Visible-infrared Cross-modality Person Re-identification(VI-ReID)is a critical technology in smart public facilities such as cities,campuses and libraries.It aims to match pedestrians in visible light and infrared ima...Visible-infrared Cross-modality Person Re-identification(VI-ReID)is a critical technology in smart public facilities such as cities,campuses and libraries.It aims to match pedestrians in visible light and infrared images for video surveillance,which poses a challenge in exploring cross-modal shared information accurately and efficiently.Therefore,multi-granularity feature learning methods have been applied in VI-ReID to extract potential multi-granularity semantic information related to pedestrian body structure attributes.However,existing research mainly uses traditional dual-stream fusion networks and overlooks the core of cross-modal learning networks,the fusion module.This paper introduces a novel network called the Augmented Deep Multi-Granularity Pose-Aware Feature Fusion Network(ADMPFF-Net),incorporating the Multi-Granularity Pose-Aware Feature Fusion(MPFF)module to generate discriminative representations.MPFF efficiently explores and learns global and local features with multi-level semantic information by inserting disentangling and duplicating blocks into the fusion module of the backbone network.ADMPFF-Net also provides a new perspective for designing multi-granularity learning networks.By incorporating the multi-granularity feature disentanglement(mGFD)and posture information segmentation(pIS)strategies,it extracts more representative features concerning body structure information.The Local Information Enhancement(LIE)module augments high-performance features in VI-ReID,and the multi-granularity joint loss supervises model training for objective feature learning.Experimental results on two public datasets show that ADMPFF-Net efficiently constructs pedestrian feature representations and enhances the accuracy of VI-ReID.展开更多
Objectives:Teachers are facing unprecedented new challenges leading them to face an increasing number of tasks that are not part of their job,as well as having to cope with the additional skills acquisition that comes...Objectives:Teachers are facing unprecedented new challenges leading them to face an increasing number of tasks that are not part of their job,as well as having to cope with the additional skills acquisition that comes with non-traditional forms of teaching and learning,and increased work pressure leading to an increase in the rate of teachers leaving the profession.Therefore,this study aims to explore the mechanism of the career calling on job burnout through career adaptability and work engagement.Methods:This study conducted a cross-sectional survey of 465 primary and secondary school teachers(PSST)in China's Mainland from the perspective of work adjustment and used structural equation modeling(SEM)to examine the mediating roles of career adaptability and work engagement in the relationship between teachers’career calling and job burnout.Results:The results show that PSSTs are above average in career calling,career adaptability,and work engagement,while job burnout is below average.A significant positive or negative correlation exists between career calling,career adaptability,work engagement,and job burnout.The result of path analysis indicates that career adaptability and work engagement exert an indirect influence on the job burnout of PSST through three paths:namely,the independent intermediary role of career adaptability(EV=−0.144),the independent intermediary role of work engagement(EV=0.172)and the chain intermediary role of the two(EV=0.176).Conclusion:This study emphasizes the importance of career adaptability and work engagement in teacher development in regulating career calling and job burnout.Therefore,on the one hand,we think that if managers want to reduce teachers’job burnout,they need to pay more attention to teachers’career adaptability and work engagement,rather than relying solely on teachers’career calling.On the other hand,it is to remind teachers not to rely on their adjustment to adapt to the work,but also to need outside help as much as possible.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 62177029,62307025in part by the Startup Foundation for Introducing Talent of Nanjing University of Posts and Communications under Grant NY221041in part by the General Project of The Natural Science Foundation of Jiangsu Higher Education Institution of China 22KJB520025,23KJD580.
文摘Visible-infrared Cross-modality Person Re-identification(VI-ReID)is a critical technology in smart public facilities such as cities,campuses and libraries.It aims to match pedestrians in visible light and infrared images for video surveillance,which poses a challenge in exploring cross-modal shared information accurately and efficiently.Therefore,multi-granularity feature learning methods have been applied in VI-ReID to extract potential multi-granularity semantic information related to pedestrian body structure attributes.However,existing research mainly uses traditional dual-stream fusion networks and overlooks the core of cross-modal learning networks,the fusion module.This paper introduces a novel network called the Augmented Deep Multi-Granularity Pose-Aware Feature Fusion Network(ADMPFF-Net),incorporating the Multi-Granularity Pose-Aware Feature Fusion(MPFF)module to generate discriminative representations.MPFF efficiently explores and learns global and local features with multi-level semantic information by inserting disentangling and duplicating blocks into the fusion module of the backbone network.ADMPFF-Net also provides a new perspective for designing multi-granularity learning networks.By incorporating the multi-granularity feature disentanglement(mGFD)and posture information segmentation(pIS)strategies,it extracts more representative features concerning body structure information.The Local Information Enhancement(LIE)module augments high-performance features in VI-ReID,and the multi-granularity joint loss supervises model training for objective feature learning.Experimental results on two public datasets show that ADMPFF-Net efficiently constructs pedestrian feature representations and enhances the accuracy of VI-ReID.
基金funded by Humanities and Social Sciences Foundation and Natural Science Foundation of Nanjing University of Posts and Telecommunications(NYY222055,NY224176)General Subject of Educational Science Planning in Jiangsu Province(C/2024/01/76)National Natural Science Foundation of China(62307025).
文摘Objectives:Teachers are facing unprecedented new challenges leading them to face an increasing number of tasks that are not part of their job,as well as having to cope with the additional skills acquisition that comes with non-traditional forms of teaching and learning,and increased work pressure leading to an increase in the rate of teachers leaving the profession.Therefore,this study aims to explore the mechanism of the career calling on job burnout through career adaptability and work engagement.Methods:This study conducted a cross-sectional survey of 465 primary and secondary school teachers(PSST)in China's Mainland from the perspective of work adjustment and used structural equation modeling(SEM)to examine the mediating roles of career adaptability and work engagement in the relationship between teachers’career calling and job burnout.Results:The results show that PSSTs are above average in career calling,career adaptability,and work engagement,while job burnout is below average.A significant positive or negative correlation exists between career calling,career adaptability,work engagement,and job burnout.The result of path analysis indicates that career adaptability and work engagement exert an indirect influence on the job burnout of PSST through three paths:namely,the independent intermediary role of career adaptability(EV=−0.144),the independent intermediary role of work engagement(EV=0.172)and the chain intermediary role of the two(EV=0.176).Conclusion:This study emphasizes the importance of career adaptability and work engagement in teacher development in regulating career calling and job burnout.Therefore,on the one hand,we think that if managers want to reduce teachers’job burnout,they need to pay more attention to teachers’career adaptability and work engagement,rather than relying solely on teachers’career calling.On the other hand,it is to remind teachers not to rely on their adjustment to adapt to the work,but also to need outside help as much as possible.
