548 results about "System configuration" patented technology

A system for translating source code in a first programming language to a target language is provided. The system is configured to receive source code for converting to target code; determine an abstract syntax tree from the source code; determine program specifications from the source code; determine a dependency graph from the source code; determine a plurality of chunks based at least in part on the abstract syntax tree, the program specifications, and the dependency graph; determine a plurality of converted chunks based at least in part on the plurality of chunks and a deep learning model, the deep learning model converting the plurality of chunks from the language of the source code to the language of the target code; post-process the plurality of converted chunks to obtain intermediate code; and provide the intermediate code as the target code.

A hybrid traffic flow testing method and system based on digital twin and virtual-physical integration includes steps as follows. Data of a realistic testing site is collected, and a virtual scene is created based on the digital twin, interactions between a realistic environment and a virtual environment are set up to achieve a system configuration of a system based on the virtual-physical integration. Virtual human-driven vehicles are generated based on a data set of the system configuration, and realistic human-driven vehicles are generated based on data collected by driving simulators operated by realistic human drivers. Human-driven vehicles are formed by combining the virtual and realistic human-driven vehicles, and status and location information of the human-driven vehicles are acquired. A set of sensing, positioning, planning, control, and V2X communication methods are set up based on the status and the location information for CAVs, thereby achieving autonomous driving.

The invention relates to the technical field of water pollutant concentration detection, and discloses a water pollutant concentration detection system and method based on big data analysis, and the water pollutant concentration detection method based on big data analysis comprises the following steps: constructing a multi-level sensing network, the multi-layer sensing network comprises a fixed monitoring station layer, a water surface unmanned ship layer and an underwater robot layer; carrying out multi-modal data fusion by utilizing a knowledge constraint data assimilation algorithm to generate consistent water quality parameter estimation; a double-layer cognitive structure combining a knowledge graph and a causal model is constructed, and water pollutant propagation understanding and tracing are achieved; continuous optimization of system configuration is realized through a multi-objective reinforcement learning framework; through collaborative optimization of a multi-layer sensing network, the system realizes three-dimensional monitoring of a water body, the monitoring coverage range is expanded, and meanwhile, the high-precision detection capability is kept.

According to the unified communication system provided by the invention, the stable communication connection between the client and the platform is realized through the end-side SDK module, the underlying protocol difference is shielded, and the complexity of multi-protocol adaptation is reduced. The registration center module and the service discovery middleware work cooperatively to perform automatic registration and health check on the service instance, so that the health state of the routing target node is ensured, the request is prevented from being distributed to the fault instance, and the reliability of the system is improved. The load balancing service module serves as a unified communication entrance, processes all flows in a centralized manner, reduces the number of externally exposed ports of the system, shrinks a network attack surface, and enhances security. The platform SDK module provides an interactive interface for the service platform, so that the service platform does not need to care about complex communication details, and the service development efficiency and the system maintainability are improved. The management service web platform provides a centralized visual management and control interface for all the modules, convenient management of plug-ins, SDKs and system configuration is achieved, and the operation and maintenance difficulty is reduced.

To provide a template creation support system capable of supporting creation of a template of a flow close to a system configuration desired to be realized by a user.SOLUTION: A template creation support system includes: a first conversion unit that converts each template of a template group into a graph including a node indicating a service and an edge indicating a relation between services based on dependencies between set resources; a second conversion unit that converts an input including information indicating a system configuration desired by a user and operation of each component into the graph composed of a node indicating service and an edge indicating a relation between services; a retrieval unit that retrieves a template of the graph close to the graph converted by the second conversion unit from graphs converted by the first conversion unit from the template group; and an output unit that outputs a setting item set in the template retrieved by the retrieval unit.SELECTED DRAWING: Figure 1

The invention provides an SOA architecture vehicle-cloud integrated communication middleware system and a deployment method, and the system comprises a unified communication interface module which is used for providing a Topic-based publishing / subscribing model communication interface for an application layer, and providing a Method-based client / server model remote service calling interface; the communication abstraction and adaptation module is used for performing unified abstraction and protocol conversion on various heterogeneous physical buses and communication protocols in the vehicle and among vehicle clouds; the system configuration and management module is used for carrying out centralized configuration and management on definition of communication interfaces, mapping relations of communication channels and system operation parameters; the system receives a communication request of an application layer through the unified communication interface module, obtains configuration information through the system configuration and management module, and adapts the communication request to a specific physical bus or a network protocol for transmission through the communication abstraction and adaptation module. According to the system and the deployment method provided by the invention, the service logic of the application layer and the complex communication of the bottom layer are thoroughly decoupled.

The invention discloses an IEC61850 multi-protocol version oriented communication server-side self-adaption method and device, and the method comprises the steps: carrying out the protocol version dynamic recognition, service interface dynamic configuration and service interface dynamic response for IEC61850 standard protocol versions including ED1.0, ED2.0 and ED2.1, and forming a differential processing mechanism for different protocols, and the automatic switching of the ED1.0 / ED2.0 / ED2.1 protocol can be realized. According to the invention, through compatibility adaptive processing of different versions of difference communication services, system configuration complexity caused by protocol version difference and multi-version maintenance cost of device software are reduced, so that diversified requirements of a power system in multi-scene application and internationalized markets are met; and the flexibility of system configuration and the reliability of device operation are improved.

The invention relates to the technical field of industrial control, and discloses an industrial communication protocol adaptation method and system based on OpenHarmony. The method comprises the following steps: performing distributed soft bus deployment on a plurality of industrial devices in an industrial control network to obtain a distributed device connection architecture; carrying out multi-protocol adapter loading on the industrial automation runtime service of the distributed equipment connection architecture to obtain a multi-protocol runtime service instance; performing communication protocol identification and configuration on the plurality of industrial devices according to the multi-protocol runtime service instance to obtain standardized device data; and establishing a data transmission channel according to the standardized device data, and performing global state synchronization and cooperative control instruction distribution on the plurality of industrial devices to generate a distributed cooperative control network. The deployment and maintenance work of the industrial control system is simplified, the accuracy and consistency of system configuration are improved, the risk of manual configuration errors is reduced, and the development cost and maintenance complexity of industrial application are reduced.

A system for AI-supported cybersecurity and regulatory compliance in energy distribution networks, consisting of: a hardware-embedded data acquisition module configured to intercept, capture, and time-stamp operational data streams and to control data traffic from SCADA (Supervisory Control and Data Acquisition) systems, AMI (Advanced Metering Infrastructure) systems, and energy management systems (EMS) via multiple communication protocols without operational latency; an FPGA-based deep packet inspection unit coupled with the data acquisition module, wherein the FPGA firmware is configured to perform line rate filtering, protocol decomposition and metadata extraction of the acquired data and forwards preprocessed packet data to an AI processing unit; an AI processing unit consisting of a multi-core central processing unit (CPU), a dedicated AI accelerator selected from a graphics processing unit (GPU) or a tensor processing unit (TPU), and a volatile memory buffer; a response orchestration module that is communicatively coupled with network management devices and operations controllers, wherein the response orchestration module is configured to perform automated security and compliance remediation measures, including network isolation of compromised segments, enforcement of protocol encryption, and privilege revocation; and an immutable audit logging subsystem configured to record all detected events, compliance assessments, and corrective actions in a blockchain-based distributed ledger, with each log entry cryptographically anchored with a secure hash value and digitally signed with keys stored in a secure hardware enclave.

The invention discloses a singularity-avoiding trajectory planning method for a free floating space mechanical arm, and belongs to the technical field of robot trajectory planning. The method comprises the steps that the expected whole-course tail end position track and posture track of the mechanical arm are obtained; setting a control period and circularly executing; at each control moment, a generalized Jacobian matrix and system singularity measurement are calculated, and whether the system is close to singularity or not is judged; traversing all the possible values of the base postures if the base postures are close to singularity, calculating joint angle states and corresponding singularity measurement which do not change the tail end postures, and searching a system configuration corresponding to the maximum singularity measurement; then, the state of the mechanical arm is reconstructed, and the mechanical arm is made to move to the maximum singularity measurement configuration to be separated from singularity; and calculating the inverse of the generalized Jacobian matrix to obtain velocity inverse kinematics, and further calculating the joint angular velocity and the joint angle at the next moment. According to the method, an accurate trajectory planning effect without introducing any theoretical error is realized while the singularity avoidance capability is ensured.

The invention discloses a configuration drift detection and consistency coordination method during operation of a Changsafety chain, and relates to the technical field of distributed system configuration management, the method comprises the following steps: deploying a main controller and a query-side double container in an Operator controller Pod, setting a client tool and a hierarchical cache in the query-side, and obtaining on-chain configuration by the main controller through a localhost interface; in the Recencile cycle, configuration drift is judged through standardization processing and hash comparison, and a change source is recognized in combination with self-defined resource metadata and chain side change metadata; coordination is executed according to four synchronization modes of CR forcing, chain observation, bandwidth period CR forcing and manual arbitration; according to the scheme, the problems of state fuzziness, error coverage and the like caused by dual fact sources are solved, low-delay detection and flexible coordination are achieved, and configuration consistency during running of the long safety chain is guaranteed.

The invention discloses a container resource prediction method and system based on a graph neural network, and the method comprises the steps: building a Kubernetes-based micro-service system, configuring a monitoring platform, and obtaining a log result through simulating the use of a real user, and constructing a data set; on the basis of the data set, constructing a time series prediction G-Times Net model based on a graph neural network, extracting interrelation characteristics between containers, and mining a periodic rule of container resource use; according to the predicted value of the G-Times Net model, carrying out elastic expansion and contraction judgment on the container resources; according to the method, the topological dependency relationship of real-time change among the containers is dynamically captured through the graph neural network, and comprehensive modeling of the container resource use mode is realized by combining the extraction capability of the TimesNet model on the multi-scale periodic features, so that the defects of a traditional method on spatial-temporal feature conjoint analysis are overcome, and the container resource prediction accuracy is remarkably improved.

The invention discloses a configuration method and system for a network-constructing type energy storage system for suppressing broadband oscillation, and relates to the technical field of new energy power generation grid connection and power system stability control. The invention aims to solve the problems that broadband oscillation is easily caused when a new energy field station is connected into a weak power grid, an existing suppression method affects equipment characteristics or needs additional investment, and netting type energy storage locating and sizing lacks scientific guidance. The method comprises the following steps: firstly, simplifying a system comprising a new energy station, a constructed network type energy storage system and a power grid, then carrying out impedance modeling on the two systems (reserving complete impedance characteristics of energy storage), and judging the stability through an impedance analysis method; and the optimal capacity is determined at a single position, and then the global optimal capacity and the corresponding position are determined by traversing the positions, so that low-cost broadband oscillation suppression is realized.

The invention relates to the field of ship route optimization, discloses a route optimization method and system based on a particle swarm optimization algorithm and geographic information, and is used for providing comprehensive decision support covering route planning, energy scheduling, risk control and carbon emission management for shipping enterprises. Comprising the steps that a commercial decision basic data set integrating geographic information, ship multi-energy system configuration and marine environment forecast data is constructed, and a commercial fractional order parameter set is generated; environment uncertainty is modeled by using a stochastic differential equation, a multi-energy system operation cost function is integrated, and a commercial cost prediction model capable of outputting operation cost probability distribution is formed; and carrying out risk-aware business strategy optimization based on a particle swarm optimization algorithm, and finally generating an executable business decision proposal containing a detailed route trajectory, a speed plan and a multi-energy equipment scheduling strategy. According to the invention, collaborative optimization of route planning and energy management is realized, and economy, safety and environmental protection of ship operation are significantly improved.

A storage system distributes data across multiple nodes, where the data is stored with partial redundancy to meet a predetermined reliability level. The system monitors a number of nodes in the storage system to determine whether a number of nodes changes. Responsive to determining that the number of nodes changes, the system determines whether reliability level of the storage system exceeds the predetermined reliability level by a threshold. Responsive to determining that the reliability level of the storage system exceeds the predetermined reliability level by the threshold, the system adjusts a data storing scheme of the storage system to reduce redundancy and increase available storage capacity in the storage system, while maintaining the predetermined reliability level.

The invention provides a configuration adjustment method of a model training system, and relates to the field of artificial intelligence. Firstly, system performance parameters of a model training system are obtained; the system performance parameters comprise configuration parameters, actual computing power values and hardware performance indexes corresponding to historical training tasks. And inputting the system performance parameter into the first specified large model based on the first cue word project to obtain a target configuration parameter after the to-be-optimized configuration parameter is adjusted. And sorting the target configuration parameters according to the hardware performance indexes to obtain a target configuration sequence. And generating a target training strategy for training the target model according to the target configuration sequence. The full-process automatic adjustment of the configuration parameters of the model training system is realized, the optimization efficiency and the optimization effect of the configuration parameters are improved, and the training efficiency and the resource utilization rate of the model training system are further improved.

The present invention belongs to the technical field of autonomous driving. Disclosed are a method and apparatus for evaluating the compliance of autonomous driving. A specific embodiment of the method comprises: acquiring current traveling data generated by an autonomous driving target vehicle during traveling; acquiring parsing processing corresponding to a preset compliance engine system configuration file; and on the basis of a parsing result, calling a mathematical function library to perform compliance evaluation on the current traveling data, so as to generate a compliance evaluation result. In the present embodiment, a legal language can be converted into logical descriptions and mathematical equivalence relations; and software codes of an embedded language are generated on the basis of the logic and mathematical relations, current traveling data of a target vehicle is then evaluated on the basis of the software codes, and a compliance evaluation result is automatically generated. Thus, the compliance of autonomous driving can be automatically evaluated on the basis of the current traveling data of the target vehicle, and the solution meets the requirements of autonomous driving of the target vehicle, and is also applicable to different scenarios, thereby improving the application universality of the solution.

The invention discloses a vehicle-mounted system safety detection and risk assessment system, which belongs to the technical field of vehicle-mounted network safety, and comprises a vehicle-mounted terminal environment sensing module used for collecting multi-level environment information of a vehicle-mounted system, including system layer information, network layer information and safety layer information; the vehicle-mounted configuration file and communication white list detection module is connected to the vehicle-mounted terminal environment sensing module and is used for establishing and maintaining a safety white list library according to the collected system information, comparing the current configuration file, the dynamic library, the port and the certificate state of the system with the safety white list library through periodic scanning, and sending the comparison result to the vehicle-mounted terminal environment sensing module; detecting configuration abnormity and file tampering events; a vehicle-mounted process and control task analysis module; a communication abnormity detection and code identification module; and a safety evaluation and risk feedback module. According to the invention, all-around monitoring and intelligent analysis of vehicle-mounted system configuration, process behaviors and network communication can be realized, and hidden backdoors, abnormal processes and malicious communication can be effectively identified.

The present specification proposes a method and an apparatus for managing energy information in a next-generation wireless communication system. A next-generation wireless communication system including a 5G system may have defined therein an energy information repository function (EIRP) having a new network function capable of: exposing energy information to an AF; collecting information regarding energy of the AF; and storing and managing the energy information. The EIRF may provide energy information of a UE to the AF of a third party, and the AF may acquire energy information from the 5G system and monitor the acquired energy information. In addition, the AF may perform a system configuration based on energy efficiency, such as charging or restricting a service according to the energy information. Also, by the function, the AF may adjust service provision such as video playback by checking energy source information or carbon emission information.

A textual description of a machine-readable model describing a configuration of the storage system is created. The textual description includes a plurality of textual statements, in which each individual textual statement describes a relationship between a pair of objects of the machine-readable model, or describes a relationship between a given object and a respective value of the given object. The textual statements describing the configuration of the storage system are provided as training input to a large language model to train the large language model to learn the textual description of the storage system configuration. The large language model is then used, by an interactive voice response system to respond to natural language queries about the storage system configuration. The machine-readable model may be implemented using a Java model that is annotated to identify relationships between objects that should be used to generate textual statements describing the storage system configuration.

The present disclosure provides a data storage method, device, electronic equipment and storage medium. The data storage method comprises: in response to a file storage request for a first target data file, obtaining the first target data file to be stored in a target storage system, the target storage system being configured with table metadata, the table metadata indicating storage branch information corresponding to the target storage system, the storage branch information comprising a main branch and at least one experimental branch, the main branch being used to mount data files that have been used for model training and the training results of which meet preset requirements, and the experimental branch being used to mount data files that have not been used for model training; based on the table metadata, determining a first target experimental branch corresponding to the file storage request, and newly creating a first target snapshot corresponding to the first target experimental branch; and based on the first target snapshot, storing the first target data file to a corresponding storage location in the target storage system. The embodiments of the present application can improve the data storage efficiency.

Some embodiments provide systems comprises: a customer database; a product database; a training data database; a customer evaluation system configured to implement one or more machine learning acceptance probability models to identify an acceptance likelihood factor, and determine whether the each respective customer has a corresponding acceptance likelihood factor greater than a likelihood threshold value; and a plurality of point of sale (POS) systems configured to complete sales transactions, obtain customer identifying information, and communicate the customer identifying information to the customer evaluation system; wherein the customer evaluation system is configured to communicate customer information to the payment method offer entity when the customer has an acceptance likelihood factor greater than a likelihood threshold value, receive authorization to present the customer with a payment method offer, and to present the payment method offer.

The invention discloses an intelligent fault diagnosis method and system for pump valve equipment, and relates to the technical field of fault diagnosis, and the method comprises the following steps: collecting operation data; cleaning and verifying the data; key features are extracted; performing fault diagnosis on the operation state of the equipment; a fault diagnosis result is received, and a dynamic early warning model is established in combination with equipment historical data and operation conditions; a knowledge base is configured for storing and managing professional knowledge, historical fault cases, diagnosis rules and expert experience related to the equipment; a user interface is provided for displaying system configuration, operation monitoring, fault alarm and diagnosis results; data generated by the system is stored and managed. According to the invention, by adopting the dynamic threshold early warning model, the early warning threshold can be adaptively adjusted, false alarm and missing alarm are effectively reduced, and the accuracy of fault early warning is remarkably improved, so that equipment maintenance personnel can find potential problems in time, equipment operation with faults is avoided, and the accuracy of fault early warning is improved.

The invention discloses a service system configuration method, an electronic device and a storage medium, and relates to the technical field of storage systems, and the method comprises the steps: introducing an input and output tracking tool to automatically monitor the read-write performance data of each level of a service system, replacing a conventional manual collection and analysis process, and improving the efficiency. And the dependence on professional technicians and the time cost are greatly reduced. Meanwhile, through the application of the pre-training configuration model, the performance optimization experience of the business system in different preset scenes is solidified into the model, and the target configuration file can be quickly matched and generated according to the real-time analysis result, so that the hysteresis and subjectivity of manual evaluation are avoided, and the quick output of the optimization scheme is realized. Through continuous monitoring and analysis of full-link performance data, a bottleneck link can be accurately positioned, targeted adjustment is performed on a service system based on a target configuration file, and the performance bottleneck is fundamentally relieved instead of being temporarily avoided.

A system, method and computer program product control data communication based on a characteristic of an exhaust gas from a vehicle. In the context of a system, an exhaust snorkel is in fluid communication with an exhaust system of the vehicle and configured to direct the exhaust gas from the vehicle to a ventilation system. The system also includes a data transmission system configured to provide for data communication between the vehicle and an offboard computer system. The system further includes a sensor system configured to control operation of the data transmission system based on the characteristic of the exhaust gas.

Real-Time Locating System (RTLS) enabled human to automated vehicle interaction apparatus and methods. Systems may include a control system configured to communicate with RTLS transceivers and anchors within an environment, and autonomous vehicles (AVs) equipped with sensors and RTLS communication transceivers. A control system determines a real-time location of RTLS transceivers (“Tags”) and provides navigation, task, and behavioral instructions to AVs based on location data. RTLS transceivers can be worn by humans or attached to objects, machines, equipment, floorspace, storage bins, or other destination, thereby enabling AVs to locate and travel to humans, objects, or other destination points, perform tasks based on location data, and dynamically alter actions and behaviors. Locating and traveling to destination points may include dynamic destination points based upon movement of a destination human or item. User interactions via RTLS tags may trigger specific actions, enhancing human-automated vehicle collaboration and operational efficiency in diverse environments.

The invention discloses a personalized configuration method for a cloud mobile phone and related equipment, and relates to the technical field of cloud computing, and the method comprises the steps: obtaining user operation behavior data; based on the user operation behavior data, determining a user behavior model through a time sequence analysis model and an association rule mining algorithm; determining a target configuration parameter based on the user behavior model; and controlling the cloud mobile phone system to perform dynamic configuration operation according to the target configuration parameter. The user behavior analysis module is used for collecting multi-dimensional data such as the touch track and the application switching frequency, and the accurate user behavior model is constructed by using the LSTM time sequence model and the Apriori algorithm, so that personalized configuration optimization based on fine-grained user behaviors is realized, and the adaptability of cloud mobile phone system configuration and user behavior habits is effectively improved.

The invention discloses a task plan generation method and system based on a large model, and relates to the technical field of intelligent information scheduling. Comprising a data pre-processing module, a man-hour evaluation module, a task modeling module, a large model reasoning module and a performance analysis module. By obtaining enterprise order data, process man-hour data and system configuration data, hierarchical processing is performed on tasks, process complexity and correction man-hours are calculated, and man-hour demands are generated in combination with equipment utilization and cooperation number of people; the orders are divided into a deduction task plan group, a process dependency graph is constructed, and a large model reasoning module disassembles tasks based on historical task samples to generate sub-task working hours; task allocation is carried out in combination with the special ability and the overall ability of the employees, the processing duration and the optimal value are calculated, and an optimal task plan is screened; the method realizes accurate man-hour prediction, reasonable resource allocation, employee load balancing and task execution efficiency improvement, and is suitable for scenes such as software development, project management and production scheduling.

The invention discloses a hierarchical intelligent multi-type task scheduling system and method, and the system comprises a runtime situation perception analysis module which is used for collecting runtime situation information in a cloud edge collaborative streaming data processing system in real time, and analyzing and extracting runtime situation features; the hierarchical intelligent scheduling decision module is used for generating a system multi-dimensional configuration knob scheduling decision by adopting macro scheduling and micro scheduling according to the situation characteristics during operation; and the stream data processing control module is used for updating system configuration according to the scheduling decision and controlling the analysis processing flow of the stream data on the cloud edge distributed equipment. According to the method, flow data task scheduling of sensing, calculation and control integration is realized based on hierarchical body intelligence, through cooperation of a deep reinforcement learning network and a plurality of independent negative feedback adjustment algorithms, an exponential decision space in a multi-system knob scheduling scene is decomposed into two stages of coarse-grained decision and fine-grained decision, the decision complexity is reduced, and the decision efficiency is improved. And the model convergence difficulty is reduced.

The invention relates to the technical field of substation automation of a power system, discloses a monitoring information table intelligent generation method and system for a substation and a medium, and solves the problems that in the prior art, compiling of a monitoring information table depends on manpower, the efficiency is low, and the accuracy is poor. The method comprises the following steps of: analyzing a system configuration description file of a transformer substation to obtain initial information of signals of the whole substation, simulating to generate a signal displacement message with a unique identifier, and sending the signal displacement message to a station level network; acquiring actual signal data fed back from a telecontrol device and a monitoring host in response to the signal displacement message; taking the unique identifier as a correlation factor, matching the initial information with the fed-back actual signal data, and constructing a multi-source signal correlation mapping table; performing consistency verification and decision fusion on the multi-source description of each signal entry in the association mapping table to generate a unified and accurate signal description; and automatically generating a standardized monitoring information table based on the unified description and the associated signal attributes.