Abstract: A smart acoustic information recognition-based welded weld impact quality determination method and system, comprising: controlling a tip of an ultrasonic impact gun (1) to perform impact treatment on a welded weld with different treatment pressures, treatment speeds, treatment angles and impact frequencies, obtaining acoustic signals during the impact treatment, calculating feature values of the acoustic signals, and constructing an acoustic signal sample set including various stress conditions; marking the acoustic signal sample set according to impact treatment quality assessment results for the welded weld; establishing a multi-weight neural network model, and using the marked acoustic signal sample set to train the multi-weight neural network model; obtaining feature values of welded weld impact treatment acoustic signals to be determined, inputting the feature values into the trained multi-weight neural network model, and outputting determination results for welded weld impact treatment quality to be det

Abstract: The present disclosure provides a method and apparatus for determining an application service dependency, and a processor. The method includes that: an input pulse of first application service and an output pulse of second application service are acquired; a time interval between the input pulse and the output pulse is determined; and an application service dependency between the first application service and the second application service is determined based on the time interval. According to the present disclosure, a technical problem that an application service dependency between different pieces of application service cannot be determined accurately through a method for determining an application service dependency provided in the related art is solved.

Abstract: A communication speed prediction apparatus (1) includes: a position prediction unit (111) for predicting a future positional relationship between first and second communication apparatuses (B, D); a speed prediction unit (112) for predicting the future communication speed between the first and second communication apparatuses by using a predicted result by the position prediction unit and a prediction model (PD) for predicting the future communication speed between the first and second communication apparatuses; an extraction unit (113) for extracting a training information from an information source (121) including information relating to a past positional relationship between the first and second communication apparatuses and information relating to a past communication speed between the first and second communication apparatuses; a training unit for training a parameter of the prediction model by using the training information; and a model update unit (115) for updating, by using the trained parameter, the

Abstract: Provided herein is an integrated sampling and testing device, comprising a sampling device that comprises a syringe and specimen collector, and a testing device that comprises a cap, cylindrical container, and adaptor configured for sampling or testing.