Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions f...Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera angles.This research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)videos.The first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale images.The YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further processing.The joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are included.These features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity classification.Real-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing methods.In particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.展开更多
Resistive random-access memory(RRAM),also known as memristors,having a very simple device structure with two terminals,fulfill almost all of the fundamental requirements of volatile memory,nonvolatile memory,and neuro...Resistive random-access memory(RRAM),also known as memristors,having a very simple device structure with two terminals,fulfill almost all of the fundamental requirements of volatile memory,nonvolatile memory,and neuromorphic characteristics.Its memory and neuromorphic behaviors are currently being explored in relation to a range of materials,such as biological materials,perovskites,2D materials,and transition metal oxides.In this review,we discuss the different electrical behaviors exhibited by RRAM devices based on these materials by briefly explaining their corresponding switching mechanisms.We then discuss emergent memory technologies using memristors,together with its potential neuromorphic applications,by elucidating the different material engineering techniques used during device fabrication to improve the memory and neuromorphic performance of devices,in areas such as ION/IOFF ratio,endurance,spike time-dependent plasticity(STDP),and paired-pulse facilitation(PPF),among others.The emulation of essential biological synaptic functions realized in various switching materials,including inorganic metal oxides and new organic materials,as well as diverse device structures such as single-layer and multilayer hetero-structured devices,and crossbar arrays,is analyzed in detail.Finally,we discuss current challenges and future prospects for the development of inorganic and new materials-based memristors.展开更多
Volatile organic compounds(VOCs)released from the waste treatment facilities have become a significant issue because they are not only causing odor nuisance but may also hazard to human health.Non-thermal plasma(NTP)t...Volatile organic compounds(VOCs)released from the waste treatment facilities have become a significant issue because they are not only causing odor nuisance but may also hazard to human health.Non-thermal plasma(NTP)technologies are newly developed methods and became a research trend in recent years regarding the removal of VOCs from the air stream.Due to its unique characteristics,such as rapid response at room temperature,bulk homogenized volume,high reaction efficiency,dielectric barrier discharge(DBD)plasma technology is considered one of the most promising techniques of NTP.This paper reviews recent progress of DBD plasma technology for abatement of VOCs.The principle of plasma generation in DBD and its configurations(electrode,discharge gap,dielectric barrier material,etc.)are discussed in details.Based on previously published literature,attention has been paid on the effect of DBD configuration on the removal of VOCs.Effect of various process parameters such as initial concentration,gas feeding rate,oxygen content and input power on VOCs removal are also considered.Moreover,the role of catalysis and inhibitors in VOCs removal by DBD system are presented.Finally,a modified configuration of the DBD reactor,i.e.double dielectric barrier discharge(DDBD)for the abatement of VOCs is discussed.It was suggested that the DDBD plasma reactor could be used for higher conversion efficiency as well as for avoiding solid residue deposition on the electrode.These depositions can interfere with the performance of the reactor.展开更多
Energy harvesting from ambient sources present in the environment is essential to replace traditional energy sources.These strategies can diversify the energy sources,reduce maintenance,lower costs,and provide near-pe...Energy harvesting from ambient sources present in the environment is essential to replace traditional energy sources.These strategies can diversify the energy sources,reduce maintenance,lower costs,and provide near-perpetual operation of the devices.In this work,a triboelectric nanogenerator(TENG)based on silane-coupled Linde type A/polydimethylsiloxane(LTA/PDMS)is developed for harsh environmental conditions.The silane-coupled LTA/PDMS-based TENG can produce a high output power density of 42.6μW/cm^(2) at a load resistance of 10 MQ and operates at an open-circuit voltage of 120 V and a short-circuit current of 15μA under a damping frequency of 14 Hz.Furthermore,the device shows ultra-robust and stable cyclic repeatability for more than 30 k cycles.The fabricated TENG is used for the physiological monitoring and charging of commercial capacitors to drive low-power electronic devices.Hence,these results suggest that the silane-coupled LTA/PDMS approach can be used to fabricate ultra-robust TENGs for harsh environmental conditions and also provides an effective path toward wearable self-powered microelectronic deVices.展开更多
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB Bremen.Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2024R348),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera angles.This research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)videos.The first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale images.The YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further processing.The joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are included.These features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity classification.Real-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing methods.In particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.
基金Basic Science Research Program through the National Research Foundation of Korea(NRF),funded by the Ministry of Education(NRF-2019R1F1A1057243)together with the Future Semiconductor Device Technology Development Program(20003808,10080689,20004399)funded by MOTIE(Ministry of Trade,Industry&Energy)and KSRC(Korea Semiconductor Research Consortium).
文摘Resistive random-access memory(RRAM),also known as memristors,having a very simple device structure with two terminals,fulfill almost all of the fundamental requirements of volatile memory,nonvolatile memory,and neuromorphic characteristics.Its memory and neuromorphic behaviors are currently being explored in relation to a range of materials,such as biological materials,perovskites,2D materials,and transition metal oxides.In this review,we discuss the different electrical behaviors exhibited by RRAM devices based on these materials by briefly explaining their corresponding switching mechanisms.We then discuss emergent memory technologies using memristors,together with its potential neuromorphic applications,by elucidating the different material engineering techniques used during device fabrication to improve the memory and neuromorphic performance of devices,in areas such as ION/IOFF ratio,endurance,spike time-dependent plasticity(STDP),and paired-pulse facilitation(PPF),among others.The emulation of essential biological synaptic functions realized in various switching materials,including inorganic metal oxides and new organic materials,as well as diverse device structures such as single-layer and multilayer hetero-structured devices,and crossbar arrays,is analyzed in detail.Finally,we discuss current challenges and future prospects for the development of inorganic and new materials-based memristors.
文摘Volatile organic compounds(VOCs)released from the waste treatment facilities have become a significant issue because they are not only causing odor nuisance but may also hazard to human health.Non-thermal plasma(NTP)technologies are newly developed methods and became a research trend in recent years regarding the removal of VOCs from the air stream.Due to its unique characteristics,such as rapid response at room temperature,bulk homogenized volume,high reaction efficiency,dielectric barrier discharge(DBD)plasma technology is considered one of the most promising techniques of NTP.This paper reviews recent progress of DBD plasma technology for abatement of VOCs.The principle of plasma generation in DBD and its configurations(electrode,discharge gap,dielectric barrier material,etc.)are discussed in details.Based on previously published literature,attention has been paid on the effect of DBD configuration on the removal of VOCs.Effect of various process parameters such as initial concentration,gas feeding rate,oxygen content and input power on VOCs removal are also considered.Moreover,the role of catalysis and inhibitors in VOCs removal by DBD system are presented.Finally,a modified configuration of the DBD reactor,i.e.double dielectric barrier discharge(DDBD)for the abatement of VOCs is discussed.It was suggested that the DDBD plasma reactor could be used for higher conversion efficiency as well as for avoiding solid residue deposition on the electrode.These depositions can interfere with the performance of the reactor.
基金This publication is based upon work supported by the System on Chip Lab grant from Khalifa University of Science and Technology under award no.8474000134 and award no.8474000137the Competitive Internal Research Award(CIRA)(2020-034).
文摘Energy harvesting from ambient sources present in the environment is essential to replace traditional energy sources.These strategies can diversify the energy sources,reduce maintenance,lower costs,and provide near-perpetual operation of the devices.In this work,a triboelectric nanogenerator(TENG)based on silane-coupled Linde type A/polydimethylsiloxane(LTA/PDMS)is developed for harsh environmental conditions.The silane-coupled LTA/PDMS-based TENG can produce a high output power density of 42.6μW/cm^(2) at a load resistance of 10 MQ and operates at an open-circuit voltage of 120 V and a short-circuit current of 15μA under a damping frequency of 14 Hz.Furthermore,the device shows ultra-robust and stable cyclic repeatability for more than 30 k cycles.The fabricated TENG is used for the physiological monitoring and charging of commercial capacitors to drive low-power electronic devices.Hence,these results suggest that the silane-coupled LTA/PDMS approach can be used to fabricate ultra-robust TENGs for harsh environmental conditions and also provides an effective path toward wearable self-powered microelectronic deVices.
