Abstract: In implementations of the present disclosure, there is provided a method for access point (AP) validation. The method comprises detecting a trigger event for validating a network including a plurality of APs, and selecting a target AP from the plurality of APs based on a neighbor table of an AP associated with the detected trigger event. The method further comprises determining a validation case corresponding to the detected trigger event from a knowledge base. The method further comprises sending the validation case to the target AP, and, receiving a result of performance of the validation case from the target AP in response to the validation case being performed. Implementations of the present disclosure can validate whether the network change takes effect in the network automatically, and can improve the validation efficiency of the network changes.

Abstract: Embodiments of the present disclosure relate to a solution for translation verification and correction. According to the solution, a neural network is trained to determine an association degree among a group of words in a source or target language. The neural network can be used for translation verification and correction. According to the solution, a group of words in a source language and translations of the group of words in a target language are obtained. An association degree among the group of words and an association degree among the translations can be determined by using the trained neural network. Then, whether there is a wrong translation can be determined based on the association degrees. In some embodiments, corresponding methods, systems and computer program products are provided.

Abstract: According to an aspect, a computer-implemented method includes accessing a profile of a user that indicates a likelihood that the user will execute each of a plurality of types of processing when training a new AI model. A runtime matrix that includes identifiers of runtime environments is accessed. The matrix also includes, for each of the runtime environments, a frequency of use of the runtime environment to train previously trained AI models using each of the plurality of types of processing. One or more of the runtime environments is selected for output to the user based at least in part on the profile of the user and the runtime matrix. Identifiers of the selected one or more of the runtime environments are output to a user interface of the user along with a suggestion to use one of the selected one or more of the runtime environments.

Abstract: A silicon-based anode material for secondary batteries, a preparation method thereof and a secondary battery are provided. The silicon-based anode material includes: an inner core including an Si particle and silicon oxide SiOx1, where 0<x1<2, a first shell layer including a compound of the general formula MySiOz (0<y?4, 0<z?5, and z?x1) and a C particle, wherein the first shell layer covers the inner core, and the contents of M and C in the first shell layer gradually increase from a side thereof close to the inner core to another side thereof far away from the inner core; and a second shell layer including a carbon film layer or a composite film layer formed by a carbon film layer and a conductive additive, the second shell layer covers the first shell layer. The first charge-discharge cycle capability of the silicon-based anode material is improved, and the manufacturing cost is reduced.

Abstract: The application provides a determination method and a determination apparatus for conversion efficiency of hydrogen production by wind-solar hybrid electrolysis of water. The method includes that: first test data of a target factor influencing the conversion efficiency of hydrogen production by wind-solar hybrid electrolysis of water is acquired in real time; a neural network model of the conversion efficiency is established; and the conversion efficiency is determined according to the neural network model and the first test data.

Abstract: The present disclosure relates to a method for early kick detection in a drilling system with a drilling fluid loop, comprising: collecting flow-in rate and flow-out rate of a drilling fluid; calibrating the flow-out rate to obtain a calibrated flow-out rate of the drilling fluid; determining a flow rate difference between the flow-in rate and the calibrated flow-out rate of the drilling fluid; and identifying the kicks based on the flow rate difference. The present disclosure also relates to an apparatus for early kick detection in a drilling system with a drilling fluid loop.