12 results about "Sequence alignment algorithm" patented technology

The invention relates to a PCBA automatic testing system and method, and relates to the technical field of PCBA automatic testing, and the system comprises a multi-source data collection module which is used for collecting chip dynamic power consumption waveform, PCB interlayer temperature gradient, and multi-source data of signal loop impedance change, and eliminating the sampling delay error of a sensor through a synchronous collection time sequence alignment algorithm; transmitting the acquired multi-source data to a dynamic modeling engine; according to the invention, by dynamically fusing the multi-physical-quantity data and adaptively generating the test path, the system can detect the fault of the PCBA more comprehensively and accurately, the detection efficiency is improved, and the false detection rate is reduced; the thermal aging and faults of the PCB are predicted by using a dynamic modeling engine, so that potential failure risks can be found in advance, and a powerful guarantee is provided for quality control of the PCB; and the test path is automatically generated according to the dynamic modeling result and the data of the fault knowledge graph, so that the workload and error of manually planning the test path are reduced.

The invention provides a heuristic biological sequence clustering method based on semi-global comparison. The method comprises the following steps: firstly, reading all biological sequences, removing repetitive sequences, and carrying out descending sorting on the biological sequences according to sequence lengths; a first sequence is used as a representative sequence of a first category, then a next sequence is read, the similarity between the current sequence and the representative sequence is calculated by adopting a semi-global sequence comparison algorithm, each sequence can be compared to the most similar area in the representative sequence through semi-global sequence comparison, the similarity between the sequences is found to the maximum extent, and the similarity between the sequences and the representative sequence is calculated. Obtaining a relatively high comparison similarity value between the sequences; if the similarity meets a clustering threshold value, adding the similarity into a category with the same representative sequence, otherwise, taking the similarity as a new representative sequence, and generating a new category; repeating the steps until all the sequences are processed; the number of the final representative sequences is the number of clustering categories, and the categories which are the same as the representative sequences are member sequences of each category.

The invention discloses a real-time SNV and Indel detection method for second-generation sequencing data, and relates to the real-time SNV and Indel detection method for the second-generation sequencing data. The invention aims to solve the problem that a large amount of initial data generated by a modern high-throughput sequencing platform in a sequencing fragment extension and stack information updating process is in an idle state; the problems of serious waste of computing resources and low efficiency of an analysis process are caused, so that the total period from sample sequencing to obtaining of a variation detection result is remarkably prolonged. The method comprises the following steps: acquiring and processing generated sequencing fragment data in real time while a sequencer performs sequencing operation, immediately mapping the fragments onto a reference genome by utilizing an improved sequence alignment algorithm, determining the accurate positioning of the fragments on the genome, and then continuously performing the sequencing process to obtain the accurate positioning of the fragments on the reference genome. And the obtained comparison result is continuously extended and updated, so that the parallel execution of sequencing and variation detection is finally realized, and the variation detection efficiency is remarkably improved.

The invention provides a financial statement intelligent standardization processing method and system, and the method comprises the steps: constructing a hierarchical standard knowledge base which comprises a standard item name reference system and a feature vector; by taking the standard knowledge base as a reference, matching an original financial statement item name with the standard item name by adopting a weighted sequence comparison algorithm to realize preliminary matching; a matching result is optimized by adopting rule matching of context awareness; and constructing a mapping relation table of the original items and the standard items, and converting the original financial statements according to the mapping relation table to finish standardized processing of the financial statements. The problems of format differences, wrongly written characters, OCR identification errors and the like of financial statement item names can be effectively solved, the matching accuracy rate reaches 95% or above, the processing efficiency is improved by 20 times, the labor cost is remarkably reduced, and reliable technical support is provided for automatic processing and analysis of financial data.

The invention provides a heterogeneous acceleration method and system based on a parallel gene sequence alignment algorithm, and the method comprises the steps: S1, dividing DNA into n fragments, and enabling a CPU end to read the fragment data of the DNA; s2, performing parallel multi-thread processing on the fragment data at a CPU (Central Processing Unit) end to generate input data; s3, predicting the execution time of the corresponding thread at the software CPU end and the execution time of the corresponding thread at the hardware FPGA end; s4, according to the predicted execution time, selecting a position where the input data continues to be executed; s5, if acceleration processing is carried out at the FPGA end, the processed data are stored in a global memory; and S6, enabling the CPU end to perform parallel sequence alignment on the data in the global memory to complete sequence alignment. According to the invention, a strategy for realizing parallel processing of a plurality of to-be-aligned sequences based on software multithreading is realized, and the FPGA equipment end realizes parallel and streamlined processing of a plurality of sequences based on multiple cores.

This disclosure provides a security detection method, apparatus, and device for communication protocols, comprising: obtaining the structure of the communication protocol through unsupervised learning and structural parsing based on bidirectional raw traffic data; utilizing sequence alignment algorithms to find common patterns and variable fields among packets in different protocol session streams; identifying high-frequency byte sequences that consistently appear in application layer payload data; dividing the payload of a single packet into multiple fields and inferring the semantic type of each field; and constructing a protocol syntax tree for the communication protocol; then, based on the protocol syntax tree, modeling normal communication behavior to obtain a behavioral baseline of the behavioral patterns under normal communication behavior; and performing anomaly detection on real-time traffic obtained from the communication network based on the protocol syntax tree and the behavioral baseline. Thus, without prior knowledge of the detailed protocol specifications, it can intelligently learn from communication behavior to discover potential threats, reducing the application limitations of this security detection method.

The invention discloses an industrial control network protocol security detection method based on fuzzy testing, and belongs to the technical field of detection. According to the method disclosed by the invention, the protocol information is reversely deduced through the captured network flow during protocol entity communication, and the fuzzy test case is automatically constructed, so that industrial control protocol security detection is realized; under the condition that protocol priori knowledge does not need to be mastered, sequence alignment is conducted on original data through sequence comparison and sequence alignment algorithms, protocol information and a state machine model are deduced through similarity calculation, and the problem of obtaining protocol feature information needed by industrial control protocol fuzz test case generation is solved; a random generation strategy and a data variation strategy are combined to automatically and rapidly generate a paste test case, a large number of variation random inputs are sent to a tested target, behavior actions of the tested target are analyzed to achieve safety detection of an industrial control protocol, the problem that an existing fuzzy test method depends on manual single-field random filling to generate test data, and the efficiency is low is solved, and the test efficiency is improved. And the test accuracy is ensured.

The present invention is a method and device for reverse analysis of network protocol formats based on a co-evolutionary algorithm. The main purpose is to provide a protocol reverse tool based on network protocol traffic, which can analyze the protocol format without the need for protocol specifications or binary codes or programs that implement the protocol. The specific steps include pre-processing the traffic through a private protocol data extraction module and a message transmission direction identification module, and then handing the pre-processed traffic to a pre-clustering module for grouping. Then, each group of traffic is input into a protocol format extraction module constructed based on a multiple sequence alignment algorithm and a probabilistic statistical algorithm to obtain multiple groups of initial protocol specification seeds. Finally, a multi-population co-evolutionary algorithm is constructed on the basis of the two populations to optimize the obtained protocol specifications. This method comprehensively utilizes the results of multiple sequence alignment and probabilistic statistical algorithms, effectively improving the accuracy of reverse analysis of protocol specifications.

The application relates to a micro-service load balancing method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a micro-service task, dividing the micro-service task into sub-tasks according to the number of micro-service instances in a current system, and placing all the sub-tasks in a ring form into the same batch; respectively obtaining the cumulative load of each micro-service instance in the current system and the load of each sub-task in the batch, taking the cumulative load and the load of each sub-task in the batch as two ring sequences, and aligning the two ring sequences by using a dynamic programming-based sequence alignment algorithm, so that the maximum 'load value' in all micro-service instances is minimized; based on the alignment result of the two ring sequences, each sub-task in the batch is distributed to the micro-service instances, so that the predecessor and successor relationship of the sub-task distributed to the micro-service instances remains unchanged. The application embodiment can maintain good load balancing effect, optimize resource utilization, and improve task processing efficiency.

The invention relates to the field of computer internet and cloud computing, and discloses a project dimension-based precise operation and maintenance quantification and intelligent recommendation method, which comprises the following steps of: encoding distributed link tracking data into an ordered service gene sequence, and realizing automatic identification and resource quantification of a project by using a sequence alignment algorithm. By extracting a gene mutation rate and an epigenetic modification tag, system stability and external environment constraint are dynamically sensed. On the basis, a non-cooperative game model containing performance, cost and risk agents is constructed, game rules are dynamically reconstructed based on gene characteristics, risk sensitivity and constraint strategy space are adjusted in a non-linear mode, a biological adaptability evolution mechanism is simulated, a horizontal gene transfer mechanism is introduced, and a cold start decision of a new project is optimized. And finally, an optimal operation and maintenance configuration instruction is generated by solving a Nash equilibrium point. According to the method, accurate quantification, dynamic self-adaption and risk control of operation and maintenance decisions in a complex cloud environment are effectively realized.

The invention discloses a fine-grained evaluation method for logic security of a large language model, which comprises the following steps of: aiming at an obtained dynamic test case, analyzing variable interaction influence, injecting a private instruction sequence by embedding a risk module, and determining a test case version of which the difficulty is adjusted; selecting an intermediate step sequence from the determined test case version, and calculating a deviation value with a standard reasoning path by adopting a sequence comparison algorithm to obtain a fine-grained deviation index set; according to the obtained deviation index set, the accuracy data derived in multiple steps are fused, if the deviation value exceeds a preset threshold value, the deviation value is marked as a logic bottleneck point, and a potential safety crash position is judged; quantifying a step-by-step reliability index of the reasoning process through the judged safety crash position to obtain a numerical score of the logic capability; and a safety performance subset is extracted from the obtained numerical score, clustering analysis is adopted to conclude a performance mode in a high-risk scene, and a final comprehensive evaluation report is determined.

The invention relates to the technical field of biological feature recognition and front-end security authentication, and provides a front-end implicit authentication method based on multi-dimensional operation behavior features, and the method comprises the steps: S1, carrying out the collection and modeling of multi-dimensional behavior features; s2, carrying out real-time behavior consistency verification, namely collecting real-time operation data of a user according to a preset frequency, converting the data into a feature vector, analyzing a behavior pattern of the feature vector through a time sequence model, calculating the similarity between a real-time feature sequence and a reference sequence in a behavior benchmark library by adopting a sequence comparison algorithm, and carrying out real-time behavior consistency verification; generating a quantitative similarity score, and setting an abnormal judgment condition; and S3, performing an authentication decision and dynamic response mechanism, including executing a hierarchical authentication decision according to a similarity score, matching processing strategies of different risk levels, dynamically adjusting authentication parameters and a calculation mode in combination with a user use scene, balancing authentication security and applicability, and adopting a data privacy protection measure in the whole process. And the security, the universality, the user experience and the privacy compliance are comprehensively improved.