16 results about "Sequence rule" patented technology

Methods and apparatus for video processing are described. The processing may include video encoding, video decoding, or video transcoding. An example video processing method includes performing conversion between a video including one or more pictures and a bitstream of the video, the one or more pictures including one or more sub-pictures, and wherein the one or more pictures and / or the one or more sub-pictures are included in the bitstream according to an order rule, and wherein the order rule specifies a relationship between a position of a current instantaneous decoder refresh (IDR) picture or a current IDR sub-picture in the bitstream relative to another picture referenced by an entry in a reference picture list of a current slice of the current IDR picture or the current IDR sub-picture.

The invention discloses a relay protection operation state monitoring system and method, and the system comprises a data processing module which is used for obtaining a preprocessing equipment image before or after relay protection operation, and generating an equipment state code; the intelligent analysis engine comprises a safety measure card execution sequence modeling module which is used for analyzing a safety measure ticket text to construct an operation sequence rule base; the guiding operation module is used for generating operation steps according to the operation sequence rule base so as to guide a user to operate; the operation recording module is used for structurally generating a safety measure operation behavior record of the user; the intelligent state comparison module is used for comparing equipment state differences before and after relay protection operation according to the equipment state codes, the operation sequence rule base and the safety measure operation behavior records; and the leakage recovery early warning module is used for triggering leakage recovery early warning according to the comparison result. According to the invention, the safety and efficiency of relay protection operation can be improved.

The invention discloses a historical load and real-time state-based resource available amount prediction method and system, and relates to the technical field of big data analysis, and the method comprises the steps: collecting data to form a CPU data set and a GPU data set; removing abnormal values and carrying out feature coding to form a structured feature matrix; extracting a CPU time sequence rule, and introducing an attention mechanism to dynamically adjust and predict a CPU available interval; capturing GPU long-period stage features, and predicting a GPU available interval in combination with a historical stage computing power demand rule; and integrating the available intervals of the two into a global resource matrix, and matching new task resource requirements to judge whether migration is needed or not. The system comprises a data acquisition module, a feature processing module, an available prediction module and a task judgment module which work cooperatively. According to the method, the historical load and the real-time state are fused, the prediction accuracy of the available resource amount is improved, resource scheduling is optimized, failure of tasks due to insufficient resources is avoided, and the computing power resource utilization rate is increased.

The application discloses a data processing method and device, equipment and a storage medium, and belongs to the technical field of data security. The method comprises the following steps: extracting API traffic of API service successful calls from business data traffic; dividing the API traffic according to API service types to obtain an API traffic initial sample set comprising API traffic initial samples of each API service type in N API service types; extracting the calling logic sequence of the API traffic initial samples in the API traffic initial sample set to obtain an API calling sequence rule set comprising API calling sequence rules corresponding to the API traffic initial samples of each API service type; and determining whether there is an illegal API calling behavior in the API traffic initial samples of the i-th API service type based on the number of the API calling sequence rules corresponding to the API traffic initial samples of the i-th API service type. In this way, the automatic carding of the API calling logic and sequence can be realized, the artificial dependence of API over-authorization identification is reduced, and the occurrence of API data leakage accidents is avoided.

Methods, computer program products, and systems are presented. The method, computer program products, and systems can include, for instance: performing an association analysis on a transaction dataset to return an association rule, wherein the association analysis is performed independent of timing data indicating a time order of data items for the respective transactions; extracting transaction data defining a set of transactions of the transaction dataset using the association rule, the transaction data including timing data indicating a time order of data items for the set of transactions; examining data of the transaction data using the timing data indicating the time order of data items for transactions of the set of transaction; returning a time ordered sequence rule specifying a time ordered premise and predicted result, wherein the time ordered sequence rule is in dependence on the examining; monitoring activities of a user for occurrence of a condition defining the premise of the sequence rule; and returning an action decision in response an occurrence of the condition.

The present invention discloses a negative sequence rule influence analysis system and method based on campus data. The system includes a data preprocessing module, a frequent pattern mining module, an influence-oriented sequence rule mining module, a missing item contribution and influence analysis module, and a graphical interface representation module. The system preprocesses the data and mines positive and negative frequent sequence patterns, then further mines all influence-oriented sequence rules, performs influence analysis on the missing items in the influence-oriented negative sequence rules, calculates the contribution and influence of one or more missing items in the sequence rule antecedents on the result, and then represents them on a graphical interface. The present invention mines influence-oriented negative sequence rules based on student campus sequence data, and calculates the influence of the relevant missing items in the influence-oriented negative sequence rule antecedents on the result, which can more comprehensively and specifically analyze the factors affecting students' academic performance and their influence patterns.

An embodiment of the present invention provides a data transmission method, apparatus, terminal device, and storage medium, including: receiving non-video data packets sent by a visual connection router at a sending end, where the non-video data packets include at least two fragmented data packets; parsing the non-video data packets to obtain a first quantity of the fragmented data packets, a first sequence tag of the fragmented data packets, and a first hash value; determining a second hash value according to the first quantity of the fragmented data packets and the first sequence tag of the fragmented data packets; if the second hash value is different from the first hash value, determining a second sequence tag of the lost fragmented data packet according to a pre-configured data packet sequence rule and the first sequence tag; sending a retransmission request to the visual connection router at the sending end, where the retransmission request includes the second sequence tag. In this way, only the fragmented data packets of the lost packets need to be retransmitted, rather than the entire data packet, improving the transmission efficiency.

The present application relates to the technical field of vehicle-mounted electronic control unit software development and testing, and discloses a kind of quick offline calibration method and system of vehicle-mounted s19 file, the method is first obtained and related file information is supplemented variable complete information and forms variable set;Variable set is sorted and preprocessed using the monotone increasing characteristics of S19 file address;First variable is located in the Record rewrite position of S19 file using dichotomy, and Merge table is established;Subsequent variables are positioned and updated Merge table according to the corresponding dichotomy boundary mode selected according to the Block index;For CURVE, AXIS, VAL_BLK and MAP type calibration quantity respectively, complete information domain rewriting according to address continuous rule or matrix to one-dimensional sequence rule;Loop processing all variables to obtain the Merge table of Record position monotone increasing, and then merge the rewriting information to the original S19 file by dichotomy, and output the calibration file after updating checksum.The present application reduces address matching error, significantly improves the efficiency and stability of vehicle-mounted S19 file offline calibration.

The invention discloses a property task processing personnel selection recommendation method and device, equipment and a medium, and relates to the technical field of property task management. The method comprises the following steps: determining a preset serial number splicing sequence rule according to a task type identifier of a property task to be distributed; after recommendation index scoring processing and scoring sorting table generation processing based on a preset sequence number compiling rule are sequentially performed according to the task processing record information of each candidate processing person, a task matching degree sorting number, an idle degree sorting number, a task completion efficiency sorting number and a task completion quality sorting number of each candidate processing person are determined; carrying out number sorting and splicing processing to obtain a recommendation degree serial number; and determining a target recommendation object from the plurality of candidate processing personnel based on the recommendation degree serial number and a preset number, and generating processing personnel selection recommendation information in combination with the task type identifier and the target recommendation object. Reliable reference can be provided for order dispatching of the order dispatching manager, so that the order dispatching accuracy and the order dispatching efficiency of the order dispatching manager are improved.

The invention discloses a disaster event prediction method, a disaster event prediction system, disaster event prediction equipment and a medium based on artificial intelligence, and relates to the technical field of disaster event prediction. For catastrophic events in a multi-service environment, event modes, risk scores and root causes are recognized from historical and real-time data, and the problems that in the prior art, dependence of mode recognition and time series is insufficient, the high-dimensional multi-feature data modeling capacity is poor, and combination of sequence rules and a machine learning model is difficult are solved.

The invention discloses a WiFi feature data structure optimization method for a mobile terminal, and the method comprises the steps: dividing WiFi feature data into AP, RATIO and MAX unit data for storage, loading MAX units in batches during the APP analysis of the mobile terminal, dispersing the memory use time, and reducing the memory peak value; the assembled unit data follows a fixed byte occupation rule, so that the size of the unit is predictable, excessive memory is prevented from being reserved, and the peak value is further reduced; data are assembled according to a specific sequence rule, a compact structure is formed, redundant intervals are reduced, the storage density is improved, a mobile terminal can efficiently access the data, the average memory overhead is reduced, meanwhile, the data are stored in a fixed sequence, analysis can be accessed in a memory address sequence, the memory utilization efficiency is improved, and the average overhead is also reduced; in addition, a fixed rule and an ordered structure are convenient for accurately distributing and releasing the memory, timely releasing the unit memory, avoiding invalid occupation leakage, reducing memory garbage, improving the memory utilization rate, reducing the management complexity and reducing fragment-related garbage.

The application discloses a kind of relay protection operation state monitoring system and method, the system includes: data processing module, for obtaining the pre-processing equipment image before or after relay protection operation, generates equipment state code;Intelligent analysis engine, it includes: safety measure card execution sequence modeling module, for parsing safety measure ticket text, to construct operation sequence rule base;Guidance operation module, for generating operation step according to operation sequence rule base, to guide user operation;Operation record module, for structured generation user's safety measure operation behavior record;Intelligent state comparison module, for comparing the equipment state difference before and after relay protection operation according to equipment state code, operation sequence rule base and safety measure operation behavior record;Miss recovery early warning module, for triggering miss recovery early warning according to comparison result.Adopt the application can improve the safety and efficiency of relay protection operation.

The invention relates to a database technology, in particular to a method for customizing a character sorting sequence, a storage medium and equipment. The method for customizing the character sorting sequence comprises the following steps: in response to a custom character sequence instruction, obtaining a custom character sequence and a to-be-sorted object in the custom character sequence instruction; setting a character sequence rule corresponding to the to-be-sorted object according to the custom character sequence; and replacing and / or sorting the characters in the to-be-sorted object according to the modified character sequence rule. According to the method for customizing the character sorting sequence, the characters in the to-be-sorted object can be replaced and / or sorted based on the custom character sequence, so that complex characters can be effectively replaced conveniently, and operations such as special processing on the size sequence of the characters can be carried out conveniently; the problems of high query complexity, long execution time and the like caused by fixed sorting rules of the to-be-sorted objects are avoided, the query efficiency is improved, and the performance of a database system is improved.

The application discloses a resource available quantity prediction method and system based on historical load and real-time state, relates to the technical field of big data analysis, and collects data to form CPU data set and GPU data set; removes abnormal values and carries out feature coding to form a structured feature matrix; extracts CPU time sequence rules, introduces an attention mechanism to dynamically adjust a predicted CPU available interval; captures GPU long-period stage features, combines historical stage computing power demand rules to predict a GPU available interval; integrates both available intervals into a global resource matrix, matches new task resource demand to determine whether migration is needed. The system comprises data acquisition, feature processing, available prediction and task judgment modules, and the modules work cooperatively. The application combines historical load and real-time state, improves resource available quantity prediction accuracy, optimizes resource scheduling, avoids task failure due to insufficient resources, and improves computing power resource utilization.

This invention relates to the field of business forecasting and management, specifically to a complex business planning method based on a data platform and multi-agent collaboration. First, it acquires logical sequence deviations and physical environment jitter in parallel, and constructs a multi-dimensional evaluation benchmark using modular arithmetic and a sliding window algorithm, effectively solving the problems of sequence number flipping misjudgment and single-delay fluctuation interference. Second, it introduces a thermodynamic dissipation model to calculate the residual potential energy of missing data, causing it to decay non-linearly with waiting time, and combines business priority and network stability to calculate the real-time utility value of new data. Finally, it constructs a dynamic energy barrier by comprehensively considering buffer backlog depth, and determines whether to break the sequence rules by calculating a jump decision factor. This invention can effectively eliminate head-of-line blocking, ensure the real-time performance of high-priority control commands, and improve the robustness and consistency of industrial distributed collaborative computing.

The present application relates to the field of business prediction and management, in particular to a complex business planning method based on data middle station and multi-agent cooperation, first, the logical sequence deviation and physical environment jitter are acquired in parallel, the multi-dimensional evaluation benchmark is constructed by using modulo operation and sliding window algorithm, effectively solving the sequence number flip misjudgment and single time delay fluctuation interference problem. Secondly, the residual value potential of missing data is calculated by introducing the thermodynamic dissipation model, which decays nonlinearly with waiting time, and the real-time utility value of new data is calculated combined with business priority and network stability. Finally, the dynamic energy barrier is constructed by comprehensively considering the buffer backlog depth, and whether to break the sequence rule is determined by calculating the jump decision factor. The present application can effectively eliminate the head-of-line blocking, ensure the real-time performance of high priority control instructions, and improve the robustness and consistency of industrial distributed collaborative computing.