Abstract: An efficient and low-energy ship CO2 capture-membrane desorption-mineralization fixation system, comprising a cooler, a fan, an absorption tower, a CO2-rich solution pump, a plurality of hollow fiber membrane contactors, and a CO2-lean solution pump, which are connected one by one to form a queue. The beginning of the queue is connected to a marine diesel engine, and the end of the queue is connected to the absorption power again. The hollow fiber membrane contactors are arranged in parallel. The present invention uses a CO2 mineralization fixation by seawater as the driving force for the regeneration of CO2 from the CO2-rich solution. This system and method can solve the problems existing in the existing ship CCUS technology with zero CO2 regeneration energy consumption, and easier and safer CO2 storage in the ocean.

Abstract: Provided is a method for detecting deceptive e-commerce reviews based on a sentiment-topic joint probability, which belongs to the fields of natural language processing, data mining and machine learning. In the data of different fields, a STM model is superior to other reference models; compared with other models, the STM model belongs to a completely un-supervised (no label information) statistic learning method and shows great advantages in processing unbalanced large sample dataset. Thus, the STM model is more suitable for application in a real e-commerce environment.

Abstract: Provided is a method for detecting deceptive e-commerce reviews based on a sentiment-topic joint probability, which belongs to the fields of natural language processing, data mining and machine learning. In the data of different fields, a STM model is superior to other reference models; compared with other models, the STM model belongs to a completely un-supervised (no label information) statistic learning method and shows great advantages in processing unbalanced large sample dataset. Thus, the STM model is more suitable for application in a real e-commerce environment.