20 results about "Reliable computing" patented technology

The invention discloses a financial data privacy protection system based on block chain security multi-party computing, and belongs to the technical field of data protection, and the system specifically comprises the steps that a data preprocessing module segments original financial data, and adds a unique watermark identifier; the distributed account book stores the Hash abstract and watermark mapping relation of the encrypted logic data fragment, and the digital signature and the timestamp are fused to ensure reliability; the computing node cluster receives data through a special interface, dynamically builds a computing group according to a service rule and outputs an encrypted computing result; bidirectional authentication is carried out on the zero-knowledge proof verifier and the computing node cluster to verify the data holding right; the encryption proxy gateway processes an output result of the computing node cluster to complete format conversion and ciphertext superposition; the cross-link routing module constructs a virtual coverage layer, cross-link transmission of encryption results is achieved through protocol conversion and three-way handshake verification, and a heterogeneous chain protocol converter and a verification assembly guarantee transmission safety; the financial data privacy security is comprehensively guaranteed, and the data processing efficiency and reliability are improved.

The invention relates to a secure and trusted computing system based on real-time virtualization of an aneuhua OS (Operating System). The secure and trusted computing system comprises three program modules and a virtual machine manager, wherein the virtual machine manager provides a high-efficiency virtualization technology, adopts a Type1 type virtualization architecture, realizes a lightweight virtual machine manager at a bottom layer, and runs on a hardware platform; the trusted computing core is specially responsible for running an embedded operating system and is used for executing a secure and sensitive trusted computing task; the Linux core is used for operating user service processing and providing user experience and service support; the security isolation and monitoring module is used for realizing security isolation between the two trusted computing cores and the Linux core; the security authentication and authorization module is used for performing identity authentication and authorization on the user and the application program; the problems that real-time guarantee of tasks is difficult to realize and application requirements in the technical field cannot be met in a current system security extension technology are solved, and a secure and credible operation environment during multi-core heterogeneous hybrid deployment and credible computing is realized.

The invention relates to a power distribution network three-phase power flow analytical solution calculation method based on restart, and belongs to the field of power distribution network power flow estimation. The method comprises the following steps: taking a three-phase HELM as an initial starting model; a flexible three-phase HELM model is deduced in combination with a three-phase element model of the power grid, and the flexible three-phase HELM model is used as a load flow calculation model after restarting; based on slow convergence of the power flow and even falling into two phenomena of stagnation solution and power flow divergence, different power flow restarting strategies are provided, and a'bud solution 'state, namely a no-load state, of the algorithm is restarted and updated in a recursive solving process. According to the method, rapid and reliable calculation of the power flow can be realized in a large-scale and heavy-load power distribution network three-phase system; the power flow restarting mechanism can dynamically respond to different distribution network systems and specific conditions of a power flow solving process, the restarting opportunity is flexibly adjusted, and the universality is high; the power flow restarting mechanism provides related reference for convergence domain analysis of power flow calculation in a three-phase system.

The application discloses a multi-modal graph fusion driven spatial transcriptome region identification method, and belongs to the field of biomedical informatics and computational biology. The method comprises the following steps: step 1, data acquisition; step 2, data processing; step 3, multi-modal adjacency matrix generation; step 4, differentiable multi-modal graph structure fusion; step 5, variational graph autoencoder training; and step 6, clustering. By constructing a spatial domain identification framework based on multi-modal graph fusion and variational autoencoder, the application significantly improves the accuracy, continuity and biological interpretability of spatial transcriptome clustering analysis, effectively solves the deficiencies of existing methods in multi-modal fusion, graph structure optimization and feature discriminability, and provides a more reliable computing tool for in-depth revealing of tissue spatial heterogeneity in the fields of brain science, tumor microenvironment analysis and other frontier biomedical researches.

This invention provides a method and apparatus for measuring computing power on an intelligent computing cloud platform based on GPU computing power consumption and inference token values. It relates to the fields of intelligent computing centers, smart computing centers, computing infrastructure, and smart computing cloud technologies, and includes the following steps: Step S1, collecting task data, GPU runtime data, and model and engine parameters during inference on the intelligent computing cloud platform; Step S2, extracting first feature information, second feature information, and third feature information from the task data, GPU runtime data, and model and engine parameters; Step S3, performing token fitting computing power calculation based on the first feature information, GPU model, and third feature information to obtain a first computing power consumption value; Step S4, performing GPU computing power consumption benchmark calculation based on the first, second, and third feature information to obtain a second computing power consumption value; Step S5, determining a reliable computing power consumption value based on the first and second computing power consumption values. This invention can significantly improve the accuracy of computing power measurement on intelligent computing center cloud platforms.

The invention provides a dual-redundancy high-reliability computing device based on a PSOC. The dual-redundancy high-reliability computing device based on the PSOC comprises two PSOC computing units which are both in communication interaction with an avionics system through an FC bus; a dual-redundancy mechanism is realized between the two PSOC calculation units through a CCDL (Charge Coupled Device Language) protocol; the two PSOC computing units are respectively integrated with a 1394 bus daughter card, and the 1394 daughter card is used as a physical link for realizing a CCDL protocol between the two PSOC computing units; the two PSOC calculation units are respectively connected with a remote interface unit (RIU) through 1394 bus daughter cards, and are used for controlling execution mechanisms related to the remote interface unit (RIU) to execute service actions. According to the invention, the logic and physical interchangeability of the system is improved through the completely consistent dual-redundancy calculation unit design; the PSOC circuit is selected to realize integrated fusion of programmable logic and general calculation of the calculation unit, and the reliability and the energy consumption level of the system are improved; data communication and dual-redundancy function enabling realized by adopting a CCDL protocol provide an efficient path.

The application discloses a method and system for judging single-phase grounding fault of a power distribution network, and relates to the field of power distribution network fault judgment. The judgment system provided by the application adopts a starting algorithm for monitoring changes in fault component mutation variables in real time. After starting, the judgment system calculates relevant parameters of first-stage transient variables at the moment of fault and relevant parameters of second-stage steady-state variables after the fault is stabilized. After multi-criterion judgment and comprehensive fusion, reliable on-site judgment of single-phase grounding is realized. The method is simple and reliable, and has high calculation speed, thereby realizing on-site rapid judgment.

This application relates to the field of natural language processing technology, and more particularly to a method for solving mathematical problems using a small-parameter, large-language-model approach and its applications. The method involves a teacher model that structurally decomposes the mathematical problem, providing a reasoning path for the student model. Simultaneously, an external sandbox executor handles all numerical computation tasks, avoiding computational biases and reasoning errors that may arise from greedy decoding, thus achieving reliable computation for small-parameter models in solving mathematical problems. The aim is to address the problem of unreliable mathematical problem-solving caused by greedy decoding in long-term reasoning processes using small models. Without requiring model retraining, this method significantly improves the logical consistency, computational accuracy, and overall robustness of small-parameter models in mathematical reasoning tasks, making it suitable for applications such as mathematical problem solving, enhanced mathematical reasoning, and related intelligent problem-solving systems.

This disclosure relates to a server auditing method, apparatus, device, and medium, belonging to the field of computer technology. The method includes: controlling the server to start according to a preset startup mode to ensure that data information remains unchanged during the startup process from the Basic Input / Output System (PIOS) to the operating system; mapping the operating system's auditable data to a PCIe card connected to the server via direct memory access, so that the PCIe card audits the auditable data according to a preset audit cycle and preset audit mode, obtaining an audit result; obtaining the PCIe card's audit result as indicating that the data has not been modified; and auditing the process through an internal audit module embedded in the operating system, obtaining a process audit result. By employing the above technical solution and using a dual auditing approach, a secure and reliable computing environment is constructed for the server, ensuring the immutability of the computing environment and guaranteeing the security, integrity, and confidentiality of loaded server code and data.

Secure Digital Processing Console with Multi- Layer Information Management Matrix for Reliable Computing Operations

The invention discloses a drug target interaction multi-task prediction method based on multi-modal characteristics. According to the method, drug multi-dimensional structure features and drug target text semantic features are comprehensively utilized, and a multi-modal feature embedding framework is constructed. A multi-nuclear magnetic relation convolution layer is designed, a magnetic Laplacian matrix and a frequency domain graph filter are introduced, and a DTI multi-classification prediction model MFFGCN based on a graph convolution neural network is constructed. And a DTI natural language explanation text generation task is further proposed, a DTI natural language explanation text generation model EXDTI is utilized to formalize drug target interaction prediction into natural language explanation text generation, and readable mechanism description and relation explanation are generated. The method has excellent performance in DTI multi-task joint prediction, has good cold start adaptability, and provides an efficient and reliable calculation tool for new drug research and development and candidate screening.

The invention discloses a spatial transcriptome region identification method driven by multi-modal graph fusion, and belongs to the field of biomedical informatics and computational biology. The method comprises the following steps: step 1, data acquisition; 2, data processing; step 3, generating a multi-modal adjacent matrix; 4, carrying out the structure fusion of the differentiable multi-modal graph; step 5, variational graph self-encoder training is carried out; and step 6, clustering. According to the method, the spatial domain recognition framework based on multi-modal graph fusion and the variational autoencoder is constructed, so that the accuracy, continuity and biological interpretability of spatial transcriptome clustering analysis are remarkably improved, and the defects of an existing method in the aspects of multi-modal fusion, graph structure optimization and feature discrimination are effectively overcome; and a more reliable calculation tool is provided for deeply revealing tissue spatial heterogeneity in the field of advanced biomedical research such as brain science, tumor microenvironment analysis and the like.

The invention relates to the technical field of cross-domain resource scheduling, and particularly provides a cross-domain resource pool dynamic optimization and service rapid deployment method and device, comprising: (1) a first layer: a cross-domain resource pool dynamic optimization main process, Spring state machine drive; (2) a second layer: a computing power transaction trusted execution sub-process which is driven by a block chain and LiteFlow; (3) a third layer: a service containerization rapid deployment sub-process which is driven by K8s Java Client + LiteFlow; and (4) process instance management. Compared with the prior art, the real-time and high-reliability computing power service requirements can be met.

The invention discloses a cloud-edge collaborative intelligent scheduling method for a satellite fusion network, and relates to the technical field of cloud computing, edge computing, ad hoc networks and satellite communication. The method comprises the following steps of: setting a CPU (Central Processing Unit) utilization rate threshold and a memory utilization rate threshold of an edge server cluster, and a link quality threshold of an ad hoc network and a satellite fusion network communication link; the method comprises the following steps: calculating the task priority of a computing task, maintaining a to-be-executed task queue, and arranging the computing task to one of an edge server cluster, a cloud and the to-be-executed task queue according to the task priority of the computing task in combination with the link quality of a communication link of an ad hoc network and a satellite convergence network; corresponding task decomposition is carried out, and the suspended low-task-priority calculation tasks are added into the task queue to be executed again. According to the method, a reliable calculation task scheduling service can be provided in a complex and changeable network environment, key tasks are ensured to be processed in time, meanwhile, resource allocation is optimized, and the response speed and the working efficiency of the whole system are improved.

The application discloses a drug target interaction multi-task prediction method based on multi-modal features. The method comprehensively utilizes drug multi-dimensional structure features and drug target text semantic features to construct a multi-modal feature embedding framework. By designing a multi-core magnetic relationship convolution layer, introducing a magnetic Laplace matrix and a frequency domain graph filter, a DTI multi-classification prediction model MFFGCN based on a graph convolutional neural network is constructed. Furthermore, a DTI natural language explanation text generation task is proposed, and a DTI natural language explanation text generation model EXDTI is used to formalize the drug target interaction prediction into natural language explanation text generation, and readable mechanism explanation and relationship explanation are generated. The method performs excellently in the DTI multi-task joint prediction, has good cold start adaptability, and provides an efficient and reliable computing tool for new drug research and development and candidate screening.

The invention discloses a vehicle-mounted computing power scheduling method, system, device and medium, and the method comprises the steps: obtaining the current computing power demand of a vehicle and schedulable computing power resources around the current driving lane of the vehicle, and enabling the schedulable computing power resources to comprise a plurality of computing power transfer stations around the current driving lane of the vehicle; and determining a target computing power transfer station to which the vehicle needs to access according to the current computing power demand of the vehicle and the plurality of computing power transfer stations, and establishing communication connection with the schedulable computing power equipment around the target computing power transfer station by using the distributed soft bus to obtain the computing power of the schedulable computing power equipment. According to the method, through a dynamic computing power transfer station and a real-time scheduling mechanism, communication delay is remarkably shortened, meanwhile, a multi-layer network coverage system is constructed, it is ensured that the vehicle can obtain reliable computing power support at any place, and continuity and stability of computing power service are improved. In addition, by efficiently integrating idle computing power resources, the dependence on a traditional remote server is reduced, and the computing power cost is reduced.

The invention discloses a numerical calculation method for a hydrofoil cavitation dynamics evolution induced energy release mechanism. The numerical calculation method comprises the following steps: constructing a hydrofoil streaming flow field calculation domain; dividing grids for the computational domain, and importing the grids of the computational domain into computational fluid mechanics simulation software; setting a boundary condition and a solution algorithm of hydrofoil cavitation calculation, selecting a discrete phase model, and injecting multiple particles into the head of the hydrofoil; through cavitation flow field calculation, motion characteristics of cavitation bubbles in a cavitation flow field are obtained based on the motion data of the particles; and constructing a multi-cavitation energy numerical model considering the cavitation aggregation effect, and coupling the multi-cavitation energy numerical model with the cavitation kinetic equation to obtain the cavitation radius, the internal pressure, the energy distribution rule and the release mechanism in the cavitation flow. By means of the method, reliable calculation of cavitation characteristic changes of the hydrofoil surface cavitation flow in different forms is achieved, theoretical reference is provided for revealing cavitation dynamics evolution induced energy release, and meanwhile prediction means of energy conversion in the hydraulic machinery cavitation flow with the airfoil section as a basic blade unit are enriched.

The invention discloses a flood simulation real-time correction method considering system non-Gaussian property. The method comprises the following steps: constructing a hydrological model for flood simulation in a basin to be simulated; constructing an ensemble Kalman filter coupled with the hydrological model; training a routing network model based on the hydrological model and an ensemble Kalman filter to process the non-Gaussian property of the hydrological model; and carrying out real-time correction on a hydrological model forecasting result based on the trained routing network model. The method has the advantages of stable and reliable data source, high calculation efficiency, objective and reasonable result and the like, and the simulation forecast precision of the hydrological model on the flood process is improved.

The invention discloses a redundancy calculation system, a redundancy calculation processing method and related equipment. The system comprises a first computing unit running in a first kernel in a software lock step mode, a second computing unit running in a second kernel in a software lock step mode, an arbitration unit running in a third kernel and a watchdog unit running in a fourth kernel. The second calculation unit monitors the operation condition of the controller according to a technical scheme different from that of the first calculation unit; the first kernel, the second kernel, the third kernel and the fourth kernel are respectively provided with first middleware used for coordinating time synchronization among the kernels, and second middleware used for scheduling the first calculation unit and the second calculation unit in an absolute time scheduling mode. According to the method, environmental interference in the same time space is avoided to a certain extent, a more reliable calculation result can be obtained, the security level is improved through software redundancy, the system failure rate is reduced, and the method has high software execution efficiency.

The invention discloses a localized environment-based cross-department comprehensive supervision platform and a data processing method. The system architecture comprises an infrastructure layer, a data layer, a support layer, an application layer, a display layer and a security processing module. The infrastructure layer provides safe and reliable computing storage network resources by adopting a creative cloud and an e-government affair external network; the data layer stores and manages supervision data through a supervision basic library and a supervision thematic library; the support layer provides unified tool support and data support capabilities. According to the invention, a localized unified platform is constructed, the problems of cross-department data sharing and business collaboration are solved, interconnection and on-demand sharing, efficient collaboration and accurate differentiated supervision of supervision data are realized, the supervision efficiency and accuracy are improved, and the whole-process data security is guaranteed through multi-level security measures.