52 results about "Resource use" patented technology

The invention relates to the technical field of data processing, can be applied to business scenes such as financial science and technology and medical health, and discloses a self-adaptive data processing optimization method, device and equipment and a medium, and the method comprises the steps: collecting operation data, host performance data, network state data and historical task data of a target data source, and constructing an analysis model in combination with recovery parameters and strategy preference, predicting a task load state, resource consumption and execution duration, generating a task execution strategy, completing task scheduling and execution monitoring, and collecting execution feedback data for iterative optimization of the analysis model. According to the method, an analysis model is constructed by fusing multi-source system data and historical task information, a task execution strategy is generated in combination with a dynamic prediction result and a strategy weight, intelligent task scheduling and process monitoring are realized, and feedback data is used for model iterative optimization. The task execution efficiency is improved, the resource use rationalization is realized, and the model adaptive capability is enhanced.

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical treatment and health and the like, and discloses a data hierarchical storage method, device, equipment and medium based on access characterization. Writing the data into a matched first target storage device according to a preset device performance corresponding relation; after the data are stored, continuously monitoring subsequent access characteristics of the data, and dynamically judging whether the heat state is changed or not; and if the popularity state is changed and a specific migration condition is met, redistributing the second target storage device and completing data migration operation so as to realize automatic hierarchical storage management of cold and hot data. By acquiring the data access representation and dynamically identifying the popularity state, hierarchical migration of data with different popularity among storage devices with different performances is realized, the resource use efficiency and access performance of a storage system are improved, and the storage cost is reduced.

The invention discloses a resource scheduling method and device based on IT asset health assessment, a medium and equipment, and the method comprises the steps: obtaining resource use data, network connection data and abnormal information data corresponding to each node in a distributed system, and carrying out the health degree scoring calculation based on the resource use data, the network connection data and the abnormal information data, obtaining a health degree score corresponding to each node; obtaining the priority of the service adapted to each node, and performing calculation based on the health degree score corresponding to each node and the priority of the adapted service to obtain a comprehensive evaluation value corresponding to each node; and scheduling resources based on the comprehensive evaluation value corresponding to each node. According to the method, the comprehensive evaluation value of multi-modal fusion is calculated, resource scheduling is carried out according to the comprehensive evaluation value, comprehensive and real-time comprehensive evaluation is carried out on the health condition of IT assets, corresponding scheduling processing is carried out according to the comprehensive evaluation condition, and the stability and reliability of the system are remarkably improved.

The invention relates to the technical field of medical resource management, in particular to a pediatric outpatient service resource intelligent scheduling and patient flow prediction management system which comprises a data acquisition module, a flow prediction module, a resource scheduling module, a scheduling optimization module and a feedback correction module. Historical patient flow data, doctor scheduling data, consulting room availability data and patient reservation data are collected in real time, a patient flow prediction result generated by the flow prediction module is combined, data support is provided for resource scheduling, the resource scheduling module generates a preliminary scheduling scheme according to the prediction result and actual data, and the preliminary scheduling scheme is used for resource scheduling. And a scheduling scheme is optimized through a simulated annealing algorithm, and the resource utilization rate is improved. And the feedback correction module monitors patient flow and resource use conditions in real time, and adjusts a scheduling scheme in time to cope with emergencies and expected changes. According to the invention, the scheduling scheme can be dynamically adjusted under different demand fluctuations, the high efficiency and flexibility of resource allocation are ensured, and the service quality of hospitals is improved.

The invention discloses a multi-hospital first-aid collaborative strategy recommendation method and system, and relates to the technical field of pre-hospital first-aid collaboration.The method comprises the steps that spare medical resource information is acquired in real time, and an initial collaborative strategy set is acquired based on the spare medical resource information according to department and hospital positions and basic first-aid configuration; acquiring historical medical resource use information, and constructing a medical resource candidate influence relationship based on the medical resource use frequency and the importance degree according to the historical medical resource use information; and responding to the first-aid information, matching an initial collaborative strategy according to the first-aid information, generating an auxiliary collaborative strategy according to the medical resource candidate influence relationship, and executing collaborative strategy recommendation according to the initial collaborative strategy and the auxiliary collaborative strategy. The method has the beneficial effects that the medical resource scheduling efficiency and the anti-risk capability in the emergency treatment process are improved.

The invention discloses an internet-based physical hospital comprehensive information management system, which relates to the technical field of hospital information management and comprises a data acquisition module, a data processing module, a calculation module and an analysis module. According to the method, factors such as resource types, use frequency and maintenance cost are comprehensively considered, a visual resource utilization situation overview is provided for hospitals, resource allocation can be optimized to a certain extent, resource waste is reduced, the resource use efficiency is improved, and the method combines multiple dimensions such as medical service quality and patient satisfaction, so that the medical service quality and the patient satisfaction are improved. The medical service efficiency is comprehensively evaluated to provide an improvement direction for hospitals, the system comprehensively evaluates the information management efficiency from multiple aspects of information management cost, information processing capability, information security and the like, and the hospitals can clearly see the actual effect of an information management strategy through quantitative analysis, so that the strategy is adjusted, the cost is reduced, and the medical service efficiency is improved. And the information management efficiency is improved.

The invention relates to the technical field of medical management informatization, in particular to a visual multi-dimensional patient flow adjustment system and method, and the system comprises a patient sensing module, an intelligent analysis gateway, an adjustment strategy generation module, a resource dynamic scheduling engine, and a visual positioning platform. Wherein the patient sensing module is used for collecting basic information, doctor seeing states, department resource use conditions and environment data of patients in all areas of a hospital; the intelligent analysis gateway is used for fusing and processing data and predicting the patient flow risk through the gating circulation unit; the adjustment strategy generation module is used for carrying out treatment priority fine classification on the patients and generating a personalized flow adjustment strategy; the resource dynamic scheduling engine is used for performing accurate scheduling through an intelligent allocation algorithm according to the adjustment strategy; the visual positioning platform is used for calibrating patient positions and rendering a hospital-wide patient distribution thermodynamic diagram and a resource occupancy rate in real time. Therefore, the problems of long waiting time, unreasonable resource allocation, single management strategy and the like in the prior art are solved.

Various methods, devices, and systems for task identification and resource management are described. In one aspect, a method includes obtaining information about a subject, obtaining identification of a condition of the subject based on the information, and obtaining identification of a treatment for the subject. The method also includes identifying a set of tasks corresponding to the treatment, generating, via a rules engine, a first set of parameters for the tasks, and generating, via an artificial intelligence (AI) engine, a second set of parameters for the tasks. The method further includes generating a resource allocation schedule for the treatment using the set of tasks, first set of parameters, and the second set of parameters, including assigning one or more tasks to a particular entity, and providing information about the one or more tasks to the particular entity.

The present application discloses a data resource health maintenance method and apparatus, and a device. The data resource includes data computing resource and data storage resource. The method includes: obtaining a health assessment indicator for assessing health of the data resource, wherein the health assessment indicator includes a resource effective utilization degree and a resource risk level of the data resource in a use process; determining a weight corresponding to the resource effective utilization degree and a weight corresponding to the resource risk level; obtaining a health assessment result of the data resource based on the resource effective utilization degree, the resource risk level, the weight corresponding to the resource effective utilization degree, and the weight corresponding to the resource risk level; and obtaining a data resource use event related to the health assessment result, and performing data resource governance based on the data resource use event.

The invention relates to the technical field of health care accompanying robots, and particularly discloses a memory optimization system for an intelligent health care accompanying robot, which comprises the following steps: acquiring state data of a first application program and a time sequence of memory resource usage amount; embedding coding of state data of the first application program and time sequence association of the memory resource usage amount of the first application program are carried out by utilizing a data analysis and coding mode based on deep learning; therefore, whether memory cleaning operation is executed on the first application program or not is intelligently judged according to semantic alignment fusion representation between the application program state embedded coding feature and the application program memory resource usage amount time sequence implicit association feature. In this way, the condition of the application program memory can be accurately recognized, and misjudgment possibly caused by a traditional static rule is effectively avoided. Moreover, the optimization strategy can be automatically adjusted according to different equipment and user behavior modes, and the method does not need to depend on a fixed rule set, so as to better adapt to diversified application scenes.

When deciding which medical treatments and procedures to provide to patients from among the hospital's medical resources, a computer is used to predict how patients will use medical resources, and by systemizing the medical resource decisions, the hospital aims to optimize its profits by making resource use more efficient and profitable. [Solution] Patient information and information on available medical resources that can be provided to patients by medical institutions are stored, and a prediction of the medical resources required by the patient is calculated based on the patient information as predicted patient resource information, and the predicted patient resource information is matched with the available medical resource information (S707). The matching results are presented to medical professionals, and input from the medical professionals is accepted. The predicted patient resource information is changed to planned (decided) patient resource information (S710), allowing the patient to be selected and accepted, and medical resources to be provided to the patient.

The invention relates to a data processing technology, can be applied to business system platforms of medical health, financial science and technology and the like, and discloses a resource dynamic adjustment method, device and equipment and a medium, and the method comprises the steps: obtaining the use condition and weight information of each resource group in a current database; generating resource configuration information corresponding to each resource group based on the use condition and the weight information of each resource group; submitting a resource adjustment request to a database front-end node according to the resource configuration information in a hard restriction isolation mode; and forwarding the resource configuration information to a database rear-end node based on the database front-end node, executing the resource configuration information based on the database rear-end node, and storing a resource use condition. Dynamic adjustment of resources is supported, the system resources are fully utilized, the query response time is shortened, and meanwhile the stability of the system can be guaranteed; and for tasks with high weights, resources can be preferentially allocated or allocated more, and the operation and maintenance efficiency is improved.

The invention relates to the technical field of computers, and provides a resource use method, device and system, and the method comprises the steps: determining a resource use plan of a tenant according to the resource demands of the tenant and the resource configuration of a plurality of resource points, the resource demand of the tenant comprises the resource demand quantity of at least one resource demand point in a plurality of resource demand points associated with a plurality of resource points, the resource configuration of the resource points comprises resource capacity and resource price, and the resource use plan of the tenant is used for indicating that the resource demand of the tenant is met. At least one target resource point in the plurality of resource points provides the resource usage amount for at least one resource demand point. And using the resources of the at least one target resource point according to the resource use plan of the tenant. The resource usage plan determined according to the method can indicate that the resources of one or more target resource points are selected and used in the plurality of resource points, and the resource usage amount of the used target resource points can guarantee the resource requirements of the tenants.

The invention relates to the technical field of medical management, in particular to an emergency department emergency disposal decision system which comprises a resource distribution analysis module, a task allocation engine module, a hierarchical structure mapping module, an execution degree screening module and an abnormity regulation and control module. According to the method, through processing steps of resource distribution analysis, task optimization matching, hierarchical structure division, execution degree screening and the like, configuration and scheduling of emergency resources of the emergency department are optimized, high-efficiency and low-efficiency areas, abnormal points and logic differences of resource clusters are identified, resource allocation is more targeted and efficient, and the resource allocation efficiency is improved. Reasonable allocation of resources on different scales and levels is achieved through hierarchical structure division and fluctuation change recognition, resource use is maximized, decision making efficiency and response speed are improved, low efficiency and misjudgment of traditional manual decision making are effectively avoided through an intelligent scheduling method, the emergency response capability and the resource utilization rate are improved, and the resource utilization rate is increased. And rapid and accurate execution of the emergency task is ensured.

The invention relates to the technical field of medical resource management, in particular to a medical resource allocation method and device for pre-hospital first aid, electronic equipment and a storage medium. And importing the scoring result of each evaluation sub-item to each medical resource allocation scoring model to obtain an allocation scoring result of each medical resource, obtaining various medical resource scoring results of other patients to be subjected to resource allocation at the current moment, and determining the recommendation probability of the target patient in various medical resources based on a recommendation probability function. Compared with an existing mode of obtaining allocation results of various medical resources by using the same model, the medical resource allocation method disclosed by the embodiment of the invention fully considers influence factors of various medical resources, so that allocation of various medical resources is more reasonable and accurate, idle or overuse of part of medical resources is avoided, and the medical resource allocation efficiency is improved. The effectiveness of patient rescue is ensured, and the rescue success rate is improved.

A resource dynamic scheduling adaptation method and system in a limited demand scenario. This method uses historical data of user resource usage to predict the confidence interval of resource demand in the resource usage area, comprehensively considering the high dynamics and uncertainties during the user's resource usage process in the resource interval, and predicts the demand distribution of users in the demand area in the form of a demand interval, transforming the point estimation problem of user demand prediction into an interval prediction problem of demand prediction. At the same time, the prediction model incorporates the characteristics of external factors affecting the current area's resource usage, making a highly robust and accurate confidence interval prediction of the user resource demand situation in the resource usage area. The present invention realizes a better and more optimal efficient resource scheduling plan for the user resource demand distribution in each area under the conditions of overall resource limitation and scheduling capacity limitation, can efficiently and stably generate a resource scheduling strategy for the resource usage area, and improve the effective adaptation efficiency of the overall resources.

The invention discloses a community hospital vaccination outpatient service area measuring and calculating method based on virtual scene behavior simulation, and the method comprises the steps: S1, analyzing the hospital function demands, service object features and regional features of different hospitals, and constructing a preliminary demand framework; s2, collecting basic data of a hospital, establishing a preliminary virtual scene model based on a demand framework, and simulating inoculation processes and resource use under different conditions; s3, according to the characteristics of different hospitals and the virtual scene model, the vaccination outpatient service site layout is designed, and the outpatient service area is adjusted through combination of virtual simulation and genetic algorithm optimizing.According to the method, through comprehensive consideration of hospital function requirements, service object characteristics and regional characteristics, flexible adjustment and accurate application of different hospitals are achieved, and the vaccination outpatient service site layout is achieved. Through combination of virtual scene behavior simulation and a genetic algorithm, the area required by the vaccination outpatient service can be measured more accurately, and reasonable allocation of resources is ensured.

The present invention relates to a system (1) which enables focal agendas of an organization to be visualized; the status of service infrastructures such as growth, bottlenecks and use of resources to be assessed; problems and solutions to be announced to the entire organisation; and automated reporting to be performed.

The invention relates to the technical field of data processing, can be applied to the field of science and technology finance / digital medical treatment, and discloses a data pipeline exception processing method and device, electronic equipment and a storage medium. The method comprises the steps of monitoring a task execution state in a data pipeline, and collecting abnormal log information and abnormal context information when execution abnormity occurs; performing semantic analysis on the exception log by using a pre-trained large model, determining an exception reason type and generating an exception processing strategy; executing automatic repair or strategy execution operation according to the exception handling strategy; the task scheduling priority, the execution sequence and the resource allocation are optimized in combination with the task running state and the resource use state in the exception processing process, and the overall processing efficiency is improved; and performing associated storage on the exception log, the exception reason, the processing strategy and the processing result, and continuously updating the exception processing strategy library. According to the method, intelligent diagnosis, self-repairing and continuous stability optimization of data pipeline abnormity are realized.

The present invention relates to the technical field of nuclear fusion tokamak device control systems, and in particular to a method for predicting resource usage of a plasma control system based on LSTM. The technical solution includes data preprocessing and feature extraction, introduction of an LSTM network for time series prediction, feature embedding and feature separation strategies, standard value prediction and memory leak detection, health index calculation and feedback adjustment, and feedback adjustment within the prediction cycle. The present invention is used to predict the standard value of resource usage during system operation, and by comparing with real-time monitoring data, determines whether resource usage deviates too much from the standard value. It can capture the long-term dependence and nonlinear variation of system resource usage, and is particularly suitable for processing complex periodic waveforms. It can not only improve the accuracy of the predicted standard value, but also more effectively evaluate the system health status and provide early warning of potential abnormal situations, providing important support for the stable operation of the system.

The invention provides a resource quota configuration method and device and a training method of a credit evaluation model, relates to the technical field of data processing, and can optimize the quota of resource application of a stock user, improve the passing rate of resource application of the stock user and reduce the mobility of the stock user. According to the specific technical scheme, credit data such as business conditions of stock users, historical resource application performance data, credit evaluation data and resource management scale AUM data are collected; and evaluating the credit rating of the stock user according to the credit data by using a pre-trained credit evaluation model. And determining a resource limit coefficient of the stock user in combination with the credit rating of the stock user, the service demand information of the resource application service and the multi-dimensional risk assessment parameter. And determining an initial quota, a first configuration quota and a second configuration quota based on the resource quota coefficient, the historical resource application performance data and the application time, and determining a resource use quota which can be applied by the stock user according to the data.

The embodiment of the invention provides a resource management method and a related device, and the method comprises the steps that a management device is used for managing a resource pool, the resource pool comprises a plurality of resources and a plurality of resource logic isolations, the plurality of resources can be used by a plurality of devices, and each device can use the bound resource; the management device can distribute the resources used by one device to the other device for use based on the requirements of the devices, and can also distribute new resources in the resource pool for one device, and through redistribution of the resources in the resource pool by the management device, the distribution efficiency of the resources in the resource pool is improved, and the resource utilization rate is improved. And the utilization rate of the resources in the resource pool is improved.

Described herein are methods for reducing healthcare resource use by patients treated with metoclopramide.

A system for improving efficiency of resource use at wash facilities is provided. The system comprises a chemical pod installed at a wash facility that receives captured data describing a vehicle as the vehicle enters a wash facility for servicing. Based at least on the data, the system also receives a determination that elements of a cleaning system at the facility are not optimally configured for servicing of the vehicle. The system also alters flow of resources of the cleaning system based on instructions received based at least on the determination. Elements of the cleaning system comprise at least one applicator. The resources comprise at least one of chemicals, water, and air. The determination and the instructions are received from at least one control system. Adjustments to the resources are controlled electronically and without physical swapping of components or manual intervention.

The application discloses a data resource health maintenance method, device and equipment, and the data resource includes data computing resource and data storage resource. A health evaluation index for evaluating the health of the data resource is determined, and the index includes resource effective use degree and resource risk level. The resource effective use degree is used to represent the degree of effective use of the data resource, and the resource risk level is used to represent the degree of negative impact of the use of the data resource on the business. The resource effective use degree is negatively correlated with the increase rate of the resource risk level. The weights corresponding to the two indexes are determined, and the health of the data resource is evaluated based on the two indexes and the weights corresponding to the two indexes. In this way, the health of the data resource is evaluated based on the degree of effective use of the resource and the degree of negative impact of the use of the data resource on the business, which can more accurately reflect the health of the resource. In addition, the data resource can be managed to improve the health of the data resource.

Embodiments of the disclosure describe system and methods to perform Intra-gNodeB-Central Unit (CU) handover by a gNodeB(gNB) is disclosed herein. The method includes determining, by the gNB (502), whether resource usage at a first gNB-CU-User Plane(gNB-CU-UP) (506) associated with the gNB-CU (504) of the gNB exceeds a predefined threshold value. Upon determining that the resource usage at the first gNB-CU-UP exceeds the predefined threshold value, the method includes detecting, by the gNB, whether one or more User Equipment (UEs) (510a and 510b) connected with the gNB experiencing performance degradation based on the resource usage at the first gNB-CU-UP. Further, the method includes initializing, by the gNB, a handover of at least one of the one or more UEs from the first gNB-CU-UP to a second gNB-CU-UP (508) associated with the gNB-CU of the gNB.

The application belongs to the technical field of cloud computing and container orchestration resource management, and discloses a Kubernetes resource portrait and cost optimization method and system, which comprises the following steps: obtaining container resource index original data; performing aggregation to obtain aggregated data; using a resource portrait engine to classify services and generate service resource portraits; performing multi-dimensional anomaly detection according to the service resource portraits to obtain an abnormal service list; generating adjustment suggestions based on the abnormal service list to obtain an optimization suggestion set; adopting a differentiated merging request submission strategy according to the risk level of the optimization suggestion set to output a merging request; comparing resource usage data and service running indexes before and after merging to generate an optimization effect verification report; and using a capacity predictor to predict resource demand of the service resource portrait, and generating a capacity warning and calibrating the predictor when the predicted value exceeds a threshold value. The application solves the deficiencies of the prior art in pattern recognition, risk management and capacity planning.

The present invention relates to the technical field of resource sharing, and specifically to an entity resource sharing economic system and its method. The system includes a resource monitoring module, a resource flow analysis module, a demand response strategy module, a cost assessment module, a periodic analysis module, and a stability assessment module. In the present invention, by collecting and analyzing the usage and flow data of entity resources, the dynamic adaptability and accuracy of resource allocation are effectively improved. Through the data recorded in real time with geographical location and time tags, the periodic changes and flows of resources are analyzed. This dynamic monitoring and analysis not only helps to predict peak resource demands, but also enables the design of more effective sharing and allocation strategies for shortage areas. By simulating various allocation schemes, the response strategy can be optimized, the resource utilization efficiency can be enhanced, and at the same time, the operating cost can be reduced, ensuring the long-term benefits and sustainable development of the resource sharing economic system, improving cooperation and interaction among communities, and supporting environmental sustainability.

The invention discloses a public service health management method based on big data, and relates to the technical field of public health services, and the method comprises the following steps: an information collection end collects the address, department classification floor and medical equipment of a hospital, and a material management end carries out the statistics of supporting facilities and resources in the hospital, and then the resource use condition is counted and calculated, a signal is sent to the public server side, and a patient needing to see a doctor inputs a department to be hung and the position of the current patient at a user side, so that the signal is sent to the public server side. Compared with a traditional data management and evaluation module, the public service health management method based on the big data evaluates whether other patients are registered for treatment within the time when the current patient arrives at the optimal treatment hospital, avoids the problems that the patient waits for a long time and cannot be ranked to the number when arriving at the treatment hospital, enables the patient to quickly see the treatment after arriving at the hospital, and improves the treatment efficiency. And the quality and efficiency of hospital medical services are improved.