腹腔镜视频回放软件在临床教学中有着广泛的应用前景,本文介绍了腹腔镜视频回放软件的设计与实现过程。在Windows XP平台上,采用ACCESS数据库管理系统,利用Visual C++ 6.0基于MFC进行程序开发。实验结果显示,视频回放清晰流畅,完全满足...腹腔镜视频回放软件在临床教学中有着广泛的应用前景,本文介绍了腹腔镜视频回放软件的设计与实现过程。在Windows XP平台上,采用ACCESS数据库管理系统,利用Visual C++ 6.0基于MFC进行程序开发。实验结果显示,视频回放清晰流畅,完全满足腹腔镜视频回放软件应用于临床教学的要求,用户界面友好并且简单直观,符合医师操作习惯。展开更多
With the development of short video industry,video and bullet screen have become important ways to spread public opinions.Public attitudes can be timely obtained through emotional analysis on bullet screen,which can a...With the development of short video industry,video and bullet screen have become important ways to spread public opinions.Public attitudes can be timely obtained through emotional analysis on bullet screen,which can also reduce difficulties in management of online public opinions.A convolutional neural network model based on multi-head attention is proposed to solve the problem of how to effectively model relations among words and identify key words in emotion classification tasks with short text contents and lack of complete context information.Firstly,encode word positions so that order information of input sequences can be used by the model.Secondly,use a multi-head attention mechanism to obtain semantic expressions in different subspaces,effectively capture internal relevance and enhance dependent relationships among words,as well as highlight emotional weights of key emotional words.Then a dilated convolution is used to increase the receptive field and extract more features.On this basis,the above multi-attention mechanism is combined with a convolutional neural network to model and analyze the seven emotional categories of bullet screens.Testing from perspectives of model and dataset,experimental results can validate effectiveness of our approach.Finally,emotions of bullet screens are visualized to provide data supports for hot event controls and other fields.展开更多
文摘腹腔镜视频回放软件在临床教学中有着广泛的应用前景,本文介绍了腹腔镜视频回放软件的设计与实现过程。在Windows XP平台上,采用ACCESS数据库管理系统,利用Visual C++ 6.0基于MFC进行程序开发。实验结果显示,视频回放清晰流畅,完全满足腹腔镜视频回放软件应用于临床教学的要求,用户界面友好并且简单直观,符合医师操作习惯。
基金National Natural Science Foundation of China(No.61562057)Gansu Science and Technology Plan Project(No.18JR3RA104)。
文摘With the development of short video industry,video and bullet screen have become important ways to spread public opinions.Public attitudes can be timely obtained through emotional analysis on bullet screen,which can also reduce difficulties in management of online public opinions.A convolutional neural network model based on multi-head attention is proposed to solve the problem of how to effectively model relations among words and identify key words in emotion classification tasks with short text contents and lack of complete context information.Firstly,encode word positions so that order information of input sequences can be used by the model.Secondly,use a multi-head attention mechanism to obtain semantic expressions in different subspaces,effectively capture internal relevance and enhance dependent relationships among words,as well as highlight emotional weights of key emotional words.Then a dilated convolution is used to increase the receptive field and extract more features.On this basis,the above multi-attention mechanism is combined with a convolutional neural network to model and analyze the seven emotional categories of bullet screens.Testing from perspectives of model and dataset,experimental results can validate effectiveness of our approach.Finally,emotions of bullet screens are visualized to provide data supports for hot event controls and other fields.
