60results about How to "Improve resource efficiency" patented technology

The invention relates to the technical field of storage equipment management, in particular to an intelligent control method and system for storage equipment, and aims to solve the problems of task allocation, path optimization and equipment collaboration in a complex storage scene. According to the method, a storage equipment function model comprising an upper-layer frame model and a lower-layer equipment model is constructed, task allocation and path planning are optimized by using a neural network model in combination with task requirements, and a storage equipment control instruction is generated. In the task execution process, task priorities and path planning are adjusted in real time to adapt to dynamic environment changes, and it is ensured that tasks are completed efficiently. According to the method, a task distribution diagram and a path planning scheme are further optimized through a dynamic task diagram and a dynamic energy field, the problems of equipment congestion, too high energy consumption and task delay are effectively solved, the collaboration efficiency and the resource utilization rate of storage equipment are improved, and the method is suitable for various complex storage scenes.

The invention provides a production business mode construction method based on an industrial internet platform, and relates to the technical field of data processing, and the method comprises the steps: collecting multi-source data, and carrying out the preprocessing of the multi-source data; calculating the adaptation degree of the equipment and the task; dynamic influence parameters are extracted, and operation parameters in the equipment data are adjusted in combination with the adaptation result; constructing a weighted multi-objective function in combination with a completion time limit, a resource demand and a priority factor in the task data; generating a task priority sequence by solving the multi-objective function, and generating a task scheduling strategy according to the task priority sequence; in combination with the real-time state parameters in the equipment data, calculating the utilization efficiency of the equipment resources; performing priority ranking on the equipment according to the equipment resource use efficiency, and generating a resource allocation scheme through a segmented dynamic optimization algorithm; generating a production business mode according to the task scheduling strategy and the resource allocation scheme; according to the invention, the autonomy and accuracy of the production business mode are improved.

The invention discloses an agent task scheduling planning method, and relates to the technical field of agent scheduling. The method comprises the steps of analyzing a task instruction to generate atomic tasks capable of being independently executed, constructing a subtask dependency graph, and defining association constraints between the tasks; determining the real-time resource occupancy state of the intelligent agent to obtain a resource state tensor, completing resource-task association anchoring and dependency priority ranking in combination with the sub-task dependency graph, and generating a task priority sequence with resource constraint; performing dynamic capability matching and predictive load balancing calculation on the sequence through a task-agent adaptation model, and determining a target execution agent of each atomic task; and based on the target execution agent and the subtask dependency graph, performing time sequence scheduling arrangement and conflict resolution, and generating a collaborative execution scheme. The method improves the reasonability and efficiency of agent task scheduling, reduces resource conflicts and execution timeout risks, and is suitable for agent cluster collaborative scheduling in a complex scene.

The invention discloses a polymorphic heterogeneous intelligent computing resource fusion scheduling method and system compatible with a meteorological supercomputing architecture. The method comprises the following steps: creating a service cluster and a computing cluster; constructing a computing cluster computing power aggregation application service; creating a meteorological supercomputing architecture intelligent computing cluster fusion scheduling support environment; an elastic supercomputing service is constructed in the meteorological supercomputing architecture intelligent computing cluster; and constructing a software stack support environment adaptive to the polymorphic heterogeneous intelligent computing resources. According to the method, a service cluster is established, a computing cluster is scheduled based on a Kubernetes scheduling component of a fusion scheduler, adaptive heterogeneous resources are scheduled by adopting a container technology, a software interface is managed based on an intelligent computing cluster queue of a meteorological super computing architecture, scheduling based on a Slurm scheduling component of the fusion scheduler is realized, and native job scheduling of the intelligent computing cluster of the super computing architecture is realized; an elastic super-computing container technology is adopted, and an adaptive super-computing architecture intelligent computing power and software stack distributed environment is constructed; a fusion unified scheduling technology is formed, unified efficient scheduling utilization is achieved, and the resource utilization efficiency is improved.

The invention belongs to the field of intelligent manufacturing, and provides an intelligent recommendation method and system based on a shared robot, and the method comprises the steps: receiving a picture and a processing demand provided by a user; determining the processing attribute of the target workpiece according to the picture; determining a processing sub-task according to the processing attribute; determining an optimal shared robot combination according to the processing subtasks and the processing requirements; and displaying the optimal shared robot combination to the user.

The invention discloses a scheduling system for efficiently scheduling a Serverless function calculation task in a large-scale scene. The system comprises a Storage module, a task scheduling module, a task scheduling module and a task scheduling module, wherein the Storage module is used for providing a cache function of an apiserver component and a storage function of an etcd component; the Client module is used for providing an SDK (Software Development Kit) API (Application Program Interface) which is compatible with KubuBuilder; the Apiserver module is used for ensuring that external services and tools continue to use the original operation mode; the WatchCache module is used for ensuring that event circulation in the List-Watch mechanism is consistent with that in a native system; and the Persister module is used for persisting the data into the BadgerDB library, so that the data can be recovered from the persistent BadgerDB library. According to the method, the calculation efficiency and performance in a large-scale Serverless scene can be improved, and the waiting time is shortened.

The application provides a communication control method and device, computer equipment and a computer readable storage medium, and belongs to the technical field of computers. The method comprises the following steps: receiving and analyzing an event subscription request sent by a service server, determining at least one subscription event and at least one subscription data indicated by the event subscription request; sending a data transmission instruction to the service server according to each subscription event; and in response to receiving confirmation information sent by the service server, sending each subscription data corresponding to each subscription event to the service server. The application can improve the resource utilization rate and efficiency during server communication.

This invention belongs to the field of hard carbon technology, specifically relating to a bamboo-based and lignin-based hard carbon composite material, its preparation method, and its applications. The process involves pretreating raw materials to obtain pretreated material; pretreating the pretreated material with an acidic oxidant to obtain acidic oxidant pretreated material; pre-oxidizing the acidic oxidant pretreated material to obtain pre-oxidized material; pre-carbonizing the pre-oxidized material under a protective atmosphere to obtain pre-carbonized material; pulverizing the pre-carbonized material to obtain pulverized material; acid washing followed by water washing to obtain purified material; soaking the purified material in acid, filtering, and drying to obtain soaked material; mixing the soaked material with a modifier, and high-temperature coating and carbonizing under a protective atmosphere to obtain bamboo-based coated hard carbon or lignin-based coated hard carbon. Mixing the two types of hard carbon and carbon coating yields a bamboo-based and lignin-based hard carbon composite material, which is used in negative electrode sheets and batteries. When applied to batteries, the hard carbon composite material of this invention can improve battery energy density.

This invention discloses a large-scale model defense method based on semantic logic. By employing semantic logic analysis and model learning techniques, it systematically identifies and blocks the confusion effect of bias, thereby reducing the impact of bias in pre-training data on the guidance process. It includes an interpretable component that provides insight into the alignment between the generated output and the desired direction, enhancing the interpretability of the guidance process, increasing model transparency and user trust. This method may reduce reliance on manual annotation and computational resources, thus improving resource efficiency. Through unbiased guidance representation, it improves the model's generalization ability across different tasks and domains, contrasting with the limited generalization capabilities of existing technologies, exhibiting high scalability and adaptability. It can be applied to different language models, providing in-depth understanding of the consistency between the generated output and the desired direction, thereby enhancing the interpretability of the steering process while mitigating the impact of bias.

A digital project task management cooperation platform system based on cloud deployment comprises a data layer, a service layer, an interface layer and an access layer. The service layer comprises service configuration, an intelligent task engine, basic service and task service; the service layer provides diversified contract service interfaces for the access layer; the intelligent task engine provides standard task management service; each basic service is integrated, and a universal intelligent task service system is realized; the intelligent task engine processes wide task types; the state and progress of a task are managed through a task service, document data related to the task are stored and managed through a file service, and smooth communication between task participants is ensured through a message service; and finally, key information in the document is automatically extracted through an intelligent identification technology. The platform system can greatly improve the conditions of information asymmetry, unsmooth communication and low management efficiency in the existing project management.

The present application belongs to the technical field of resource allocation, and particularly relates to a space resource dynamic allocation method based on an AI model and BIM operation and maintenance, comprising: obtaining a to-be-processed task and a spatial position identifier thereof, and constructing a task feature vector set; inputting the task feature vector set into a modal recognition network model to obtain a plurality of primary scheduling modes containing spatial coupling components and resource demand components through mapping; iteratively updating coupling weights between the primary scheduling modes and high-level scheduling modes until convergence, determining a current resource allocation mode based on the converged high-level scheduling modes, and determining the association strength of each task relative to the current resource allocation mode based on the coupling weights; generating a scheduling instruction set containing joint scheduling paths and independent scheduling instructions according to the association strength and in combination with the spatial position identifier, and converting the scheduling instruction set into executable control instructions; and the present application realizes fine and adaptive dynamic resource allocation based on BIM and real-time situation.

The invention provides a sulfating roasting smelting process of lepidolite, and relates to the technical field of mineral processing. A sulfating roasting smelting process of lepidolite comprises the following steps that S1, low-temperature oxidizing roasting is conducted, specifically, the lepidolite and concentrated sulfuric acid are evenly mixed, and a mixed material A is obtained through low-temperature oxidizing roasting; s2, high-temperature reduction roasting: crushing the mixed material A, adding an auxiliary agent and a wave-absorbing agent, uniformly mixing, and performing high-temperature reduction roasting to obtain a mixed material B; s3, water leaching: carrying out water leaching reaction on the mixed material B, and filtering to obtain lithium slag and brine; s4, concentrating and cooling: concentrating and cooling the brine to obtain concentrated brine and potassium sulfate; s5, impurity removal: removing impurities from the concentrated brine, and filtering to obtain purified liquid; s6, lithium precipitation: adding sodium carbonate into the purified liquid to obtain lithium carbonate and lithium precipitation mother liquid; and S7, extraction and reverse extraction: performing multi-stage extraction and reverse extraction on the lithium precipitation mother liquor to obtain rubidium cesium salt. The smelting process provided by the invention is low in energy consumption and high in product yield.

A terminal according to one embodiment of the present disclosure is provided with: a control unit that determines a specific antenna port orthogonal to a first antenna port used for receiving a physical downlink control channel (PDCCH) of a plurality of layers; and a reception unit that assumes that the specific antenna port is not associated with a physical downlink shared channel (PDSCH) and a PDCCH facing a specific other terminal, and that receives the PDCCH of the plurality of layers. According to one mode of the disclosure, the resource efficiency can be improved.

A method for sending a signal by a terminal operating in an unlicensed frequency band, comprising the following steps: receiving configuration information about a carrier from a base station; receiving configuration information for configuring N (where N is an integer) guard bands for certain frequency regions of the carrier; sending a signal to the base station using a first frequency region belonging to a bandwidth portion of the carrier, wherein the first frequency region may be a region of the frequency region of the bandwidth portion that does not include the N guard bands.

A terminal according to one embodiment of the present disclosure is provided with: a reception unit that receives first downlink control information (DCI) based on a sequence without using a demodulation reference signal (DMRS); and a control unit that, on the basis of the first DCI, controls reception of a second DCI using a DMRS. According to one mode of the disclosure, the resource efficiency can be improved.

The application relates to a digital wave trap, a digital low-pass filter and a design method, a medium and an electronic device. The digital wave trap comprises a wave limit boundary anchoring unit and a wave limit zero point modulation unit which are cascaded in sequence, the wave limit boundary anchoring unit adopts a cascaded integral comb filter structure and is used for generating a first attenuation zero point at a boundary frequency of a target wave trap frequency band; the wave limit zero point modulation unit adopts a finite-length unit impulse response filter structure and is used for generating at least one second attenuation zero point in the target wave trap frequency band; and a continuous suppression band for the target wave trap frequency band is formed in the amplitude-frequency response of an output signal of the wave limit zero point modulation unit by the first attenuation zero point and the at least one second attenuation zero point. By using the digital wave trap provided by the application, a digital low-pass filter which can deeply and widely suppress power frequency interference and maintain strict linear phase and excellent low-pass characteristics can be designed without significantly increasing hardware resources and power consumption.

The invention discloses a zero-knowledge proof generation method for optimizing resource utilization, which comprises automatic division of a zero-knowledge proof circuit and parallel execution of a configurable pipeline of a sub-circuit, and aims to solve the problems of high memory consumption and low resource utilization rate of a zero-knowledge proof system. The method comprises the following steps: firstly, automatically dividing a complex zero-knowledge proof circuit into a plurality of sub-circuits, ensuring that the calculation process of the sub-circuits can be completed in series through public shared variables, and reducing memory occupation in a proof generation process; and secondly, by decoupling a witness generation stage and a proof calculation stage and introducing a pipeline processing mode, witness generation and proof calculation between sub-circuits are enabled to be independent and coordinated and executed in parallel, the resource utilization rate is optimized, and the degree of parallelism can be adjusted to adapt to different scene requirements. According to the method, the memory use of the zero-knowledge proof system is effectively reduced, and the resource utilization rate and the proof generation efficiency are remarkably improved under the controllable memory condition, so that the overall performance and the expandability of the system are improved.

The application discloses a kind of flight platform cluster's track planning method and device, the method includes: collection obtains task demand information set and flight platform cluster technical index information set;The task demand information set includes the execution position and demand information of each to be executed task;The demand information includes demand task type information and the demand value of all technical indexes;The flight platform cluster technical index information set includes the execution task type information, position information and technical index value set of each flight platform;The technical index value set includes several technical index values;The task demand information set and flight platform cluster technical index information set are preprocessed, and obtain preprocessed information set;The preprocessed information set is subjected to track planning processing, and obtains the track set of flight platform cluster.

The invention discloses an auto-regression and mask diffusion double-normal-form fusion language model hardware acceleration system based on an FPGA (Field Programmable Gate Array), and relates to the field of FPGA and machine learning. The invention provides a model core calculation process-oriented hardware acceleration architecture by aiming at a language model fusing double normal forms of an autoregression model and a mask diffusion model and adopting the characteristics of revising an attention mechanism and parallel generation of a KV cache. The method disclosed by the invention is implemented by taking an Eso-LMs (Esolic Language Models) model as an example. The system comprises a layer normalization and adaptive layer normalization modulation module, a QKV projection module, a rotation position coding application module, a KV cache management module, a multi-head attention calculation module, an output projection and residual connection module and a multi-layer perceptron module. By optimizing the calculation sequence and the data flow of each module in the model calculation process and adopting the pipeline parallel and resource reuse technology, the efficient reasoning acceleration of the language model fusing the autoregression and mask diffusion double normal forms on the FPGA platform is realized, and the model reasoning speed is obviously improved. According to the system, the advantage of FPGA customizable hardware acceleration is fully exerted, the utilization efficiency of hardware resources is improved, data pipeline blockage is eliminated, calculation delay and storage overhead are reduced by reconstructing the data flow direction and constructing a whole-process pipeline processing architecture, and the system is suitable for the deployment requirement of an edge calculation scene.

The embodiment of the invention provides a gas Internet of Things application system, an implementation method, electronic equipment and a storage medium, and the system comprises a target object domain, a perception control domain, a service providing domain, an operation and maintenance management and control domain and a user domain. Efficient access and standard operation management of internet-of-things data are promoted, high-quality data services are provided for business applications, data sharing and opening are achieved, the quality and value of data assets are improved, and decision making and innovation of enterprises are supported. A top-level framework support is provided for application of the gas transmission and distribution Internet of Things system from a macroscopic level, customizability and expansibility of upstream and downstream enterprises are supported, and collaboration and sharing among the enterprises are promoted.

This invention provides a method for preparing hydrogen and sulfur from solid waste gypsum through reduction and acidification in a cement kiln, relating to the field of solid waste disposal technology. The method involves targeted local modifications to a novel dry-process cement clinker rotary kiln production system. Using desulfurized gypsum, phosphogypsum, and other solid waste gypsum as raw materials, the gypsum is crushed, ground, preheated, and dehydrated. Then, it is calcined in a modified three-lobe gravity semi-suspended rotary kiln at 800–1100℃ in a reducing atmosphere to generate high-purity calcium sulfide. After sealed cooling, the calcium sulfide reacts with byproduct hydrochloric acid to produce high-purity hydrogen sulfide. The hydrogen sulfide is then used to co-produce hydrogen and sulfur via a medium-assisted electrochemical decomposition method, or high-purity sulfur can be directly prepared using the Claus process. This invention achieves full resource utilization of solid waste gypsum using existing cement kiln equipment, requires minimal modification, has low investment costs, and enables the cascade utilization of CO waste gas and kiln waste heat, reducing overall energy consumption by more than 30% compared to traditional processes.

The present invention provides a project management system based on an industrial cloud platform and an implementation method, comprising: a cloud industrial platform, users, and suppliers; wherein the cloud industrial platform comprises a database module for collecting user input data, an intelligent module for data processing, optimization, and generation of feasible solutions, and a decision support module for solution evaluation and comparison; the cloud platform collects user manufacturing service requests and supplier quotations, processes them through an intelligent decision-making algorithm, and finds the best manufacturing solution according to user needs; the intelligent decision-making algorithm generates solutions based on a nested algorithm, helping suppliers and users to minimize time and cost according to specific solution feature factors, and has good stability and system performance.

The invention discloses a construction method for filling a roadbed with bagged broken solidified soil, and relates to the technical field of road engineering and dredged sludge solidification resource utilization. According to the construction method, through the technological process of solidification, crushing, screening, bagging and layered filling, the overall solidified soil which is large in size, prone to cracking and poor in gradation is converted into gradation artificial aggregate with the controllable particle size and the good compaction degree, and the gradation artificial aggregate is used for roadbed filling in a bagged unit mode. Compared with a traditional in-situ overall curing or fluid curing method, the method has the advantages that the grading and compaction performance of the cured soil can be remarkably improved, and the roadbed filler structure is more uniform and controllable; the stability and durability of the curing material are improved through lateral restraint and water control and air permeability of the bag body, and the risks of cracking and water damage are reduced. The method is simple and convenient in construction process, can be combined with field machinery to realize continuous operation, and is beneficial to in-situ resource utilization of a large amount of dredged sludge and popularization and application of road foundation engineering.

The invention provides a distillation method for a visual large model, and the method comprises the steps: obtaining a teacher model which is a visual large model with a Transform structure; performing structure pruning on the teacher model to generate a plurality of auxiliary models; optimizing and training the teacher model and the plurality of auxiliary models in a parameter sharing mode by utilizing an optimization loss function Loss number; selecting the auxiliary model with the highest comprehensive score from the plurality of optimized auxiliary models as a selected auxiliary model; and training the selected auxiliary model and the student model by using an optimized loss function to obtain a final student model. By utilizing the technical scheme of the invention, the model knowledge can be transmitted from the full-scale teacher model to the student model as much as possible, so that the student model achieves the best scale and performance, and the scale of the student model is small enough, so that the student model can be conveniently embedded into actual application equipment.

The invention provides a resource scheduling method and system for BIM (Building Information Modeling) analysis and visualization, and the method comprises the steps: initiating a model service request to a server side through a user side, the request parameter at least comprising a project ID (Identity); the service registration center of the server side selects a server node of which the load is lower than a threshold value as a transfer station to temporarily receive the model service request; the transfer station classifies the requests based on the request names of the model service requests, obtains target data based on public query and feeds back the target data to the user side or continues to execute the following steps; the transfer station verifies a routing identifier carried in a request header of the model service request, obtains a target server node, and forwards the model service request to the target server node; and the target server node executes a model analysis or visualization task based on the model service request. According to the method, the single-machine deployment performance bottleneck is solved, and the model analysis and visualization efficiency is remarkably improved.

The invention provides a communication system signal accurate scheduling method and device. The method comprises the steps that configuration parameters including a load indication coding sequence, exclusive orthogonal resource configuration and time sequence relation parameters are determined; based on the configuration parameters, when the terminal has to-be-transmitted data, determining a target load size according to a pre-configured load size value set, generating a corresponding load indication signal, and sending the load indication signal through an orthogonal resource allocated to the load indication signal; the network side receives and analyzes the load indication signal to obtain a target load size, and generates and issues uplink precise authorization containing matched transmission resource parameters according to the target load size; and the terminal executes uplink data transmission according to the authorization. According to the invention, through a mechanism of'short load indication + precise authorization ', a multi-round signaling interaction and base station first decoding process in traditional dynamic scheduling is eliminated, the power consumption and transmission delay of the terminal are remarkably reduced, the uplink resource utilization rate is improved, and the method is particularly suitable for low-power-consumption and low-delay scenes such as the Internet of Things and industrial control.

This application relates to a digital notch filter, a digital low-pass filter, a design method, a dielectric, and an electronic device. The digital notch filter includes: a cascaded limiting boundary anchoring unit and a limiting zero-point modulation unit. The limiting boundary anchoring unit employs a cascaded integrator-comb filter structure to generate a first attenuation zero at the boundary frequency of the target notch band. The limiting zero-point modulation unit employs a finite-length unit impulse response filter structure to generate at least one second attenuation zero within the target notch band. The first attenuation zero and at least one second attenuation zero constitute a continuous suppression band for the target notch band in the amplitude-frequency response of the output signal of the limiting zero-point modulation unit. Using the digital notch filter provided in this application, a digital low-pass filter that can perform deep broadband suppression of power frequency interference while maintaining strict linear phase and excellent low-pass characteristics can be designed without significantly increasing hardware resources and power consumption.

The invention relates to the technical field of resource utilization of household garbage and municipal sludge, in particular to a method for preparing powdered activated carbon from household garbage, which comprises the following steps of: firstly, preparing sludge garbage particles by using the household garbage and the municipal sludge as raw materials; then, pyrolyzing and carbonizing the sludge garbage particles in an organic solid waste multifunctional pyrolyzing and carbonizing furnace to obtain activated carbon; then, the activated carbon is crushed and floated, and a high-quality activated carbon suspension is obtained; and finally, carrying out spray drying on the high-quality activated carbon suspension to obtain powdery activated carbon. The powdery activated carbon is prepared from the household garbage and the municipal sludge, the municipal sludge does not need to be dried in advance, the preparation technology for preparing the activated carbon from the household garbage is simplified, the production cost of the activated carbon is remarkably reduced, efficient resource utilization of the household garbage and the municipal sludge is achieved, and the method has the advantages of saving resources, protecting the environment and improving the economic benefits. The method has important economic benefits and environmental benefits.

The application relates to the technical field of satellite communication, and discloses a transmission resource scheduling method, equipment and a program product, wherein the method comprises the following steps: obtaining one or more target transmission requests, the target transmission requests coming from different target equipment; determining a scheduling control coefficient of each target transmission request, and constructing a transmission request sequence based on the scheduling control coefficient, wherein the scheduling control coefficient comprises a load saturation coefficient and a forwarding priority coefficient; obtaining a channel quality parameter corresponding to each target transmission channel, determining an available waveform set of the target transmission channel according to the channel quality parameter, and determining a target transmission waveform of the target transmission request in the available waveform set; for any target transmission request in the transmission request sequence, allocating a time slot resource to the target transmission request according to the target transmission waveform, and distributing the allocation result to the corresponding target equipment. The technical scheme provided by the application can improve resource efficiency, fairness of resource allocation and reliability of transmission.

The application discloses a Bluetooth earphone dynamic teaming method and system based on Auracast protocol, and belongs to the technical field of wireless communication and audio processing. The method comprises the following steps: embedding a scene semantic label in a broadcast assistant signal by a broadcasting device; collecting self context information by a listening device, calculating a matching weight with each broadcast source through a recommendation decision engine, and realizing intelligent sorting, filtering or automatic joining of a broadcast group. The broadcasting device supports creating a dynamic hierarchical broadcast group with role permissions, time-limited access codes and multiple audio sub-streams. In the overlapping coverage area, the listening device triggers intelligent switching based on signal quality and context matching degree, and realizes seamless connection by using pre-synchronization technology. In addition, the system synchronizes group state information through an auxiliary channel to realize state visualization and interaction. The application upgrades Auracast broadcast from "manual, static and equal" to "automatic, dynamic and intelligent", greatly improving the convenience, management accuracy and immersion experience in the multi-user audio sharing scene.