Background The redirected walking(RDW)method for multi-user collaboration requires maintaining the relative position between users in a virtual environment(VE)and physical environment(PE).A chasing game in a VE is a t...
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Background The redirected walking(RDW)method for multi-user collaboration requires maintaining the relative position between users in a virtual environment(VE)and physical environment(PE).A chasing game in a VE is a typical virtual reality game that entails multi-user *** a user approaches and interacts with a target user in the VE,the user is expected to approach and interact with the target user in the corresponding PE as *** methods of multi-user RDW mainly focus on obstacle avoidance,which does not account for the relative positional relationship between the users in both VE and *** To enhance the user experience and facilitate potential interaction,this paper presents a novel dynamic alignment algorithm for multi-user collaborative redirected walking(DA-RDW)in a shared PE where the target user and other users are *** algorithm adopts improved artificial potential fields,where the repulsive force is a function of the relative position and velocity of the user with respect to dynamic *** the best alignment,this algorithm sets the alignment-guidance force in several cases and then converts it into a constrained optimization problem to obtain the optimal ***,this algorithm introduces a potential interaction object selection strategy for a dynamically uncertain environment to speed up the subsequent *** balance obstacle avoidance and alignment,this algorithm uses the dynamic weightings of the virtual and physical distances between users and the target to determine the resultant force *** The efficacy of the proposed method was evaluated using a series of simulations and live-user *** experimental results demonstrate that our novel dynamic alignment method for multi-user collaborative redirected walking can reduce the distance error in both VE and PE to improve alignment with fewer collisions.
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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Users may now create and use large amounts of data saved online thanks to e-commerce systems. Modern shoppers examine online reviews before making purchases. Evaluations are essential for both people and organizations...
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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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The rapid expansion of intra-vehicle networks has increased the number of threats to such *** modern vehicles implement various physical and data-link layer *** are becoming increasingly autonomous and *** area networ...
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The rapid expansion of intra-vehicle networks has increased the number of threats to such *** modern vehicles implement various physical and data-link layer *** are becoming increasingly autonomous and *** area network(CAN)is a serial bus system that is used to connect sensors and controllers(electronic control units-ECUs)within a *** vary widely in processing power,storage,memory,and *** goal of this research is to design,implement,and test an efficient and effective intrusion detection system for intra-vehicle *** cryptographic approaches are resource-intensive and increase processing delay,thereby not meeting CAN latency *** is a need for a system that is capable of detecting intrusions in almost real-time with minimal *** research proposes a long short-term memory(LSTM)network to detect anomalies and a decision engine to detect intrusions by using multiple contextual *** have tested our anomaly detection algorithm and our decision engine using data from real *** present the results of our experiments and analyze our *** detailed evaluation of our system,we believe that we have designed a vehicle security solution that meets all the outlined requirements and goals.
This article introduces a novel Multi-agent path planning scheme based on Conflict Based Search (CBS) for heterogeneous holonomic and non-holonomic agents, designated as Heterogeneous CBS (HCBS). The proposed methodol...
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Branched polyolefins with controllable topology structures were generated from the chain-walking(co)polymerizations of ethylene,1-pentene(1P)and 2-pentene(2P)using Brookhart-typeα-diimine Ni(II)-based catalysts posse...
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Branched polyolefins with controllable topology structures were generated from the chain-walking(co)polymerizations of ethylene,1-pentene(1P)and 2-pentene(2P)using Brookhart-typeα-diimine Ni(II)-based catalysts possessing different para-substituted groups,{[(4-R-2-Et-6-Me-C6H2N=C)2Nap]NiBr2,Nap:1,8-naphthdiyl;R=CHMePh,Ni1;R=Ph,Ni2;R=H,Ni3}.The X-ray diffraction analysis demonstrated that the crystalline structure of Ni1′is in centrosymmetric dimer structure mode with the bimetallic Ni center connected by two bromide *** para-sec-phenethyl moiety in the catalyst Ni1 obviously improved its catalytic performance and thermal stability in the ethylene *** Ni1/Et2AlCl system showed great catalytic activities(up to 7.73×106 g·mol-1·h-1)and achieved polyethylene(PE)with alkyl chains,including Me,Et,n-Pr,n-Bu,sec-Bu branches and longer chains(Lg).Compared with the 1-pentene polymerization,this catalyst system successfully mediated the polymerization of 2P to give highly branched polymers with approximately 195 branches/1000C possessing Me,Et,and n-Pr branches and a long methylene sequence due to the monomer *** Et branches derived from 2,3-insertion is slightly less than the sum of Me and n-Pr branches derived from 3,2-insertion,indicating that the 3,2-insertion mode is a slightly favorable pathway in the polymerization of 2P.
Accurate 3D hand pose estimation is a challenging computer vision problem primarily because of self-occlusion and viewpoint variations. Existing methods address viewpoint variations by applying data-centric transforma...
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Accurate 3D hand pose estimation is a challenging computer vision problem primarily because of self-occlusion and viewpoint variations. Existing methods address viewpoint variations by applying data-centric transformations, such as data alignments or generating multiple views, which are prone to data sensitivity, error propagation, and prohibitive computational requirements. We improve the estimation accuracy by mitigating the impact of self-occlusion and viewpoint variations from the network side and propose MH-Net, a novel multiheaded network for accurate 3D hand pose estimation from a depth image. MH-Net comprises three key components. First, a multiscale feature extraction backbone based on an improved multiscale vision transformer (MViTv2) is proposed to extract shift-invariant global features. Second, a 3D anchorset generator is proposed to generate three disjoint sets of 3D anchors that serve two purposes: formulating hand pose estimation as an anchor-to-joint offset estimation and defining three unique viewpoints from a single depth image. Third, three identical regression heads are proposed to regress 3D joint positions based on unique viewpoints defined by their respective anchorsets. Extensive ablation studies have been conducted to investigate the impact of anchorsets, regression heads, and feature extraction backbones. Experiments on three public datasets, ICVL, MSRA, and NYU, show significant improvements over the state-of-the-art. IEEE
Air is very beneficial and crucial for every living creature on earth, hence it is very important to protect the air quality in order to avoid diseases. However, due to the increase in population, some human activitie...
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Agriculture is crucial to the global economy, particularly in ensuring food security. Recent trends indicate that various plant diseases are causing substantial financial losses in the agricultural sector worldwide. T...
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