Objective: in view of the influence of different processing methods of traditional Chinese medicine on the actual curative effect of traditional Chinese medicine decoction pieces, a comprehensive and in-depth analysis...Objective: in view of the influence of different processing methods of traditional Chinese medicine on the actual curative effect of traditional Chinese medicine decoction pieces, a comprehensive and in-depth analysis and research are carried out. Methods: one hundred and twenty patients from 2016 to 2017 were selected from our hospital as the research object. All patients were divided into three groups by the way of random average grouping, that is, Group A, Group B and Group C. For all the patients in Group A, the TCM water treatment pre-grading method was used, all patients in Group B were treated with traditional Chinese medicine before processing, and all patients in Group C were treated with traditional Chinese medicine before water treatment and before processing. After a period of treatment, the clinical treatment conditions of patients in three groups were compared comprehensively. Results: the comprehensive efficiency of clinical treatment of patients in Group C exceeded 90%, which was significantly higher than the treatment effect of Group A and B. Conclusion: the processing method of traditional Chinese medicine plays an important role in improving the clinical treatment effect of traditional Chinese medicine decoction pieces. Therefore, in the teaching of traditional Chinese medicine processing, students should be actively taught relevant knowledge before water treatment and before processing, so as to promote students' in-depth understanding and mastery of the processing method of traditional Chinese medicine decoction pieces.展开更多
We present an improved digital image processing(DIP)method to calculate the widths of single slits.Different from the traditional laser Fraunhofer diffraction experiment in college physical experiments,by performing f...We present an improved digital image processing(DIP)method to calculate the widths of single slits.Different from the traditional laser Fraunhofer diffraction experiment in college physical experiments,by performing fast Fourier transform,inverse fast Fourier transform and the nonlinear leastsquare fitting on the diffraction pattern taken by a camera,the DIP method can quickly return an analytic expression,whose period is used to calculate widths of single slits.By comparing the measured results by the DIP method and the successional difference(SD)method,we find that for a single slit whose width is 60372μm,the DIP method is more accurate.Experimental results show that for single slits with widths between 40μm and 160μm,the relative error of the DIP method is less than 2.78%.Also,the DIP method can be used to measure the diameter of filament and fibres online in real time.展开更多
There are two types of methods for image segmentation.One is traditional image processing methods,which are sensitive to details and boundaries,yet fail to recognize semantic information.The other is deep learning met...There are two types of methods for image segmentation.One is traditional image processing methods,which are sensitive to details and boundaries,yet fail to recognize semantic information.The other is deep learning methods,which can locate and identify different objects,but boundary identifications are not accurate enough.Both of them cannot generate entire segmentation information.In order to obtain accurate edge detection and semantic information,an Adaptive Boundary and Semantic Composite Segmentation method(ABSCS)is proposed.This method can precisely semantic segment individual objects in large-size aerial images with limited GPU performances.It includes adaptively dividing and modifying the aerial images with the proposed principles and methods,using the deep learning method to semantic segment and preprocess the small divided pieces,using three traditional methods to segment and preprocess original-size aerial images,adaptively selecting traditional results tomodify the boundaries of individual objects in deep learning results,and combining the results of different objects.Individual object semantic segmentation experiments are conducted by using the AeroScapes dataset,and their results are analyzed qualitatively and quantitatively.The experimental results demonstrate that the proposed method can achieve more promising object boundaries than the original deep learning method.This work also demonstrates the advantages of the proposed method in applications of point cloud semantic segmentation and image inpainting.展开更多
文摘Objective: in view of the influence of different processing methods of traditional Chinese medicine on the actual curative effect of traditional Chinese medicine decoction pieces, a comprehensive and in-depth analysis and research are carried out. Methods: one hundred and twenty patients from 2016 to 2017 were selected from our hospital as the research object. All patients were divided into three groups by the way of random average grouping, that is, Group A, Group B and Group C. For all the patients in Group A, the TCM water treatment pre-grading method was used, all patients in Group B were treated with traditional Chinese medicine before processing, and all patients in Group C were treated with traditional Chinese medicine before water treatment and before processing. After a period of treatment, the clinical treatment conditions of patients in three groups were compared comprehensively. Results: the comprehensive efficiency of clinical treatment of patients in Group C exceeded 90%, which was significantly higher than the treatment effect of Group A and B. Conclusion: the processing method of traditional Chinese medicine plays an important role in improving the clinical treatment effect of traditional Chinese medicine decoction pieces. Therefore, in the teaching of traditional Chinese medicine processing, students should be actively taught relevant knowledge before water treatment and before processing, so as to promote students' in-depth understanding and mastery of the processing method of traditional Chinese medicine decoction pieces.
基金National Natural Science Foundtion of China(No.11435011)Young Teachers Fund of Nanjing Institute of Technology,China(Nos.QKJ201907 and QKJ201908)+2 种基金China Scholarship Council(No.201708320319)Postgraduate Research and Practice Innovation Program of Jiangsu Province,China(No.KYZZ16-0349)Qing Lan Project of Jiangsu Province,China。
文摘We present an improved digital image processing(DIP)method to calculate the widths of single slits.Different from the traditional laser Fraunhofer diffraction experiment in college physical experiments,by performing fast Fourier transform,inverse fast Fourier transform and the nonlinear leastsquare fitting on the diffraction pattern taken by a camera,the DIP method can quickly return an analytic expression,whose period is used to calculate widths of single slits.By comparing the measured results by the DIP method and the successional difference(SD)method,we find that for a single slit whose width is 60372μm,the DIP method is more accurate.Experimental results show that for single slits with widths between 40μm and 160μm,the relative error of the DIP method is less than 2.78%.Also,the DIP method can be used to measure the diameter of filament and fibres online in real time.
基金funded in part by the Equipment Pre-Research Foundation of China,Grant No.61400010203in part by the Independent Project of the State Key Laboratory of Virtual Reality Technology and Systems.
文摘There are two types of methods for image segmentation.One is traditional image processing methods,which are sensitive to details and boundaries,yet fail to recognize semantic information.The other is deep learning methods,which can locate and identify different objects,but boundary identifications are not accurate enough.Both of them cannot generate entire segmentation information.In order to obtain accurate edge detection and semantic information,an Adaptive Boundary and Semantic Composite Segmentation method(ABSCS)is proposed.This method can precisely semantic segment individual objects in large-size aerial images with limited GPU performances.It includes adaptively dividing and modifying the aerial images with the proposed principles and methods,using the deep learning method to semantic segment and preprocess the small divided pieces,using three traditional methods to segment and preprocess original-size aerial images,adaptively selecting traditional results tomodify the boundaries of individual objects in deep learning results,and combining the results of different objects.Individual object semantic segmentation experiments are conducted by using the AeroScapes dataset,and their results are analyzed qualitatively and quantitatively.The experimental results demonstrate that the proposed method can achieve more promising object boundaries than the original deep learning method.This work also demonstrates the advantages of the proposed method in applications of point cloud semantic segmentation and image inpainting.
