246 results about "Asynchronous communication" patented technology

The invention relates to the technical field of robot scheduling, and discloses a robot task management framework system based on asynchronous communication. The system comprises a task asynchronous analysis module for performing time sequence decoupling on an original task instruction stream of a heterogeneous robot terminal by means of a multi-channel buffer queue to separate out independent executable task units; the resource dynamic mapping module is used for establishing a variable granularity resource allocation mapping table according to cluster real-time load and task resource requirements, and recording various resource dynamic binding relationships; the task priority reconstruction module is used for constructing a directed acyclic graph scheduling topology based on task logic dependence and deadline constraint, and generating a weighted execution sequence through topological sorting; the exception isolation processing module captures exceptions during operation and triggers an isolation strategy; and the cross-node cooperation module guarantees the multi-robot cooperation task state consensus through a distributed consistency protocol. The system is suitable for heterogeneous robot cluster complex task scenes.

The invention discloses a gallery integrated internal production software system based on a modular low-coupling architecture, which is characterized in that a system function is divided into a plurality of modularized modules and the modularized modules are packaged and deployed by a uniform interface, so that the coupling degree between the modules is remarkably reduced, and the problem of global code change caused by module dependence in a traditional single architecture is avoided; direct calling is replaced by an event-driven mechanism, asynchronous communication and decoupling cooperation between modules are realized, and the stability and maintainability of the system during function change or addition are improved; the configuration driving mechanism enables the business process to be dynamically adjusted, different business requirements can be met without modifying a program source code, the plug-in management mechanism provides a standardized third-party extension access channel and supports function loading according to requirements, and the limitation that a traditional system is fixed in function and closed in development is broken through; according to the method, the software can run consistently in Windows, Linux, MacOS and other environments, and the key problems that in the prior art, the coupling degree is high, the expansibility is poor, configuration is not flexible, and the platform adaptation capacity is weak can be effectively solved.

The invention provides a Cholesky decomposition heterogeneous parallel optimization method and system based on an SW architecture, and relates to the technical field of high-performance computing. The method comprises the following steps: performing sub-block division on a symmetric positive definite matrix based on a distributed parallel distribution scheme, and performing iteration to complete matrix decomposition; each sub-block is distributed to different processes through an MPI programming model, data exchange is carried out between the processes through asynchronous communication, and coarse-grained task-level parallel acceleration is carried out; performing two-stage parallel acceleration on four operations in Cholesky decomposition by utilizing the acceleration parallel characteristic of a master core and a slave core of the SW architecture; wherein for GEMM and SYRK operations, column vectors of a matrix are mapped to a slave core array, and columns are divided according to the number of slave cores; the calculation process is optimized through a double-buffering mechanism, vectorization operation and a loop expansion technology, and the parallel efficiency is improved; and for the TRSM operation, the TRSM operation is decomposed into a plurality of TRSV operations, the TRSV operations are allocated to the slave cores for parallel execution, and a circular reading and data broadcasting mode is adopted to reduce data dependence and realize efficient parallel calculation.

The invention discloses a multi-platform cooperative intelligent office management system and a coordination method, and the method comprises the steps: a protocol unification module builds a standardized communication interface with a plurality of heterogeneous office platforms, and converts a document operation instruction of each platform into a unified intermediate protocol format; the multi-platform interactive interface module comprises a cross-platform identity verification unit and an asynchronous communication unit; the file synchronization and version control module adopts an operation conversion algorithm to realize multi-platform real-time collaborative editing; the modification content evaluation module performs agreement evaluation on the modification content of the office file by each platform to obtain an optimal modification scheme; the decision engine module is configured with a dynamic weight distribution algorithm, and an optimal version is generated by integrating user permission levels, historical behavior data and real-time evaluation results; and the feedback learning module optimizes evaluation model parameters by collecting final adoption decision data of the user. The method has the advantages that the problems of protocol isomerism, modification conflict and decision optimization in cross-platform cooperation are effectively solved.

The invention discloses an intelligent building multi-dimensional monitoring system supporting edge computing and cross-terminal collaborative management, and relates to the technical field of intelligent buildings, the intelligent building multi-dimensional monitoring system comprises a multi-area edge monitoring node and an asynchronous communication cloud management platform, the edge node is provided with a lightweight dynamic collaborative engine, a node database and equipment management and control module, and a management and control terminal device; data are collected and standardized, simple / complex events are identified, risk levels are divided, and autonomous networking is carried out to form a temporary collaborative cluster when the risk is high; the data interaction module adopts UDP lightweight protocol low-delay transmission and local retransmission to guarantee data integrity, the cloud platform stores event processing abstracts, analyzes historical data optimization strategies and rules and silently issues in idle periods, the visual module assists monitoring and decision making, the system realizes distributed sensing and collaborative management and control, cloud dependence is reduced, and the real-time performance of the system is improved. The event response efficiency and the resource utilization rate are improved.

The invention provides a file system client kernel mode and user mode communication method based on asynchronous communication. According to the asynchronous communication-based file system client kernel mode and user mode communication method provided by the embodiment of the invention, the context switching overhead of communication between the user mode and the kernel mode can be reduced, the data transmission throughput is improved, the resource utilization rate is optimized through dynamic queue management, and the problem of performance bottleneck in a high-concurrency scene is effectively solved.

The invention relates to a personalized federal learning method for cross-regional vehicle trajectory anomaly detection, which belongs to the technical field of intelligent traffic systems and comprises the following steps: constructing a federal system architecture consisting of a cloud server and a plurality of geographical distributed clients, each client holding local trajectory data; issuing a global model and constructing a double-model structure comprising a messenger model and a personalized model; the client simultaneously trains double models based on local data, and realizes knowledge migration through mutual distillation; protecting gradient information of the messenger model by adopting a differential privacy mechanism; uploading the protected model to a server, and executing asynchronous aggregation weighted according to the number of samples; and repeating the model issuing and local training process until a termination condition is met. The method gives consideration to global generalization and local adaptation, has the characteristics of asynchronous communication, differential privacy protection and the like, and can effectively improve the trajectory anomaly detection performance in data heterogeneous and communication limited environments.

The invention discloses a distributed training method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence. Comprising the following steps: a computing node reads training data, generates a local gradient in combination with a current model parameter, and sends the local gradient and a timestamp during sending to a central aggregation server; the server receives the local gradients from the computing nodes and the timestamps during sending; under the condition that the number of the computational nodes receiving the local gradient is larger than a preset aggregation threshold value, the weight of each computational node is calculated, gradient aggregation is carried out, and a global gradient is obtained; calculating a target learning rate and a target model parameter based on the global gradient; respectively sending the target learning rate and the target model parameter to each computing node; and the node receives the target learning rate and the target model parameter for iterative updating. By adopting an asynchronous communication mechanism and considering the actual performance of each node, the distributed training method which can flexibly adjust each node, is higher in training efficiency and improves the resource utilization rate is provided.

The invention discloses a dual-channel adaptive network stability testing method and system, and belongs to the technical field of computer network testing. The system adopts a dual-channel asynchronous communication architecture in which a control channel and a data channel are physically separated, instructions and state information are transmitted through an independent TCP control channel, and high-speed test data streams are transmitted through a UDP or TCP data channel. The method comprises the following steps: dynamically and adaptively adjusting a timeout parameter based on real-time network delay detection; nanosecond constant interval packet sending control is realized by using a high-precision monotonic clock source and busy waiting compensation mechanism; a packet loss detection, positioning and ACK confirmation mechanism based on the serial number is realized in an application layer; and real-time statistical display and idle detection automatic termination are realized through multi-thread parallel processing. According to the invention, the precision, the stability and the adaptive capability of network testing are remarkably improved, and the method is suitable for long-time stability testing in various scenes such as a high-speed Ethernet, a satellite link, an industrial Internet of Things gateway and the like.

The present invention relates to a communication system and method designed for patients in clinical settings who face challenges using standard communication devices. This system includes a mobile application and associated devices that establish a secure, asynchronous communication channel between clinicians, patients, and their support networks. Authorized users can record and send voice messages and other media, which are automatically played on the patient's device without requiring active operation. The system is tailored for ease of use, accommodating patients with severe physical or cognitive limitations through hands-free operation and simple commands. It adapts to the patient's condition, pausing messages during rest or medical procedures and resuming when appropriate. The system also features cross-linguistic messaging, translating and synthesizing voice messages across languages while maintaining the speaker's voice. Additional features include support for rich media, automatic transcription, and AI-driven content analysis. Secure, encrypted channels ensure privacy, complying with healthcare regulations. This invention enhances emotional connection and support for isolated patients, acting as a virtual visitation tool.

The invention relates to the technical field of calculation, and provides a CFD solution acceleration method and system based on parallel calculation and load dynamic balance. Physical characteristics such as a CFL number and a residual error are quantified into load indexes, so that a load balancing decision and a flow field evolution rule are tightly coupled; by adopting an asynchronous communication overlapping framework deeply coupled with a CFD solver, blocked communication waiting time is converted into effective calculation time, and communication delay is systematically hidden; based on an incremental grid migration strategy of real-time load evaluation, high-load grid blocks in a hotspot process can be intelligently identified and migrated, and differentiation and high-efficiency utilization of computing power are realized.

The invention discloses an RDMA asynchronous communication optimization method and system based on a lock-free queue, a medium and a processor, and relates to the technical field of remote communication. The method comprises the following steps: constructing a lock-free annular buffer area at an edge node, registering the lock-free annular buffer area as an RDMA memory area, and configuring a queue and a thread pool; the collection thread concurrently writes data, and the RDMA submission thread asynchronously completes remote transmission based on a buffer area state; and the queue processing thread performs closed-loop linkage transmission and buffer area states through'batch polling-result analysis-state synchronization-exception processing ', and dynamically adjusts the buffer area and queue parameter optimization performance at the same time. The problems that an existing RDMA scheme is poor in thread cooperation, weak in resource adaptation, not timely in state linkage and the like are solved, transmission delay and CPU overhead are greatly reduced, communication stability and the resource utilization rate are improved, and the method is suitable for edge computing and other high-concurrency data interaction scenes.

The invention discloses a hybrid expert model training optimization method based on expert calculation load balancing scheduling, and the method comprises the steps: firstly predicting current iteration global expert load data, and obtaining sampling data; and secondly, designing a multi-dimensional performance perception expert placement evaluation method, and realizing quantitative comparison and decision in a stage of searching an expert placement scheme by converting multi-dimensional communication and calculation into a unified time delay index. And then designing an expert placement strategy by adopting an expert grouping search algorithm of dynamic load feature perception and a matching algorithm of expert grouping and resource perception based on the sampling data and an expert placement evaluation method. Finally, on the basis of an expert placement strategy, an asynchronous communication strategy is adopted to implement expert and optimizer parameter scheduling, and training optimization is completed. According to the method, by improving the computing load balance and asynchronous communication concealment between the devices, synchronous waiting is reduced, and the training efficiency and the overall performance of the hybrid expert model are effectively enhanced.

The invention discloses a system manager, an error data processing method, error data processing equipment and a program product, and relates to the technical field of data process.A processor is used for writing error data corresponding to a system error into an error information storage area when the system error is detected, and a controller is used for writing the error data corresponding to the system error into the error information storage area when the system error is detected. And the alarm module is used for reading the error data stored in the error information storage area and generating alarm information when the error data meets a preset condition, so that transmission and efficient asynchronous communication of the error data are realized through the error information storage area and the interrupt register, the preset condition is added, and the alarm information is triggered when the preset condition is met. The processor is prevented from entering a system management mode, meanwhile, performance jitter of an operating system caused by frequent system management interruption is reduced, and the efficiency of processing error data by the system is improved.

The invention relates to the technical field of computer vision and edge computing, and discloses a multi-computing-power collaborative video structured analysis method, which comprises the following steps of: acquiring a plurality of paths of original video streams, and synchronously decoding the plurality of paths of original video streams; gradient analysis is adopted to evaluate the decoded multiple paths of original video streams, and a preprocessing algorithm combination is selected based on a quality feature vector; establishing a data transmission channel, and adopting an asynchronous communication protocol and a multi-level cache system; performing content complexity analysis, and performing model matching according to the content complexity analysis to obtain a scheduling decision; carrying out distributed deployment, and carrying out pipeline reasoning on the deployed model; pipeline reasoning results are fused, and consistency constraint verification is carried out on fusion results; optimizing system configuration parameters according to a video structured analysis result to realize video structured analysis; the real-time performance, the accuracy and the system stability of video analysis are improved.

The invention provides a number card distribution system based on message middleware, relates to the field of data management, and solves the technical problem of high data storage security risk of an existing number card distribution system. The system comprises a message center module which is used for processing asynchronous communication and data transmission in the system by adopting a distributed message middleware cluster; the data security module is used for managing distribution data of each region by adopting a data fragmentation storage mechanism; and the demand prediction module is used for predicting the number card demand quantity of the next period according to the sales data and the demographic data of each region, and guiding the formulation of a sales strategy of the next period. The method and the device are used in the whole-process management process of the number card distribution service.

The invention relates to a localized intelligent adaptation system and method based on multi-agent interaction, the system is realized based on a large language model and multi-agent cooperation, and the system comprises an offline knowledge extraction module, a diagnosis prompt generation module, a multi-agent cooperation diagnosis module and a man-machine cooperation module. Wherein the offline knowledge extraction module is used for extracting knowledge blocks and dynamically registering an API (Application Program Interface) of an operation and maintenance tool into the system; the diagnosis prompt generation module is used for screening out most relevant knowledge blocks and operation and maintenance tools; the multi-agent cooperative diagnosis module is used for cooperatively generating a diagnosis report among the agents based on asynchronous communication and a cross review mechanism; and the man-machine cooperation module realizes cooperation of manual auditing and automatic repairing through a natural language dialogue interface and a work order system. The invention aims to improve the intelligent level of fault diagnosis and repair through the following innovation breakthrough, and better meet the requirements of localization adaptation.

The invention discloses an Internet of Vehicles low-delay federated learning method based on semi-asynchronous communication, and the method comprises the steps: constructing a vehicle-road cloud cooperative federated learning framework and a system performance model, building a federated learning training time delay optimization model, minimizing the overall training time delay, and meeting the vehicle energy consumption upper limit and global model precision constraint conditions; a multi-dimensional priority dynamic vehicle selection mechanism is realized, and probability sampling is carried out by using a roulette selection algorithm; a vehicle-RSU federated learning strategy based on semi-asynchronous communication and knowledge distillation optimizes the problem of lagging behind and the problem of model obsolessness; a cloud model aggregation opportunity is optimized based on a model difference metric and an adaptive cloud aggregation strategy of a dynamic threshold trigger mechanism. According to the method, collaborative optimization is carried out on multiple levels of equipment selection, intra-layer communication aggregation, old model processing, inter-layer aggregation triggering and the like, so that the overall training time delay of the Internet of Vehicles federated learning system can be effectively reduced on the premise of satisfying model precision and equipment energy consumption constraints.

The invention belongs to the technical field of data processing, and particularly relates to an efficient and stable code-scanning ordering electricity digital data processing and storage system. Comprising a user terminal, a front-end access module, an event bus module, a core service logic processing module, a high-performance data persistence module, a real-time data query and analysis module and a system fault-tolerant and elastic telescopic module. And high concurrent processing, hierarchical storage and fault-tolerant scaling are realized. Asynchronous communication among the modules is realized by introducing an event bus module, and real-time processing of high-concurrency requests and rear-end data persistence operation are decoupled. The front-end request is quickly converted into an event to be merged into a queue, so that the direct pressure of back-end service is avoided, the high concurrency far exceeding that of a traditional synchronization architecture can be borne, and the problems of slow system response and order loss in peak hours are effectively solved.

The invention provides a collaborative management method and system for a digital twinning and optical transport network management and control system, and the system comprises a multidirectional interface architecture of a physical layer southbound interface gateway, an application layer northbound interface gateway and a digital twinning east-west interface gateway, and supports data interaction and instruction transmission among a physical layer, an application layer and a digital twinning system. The method covers acquisition and processing of real-time data streams, full life cycle management of digital twin, simulation deduction and decision optimization, asynchronous communication and identity verification and authority management. According to the method, closed-loop control from user intention definition, simulation deduction, configuration issuing, real-time monitoring to optimization adjustment is realized through a multidirectional interface coordination mechanism, the coordination efficiency and control precision between systems are remarkably improved, the requirements of an optical transport network for real-time, dynamic and high-concurrency data processing are met, and the method is suitable for popularization and application. Cooperative operation in a multi-manufacturer and multi-device environment is supported, and an efficient and flexible solution is provided for intelligent management and optimization of the optical transmission network.

The invention discloses a nursing information online management system based on multi-source data fusion, which belongs to the field of nursing and comprises modules of data acquisition, access, standardization, compatible processing, storage, privacy protection, intelligent fusion and the like. The system collects multi-protocol data through edge nodes, uniformly converts the multi-protocol data into an intermediate format and performs standardized processing, so that semantic consistency and structure unification are realized. A structure mapping and primary key synchronization mechanism is adopted, and a heterogeneous system data barrier is broken through. Nursing information storage is based on a column database, and performance and reliability are enhanced by combining cold and hot stratification and replica redundancy. The encryption module supports field-level encryption and auditing traceability, and data privacy is guaranteed. The fusion engine utilizes a graph neural network and time sequence modeling to aggregate multi-maintenance information and predict risks. Asynchronous communication and a Protobuf protocol are adopted among the modules, so that low-delay and high-throughput data flow is realized. The intelligent nursing management system has the beneficial effects that the intelligence, precision and safety of nursing management are remarkably improved.

The invention discloses a cooperative control method for a multi-domain unmanned system. The method comprises the following steps: acquiring an original sensor sequence and a late message set; according to the original sensor sequence, calculating a dominant function and anti-fact regret to obtain a value signal; generating a time delay weight according to the late message set; constructing a space-time source item based on the value signal and the time delay weight; constructing a neural pheromone field by solving partial differential equation dynamics by using space-time source items and pheromone field parameters; under the guidance of the neural pheromone field, sampling to generate a candidate path set; and selecting a cooperative path from the candidate path set for the unmanned system to execute. According to the method, the problems of value characterization and timeliness under asynchronous communication are solved, deep coupling of a decision strategy and a physical model is realized, and the robustness and the adaptive ability of collaborative decision are improved.

The invention discloses an industrial robot master control system which comprises a robot hardware abstraction layer, a real-time control algorithm plug-in layer and a non-real-time request corresponding layer, non-blocking asynchronous communication between different modules is achieved through a shared memory, and the robot hardware abstraction layer is used for shielding hardware differences generated due to different robot types. The high reusability of the robot master controller is realized; the real-time control algorithm plug-in layer is used for realizing the separation of the real-time control algorithm layer and the hardware abstraction layer and realizing the overall control of the robot; and the non-real-time request response layer is used for realizing interaction and communication capabilities of the robot and an external function module. The invention also provides a plurality of standardized system development interfaces, so that the system can form a unified development specification, a communication specification and a development mode under software and hardware decoupling. The system architecture provided by the invention is easy to realize in an industrial robot system, the mobility, compatibility and stability of software are improved through modular design, and the system architecture has relatively high applicability.

A method for authenticated asset assessment is provided. The method includes authenticating, by a scan assistant, a scan engine with the scan assistant for executing one or more scan operations on the asset to determine a state of the asset. The asset includes at least one computing resource. The method also includes receiving, by the scan assistant, a plurality of scan requests associated with the one or more scan operations from the scan engine. The method further includes responding, by the scan assistant, to at least one scan request of the plurality of scan requests by transmitting one or more scan responses to the scan engine after receiving the plurality of scan requests. The scan assistant and the scan engine implement an asynchronous communication protocol that permits the scan engine to send the scan requests without waiting for scan responses for previous scan requests.

A system and method for managing communication transitions between synchronous and asynchronous communication channels across diverse communication interfaces is disclosed. The system comprises a communication management server implementing an AI orchestration framework that coordinates bidirectional transitions across multiple communication channels while maintaining contextual integrity and communication privacy. When a primary communication device is unavailable to attend to an incoming communication, an AI communication agent may initiate a synchronous communication channel with the initial communication source. Upon detecting a mode switch opportunity, a communication mode orchestrator generates an asynchronous communication channel using an optimal transducer interface between the AI communication agent and the secondary communication device. The communication mode orchestrator enables transitions between the asynchronous and synchronous communication channels to relay selective information. A conversation state manager preserves distinct context boundaries between the communication channels, allowing for sophisticated multi-modal communication routing and management.

The invention provides a distributed futures transaction service system of a stateless micro-service architecture based on RestfulApi. The system comprises a front routing service, a relay transaction service, a market information acquisition service, a market information service, a tidb distributed database and a codis memory distributed database. The front routing service provides a stateless interface based on Restful Api, and supports multi-node parallel expansion and dynamic load adjustment; the relay transaction service is integrated with mainstream futures sdk and interacts with the counter system through an asynchronous communication mechanism; the market information acquisition service acquires dynamic market information data and writes the dynamic market information data into the codis memory distributed database; the market information service reads the dynamic market information data and externally provides an api interface; the tidb distributed database is used for storing user account information, and the codis memory distributed database is used for storing entrustment return, transaction return and dynamic market data. All the modules cooperate to realize high-concurrency, low-delay, high-availability and multi-mode futures transaction request processing and return information management.

The invention discloses a compilation optimization method and device for accelerating Attention calculation, and belongs to the field of compilation optimizing.The method comprises the following steps that multiple scheduling strategies are generated according to the number, shape and Attention type of input matrixes and a target hardware platform; defining a cost function, evaluating time and space overhead of each scheduling strategy, and selecting an optimal strategy based on hardware platform characteristics and user requirements; the method comprises the following steps of: performing multi-core parallel division on input data in sequence length and Head dimension, and reducing delay through asynchronous communication overlapping calculation and communication; in a training stage, a random floating point matrix generated by hardware and an attention weight are used for carrying out Hadamard product operation, and a Dropout function is realized. According to the method, the characteristics of different hardware platforms can be flexibly adapted through the generated Attention operator template, excellent performance can be achieved under various shapes, and efficient data division is achieved by optimizing balance between calculation and communication.

The invention discloses a local inter-process communication method, device and equipment and a storage medium, relates to the technical field of computers, is applied to a first preset platform, and comprises the following steps: if in an asynchronous communication mode at present, executing an asynchronous communication mode through an asynchronous input / output programming library, an I / O object and a local operating system; triggering asynchronous connection between a first local process and a second local process of a second preset platform; after the asynchronous connection is completed, binary serialization format conversion and packaging are carried out on data transmitted in the asynchronous input and output operation execution process based on a preset packaging algorithm, and a determined operation result is stored in a target queue; and performing operation result reading on the target queue through an I / O execution context component and a preset callback function until asynchronous input and output operation in an uncompleted state does not exist between the first local process and the second local process, and completing communication operation. According to the method and the device, cross-platform and asynchronous local process communication can be effectively realized.

The invention relates to a three-dimensional visual synthesis system based on heterogeneous collaboration and screen alignment fusion, which is characterized in that a master control system generates complete viewpoint configuration information of a current scene acquired by an image acquisition device, and the complete viewpoint configuration information is used as a single data source and is simultaneously distributed to a graphic processing unit and a neural rendering coprocessor of the master control system; synchronous starting and parallel execution of the two heterogeneous rendering pipelines are achieved. And in combination with a subsequent screen alignment fusion mechanism, an end-to-end collaboration framework with low delay, low coupling and high coordination is constructed, and the key problem of real-time integration of high-fidelity contents is effectively solved. On the premise of not depending on a traditional deep buffer area or geometric alignment, high-fidelity visual content generated by special hardware acceleration and a dynamic environment of a main control system are efficiently fused, and complex effects such as lightweight asynchronous communication and real-time shadow are supported. Therefore, multiple bottlenecks in the aspects of real-time performance, compatibility and engineering deployment in the prior art are broken through.

The invention discloses an edge federated learning communication method combining dynamic sampling and bandwidth optimization, which relates to the technical field of edge computing, and comprises the following steps of: collecting the sample size, training time and network bandwidth of terminal equipment through a monitoring tool, classifying and extracting bandwidth labels after preprocessing, and optimizing by adopting dynamic sampling and asynchronous communication to obtain an edge federated learning result. Gradient compression based on bandwidth perception is combined, important gradients are preferentially transmitted, convergence speed is evaluated, resource collaboration is optimized, an MEC server asynchronously distributes parameters, a queue is managed and updated, and a model is aggregated. By combining dynamic sampling and bandwidth optimization, the edge federated learning communication efficiency is remarkably improved, the transmission cost is reduced, the sampling strategy is dynamically adjusted, the important gradient is preferentially transmitted, the model convergence is accelerated, and the equipment resource collaboration and asynchronous parameter distribution and queue management of the MEC server are optimized; the timeliness and accuracy of model updating are ensured, and the practicability and flexibility of edge learning are enhanced.