12results about How to "Avoid accidental deletion" patented technology

This invention discloses a clutter discrimination and suppression method based on multiple echo features, comprising: acquiring radar front-end clutter and target echo detection video data and dividing it into several connected regions; extracting multi-dimensional features and labeling prior information for each connected region; using the Relief feature selection algorithm to calculate and filter the weights of the multi-dimensional features, removing redundant features to obtain the optimal feature vector; using this feature vector to train a support vector machine classifier, and obtaining the optimal parameter model through cross-validation; acquiring measured clutter data, extracting corresponding features and inputting them into the model; and determining whether to remove clutter and retain targets based on the output. This invention effectively filters out dynamic clutter spots, avoids false deletion of weak targets, significantly reduces the false alarm rate of the system, and alleviates the computational burden of subsequent track processing.

The invention relates to the technical field of laser radars, and particularly provides a 2D laser radar point cloud data processing method. The method comprises the following steps: setting a distance threshold value and an echo intensity threshold value of data processing; obtaining a circle of point cloud data, and obtaining a radar actual measurement distance and echo intensity; retaining the point cloud data with the distance smaller than the preset distance, and setting the data points larger than the distance as invalid values to obtain a circle of new data set; judging the boundary of the target object according to the invalid value to obtain an index value of the boundary; according to echo intensity characteristics, setting sliding windows and sliding times, comparing echo intensity mean values in adjacent windows, if a difference value is greater than a set threshold value or reaches the set sliding times, retaining the point cloud and quitting data processing, otherwise, deleting the edge broadening points. According to the method, the broadening problem of the edge of the target object is effectively eliminated, and the real contour of the scanned target object is restored.

This invention belongs to the field of Internet technology and relates to a distributed task monitoring method and system based on state transition and targeted push. It includes receiving subscription requests initiated by clients, adding clients to communication groups associated with the task status corresponding to a tab, and maintaining the group affiliation information of each client in real time; based on the group affiliation information, when a task status transitions from its original state to a new state, locating the original state group and the new state group, pushing a removal notification to the original state group and a move-in notification to the new state group; when a task in the execution state experiences a progress update, locating the execution state group and pushing a progress update message only to that group; and using the removal notification, move-in notification, and progress update message as outputs to trigger clients to perform removal, addition, and progress refresh operations on the corresponding tasks in their local task lists, respectively. This solves problems such as list synchronization issues and numerous invalid pushes, achieving real-time list consistency and accurate push notifications.

The invention relates to a mail system single copy storage system and method based on object storage. The system comprises a mail index service module, an object storage service module, a single copy storage management service module and a mail client. When a mail is sent, the hash value of a mail body file is calculated, only a unique copy is stored in the object storage, and the reference count of the unique copy is managed through the metadata table; when the mail is read, the file in the object storage is directly accessed through the mail index; when the mail is deleted, the reference count is decreased progressively, and the file is physically deleted only when the count is zero. According to the method and the system, single copy storage of the mail attachments is realized, the storage space occupation in a mass mail sending scene is remarkably reduced, and meanwhile, the consistency and the security of data are ensured through a reference counting mechanism.

This invention belongs to the field of communication technology and discloses a low-power data communication method and system for electricity meters based on a CAT1 module. The electricity meter collects metering data and event data, encapsulates them into data frames with serial numbers, and writes them into a transmission queue. When a queue threshold, alarm threshold, or time threshold is met, a communication session is established, waking up the CAT1 module to send batch uplink data containing a session identifier and batch sequence start and end numbers. The platform returns confirmation information, including a set of confirmed sequence intervals, missing data frame identifiers, and downlink pending transmission identifiers. The terminal retransmits missing frames within the session based on this information, opens a listening window only when a downlink command exists, deletes confirmed frames after the session ends, enters low-power mode, and persists the queue state to support power-off resume transmission.

This application provides an operation processing method, apparatus, device, and readable storage medium. In the technical solution provided by this application, a dual-level processing mechanism of message level and point level is constructed. At the message level, permission conflict detection based on user identity is introduced to effectively prevent non-creator users from accidentally deleting or tampering with other people's content, thus achieving fine-grained operation isolation. At the point level, conflict detection is pushed down to the smallest data unit coordinate point. By comparing the point position sets of the current operation and the historical operation, the spatial overlapping area is accurately identified, and the operation type corresponding to the current operation message is combined to dynamically determine whether execution is allowed, ensuring that the operation result is certain and predictable. This achieves hierarchical deterministic operation conflict processing, improving the smoothness and user experience of the online collaborative whiteboard system.

The application relates to the technical field of concrete ultrasonic flaw detection image processing, and discloses a concrete flaw detection ultrasonic image speckle noise suppression method and system based on multi-modal signal processing, which is characterized in that the original ultrasonic signal is subjected to adaptive white noise injection and EMD decomposition, non-aliasing IMF components are obtained through modal alignment and averaging, and high-frequency noise dominant components and medium-low-frequency effective signal components are divided according to the kurtosis criterion; subsequently, the high-frequency components are subjected to VMD optimization, the frequency band is accurately divided by constructing a variational constraint model and iteratively solving; the improved adaptive wavelet threshold function and the hierarchical hybrid threshold strategy are adopted for the medium-low-frequency components, so that the noise is accurately filtered out and the effective signal is retained; finally, the de-noised components of various frequency bands are fused to generate a one-dimensional time domain signal, the residual noise points are removed through median filtering after being restored into a two-dimensional image, and the de-noised enhanced image is output. The application realizes accurate separation of the noise and the effective signal, and completely retains the fine defect features in the concrete.

This invention relates to the field of speech data processing technology, and discloses a data processing method and system based on a language function detection system. The method includes: acquiring raw detection audio streams and task event logs through the language function detection system; constructing a task-level unified time index sequence; constructing a dynamic silence threshold; performing task-level coarse segmentation on the raw detection audio stream; constructing effective response scores; identifying effective response segments and secondary correction segments; reconstructing task-level structured results; and outputting aphasia language ability assessment data. Compared to existing technologies that primarily process entire recordings uniformly, especially in aphasia rehabilitation assessment scenarios with long pauses, repetitive pronunciations, and intrusive prompts, this invention addresses the technical problem of accurately extracting effective response segments. By using task event-driven temporal alignment and dynamic silence threshold segmentation, this method improves the reliability of aphasia language function assessment data.

The invention provides a data management method, a server and a storage medium, and belongs to the technical field of data processing.The method comprises the steps that in response to an operation request for any target attachment, a unique identifier of the target attachment is determined; according to the unique identifier, querying attachment information corresponding to the target attachment from an attachment table; updating a reference count in the attachment information, wherein the reference count is used for representing the number of times that the target attachment is referenced by the business entity; according to the operation request, a reference relation table of the target attachment is updated, and the reference relation table is used for recording the incidence relation between the service entity and the attachment. In this way, for one attachment, the server only stores the data stream in the attachment once, redundant storage caused by repeated copying of the same attachment is avoided, the number of times that the attachment information is referenced by the service entity is recorded through the number of times of reference, so that when deletion operation is executed, the number of times of reference of the attachment is used as a reference, deletion of the currently referenced attachment is avoided, and user experience is improved. Accessories are prevented from being deleted by mistake, and a data management mode is optimized.

The invention discloses a cue word generation method and system based on large language model semantic reflection and multi-objective evolution. The method comprises the following steps: initializing a cue word population; calculating a performance index of each cue word, and performing semantic segmentation by using a large language model to calculate an abstraction degree index; performing comprehensive evaluation based on the performance and the abstraction degree, and screening elite individuals by adopting a hierarchical greedy strategy based on a Pareto level; performing semantic reflection variation or parent fusion crossover on elite individuals by using a large language model to generate a next generation population; and the above process is iterated until a termination condition is met. According to the method, the abstraction degree index and the semantic reflection mechanism are introduced, so that the problems of easy overfitting and low variation efficiency in the traditional cue word optimization are solved, and the cue word with high performance and strong generalization ability can be automatically generated.

The application relates to the field of new energy power generation technology and discloses a wind turbine abnormal data identification method, device, medium and product, which comprises the following steps: obtaining historical standard operation data and actual operation data of a wind turbine; calculating and determining a strong abnormal threshold and a general abnormal threshold according to the mean value and the standard deviation of the first logarithmic density estimation value of the historical standard operation data; calculating the second logarithmic density estimation value of the actual operation data; identifying abnormal data according to the comparison results of the second logarithmic density estimation value and the strong abnormal threshold and / or the general abnormal threshold and the comparison result of the variable observation value and the theoretical value in the actual operation data; the strong abnormal threshold and the general abnormal threshold are calculated from normal data; the bandwidth of each operation data is adaptively determined according to the geometric mean density; abnormal discrimination based on local density is realized; meanwhile, the double constraint judgment conditions of the observation value and the theoretical value are introduced; and the accuracy of abnormal data identification is improved.

The application discloses a shield large data scalable warehousing and processing method, comprising the following steps: based on the multivariate heterogeneous data stream collected on the shield construction site, effective tunneling data in the tunneling stage is extracted; the statistical baseline corresponding to the ring number where the effective tunneling data is located is acquired, and the effective tunneling data is dynamically tolerance detected and the abnormal value is eliminated according to the statistical baseline, so that the cleaned time series data is obtained; the expected data amount of the current ring is calculated based on the ring boundary moment determined by the multivariate heterogeneous data stream, and the data coverage of each physical parameter is calculated in combination with the actual effective data amount of the cleaned time series data; the completeness score of the current ring containing a short board penalty term is calculated; when the preconfigured hierarchical trigger threshold is satisfied, the cleaned time series data is input into a preset construction analysis algorithm model, and a construction state analysis result is obtained. The application breaks the dependence on discrete hardware signals, suppresses the high-frequency jitter of the working condition state, and effectively prevents the false deletion of the physical mutation data of the stratum transition section.