107 results about "System Fault Tolerance" patented technology

The invention discloses a cooperative autonomous synchronous networking method for a multi-networking type energy storage converter without communication interconnection. The method comprises the following steps: S1, state perception and estimation based on local measurement: acquiring local electrical parameters in real time by using a sensor, and performing state estimation through an improved Kalman filtering algorithm and a local dynamic model; s2, a cooperation mechanism of the virtual synchronous machine and droop control: combining the virtual synchronous machine with the droop control mechanism, and realizing automatic power adjustment and cooperation work by setting a virtual inertia, a damping coefficient and a droop coefficient; s3, self-adaptive synchronization algorithm: based on the local state estimation and the output of the virtual synchronous machine, adjusting the phase and frequency of the output voltage, and dynamically adjusting synchronization parameters according to the state of the power grid; and S4, detecting a fault by monitoring local electrical parameters and a self state in real time, and automatically adjusting a control strategy and realizing system fault tolerance when the fault occurs.

The invention relates to the technical field of mine safety monitoring, and discloses a mine high-temperature heat damage monitoring system based on multi-mode Internet of Things data, and the system comprises a prediction and control integrated system architecture module which constructs a prediction and control integrated system architecture, and builds a three-layer PCIS architecture of a perception layer, a prediction layer and a control layer; the thermal field and flow field combined optimizer module is used for constructing a thermal field and flow field combined optimizer and realizing direct coupling of a prediction model and a control algorithm; the self-adaptive anti-interference control mechanism module is used for implementing a self-adaptive anti-interference control mechanism and realizing system fault tolerance through a fault mode library and dynamic reconstruction; the performance self-optimization module is used for implementing system performance self-optimization and continuously improving the system performance through incremental learning and knowledge migration; according to the method, through multi-modal data fusion and the space-time diagram convolutional network, the heat damage prediction precision is improved, the prediction time range is expanded, and more sufficient response time is provided for heat damage prevention and control.

The invention provides a complex task multi-agent collaborative disassembling method and system based on a business process, and relates to the technical field of artificial intelligence, and the method comprises the steps: constructing a graph through analyzing a business process document, matching a complex task with a process node, identifying a closed loop dependence path, and selecting an agent based on a constraint logic formula. And establishing a causal tracing chain to process abnormal conditions, and performing semantic alignment to ensure data transmission between subtasks. According to the method, the automation degree and the execution efficiency of multi-agent cooperative processing of complex tasks are improved, and the fault-tolerant capability of the system and the reliability of task completion are enhanced.

The invention discloses a fault fallback method and device in a multi-agent cooperative system, equipment and a medium, and the method comprises the steps: recognizing a plurality of target agents used for jointly executing a target transaction in the multi-agent cooperative system according to a target transaction operation request; the target agent is used for executing one atomic operation in the target transaction; after a transaction submission instruction is sent to each target agent which completes preparation in the preparation stage, whether an execution fault occurs in the execution process of the target transaction is monitored in real time in the submission stage; when the target execution fault is detected, at least one fault agent generating the target execution fault is positioned in the target agents; according to the fault agent, the local or complete rollback operation of the target transaction in the submission stage is executed, and according to the technical scheme of the embodiment of the invention, by monitoring multi-agent transaction execution in real time, accurately positioning the fault node and supporting the local or global rollback operation, the fault-tolerant capability of the system is remarkably improved, and the transaction consistency is also ensured.

The present invention discloses an e-commerce management method and system based on big data analysis, which relates to the field of data management technology. The present invention realizes the stable operation and efficient data transmission of the e-commerce platform in a complex network environment by introducing big data analysis and dynamic slicing scheduling mechanism. With the help of real-time evaluation and classification processing of the network status of user terminals, the present invention can intelligently adapt to different types of e-commerce business needs, thereby realizing personalized transmission strategies, and effectively alleviates the network congestion problem during the promotion period through time-series differential encoding and interpolation compensation of high-priority data such as flash sales, thereby improving the response speed and user experience of key businesses. Combined with dynamic delay floating analysis and packet loss rate evolution judgment, the present invention can adaptively adjust the data sending rhythm, ensure the smooth scheduling of slice data when bandwidth fluctuates, and significantly improve business continuity and system fault tolerance.

The invention discloses a weak current intelligent building control management system, which comprises a plurality of groups of different types of sensors, a data collection module, a data storage module, a data comparison and elimination module, an emergency management module and a control center. A plurality of groups of different types of sensors are distributed in each key area of a building, all-directional environment monitoring is ensured, preprocessing steps such as Kalman filtering and mean value filling are introduced to improve data quality, data storage adopts a block chain technology based on Hyperledger Fabric, data cannot be tampered and high security is realized, and the method is suitable for large-scale popularization and application. And the data comparison and elimination module verifies the sensor data in multiple dimensions by using transverse comparison, longitudinal comparison, logic verification and redundancy cross validation, so that the accuracy and consistency are improved, and the fault-tolerant and anti-interference capabilities of the system are enhanced.

The invention provides an automatic fault-tolerant propulsion method and system for task execution abnormity and a storage medium, and relates to the technical field of distributed system fault-tolerant control, and the method comprises the steps: task dynamic arrangement: arranging tasks into a serial, parallel or dependent execution mode according to a preset dynamic rule, and realizing task trigger execution through an asynchronous thread pool; performing process monitoring, adding a monitoring annotation to an execution method of each task by using an AOP tangent, and capturing a task execution state in real time; performing abnormal grading processing, and executing a strategy according to a pre-configured three-level processing channel; spreading a dependency state, and automatically updating an associated task state based on a dependency relationship among the tasks: when an upstream task fails, pausing a downstream dependency task and marking the downstream dependency task as a waiting state, and continuing to execute a non-dependency task; and performing global state statistics, calculating a global state in real time through a task state algorithm, if all tasks are completed, marking the tasks as completed, if abnormal tasks exist, marking the tasks as abnormal, and triggering root cause analysis.

The invention relates to the technical field of industrial robot control, and discloses a single-connecting-rod mechanical arm system fault-tolerant asynchronous control method based on double-variable decision, which comprises the following steps: establishing a semi-Markov jump system dynamic model for describing the operating characteristics of a single-connecting-rod mechanical arm; based on the dynamic model, designing a fault-tolerant asynchronous controller structure based on a double-variable decision and an experience-machine cooperative operation strategy; establishing sufficient conditions which enable the closed-loop system to be randomly stable and meet H infinity performance indexes; and the numerical value of the gain of the machine controller is obtained by solving the linear matrix inequality set, and a final control law is generated to conduct fault-tolerant asynchronous control on the single-connecting-rod mechanical arm. According to the fault-tolerant asynchronous control method for the mechanical arm, fault-tolerant asynchronous control of the mechanical arm is achieved through a double-variable decision and an experience-machine cooperation strategy in combination with modal transfer rate boundary processing, and the random stability and the H-infinity performance of the system are guaranteed under the modal mismatching and fault working conditions.

The invention relates to a remote firmware updating optimization method for an electric bicycle charging pile, relates to the technical field of remote firmware updating of Internet of Things equipment, and solves the problem of transmission reliability in a weak network environment by optimizing a data block size and a transmission protocol according to real-time network quality through a dynamic block transmission strategy and a protocol adaptive switching mechanism. Constructing an end-to-end security protection system by adopting a multi-level security verification mechanism and combining frame verification, file hash and digital signature hierarchical verification; a hardware compatibility precise matching algorithm is designed, and based on structured version number interval comparison and a double-partition firmware updating mechanism, the adaptability of a firmware version and hardware is ensured; and establishing an exception monitoring and closed-loop recovery system, and realizing full-process self-healing after updating failure through an error classification model, a recovery strategy routing table and intelligent state rollback. The method improves the transmission success rate of firmware updating, the safety protection level and the system fault-tolerant capability, and is suitable for a remote operation and maintenance scene of a large-scale charging pile group.

The present invention discloses an intelligent scheduling method for a comprehensive virtual power plant, which relates to the technical field of intelligent scheduling of power plants. By deploying a high-concurrency acquisition module on the edge side, redundant filtering and unified timing calibration are performed on multi-node sensor data such as cold and hot energy stations and energy storage equipment to generate high-quality timing fusion sequences and screen schedulable resources. An error dynamic evaluation mechanism is used to achieve online model correction. Aiming at economic, reliability, and environmental protection goals, an improved particle swarm algorithm is used to generate a multi-stage scheduling strategy, and the optimal instructions are output in combination with equipment constraints. Deviations are evaluated through priority control and real-time monitoring indicators to trigger rolling corrections and backup strategies, achieve equipment-level fault risk quantification and self-healing control, quickly isolate anomalies, and activate redundant resources. Through data-prediction-scheduling-execution closed-loop collaboration, resource utilization, scheduling accuracy, and system fault tolerance are significantly improved, and the scheduling capability of heterogeneous resources is enhanced.

The invention discloses a group scheduling control method and system for a PCS energy storage system, relates to the technical field of group scheduling of energy storage systems, and solves the technical problems of insufficient SOC balance regulation and control accuracy and weak capacity proportion distribution fault-tolerant capability. The SOH correction coefficient is accurately calculated through the linear relation, it is ensured that the PCS with the high health degree and the large capacity preferentially undertakes the balancing task, the weak health battery is effectively protected, the cycle life of the battery is prolonged, multiple screening constraints of the available PCS are defined, and according to the size relation between the exceeding power and the total redundant power, a capacity proportion or redundant power proportion distribution strategy is adopted, so that the capacity of the PCS is effectively protected. Reasonable power distribution and no equipment overload risk are ensured, the power distribution deviation after the fault of a single PCS can be reduced, and the fault-tolerant response speed of the system is improved.

The invention provides a triple redundant data synchronization method and system based on dynamic priority weighting. The method comprises the following steps: collecting multi-source data; calculating a health degree index of each processor module according to the multi-source data; calculating the dynamic weight of each processor module according to the health degree index of each processor module, and normalizing the dynamic weight; calculating the weighted support degree of the input value according to the input value of the processor module and the normalized dynamic weight; according to the weighted support degree, voting and selecting an input value as a voting output of a three-system processor module; and if the normalized dynamic weight of a certain processor module is continuously lower than a predefined threshold value for a preset number of cycles, automatically isolating the processor module. According to the scheme provided by the invention, the voting weight can be dynamically adjusted by evaluating the health degree of the module in real time, and the system fault-tolerant capability and the resource utilization rate are improved by combining weighted voting and a fault pre-isolation mechanism.

The invention provides a multi-scene composite scheduling method and system for heterogeneous unmanned aerial vehicles, and the method comprises the steps: collecting the flight demand data and flight resource data of a heterogeneous unmanned aerial vehicle cluster in real time, and constructing an unmanned aerial vehicle global resource pool; calculating a matching degree between each flight demand and each flight resource in the unmanned aerial vehicle global resource pool; and constructing a multi-target composite optimization model based on the matching degree, and solving the multi-target composite optimization model to obtain an optimal scheduling result of the unmanned aerial vehicle. According to the invention, for the demands of multi-task concurrence, dynamic environment change and resource collaborative allocation in logistics distribution, forest and equipment inspection, emergency disaster rescue, agricultural plant protection and wide-area monitoring scenes, the matching degree of a flight task and an idle unmanned aerial vehicle is calculated in a multi-dimensional manner, and the tasks are dynamically allocated; the method is suitable for efficient matching of heterogeneous computing resources and diversified tasks of a large-scale unmanned aerial vehicle cluster so as to realize collaborative improvement of global scheduling efficiency and system fault tolerance.

The invention discloses an employee assessment management method and system based on a cloud platform, and particularly relates to the technical field of human resource management.The method comprises the steps that attendance coordinate data, customer evaluation star-level scores and sales order completion quantity are collected in real time through a real-name account system, and a multi-source work data set is generated through abnormal value filtering and sliding window mean value processing; dynamically adjusting the ratio of the customer evaluation weight to the attendance weight, and constructing a five-level achievement step based on extreme value difference equal-ratio division; extracting historical threshold data according to the number of times of achievement unlocking to generate a calibration evaluation benchmark, and verifying and triggering a cross-end game reward instruction in combination with a double-end timestamp difference value; and aligning a re-judgment achievement condition through a timestamp, and sending a virtual asset increment update packet to realize cross-end state synchronization. According to the method, the dynamic adaptive capacity of an evaluation system to service fluctuation is improved, the association accuracy of achievement excitation and work performance is enhanced, the problem of misjudgment caused by asynchronous transmission of data is solved, and the objectivity of an evaluation result and the fault tolerance of the system are ensured.

The invention discloses a multi-modal stability identification and evaluation method and system for a transformer substation monitoring system. The method comprises the following steps: evaluating static model vulnerabilities in a system configuration file based on the transformer substation monitoring system; dynamically linking a transformer substation monitoring system through an application system, performing application function test on the monitoring system by utilizing a dynamic linkage test case, and performing dynamic vulnerability evaluation on the model; and monitoring system application function module faults through verification function logic, memory leakage, alarm coverage rate and system fault tolerance verification, and carrying out positioning inversion. Technical difficulties existing in application scenes such as equipment research and development, network access detection, transformer substation design, factory joint debugging, field debugging, operation and maintenance and the like of an intelligent transformer substation monitoring system can be taken as entry points, and model vulnerability detection, data flow section detection and function and performance defect testing can be carried out; and a defect panoramic evaluation means suitable for a novel power system intelligent substation monitoring system is formed.

This invention provides a multi-agent cooperative underwater logistics system and method based on reinforcement learning, applicable to the fields of underwater robot cooperative control and intelligent logistics technology. The system integrates six modules: task management, multimodal communication, cooperative localization, path planning, energy management, and fault handling. Through a dynamic switching mechanism in multimodal communication, it adaptively selects between acoustic, optical, and magnetic induction modes to ensure communication reliability in underwater environments. A distributed cooperative localization method based on dynamic weights is employed, optimizing weight allocation by considering communication quality, battery power, and computing power to achieve cooperative localization. A multi-agent reinforcement learning controller with a multi-branch attention mechanism is introduced to achieve real-time obstacle avoidance, formation maintenance, and task-oriented cooperative path planning. An intelligent charging strategy based on multi-level battery thresholds and task urgency supports continuous system operation. A sliding window fault detection and adaptive task reassignment mechanism enhance the system's fault tolerance and robustness.

The application provides a SINS and GNSS combined navigation system fault-tolerant method based on an LSTM neural network, and a set of fault detection and system fault-tolerant method based on an LSTM neural network auxiliary is provided for sudden faults and slowly changing faults in a SINS / GNSS loosely coupled navigation system. A new information Mahalanobis distance auxiliary chi-square test algorithm is used to detect the sudden faults existing in the system in real time, and a sequential probability ratio algorithm is used to detect the slowly changing faults existing in the system. Robust Kalman filtering based on M estimation is used to complete the robustness enhancement of the system, thereby effectively inhibiting the influence of sudden faults on the system. The LSTM neural network is used in the form of replacement to effectively inhibit the influence of slowly changing faults on the system, and signal repair is realized. Through detection and fault tolerance of the two kinds of faults existing in the GNSS signal, the precision of the combined navigation positioning is improved.

The invention discloses a driving circuit with IGBT (Insulated Gate Bipolar Translator) fault diagnosis and protection, which can realize synchronous and independent control driving according to driving requirements and module faults through a switchable driving circuit. The fault detection circuit detects the operation state information of the power module to judge whether the module has a fault and judge the fault type at the same time, and executes a protection strategy. When a plurality of IGBTs connected in parallel work at the same time, a plurality of power modules are driven to work at the same time through the push-pull amplification circuit post-stage. When a certain module breaks down but still needs small current output in a short time, single power module output can be switched, meanwhile, the three-phase driving mode is switched to single module output, and output consistency is guaranteed. The method solves the problems that a parallel IGBT system is poor in fault tolerance, high in fault misjudgment rate, insufficient in long-term reliability and the like, is suitable for the fields with high reliability requirements, such as new energy automobiles, aerospace power supplies and the like, and has industrialization popularization potential.

Disclosed are a method for initializing a controller area network interface, an electronic device, and a robot. The method for initializing a controller area network interface provided by the present disclosure is suitable for interface initialization in the CAN bus communication scenario of an industrial robot. By adopting a multi-source hierarchical configuration analysis mechanism, the priority of configuration sources such as environment variables and command line parameters is determined, CAN interface zero-configuration deployment is achieved, and the configuration flexibility and environment adaptation capability are greatly improved. By introducing a state-aware redundant configuration skipping mechanism, the current state of the interface is queried during initialization, unnecessary repeated operations are skipped, hardware loss and initialization delay are reduced, and system startup efficiency is improved. The method has a graceful degradation strategy, and in a multi-interface scenario, the failure of partial interface initialization does not block the overall service startup, thereby improving the system fault tolerance and operation stability. Meanwhile, by adopting an initialization strategy with fixed interval retries, the method avoids the endless loop caused by the failure of initialization due to temporary faults.

The invention relates to a system fault-tolerant degree estimation method considering professional performance, belongs to the technical field of fault-tolerant analysis, and solves the problem that the actual fault-tolerant capability of a system under different degradation levels is difficult to accurately evaluate due to the lack of comprehensive consideration on the degradation degree of professional performance of the system in the prior art. The system fault tolerance estimation method comprises the following specific steps: step 1, constructing a professional performance margin model of a system according to a subject crossover equation, a degradation equation and a margin equation; step 2, acquiring first wearing time according to professional performance allowance of the system; step 3, obtaining professional performance fault tolerance of the system based on the reliable degradation time range of the system determined during first wearing; and 4, carrying out approximate solution on the professional performance fault tolerance of the system to obtain the professional performance fault tolerance concerning the degradation time under the discrete condition.

The invention relates to a system fault tolerance estimation method based on a system component structure, belongs to the technical field of fault tolerance analysis, and solves the problems that in the prior art, a systematic evaluation method for fault tolerance is lacked, and an evaluation result is inaccurate. The system fault tolerance estimation method comprises the following specific steps: step 1, constructing a component structure-oriented system directed graph; and 2, based on the component structure-oriented system directed graph, the fault tolerance of the system structure is obtained, the system fault tolerance estimation method quantifies the influence of component errors on the fault tolerance of the system from the perspective of functional logic, and the fault tolerance of the system can be evaluated more accurately.

The present invention discloses a data interaction system between an unmanned road sweeper and a cloud platform based on hybrid encryption, which specifically relates to the field of communication interaction information security technology, including an authority authentication module, a data encryption module, an information processing module, a master-slave authentication control module, a horizontal trust management module and a communication scheduling module. It dynamically matches encryption strategies and key templates through task scoring and mapping models, supports offline identity authentication, horizontal trust signatures and channel switching mechanisms, and improves the security of data transmission, system fault tolerance and collaborative reliability in scenarios such as task switching and network anomalies. The present invention implements a task-driven dynamic encryption matching mechanism to improve data security and resource efficiency; constructs a multi-level authentication and role signature map to enhance the collaborative credibility and fault tolerance of equipment; introduces a priority index scheduling strategy to ensure that key data is transmitted first in a highly volatile network environment, thereby improving the overall stability and security of the system.

The invention discloses a guide vane locking anti-maloperation device and method, and the device employs a multi-redundancy configuration of double sensors and double relays, and constructs a monitoring control mechanism for mutual verification. Even if a single element breaks down, the system can still accurately judge the real position of the locking device, safety accidents caused by uncertain states or misjudgment are fundamentally avoided, the safety of a unit is guaranteed, and the fault-tolerant capability and the availability rate of the system are improved. By preventing fault shutdown caused by misoperation, the device ensures stable operation of a unit, and effective power generation time is prolonged, so that operation efficiency and economic benefits are improved. In addition, detailed fault information can be provided through the integrated intelligent alarm function, operation and maintenance personnel are helped to rapidly position problems, the maintenance process is simplified, and manual inspection is reduced. Through seamless integration with an automatic system, remote monitoring and operation are realized, and the intelligent management level of the power station is improved.

This invention relates to the field of distributed storage technology and provides a data collaboration method and system for distributed transaction terminals. The method involves each transaction terminal performing erasure coding on its local ledger data to generate a set of data fragments consisting of original data fragments and verification data fragments. These data fragments are then distributed and stored across different transaction terminals according to distributed storage rules, and the terminals exchange online status and fragment integrity information. When a request to access the target ledger is received, the terminal storing its fragments is located based on the ledger identifier, and the fragments are retrieved in parallel to reconstruct the target ledger. When a terminal is detected to be offline or a fragment is corrupted, online terminals collaborate to reconstruct the original data using surviving fragments, re-encode new fragments, and distribute them to healthy terminals. This invention, through erasure coding and distributed collaborative storage, reduces storage overhead while improving system fault tolerance and data availability, achieving efficient and reliable distributed ledger data collaborative management.

The application relates to the computer technical field, in particular to a system fault-tolerant test method, an electronic device and a storage medium. In the system fault-tolerant test method, the function characteristic type information and the disaster simulation program are acquired first, then the cloud platform system to be tested is divided into levels based on the function characteristic type information, a cloud system hierarchical model corresponding to the cloud platform system is obtained, further, a data disaster environment is simulated in the cloud system hierarchical model based on the disaster simulation program, finally, the cloud system hierarchical model in the data disaster environment is tested for fault tolerance, and fault-tolerant indexes corresponding to the cloud platform system are obtained. Through the system fault-tolerant test method, the data disaster of the cloud platform system is simulated based on the cloud system hierarchical model, so that the fault-tolerant indexes of the cloud platform system are obtained through the fault-tolerant test, and the fault-tolerant indexes of the cloud platform system can be more accurately measured.

The invention relates to the technical field of intelligent traffic and robots, in particular to an interconnection communication system for fault detection of a road berth robot, which is used for solving the problems that a fault recognition mechanism integrating various abnormal conditions cannot be constructed, key task information cannot be extracted for replacing judgment and the fault detection efficiency cannot be improved in the prior art. An optimal substitute cannot be selected through a comprehensive cost model, and the fault tolerance, the task completion rate and the operation robustness of the system cannot be improved. Lightweight distributed modeling is realized through a collaborative task recovery module, a fault recognition mechanism synthesizes various abnormal conditions, key task information is extracted for replacement judgment, candidate robots are screened according to distances, priorities and resource conditions, an optimal replacement person is selected through a comprehensive cost model, and the optimal replacement person is selected according to the optimal cost model. And the successor executes movement control, obstacle avoidance adjustment and state broadcasting according to the perception graph and the state of the successor, so that the fault tolerance, the task completion rate and the operation robustness of the system are improved.

This application proposes a multi-sensor target fusion processing method, system, device, and medium, including: synchronously fusing the output data of multiple sensor processing units at the arrival of each preset fusion cycle to obtain target fusion data; updating the target fusion data to each sensor processing unit, and using the sensor processing unit to data-associate the target fusion data with real-time sensor data to obtain associated data as the output data of each sensor processing unit; and outputting the target fusion data to the application end after each fusion cycle. This application can effectively improve the system's fault tolerance and the efficiency of target data fusion processing.

The invention discloses a data storage method and device, equipment, a medium and a program product, and relates to the technical field of electronic computers.The data storage method comprises the steps that to-be-stored original data are obtained, the original data are divided into first-level data strips according to the (K, M) redundancy ratio, first-level verification strips are obtained through coding calculation, and the first-level verification strips are stored in the first-level verification strips; the first-level data strip and the second-level check strip form a first-level erasure code, the first-level erasure code serves as original data, a second-level erasure code is constructed according to the (K-1, M) redundancy ratio, and the first-level erasure code and the second-level erasure code are stored in different storage nodes. According to the method, the multi-level erasure codes are constructed, so that the data recovery capability, the system fault-tolerant capability and the node utilization rate are remarkably improved when the problems that the data reliability is insufficient and the fault-tolerant capability is limited in a storage system are faced.

The application relates to the field of integrated circuits, in particular to a multi-stage threshold watchdog circuit based on temperature compensation and a control method and chip device thereof. The circuit comprises a watchdog counter for outputting a count value; a temperature compensation calculation unit for dynamically compensating a count threshold of the watchdog counter based on a current temperature value collected, a temperature-frequency characteristic curve of a clock source and a compensation mode; and a state machine for outputting a corresponding control signal based on a comparison result of the count value and the count threshold. The application avoids the false triggering / missing triggering of the watchdog reset caused by the frequency temperature drift of the clock source, improves the timing accuracy of the watchdog, enhances the fault tolerance of the system and improves the reliability of the system.

The embodiment of the invention provides a resource providing method and device, equipment and a readable medium. The method comprises the following steps: receiving a user request for a target resource; determining a providing state of a target resource stored in a content delivery network CDN; and in response to the provision state of the target resource stored in the CDN indicating that the target resource cannot be provided, requesting the corresponding user to provide the target resource to the user through a first path corresponding to the cloud storage service or a second path corresponding to the local storage service. In this way, the stability and availability of the resource management system can be improved, the fault tolerance and maintainability of the system can be improved, and the user experience can be improved.