Detecting dangerous driving behavior is a critical research area focused on identifying and preventing actions that could lead to traffic accidents, such as smoking, drinking, yawning, and drowsiness, through technica...
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With the development of artificial intelligence, deep learning has been increasingly used to achieve automatic detection of geographic information, replacing manual interpretation and improving efficiency. However, re...
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In the evolving landscape of surveillance and security applications, the task of person re-identification(re-ID) has significant importance, but also presents notable difficulties. This task entails the process of acc...
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In the evolving landscape of surveillance and security applications, the task of person re-identification(re-ID) has significant importance, but also presents notable difficulties. This task entails the process of accurately matching and identifying persons across several camera views that do not overlap with one another. This is of utmost importance to video surveillance, public safety, and person-tracking applications. However, vision-related difficulties, such as variations in appearance, occlusions, viewpoint changes, cloth changes, scalability, limited robustness to environmental factors, and lack of generalizations, still hinder the development of reliable person re-ID methods. There are few approaches have been developed based on these difficulties relied on traditional deep-learning techniques. Nevertheless, recent advancements of transformer-based methods, have gained widespread adoption in various domains owing to their unique architectural properties. Recently, few transformer-based person re-ID methods have developed based on these difficulties and achieved good results. To develop reliable solutions for person re-ID, a comprehensive analysis of transformer-based methods is necessary. However, there are few studies that consider transformer-based techniques for further investigation. This review proposes recent literature on transformer-based approaches, examining their effectiveness, advantages, and potential challenges. This review is the first of its kind to provide insights into the revolutionary transformer-based methodologies used to tackle many obstacles in person re-ID, providing a forward-thinking outlook on current research and potentially guiding the creation of viable applications in real-world scenarios. The main objective is to provide a useful resource for academics and practitioners engaged in person re-ID. IEEE
Vehicular data misuse may lead to traffic accidents and even loss of life,so it is crucial to achieve secure vehicular data *** paper focuses on secure vehicular data communications in the Named Data Networking(NDN).I...
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Vehicular data misuse may lead to traffic accidents and even loss of life,so it is crucial to achieve secure vehicular data *** paper focuses on secure vehicular data communications in the Named Data Networking(NDN).In NDN,names,provider IDs and data are transmitted in plaintext,which exposes vehicular data to security threats and leads to considerable data communication costs and failure *** paper proposes a Secure vehicular Data Communication(SDC)approach in NDN to supress data communication costs and failure *** constructs a vehicular backbone to reduce the number of authenticated nodes involved in reverse *** the ciphtertext of the name and data is included in the signed Interest and Data and transmitted along the backbone,so the secure data communications are *** is evaluated,and the data results demonstrate that SCD achieves the above objectives.
Supported Ru nanoparticles with high utilization are promising for the hydrogen evolution reaction（HER） but the effect of the crystal phase engineering of supports on their performance remains ***,the impact of the ...
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Supported Ru nanoparticles with high utilization are promising for the hydrogen evolution reaction（HER） but the effect of the crystal phase engineering of supports on their performance remains ***,the impact of the crystal phase of the support on the catalytic activity of Ru was probed by anchoring Ru nanoparticles onto precisely synthesized hexagonal(WO3-H),orthorhombic(WO3-O),and monoclinic（WO3-M） supports followed by thorough evaluation for *** them,WO3-H demonstrated superior performance by providing enhanced Ru anchoring and uniform dispersion,maximizing active site availability.A critical finding is the small work function difference（ΔWF） between Ru and WO3-H,which minimizes interfacial charge accumulation and facilitates efficient hydrogen spillover,thereby accelerating HER *** contrast,WO3-O and WO3-M exhibited larger ΔWFand less effective Ru dispersion,resulting in a larger hydrogen spillover barrier and suboptimal hydrogen adsorption/desorption *** a result,Ru/WO3-H exhibited the best performance,achieving an overpotential of 43.8 mV at 10 mA cm-2and a Tafel slope of 49.1 mV *** work highlights the critical role of the crystal phase in optimizing the intrinsic catalytic activity of catalysts,offering new insights for designing efficient HER catalysts.
The current urban intelligent transportation is in a rapid development stage, and coherence control of vehicle formations has important implications in urban intelligent transportation research. This article focuses o...
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Global illumination(GI)plays a crucial role in rendering realistic results for virtual exhibitions,such as virtual car *** scenarios usually include all-frequency bidirectional reflectance distribution functions(BRDFs...
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Global illumination(GI)plays a crucial role in rendering realistic results for virtual exhibitions,such as virtual car *** scenarios usually include all-frequency bidirectional reflectance distribution functions(BRDFs),although their geometries and light configurations may be *** allfrequency BRDFs in real time remains challenging due to the complex light *** approaches,including precomputed radiance transfer,light probes,and the most recent path-tracing-based approaches(ReSTIR PT),cannot satisfy both quality and performance requirements ***,we propose a practical hybrid global illumination approach that combines ray tracing and cached GI by caching the incoming radiance with *** approach can produce results close to those of ofline renderers at the cost of only approximately 17 ms at runtime and is robust over all-frequency *** approach is designed for applications involving static lighting and geometries,such as virtual exhibitions.
Safety equipment detection is an important application of object detection, receiving widespread attention in fields such as smart construction sites and video surveillance. Significant progress has been made in objec...
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Exploring efficient and nonprecious metal electrocatalysts of oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)is crucial for developing rechargeable zinc-air batteries(ZABs).Herein,an alloying-degree c...
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Exploring efficient and nonprecious metal electrocatalysts of oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)is crucial for developing rechargeable zinc-air batteries(ZABs).Herein,an alloying-degree control strategy was employed to fabricate nitrogen-doped carbon sphere(NCS)decorated with dual-phase Co/Co_(7)Fe_(3)heterojunctions(CoFe@NCS).The phase composition of materials has been adjusted by controlling the alloying *** optimal CoFe_(0.08)@NCS electrocatalyst displays a half-wave potential of 0.80 V for ORR and an overpotential of 283 mV at 10 mA·cm^(-2)for OER in an alkaline *** intriguing bifunctional electrocatalytic activity and durability is attributed to the hierarchically porous structure and interfacial electron coupling of highly-active Co_(7)Fe_(3)alloy and metallic Co *** the CoFe_(0.08)@NCS material is used as air-cathode catalyst of rechargeable liquid-state zinc-air battery(ZAB),the device shows a high peak power-density(157 mW·cm^(-2))and maintains a stable voltage gap over 150 h,outperforming those of the benchmark(Pt/C+RuO_(2))-based *** particular,the as-fabricated solid-state flexible ZAB delivers a reliable compatibility under different bending *** work provides a promising strategy to develop metal/alloy-based electrocatalysts for the application in renewable energy conversion technologies.
Multi-hop reasoning for incomplete Knowledge Graphs(KGs)demonstrates excellent interpretability with decent *** Learning(RL)based approaches formulate multi-hop reasoning as a typical sequential decision *** intractab...
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Multi-hop reasoning for incomplete Knowledge Graphs(KGs)demonstrates excellent interpretability with decent *** Learning(RL)based approaches formulate multi-hop reasoning as a typical sequential decision *** intractable shortcoming of multi-hop reasoning with RL is that sparse reward signals make performance *** mainstream methods apply heuristic reward functions to counter this ***,the inaccurate rewards caused by heuristic functions guide the agent to improper inference paths and unrelated object *** this end,we propose a novel adaptive Inverse Reinforcement Learning(IRL)framework for multi-hop reasoning,called AInvR.(1)To counter the missing and spurious paths,we replace the heuristic rule rewards with an adaptive rule reward learning mechanism based on agent’s inference trajectories;(2)to alleviate the impact of over-rewarded object entities misled by inaccurate reward shaping and rules,we propose an adaptive negative hit reward learning mechanism based on agent’s sampling strategy;(3)to further explore diverse paths and mitigate the influence of missing facts,we design a reward dropout mechanism to randomly mask and perturb reward parameters for the reward learning *** results on several benchmark knowledge graphs demonstrate that our method is more effective than existing multi-hop approaches.
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