76 results about "Graph generator" patented technology

The present invention relates to a computer-based system for identifying supply chain risks and generating supply chain graphs representing an interconnected network of entities. An industrial graph database application is configured to account for direct and indirect (transitive) supplier risk and importance, based on a weighted set of measures: criticality, replaceability, centrality and distance. A graph-based model serves as an interactive and visual supply chain risk and importance explorer. A supply network is induced from textual data by applying text mining techniques to news stories and used to populate the supply chain / graph database.

A method and a system generate a reputation value for a user in a network-based community. A processor-implemented transaction data collector module collects transaction data of users of a network-based community. A processor-implemented transaction graph generator module generates a transaction graph based on the collected transaction data. The transaction graph has a transaction relationship between two users, and a weight corresponding to the transaction relationship. The weight is representative of a mutually reinforcing relationship between two users. A processor-implemented reputation generator module generates a reputation value for a user from the transaction graph.

An attribute collector may collect an attribute set for each test entity of a plurality of test entities associated with a software test executed in a software environment. An attribute analysis signal handler may receive an attribute analysis signal associated with a change in the software environment, and a view generator may provide an attribute-based view associated with an affected attribute set associated with the change, the attribute-based view identifying an affected test entity that is affected by the change.

The invention provides a combined anti-counterfeit label which comprises a two-dimensional code, a blank area and a dot matrix graph, wherein the two-dimensional code, the blank area and the dot matrix graph are arranged on the same plane. A method for generating the combined anti-counterfeit label comprises the steps of obtaining a two-dimensional code pattern converted from plaintext information and ciphertext information via a two-dimensional code generator, generating a dot matrix graph pattern with the area not greater than that of the blank area via a dot matrix graph generator, and superimposing the dot matrix graph pattern on the blank area in the two-dimensional code pattern, wherein the dot matrix graph is to be implanted into the blank area of the two-dimensional code pattern. A device for generating the combined anti-counterfeit label comprises the two-dimensional code generator, a dot matrix graph ID (identification) database, the dot matrix graph pattern generator and a merging device. The label is formed by combining the two-dimensional code and the dot matrix graph; even if the label is imitated by a counterfeiter, information bound with the anti-counterfeit label cannot be acquired, and the anti-counterfeit label has high-grade anti-counterfeiting performance.

An interactive diagnostic schematic generator illustrates diagnostic test procedures for diagnosing failure modes of a vehicle. The schematic generator reads a schematic data file such as a wiring diagram from a computer memory, indicates a test subject in the schematic or illustrates a location where test equipment is to be connected, and formats the schematic for display on a display device. The schematic generator also receives feedback from a vehicle onboard computer, test equipment or user input indicating that the action has been performed, and removes the indication of the test subject in the schematic. The schematic generator further marks the test subject to indicate that the action has been performed with a marking style that is visually distinct from the indicating style, optionally indicating that the result has validated or invalidated the test subject.

The invention provides a combined-type anti-counterfeiting mark based on a same ID. The combined-type anti-counterfeiting mark is composed of a quick response code and a raster graph. The quick response code and the raster graph all comprise the same ID number extracted from an ID number database during a generating process. The method for generating the combined-type anti-counterfeiting mark comprises the steps that by using a quick response code generator, the ID number, parameter information of the quick response code, plaintext information and preset ciphertext information memory area are converted into the quick response code, wherein the ID number, the parameter information of the quick response code and the plaintext information are extracted from the ID number database; by using a raster graph generator, the raster graph is generated by the ID number which is same as the quick response code. The device for generating the combined-type anti-counterfeiting mark comprises the quick response code generator and the raster graph pattern generator. The quick response code and the raster graph comprise the same ID number, and therefore the quick response code and the raster graph have relevancy, due to the fact that quick response code can only be recognized and read through dedicated equipment, the raster graph cannot be recognized once again after being copied and scanned, and therefore the high level anti-counterfeiting performance is achieved.

A method and apparatus for analyzing a joint. The apparatus comprises a graph generator and a model generator. The graph generator forms a first graph based on a plurality of points within a region. The plurality of points represent a plurality of locations relative to a structure for a plurality of fastener devices configured to be installed in the structure to form a joint. The graph generator is configured to identify primary points and secondary points based on the first graph. The graph generator is further configured to form a second graph using the primary points, the secondary points, and the first graph. The model generator is configured to generate a two-dimensional model comprised of triangular sectors using vertices of the second graph. The two-dimensional model is configured for use in forming a mesh for use in performing finite element analysis for the joint.

A method of generating bitmaps of a three-dimensional model, and a device and a system for performing the method are disclosed. The bitmap generator includes a model divider configured to divide the three-dimensional model into a plurality of sub models, wherein the three-dimensional model is divided in a direction parallel with an output direction of a three-dimensional printer, a plurality of sub bitmap generators each configured to generate a sub bitmap for a plane perpendicular to the output direction for the plurality of sub models, an operation distributer configured to transfer and distribute the plurality of sub models to the plurality of sub bitmap generators so that an operation of generating the sub bitmaps are processed in parallel, and a bitmap adder configured to merge the sub bitmaps whose coordinates of the output direction are the same among the generated plurality of sub bitmaps.

A system for management and tracking of collaborative projects is provided, comprising a logging service configured to track contributions of a plurality of participants of a monitored project, and log the contributions in a graph and timeseries-based contributions dataset; a knowledge graph generator configured to generate a graph and timeseries-based knowledge graph from gathered information from a plurality of sources; an automated planning service configured to determine an associated value of the monitored project; and a remuneration service to analyze the contributions dataset to determine appropriate apportionment of remuneration.

The invention provides a two-dimensional splicing treatment method for an inclined scanning type photoetching machine during stepping type exposure. The two-dimensional splicing treatment method comprises the following steps: calculating a unit bitmap size of a graph to be exposed, which is split for each time; splitting the graph to be exposed into a plurality of unit bitmaps and filling a black graph into an insufficient part; rotating the unit bitmap and extending the unit bitmap to the size of a view field of a graph generator; and moving a precision movement platform and gradually finishing exposure. With the adoption of the two-dimensional splicing treatment method, the problem that the inclined scanning type photoetching machine cannot normally splice at the spliced part in the stepping type exposure process is solved; when the exposed graph is split, conversion treatment is carried out on the exposed graph according to a fixed included angle between the graph generator and the precision movement platform; and by controlling the precision movement platform, all the unit bitmaps are combined to one complete exposed graph, and all the splicing positions of the finally-etched graph have the good splicing effect, so that the quality of the stepping type exposure of the inclined scanning type photoetching machine is improved.

The present invention provides a method for marking animal or plant living body crust under the condition of no damaging living body and its equipment for using said method. The described equipment to formed from laser generator, light-conducting arm, X and Y vibrating mirror, graph generator, F theta lens and light-conducting cylinder. The laser beam produced by laser generator is reflected or refracted by means of one group of lens and focussed on the living body material on the working table under the control of graph generator and a certain pattern is formed on it. Said method is simple and easy to implement, and the mark formed by said method is not easy to be fallen off when it is worked at high temp. or soaked in water.

Branch sequences for branch prediction performance test are generated by performing the following steps: (i) generating a branch node graph, by a branch node graph generator machine logic set, based, at least in part, upon a set of branch traces of a workload or benchmark code; (ii) generating a first assembly pattern file, for use with a first instruction set architecture (ISA) / microarchitecture set, by an assembly pattern generator machine logic set, based, at least in part, upon the branch node graph so as to mimic the control-flow pattern of the workload or benchmark code; and (iii) running the assembly pattern file on the first ISA / microarchitecture set to obtain first execution results.

A spherical lithography system with area differentiation comprises a light source, an illumination system, a mask graph generator, a computer control system, a projection imaging system and an object table. The light source provides illumination light which illuminates the mask graph generator after being parallel uniformized by the illumination system; the computer control system controls the mask graph generator to provide mask graphs, and subdivides an exposure field into a plurality of units according to the curvature of a sample and the focus depth of the projection imaging system, so that the mask graph generator does not defocus on a single-binning imaging; the projection imaging system develops the mask graphs provided by the mask graph generator onto the sample mounted on the object table; and the computer control system identifies the swing length and the bidimensional movement of the object table according to the curvature of the spherical sample, and differentiates the area of the plane mask, thereby realizing the surface splicing lithography on the samples with different curvatures. The invention has great flexibility and maneuverability in the projection exposure lithography of the spherical samples, and has indigenous advantage in the exposure lithography of the spherical samples with different curvature radiuses.

A support apparatus of an injection-molding machine has a neural network that receives test molding data corresponding to molding conditions and a quality value obtained by measuring a non-defective molded article, and that determines a quality prediction function based on the received test molding data. A computer calculates a predicted value of the quality value using the quality prediction function. An input apparatus inputs into the neural network fixed values for the molding conditions except for a selected at least one of the molding conditions, and inputs a target value of the quality value. A graph generator generates a graphical relationship between the selected at least one molding condition and the predicted value. A graph correction unit corrects the graphical relationship generated by the graph generator on the basis of the target value. A display unit selectively displays the graphical relationship generated by the graph generator and the graphical relationship corrected by the graph correction unit.

A system for measuring performance of an enterprise architecture includes an enterprise collaborative recommender engine that provides recommendations for an account within the enterprise architecture based upon enterprise assessments; a health control process engine that triggers rebuilding of the heat map topology view that provides recommendations for updating the enterprise architecture towards increased maturity in response to recommendations from the enterprise collaborative recommender engine; and an enterprise heat map generator that presents a heat map providing maturity information of the enterprise architecture for each domain.

An edge routing system is described herein that uses a spatial decomposition to achieve faster routing, and more quickly generates a sparse visibility graph using a cone spanner. The system provides two approaches that can be used separately or in combination to achieve faster-and hence more scalable and more interactive-edge routing using approximate shortest paths. The first approach uses a spatial decomposition of the nodes in a graph, moving them slightly to obtain strictly disjoint convex hulls around groups of nodes, and then computing visibility graphs over these composite hulls rather than individual nodes. The second approach generates a sparse visibility-graph spanner to accelerate the process of producing the visibility graph. The system allows high quality obstacle avoiding edge routing for large diagrams in interactive diagramming applications where very fast refreshes of routing are used with many nodes moving at the same time.

The invention provides an online diagnosis method and system for the internal insulation performance of a capacitor voltage transformer, and the method comprises the steps: building a source domain data set and a target domain data set of a CVT diagnosis model, and determining the personalized features and common features in CVT data; according to a CVT internal insulation performance degradation mechanism, extracting related parameters of the internal insulation fault CVT as common characteristics; estimating a common feature distribution model through a Dirichlet process Gaussian mixture model; constructing an internal insulation fault virtual CVT generation model to generate an internal insulation fault virtual CVT sample; based on the number of normal-state CVT samples and the number of virtual CVT samples in a graph generator balance target domain, nodes on a balance network are distinguished through a training graph convolutional network recognizer, and a fault diagnosis model is obtained; and performing internal insulation fault diagnosis on the to-be-tested CVT sample through the fault diagnosis model. Through the scheme, the sample data demand can be reduced, the fault diagnosis model is constructed based on the generated virtual sample, and the recognition accuracy of the fault diagnosis model can be effectively guaranteed.

Provided in the invention is a multiplying power calibration method of a zooming objective lens of a write-through photoetching machine. The multiplying power calibration method comprises: multiplying powers of a marking graph formed on a substrate along an X shaft direction and Y shaft direction of a precision motion platform at a CCD observation light path from a zooming objective lens to a CCD are calculated respectively; and multiplying powers of a graph generator along the X shaft direction and Y shaft direction of the precision motion platform at the light path from the zooming objective lens to the substrate and then from the substrate to the CCD through the zooming objective lens are respectively calculated. With the method, a multiplying power calibration problem of the write-through photoetching machine between the graph generator and the precision motion platform projection light path can be solved; and on the basis of the specific optical structure, an actual zooming multiplying power can be obtained according to a specific location relation of the CCD camera, the graph generator, and the precision motion platform. The method is easy to realize; and the calibration precision is high.

The invention relates to the technical field of video test, and particularly relates to a video frame rate test method. The video frame rate test method can be used in whole process image signal test of a digital end-to-end device, and the digital end-to-end device comprises a graph generator provided with an LED lamp array; a plurality of LED lamps on the LED lamp array along a preset direction are selected to serve as a test lamp group, the test lamp group comprises a plurality of light emitting units, and each light emitting unit comprises a plurality of adjacent LED lamps; each light emitting unit is turned on in sequence, and the lighting frequency of the light emitting units is gradually increased; and an image displayed by the test lamp group is obtained by an image capturer in real time, and when the obtained image of the light emitting unit is static, the lighting frequency value on the graph generator at the moment is used as the value of the video frame rate of the digital end-to-end device, and then the whole process image signal test is completed. Since the video frame rate test method in the technical scheme is simple, easy to implement and is relatively high in test efficiency and reliability, the whole process image signal test can be completed quickly.

The invention provides a large-scale array fast adaptive anti-interference method based on a convolutional neural network, mainly solving the problems of large calculation amount and poor beam conformality in large-scale phased array adaptive beam forming in the prior art. The method in the implementation scheme comprises the following steps of constructing a phased array radar receiving signal model, a training sample set and a test sample set, establishing an array element weight prediction sub-network W to generate an array element weight, generating a directional diagram Q by using a directional diagram generator P according to the array element weight, and cascading W and P to form a directional diagram zeroing conformal network H, setting a directional diagram zeroing conformal network loss function L composed of a zeroing loss function L1 and a conformal loss function L2, training H by using the training sample set and adopting a gradient descent method, and inputting the test sample set into the trained weight prediction network to obtain a large-scale array anti-interference result. Due to the fact that the influence of interference null on the directional diagram is avoided, the calculation amount of the self-adaptive anti-interference algorithm is reduced, and the method can be used for target detection.

A system and method for rapid workflow design utilizing machine learning includes a scanner, a convolutional neural network, a converter, a graph generator, and a controller. The scanner may convert a paper copy of a process flow into a pixelated image. The convolutional neural network is configured to segment the pixelated image into objects including at least one of an action, a decision, a connector, or a combination thereof. The converter is configured to transform the objects into a connectivity matrix. The graph generator is configured to transform the connectivity matrix into a rectilinear graph. The controller is configured to identify automated actions, semi-automatic actions, and actions requiring operator input from graphical icons provided on the paper copy and, based on the rectilinear graph, to serialize the automated actions, the semi-automatic actions, and the actions requiring operator input as control commands to a printing system.

The invention discloses a high-capacity data protection method based on a GAN augmented image foreground object. By applying various GANs to information hiding, the high-capacity data protection method obtains an embedded distortion probability graph, calculates an unsuitable steganography area according to the embedded distortion probability graph, generates a foreground object in the unsuitablesteganography area through a fixed area object generation and information embedding module, and then hides the secret information in the generated graph. The high-capacity data protection method mainly comprises the following steps: (1) inputting an original image into a steganography probability graph generator; (2) calculating the steganography probability graph; (3) calculating the unsuitable steganography area; (4) adding a texture object into the original image; and (5) carrying out an information hiding algorithm to embed secret information. According to the high-capacity data protectionmethod, the unsuitable hidden area is calculated for the image in advance, so that the directional hiding capability of the unsuitable hidden area of the original image in information hiding is improved; and provided is a high-capacity data protection method which increases hiding capacity and has high security.

An apparatus for generating a depth map comprising: a single camera module with a fixed near field focus configured to capture a single image; an image divider configured to segment the image into a plurality of regions; a focus metric determiner configured to determine a focus metric for each of the plurality of regions; and a depth map generator configured to map the focus metric into a depth value for each of the plurality of regions and combine the plurality of depth values to generate a depth map for the single camera.

Provided are a search system and a search method capable of searching an unknown combination of material property parameters having a significant relationship based on already known relationships from among multiple arbitrary combinations of material property parameters. The search system includes a database, a graph generator, and a graph searcher, and is configured as follows: the database stores the plurality of pairs of material property parameters having mutual relationships, and the graph generator generates a graph in which material property parameters stored in the database are nodes, and an inter-node corresponding to the pairs of material property parameters stored to have mutual relationships is an edge. The graph searcher searches the graph generated by the graph generator based on a given search condition and outputs a search result.

The invention relates to a graph generator based on an FPAG (Field-Programmable Gate Array) and a working method thereof. The graph generator comprises an FPGA chip, multiple external SRAMs (Static Random Access Memories), FLASH memories and an outgoing sensing chip, wherein the FPGA chip is respectively in control connection with the eight external SRAMs; two FLASH memories and the outgoing sending chip are used for controlling and processing data; the number of the FLASH memories is two, comprising a graph gallery FLASH chip and a command FLASH chip respectively used for storing commands and the graph galleries; the multiple external SRAMs are used for accelerating the display of the graphs; and the outgoing sensing chip is used for converting the format of the data output from the FPAG.

The invention provides a depression recognition method and device based on a face video and a storage medium. The depression recognition method comprises the following steps: extracting a pre-acquired target spatial-temporal feature of each to-be-recognized face sub-video through a pre-trained target depression recognition model; outputting a depression degree recognition score of each to-be-recognized face sub-video through a target depression recognition model, and determining a thermodynamic video of each to-be-recognized face sub-video through a thermodynamic diagram generator; determining a first depression recognition result of the target person based on the depression degree recognition score of each to-be-recognized face sub-video; determining a second depression recognition result of the target person based on the thermodynamic video; and determining a final depression recognition result of the target person based on the first depression recognition result and the second depression recognition result. In this way, the final depression recognition result of the target person is determined based on the depression degree recognition score obtained based on the spatial-temporal features of the to-be-recognized face sub-video and the thermal video, and the accuracy of the depression recognition result can be effectively improved.

The invention provides an anti-counterfeiting code figure with identification points. The code figure is provided with at least one identification point printed by adopting special ink or an identification pattern formed by multiple identification points. When excitation lines shine on the surface of the code figure or the code figure is checked through different perspectives, the identification point or the identification pattern presents a color different from the code figure. The code figure generation method comprises steps: an electronic pattern of the needed code figure is generated; according to the size of the electronic pattern, multiple virtual grids with printing identification point implantation regions are divided; after basic parameters of the identification point or the identification pattern are set, the ink type is selected and a specified virtual grid is selected, the identification point is printed on the code figure via the virtual grid. The code figure generation device comprises a code figure generator, an image processor, a size comparison module and a parameter setter. Before the code figure is scanned, through identifying whether an identification point or an identification pattern exists in the code figure, the source can be known.

A video processing unit can include a non-object-based region-of-interest detection neural network, a threshold selection module and a region-of-interest map generator. The non-object-based region-of-interest detection neural network can be configured to receive a video frame and generate a plurality of candidate non-object-based region-of-interest blocks. The threshold selection module can be configured to receive the plurality of candidate non-object-based region-of-interest blocks and identify a plurality of selected region-of-interest blocks based on a predetermined threshold. The region-of-interest map generator can be configured to receive the selected non-object-based region-of-interest blocks and generate a region-of-interest map.

The invention provides a breast tissue classification and identification method based on transfer learning. The method comprises the following steps: firstly, obtaining a suspected patient breast tissue slice pathological image through a tissue slice, then carrying out format adjustment and a series of image processing to obtain a breast tissue slice preprocessed pathological image, and manually marking the preprocessed image pathological category; constructing a transfer learning breast tissue classification model, sequentially inputting the preprocessed images into the model, predicting a pathological category through the model, constructing a loss function model in combination with an actual pathological category of the images, and performing optimization training to obtain an optimized transfer learning breast tissue classification model; and predicting the pathological category of the suspected patient through the optimized model, and combining the pathological category with a heat map generator to obtain a thermodynamic diagram corresponding to the evidence region. The invention has the advantages that the method is suitable for an application environment with a small data set, the robustness is enhanced in training, and the credibility of a result is improved in prediction.