Abstract: A method and a system for selecting ions in a mass spectrometer. The method comprises: applying a first voltage to a deflection conductor to generate a deflection electric field at the deflection conductor, where ions are deflected to a trajectory not reaching the detector when flying through the deflection electric field; maintaining the first voltage applied to the deflection conductor to deflect non-target ions which fly out of the acceleration electric field, in response to detecting that a pulse synchronized with a laser is outputted; applying a second voltage to the deflection conductor to stop generating the deflection electric field and enable target ions to reach the detector, in response to the target ions flying out of the acceleration electric field; and applying the first voltage to the deflection conductor, in response to all target ions flying past the deflection conductor.

Abstract: An embodiment of the present application provides a method and a device for predicting a pair of similar questions and an electronic equipment, wherein a pair of similar questions to be predicted are input into multiple different prediction models, and a prediction result output by each of the prediction models is obtained; a random disturbance parameter is added into an embedding layer of at least one of the prediction models; and voting operation is performed on multiple prediction results to obtain a final prediction result of the pair of similar questions to be predicted. According to the present application, the a random disturbance parameter is added into the embedding layer of the prediction model, so that over-fitting caused by over-learning of sample knowledge by the prediction model can be effectively prevented, and the prediction accuracy can be effectively improved by predicting the pair of similar questions utilizing the prediction model.

Abstract: This application provides an object recognition method and apparatus, and a storage medium, and relates to the technical field of image recognition. The object recognition method includes: receiving an image of an object to be recognized; inputting the image of the object to be recognized into a pre-trained image feature extractor to obtain a first feature vector of the image of the object to be recognized; and determining category information of the object to be recognized according to the first feature vector of the image of the object to be recognized as well as image feature vectors in an image database, wherein the image database includes image information of a plurality of objects.