47 results about "Mapping techniques" patented technology

The invention discloses a soil type prediction model training method, drawing method and system based on multi-modal feature fusion and spatial neighborhood constraint, and the training method comprises the steps: constructing a multi-source heterogeneous digital soil drawing data sample set which comprises a continuous environment variable, a discrete environment variable and a multi-source remote sensing image; extracting the characteristic quantity of the data sample set and carrying out multi-modal adaptive characteristic fusion, and adaptively determining a fusion weight by using a cross attention mechanism to obtain a joint characteristic quantity; constructing a composite loss function including a spatial neighborhood smooth regular term and classification cross entropy loss; and performing joint optimization training on a preset deep learning model according to the joint characteristic quantity and the composite loss function until a preset requirement is met, and determining a soil type prediction model. According to the embodiment of the invention, the accuracy and spatial continuity of the mapping result expression output by the model and the generalization performance of the model can be effectively improved, and the method can be widely applied to the technical field of digital soil mapping.

The invention discloses an automatic administrative boundary fusion charting method and a meteorological charting method based on a python language. Belongs to the technical field of meteorological charting, and particularly relates to the cross technical field of meteorological data processing and geographic information system visualization. The method starts with the construction of a multi-scale adaptive boundary fusion map, so as to solve the problems of cross-scale (such as province-to-village) precision faults and large interpolation errors of complex terrains, and achieve a cross-level administrative division boundary seamless aggregation technology (village level-town level-county level-province level). Therefore, the problem that precision is easy to lose when cross-scale conversion (such as from province to village) is carried out during meteorological mapping is solved.

The invention relates to the technical field of engineering drawing, and particularly discloses an engineering drawing generation method and device based on BIM and CAD fusion, equipment and a medium, and the method comprises the steps of multi-source data preprocessing, semantic annotation enhancement, knowledge graph construction, intelligent component matching, real-time synchronization and conflict detection, and dynamic optimization and model output. According to the method, by introducing natural language processing and the graph neural network, character annotations and symbol marks scattered in the CAD drawing can be automatically recognized and understood, and the character annotations and symbol marks are efficiently mapped into attribute parameters of the BIM model. Compared with a traditional mode depending on manpower or template rules, the technology breaks through dependence on standardized annotation, and integrated semantic extraction of fuzzy description and diversified symbols is achieved; cAD geometry, design documents, GIS geographic information and IoT sensor real-time data are subjected to deep alignment and fusion on a semantic level by utilizing technologies such as comparative learning, self-supervised pre-training and knowledge graph construction, and an enhanced BIM model with space-time relevance is generated.

Techniques are provided for performing a resync transfer to recover from a storage site failure. During normal operation of a first site hosting a first volume, data is replicated to a second volume hosted by a second site. If the first site fails, when clients are redirected to the second volume at the second site. When the first site recovers, data modifications made to the second volume are resynced back to the first volume. As part of synchronizing the first volume, a data warehouse is rebuilt at the first site in order to track the location of blocks present on the replication destination. Typically, the data modifications are transferred after the data warehouse is rebuilt, which results in significantly long resync times. The techniques provided herein decrease the resync time by either rebuilding the data warehouse in parallel with resyncing the data modifications or circumvent the need for rebuild.

Systems and methods of configuring a fixed memory array of an integrated circuit with coefficients of one or more applications includes identifying a utilization constraint type of the fixed memory array from a plurality of distinct utilization constraint types based on computing attributes of the one or more applications; identifying at least one coefficient mapping technique from a plurality of distinct coefficient mapping techniques that addresses the utilization constraint type; configuring the fixed memory array according to the at least one coefficient mapping technique, wherein configuring the array includes at least setting within the array the coefficients of the one or more applications in an arrangement prescribed by the at least one coefficient mapping technique that optimizes a computational utilization of the fixed memory array.

The application relates to the technical field of remote sensing mapping, in particular to a remote sensing mapping method for a karst rocky desertification treatment grassland, which comprises the following steps: obtaining remote sensing images and DEM data of a target karst region; quantifying the shadow shielding possibility, vegetation confidence and vegetation density of a pixel based on the radiation brightness, spectral reflectance change trend of the remote sensing images and DEM topographic features, and then adaptively constructing an adjustment factor for correcting a soil-adjusted vegetation index; and calculating the soil-adjusted vegetation index at each pixel according to the adjustment factor, so as to draw a remote sensing vegetation map of the target karst region. The adjustment factor is adaptively determined by constructing a shadow vegetation characteristic value, the problem that the existing technology cannot distinguish between dense shadow vegetation and bright sparse vegetation under the complex karst topography due to the use of a unified adjustment factor is solved, and the precision and reliability of vegetation mapping in a karst rocky desertification treatment area are improved.

The invention belongs to the technical field of digital soil mapping, and particularly relates to a soil barrier layer distribution diagram, a mapping method thereof and computer equipment. According to the method, the soil barrier layer is drawn through the historical remaining soil data in combination with the expert knowledge base, any field investigation work does not need to be carried out, and the investment of manpower and material resources is reduced. Compared with a traditional method, the cost is greatly reduced, and the efficiency is also improved due to the fact that field sampling is not needed. The technical problem that in the prior art, a soil drawing method is high in cost and low in efficiency is solved.

Techniques for efficiently managing and rendering graphical primitives in three-dimensional (3D) objects are disclosed. A surface of a 3D object is partitioned into a plurality of clusters, each containing a quantity of graphical primitives. Each cluster is mapped to a respective virtual space, which is then hierarchically partitioned into multiple regions. Partition information for the respective virtual space is encoded based on the hierarchical partitioning, and the surface of the 3D object is rendered for display based on the encoded partition information.

The invention relates to the technical field of soil attribute mapping, in particular to a soil mapping method, system and program combining a convolutional neural network and a structural equation model. According to the method, a causal relationship network between soil attributes and environmental factors is established through a structure equation model, and the causal relationship network is converted into a CNN network topology for guiding neural network structure design and parameter training. By introducing the latent variable constraint and the joint loss function, the prediction precision, the physical consistency and the interpretability of the model are improved. Experimental results show that the method has higher precision and generalization ability in soil attribute space prediction, and is significantly superior to an existing single data driven model.

Disclosed herein are methods, systems, and components for the design of a flat belt based block and tackle design that is theoretically free of fleet angles. A mapping technique forms a set of planar positions for the centerlines of the free spans that provides a plurality of sheave geometries, which reside on a common axis and spans that are free of fleet angles at the sheave engagement interfaces. This permits the use of high-performing flat belts in high-reduction block and tackle topologies, with the principal benefits of an extended service life, high power transmission efficiency, more effective traction power transfer, and a compact machine design.

The application provides a bridge structure parameterized modeling and drawing method, constructs a bridge general element library with unique topological coding, takes the unique topological coding in the bridge general element library as an associated index, establishes a bidirectional mapping rule of design parameters, element models and drawing elements, generates a bridge three-dimensional model and a corresponding initial drawing framework after inputting design parameters based on the bidirectional mapping rule through parameterized modeling and engineering drawing technology, identifies component priority based on the unique topological coding, constructs a multi-constraint global optimization target, obtains a globally optimal labeling layout scheme through improved genetic algorithm iteration, completes intelligent labeling of the initial drawing, and generates a construction drawing. The application realizes intelligent labeling and synchronous compliance verification of the bridge construction drawing through the unique topological coding of the bridge element and the multi-constraint global optimization solution of the improved genetic algorithm.

Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.

The invention relates to the technical field of computer graphic processing and geology drawing making technologies, and discloses a lithologic symbol splicing method. The method comprises the steps of obtaining lithology naming data and industry template rules, and generating a splicing priority sequence through standardization processing and analysis binding; carrying out basic symbol selection and parameter instantiation based on the sequence to form an assembly candidate set; generating a pose solution set and a conflict list through adsorption matching, topological constraint solution and conflict detection; performing rule checking and conflict resolution to obtain a compliant splicing format and a quality mark; performing dependency analysis and increment regeneration on the compliant splicing format to obtain a regeneration result packet; and finally generating an export result package through pattern matching, parameter synthesis and cross-platform adaptation construction. According to the method, automation, standardization and cross-platform compatibility of lithologic symbol generation are realized, and the efficiency and consistency of geological map manufacturing are remarkably improved.

The present application relates to the technical field of cartography, and particularly relates to a cartography method, a cartography system and a storage medium. The method sets a user terminal, a map tool service subsystem, a map pipeline subsystem and a task running service subsystem, the user terminal loads a corresponding user interface, determines a cartography pipeline request in response to an operation on the user interface, and sends a sub-map tool service subsystem; the map tool service subsystem obtains corresponding map data from a map pipeline database according to the cartography pipeline request, and sends the map data to a map pipeline service subsystem; the map pipeline service subsystem performs cartography operation according to the map data, generates a complete version of a map and a cartography task request, and sends the cartography task request to a task running service subsystem; the task running service subsystem starts a cartography process according to the cartography task request, and performs map production, publication and release on the complete version of the map. The method realizes automatic operation of cartography, and improves the efficiency of cartography.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a transmitter may obtain a sequence of information bits. The transmitter may generate, using at least a probabilistic amplitude shaping (PAS) technique, a set of symbols from the sequence of information bits, wherein the generation of the set of symbols using at least the PAS technique includes using at least one of a sign-bit-shaping technique or a selective-mapping technique. The transmitter may transmit, to a receiver, the set of symbols. Numerous other aspects are described.

This invention proposes a planar parameterization method applicable to complex geometric regions and possessing G1 smoothness properties. The technique first generates the meshed structure of a given region based on its central axis information; then, by applying G1 continuity constraints to adjacent patches, it constructs an initial parameterization that satisfies G1 continuity overall; finally, it uses quasi-conformal mapping techniques to further optimize the parameterization quality of each patch. This invention simultaneously uses rectangular and triangular Bezier patches to represent the geometric region, making it effective for arbitrarily topologically complex domains. Compared with other existing methods, it not only enhances design flexibility but also achieves significant improvements in the generation and parameterization quality of multi-patch structures, resulting in greater efficiency.

The present application discloses a method for constructing a decentralized Rollup sequencer, which relates to the field of Rollup sequencer construction. The method includes deploying multiple smart contracts at the L1 layer of the decentralized Rollup sequencer; at the L2 layer, using an improved WRR algorithm, combining with the trusted random numbers generated at the L1 layer, and adopting a linear mapping technique to screen multiple submitters, who respectively package and sort the transactions at the L2 layer to determine the transaction blocks, and the final submitter is selected through a competition process; submitting the transaction blocks generated by the final submitter to the remaining submitters for voting review, and multiple candidates monitor the operations of all submitters; when it is found that the transaction blocks submitted by the final submitter to the L2 layer are illegal, the suspicious label mechanism is used to label the illegal transaction blocks, and the transactions with suspicious labels are rolled back to the L1 layer for review, and the candidates initiate challenges to the final submitter through the challenge mechanism to improve the overall decentralization degree of the system.

The invention provides a mapping method of a geochemical map of rock exposed out of earth crust, and belongs to the technical field of geochemical mapping of rock. The method comprises the steps of constructing a multi-source database, carrying out step-by-step attribute matching, calculating a weighted average value of geological unit element contents, and generating a geochemical map. According to the method, a multi-source data fusion technology and a step-by-step attribute matching algorithm are utilized to combine relatively low-density rock data with a geological unit structure and geological unit space distribution, a rock geochemical map is finally generated by relying on a GIS technology, the step-by-step matching method follows an objective rule of rock element distribution, and compared with simple matching, the step-by-step matching method has the advantages that the matching efficiency is greatly improved; the assignment precision can be improved, and the existing rock chemical data can be utilized to the maximum extent; public geological map data are compatible, and the data collection cost is reduced; the requirement for the number of samples is greatly reduced, at least dozens of rock sample data are needed, and the drawing is more accurate along with the increase of the types and the number of the samples.

The present invention relates to the technical field of soil property mapping, and in particular to a soil mapping method, system and program that combine a convolutional neural network and a structural equation model. This method establishes a causal relationship network between soil properties and environmental factors through a structural equation model, and transforms this causal structure into the network topology of a CNN to guide the design of the neural network structure and parameter training. By introducing latent variable constraints and a joint loss function, the prediction accuracy, physical consistency and interpretability of the model are improved. Experimental results show that this method has higher accuracy and generalization ability in soil property spatial prediction, significantly superior to existing single data-driven models.

There is provided a system and method for a backend package to facilitate global connectivity and seamless integration through standardized API interactions. A managed user authentication across all provider interactions allows for construction of custom user interfaces using parject JSONs, integrated with a no-code platform, specifically within its UI flow engine. This integration enhances the relationship between UI elements and the backend side using mapping techniques, allowing for designing and creating interactive and dynamic web applications. Specialized microservices are included in the system and methods.

Methods, systems, and devices for validity mapping techniques are described. A memory device may use a change log to update a mapping that indicates whether data stored at respective physical addresses is valid. For example, the memory device may receive a command associated with data having a corresponding set of addresses (whether logical block addresses or physical addresses). The memory device may set an entry of the change log based on whether the set of addresses are consecutive. For example, the memory device may identify whether the set of addresses are consecutive and may set a flag in the entry of the change log to indicate whether the addresses are consecutive. Then, the memory device may update one or more entries of the mapping corresponding to the entry of the change log to indicate whether the addresses corresponding to the one or more entries of the mapping store valid data.

Techniques are described for a computing system to maintain security by (a) detecting updates from a plurality of interrelated systems; (b) determining a risk account having an inappropriate access level with reference to the detected update and mapping set; and (c) in response to determining the risk account, providing an alert of the risk account to the entity authorized to change or remove the risk account. Systems, apparatuses, and computer program products for performing the methods and similar methods are also described.

The application discloses a soil type prediction model training method, mapping method and system based on multi-modal feature fusion and spatial neighborhood constraint, and the training method comprises the following steps: constructing a multi-source heterogeneous digital soil mapping data sample set, wherein the data sample set comprises continuous environmental variables, discrete environmental variables and multi-source remote sensing images; extracting feature quantities of the data sample set and performing multi-modal adaptive feature fusion, adaptively determining fusion weights by using a cross attention mechanism, and obtaining joint feature quantities; constructing a composite loss function comprising a spatial neighborhood smoothing regularization term and a classification cross-entropy loss; and performing joint optimization training on a preset deep learning model according to the joint feature quantities and the composite loss function until a preset requirement is met, so as to determine a soil type prediction model. According to the embodiment of the application, the accuracy and spatial continuity of the mapping results output by the model and the generalization performance of the model can be effectively improved, and the application can be widely applied to the technical field of digital soil mapping.

The application discloses a terminal security evaluation method and system based on a nonlinear mapping technology, equipment and a medium, mainly relates to the technical field of terminal security evaluation, and is used to solve the problems that the existing scheme has single risk evaluation mode, is easy to cause secondary disclosure risk, and the risk response mechanism is lagging behind. Including: obtaining real-time data of terminal preset risk dimension, determining whether the real-time data meets the preset risk trigger condition; when the preset risk trigger condition is met, the risk scoring mode is entered: obtaining the nonlinear calculation formula corresponding to the specific preset risk trigger condition triggered, extracting the corresponding real-time data, and then obtaining the triggered risk score by using the nonlinear calculation formula; when the risk scoring mode is not entered, the comprehensive risk score is obtained by weighting according to the real-time data of the preset risk dimension; according to the falling interval of the triggered risk score or the comprehensive risk score, the security risk level of the current terminal is determined.

Techniques are provided for increasing the accuracy of automated classifications produced by a machine learning engine. Specifically, the classification produced by a machine learning engine for one photo-realistic image is adjusted based on the classifications produced by the machine learning engine for other photo-realistic images that correspond to the same portion of a 3D model that has been generated based on the photo-realistic images. Techniques are also provided for using the classifications of the photo-realistic images that were used to create a 3D model to automatically classify portions of the 3D model. The classifications assigned to the various portions of the 3D model in this manner may also be used as a factor for automatically segmenting the 3D model.

This invention relates to the fields of computer graphics and image processing technology, specifically to a 3D reconstruction system and method for a 3D unfolded image. The system includes a topological feature extraction module, a folding axis positioning module, a coordinate mapping module, a mesh generation module, an error warning module, and a 3D rendering module. First, it acquires images of the folded paper image and the target unfolded image, extracts topologically invariant feature points, and determines the position parameters of the folding axis in 3D space based on the feature point matching results. It then establishes a mapping relationship from 2D coordinates to 3D coordinates, constructs a triangular mesh, and detects fold lines. The mesh is classified, and the relationship between the normal vector and the center point is analyzed to identify erroneous folding regions. Finally, it generates a 3D model visualization result. Topologically invariant feature extraction and manifold mapping techniques are used to improve the accuracy of feature matching. Lie group transformation theory is introduced to construct an accurate coordinate mapping relationship, and an error warning mechanism based on nonlinear dynamic system theory is developed, effectively improving reconstruction accuracy and efficiency.

The present disclosure describes a method (300) and a device (106) for predicting fault conditions in vehicles using field complaint data. The method (300) comprises processing (302) field complaint data collected from a plurality of vehicles to generate a processable data set comprising a plurality of rows and a plurality of columns. The method (300) further comprises determining (304) a match factor for two or more columns of the processable data set after determining a mapping between the two or more columns. The mapping is determined based on at least one unconditional mapping technique, one conditional mapping technique, or both.The method (300) further comprises generating (306) an attribute cluster corresponding to the two or more columns if the match factor for the two or more columns satisfies a predetermined criterion, and generating (308) a predictive message to correct the fault condition in at least one vehicle.

The invention relates to the technical field of automatic drawing, in particular to an online automatic thematic map drawing method and system based on artificial intelligence. The method comprises the following steps: synchronously collecting multi-modal input parameters of a user, carrying out time sequence alignment, respectively extracting geometric features and semantic features, and fusing through a self-adaptive confidence mechanism to generate a unified semantic geometric vector; through two-channel parallel analysis of semantic projection and geometric projection, candidate charting schemes of a concept layer and a graph layer are generated respectively, and semantic consistency and space consistency calibration and fusion are carried out on candidates; carrying out local geometric optimization, semantic adjustment and global layout optimization on the candidate set, introducing micro-variation to generate diversity, and outputting a graph which can be directly rendered online through feature weighted fusion and global consistency optimization; a self-learning knowledge base is constructed by collecting historical samples, and continuous accumulation and personalized output optimization of drawing experience are completed. According to the invention, a complete intelligent closed loop from multi-modal input to automatic mapping is realized.

The invention provides a special graph patterning method and device, electronic equipment and a medium, and relates to the technical field of surveying and mapping. The method comprises the following steps: performing shape decomposition on a preset special graph to obtain a shape decomposition file of the preset special graph; the shape decomposition file at least comprises a main body shape and attribute information; the preset special graph is a graph without a corresponding graphical file in a corresponding graphical file library in a preset database; the main body shape is the shape of an existing graphical file in a graphical file library; according to the main body shape, constructing a standard graphical file corresponding to the preset special graph; transmitting the attribute information of the main body shape to each part of a standard graphical file, so that a main body part and a non-main body part in the standard graphical file have the attribute information; and storing the standard graphical file into a corresponding graphical file library in a preset database. According to the method, accurate graphical expression is carried out on the special graph, and linkage updating of the graph and the attribute is ensured.