Abstract: Systems and methods for reconciling location based on multiple computing device signals. For example, the computing system can obtain location datasets associated with freight carrier services from computing sources. The computing system can determine an expected signal pattern for a location associated with a freight transportation service. The computing system can determine, for each computing source, a confidence score. The confidence score can represent the probability that the respective location dataset is associated with a load being transported for a freight transportation service. The computing system can determine a primary location dataset based on the confidence scores. The computing system can perform actions based on the primary location dataset.

Abstract: The present application relates to an organic compound, and an electronic element and an electronic apparatus using the same. The organic compound of the present application has a structure shown in Formula I. The organic compound of the present application is applied to the electronic element, such as an organic electroluminescent device, so that the performance of the device can be significantly improved.

Abstract: Disclosed are a system and a method for capturing a space target. The system includes a plurality of capturing devices, a delivery device, a launching device, and a deceleration and recovery device, each of the plurality of capturing devices is configured to be launched into a target orbit to capture a defunct space target, the delivery device is configured to deliver, along a preset delivery trajectory, each of the plurality of capturing devices to a first preset location in the launching device, the launching device is configured to launch each of the plurality of capturing devices located at the first preset location into the target orbit to capture the defunct space target, and the deceleration and recovery device is configured to decelerate each of the plurality of capturing devices after it is launched and flies a preset distance.

Abstract: The present disclosure provides a multi-arm spacecraft model predictive control method based on the mixture of Gaussian processes, equipment, and a medium. Model predictive control has excellent performance in dealing with complex nonlinear systems such as multi-arm spacecrafts with various constraints, and is widely applied to ground robots, unmanned aerial vehicles, autonomous driving and other practical scenarios. Therefore, a task space controller is designed based on the model predictive control in the present disclosure. Besides, in order to enhance the anti-interference capability of the present disclosure, an interference model is established and compensation is carried out in the model predictive control by utilizing the characteristics of small training data volume and high training speed in the mixture of Gaussian processes. Finally, a thrust distribution method is designed to complete platform control.

Abstract: A smart manipulator based on vision-based force and position fusion measurement, which solves overall bloated structure in the existing manipulator system, includes a thumb, an index finger, a middle finger, a ring finger, a little finger, a palm, two depth cameras and a plurality of drive measurement units, wherein the drive measurement units are evenly distributed to form a truncated cone structure, the two depth cameras are symmetrically arranged on a rear end of the drive measurement units while each depth camera is respectively arranged along a generatrix direction of the truncated cone structure. The palm is arranged at a front end of the drive measurement units, and the five fingers are arranged at a front end of the palm, each of the thumb, the index finger, the middle finger, the ring finger and the little finger are connected to two or more the drive measurement unit respectively.

Abstract: Systems and methods for reconciling location based on multiple computing device signals. For example, the computing system can obtain location datasets associated with freight carrier services from computing sources. The computing system can determine an expected signal pattern for a location associated with a freight transportation service. The computing system can determine, for each computing source, a confidence score. The confidence score can represent the probability that the respective location dataset is associated with a load being transported for a freight transportation service. The computing system can determine a primary location dataset based on the confidence scores. The computing system can perform actions based on the primary location dataset.

Abstract: Systems and methods for reconciling location based on multiple computing device signals. For example, the computing system can obtain location datasets associated with freight carrier services from computing sources. The computing system can determine an expected signal pattern for a location associated with a freight transportation service. The computing system can determine, for each computing source, a confidence score. The confidence score can represent the probability that the respective location dataset is associated with a load being transported for a freight transportation service. The computing system can determine a primary location dataset based on the confidence scores. The computing system can perform actions based on the primary location dataset.

Abstract: Systems and methods for reconciling location based on multiple computing device signals. For example, the computing system can obtain location datasets associated with freight carrier services from computing sources. The computing system can determine an expected signal pattern for a location associated with a freight transportation service. The computing system can determine, for each computing source, a confidence score. The confidence score can represent the probability that the respective location dataset is associated with a load being transported for a freight transportation service. The computing system can determine a primary location dataset based on the confidence scores. The computing system can perform actions based on the primary location dataset.

Abstract: Disclosed are a system and a method for capturing a space target. The system includes a plurality of capturing devices, a delivery device, a launching device, and a deceleration and recovery device, each of the plurality of capturing devices is configured to be launched into a target orbit to capture a defunct space target, the delivery device is configured to deliver, along a preset delivery trajectory, each of the plurality of capturing devices to a first preset location in the launching device, the launching device is configured to launch each of the plurality of capturing devices located at the first preset location into the target orbit to capture the defunct space target, and the deceleration and recovery device is configured to decelerate each of the plurality of capturing devices after it is launched and flies a preset distance.

Abstract: The present disclosure provides a multi-arm spacecraft model predictive control method based on the mixture of Gaussian processes, equipment, and a medium. Model predictive control has excellent performance in dealing with complex nonlinear systems such as multi-arm spacecrafts with various constraints, and is widely applied to ground robots, unmanned aerial vehicles, autonomous driving and other practical scenarios. Therefore, a task space controller is designed based on the model predictive control in the present disclosure. Besides, in order to enhance the anti-interference capability of the present disclosure, an interference model is established and compensation is carried out in the model predictive control by utilizing the characteristics of small training data volume and high training speed in the mixture of Gaussian processes. Finally, a thrust distribution method is designed to complete platform control.

Abstract: Disclosed are a ground test system and a test method for a space-oriented multi-arm spacecraft system. A spacecraft system simulator floats on an air-floating platform through four porous air feet, a test truss is placed around the air-floating platform, a simulation auxiliary docking device, a simulation crawling truss and a satellite model are arranged in a middle of a ceiling of the test truss, and an assembly test area and a silent air compressor are arranged on sides of the test truss. The application is used to solve the problems that the prior art cannot simulate the movement and crawling of the multi-arm spacecraft system in space, assembly of large space structures, and the prior art cannot simulate the influence of assembling, catching and other actions on a base in a weightless environment.

Abstract: Disclosed are a ground test system and a test method for a space-oriented multi-arm spacecraft system. A spacecraft system simulator floats on an air-floating platform through four porous air feet, a test truss is placed around the air-floating platform, a simulation auxiliary docking device, a simulation crawling truss and a satellite model are arranged in a middle of a ceiling of the test truss, and an assembly test area and a silent air compressor are arranged on sides of the test truss. The application is used to solve the problems that the prior art cannot simulate the movement and crawling of the multi-arm spacecraft system in space, assembly of large space structures, and the prior art cannot simulate the influence of assembling, catching and other actions on a base in a weightless environment.

Abstract: According to embodiments of the present disclosure, there is provided a method, system, apparatus, electronic device, storage medium and program product for data exchange. The method described herein comprises: obtaining original data to be exchanged by a target application between a first platform and a second platform; obtaining normalized data corresponding to a type of the original data by processing the original data based on the type; determining a satisfaction of a data exchange constraint from the normalized data. In this way, the embodiments of the present disclosure may simplify and promote the determination of the data exchange constraint and accelerate the data exchange process.

Abstract: The application is directed to a cloud computing platform. The cloud computing platform includes a memory having instructions stored thereon for managing updates the cloud computing platform. The cloud computing platform also includes a controller, operably coupled to the memory. The controller is configured to execute an instruction of identifying an update for an existing cloud computing service operating on the cloud computing platform. The controller is also configured to download the update for the existing service. The controller is also configured to merge the differences between the downloaded update and the existing service to create a new image. The controller is also configured to test the new image offline. Further, the controller is configured to validate the new image online.

Abstract: System management services can discover the addition of new physical devices, take automated actions to provision software (operating system and other related cloud services software components) on them, and scale out management infrastructure based on the new capacity of the total resources (including the newly added resources). A configuration file can contain the rules for automatic expansion and contraction of the system.

Abstract: A cloud declarative language is used to configure and reconfigure cloud computing environments. The language includes physical and logical topology declarations as well as cloud operations commands, and allows users to declare commands at multiple topology hierarchies. The language may be used to create scripts and sets of scripts that are used to configure cloud stacks and other operational parameters. Scripts may be created through direct editing by cloud designers or with the aid of graphical user interfaces. Scripts may be automatically generated using templates of configurations and requirements and use for rapid prototyping and testing of cloud environments. Scripts may also be used to monitor conformance with specified configurations, and to facilitate deployment of incremental modifications to configurations.

Abstract: The application is directed to a cloud computing platform. The cloud computing platform includes a memory having instructions stored thereon for managing updates the cloud computing platform. The cloud computing platform also includes a controller, operably coupled to the memory. The controller is configured to execute an instruction of identifying an update for an existing cloud computing service operating on the cloud computing platform. The controller is also configured to download the update for the existing service. The controller is also configured to merge the differences between the downloaded update and the existing service to create a new image. The controller is also configured to test the new image offline. Further, the controller is configured to validate the new image online.

Abstract: The application is directed to a cloud computing platform. The cloud computing platform includes a memory having instructions stored thereon for managing updates the cloud computing platform. The cloud computing platform also includes a controller, operably coupled to the memory. The controller is configured to execute an instruction of identifying an update for an existing cloud computing service operating on the cloud computing platform. The controller is also configured to download the update for the existing service. The controller is also configured to merge the differences between the downloaded update and the existing service to create a new image. The controller is also configured to test the new image offline. Further, the controller is configured to validate the new image online.

Abstract: System management services can discover the addition of new physical devices, take automated actions to provision software (operating system and other related cloud services software components) on them, and scale out management infrastructure based on the new capacity of the total resources (including the newly added resources). A configuration file can contain the rules for automatic expansion and contraction of the system.

Abstract: A cloud declarative language is used to configure and reconfigure cloud computing environments. The language includes physical and logical topology declarations as well as cloud operations commands, and allows users to declare commands at multiple topology hierarchies. The language may be used to create scripts and sets of scripts that are used to configure cloud stacks and other operational parameters. Scripts may be created through direct editing by cloud designers or with the aid of graphical user interfaces. Scripts may be automatically generated using templates of configurations and requirements and use for rapid prototyping and testing of cloud environments. Scripts may also be used to monitor conformance with specified configurations, and to facilitate deployment of incremental modifications to configurations.