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435results about How to "Quick migration" patented technology

Dependable virtual platform and construction method thereof, data migration method among platforms

The invention discloses a dependable virtual platform and a construction method thereof, a data migration method among platforms. The dependable virtual platform comprises a hardware security chip, a virtual machine monitor (VMM), an administrative domain, a user domain and a dependable serving domain (TSD), wherein an expanded trust chain is used by the TSD for users to establish dependable operating environment. The construction method includes: building the TSD; then establishing secure communication mechanisms between the managing domain and the TSD and between the managing domain and a domestic user domain; accomplishing calls of security application of the user domain to a dependable function by the user domain through interaction with the managing domain, accomplishing transmission and treatments of dependable orders by the managing domain through the interaction of the TSD; interacting a source platform migration engine and a goal platform migration engine; migrating migration data which is produced and based on the hardware security chip and the TSD to a goal platform, and recovering data on the goal platform, accomplishing quick migration of the TSD and a virtual machine. The dependable virtual platform and the construction method thereof, the data migration method among platforms are capable of improving safety of dependable service and providing flexible operation and deployment mechanisms for the platforms.
Owner:INST OF SOFTWARE - CHINESE ACAD OF SCI

Image style migration method and device, electronic device and storage medium

The invention discloses an image style migration method and device, an electronic device and a storage medium. The image style migration method comprises the steps of obtaining a to-be-processed image; processing the to-be-processed image by adopting a style migration model to obtain a first stylized image; wherein the style migration model is obtained by carrying out model training in advance according to the content image, the second stylized image and the third stylized image, the second stylized image is obtained by carrying out stylization processing on the content image, and the third stylized image is obtained by processing the content image by adopting a neural network model. According to the method, the style migration model obtained through pre-training is adopted to perform style migration processing on the to-be-processed image, the processes of solving, optimizing and the like on the loss function in the process of executing style migration are avoided, and therefore rapidstyle migration is achieved. Moreover, the style migration model is obtained by supervising and training the neural network model by adopting paired input and output samples, so that the stylizationeffect of the model can be improved.
Owner:BEIJING DAJIA INTERNET INFORMATION TECH CO LTD

Deep reinforcement learning method and device based on environment state prediction

The invention discloses a deep reinforcement learning method and device based on environment state prediction. The method comprises the following steps that: establishing a deep reinforcement learningnetwork based on the environment prediction, and selecting a proper strategy decision method according to the characteristics of tasks; initializing network parameters, and establishing a storage area which meets a storage condition as an experience replaying area; according to the output of a strategy decision network, selecting a proper strategy to interact with environment, and continuously storing the interaction information of an interaction process into the experience replaying area; sampling a first sample sequence from the experience replaying area, utilizing a supervised learning method to train an environment prediction part, and repeating a first preset frequency; sampling a second sample sequence from the experience replaying area, fixing the parameter of the environment prediction part to be constant, utilizing a reinforcement learning method to train the strategy decision part, and repeating a second preset frequency; when network convergence meets a preset condition, obtaining a reinforcement learning network. By use of the method, learning efficiency can be effectively improved.
Owner:TSINGHUA UNIV

Graphene modified composite mesoporous carbon microsphere air purifying preparation

The invention provides a graphene modified composite mesoporous carbon microsphere air purifying preparation. A certain amount of beta-cyclodextrin is added to thin-layered nano-SiO2 particles covering the surfaces of obtained micro-SiO2 particles, a certain quantity of obtained RGO/TiO2 nanoparticles is added simultaneously, -OH, -COOH, C-O-C and C=O oxygen-containing functional groups rich on the surface of graphene are adsorbed by and bonded with the RGO/TiO2 nanoparticles on the basis of the molecular recognition characteristic of beta-cyclodextrin, then a certain amount of CTAB (cetyltrimethylammonium bromide) surfactant is added, CTAB serving as a micelle stabilizer can stop the RGO/TiO2 nanoparticles from further hydrolysis and growth, and finally, the novel air purifying preparation adopting RGO/TiO2 supported by carbon microspheres with a mesoporous shell structure is obtained. With adoption of the scheme, the purity is high, RGO/TiO2 supported by the carbon microspheres with the mesoporous shell structure in powder is better in bonding performance, uniform in distribution and controllable in dimension at mesopores, and the air purifying preparation can be used for purifying polluted air and removing dust in a haze environment as well as photo-catalytically degrading and separating nitric oxide, sulfide or other organic pollutants in the polluted air.
Owner:AVIC BEIJING INST OF AERONAUTICAL MATERIALS

A question and answer library knowledge management system based on deep learning and an implementation method thereof

The invention relates to the technical field of big data, in particular to a question and answer library knowledge management system based on deep learning and an implementation method thereof. The system comprises a global setting module, a knowledge management module, a knowledge learning module, a knowledge statistics module, a session simulation module and a terminal docking module, each module has setting functions of adding, deleting, modifying, checking and the like; the method comprises the following basic steps: (1) carrying out global setting; (2) performing knowledge management, including knowledge creation; (3)carrying out knowledge learning, wherein knowledge mining and problem clustering are carried out through an iteration process of big data information/historical sessions,and user annotation feedback is carried out; (4) carrying out session simulation: simulating a session of a real environment; (5) carrying out knowledge statistics, and high frequency and sudden increase problems in the application field are understood for improvement and decision making; and (6) carrying out multi-terminal adaptation and distribution on the packages by the modules. According tothe system and the method, the natural language habit of human beings can be known, the complex problem of a user can be known, and manual intervention is not needed.
Owner:G CLOUD TECH

Preparation method and application of network structure nano NaVPO4F/C composite material and application thereof

The invention discloses a network structure nano NaVPO4F / C composite material, and a preparation method thereof. The preparation method comprises the steps of adding a proper amount of alcohol to a mixed aqueous solution of a sodium source, a vanadium source, a fluorine source, a phosphorus source, a reducing agent and a carbon source; carrying out a solvothermal reaction at a temperature of 120-210 DEG C to obtain a carbon coated NaVPO4F precursor; and then calcining at a temperature of 750-900 DEG C under an inert atmosphere. In a high temperature environment, amorphous carbon is partially burned; a degree of graphitization is increased; NaVPO4F particles are fused and crystallized; grains grow; the carbon layer coating the NaVPO4F precursor can inhibit NaVPO4F particles from fusing together to some degree; and finally the network structure nano NaVPO4F / C composite material is formed. The material has a unique network structure and good porosity, and is beneficial to rapid migration of an electrolyte. Electrical conductivity of the whole material is improved due to effective compounding with carbon, and further electrochemical performance of NaVPO4F is increased. The network structure nano NaVPO4F / C composite is an excellent positive electrode material of the sodium ion battery.
Owner:SOUTHWEST UNIV

Preparation method of multistage-channel carbon electrode material

InactiveCN103183329ARich pore size distributionFacilitate quick migrationCarbon preparation/purificationHalogenEmulsion
A preparation method of a multistage-channel carbon electrode material mainly comprises the following steps: cleaning a halogen egg shell, performing ball milling on the shell for 2-12 hours, performing acid-base soak on the shell for 6-48 hours, after being subjected to calcination in an inert atmosphere, performing ultrasonic treatment on the shell in HNO3, using HCl to soak the shell, washing the shell to be neutral, and drying the shell to obtain a multistage-channel carbon material; grinding the multistage-channel carbon material to powder; mixing the carbon material, acetylene black and PTFE emulsion according to the mass ratio of 80:15:5 uniformly by adopting alcohol ultrasonography; performing water bath at 65 DEG on the mixture to enable the mixture to be heated to be muddy; then taking out 0.5-10 mg muddy product to uniformly coat on a piece of foam nickle of 1*1 cm; drying the foam nickle in the vacuum for 12 hours; and finally performing tabletting on the foam nicke under a pressure of 4 MPa to obtain an electrode piece, and vacuum soaking the electrode piece in an electrolyte solution for 6 hours for reservation. The carbon electrode material is energy-saving, environment-friendly and good in recycling stability of the carbon electrode material; and the discharge specific capacity can reach up to 176 F/g.
Owner:YANSHAN UNIV
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