Abstract: A method includes: determining, a first pixel in a receiving field of view of a radar and N sampling point sets in an echo signal corresponding to the first pixel; estimating an estimated distance between the radar and a target object based on each first sampling point set of the N sampling point sets, and determining, based on each estimated distance, M cumulative receiving fields of view in a one-to-one correspondence with M data frames; determining a second sampling point set in echo signals corresponding to Q neighboring pixels, and superposing each first sampling point set and the corresponding second sampling point set to obtain an echo signal that corresponds to the first pixel and that is obtained; and calculating an actual distance between the radar and the target object based on the echo signal obtained after superposition processing.

Abstract: An example data center system includes server devices hosting data of a first tenant and a second tenant of the data center, network devices of an interconnected topology coupling the server devices including respective service virtual routing and forwarding (VRF) tables, and one or more service devices that communicatively couple the network devices, wherein the service devices include respective service VRF tables for the first set of server devices and the second set of server devices, and wherein the service devices apply services to network traffic flowing between the first set of server devices and the second set of server devices using the first service VRF table and the second service VRF table.

Abstract: Techniques are disclosed for deploying software upgrades to a mixed network of In-Service Software Upgrade (ISSU)-capable and ISSU-incapable network devices without interrupting network traffic serviced by the mixed network. In one example, a centralized controller for a network determines that first network devices of a plurality of network devices for the network are In-Service Software Upgrade (ISSU)-capable and second network devices of the plurality of network devices are not ISSU-capable. The centralized controller transmits messages instructing the first network devices to perform an ISSU operation. Further, the centralized controller transmits messages instructing each network device of the second network devices to transmit a message to peer network devices of the network device, the message indicating that the network device is not ISSU-capable.

Abstract: A multi-dimensional feature identification method of a disaster-causing cyclone includes: determining a disaster-causing range based on a path of the disaster-causing cyclone, dividing the disaster-causing range into multiple grid points, obtaining meteorological data including wind speeds and rainfall amounts of the grid points within the disaster-causing range; determining, based on historical typhoon data, disaster-causing thresholds including a wind speed disaster-causing threshold and a rainfall disaster-causing threshold for the meteorological data; constructing a multi-dimensional feature database for disaster-causing events; and performing multi-dimensional feature identification on the disaster-causing cyclone based on the multi-dimensional feature database for disaster-causing events.

Abstract: A method, a device and a storage medium for evaluating wind energy resources in complex terrain are provided, and the method includes: obtaining a climate field based on observation data of wind speed; obtaining an anomaly field; superimposing a climate field interpolation result and an outlier interpolation result with a consistent spatial resolution to obtain a wind speed interpolation result; performing a deviation correction on the wind speed interpolation result and the observation data of wind speed to obtain a final result; calculating an average effective wind power density; and estimating a wind power density based on a daily average wind speed. An accuracy of wind speed data is improved; the wind energy resources are evaluated in situations including complex terrain and lack of hourly wind speed data; and a high-precision data set of the wind energy resources is established to improve an evaluation accuracy of the wind energy resources.

Abstract: A radar power control method and an apparatus are provided. The method includes: emitting a first detection signal at a target emission angle; obtaining a reflectivity of a first detection point of the first detection signal if signal power of an echo signal of the first detection signal is less than a preset power threshold, where the first detection point is a point on a surface of a detected object in a direction of the target emission angle; and increasing emission power corresponding to the target emission angle if the reflectivity of the first detection point is greater than a preset first threshold. The solution helps consider both power consumption and a detection distance of a radar.

Abstract: The invention relates to a fault transient features optimization method and system of AC/DC system based on dissipated energy, which belongs to the HVDC transmission technology and is used to solve the problem that the DC pulsed current is too high and the generator power angle swing of the AC system on the rectifier side is too large during the process of the HVDC transmission system restart on fault.

Abstract: A method and system for evaluating casualty caused by landslide chain disaster induced by heavy rain are provided. The method includes: obtaining historical landslide data, candidate influence factors and personnel traffic distribution data of an observation site; dividing the historical landslide data into a model construction sample group, a model verification sample group, and a model test sample group; obtaining an occurrence probability of landslide chain disaster of each spatial position in the observation site; determining a start-up landslide source region of the landslide chain disaster according to the model verification sample group and the occurrence probability; determining an affected region of the landslide chain disaster according to the start-up landslide source region; determining a personnel number exposed to the landslide chain disaster; and setting an event division threshold, and evaluating the number of casualties according to the event division threshold and the personnel number.

Abstract: A system for configuring a data center includes a fabric management server coupled to a management switch. A provisional Software Defined Networking (SDN) controller executing on the fabric management server can discover physical servers coupled to the management switch, receive network interface configuration information from the physical servers, and use the discovered network interface configuration information to determine a configuration for switches and servers coupled to an IP fabric. The configuration can be migrated to a full functionality SDN controller.

Abstract: Techniques are disclosed for promulgating service information and topology information in a network in a high availability manner. An example device is configured to create a first service and topology exchange protocol (STEP) document. The first STEP document includes service information and topology information. The example device is configured to send the first STEP document to a first STEP repository for forwarding to at least one subscribing network device. The example device is also configured to send the first STEP document to a second STEP repository for forwarding to the at least one subscribing network device.

Abstract: A virtual port group abstraction can facilitate automated configuration of devices in a data center. For example, a data center administrator can define a virtual port group to include a set of logical and physical interfaces for devices allocated to a particular department or other group within a company. An administrator for the department can then utilize a user interface to perform actions with respect to the virtual port group. The actions can include configuration actions, modeling actions and/or deployment actions. An action received by a network management controller such as a Software-Defined Networking (SDN) controller can be converted into the appropriate actions for the relevant logical and physical interfaces that are configured to be part of the virtual port group.

Abstract: A high-temperature disaster forecast method based on a directed graph neural network is provided, and the method includes the following steps: S1, performing standardization processing on meteorological elements respectively to scale the meteorological elements into a same value range; S2, taking the meteorological elements as nodes in the graph, and describing relationships among the nodes by an adjacency matrix of graph; then learning node information by a stepwise learning strategy and continuously updating a state of the adjacency matrix; S3, training the directed graph neural network model after determining a loss function, obtaining a model satisfying requirements by adjusting a learning rate, an optimizer and regularization parameters as a forecast model, and saving the forecast model; and S4, inputting historical multivariable time series into the forecast model, changing an output stride according to demands, and thereby obtaining high-temperature disaster forecast for a future period of time.

Abstract: The present disclosure provides a meteorological big data fusion method based on deep learning, including the following steps: constructing multi-source meteorological data samples; according to an original resolution of different climate variables, selecting a corresponding super-resolution multiple to obtain an optimized super-resolution module under the constraint of maximizing information retention efficiency; constructing a spatial-temporal attention module using a focused attention mechanism, and selecting a corresponding time stride according to periodic characteristics of different climate variables; constructing a meteorological data fusion model in combination with the optimized super-resolution model and the spatial-temporal attention module; taking a minimum resolution of climate variables as a loss function, and training the meteorological data fusion model with the multi-source meteorological data samples; and importing the acquired real-time meteorological data from multiple data sources into t

Abstract: A high-temperature disaster forecast method based on a directed graph neural network is provided, and the method includes the following steps: S1, performing standardization processing on meteorological elements respectively to scale the meteorological elements into a same value range; S2, taking the meteorological elements as nodes in the graph, and describing relationships among the nodes by an adjacency matrix of graph; then learning node information by a stepwise learning strategy and continuously updating a state of the adjacency matrix; S3, training the directed graph neural network model after determining a loss function, obtaining a model satisfying requirements by adjusting a learning rate, an optimizer and regularization parameters as a forecast model, and saving the forecast model; and S4, inputting historical multivariable time series into the forecast model, changing an output stride according to demands, and thereby obtaining high-temperature disaster forecast for a future period of time.

Abstract: The present disclosure provides a meteorological big data fusion method based on deep learning, including the following steps: constructing multi-source meteorological data samples; according to an original resolution of different climate variables, selecting a corresponding super-resolution multiple to obtain an optimized super-resolution module under the constraint of maximizing information retention efficiency; constructing a spatial-temporal attention module using a focused attention mechanism, and selecting a corresponding time stride according to periodic characteristics of different climate variables; constructing a meteorological data fusion model in combination with the optimized super-resolution model and the spatial-temporal attention module; taking a minimum resolution of climate variables as a loss function, and training the meteorological data fusion model with the multi-source meteorological data samples; and importing the acquired real-time meteorological data from multiple data sources into t

Abstract: An evaluation method for evaluating a precipitation-induced landslide disaster loss under climate change is provided. The evaluation method belongs to the technical field of geological disaster prevention and treatment. The evaluation method uses a physical process based model, in considering of spatial heterogeneity of land-surface features of grids in the area, to obtain precipitation thresholds corresponding to the respective grids in the area having the spatial heterogeneity. Historical data and climate model data are taken in combination to select suitable climate models, and the model then is used to simulate landslide prone zones and possible influence zones caused by landslides. An influence zones simulated by the evaluation method can better match disaster loss grid data, which can solve the problem that climate change scenarios and influence of landslide are difficult to be evaluated in landslide disaster evaluation.

Abstract: An evaluation method for evaluating a precipitation-induced landslide disaster loss under climate change is provided. The evaluation method belongs to the technical field of geological disaster prevention and treatment. The evaluation method uses a physical process based model, in considering of spatial heterogeneity of land-surface features of grids in the area, to obtain precipitation thresholds corresponding to the respective grids in the area having the spatial heterogeneity. Historical data and climate model data are taken in combination to select suitable climate models, and the model then is used to simulate landslide prone zones and possible influence zones caused by landslides. An influence zones simulated by the evaluation method can better match disaster loss grid data, which can solve the problem that climate change scenarios and influence of landslide are difficult to be evaluated in landslide disaster evaluation.

Abstract: A device may receive information identifying a set of tasks to be executed by a microservices application that includes a plurality of microservices. The device may determine an execution time of the set of tasks based on a set of parameters and a model. The set of parameters may include a first parameter that identifies a first number of instances of a first microservice of the plurality of microservices, and a second parameter that identifies a second number of instances of a second microservice of the plurality of microservices. The device may compare the execution time and a threshold. The threshold may be associated with a service level agreement. The device may selectively adjust the first number of instances or the second number of instances based on comparing the execution time and the threshold.

Abstract: The invention relates to a fault transient features optimization method and system of AC/DC system based on dissipated energy, which belongs to the HVDC transmission technology and is used to solve the problem that the DC pulsed current is too high and the generator power angle swing of the AC system on the rectifier side is too large during the process of the HVDC transmission system restart on fault.

Abstract: A system for configuring a data center includes a fabric management server coupled to a management switch. A provisional Software Defined Networking (SDN) controller executing on the fabric management server can discover physical servers coupled to the management switch, receive network interface configuration information from the physical servers, and use the discovered network interface configuration information to determine a configuration for switches and servers coupled to an IP fabric. The configuration can be migrated to a full functionality SDN controller.