomaly occurring before the fault occurs. A second anomaly occurring outside the normal operating range of the pump by inputting the real-time data into a second model having unsupervised learning of the normal operating data. A third anomaly occurring outside the initial normal operating range of the pump by inputting the real-time data into a third model that has unsupervised learning of the initial operating data.

The invention discloses a code embedding method based on a semantic embedding vector generation model, which belongs to the technical field of computers, and comprises the following steps of: obtaining a binary code block, and performing disassembling processing and code structure analysis based on different granularities to obtain a basic block corresponding to the binary code block and a control flow diagram structure feature; performing assembly instruction linear conversion and cross-instruction-set semantic embedding conversion on the basis of the basic blocks corresponding to the binary code blocks and the structural features of the control flow graph to generate a unified binary code semantic embedding vector space corresponding to a cross-instruction-set architecture; obtaining a known vulnerability sample, and performing semantic vulnerability characterization analysis and candidate vulnerability retrieval positioning to generate a candidate vulnerability code block set; and carrying out dynamic analysis verification on the candidate vulnerability code block set and identifying a corresponding vulnerability repair state so as to output a corresponding binary vulnerability code block detection report. According to the method, high-precision semantic embedding of binary codes can be realized.

To provide an information processing device, a control method, a program and a storage medium that stores the program, with which it is possible to suitably generate information even at fault occurrence time.SOLUTION: A computation block 17 of a control unit 13 generates first measurement information generated on the basis of a first combination, out of measured physical quantities measured by a plurality of sensors (detection units) that respectively measure the measured physical quantities of mutually different measurement objects, and second measurement information generated on the basis of a second combination different from the first combination. A abnormality determination block 18 of the control unit 13 detects the abnormality of each individual measured physical quantity. An output control block 19 of the control unit 13 controls the output of measured information, out of the first and second measured information, that is measured by the sensor (detection unit) having measured the measured physical quantity for which abnormality was detected by the abnormality detection block 18.SELECTED DRAWING: Figure 4

The present invention discloses a method for detecting block drop in a railway track area, comprising a track area image acquisition step, in which a visual camera is used to collect an image of a running track area as a sleeper image; a block drop image detection step, in which block drop features in the sleeper image are extracted based on a preset image edge detection algorithm model, wherein the image edge detection algorithm model is configured to fuse Canny edge detection and multi-scale gradient feature extraction; a block drop verification step, in which, when a block drop feature is detected, a block drop verification device is started to spray an air flow toward an area where the block drop feature is located to drive the block drop to move; an image continuous acquisition step, in which, after the block drop verification device is started, track area images are continuously acquired as verification images; a block drop position comparison and output step, in which the sleeper image and the verification image are aligned, a coordinate system is divided based on two tracks, and the relative position offset of the block drop feature in the two track coordinate systems is compared. If the offset exceeds a preset threshold, it is determined to be a real block drop and a marking result is output.

The embodiment of the invention provides a bad block detection method, device and equipment for a memory and a storage medium. An idle peripheral register is used as a temporary data storage carrier in the running process of a server, so that the data storage efficiency is improved on the premise of not interrupting the normal running of the server; and according to the determined detection sequence, sequentially transmitting the running data of each storage area to an idle peripheral register so as to complete bad block detection on each storage area. According to the invention, the server is ensured to work continuously and normally during the detection period, and system shutdown or performance reduction caused by detection is avoided; by reasonably planning the detection sequence of the storage area and utilizing the idle peripheral resources, the efficiency of the detection process is optimized, the influence of the detection operation on the normal performance of the server is minimized, and both the system stability and the operation efficiency are considered.

The present invention relates to the field of digital communication, and discloses a testing method, device, equipment and storage medium for a Beidou module. The method includes: when connecting to the Beidou module, identifying the module type of the Beidou module; obtaining the command line and instruction format corresponding to the module type; generating a test command according to the command line and the instruction format; sending the test command to the Beidou module, and detecting the response result sent by the Beidou module in response to the test command; when the response result is detected, parsing the response result to obtain a test result; and outputting the test result. The present invention improves the efficiency of testing the Beidou module.

A method for modifying a procedure includes: accessing an instructional block library containing a set of verified instructional blocks associated with approved digital procedures performed within a facility; accessing an unverified instructional block, authored by an operator, for a new digital procedure at the facility; detecting a set of language signals in the unverified instructional block; correlating an equipment unit language signal, in the set of language signals, with an equipment unit located within the facility; correlating an action language signal, in the set of language signals, with an action prompt related to the equipment unit; identifying a verified instructional block, in the set of verified instructional blocks in the instructional block library, as analogous to the unverified instructional block in response to the verified instructional block including language signals associated with the equipment unit and the action prompt; and inserting the verified instructional block in the new digital procedure.

The invention relates to a blocking detection method and device for a structured query statement, equipment, a readable storage medium and a program product. A first thread identifier and a second thread identifier are determined according to an active service table of a target database, a first service identifier of a first service requesting a lock and a second service identifier of a second service holding the lock, and a first structured query statement and a second structured query statement corresponding to the first thread identifier and the second thread identifier respectively are used for querying the first structured query statement and the second structured query statement. And structuring the time corresponding relationship between the query statements to obtain a blocking detection result. Compared with a traditional method of searching according to manual experience, the method has the advantages that the first thread identifier and the second thread identifier are determined by using the first service identifier of the request lock and the second service identifier of the holding lock, each structured query statement is determined by using each thread identifier, and the blocking detection result is determined by combining the corresponding relationship between the query statements; and the blocking detection efficiency of the structured query statement is improved.

The application discloses a kind of non-contact heart rate detection methods for face has sheltered scene, steps are as follows: input training video, face picture sequence is intercepted by face recognition;Training is based on the three-dimensional residual neural network of block;Extract the block weight based on correlation coefficient;Extract the block frequency domain feature clustering center;Input real video, face picture sequence is intercepted by face recognition;Extract the block depth feature by the three-dimensional residual neural network of block based on the training;Extract the block weight based on clustering;Extract block detection heart rate, the block weight based on correlation coefficient and the block weight based on clustering are weighted summation, obtain final detection heart rate.The application assigns different weights to the heart rate detection results of different facial regions, overcoming the problem of accuracy decline in non-contact heart rate detection method under the scene of partially occluded face.

The invention provides an overlapping frame optimization processing method based on remote sensing image partitioning. The method comprises the following steps: reading an image and carrying out block processing; calling the target detection model to generate a detection frame; converting the detection box into a vector file; calculating a detection frame overlapping degree and a center distance; eliminating a redundant frame according to an overlapping threshold and a merging strategy; and for a horizontal detection frame, overlapping degree and distance dual-threshold combination is adopted, and a directional detection frame only needs an overlapping degree threshold, so that the problem of inter-block redundant frames caused by block detection is solved, and the accuracy and readability of a detection result are remarkably improved. The invention relates to the technical field of remote sensing.

The invention discloses a database fault self-recovery method, system and device and a storage medium, and relates to the field of computers.The method is applied to the database fault self-recovery system, a fault processing module is deployed between an application layer of the system and a database, and the method comprises the steps that in response to a data processing request, the state of a main database is detected through the fault processing module; and when the main database is in a fault state, controlling the fuse to be switched to a fusing state so as to transfer the data processing request to the standby database for processing. According to the application, the fault processing module is deployed between the application layer and the database, when the fault processing module detects that the main database is in the fault state, the fuse is controlled to be switched to the fusing state, so that the request is transferred and sent to the standby database to be processed, a complex switching process of a server cluster is not needed, and the processing efficiency is improved. Instead, the deployed module directly detects the fault, triggers the fusing and transfers the request, so that the switching time consumption can be shortened, and the service can still run continuously when the main database fails.

The present application relates to the technical field of communications, and discloses a synchronization signal block detection method and device, and a terminal. The method in embodiments of the present application comprises: a terminal performs detection on a first synchronization signal block on a first resource to obtain target synchronization information; the terminal determines a third resource from among second resources on the basis of the target synchronization information, wherein the second resources are resources associated with a second synchronization signal block; and the terminal performs detection on the second synchronization signal block on the basis of the third resource, wherein the first synchronization signal block uses any one of the following waveforms or modulation modes: amplitude-shift keying (ASK); frequency-shift keying (FSK); on-off keying (OOK)-integrated orthogonal frequency division multiplexing (OFDM); and OFDM.

The application discloses a kind of disk bad block repair method and device of stream replication cluster, at least one master node and multiple backup nodes are included in the stream replication cluster, wherein each backup node is used to backup at least part of data of the at least one master node, disk bad block repair method includes: in the case where it is determined that current node exists bad block, determine a target node from remaining nodes, the target node includes the data block corresponding to the bad block;According to the bad block parameter of the bad block, call preset function to obtain the data of corresponding data block from the target node;The data obtained is checked, and in the case where it is checked, the data of the data block is used to repair the bad block.The disk bad block repair method of the embodiment of the application can be repaired immediately during use, and the user request is almost zero delay.In idle service state, it can actively initiate bad block detection and repair, and fully guarantee the safety and accuracy of disk data.

The invention discloses a newly-added bad block detection method, system and device for an SSD (Solid State Disk), and the method comprises the steps: obtaining log data of the SSD, and carrying out the unified processing of the semantics of the log data, and obtaining standard log data; the standard log data are input into a newly-added bad block prediction model to obtain a newly-added bad block probability, and the newly-added bad block probability refers to the probability that newly-added bad blocks appear in the SSD; when the bad block adding probability is greater than a preset probability, inputting the standard log data into an online change point detection model to obtain a suspected bad block cluster; and performing read-write verification on the suspected bad block cluster to determine a newly added bad block, and generating a detection report according to the newly added bad block. According to the method, the semantic meaning of the log data is subjected to unified processing, the definition difference of the log field is eliminated, the detection universality is improved, and the detection accuracy is improved by firstly detecting the probability of the newly-added bad block, then detecting the suspected bad block cluster and accurately positioning the newly-added bad block from the suspected bad block cluster.

The embodiment of the invention discloses a contract consensus method and device, a computer, a storage medium and a program product, and the method comprises the steps: obtaining first transaction data comprising a contract installation request transaction, packaging the first transaction data into a first transaction block, and obtaining a first block detection result of the first transaction block; broadcasting the first transaction block to a first slave node, and when the first slave node passes the consensus of the first transaction block for a second block detection result of the first transaction block and the first block detection result, performing uplink processing on the first transaction block; when a first transaction detection result for the contract installation request transaction in the first block detection result is a transaction passing result, installing the first smart contract, and generating first contract installation information for the first smart contract; the first contract installation information is used for generating a contract enabling transaction for the first smart contract. According to the invention, the contract consensus efficiency can be improved.

The invention discloses a side channel defense method based on Raptor coding and Intel SGX, which can prevent an attacker from acquiring side channel information by injecting random noise in response to a cloud end and confusing uploaded block information by using the Raptor coding; for side channel sensitive content attacks, an efficient dirty block detection mechanism is realized based on the SGX, and security encryption is performed based on the SGX. Through security analysis, the existence inference attack success rate can be reduced to a theoretical lower limit. Experiments show that compared with a traditional scheme, the throughput performance of the system is remarkably improved, and bandwidth consumption is reduced.

The application relates to an IO blocking detection method and device, computer equipment, a storage medium and a product. The method comprises the following steps: obtaining a current IO request number and a current IO request completion number from a system; the current IO request number is used for representing the number of IO requests to be processed at the current time; the current IO request completion number is used for representing the number of IO requests processed within a first preset time period before the current time; according to the current IO request number and the current IO request completion number, it is determined whether the system has IO blocking; if the system has IO blocking, an alarm information is output. By using the method, whether the system has IO blocking caused by software and hardware faults can be determined through the current IO request number, the current IO request completion number and a counting variable, the problem that the IO blocking detection accuracy is low in the traditional method can be avoided, and thus accurate IO blocking detection can be realized.

Technology is disclosed herein for detecting evolved bad blocks in three-dimensional NAND. The test may include a drain side erase that includes applying an erase voltage from the bit lines and a source side erase that includes applying an erase voltage from the source line(s). If the source side erase performed worse than the drain side erase this may indicate a defect near the source side of the block. For example, the source side erase may fail but the drain side erase may pass. As another example the source side erase may take at least a pre-determined number of additional erase pulses to pass than the drain side erase. If the block is found as having a defect the entire block could be marked bad or the defective region could be identified such that the defective region is no longer used.

The invention discloses a null read instruction execution method and device, electronic equipment and a storage medium, relates to the technical field of storage, and is applied to a flash memory controller which comprises an execution module. The method comprises the steps that an execution module obtains a first address from an address table and generates a first null read instruction based on the first address, and the address table comprises a plurality of target data block addresses of a plurality of target data blocks of a flash memory; the execution module obtains a fault block index table, a plurality of fault block addresses are recorded in the fault block index table, and each fault block address is the address of any fault data block in at least one fault data block existing in all data blocks of the flash memory; the execution module detects whether a fault block address which is the same as the first address is recorded in a fault block index table or not; and if not, the execution module sends a first null read instruction to the flash memory. The method can improve the efficiency of executing the null read operation, and avoids occupying resources and time of a system where a firmware program is located.

Data digitization via custom integrated machine learning ensembles is provided. For example, a system integrates multiple trained machine learning ensembles to identify, extract, and map data. The system receives a data set from sources. The system identifies ensembles can include machine learning models that can determine an outcome. The system filters a subset of data from the data set. The system identifies a layout for the data set based on a vendor type, data type, and the data set. The system executes a block detection module to identify blocks of the layout. The system executes a header detection module. The system executes a policy detection module to identify the headers as policies. The system transforms, based on the headers, the layout, the blocks, and the policies, the data set into a second file type, and presents the transformed data set for integration into a capital management system.

A system (100) for analyzing log data for operational and security anomalies is provided. A preparation module (120) prepares log data by determining the necessary volume, evaluating suitability, and categorizing it. A pattern discovery module (125) identifies structures in the log data using a plurality of methods. A patterned-message structure module ( 130) creates a structured format for each log message and computes hashes for data integrity. A processing module (135) stores and validates the structured logs. A message pattern curation module (140) customizes patterned messages and offers suggestions. A log message grouping module (145) organizes log messages into groups based on patterns and binding variables. An error identification module (150) detects and categorizes errors, highlighting operational and security issues. Finally, a log storage module (155) stores configurations, static log data, and variable content efficiently.

The application provides an information security event alarm level evaluation method and system, the method comprises the following steps: obtaining transmission data information of data in a transmission process, wherein the transmission data information comprises transmission message data and transmission content data; obtaining turning data information of data after turning, wherein the turning data information comprises turning message data and turning content data; obtaining security evaluation information according to the transmission data information and the turning data information; and obtaining a security level by processing the security evaluation information through a neural network. The information security event alarm level evaluation method and system provided in the embodiment of the application can monitor data flow and communication data on a network, accurately match network attack behaviors and other information security events by using a large number of rules, timely discover attacks and give early warnings, accurately evaluate security levels and block detection behaviors.

Embodiments of the present application relate to the technical field of kernel security, and provide a memory exception detection method and a computing device. The method comprises: in response to receiving a memory allocation instruction, determining a first memory block corresponding to the memory allocation instruction; detecting post-release use of the first memory block based on content in an isolated block and a data block corresponding to the first memory block; if it is detected that the first memory block has post-release use, filling the isolated block and the data block of the first memory block with a preset padding value; detecting out-of-bound access of a second memory block adjacent to the first memory block; and generating an exception detection record according to a detection result of the first memory block and a detection result of the second memory block. Based on the present solution, the computing device can detect the security status of a memory block to be called and its adjacent memory block in linkage when the memory is called, implement security protection of a process of using the memory of the computing device, reduce a blind area of memory exception detection, and improve the accuracy and response timeliness of memory exception detection.

To prevent monitoring accuracy of behavior of an object existing in a predetermined area from being affected by an environment in the area.SOLUTION: The monitoring control apparatus 30 is configured to monitor a behavior of an object in a predetermined area based on a captured image in which the area is captured, divide a predetermined range of the captured image into a plurality of blocks to detect a motion vector of each block, and determine, based on a direction and a magnitude of the motion vector of each block, whether an object moving in a doorway direction of the area is present in the captured image without detecting the object captured in the captured image.SELECTED DRAWING: Figure 1

The invention discloses a synchronization signal block detection method and device and a terminal, and belongs to the technical field of communication, and the method comprises the steps that the terminal detects a first synchronization signal block on a first resource, and obtains target synchronization information; the terminal determines a third resource in a second resource based on the target synchronization information, wherein the second resource is a resource associated with a second synchronization signal block; the terminal detects the second synchronization signal block based on the third resource; wherein the first synchronization signal block adopts any one of the following waveform or modulation modes: amplitude shift keying ASK; a frequency shift keying (FSK); an on-off keying (OOK) superposes orthogonal frequency division multiplexing (OFDM); and OFDM.

The application provides a training system, a chip and a storage medium of a parallel bus link, the system comprising: a data detection module, configured to detect the validity of data signals corresponding to different phase stages in a plurality of preset phase stages of a clock phase, and obtain binary detection results of the data signals corresponding to the different phase stages; a maximum cluster detection module, configured to obtain a plurality of groups of binary sequences based on an initial binary sequence; obtain a target phase adjustment value based on a binary sequence corresponding to a maximum value in a plurality of values corresponding to the plurality of groups of binary sequences; and a clock module, further configured to adjust the clock phase based on the target phase adjustment value, and detect the validity of data signals corresponding to the adjusted clock phase through the data detection module, and when the data signals corresponding to the adjusted clock phase are detected to be valid, training of the parallel bus link is ended. Thus, fine adjustment of the clock phase is realized through the system.

The invention belongs to the technical field of computer hardware and memories, and particularly discloses a memory bad block parallel detection and repair system based on a multi-core processor. The system comprises a memory array, a multi-core processor, a system state monitoring module, a dynamic strategy generation module and a task scheduling and executing module. The system state monitoring module collects multivariate state parameters in real time; the dynamic strategy generation module calculates optimal scheduling control parameters in real time according to the state parameters on the basis of a reinforcement learning decision model; and the task scheduling and execution module schedules the multi-core processor to execute bad block detection and repair tasks of the storage area in parallel according to the parameters. According to the invention, adaptive global optimization balance of performance, power consumption and reliability in a dynamic change environment is realized.