14 results about "Federated search" patented technology

The invention provides a link prediction method, system and device for a graph network and a storage medium, and belongs to the crossing field of a graph neural network and machine learning, and the method comprises the steps: firstly, constructing a three-dimensional joint search space composed of a sub-graph extraction strategy, a motif structure type and a graph neural network architecture, and through a differentiable architecture search technology, carrying out the three-dimensional joint search of the sub-graph extraction strategy, the motif structure type and the graph neural network architecture; automatically learning an optimal analysis combination for a specific network structure; the optimal analysis combination is used for prediction, the system fuses local adjacency information based on the self-adaptive subgraph and a high-order structure mode based on the selected motif, the optimized graph neural network is used for coding and aggregation, and finally the high-precision link existence probability is output. Experimental verification shows that the method achieves remarkable and stable performance improvement on isomorphic and heterogeneous data sets, the limitation of a traditional method under different topological structures is effectively overcome, and a universal, robust and efficient solution is provided for a link prediction task in a complex network.

The application discloses a noise elimination and transformation model robust estimation method in multi-modal image registration, comprising: obtaining initial matching point pairs, establishing a homography transformation model to be estimated and residual error measurement; performing vector field consistency calculation on the initial matching point pairs, and constructing an edge expansion consensus set; performing initial fitting on the homography transformation model on the edge expansion consensus set to obtain an initial homography transformation model; estimating noise scale and initializing residual error threshold based on residual error statistics induced by the initial homography transformation model; regarding the residual error threshold and the homography transformation model parameters as same-order decision quantities, constructing a joint optimization framework of threshold-model cooperation; adaptively constructing a joint search domain according to regularity statistics of residual error distribution; constructing a threshold-coupled cost function under a mixed statistical modeling framework of inliers / outliers; performing collaborative iterative updating on the homography transformation model and the residual error threshold by adopting a group optimization strategy, and outputting the homography transformation model and a refined inlier set.

The invention provides a signal detection method, apparatus and device, and a storage medium, which can effectively avoid the problem of self-information interference without introducing iterative feedback and feeding back the estimation result of the symbol for self-correction by constructing a state based on an original received symbol and a known channel structure, and improve the detection efficiency of the signal. An interference structure with any complexity can be accurately described, high-precision symbol detection is realized, and the method is suitable for any time delay-Doppler extension scene. In the process of advancing from the state of one received symbol to the state of another received symbol, the differentiated undetermined sending symbols playing a key information updating role between adjacent states are concerned, all sending symbols do not need to be reprocessed, joint search for full combinations is avoided, and the transmission efficiency is improved. The calculation complexity is reduced from the index level to the polynomial level related to the difference scale between the states, and the processing capacity is improved on the premise that the detection performance is not reduced.

The application discloses a kind of based on defining organization attack preference guard graph decision method and system, its method includes steps: from the log server of honeypot collection attack information, through the joint search of threat intelligence knowledge graph and external threat intelligence library, ascription defines the behavior mode of attack organization, and the attack preference of attack organization is sorted;From the perspective of attacker, through the topological information in target network, asset information and configuration information generation attack graph, and the mapping of defining organization attack preference to attack graph node is carried out, generates guard graph, and then generates the guard matrix for quantifying calculation attack graph attack mode preference influence;Based on the analysis of the guard matrix of attack graph to defining organization attack preference, with emphasis, generate honeypot service, provide decision support for the deployment of defense measures.The application can more flexible quickly generate the type of honeypot service, greatly saves manpower and time cost for the analysis and deployment of deception defense.

The application provides a gait emotion joint recognition method based on heterogeneous space neural architecture search, comprising the following steps: extracting three-dimensional human posture joints in different emotion video data; performing space conversion, and converting into a rectangular coordinate system and a spherical coordinate system respectively; performing position information space mapping and angle information space mapping on the joints in different coordinate systems based on a similarity minimization strategy; constructing a neural architecture search space and a joint search strategy in different spaces, searching for optimal backbone networks respectively, and training the optimal backbone networks respectively; extracting human time sequence gait emotion features in different spaces by using the trained optimal backbone networks, inputting the features into a Softmax classifier, and obtaining scores of different emotions; and performing joint scoring to complete the gait emotion joint recognition based on the heterogeneous space neural architecture search.

The invention discloses a noise elimination and transformation model robust estimation method in multi-modal image registration, and the method comprises the steps: obtaining an initial matching point pair, and building a to-be-estimated homography transformation model and a residual measurement; vector field consistency calculation is carried out on the initial matching point pairs, and an edge expansion consensus set is constructed; performing initial fitting on the homography transformation model on the edge expansion consensus set to obtain an initial homography transformation model; estimating a noise scale based on residual statistics induced by the initial homography transformation model and initializing a residual threshold; regarding a residual threshold and a homography transformation model parameter as same-order decision quantities, and constructing a threshold-model collaborative joint optimization framework; a joint search domain is constructed in a self-adaptive mode according to regularity statistics of residual error distribution; constructing a threshold coupling cost function under an inner point / outer point mixed statistical modeling framework; and carrying out collaborative iteration updating on the homography transformation model and the residual threshold by adopting a group optimization strategy, and outputting the homography transformation model and a refining inner point set.

This application relates to automatic operation detection on protected fields that support federated search. Systems and methods are provided for automatic operation detection on protected fields. A data model configuration can be used to specify which properties of a data model used by a cloud-based application are protected by a data security provider that monitors communications between the application and client devices. A determination can be made automatically as to which operations of the cloud-based application are supported for protected fields. The cloud-based application can be configured to enable / disable certain features, such as validators, autocomplete, search operators, etc., depending on whether a property is a protected field.

Apparatus and methods for joint search space assembly for enhanced multi-beam, multi-TRP PDCCH transmission are described. The apparatus includes: a processor that generates a plurality of downlink control information (DCI) versions for transmission from a plurality of transceiver identities with a plurality of control resource sets (CORESETs), each CORESET being transmitted from one of the transceiver identities; and configures an information element (IE) indicating a joint search space assembly for the DCI, wherein the joint search space assembly comprises a plurality of component search space assemblies; and a transmitter that transmits the DCI and the IE using the plurality of transceiver identities; wherein each of the component search space assemblies is configured to monitor and detect a DCI version.

The augmented reality processing unit and the one or more augmented reality devices may share a joint access code. The processing unit may transmit an access code and an identifier corresponding to the processing unit and the device to the wireless access network node. The node may configure the processing units and apparatus with respective control channel search space resources and respective scrambling codes corresponding thereto. The node may receive traffic directed to one of the devices. If the transmission of control channel information corresponding to traffic will violate the latency criterion corresponding thereto, the node may puncture resources that occur during the joint search space opportunity and are configured for use by the processing unit to transmit the control channel information to the apparatus. The node may determine a control information format suitable for a residual portion of the punctured federated search space opportunity to deliver the control information to a processing unit.

The invention relates to an electroencephalogram channel and feature selection device and method based on a proxy model, and belongs to the technical field of brain-computer interfaces. Firstly, conventional preprocessing and feature extraction are conducted on multi-channel EEG signals, and multi-dimensional feature representation is obtained; then, jointly forming a joint search space by the channel selection vector, the feature selection matrix and the classification model hyper-parameter; a proxy model with XGBoost as a core is constructed, and a LambdaRank sorting loss function is adopted to carry out sorting prediction on the performance of the candidate samples; and screening the candidate combination with the optimal performance based on an output result of the proxy model to carry out true verification, and iteratively updating the proxy model by utilizing true performance feedback, so that self-adaptive guidance of heuristic search is realized. According to the method, the real training times can be reduced on the premise of ensuring the classification precision, the search efficiency and the calculation performance are improved, and the method is suitable for various EEG decoding and classification tasks.

The invention particularly relates to an ROV multi-target joint search method based on an MQTT protocol, and aims at underwater large-scale multi-target ROV search tasks, a bus-distributed lightweight communication strategy is adopted, a joint task allocation scheme and a bus-type integrated ROV task execution strategy are included, and underwater multi-target joint search is completed jointly. The joint task allocation scheme is a collaborative allocation scheme of underwater ultra-short baseline guidance, underwater foresight sonar guidance and underwater camera target guidance of the ROV, and the bus type integrated ROV task execution strategy comprises state confirmation, rule conversion and upper computer task allocation implementation. The system integrates bus type multi-sensor data receiving and transmitting and state confirmation and strategy switching during multi-target searching, can serve as a semi-physical simulation platform of an ROV target task, and facilitates an operator to achieve an ROV multi-target joint searching task.

This application relates to a method, apparatus, device, and medium for managing data asset models across the entire process, belonging to the field of data processing technology. The method includes: sequentially extracting metadata from multiple data sources of a target business system, constructing a data asset catalog, and accessing data assets based on metadata association and catalog binding to generate a full-process data asset flowchart showcasing the entire data asset access path; performing missing metadata prediction and completion using a dual algorithm based on data lineage logic reasoning and knowledge graph rule judgment; conducting a correctable, multi-stage, multi-round recursive quality assessment on the data asset flowchart after missing metadata prediction and completion; and simultaneously executing a three-layer parallel joint retrieval mechanism based on the quality assessment results to complete the joint search of multiple data assets and display high-quality retrieval results. This method enables efficient and accurate management of the data asset model of the target business system.

The application relates to the technical field of artificial intelligence and large model, and particularly provides a cross-domain large model method and system based on a federated RAG. The method comprises query receiving and analysis; target client determination; federated search request distribution; local search and security processing, the client receives a search request, performs vector similarity calculation and keyword search, obtains an initial knowledge fragment set, and processes the initial knowledge fragment set; the processed intermediate result is returned to the server; multi-source result fusion, the server receives intermediate results from multiple clients, performs fusion processing on the intermediate results, and obtains an enhanced context document; an answer is generated, the server generates a natural language answer through semantic analysis and context-aware reasoning on the enhanced context document and the original query; and the natural language answer is returned to the server to complete a cross-domain question and answer interaction, and the method realizes effective cross-domain knowledge cooperation.

The embodiment of the application discloses a private domain data federated search method and system for data space, relates to the technical field of computers, and can realize effective and accurate query of scattered private domain data in a data space while meeting the requirement of a data owner in local control and management of private domain data. The method calls the search capability of a local private domain data source of a federation, thereby realizing effective search of scattered private domain data in the data space without the need of establishing centralized indexes. Based on a probability local sensitive hash table, the method can fuzzily select a target data source in which stored private domain data is consistent with a user query intention without knowing original data in the private domain data source, and sends a search request to the target data source, thereby reducing the risk of leakage of the original data in the private domain data source, and realizing accurate query of scattered private domain data in the data space.