157 results about "Multi resource" patented technology

A renewable energy resource management system manages a delivery of a power requirement from a multi-resource offshore renewable energy installation to an intelligent power distribution network. The installation includes multiple renewable energy resource components and is capable of variably and independently generating power from each to microgrids comprising the intelligent power distribution network so that the entire power requirement is satisfied from renewable energy resources. An electricity grid infrastructure is also disclosed in which power production is balanced with power consumption so that power storage requirements are minimized.

Systems and methods are provided to schedule clinical tasks involving multiple sub-tasks and multiple resources in a clinical enterprise. An example method includes identifying a slot for a task defined by a task duration and one or more resources, the task including a plurality of sub-tasks, each sub-task having a sub-task duration utilizing one or more of the one or more resources, wherein each sub-task to be performed consecutively based on resource constraints; selecting a time slot for the task based on resource availability, the plurality of sub-tasks in the task, and a duration associated with each sub-task, wherein resource availability information is obtained from a clinical information system, and wherein each resource is scheduled only for one or more sub-tasks in which the resource is involved; displaying the schedule including the task and the plurality of sub-tasks; and facilitating access to view and modify the schedule.

Increased workload performance is obtained by coordinating a multi-resource computer system such that demands for resources are arbitrated across all available resources and all applications such that the proper resource will be adjusted regardless of which resource is needed to improve workload performance. In operation, a measurement is taken for each available resource to determine the enhancement achieved by adding a certain quantity of a resource. In one embodiment, resource consumption and performance data is collected over a period of time and that data is used to adjust resource requests for a workload in order to improve the workload's performance. The resource request is modified to deliver the most workload benefit for each resource modification.

A renewable energy resource management system manages a delivery of a power requirement from a multi-resource offshore renewable energy installation to an intelligent power distribution network. The installation includes multiple renewable energy resource components and is capable of variably and independently generating power from each to microgrids comprising the intelligent power distribution network so that the entire power requirement is satisfied from renewable energy resources. An electricity grid infrastructure is also disclosed in which power production is balanced with power consumption so that power storage requirements are minimized.

A renewable energy resource management system manages a delivery of a power requirement from a multi-resource offshore renewable energy installation to an intelligent power distribution network. The installation includes multiple renewable energy resource components and is capable of variably and independently generating power from each to microgrids comprising the intelligent power distribution network so that the entire power requirement is satisfied from renewable energy resources. An electricity grid infrastructure is also disclosed in which power production is balanced with power consumption so that power storage requirements are minimized.

The invention discloses a hierarchical distributed autonomous collaborative task planning system for an intelligent remote sensing satellite. The system comprises a multi-satellite task coordinator and an on-satellite scheduler, wherein the multi-satellite task coordinator distributes tasks in a task set to be distributed to multiple affiliated intelligent satellites and processes the tasks into meta-tasks which can be directly identified by the on-satellite scheduler; each intelligent satellite utilizes the on-satellite scheduler to carry out uniform scheduling on a new distributed task and an existing task; and before the multi-satellite task coordinator carries out task distribution, a scheduling result on the relevant on-satellite scheduler is estimated in advance and is taken as a basis for task distribution. Key scientific problems and technical problems of imaging task schedulability prediction, multi-task multi-resource dynamic scheduling under a high-dimensional space, refinedplanning and scheduling algorithm design are successfully tackled, a multi-satellite autonomous collaborative task planning technology can be better applied to the field of national defense construction, and the rationalization of a distribution scheme and the high efficiency of resource utilization can be accelerated.

The invention discloses a task scheduling method in a real-time system, and the method includes the steps as follows: A, the scheduling tasks can be ordered according to the time limit and computing load; B, if free resource is available, the resource can be allocated by the arrangement order which can be one or more-than-one to-be-scheduled tasks, wherein, if the arrangement order is more-than-one to-be-scheduled tasks, the max delay time between multi-tasks of allocated resource is least; the invention can realize optimal scheduling for multi-resource and multi-tasks, and thereby can improve the resource utilization, as well as the ratio of tasks which reach within time limit.

Systems and methods for searching multiple resources via a communications network, such as the Internet, are disclosed. The systems use a client-server approach in which search clients formulate search requests for a plurality of resources in a generalized format. The search requests are sent to a server, and specific uniform resource locators (URLs) for the desired resources and search terms are returned to the clients. The clients display the search results grouped by category and by resource, for example, with two sets of tabs. Each set of results is rendered using a browser engine, and the set is generally presented in its entirety. The server may define the resources available to the clients for search, and may also provide promotional information with the search results. Particular resources and features may be made available to particular groups and users.

The invention relates to a multi-resource remote sensing distinguishing method and system of an underground potassium- and halide-containing water resource in a salt lake area. The method comprises the following steps: acquiring data, namely, acquiring multi-resource remote sensing image data; processing data, namely, processing multi-spectral remote sensing image data and high-resolution remote sensing image data by the multi-color transformation technology, building a remote sensing stratum lithology interpretation mark and performing remote sensing stratum lithology interpretation; extracting salt-containing abnormality information from the multi-spectral remote sensing image data by the main component analyzing technology; extracting the salt information by the interpretation extracting method; processing a radar remote sensing image data, building a geologic structure interpretation mark for potassium- and halide-containing water resource and performing geologic structure interpretation; integrating data, namely, processing three information obtained in data processing by overlapping, projection transformation and matching. According to the method, the multi-resource remote sensing image data are processed, interpreted and integrated to realize accurate distinguishing of the potassium- and halide-containing water resource.

The invention provides an access method and system for block storage data in a distributed storage system. The access method comprises the steps that a distributed STGT multi-resource management system and a distributed block storage system are constructed; in the distributed STGT multi-resource management system and the distributed block storage system, a distributed PR mechanism is adopted to achieve Active/Active multi-path environment and cluster multi-node access block storage; a distributed watcher mechanism is adopted to regularly monitor the accessibility of block storage in the distributed storage system; the distributed PR mechanism and the watcher mechanism are adopted to decouple multi-service process starting in distributed cluster nodes. According to the access method and system for the block storage data in the distributed storage system, authority conflicts of distributed block storage concurrent access are decreased, authority control of concurrent access is enhanced, and the security and the reliability of data concurrent access, the accuracy and the timeliness of block storage early warning and the stability of the distributed storage system and block storage data access are improved.

The invention provides a multi-resource cloud job scheduling method based on Deep Q-network algorithm, comprising the following steps: collecting current configuration information of resources and demand information of jobs through a cloud environment; respectively representing The current configuration information of the resource and the demand information of the job by a matrix image, the cellsincluding the cells, the cells of the same color represent the same job, and the rectangles formed by the cells of the same color comprise M *N cells, M represents the number of resources and N represents the time step; the rectangles formed by the cells of the same color comprise M* N cells. According to the matrix image, obtaining high-level semantic information by using a depth learning method;According to the high-level semantic information, a reinforcement learning method is used to complete the real-time scheduling planning of resources. A matrix image of thepresent invention can completely and clearly represent the state of resource and jobs. The method also uses depth reinforcement learning, which combines depth learning with reinforcement learning, in which depth learning mainlycompletes state perception, while reinforcement learning completes decision-making and realizes state-to-action mapping.

The invention discloses a device and method for monitoring and early warning of flood damages based on multi-resource integration. The device comprises a hydrological actual state module, a flow forecast module, a weather forecast module, a radar analysis module, a forecast integration module and a module for product display and early warning release. The method comprises the steps that (1) the hydrological actual state module reads and monitors monitoring point data; (2) the weather forecast module reads input data and parameters to carry out weather mode forecasting; (3) the flow forecast module carries out flow forecasting according to the weather mode forecast and the monitoring point data provided by the hydrological actual state module; (4) the radar analysis module reaches basic data of a radar and estimates precipitation and optical-flow extrapolation; (5) the forecast integration module integrates and outputs information of the flow forecast module and the radar analysis module; and (6) the module for the production display and the early warning release completes the product display and the early warning release. The device and the method consider accuracy of radar extrapolation forecasting in forecasting of the position of a precipitation system and also consider capacity of numerical mode forecasting, so that limitations of the single method are avoided.

A method and system is provided for navigating a multi-resource user interface on a display of an electronic device. Method and systems aspects include displaying a deck of cards representing device resources in a presentation space occupying only a portion of a display screen, wherein a top card overlaps other cards in the deck such that no user interface controls of the other cards are visible and only the top card is selectable by a user; and in response to the user activating an input control to navigate the cards in the deck, moving the top card to another position in the deck and revealing a next card in the deck.

The invention discloses a learning type genetic algorithm-based multi-task and multi-resource rolling distribution method. According to the method, based on the rolling time domain control principle,a multi-task and multi-resource dynamic rolling distribution mechanism is constructed. The multi-task and multi-resource dynamic rolling distribution mechanism comprises a prediction window, a rollingwindow, a sub-problem distributing element and a rolling mechanism element. According to the invention, the task information is updated in real time through a current prediction window, wherein the current rolling window is determined on the basis of the prediction window. During the sub-problem distributing process, a local distribution problem is constructed according to the construction of thecurrent rolling window at each planning moment. The rolling mechanism is used for determining an execution position at the ending of a distribution scheme and a next planning moment after the distribution of a sub-problem is well solved. Through the distribution mechanism, a complex dynamic distribution problem is converted into a plurality of simple and static distribution sub-problems. After that, the optimal solutions of sub-problems are combined to replace the optimal solution of the original problem. As a result, the solving difficulty of the original problem is greatly reduced.

The invention discloses an environment-friendly water-holding coal and uranium coordinated mining system. The environment-friendly water-holding coal and uranium coordinated mining system comprises a freezing mechanism, a pumping and injecting mechanism, a water storage mechanism and a mining supporting mechanism. The freezing mechanism is provided with freezing shafts. The pumping and injecting mechanism is provided with fluid injecting wells and a fluid pumping well. The water storage mechanism is provided with an underground reservoir, a security coal pillar and advance water discharge pipes. The mining supporting mechanism is provided with a road header, a coal mining machine, a scraper conveyor and a hydraulic support. The freezing shafts in the freezing mechanism conducts freezing on an aquifer on the periphery of the pumping and injecting mechanism with the pumping and injecting mechanism as the radius; the pumping and injecting mechanism conducts uranium mining by an in-situ leaching technology; the mining supporting mechanism conducts stoping on a coal seam; and the water storage mechanism stores and purifies water in the aquifer of a broken roof. Finally, under rational cooperation of the four mechanisms, coal and uranium coordinated mining is realized, underground water is recovered and purified at the same time, and the purpose of environment-friendly water-holding multi-resource coordinated mining is achieved.

The invention provides a multi-resource coordination control method and apparatus for a direct current block fault impact alternating current channel. Static state stability limit of the alternating current channel is determined firstly; then the multi-resource coordination control sequence and coordination control quantity are determined; and finally, multi-resource coordination control is realized. By virtue of the technical scheme provided by the invention, multiple types of control resources of pumping, storing and pump switching, direct current power emergency modulation, accurate load shedding, and load shedding are taken into comprehensive consideration, so that control means are increased; the target function of a multi-resource coordination control model takes the minimum of the load shedding quantity as the optimization object, and constraint conditions are taken into consideration, so that control effectiveness is improved, control cost is lowered, and power grid defensive performance is improved; and in addition, by adoption of a heuristic algorithm, the multi-resource coordination control sequence and the multi-resource coordination control quantity are obtained, and the multi-resource coordination control quantity obtained by adopting the heuristic algorithm is high in interpretability, so that relatively high practicability can be realized.

The invention relates to a virtual instance scheduling system and method based on a cloud platform. The virtual instance scheduling system comprises an API gateway platform, a task scheduling module and a resource module. The API gateway platform is used for providing a user interface and a resource management entrance and realizing the full life cycle management of the authority authentication, computing resources and network resources; the task scheduling module is used for calculating, scheduling and distributing the network and resources, and realizing the maximization of the global resource utilization rate on the basis of meeting the user resource requirements; and the resource module is used for providing the resources and virtualization instances needing to be allocated. Accordingto the present invention, multi-virtualization-instance mixing is supported, a uniform application interface is provided, a proper multi-virtualization-instance mixing resource system is provided fora user according to different scheduling strategies, the multi-resource mixing problem needed in the cloud process on the business can be effectively solved, and the network intercommunication problemamong the multi-virtualization instances can be effectively solved.

The invention discloses a multi-resource low-temperature waste heat comprehensive utilization system. The multi-resource low-temperature waste heat comprehensive utilization system comprises a sewage treatment device, a water storage tank, a low-temperature water source heat pump, a heat storage water tank, a cold storage water tank, a first branched water collector, a second branched water collector, an air-compressor cooling water source heat pump, a solar heat collecting device, an air heat source pump, an air mixing device and a multi-stage spraying chamber. The multi-resource low-temperature waste heat comprehensive utilization system disclosed by the invention has the advantages that recovery of waste heat resources such as industrial waste gas, industrial waste water and domestic waste water and utilization of solar energy and air energy are integrated, so that the heating in winter and cooling in summer are realized; multiple waste heat resources and other energies in a mining area are fully utilized, the energy-saving effect is obvious, the dust removing effect is good and the economic and social benefits are obvious.

The invention discloses a multi-resource joint allocation and optimization method based on user service quality requirements in a perception delay tolerant network. The method comprises the steps as follows: a perception delay tolerant network model based on OFDM (Orthogonal Frequency Division Multiplexing) modulation classifies user based on service quality requirements of different users in the network into high service quality cognition users and general service quality cognition users; for the high service quality cognition users, a subcarrier bit is adopted for joine allocation based on margin self-adapting standards, and the interference power is minimized while the user business transmission rate requirements are met; and for the general service quality cognition users, a subcarrier power is adopted for joint allocation based on rate self-adapting standards, and the user transmission rate is maximized while the user total interference power is limited. The invention adopts different multi-resource joint allocation and optimization method according to different user service quality requirements, so as to realize the resource optimized allocation of the perception delay tolerant network based on the OFDM, and realize spectrum sharing while the system resource is efficiently utilized.

The invention discloses a cloud data center application perceptible distributed multi-resource combined path optimal selection method. The method comprises the steps that a cloud data center application perceptible cloud resource manager is responsible for collecting resource state information of a network, a CPU and the like in basic resources; Forming an unsupervised deep hybrid architecture model by adopting a mode of combining reinforcement learning, a value network and a strategy network, and assessing model training and node moving positions of various request streams; A novel tree search algorithm is adopted, namely, a Parallel Monte Carlo Tree Search(PMCTS) algorithm is adopted, an appropriate resource path is searched for each type of request flow in an accelerated mode, and the value and the strategy network are combined, so that an optimal resource path selection result is given. By adopting the technical scheme provided by the invention, the minimum total response time delay of various intensive request streams of the cloud data center can be ensured.

The invention discloses a dynamic multi-resource equitable distribution method oriented to the cloud computing environment. The method is based on user resource needs and the user shared resource quantity, the fairness of resource distribution is guaranteed by constructing a linear programming model, a fast polynomial time complexity algorithm, namely, a bisection method is applied, vt corresponding to a user t is looked for, and an optimum allocation scheme (please see the formula in the specification) is solved to solve the algorithm running efficiency problem of the optimum allocation scheme. According to the method, the practical condition of resource distribution in a cloud computing sharing platform can be reflected accurately and really, the fairness and efficiency of multi-user multi-resource distribution under the dynamic state are improved, and the problem that an existing resource distribution algorithm is too long in running time is solved.