483 results about "Slicing" patented technology

The invention relates to the technical field of 3D printing models, in particular to a 3D printing model slice feature compensation method and system and a medium. The method comprises the following steps that a 3D printing model is collected, a model feature skeleton is split, transverse slice features are generated, then a 3D printing environment is collected, virtual simulation is carried out, environment stress analysis is carried out on the skeleton slice features to obtain environment stress data, then deformation scale deduction and thermal deformation prediction are carried out based on the environment stress data, and a thermal deformation model is obtained. On the basis, reverse deformation simulation is carried out, deformation repair requirements are evaluated, a deformation compensation path is planned, finally, compensation simulation of a model feature skeleton is achieved, non-target deformation is analyzed, a compensation path is adjusted, and therefore the feature compensation method is optimized. According to the 3D printing model slice feature compensation method, the accuracy and quality of the 3D printing model are integrally improved.

The invention relates to the technical field of visual rendering, and provides a three-dimensional data visual rendering method and a visual rendering engine system.The method comprises the steps that space segmentation processing is conducted on three-dimensional model data to be rendered through the LOD technology to generate block slice data with different geometric detail levels, organizing the block slice data through a tree structure with a spatial relationship, and outputting the tree structure as an index file; the method comprises the following steps: adaptively screening block and slice data of different levels of detail based on a user vision field range, storing the block and slice data into a rendering request queue, querying block and slice data to be rendered from the rendering request queue according to index codes of the block and slice data, and updating a layer browser database; according to the method, to-be-rendered block slice data are downloaded and analyzed in parallel in batches in a separated collaborative operation mode, and a rendering task is executed according to a data analysis result, so that the rendering scheduling frame rate is remarkably improved, and rapid visualization of urban mass three-dimensional slice data at a webpage end is realized.

The invention discloses a 3D printing partition filling path planning method based on stress distribution. The 3D printing partition filling path planning method is suitable for FDM (fused deposition modeling) printing. The method comprises the following steps: firstly, performing finite element mechanical simulation on a to-be-printed model to obtain node coordinates and stress distribution data; then, an improved Gaussian mixture model (GMM) algorithm is adopted to carry out stress partitioning on the model, and an area boundary is optimized in combination with image processing and a Snake algorithm. Differentiated path planning of a high-stress area, a conventional area and a non-filling area is realized through an adaptive slicing and partition filling strategy, and a G-code file with multiple adjustable parameters is automatically generated. According to the method, the structural strength and the material utilization rate of a printed piece are effectively improved, and the method is suitable for high-performance 3D printing manufacturing of a complex structure.

The invention discloses a retrieval enhanced warehouse-level code completion method based on semantic topology and disambiguation redundancy pruning. Firstly, a key value code library for accurate mapping of source code fragments and induction sub-graphs is constructed through a specific slicing algorithm; in the retrieval stage, four-level layered optimization is adopted, structural similarity is evaluated by extracting a deep semantic relationship, trimming accurate duplicate items and using a new graph-based measurement (tradeoff is performed on editing according to topological importance), results are reordered to maximize correlation and diversity, candidate items are systematically refined, and the retrieval efficiency is improved. The problems of retrieval redundancy solidification and surface similarity misleading are solved, meanwhile, cross-module dependence is analyzed through an external perception identifier disambiguator, and the problem of cross-file symbol ambiguity is solved; and finally, fusing an optimization result to generate a prompt to drive the LLM to generate higher-quality output. According to the invention, through coordination of semantic and structural signals, strong performance can be obtained even in a large-scale and resource-limited code library. Meanwhile, the design allows it to be orthogonally complementary to other cross-file methods, providing collaborative improvements when used in combination.

The invention discloses a test case generation method, electronic equipment and a storage medium, and the method comprises the steps: carrying out semantic recursion slicing on a target document, and obtaining semantic coherent demand document slices; performing fragment sliding window processing on the document slices through a preset large language model to obtain a plurality of test cases; and according to the correlation of the functions contained in the plurality of test cases, merging the plurality of test cases to obtain a test case set. The invention discloses a test case generation method, electronic equipment and a storage medium, which can keep semantic integrity of a segmented text and correspond to context information, and realize that a demand document outputs a test case in an end-to-end manner.

The invention relates to the technical field of computer application, in particular to an industry document generation method based on a large language model and retrieval enhancement, which comprises the following steps: acquiring a first user demand of a building engineering project to be input, performing data preprocessing on the first user demand, and acquiring the preprocessed first user demand; performing semantic alignment on the preprocessed first user demand by adopting a cross-modal embedding model to generate a multi-modal fusion vector; according to a dynamic semantic slicing strategy, performing slice segmentation on the multi-modal fusion vector, and obtaining a plurality of slice units containing complete semantics as segmented multi-modal fusion vectors; inputting the segmented multi-modal fusion vector into a pre-trained special retrieval enhancement large model for the building industry, and generating an industry document which conforms to a building engineering specification and a first user demand; according to the method, the problems that the generated building related document content in the building industry is low in professionality and accuracy and cannot meet the industry requirements are solved.

The invention discloses a software testing method and system based on a large model, and relates to the technical field of software testing, and the method comprises the following steps: step 1: describing a code review rule, and expanding specifications required to be checked: firstly, listing the check specifications required to be satisfied by a code, and according to a thinking chain and a zero- / feed-shot example, establishing a list of the check specifications required to be satisfied by the code; the check rules in the list are described as reasoning instructions of the model according to the check key points and the check steps through combination of one or more technologies of context learning; 2, code slicing: performing structure analysis and dependency analysis on the tested software project: firstly, slicing the code according to a function by utilizing a code analysis tool; according to the software testing method and system based on the large model, convenient project management, user-defined configuration and high-automation-degree test execution can be implemented on a software evaluation task, and the evaluation efficiency is effectively improved.

The embodiment of the invention provides a front-end large file uploading method and device, and the method comprises the steps: receiving a large file uploaded by a user through a front end, carrying out the dynamic fragmentation of the large file according to a set dynamic fragmentation model, determining each corresponding fragment, carrying out the priority judgment of each fragment, and determining a corresponding priority order, the method comprises the following steps: determining a corresponding concurrent uploading fragment quantity according to a network bandwidth, a load and a preset concurrent quantity rule, carrying out concurrent uploading operation on each fragment according to a priority sequence and the concurrent uploading fragment quantity according to a preset multiplexing technology, judging whether concurrent uploading of each fragment is successful or not, and if the concurrent uploading fails, executing the concurrent uploading operation on each fragment. According to the method and the device, file fragmentation and concurrent uploading can be carried out on the basis of dynamically adjusting the sizes of the slices and the concurrent quantity, and the efficiency and the flexibility of uploading the large file are improved. The method and the device have the advantages that the file fragmentation and the concurrent uploading can be carried out on the basis of dynamically adjusting the sizes of the slices and the concurrent quantity, and the uploading efficiency and the uploading flexibility of the large file are improved.

The invention belongs to the technical field of digital bid evaluation, and provides an intelligent bid evaluation method and system based on a knowledge enhancement large language model.The method comprises the steps that firstly, a to-be-evaluated file library of project bid inviting and tendering files is established; then, files in the to-be-reviewed file library are analyzed, file slices are generated, and a reviewed file knowledge base is formed; then, text slices in the file knowledge base are retrieved and reviewed through key fields, and input cue words of the knowledge enhancement large language model are generated in combination with the key fields and the file slices; then, interacting the input cue word with a pre-trained knowledge enhancement large language model to obtain all key field information; then, scoring the bidding file according to a preset bid evaluation algorithm for all the obtained key field information; and finally, sorting the scores of all the bidding files in a descending order to generate an intelligent bid evaluation report. According to the method, the application of the knowledge-enhanced large language model in the aspects of bidding and tendering key information extraction and intelligent bid evaluation is realized, the flexibility and adaptability are relatively high, the influence of human factors on bid evaluation work is reduced, and the fairness and justice of the bid evaluation process and result are actively promoted.

The invention belongs to the technical field of image analysis, and more specifically relates to a small-sample full-section pathological image classification method and system based on a multi-modal large model, and a computer readable storage medium. The method comprises the steps of obtaining a multi-instance data set, and dividing the multi-instance data set into a training set and a test set; a complete pathology multi-instance data set composed of M full-slice pathology images is given, each full-slice pathology image comprises U image blocks, each full-slice pathology image has a package level label, and each image block has an instance level label; k full-slice pathological images are selected from the data set, L image blocks are selected from each selected full-slice pathological image, and a training data set is constructed; constructing a double small sample learning new normal form network model, and performing learning; and finally carrying out two-level classification. The problems that in the prior art, a large amount of annotation data is needed, the annotation cost is high, popularization in clinical application is difficult, and data scarcity is difficult to solve are solved.

The invention provides a small target detection method based on a superpixel mask and a dynamic kernel. The small target detection method comprises the following implementation steps: acquiring a training and testing sample set; constructing a target detection network model based on the superpixel mask and the dynamic kernel, and carrying out iterative training on the target detection network model; and obtaining a small target detection result. The greedy slicing module carries out initial image block segmentation according to the center point and the scale, the defect that space correlation features are segmented due to segmentation is avoided, the dynamic kernel module carries out multi-scale feature fusion on each image block, the receptive field can be dynamically adjusted, wide-area context information of targets of different scales can be flexibly adapted, and the image segmentation efficiency is improved. The detection precision is effectively improved; a superpixel mask generator generates a foreground region mask irrelevant to the category for each extracted feature image, and a dynamic kernel module performs multi-scale feature fusion on each foreground image block containing a target cluster obtained by a greedy slicing module; and the influence of processing useless background information on calculation overhead when the multi-scale features are obtained is avoided.

The invention provides a photocuring 3D printing intelligent slicing optimization method based on artificial intelligence, and relates to the technical field of photocuring 3D printing.The method comprises the steps that a target model summary file is generated by collecting a 3D printing model file and printing parameter data; performing slicing processing on model data in the target model summary file to generate model slicing data; analyzing the geometric complexity of the model by using a deep convolutional neural network, and dynamically adjusting the thickness of a slice layer based on a complexity coefficient; through multi-objective optimization of printing quality, time and material consumption, printing setting is dynamically adjusted according to an optimization result; and the printing state is monitored in real time, slice parameters are adjusted according to monitoring data, an optimization result is verified before actual printing, and slices are adjusted and optimized according to a verification result. The 3D printing model file and the printing parameter data input by the user can be automatically analyzed, the printing process is monitored in real time, the slicing parameters are dynamically adjusted, and the printing quality and efficiency are improved.

The invention relates to the technical field of additive manufacturing digital twinning, solves the technical problems of large calculation amount and long rendering time of a traditional 3D printing simulation method, and particularly relates to a 3D simulation system for quickly realizing additive manufacturing, which comprises the steps of loading and processing a model file, loading and processing a slice file and loading 3D model section data. According to the method, the cutting plane information of a target renderer or a material is dynamically set, the display and progress of a 3D printing model are controlled and managed, user interaction is controlled through a scroll bar, and through the operation, parts in the additive manufacturing printing process can be rapidly achieved on a Unity platform. According to the method, a vivid 3D printing simulation effect is quickly generated by utilizing a simplified geometric model, material attributes and an efficient rendering algorithm, and the whole printing process is simulated, so that a user can obtain visual preview of a printing object in a short time and can watch the whole printing process, and printing parameters can be better evaluated and adjusted.

The invention discloses an image alignment method and device, equipment and a storage medium, and relates to the field of image processing. According to the scheme, a to-be-detected circuit board scanning graph is obtained, and any unit area in the to-be-detected circuit board is recognized and extracted; based on a preset segmentation rule, segmenting the unit area into a plurality of subareas, and generating a window image set; and extracting window images in the window image set, mapping the window images to a mother layout corresponding to the Pcs particle image one by one according to image contours, and carrying out image alignment according to the image contours so as to carry out defect detection according to the mother layout. The method comprises the following steps: carrying out rasterization segmentation on a circuit board area image, and mapping the image to a target position in a mother layout in a manner that each window image is matched and aligned one by one; and each window image can be compared with the contour line of the mother layout as much as possible, the problems of element missing, dislocation, addition and damage are detected, and the subsequent defect detection precision is improved.

The invention discloses a binary vulnerability static mining method and system based on a large model, and relates to the data security and computer technology, and the method comprises the steps: extracting an external function from a decompiled binary file, recognizing a taint rendezvous point possibly causing a vulnerability by using the large language model LLM in combination with a rule base, and receiving an externally input taint source; generating an attacked target according to the calling point of the taint convergent point; performing reverse slicing based on the vulnerable target to generate a function call chain; screening the generated generation function call chain to obtain a dangerous flow; selecting an adaptive prompt template according to the type of the taint convergent point of the dangerous flow so as to perform block processing on the long function body and then perform combination to generate a prompt sequence; and utilizing the prompt sequence to guide LLM to perform vulnerability detection on the dangerous flow. According to the method, the accuracy, efficiency and automation level of binary program static vulnerability mining can be improved, and the defects of a traditional method in the aspects of complex dependency analysis and unknown vulnerability detection are overcome.

The invention discloses a power grid GIS data editing method and system, electronic equipment and a storage medium. The method comprises the steps that a server constructs power grid vector slice data based on power grid GIS data and converts power grid equipment data into GeoJSON data; the client obtains and loads the vector slices, picks up a power grid graph from the vector slices according to the position of the edited equipment, adsorbs the power grid graph to the edited equipment, and requests the server for GeoJSON data of the corresponding equipment; the server performs query based on the edited device to obtain a device associated with the edited device, and sends GeoJSON data of the edited device and the associated device to the client; and the client establishes a relation with the GeoJSON data according to a pre-configured vector slice layer, captures an editing operation, superposes the vector slice and the GeoJSON data and then displays the superposed vector slice and GeoJSON data in real time. The problems of graph rendering and large data volume online editing are solved by using a data layering mechanism combining vector slicing and GeoJSON, and the rendering efficiency is improved.

There is provided a system and a method for dynamically and adaptively slicing, reducing and bit packing a streamed serialized data sequence. A streamed serialized data sequence is received, and a reduction matrix is iteratively applied on the streamed serialized data sequence to obtain a plurality of sliced values. For a given iteration, it is determined if a corresponding given sliced value of the plurality of sliced values is present in an index. If the given sliced value is not present, the given sliced value is added by bit packing an unused id associated with the given sliced value using a first number of bits based on a current index length and using a second number of bits to encode the sliced data value to thereby obtain a given bit packed sliced value. The given bit packed sliced value is aggregated to obtain a bit packed data stream and transmitted.

According to the emergency safety management GIS big data vector slicing service map, the vector data are thinned and simplified under each level by using the optimized global constraint algorithm, and the simplified and thinned vector data are cut and sliced and are published in a service form. The style of the tile is designed, and the client renders and visualizes the requested vector tile according to the specified style. And designing a cutting thought, and cutting point, line and surface elements in the vector data. And organizing and storing the generated tiles by using a quadtree index. A cache strategy of a client is designed, existing WMS and WMTS service standards are expanded, a vector tile map style is designed, and vector tiles are published in a service form. According to the method, a prototype system is created, static and dynamic slicing services of the vector map are realized, loading and rendering are carried out at a client, and particularly, when the emergency safety management quantity is huge and the quality is poor, the map precision and efficiency advantages are obvious.

The invention provides a 3D printing path planning method and system for a three-dimensional curved surface. The method comprises the steps that printing area identification is conducted on a 3D printing model, a curved surface area is obtained, slicing processing is conducted according to the dynamic slice layer thickness, a printing path is obtained through a preset printing path planning method according to the dynamic slice layer thickness, node representation is conducted on the printing path, weight values between path nodes are determined, and a printing path sorting table is generated; 3D printing is executed, detection is conducted through a preset visual sensor, curved surface parameters are obtained, and 3D printing parameters are adjusted according to the curved surface parameters; according to the method, self-adaptive layering processing is carried out by fusing the material performance, the printer parameters and the 3D printing requirements, the path is represented in a nodal mode, the weight values between the nodes are constructed, the path sorting table is generated accordingly, transition path planning and optimization are carried out, 3D printing path planning and optimization of the three-dimensional curved surface are achieved, and the 3D printing efficiency and the printing quality are improved.

The invention belongs to the technical field of geographic information technology and remote sensing image processing and service, and discloses a slice-free image service system and method based on dynamic projection and real-time mosaic, which abandons the traditional pre-slicing mode, directly provides online service based on original image data, and improves the service efficiency. The problem of redundant storage caused by pre-generation and storage of massive tiles is fundamentally eliminated, and storage space is saved by up to 90%. Meanwhile, when the original data is updated, the system does not need to carry out a time-consuming re-slicing process, real-time updating and publishing of services can be realized, and the core pain points of long data updating period and high delay in the traditional technology are thoroughly solved. Through the integrated dynamic projection engine and the real-time mosaic module, the on-demand service request of the client for any coordinate system, any spatial range and any resolution can be responded.

The invention provides a labeling method for security management knowledge graph data, and the method comprises the steps: carrying out the slicing processing of target document data of a to-be-constructed security management knowledge graph, and generating a plurality of pieces of corresponding target slice data; the target document data is composed of knowledge data related to industrial and mining safety; inputting each piece of target slice data into a preset large model, and performing knowledge augmentation processing based on a preset cue word and the target slice data by adopting the preset large model to generate corresponding target candidate data after augmentation; in response to an auditing operation and an optimizing operation of a user on the target candidate data, performing corresponding adjustment processing on the target candidate data, and generating corresponding target knowledge data after adjustment; and adopting a preset large model to identify a target entity in the target knowledge data and generate a triple corresponding to the target entity. According to the method provided by the invention, the efficiency of data annotation is improved in a mode of combining a large model and user auditing.

A sliced graphics processing unit (GPU) architecture in a processor-based device is disclosed. In some aspects, a GPU based on a slicing GPU architecture includes a plurality of hardware slices. The GPU also includes command processor (CP) circuitry and a non-slice primitive controller (PCUS). Upon receiving a graphics instruction from a central processing unit (CPU), the CP circuitry determines a graphics workload and sends the graphics workload to the PCUS. The PCUS then divides the graphics workload into a plurality of sub-batches, and distributes each sub-batch to the PCS of the hardware slice for processing.

The invention discloses a method and a system for solving compilation errors in intelligent contract version evolution. The method comprises the following steps: collecting and cataloguing major changes of all records based on an official Solidity website, screening to obtain major changes causing a compiling problem, and constructing a knowledge base of version migration; combining codes with compiling problems and compiling error information of the codes; slicing the smart contract code by using a static analysis tool, and retrieving a version migration knowledge base by using a retriever based on compiling error information to obtain related version migration knowledge; and guiding the large language model to generate a high-quality patch in combination with a result obtained by the analysis. According to the method, a static analysis tool, structured retrieval of expert knowledge and the generation capacity of a large language model are organically combined, the problem of compiling errors caused by Solidity language evolution is systematically solved, and developers can be effectively assisted in coping with version migration and code repair tasks.

The invention relates to a hybrid model-driven reentrant vulnerability maintenance method and device and computer equipment, and the method comprises the steps: obtaining a slice set of a target function corresponding to a preset character in a to-be-repaired code, the preset character being associated with a to-be-repaired vulnerability of the code; performing classification training on the features of the slice set to obtain code snippets containing the to-be-repaired vulnerabilities; calculating the attention score of each code line in the code snippets, and selecting a specified number of target code lines with high attention scores from the code lines according to the sorting of the attention scores; and obtaining a repair template of the pre-trained large language model according to the target code line, inputting the to-be-repaired code to the large language model, and outputting the repaired code. By adopting the method, the bug repairing accuracy in the code can be improved.

The invention provides a meteorological data rendering method and system, a storage medium and electronic equipment. The method comprises the following steps: storing collected meteorological data through an Elasticsearch database; performing conversion processing on the meteorological data based on wind field UV data and a preset threshold value to obtain conversion data; performing slicing processing on the conversion data to generate grey-scale map slices; and rendering the grey-scale map slices in a WebGL mode of a browser to realize animation display of the meteorological data. According to the method, rendering is quicker, rendering bottleneck does not exist, gpu-based data real-time interpolation is easier to realize, and the data is smoother in a time sequence animation instead of a carousel graph form. Therefore, the data granularity can be reduced, the query and return of redundant data can be reduced, the data processing efficiency can be improved, and the technical problems of lagging and delay during dynamic rendering display of the meteorological data can be effectively solved.

The invention relates to the field of concrete 3D printing, and discloses a path optimization method for concrete 3D printing, which comprises the following steps: firstly, slicing a three-dimensional model of a to-be-printed concrete member, converting the sliced model into a geometric model, and initializing position information of geometric points in the geometric model; according to a graph theory principle, dividing the geometric model into a plurality of areas which can be printed at one time; the method comprises the following steps: constructing slices of a printing model into geometric figures which can be identified by a computer, extracting and numbering vertexes of the geometric figures, respectively recording coordinates of the vertexes, setting an adjacent matrix to describe a connection condition between the vertexes, then storing the vertexes into a partition matrix according to a rule, the partitions can be traversed at a time; finding out a shortest printing path in the plurality of divided areas by using an ant colony algorithm; and the printing platform is controlled to move according to the planned optimal printing path.

The invention relates to the field of computers, and discloses a data slicing method, system and device and a storage medium. The method comprises the following steps: receiving a knowledge operation instruction uploaded by a user; creating knowledge entries through the selected knowledge parser according to the uploaded file, and generating corresponding knowledge identifiers for the knowledge entries; receiving a knowledge slicing instruction sent by a user; according to the specified knowledge identifier and the type of the uploaded file, slicing the content of the uploaded file through the selected knowledge slicing strategy to obtain a plurality of knowledge fragments; and respectively inserting the plurality of knowledge fragments into different types of databases to finish classification. In the embodiment of the invention, intelligent segmentation can be carried out on a large batch of data, and management of the large batch of data is completed, so that the AI large language model and the reference data of multi-modal pre-training are provided, and the training efficiency and effect of the AI large model are improved.

The invention discloses an XR-based immersive three-dimensional modeling and straight-through 3D printing system and method, and the method comprises the steps: S1, collecting user input, and converting the user input into an interaction instruction; s2, generating three-dimensional model data; s3, superposing the three-dimensional model into a real physical environment according to a proportion of 1: 1, and outputting a virtual-real fusion display result; s4, performing printability analysis on the model, marking a problem area, guiding a user to modify and providing an automatic repair suggestion; s5, generating a support structure, and providing visual preview and interactive editing; s6, slicing and path planning are executed, and a printing instruction file meeting the control requirement of the 3D printer is generated; s7, communication connection with the 3D printer is established, and printing state information is fed back; and S8, providing storage and calling support of the three-dimensional model file, parameter configuration and environment map data. According to the invention, seamless integration of immersive XR modeling, MR real-time verification and one-key direct-through 3D printing is realized.

The invention discloses a selective laser melting method and system, and relates to the technical field of additive manufacturing. The selective laser melting method comprises the following steps that a part model created by 3D software is obtained, and whether a rib beam and / or a supporting piece are / is machined or not is judged based on the part model; the slicing software obtains the part model, divides the part model into two-dimensional layers and selects different scanning strategies; the temperature control module preheats the substrate to a set temperature; and based on the selected scanning strategy, laser is used for melting powder layer by layer till part machining is completed. The dimensional stability of the component is improved by selecting different scanning strategies, the rib beam is machined to reduce the deformation risk so as to enhance the mechanical property, and the supporting piece is machined to improve the stability of the printing process.

The invention relates to the field of BIM model visualization, in particular to a BIM design terrain and GIS live-action texture fusion method, BIM design terrain and GIS live-action texture data are processed respectively, when GIS live-action texture data changes, data updating can be achieved only by replacing slice data, and the convenience of data updating is improved; according to the method, the relation between the image slice nodes of the GIS live-action texture data and the space coordinates of the BIM design terrain is established through the coordinate system transformation matrix, so that coordinate transformation between the image slice nodes and the space coordinates of the BIM design terrain is facilitated, the space coordinates of the BIM design terrain correspond to the texture coordinates of the GIS live-action texture data, and finally fusion of the BIM design terrain and the GIS live-action texture data is realized.