53 results about "Strongly connected component" patented technology

A context-free grammar can be represented by a weighted finite-state transducer. This representation can be used to efficiently compile that grammar into a weighted finite-state automaton that accepts the strings allowed by the grammar with the corresponding weights. The rules of a context-free grammar are input. A finite-state automaton is generated from the input rules. Strongly connected components of the finite-state automaton are identified. An automaton is generated for each strongly connected component. A topology that defines a number of states, and that uses active ones of the non-terminal symbols of the context-free grammar as the labels between those states, is defined. The topology is expanded by replacing a transition, and its beginning and end states, with the automaton that includes, as a state, the symbol used as the label on that transition. The topology can be fully expanded or dynamically expanded as required to recognize a particular input string.

Paralleling processing system and method. When clusters are formed based on strongly connected components, a single cluster (fat cluster) having at least a predetermined number of blocks, or an expected processing time exceeding a predetermined threshold, is formed. The fat cluster is subjected to an unrolling process to make multiple copies of the processing of the fat cluster and to assign the copies to individual processors. Processing of the fat cluster is executed by the multiple processor devices in a pipelined manner. If a fat cluster to be iteratively executed cannot be executed in the pipelined manner because a processing result of an nth iteration of the fat cluster depends on a processing result of a preceding iteration of the fat cluster an input value needed for execution of the fat cluster is generated based on a certain prediction, and the fat cluster is speculatively executed.

A system or method for identifying text in a document. A group of connected components is created. A plurality of characteristics of different types is calculated for each connected component. Statistics are computed which describe the group of characteristics. Outlier components are identified as connected components whose computed characteristics are outside a statistical range. The outlier components are removed from the group of connected components. Text pixels are identified by segmenting pixels in the group of connected components into a group of text pixels and a group of background pixels.

The invention discloses an influence maximization parallel accelerating method based on a graphic processing unit. The purpose of the invention is to provide the influence maximization parallel accelerating method based on the GPU (graphic processing unit). Algorithm implementation is accelerated and the implementation time is shortened by parallel calculating ability of the GPU. The influence maximization parallel accelerating method is characterized by comprising the following steps: in each Monte Carlo simulation, firstly, finding out strong connectivity in a network diagram, merging all nodes in the same strong connectivity into a node, wherein the weight is the sum of the weights of all nodes in the strong connectivity; then calculating an influence value of each node in parallel by a strategy of traversing upwards from the bottom; using different threads by the GPU calculation cores to calculate in a parallel way the influence values of different nodes with the help of the parallel calculation capability of the GPU, and obtaining the K most influential nodes. According to the invention, a pattern is converted into a directed acyclic graph; the calculation quantity of an influence value can be obviously reduced, meanwhile, the overall operation time is shortened by scheduling parallel calculation of each node in the calculation core of the GPU to the maximal extent.

A method which identifies different types of substructures within a graph and encodes them using techniques suitable to the characteristics of each of them. The method is embodied by an efficient two-phase algorithm, where the first phase identifies and encodes strongly connected components as well as tree substructures, and the second phase encodes the remaining reachability relationships by compressing dense rectangular submatrices in the transitive closure matrix.

A context-free grammar can be represented by a weighted finite-state transducer. This representation can be used to efficiently compile that grammar into a weighted finite-state automaton that accepts the strings allowed by the grammar with the corresponding weights. The rules of a context-free grammar are input. A finite-state automaton is generated from the input rules. Strongly connected components of the finite-state automaton are identified. An automaton is generated for each strongly connected component. A topology that defines a number of states, and that uses active ones of the non-terminal symbols of the context-free grammar as the labels between those states, is defined. The topology is expanded by replacing a transition, and its beginning and end states, with the automaton that includes, as a state, the symbol used as the label on that transition. The topology can be fully expanded or dynamically expanded as required to recognize a particular input string.

State machines are identified from a netlist of circuit elements of a user design. Strongly connected components in the netlist are identified as candidates for analysis. The registers of each strongly connected component are identified. An optimal set of inputs and potential state transition logic is identified for the registers in the component. A set of reachable states from an initial state of the registers of a component is determined by simulating state transitions in response to permutations of input values. State machine information is created to assist compilation software in optimizing the user design. Optimizations can include identifying redundant circuit elements based on the set of reachable states and reencoding the state machine with a different state encoding scheme to reduce the amount of state transition and output logic. A subset of the set of reachable states representing a one-hot encoded state machine may be further isolated and optimized.

The invention discloses a taxpayer tax evasion suspicion group detection method based on a multi-stage MapReduce model. The method comprises the following steps: firstly, proposing a method of constructing a taxpayer benefit association network based on a color-patch map through multi-network integration; secondly, proposing a reduction method of the taxpayer benefit association network based on strongly connected components; thirdly, introducing a concept of a benefit antecedent network, and finding all maximal weakly-connected sub-graphs in the benefit antecedent network; and lastly, constructing a pattern tree for the maximal weakly-connected sub-graphs and corresponding trade edges thereof through the multi-stage MapReduce model, traversing the pattern tree to generate a pattern library, matching patterns in the pattern library pairwise, finding all pattern pairs conforming to a matching principle, and finally generating all taxpayer evasion suspicion groups. Distributed calculation is adopted in the multi-stage MapReduce model, so that the suspicion tax evasion analysis efficiency of national tax departments can be increased greatly, and the national tax loss is recovered.

The invention relates to a similar image clustering method, a similar image clustering device, a computer readable storage medium and electronic equipment, and relates to the technical field of imageprocessing, and the method comprises the steps: extracting image features of a plurality of images through a convolutional neural network model, and carrying out Hash mapping on the image features; clustering the image features through a strong connection component clustering method to determine a clustering category; and providing a category identifier for each image feature and obtaining the similar image from a database according to the category identifier. The similar image clustering efficiency can be improved.

A graph traversal system that efficiently identifies strongly connected components and simultaneously identifies entries, exits, and corresponding edges is described herein. Ingress and egress nodes can be identified by scanning each node after identifying strongly connected components, but revisiting these nodes incurs undesired overhead. The present graph traversal system identifies ingress and egress in a single traversal when strongly connected components are being identified. Furthermore, the present system modifies the semantics for some applications such that a single node alone is not considered a strongly connected component. Thus, the present graph traversal system allows efficient identification of entries and exits from strongly connected components in a manner that can be applied to a large number of computer software problems using directed graphs as data structures.

A context-free grammar can be represented by a weighted finite-state transducer. This representation can be used to efficiently compile that grammar into a weighted finite-state automaton that accepts the strings allowed by the grammar with the corresponding weights. The rules of a context-free grammar are input. A finite-state automaton is generated from the input rules. Strongly connected components of the finite-state automaton are identified. An automaton is generated for each strongly connected component. A topology that defines a number of states, and that uses active ones of the non-terminal symbols of the context-free grammar as the labels between those states, is defined. The topology is expanded by replacing a transition, and its beginning and end states, with the automaton that includes, as a state, the symbol used as the label on that transition. The topology can be fully expanded or dynamically expanded as required to recognize a particular input string.

The embodiment of the invention provides an inter-cloud computing unloading method and device in edge computing. The method comprises the steps of enabling an edge server to receive a to-be-processedtask sent by UE closest to an edge cloud sub-network where the edge server is located; decomposing the to-be-processed task into a plurality of sub-tasks, and constructing a first directed weighted graph by taking each sub-task as a current vertex; aggregating the current vertexes corresponding to the strongly connected components found in the first directed weighted graph into new vertexes, and constructing a second directed weighted graph based on the new vertexes; determining the plurality of determined edge cloud sub-networks and the central cloud sub-network as candidate matching networks; selecting a target matching network for each new vertex in the second directed weighted graph by using a preset stable matching algorithm; and sending the subtask corresponding to each new vertex inthe second directed weighted graph to the target matching network corresponding to the new vertex. According to the embodiment of the invention, the problem of unbalanced load between the existing edge cloud sub-networks can be solved.

The invention discloses a distributed data synchronization method. In the event of performing incremental synchronization, a dependency relationship of a synchronization reason is obtained through a dependency relationship of a synchronization result; therefore, a strong connection component of the synchronization reason is obtained and sent synchronously; and, in the event of performing batch synchronization and consistency check, the consistency of data states can be ensured by freezing a synchronization object. By means of the scheme, the data synchronization problem of a master controller in multi-core whole-service processing can be effectively solved; high-speed distributed forwarding is realized; therefore, the whole-service processing of a master control CPU is realized; load balancing is realized; and the processing capability of the master controller is increased.

The invention provides a project-software-oriented class cluster test method. A software system to be tested is constructed into a directed loop network; all class nodes in the directed loop network are traversed to calculate the test important degree; all strong communication components in the directed loop network are traversed, and the test pile complexity corresponding to each edge in each loop is calculated; a weight value is aligned to each edge in the loop, and the loop removing operation is performed; a class stage integrating test sequence is generated for performing class cluster test on the software system to be tested. The method has the advantages that classes easily generating errors in the software system and classes with a wide affected range after the error occurrence are regarded as important test nodes; the class complexity and the class error spreading influence power are combined, and the goals of discovering the software defect as soon as possible and effectively controlling the error spreading range are used as test objectives; the test important degree of the class is combined for breaking through the loop of the software system network; the integrated test sequence is generated; the nodes with great test important degree value is enabled to be tested in a preferential way; the general complexity of the test pile is also reduced.

A building toy and a method of building with it. The toy is designed to be constructed of a rigid and generally non-deformable material such as, but not limited to, wood and particularly hardwood, and is constructed in the fashion of a log-style building toy. The toy utilizes interconnecting notches in its construction, but provides for a variety of specialized pieces which allow for interconnection of parts where there is one notch but not another, as well as the ability to build roofs, floors, and specialty structures such as fireplaces through the use of specialized components. Further, the use of more strongly connecting components allows for stronger structures to be built.

The invention relates to a power network automatic regulation method suitable for open-loop power supply based on the depth-first search of a strongly connected component. The method comprises the following steps: step S1, setting corresponding ordered elements to instantiate a directed graph by collecting the operation conditions of the power supply network. 2, adopt a depth-first search algorithm to analyze and calculate that strongly connected component in real time. Step S3, according to the requirement of changing the operation mode, the depth-first search algorithm is adopted to simulateand calculate the brand-new strongly connected components after changing the operation mode. 4, after confirming that that simulation result is feasible, issue a fast automatic power regulation command to complete the power regulation operation. The ordered elements include: a circuit breaker, which is used to change the structure of the diagram; a transformer, internal strongly connected component; a bus, a supplementary parameter of a strongly connected component used to check that structure of a graph.

A system, method, and network node for discovering network nodes and management information distributed in different strongly connected components, SCCs, in a traffic network. When a network node in a first SCC receives a request at an application layer for network management information, the node determines whether it can reach other nodes at the application layer. If not, the node utilizes a functional overlay layer known as the Data Discovery and Distribution, D3, layer to identify and select a set of neighboring nodes to receive the request. The selection procedure provides good probabilistic guarantees that the selected neighbors will include at least one neighbor in a different SCC. The node sends the request to the selected neighboring nodes at the D3 layer.

The embodiment of the invention provides a target entity resource distribution determination method and device. The method comprises the steps that firstly, a first directed graph is obtained, the first directed graph comprises a plurality of nodes representing a plurality of entities, the nodes comprise target nodes representing target entities, the nodes with the resource occupancy relationshipshow the resource occupancy direction through directed edge connection, and the resource occupancy direction corresponds to the direction with the resource occupancy proportion; then, when it is judged that the first directed graph has at least one strong connection component; when at least one strong connection component is selected and the target strong connection component in the at least one strong connection component meets a certain condition, the sub-graph corresponding to the target strong connection component is compressed into a compression node, and directed edges between the nodesin the sub-graph and the nodes outside the sub-graph are taken as directed edges between the compression node and the nodes outside the sub-graph to obtain a compressed second directed graph; and finally, resource distribution of the target entity is determined according to the second directed graph, thereby coping with a complex cross or cyclic resource occupation structure.

The invention discloses a method for searching a strongly connected component in large-scale graph data on the basis of a disk, and belongs to the technical field of the graphic calculation and processing of a big-data field. The method adopts the main measure that a task level package is used to organize a whole calculation flow, and each task uses different algorithms to process one part of data so as to maximize the advantages and the integral calculation speed of each algorithm. The invention puts forward a method for processing graph structure change on the basis of the disk, provides independent data for each task, and improves disk access efficiency. The problem that the strongly connected component in the graph data can not be searched at high aging under a situation that a graph data scale exceeds the volume of available memory can be solved.

The invention relates to a transaction sorting method and device in a super account book and computer equipment. The method comprises the following steps: constructing a transaction conflict graph corresponding to a transaction set initiated at the same moment in a block chain; wherein each node in the transaction conflict graph represents a transaction; decomposing the transaction conflict graphthrough an algorithm for solving the strongly connected components of the directed graph to obtain a corresponding strongly connected graph set; marking the total frequency of each transaction in thetransaction set according to the strongly connected graph set; removing the node representing the transaction with the maximum total number of times from the transaction conflict graph, and updating the total number of times of occurrence of each transaction until no strong connection graph exists in the transaction conflict graph to obtain a conflict-free transaction graph; and based on the direction of each node in the conflict-free transaction graph, determining an execution sequence of effective transactions in the conflict-free transaction graph through sorting nodes of the super accountbook. Performance of the super account book can be improved.