Effects of deposition angle and axial distance on the structural and mechanical properties of niobium nitride syn- thesized by a dense plasma focus （DPF） system are studied. The x-ray diffraction （XRD） confirms th...Effects of deposition angle and axial distance on the structural and mechanical properties of niobium nitride syn- thesized by a dense plasma focus （DPF） system are studied. The x-ray diffraction （XRD） confirms that the deposition parameters affect the growth of multi-phase niobium nitride. Scanning electron microscopy （SEM） shows the granular surface morphology with strong thermally assisted coagulation effects observed at the 5-cm axial distance. The non-porous granular morphology observed at the 9-cm distance along the anode axis is different from those observed at deposition angles of 10° and 20°. Energy dispersive x-ray （EDX） spectroscopy reveals the maximum nitrogen content at the shortest （5 cm） axial position. Atomic force microscopy （AFM） exhibits that the roughness of coated films varies for coatings synthesized at different axial and angular positions, and the Vickers micro-hardness test shows that a maximum hardness value is （08.44 ±0.01） GPa for niobium nitride synthesized at 5-cm axial distance, which is about 500% more than that of a virgin sample.展开更多
Human Activity Recognition(HAR)plays an important role in life care and health monitoring since it involves examining various activities of patients at homes,hospitals,or offices.Hence,the proposed system integrates H...Human Activity Recognition(HAR)plays an important role in life care and health monitoring since it involves examining various activities of patients at homes,hospitals,or offices.Hence,the proposed system integrates Human-Human Interaction(HHI)and Human-Object Interaction(HOI)recognition to provide in-depth monitoring of the daily routine of patients.We propose a robust system comprising both RGB(red,green,blue)and depth information.In particular,humans in HHI datasets are segmented via connected components analysis and skin detection while the human and object in HOI datasets are segmented via saliency map.To track the movement of humans,we proposed orientation and thermal features.A codebook is generated using Linde-Buzo-Gray(LBG)algorithm for vector quantization.Then,the quantized vectors generated from image sequences of HOI are given to Artificial Neural Network(ANN)while the quantized vectors generated from image sequences of HHI are given to K-ary tree hashing for classification.There are two publicly available datasets used for experimentation on HHI recognition:Stony Brook University(SBU)Kinect interaction and the University of Lincoln’s(UoL)3D social activity dataset.Furthermore,two publicly available datasets are used for experimentation on HOI recognition:Nanyang Technological University(NTU)RGB-D and Sun Yat-Sen University(SYSU)3D HOI datasets.The results proved the validity of the proposed system.展开更多
文摘Effects of deposition angle and axial distance on the structural and mechanical properties of niobium nitride syn- thesized by a dense plasma focus （DPF） system are studied. The x-ray diffraction （XRD） confirms that the deposition parameters affect the growth of multi-phase niobium nitride. Scanning electron microscopy （SEM） shows the granular surface morphology with strong thermally assisted coagulation effects observed at the 5-cm axial distance. The non-porous granular morphology observed at the 9-cm distance along the anode axis is different from those observed at deposition angles of 10° and 20°. Energy dispersive x-ray （EDX） spectroscopy reveals the maximum nitrogen content at the shortest （5 cm） axial position. Atomic force microscopy （AFM） exhibits that the roughness of coated films varies for coatings synthesized at different axial and angular positions, and the Vickers micro-hardness test shows that a maximum hardness value is （08.44 ±0.01） GPa for niobium nitride synthesized at 5-cm axial distance, which is about 500% more than that of a virgin sample.
基金This research was supported by a grant(2021R1F1A1063634)of the Basic Science Research Program through the National Research Foundation(NRF)funded by the Ministry of Education,Republic of Korea.
文摘Human Activity Recognition(HAR)plays an important role in life care and health monitoring since it involves examining various activities of patients at homes,hospitals,or offices.Hence,the proposed system integrates Human-Human Interaction(HHI)and Human-Object Interaction(HOI)recognition to provide in-depth monitoring of the daily routine of patients.We propose a robust system comprising both RGB(red,green,blue)and depth information.In particular,humans in HHI datasets are segmented via connected components analysis and skin detection while the human and object in HOI datasets are segmented via saliency map.To track the movement of humans,we proposed orientation and thermal features.A codebook is generated using Linde-Buzo-Gray(LBG)algorithm for vector quantization.Then,the quantized vectors generated from image sequences of HOI are given to Artificial Neural Network(ANN)while the quantized vectors generated from image sequences of HHI are given to K-ary tree hashing for classification.There are two publicly available datasets used for experimentation on HHI recognition:Stony Brook University(SBU)Kinect interaction and the University of Lincoln’s(UoL)3D social activity dataset.Furthermore,two publicly available datasets are used for experimentation on HOI recognition:Nanyang Technological University(NTU)RGB-D and Sun Yat-Sen University(SYSU)3D HOI datasets.The results proved the validity of the proposed system.
