63 results about "Recursive analysis" patented technology

Improved processors and processing methods are disclosed for high-speed computerized comparison analysis of multiple linear symbol or character sequences, such as biological nucleic acid sequences, protein sequences, or other long linear arrays of characters. These improved processors and processing methods, which are suitable for use with recursive analytical techniques such as the Smith-Waterman algorithm, and the like, are optimized for minimum gate count and maximum clock cycle computing efficiency. This is done by interleaving multiple linear sequence comparison operations per processor, which optimizes use of the processor's resources. In use, a plurality of such processors are embedded in high-density integrated circuit chips, and run synchronously to efficiently analyze long sequences. Such processor designs and methods exceed the performance of currently available designs, and facilitate lossless higher dimensional sequence comparison analysis between three or more linear sequences.

The invention discloses a method for automatically positioning webpage Trojan mount point in a Trojan linked webpage and belongs to the field of computer security. The method comprises the following steps of: a) determining the Trojan linking webpage; b) acquiring a style sheet in the Trojan linked webpage, and performing script analysis on the scripts therein according to a step c); c) acquiringthe scripts in the Trojan linked webpage, outputting the positions of malicious scripts in a father webpage, wherein the malicious characteristics comprise: calling the objects of known bugs, containing malicious codes, opening malicious webpages, redirecting to the malicious webpages, and adding malicious webpages; and d) acquiring an embedded webpage in the Trojan linked webpage, comparing whether the website domain name is the same as the Trojan linked webpage for the embedded webpage determined to be subjected to Trojan linkage, if so, performing recursive analysis, otherwise, outputting the position of an embedded label in the father webpage. The method can be applied to the computer security, and comprises rapidly positioning the mount position of the webpage Trojan in the webpage to assist the website management personnel to rapidly remove the malicious contents contained in the webpage.

A method of automatically detecting pulmonary nodules is provided, including the operations of acquiring a chest computed tomography (CT) image, extracting a lung region from the chest CT image, extracting a group of nodule candidates from the lung region using a gray-level thresholding technique and a three-dimensional (3-D) region growing technique, and performing 3-D feature recursive analysis on all of the nodule candidates.

The embodiment of the invention provides a visitor flow rate statistics method and device. The method comprises: a target detection image of a target area is obtained; head detection is carried out on the target detection image by using a deep learning method to obtain at least one head feature; a recursive analysis is carried out on the at least one head feature to obtain attribute information of the at least one head feature; and on the basis of the attribute information of the at least one head feature, statistics of the visitor flow rate in the target area is carried out. Therefore, head detection can be realized effectively and conveniently and the accuracy of the visitor flow rate statistics can be improved.

A method of operating an aircraft. The method includes sensing, using a trusted sensor, a trusted parameter of the aircraft during operation of the aircraft; receiving, at a processor, the trusted parameter; entering, by the processor, the trusted parameter as a first immutable entry into a ledger stored on an immutable non-transitory computer-recordable storage medium, wherein immutable is defined as unchangeability of data stored on the non-transitory computer-recordable storage medium, and wherein the ledger also contains additional immutable entries regarding operations of the aircraft and an aircraft environment; executing, by the processor, a recursive analysis algorithm on the first immutable entry together with the additional immutable entries to produce analyzed data; and using, by the processor, the analyzed data to improve future operational performance of the aircraft by ordering changes in how a component of the aircraft performs during operation of the aircraft based on the analyzed data.

The invention discloses a network information automatic downloading and processing method which comprises a computer and includes the following steps: a to-be-downloaded web address URL is set; through the computer, the method can obtain the information (including text and pictures) of the web page designated by the web address URL, and can extract information such as a web page title, issue time and text according to preset web page attributes; moreover, according to the designated web address URL, the invention can realize the acquisition of return information flow, judgment of coding form, storage of the information flow in a file, extraction of web page attributes, analysis of download pictures, recursive analysis and download and storage of web page attributes. The invention has the advantages that: real-time performance, i.e. a user can realize real-time download, analysis and processing of network information from the internet; practicality, i.e. through the method, a user can obtain needed network information conveniently. Moreover, the invention is suitable to be used in personal information search and the establishment of a commercialized information search classification center.

The invention discloses a detection system and method for realizing DNS (Domain Name System) service defense, and the system comprises a plurality of heterogeneous DNS recursive analysis servers, and the DNS recursive analysis servers form an equivalent server pool of a heterogeneous executor; the executor can be used as a recursive server or an authorization server and is used for providing domain name resolution of the local or public internet; the DNS distribution decision server is used for receiving the analysis request transmitted from the analysis acceleration server and distributing the analysis request to each executor; an analysis result of the dynamically selected heterogeneous executor is collected, and a most correct result is selected through a preset algorithm and returned to the analysis acceleration server; and the analysis acceleration server is used for transmitting the analysis request, receiving a result transmitted by the DNS distribution decision server and storing a result returned by the distribution decision, and can directly request a user to return the analysis result, so that the calculation pressure of the distribution decision is reduced.

Image objects within two-dimensional images are identified by locating boundary points that describe line segments that define a polygon outlining each object. Processing follows lines of pixels between boundary points to determine whether additional pixels are a part of the same image object by reference to a discriminator, such as color. Boundary points are thus identified for contiguous pixels and contiguous lines. Arm-like regions are identified by recursive analysis in a similar manner. The resulting boundary point list may serve to identify the image object, such as for labeling or tagging in web-based manuals, catalogs, and so forth.

Contemplated cancer treatments comprise recursive analysis of patient-, cancer-, and location-specific neoepitopes from various biopsy sites of a patient after treatment or between successive rounds of immunotherapy and/or chemotherapy to inform further immunotherapy. Recursive analysis preferably includes various neoepitope attributes to so identify treatment relevant neoepitopes.

A method of merging at least two state machines includes: mapping a first node from a first state machine to a second node of a second state machine to generate an input pair; performing a depth-first recursive analysis of transitions and nodes in the first state machine and the second state machine based on the input pair to construct an output node; and mapping the output node to a third state machine.

The invention relates to the field of garlic classifying techniques, in particular to a garlic classifying method based on machine vision and unitary linear recursive analysis. The garlic classifying method based on machine vision and unitary linear recursive analysis is characterized by including the steps of carrying out image acquisition on garlic, then carrying out acute binarization processing on acquired images, labeling communicated zones in binary images, indicating the area of the communicated zones in the images according to image pixels, carrying out mathematical modeling through unitary linear recursive analysis according to the area of the acquired garlic images and garlic transverse diameter data, and classifying the pre-classified garlic according to a fitted linear equation. According to the method, the image extraction method is adopted, a CCD is high in accuracy when used for measuring length, the garlic is not damaged because the images are acquired through scanning, and meanwhile the method is simple, high in speed and capable of saving classifying time because modeling is carried out through the unitary linear recursive analysis.

The invention discloses a matrix model based multi-calculation-engine automatic selection method. The method comprises the following steps of: adopting a matrix as a programming model and R as a programming language, and calling matrix calculation operations of different calculation engines in an R language program; calculating the time for executing different operations in different engines for matrixes of different scales, and performing analysis modeling to obtain a time performance model; modeling transmission time of data of the matrixes of different scales among the engines to obtain a time performance model; performing grammatical analysis on the R program, constructing a data flow diagram of the matrix operations, and applying each matrix operation to one calculation engine through recursive analysis on the data flow diagram according to a principle of shortest total execution time; performing grammatical analysis on the R language program, and adding set engine information into the R language program to obtain a final execution solution. According to the method, the problems of single platform, low performance and matrix scale change coping capacity shortage of existing matrix calculation are solved.

The invention discloses a source tracing method during modification of a software file, a monitoring method and a restoration method and system. The source tracing method comprises the steps of S101, when an operation system kernel is about to perform write on a hard disk, intercepting a write function of the operation system kernel to the hard disk; S102, obtaining a process ID number of a process according to a parameter transmitted when the write function is called by the operation system; S103, obtaining a corresponding process object through the process ID; S104, reading a return address of the write function through a process stack, and performing recursive analysis on original request function call of the process object; S105, obtaining an operator ID and message data submitted by the operator through an original call function so as to obtain a modification source of the modified software file; S106, packaging the operator ID and the message data submitted by the operator by a client computer to form a data package, and uploading the data package to a server; and S107, receiving the data package and sending caution information to a corresponding administrator of the client computer by the server.

The invention relates to the technical field of big data, and discloses a data desensitization method, device and equipment and a storage medium, which are used for improving the efficiency and accuracy of data desensitization operation. The data desensitization method comprises the steps of when a file compiling request is received, obtaining a data model file according to the file compiling request, compiling the data model file into an initial byte code file, and operating the initial byte code file; performing recursive analysis on the initial byte code file running in the program by adopting a byte code control framework to obtain an agent object data set, and caching the agent object data set; when a desensitization processing request is received, determining to-be-desensitized dataaccording to the desensitization processing request, and querying a target proxy object from the proxy object data set; and obtaining a preset desensitization rule, calling the target agent object, and performing desensitization operation on the to-be-desensitized data according to the preset desensitization rule. In addition, the invention also relates to a blockchain technology, and the proxy object data set can be stored in the blockchain node.

The invention discloses an intelligent monitoring method and system for loosening positioning of a steel structure bolt group. The method comprises the following steps: collecting multi-channel stress wave signals under different working conditions through a piezoelectric sensing monitoring device; preprocessing the stress wave signals; performing phase-space reconstruction on the preprocessed stress wave signals according to an improved multivariable recurrence plot algorithm to obtain a multivariable recurrence plot of a corresponding working condition; training a multi-attention mechanism improved convolutional neural network model through the multivariable recurrence plot of the corresponding working condition; and performing steel structure bolt group loosening positioning through the convolutional neural network model improved by the multi-head attention mechanism. A recursive analysis method is introduced into the field of piezoelectric active sensing, multi-sensor information fusion is realized, a multivariable recursive plot and an improved convolutional neural network are combined to realize steel structure bolt group loosening positioning, and the diagnosis precision of the model is improved.

The invention provides an XML analysis method and device. The method comprises the steps that first, a string instruction structure is defined; second, a DOM tree node structure of a document object model is defined, and a string of all elements in an XML document is instructed through the string instruction structure in the DOM tree node structure to multiplex a text buffer area of the XML document; and third, recursive analysis is performed through the text buffer area of the XML document, and the DOM tree node structure is used to construct a DOM tree. Through the XML analysis method and device, when the DOM tree of the XML document is realized, a string with external length is used to represent an instruction string on the node data structure, and therefore the purpose of multiplexing the text buffer area of the XML document is achieved; under the condition that system resources are sensitive, memory occupation can be effectively lowered, frequent allocation and release of a memory are avoided, and therefore system efficiency is improved; and the string with length has higher efficiency in the process of performing corresponding comparison, search and other calculation.

The invention discloses a method for evaluating the quality of a printer image halftone outputting algorithm. The method comprises the steps of converting an output halftone image measurement value into a Munsell lightness value, performing linear fitting on the Munsell lightness value and a corresponding gray value, using four indexes including error term quadratic sum, root-mean-square errors, regression coefficient and adjusted regression coefficient to perform unitary linear recursive analysis, and accordingly analyzing the robustness of a halftone algorithm to the laser printer non-linear characteristic. By adopting the method, the purpose of evaluating the robustness of the halftone algorithm to the laser printer non-linear characteristic is achieved, and a basis is provided for further modification of the halftone algorithm and establishment of a printer model.

The invention discloses a carbon emission recursive analysis method for a non-standard structure variation process. The carbon emission recursive analysis method comprises the steps as follows: extracting carbon emission association change information of the non-standard structure variation process and creating an initial hierarchical structure variation and carbon emission association expression model; carrying out layer-by-layer subdivision and carbon emission association information mapping on a non-standard variation structure according to the hierarchical information of the structure; creating a hierarchical sub-structure variation and carbon emission association subdivision model based on the variation information of each hierarchical structure; carrying out layer-by-layer recursion and superposition to obtain carbon emission of initial non-standard structure variation. Aiming at the problem of difficulty for analyzing carbon emission of a non-standard structure of a complex mechanical product, the non-standard structure is hierarchically subdivided, a hierarchical structure variation and carbon emission association relationship is created by a structure and carbon emission association base model, the carbon emission is quantized through carbon emission factors, and the carbon emission in the non-standard structure variation process is analyzed by recursively computing the carbon emission upwards layer by layer from the most subdivided structure, therefore a quantitative basis for a low-carbon variation scheme is provided.

The invention provides a method and device for outputting application program interface data represented by specifications, and the method comprises the steps: instantiating at least one object to obtain at least one object instance, and marking the attribute identification of at least one application program interface according to the object instance; performing recursive analysis on a document object model associated with the application program interface by utilizing the attribute identifier to obtain all objects associated with the application program interface; statically analyzing all objects associated with the application program interface, and creating a data format based on a static analysis result; dynamically analyzing all objects associated with the application program interface, and updating application program interface data expressed in the data format specification based on a dynamic analysis result; and outputting the updated application program interface data represented by the data format specification. According to the application, the application program interface data can be expressed in a standardized manner, and the application of the API can be optimized based on the associated running platform, so that great convenience is brought to the actual use process.

The invention particularly relates to a GPU (ground power unit) parallel processing method for real-time detection of a hyperspectral target, which is realized on hardware of a graphics processor (GPUS) by combining with a hyperspectral real-time detection algorithm based on recursive analysis thinking. The invention comprises the following steps: (1) inputting hyperspectral data, initialized height, original data height, original data width, and original data wave section number; copying the initialized data from a host machine end to an equipment end; initializing hyperspectral data; copying current detection pixel element data from the host machine end to the equipment end; updating an inverse matrix of a related matrix by using wood bury identical equation; configuring multithreading on the GPU, and detecting the hyperspectral image by combining with an abnormal detection operator, and at last, outputting the detection result. The GPU parallel processing method fully utilizes the maxwell structural GPU to speed up the complex calculation; the GPU parallel realization of the hyperspectral target real-time detection algorithm has practicability and universality; the parallel processing method for real-time detection of the hyperspectral target can be flexibly applied to an airborne or satellite borne platform carried with an embedded system.

The invention discloses a method for measuring dynamic characteristic similarity of a complex system. A recursive analysis result has rigidity and binary value property due to the fact that a Heaviside step function is used, so an unreliable research result is produced, the slight change of a critical distance or the change of the length and the position of a time sequence can cause the obvious change of a research result; a local binary model (LBP) and a texture similarity measurement Earth Mover's Distance model (EMD) are used to propose a new idea for texture analysis of a Gaussian recursive graph for complex system dynamics characteristic analysis, and on the basis, a method system for measuring the dynamic characteristic similarity of the complex system is constructed.

The invention provides a document object classification method based on a double-channel hybrid convolutional network. The document object classification method is used for segmenting and classifyinglogic objects (texts, formulas, tables and images) in a document picture. According to the scheme, firstly, performing multi-mode matching recursion RLSA analysis on an input picture to determine segmentation coordinates; segmenting the input picture into different logic regions according to the segmentation coordinates; carrying out label marking, noise removal and category equalization processing on the region to obtain a classification data set; sending the two-dimensional image area piece to a two-dimensional CNN for training, extracting two-direction projections of the image, and sendingthe two-direction projections of the image to a one-dimensional CNN for training; and finally, using the first seven layers of the two convolutional networks as feature extractors, performing trainingof a final model through a two-channel hybrid classification network, and predicting the object category of the regional picture by using the model. According to the invention, the original two-dimensional picture and the projections in the two directions are respectively used as input, different characteristics are used, and the classification precision is improved.

The present invention relates to a device for detecting unwanted intrusions into an information network comprising a module for receiving raw data from the network, a plurality of search engines configured to detect an attack indicator and any derived data which may be corrupted, a distribution module suitable for allocating at least one search engine to each piece of raw data, an administrator module linked to the search engines and to the distribution module and configured to transmit each piece of derived data to said module as new raw data if it has not already been processed by said same search engine(s), so as to provide recursive analysis of each piece of raw data received by said receiving module. The invention further relates to a process implemented by a device of this type.

The invention discloses a latex normalization method based on katex. The method comprises the steps that a latex expression is input, katex rendering, recursive analysis and recoding are conducted, a new latex expression is output, python calls katex through multiple threads, rendering is conducted on the input latex expression, an intermediate result of katex rendering is obtained, and the intermediate result serves as an analytic tree; performing analysis and secondary processing on the analysis tree in a recursion mode; and when the output of the analysis group is {} including the left bracket and the right bracket, judging whether the analysis object is an operator, and if the analysis object is the operator, specifying the name of the operator in front of the left bracket or the right bracket. According to the scheme, latex expressions irrelevant to semantics are removed, some redundant expressions in latex training labels are removed, and the recognition rate of the model is greatly improved; the characters required for representing the score by the latex are simplified, and the analysis complexity of latex evaluation during automatic correction is reduced.