35 results about "Cloud user" patented technology

The invention relates to the field of cooking spill-proof control, and discloses a cooking spill-proof control method and system based on cloud user behavior analysis. The method comprises the following steps: based on the Internet of Things, obtaining a time sequence pressure value in the electric pressure cooker from heating start to a preset first time period through a preset cooking program and a heating switch operation record of a user on the electric pressure cooker; and when the pressure value at any moment in the time sequence pressure values is greater than or equal to the overflow pressure value and the heating switch operation record of the user on the electric pressure cooker comprises that the time duration of operating the electric pressure cooker to stop heating exceeds the preset time duration, adding an anti-overflow control program in a preset cooking program of the electric pressure cooker, and sending the anti-overflow control program to the electric pressure cooker based on the Internet of Things so as to update a preset cooking program of the electric pressure cooker. The cooking utensil can be intelligently controlled in combination with behaviors of the user to prevent overflow.

The invention provides a user application portrait analysis and management method and device based on a large model. The method comprises the following steps: collecting data through a webpage end resource management platform, wherein the data comprises behavior data, resource use state data, historical demand information and application performance indexes of government affair cloud users; carrying out integration and classification analysis on the collected data based on a SpringBoot framework, and generating a user basic portrait; inputting the user basic portrait into a Haiyu big model for deep data mining; and predicting a user service development trend and a resource use risk in a future preset period through the Haiyu model. The scheme of the invention can combine government affair cloud service characteristics to realize an application portrait analysis management method which has prediction capability and supports intelligent decision making, and improves the insight of service providers for user demands.

Disclosed is a method for implementing an intra-cloud and inter-cloud multicast function by virtual instances in a public cloud. The present invention mainly solves the issue of supporting a multicast in virtual instances of a public cloud user in a VPC or between VPCs, and also solves the issue of multicast communication between a user offline IDC and cloud-based virtual instances. When multicast members are added to a multicast group, the functions of the cloud-based virtual instances statically adding / leaving the multicast group and dynamically adding / leaving the multicast group by means of an IGMP protocol are supported, so that a cloud-based customer can use a multicast technology service in a service having a multicast requirement, providing the customer with a multicast service having low latency, fast access, and no packet loss. The method is applicable to various fields and live streaming services. The multicast is supported in a virtual network without changing a switch and a router on a computing node of a data center.

This application relates to the field of cooking anti-overflow control, and discloses a cooking anti-overflow control method and system based on cloud user behavior analysis. The method includes: obtaining, based on the Internet of Things, the sequential pressure values in the electric pressure cooker within a preset first time period from the start of heating to the preset cooking program of the electric pressure cooker, and the operation record of the heating switch of the electric pressure cooker by the user; when the pressure value at any moment in the sequential pressure values is greater than or equal to the overflow pressure value, and the operation record of the heating switch of the electric pressure cooker by the user includes that the operation of stopping the heating of the electric pressure cooker exceeds the preset duration, an anti-overflow control program is added to the preset cooking program of the electric pressure cooker, and the anti-overflow control program is sent to the electric pressure cooker based on the Internet of Things to update the preset cooking program of the electric pressure cooker. This application can intelligently control cooking appliances in combination with user behavior to prevent overflow.

The invention discloses a vehicle-mounted audio control method, system and device and a medium, and the method comprises the steps: matching the user information of a passenger at each current seat through the weight of the passenger at each current seat, matching a first song list for the passenger through a pre-training model, and if the information of the passenger at the current seat cannot be matched, carrying out the matching through a physiology-behavior combined clustering method, the current seat passenger person information and the cloud user clustering center are matched to the most similar group, a song list with the highest similarity between the group and the current seat passenger person information is extracted as a second song list, and during song list playing, a pressure vibration sensor is monitored to obtain the body movement frequency of each current seat passenger; analyzing the body movement frequency of the passengers on each current seat so as to obtain user feedback information, obtaining respective preference list overlapping parts of the passengers on each current seat by using the user feedback information, and generating a third song list for playing; the problem that personalized playing control of an existing vehicle-mounted audio playing device in a multi-passenger scene is insufficient is solved.

The present invention discloses a method for recommending oilfield cloud application components based on a coefficient of variation method, comprising the following steps: S1, collecting oilfield cloud application component log data; S2, data normalization processing; normalizing an oilfield application component evaluation matrix to eliminate dimensional differences between different indicators, so that the numerical value of each indicator is mapped to an interval between [0, 1], and obtaining a standardized evaluation matrix; S3, constructing a virtual rating matrix by using the coefficient of variation method; S4, establishing a recommendation model; establishing an oilfield cloud application component recommendation model by combining a user-based collaborative filtering algorithm with a coefficient of variation method, adopting the coefficient of variation method to analyze and simulate user ratings from multiple dimensions, calculating the similarity between oilfield cloud users according to the Jaccard formula, calculating the user's interest in the oilfield cloud application component by using an interest calculation formula, and the interest value is the user's recommendation result.

The invention relates to an online conference data transmission method and device and an online conference system. The method in one aspect is applied to local terminal equipment, a local media stream server is deployed in the local terminal equipment, accessory equipment corresponding to the local terminal equipment participates in the local media stream server through a local area network, and the local terminal equipment participates in a target online conference in a cloud media stream server through a wide area network. The method comprises the steps of obtaining a media stream subscription request of accessory equipment, subscribing SVC stream data corresponding to a target cloud user identifier from a cloud media stream server under the condition that the media stream subscription request comprises the target cloud user identifier, obtaining target SVC stream data corresponding to the media stream subscription request, forwarding the target SVC stream data to a local media stream server, and sending the target SVC stream data to the accessory equipment. And the accessory device obtains the target SVC stream data from the local media stream server. By adopting the method, the performance consumption of the local terminal equipment can be reduced.

This invention relates to the field of internet technology, specifically to a method and system for efficiently processing massive files based on cloud functions. The system includes a demand acquisition and cloud function locking module that acquires the business usage requirements of cloud users and locks the cloud functions and corresponding cloud function interfaces for the business files to be processed within those requirements. This invention deeply customizes cloud functions and object storage, reducing file upload and download processing, minimizing network impact, improving file processing speed, and reducing server consumption. File processing is event-triggered, and its business characteristics are suitable for serverless technology, providing on-demand supply. During periods of high-volume file processing, cloud function instances can be automatically scheduled to meet processing demands. Developers do not need to monitor business peaks and troughs, saving idle time costs and ultimately reducing operational costs. It also enables asynchronous processing of large batches of files, meeting the needs of high-concurrency business scenarios and achieving peak-shaving scheduling.

This invention discloses a differentiated demand coordination method based on a mathematical model of a data center. The method includes constructing a spatiotemporal coordination data center mathematical model for cloud user loads that takes into account the building's thermal dynamics, based on the building's thermal dynamics and the differentiated real-time demands of cloud user loads. Furthermore, a two-stage robust optimization model for the data center that takes into account building thermal dynamics, with the goal of minimizing the data center's daily operating costs, is constructed to obtain an optimal differentiated demand coordination solution. This method considers the impact of uncertainties and establishes a two-stage robust optimization model for the data center's load arrival rate, air conditioning cooling power, indoor temperature, and operating energy consumption. This model exploits the synergistic potential of the data center's own building thermal inertia and spatiotemporal load regulation, maximizes the load and air conditioning system's regulatory flexibility, effectively reduces the energy consumption of the data center's IT equipment and air conditioning system, and improves the economic efficiency and risk mitigation capabilities of the data center's operations.

This invention utilizes BIM software to process pre-acquired equipment structure data into BIM equipment data, which is then displayed in CAD software to create a 3D model. Through twin technology, real-time variable data during equipment operation is synchronously simulated within the 3D model, thereby constructing a dynamic simulation platform. The operational scenario data is then unidirectionally output to the cloud for storage. This accurately synchronizes the 3D operational details of the equipment, converting the operational scenario data into an AR scene labeled with real-time equipment status parameters in the cloud. During equipment diagnostics, after authorization, client terminals or cloud users can access the real-time equipment status parameters within the AR scene based on control commands, enabling information interaction. The client terminal and cloud are connected via an authorized protocol. This facilitates the training of maintenance personnel, addresses the high risk of maintenance errors leading to low equipment maintenance efficiency, and thereby improves equipment maintenance security.

The application relates to a method and system for controlling multi-level security classification of cloud users, and belongs to the technical field of computers.The method comprises the following steps: judging whether a scanning server is normally running; in the case that the scanning server is normally running, determining the security levels of a subject and an object based on a BLP model and a Biba model, the subject being used for indicating a user or a process that sends an access resource request, and the object being used for indicating data or resources that are accessed; performing read-write operations on the subject according to the security levels of the subject and the object; in the case that the read-write operations are performed on the subject, setting the permissions of the subject, and adjusting the security level of the object based on abnormal alarm information.The method can significantly improve the security of a cloud environment, enhance the access control accuracy, optimize the cloud environment management, and promote compliance.Commonly, a safer, more reliable and efficient cloud service environment is provided for cloud users.

The application discloses a novel KVM cloud host micro-isolation method, comprising a virtual machine kernel micro-isolation module based on a Netfilter framework, a host rear-end processing module for realizing a semi-virtualization channel and a cloud host micro-isolation management platform for providing a cloud user with a network strategy configuration interaction capability of a cloud host, and has the beneficial effects that based on a semi-virtualization technology and a kernel Netfilter framework Hook technology, kernel layer configuration capability of a virtual machine network is realized, and through strategy priority control, the problem of invalid security control caused by malicious or incorrect application layer configuration is avoided; based on a semi-virtualization channel, configuration data interaction is realized through a host processing rear-end and the cloud host micro-isolation management platform, a host network is used, a tenant network is not used, and when a strategy configuration is incorrect, the configuration channel can be used for repair, and the problem of cloud host disconnection caused by incorrect network strategy configuration is avoided.

The invention discloses a cloud fortress permission synchronization method, device and equipment, a medium and a product. The method comprises the steps that if it is detected that login authentication of a cloud user on a cloud platform is completed, a cloud user identity token conforming to a cloud platform protocol standard is acquired; carrying out bill exchange on the identity token of the cloud user and the credible authentication service of the cloud fortress through the bridging agent component so as to establish bidirectional credible authentication between the cloud fortress and the cloud user; if it is detected that the bidirectional credible authentication between the cloud fortress and the cloud user is established, determining a mapping relationship between the first policy data and the second policy data; according to the mapping relation between the first strategy data and the second strategy data, based on the resource relation graph of the cloud platform, the resource access authority of the cloud fortress is synchronized. According to the scheme, the problem of low authority collaboration efficiency of the cloud fortress and the cloud platform is solved, and identity authentication protocol adaptation, authority change event real-time capture and resource synchronization of the cloud platform and the cloud fortress are realized by constructing a dynamic strategy translation mechanism.

The invention discloses an electric power information network security protection system and method based on a distributed neural network probe. The system comprises a distributed neural network probe, a threat intelligence storage center, a decision center, a dynamic strategy executor, a decoy module and an immune memory module, the distributed neural network probe is in communication connection with the threat intelligence storage center, and the decoy module is in communication connection with the threat intelligence storage center, the decision center and the dynamic strategy executor in sequence. The decoy module and the immune memory module are respectively in two-way communication with the decision center, distributed neural network probes of the decoy module comprise a terminal probe, a network probe and a cloud probe, and the threat intelligence storage center adopts a mixed framework of a time sequence database, a relational database and a document database. According to the invention, global coverage from terminal process behaviors, network traffic to cloud user activities can be realized, and the discovery capability of an electric power system to unknown threats and hidden attacks is greatly improved.

The invention relates to a user management method, a storage medium, a body fat scale and a user management system. The method comprises the following steps: receiving a user information modification request sent by a terminal, if it is determined that a first cloud user identifier is associated with a first local user identifier from an association relationship between stored cloud user identifiers and local user identifiers of the body fat scale, modifying the first cloud user identifier according to a modification content; and modifying stored user information corresponding to the first cloud user identifier. Wherein the user information modification request comprises a target user identifier and modification content, and the target user identifier comprises a first cloud user identifier or a first local user identifier. Therefore, the user information in the local body fat scale and the user information in the application server can be synchronously modified, the user information in the local body fat scale and the user information in the application server are synchronously managed, the flexibility and reliability of user management operation of the body fat scale are improved, and then the accuracy of body indexes generated by the body fat scale based on the user information can be improved.

The application relates to the technical field of operating systems, in particular to a kernel-mode virtual switch of a Xiongmao operating system. The kernel-mode virtual switch of the Xiongmao operating system adopts an operating system kernel module to provide virtual switch services, supports loading and logging off of the kernel module, supports a standard virtual local area network (VLAN) model and a trunk relay mode, an overlay superposition tunnel, media access control (MAC) forwarding, Internet protocol (IP) routing, a lightweight database, quality of service (QoS) configuration and management, a source MAC load balancing mode, flow control and monitoring, a security group, network address translation (NAT) and Internet protocol version 6 (IPv6). The kernel-mode virtual switch of the Xiongmao operating system can effectively improve the processing speed of network data packets, guarantee network bandwidth indexes and improve the network use experience of cloud users.

Disclosed is a method for implementing an intra-cloud and inter-cloud multicast function by virtual instances in a public cloud. The present invention mainly solves the issue of supporting a multicast in virtual instances of a public cloud user in a VPC or between VPCs, and also solves the issue of multicast communication between a user offline IDC and cloud-based virtual instances. When multicast members are added to a multicast group, the functions of the cloud-based virtual instances statically adding / leaving the multicast group and dynamically adding / leaving the multicast group by means of an IGMP protocol are supported, so that a cloud-based customer can use a multicast technology service in a service having a multicast requirement, providing the customer with a multicast service having low latency, fast access, and no packet loss. The method is applicable to various fields and live streaming services. The multicast is supported in a virtual network without changing a switch and a router on a computing node of a data center.

The invention provides a method and system for providing a cloud application, electronic equipment and a storage medium, and aims to solve the problems that the cloud application is weak in universality and low in configurability and cannot provide customized cloud application services for enterprises, and the method comprises the following steps: obtaining various program components developed according to cloud demands of users, product categories to which the program components belong are distinguished; displaying different product categories for the cloud users for selection and use; assembling the program components of the same product category into a new application service according to the product category selected by the cloud user, and combining the application service into a new cloud product by carrying out personalized configuration on the business process; and publishing a new cloud product, and after the product is successfully published, automatically generating login information to provide cloud product service for a cloud user. According to the method and the device, the randomly assembled cloud service capability can be realized; and the plasticity, remoldability and freedom of the product are improved, and cloud services meeting the requirements of the user are provided for the user.

The application discloses an automatic parking control method, system and car. The method comprises the following steps: obtaining a user's expected shortest distance from a cloud corresponding to a user's driver account, obtaining an actual shortest distance from a historical parking record of a vehicle, then performing weighted average calculation on the two shortest distances to obtain a shortest distance of this time parking, and updating an automatic parking control strategy according to the shortest distance of this time parking, and the vehicle performs automatic parking according to the updated automatic parking control strategy, wherein the shortest distance in the application is the shortest distance between the vehicle's front end and a front obstacle; the application obtains the key index of the shortest distance of this time parking by performing weighted average calculation on the cloud user's expected shortest distance and the local actual shortest distance, realizes that different users have their own automatic parking control strategies, realizes personalized parking for thousands of people, and enhances the safety of automatic parking of the vehicle.

The application provides a non-intrusive household electrical load identification and safety warning method and system, belonging to the technical field of non-intrusive load monitoring; the method comprises: collecting total road electric signals on the edge side, extracting multi-dimensional load characteristics and detecting load switching events; when an unmatched event is detected, triggering a cloud collaborative federated learning incremental update mechanism to realize global model optimization under the premise of protecting privacy; when the identification result is uncertain, a similar device candidate list is pushed to the user, and the model parameters and feature weights are updated according to the user correction feedback; the system comprises: an edge side device, a cloud platform and a user terminal, which jointly constitute an end-edge-cloud-user collaborative closed loop architecture; the application realizes adaptive identification of new devices, stable maintenance of long-term identification accuracy and positive optimization cycle of user participation, effectively improving the intelligent level of non-intrusive load identification and the safety of household electricity.

The invention discloses a risk communication solution method and device based on cloud-side cooperation, a medium and equipment. The method comprises the following steps: acquiring a cloud user access data set and a side user behavior data set of a calling user terminal; respectively carrying out feature extraction on the cloud user access data set and the edge user behavior data set to correspondingly obtain a cloud basic feature set and an edge basic feature set; based on the cloud basic feature set and the edge basic feature set, extracting a space risk feature set and a time risk feature set in a preset time period; and inputting the cloud basic feature set, the edge basic feature set, the space risk feature set, the time risk feature set and the risk solution measure set into a multi-task supervised learning model to obtain an optimal risk solution measure set. According to the invention, the identification accuracy of the risk number and the effectiveness of risk number management and control can be improved.

The present application provides a cloud user management method and related devices, belonging to the field of cloud technologies. The method includes: obtaining user verification information for the cloud user's current access to the cloud, where the user verification information includes at least one of the cloud user's historical cloud usage records, the user type of the cloud user, and the target cloud usage data for the cloud user's current access to the cloud; obtaining evaluation data from a data source that matches the user verification information, where the data source includes the historical cloud usage data of the cloud user, a cloud user of the same user type as the cloud user, or a cloud user meeting a predetermined standard; generating cloud usage cost prediction data for the cloud user's current access to the cloud using the evaluation data, so as to predict the cloud usage cost of the cloud user based on the cloud usage cost prediction data. The embodiments of the present application achieve precise and personalized management of cloud users.

The invention discloses a shared automobile cabin adaptive adjustment method, apparatus and device, and a program product. The method comprises the steps of obtaining user identity information of a target user, current cabin software and hardware information of a target shared automobile and current driving scene information; matching in a cloud user database according to the user identity information and the current driving scene information to obtain a plurality of historical cabin parameters, and determining historical cabin software and hardware information corresponding to the historical cabin parameters; determining the priority of each historical cabin parameter according to the similarity between the historical cabin software and hardware information and the current cabin software and hardware information, and determining a target cabin parameter according to the historical cabin parameter with the highest priority; and issuing the target cabin parameter to the target shared automobile, so that the target shared automobile performs cabin adjustment according to the target cabin parameter. According to the invention, non-inductive synchronization and accurate adaptation of the cabin habits of the user among different shared vehicles are realized, the shared vehicle use experience of the user is improved, and the method can be widely applied to the technical field of intelligent cabins.

1. The name of the design product: graphical user interface for double screen setting operation of computer. 2. The use of the design product: for running programs and displaying information. 3. The design points of the design product: the graphical user interface content in the screen. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Other views are conventional designs, and other views are omitted. 6. Design 1 is designated as the basic design. 7. The use of the graphical user interface: the interface of the design product is a double screen setting graphical interface of cloud PC user terminal, there are two setting methods to facilitate users to quickly set the graphical interface of different accounts on two displays; the graphical interface of the front view is the default initial interface. The first setting method: long press and drag the user account to enter the interface of design 1 change state figure 1; place the user account in the corresponding display icon area, when the user account is set in the corresponding display icon, enter the interface of design 1 change state figure 2. The second method: click the setting icon, long press and drag the user account to enter the interface of design 2 change state 1, place the user account in the corresponding display icon area, when the user account is set in the corresponding display icon, enter the interface of design 2 change state figure 2.

The present invention relates to the field of cloud computing technology, and in particular to a graph-enhanced two-level architecture A3C scheduling method and system for multi-cloud environment tasks. The method comprises: obtaining cloud user task data; constructing a heterogeneous scheduling graph based on the obtained cloud user task data; performing GNN embedding calculation based on the heterogeneous scheduling graph; designing a hierarchical scheduling architecture based on the GNN embedding calculation to separately process mapping tasks of different intensities; performing reward calculation based on the processing results of the mapping tasks; and outputting the optimal strategy. This solution is further refined in the energy consumption and billing model. The model not only considers the communication energy consumption of subtasks, but also supports hierarchical billing strategies for on-demand, reserved, and bidding instances, ensuring that scheduling decisions are closer to the energy consumption and cost structure of the actual cloud platform.

Systems and methods for providing drone activity cloud services to cloud consumers using cloud and edge computing are provided. The drone monitoring service is rendered by drone sensors detecting and identifying drones, cloud and edge servers aggregating drone activity data from sensors and UAS traffic management systems, and cloud consumers monitoring drone activities using cloud and edge devices to access the cloud. The drone data analytics service reports drone activity statistics, predicted drone activities, and abnormal behaviors to cloud consumers based on the statistics and behavior models obtained by machine learning and federated learning techniques. The drone mitigation service, when initiated by cloud consumers, determines how to optimally configure sensors and collaboratively send signals to deactivate unauthorized drones. Moreover, data processing, artificial intelligence, mobility support, and traffic management functional units empower cloud and edge servers to support these cloud services.

The invention relates to the technical field of cloud information, in particular to a video stream optimization method and system for desktop cloud. According to the video stream optimization method for the desktop cloud, a WebRTC retransmission feedback and congestion control mechanism is utilized, the performance and congestion condition of network connection are obtained by counting the packet loss rate and the packet transmission delay, the coding resolution and the frame rate are dynamically adjusted, a super-resolution algorithm and a frame generation algorithm are started at a client, and the video stream optimization efficiency is improved. Therefore, the resolution and the refresh rate preset by the user are kept unchanged. According to the video stream optimization method and system for the desktop cloud, the problems of jamming, frame dropping and black screen can be avoided, and the user experience of the desktop cloud in a weak network scene is greatly improved.

The technical scheme of intelligent cloud management based on portrait information disclosed in the present application applies the technical idea of artificial intelligence to cloud management, and intelligently proposes cloud management suggestion information. In daily work, the use behavior of cloud resources can reflect the characteristics of cloud users or cloud tenants themselves. The technical scheme of intelligent cloud management in the present application extracts and generates portrait information reflecting the characteristics of cloud use through the abstraction of cloud use behavior data, and intelligently proposes cloud management suggestions based on the portrait information.

The invention discloses a resource scheduling method, system and device for a multi-cloud management platform, and a storage medium. The method comprises the following steps: obtaining a first historical behavior set of a user and a multi-cloud operation instruction sent by the user; the first historical behavior set is a plurality of historical operations of the cloud user for selecting a multi-cloud manufacturer; determining a cloud resource set allocated by the multi-cloud management platform according to the first historical behavior set; and in response to an operation of selecting a target cloud resource from the cloud resource set by a user, migrating service data of the multi-cloud management platform to the target cloud resource based on the multi-cloud operation instruction, and performing grid division on the service data and adjusting a data grid of the target cloud resource to obtain target grid data. The method can be widely applied to the technical field of network resource scheduling.