At present,there are indeed many problems in the training of upgraded talents among e-business students such as unclear training objectives and characteristics,as well as the lack of classified guidance and its corres...At present,there are indeed many problems in the training of upgraded talents among e-business students such as unclear training objectives and characteristics,as well as the lack of classified guidance and its corresponding mechanism.Therefore,there is a need for optimization and upgrading of faculties in which active research should be conducted on these issues.Through various measures to counter the challenges faced in the training of upgraded talents in e-business education based on the student-oriented ideology and advantages of universities,the environment needs to be constantly optimized while improving their levels,designing effective countermeasures,and having finn ideological beliefs.This article strives to educate senior e-business innovative talents in line with the needs of enterprises,continuously promote the integration of industry and education,as well as commit to contributing toward a comprehensive and healthy development of the e-business industry as well as social progress.展开更多
Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detec...Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detection accuracy and slow speed.Therefore,the current management of personnel behavior mainly relies on institutional constraints,education and training,on-site supervision,etc.,which is time-consuming and ineffective.Given the above situation,this paper proposes an improved You Only Look Once version 7(YOLOv7)to achieve the purpose of quickly detecting irregular behaviors of laboratory personnel while ensuring high detection accuracy.First,to better capture the shape features of the target,deformable convolutional networks(DCN)is used in the backbone part of the model to replace the traditional convolution to improve the detection accuracy and speed.Second,to enhance the extraction of important features and suppress useless features,this paper proposes a new convolutional block attention module_efficient channel attention(CBAM_E)for embedding the neck network to improve the model’s ability to extract features from complex scenes.Finally,to reduce the influence of angle factor and bounding box regression accuracy,this paper proposes a newα-SCYLLA intersection over union(α-SIoU)instead of the complete intersection over union(CIoU),which improves the regression accuracy while increasing the convergence speed.Comparison experiments on public and homemade datasets show that the improved algorithm outperforms the original algorithm in all evaluation indexes,with an increase of 2.92%in the precision rate,4.14%in the recall rate,0.0356 in the weighted harmonic mean,3.60%in the mAP@0.5 value,and a reduction in the number of parameters and complexity.Compared with the mainstream algorithm,the improved algorithm has higher detection accuracy,faster convergence speed,and better actual recognition effect,indicating the effectiveness of the improved algorithm in this paper and its potential for practical application in laboratory scenarios.展开更多
The newly re-named Peking Union Medical College, Tsinghua University was officially introduced to the press and the public at the Great Hall of the People on September 5, 2006.
基金Supported by Research on the Presence of Online Education under the Mobile Internet Background of Beying Young Teacher Project(Project No.:12205561110-506).
文摘At present,there are indeed many problems in the training of upgraded talents among e-business students such as unclear training objectives and characteristics,as well as the lack of classified guidance and its corresponding mechanism.Therefore,there is a need for optimization and upgrading of faculties in which active research should be conducted on these issues.Through various measures to counter the challenges faced in the training of upgraded talents in e-business education based on the student-oriented ideology and advantages of universities,the environment needs to be constantly optimized while improving their levels,designing effective countermeasures,and having finn ideological beliefs.This article strives to educate senior e-business innovative talents in line with the needs of enterprises,continuously promote the integration of industry and education,as well as commit to contributing toward a comprehensive and healthy development of the e-business industry as well as social progress.
基金This study was supported by the National Natural Science Foundation of China(No.61861007)Guizhou ProvincialDepartment of Education Innovative Group Project(QianJiaohe KY[2021]012)Guizhou Science and Technology Plan Project(Guizhou Science Support[2023]General 412).
文摘Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detection accuracy and slow speed.Therefore,the current management of personnel behavior mainly relies on institutional constraints,education and training,on-site supervision,etc.,which is time-consuming and ineffective.Given the above situation,this paper proposes an improved You Only Look Once version 7(YOLOv7)to achieve the purpose of quickly detecting irregular behaviors of laboratory personnel while ensuring high detection accuracy.First,to better capture the shape features of the target,deformable convolutional networks(DCN)is used in the backbone part of the model to replace the traditional convolution to improve the detection accuracy and speed.Second,to enhance the extraction of important features and suppress useless features,this paper proposes a new convolutional block attention module_efficient channel attention(CBAM_E)for embedding the neck network to improve the model’s ability to extract features from complex scenes.Finally,to reduce the influence of angle factor and bounding box regression accuracy,this paper proposes a newα-SCYLLA intersection over union(α-SIoU)instead of the complete intersection over union(CIoU),which improves the regression accuracy while increasing the convergence speed.Comparison experiments on public and homemade datasets show that the improved algorithm outperforms the original algorithm in all evaluation indexes,with an increase of 2.92%in the precision rate,4.14%in the recall rate,0.0356 in the weighted harmonic mean,3.60%in the mAP@0.5 value,and a reduction in the number of parameters and complexity.Compared with the mainstream algorithm,the improved algorithm has higher detection accuracy,faster convergence speed,and better actual recognition effect,indicating the effectiveness of the improved algorithm in this paper and its potential for practical application in laboratory scenarios.
文摘The newly re-named Peking Union Medical College, Tsinghua University was officially introduced to the press and the public at the Great Hall of the People on September 5, 2006.
