Deep learning technologies are increasingly used in the fi eld of geophysics,and a variety of algorithms based on shallow convolutional neural networks are more widely used in fault recognition,but these methods are u...Deep learning technologies are increasingly used in the fi eld of geophysics,and a variety of algorithms based on shallow convolutional neural networks are more widely used in fault recognition,but these methods are usually not able to accurately identify complex faults.In this study,using the advantage of deep residual networks to capture strong learning features,we introduce residual blocks to replace all convolutional layers of the three-dimensional(3D)UNet to build a new 3D Res-UNet and select appropriate parameters through experiments to train a large amount of synthesized seismic data.After the training is completed,we introduce the mechanism of knowledge distillation.First,we treat the 3D Res-UNet as a teacher network and then train the 3D Res-UNet as a student network;in this process,the teacher network is in evaluation mode.Finally,we calculate the mixed loss function by combining the teacher model and student network to learn more fault information,improve the performance of the network,and optimize the fault recognition eff ect.The quantitative evaluation result of the synthetic model test proves that the 3D Res-UNet can considerably improve the accuracy of fault recognition from 0.956 to 0.993 after knowledge distillation,and the eff ectiveness and feasibility of our method can be verifi ed based on the application of actual seismic data.展开更多
Teachers’ beliefs toward multilingual awareness in target language learning play a significant role in shaping learners’ attitudes to language awareness, affect learners’ linguistic behavior and teachers’ teaching...Teachers’ beliefs toward multilingual awareness in target language learning play a significant role in shaping learners’ attitudes to language awareness, affect learners’ linguistic behavior and teachers’ teaching practice. Therefore, the present study was aimed to explore English teachers’ beliefs about Inner Mongolian university students’ multilingual awareness in L3 learning and their teaching practice in Chinese EFL context. One hundred English teachers from six universities in Inner Mongolia, China, participated in this investigation. The data was collected through a questionnaire and teacher interviews. The results indicate that English teachers hold positive attitudes to multilingual awareness in general;however, there are belief differences between Mongolian and Han teachers;there exist discrepancies between English teachers’ beliefs about multilingual awareness and their teaching practice, and social-cultural environment, family language policy,teacher identity, learning experience, teaching materials, and, more importantly, teachers’ lack of awareness of fostering learners’ multilingual awareness lead to the discrepancies. The present research highlights the necessity of raising teacher awareness of cultivating multilingual awareness in future teacher development and emphasizes the significance of exploring the potential cognitive advantages of multilingualism in promoting L3 learning and developing English learners’ multilingual competence in the EFL context in China.展开更多
Taking TM images, SPOT photos and DEM images as the basic information, this paper had not only put forward a kind of manual controlled computer-automatic extraction method, but also completed the task of extracting th...Taking TM images, SPOT photos and DEM images as the basic information, this paper had not only put forward a kind of manual controlled computer-automatic extraction method, but also completed the task of extracting the main types of ground objects in the Three Gorges Reservoir area under relatively high accuracy, after finishing such preprocessing tasks as correcting the topographical spectrum and synthesizing the data. Taking the specialized image analysis software-eCognition as the platform, the research achieved the goal of classifying through choosing samples, picking out the best wave bands, and producing the identifying functions. At the same time the extraction process partly dispelled the influence of such phenomena as the same thing with different spectrums, different things with the same spectrum, border transitions, etc. The research did certain exploration in the aspect of technological route and method of using automatic extraction of the remote sensing image to obtain the information of land cover for the regions whose ground objects have complicated spectrums.展开更多
基金supported by the National Natural Science Foundation of China(No.42072169)。
文摘Deep learning technologies are increasingly used in the fi eld of geophysics,and a variety of algorithms based on shallow convolutional neural networks are more widely used in fault recognition,but these methods are usually not able to accurately identify complex faults.In this study,using the advantage of deep residual networks to capture strong learning features,we introduce residual blocks to replace all convolutional layers of the three-dimensional(3D)UNet to build a new 3D Res-UNet and select appropriate parameters through experiments to train a large amount of synthesized seismic data.After the training is completed,we introduce the mechanism of knowledge distillation.First,we treat the 3D Res-UNet as a teacher network and then train the 3D Res-UNet as a student network;in this process,the teacher network is in evaluation mode.Finally,we calculate the mixed loss function by combining the teacher model and student network to learn more fault information,improve the performance of the network,and optimize the fault recognition eff ect.The quantitative evaluation result of the synthetic model test proves that the 3D Res-UNet can considerably improve the accuracy of fault recognition from 0.956 to 0.993 after knowledge distillation,and the eff ectiveness and feasibility of our method can be verifi ed based on the application of actual seismic data.
文摘Teachers’ beliefs toward multilingual awareness in target language learning play a significant role in shaping learners’ attitudes to language awareness, affect learners’ linguistic behavior and teachers’ teaching practice. Therefore, the present study was aimed to explore English teachers’ beliefs about Inner Mongolian university students’ multilingual awareness in L3 learning and their teaching practice in Chinese EFL context. One hundred English teachers from six universities in Inner Mongolia, China, participated in this investigation. The data was collected through a questionnaire and teacher interviews. The results indicate that English teachers hold positive attitudes to multilingual awareness in general;however, there are belief differences between Mongolian and Han teachers;there exist discrepancies between English teachers’ beliefs about multilingual awareness and their teaching practice, and social-cultural environment, family language policy,teacher identity, learning experience, teaching materials, and, more importantly, teachers’ lack of awareness of fostering learners’ multilingual awareness lead to the discrepancies. The present research highlights the necessity of raising teacher awareness of cultivating multilingual awareness in future teacher development and emphasizes the significance of exploring the potential cognitive advantages of multilingualism in promoting L3 learning and developing English learners’ multilingual competence in the EFL context in China.
基金Under the auspices of the Construction Committeeof Three GorgesR eservoirProject(No .SX [2002]00401) andChineseAcademy ofSciences(No .KZCX2-SW-319-01 )
文摘Taking TM images, SPOT photos and DEM images as the basic information, this paper had not only put forward a kind of manual controlled computer-automatic extraction method, but also completed the task of extracting the main types of ground objects in the Three Gorges Reservoir area under relatively high accuracy, after finishing such preprocessing tasks as correcting the topographical spectrum and synthesizing the data. Taking the specialized image analysis software-eCognition as the platform, the research achieved the goal of classifying through choosing samples, picking out the best wave bands, and producing the identifying functions. At the same time the extraction process partly dispelled the influence of such phenomena as the same thing with different spectrums, different things with the same spectrum, border transitions, etc. The research did certain exploration in the aspect of technological route and method of using automatic extraction of the remote sensing image to obtain the information of land cover for the regions whose ground objects have complicated spectrums.
