Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,...Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.展开更多
To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic ...To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.展开更多
In dynamic scenes,the pose estimation and map consistency of visual simultaneous localisation and mapping(visual SLAM)are affected by intermittent changes in object motion states.An adaptive motion-state estimation an...In dynamic scenes,the pose estimation and map consistency of visual simultaneous localisation and mapping(visual SLAM)are affected by intermittent changes in object motion states.An adaptive motion-state estimation and feature-reuse mechanism is proposed which restores features once objects become stationary.Camera ego-motion is com-pensated via projection-based point-to-point red-green-blue-depth(RGB-D)Iterative Closest Point;the alignment residual yields a short-term jitter score.An Extended Kalman Filter fuses the centre-pixel trajectory and depth of the object,using depth innovation as strong evidence to suppress false triggers.Applied adaptive decision thresholds involve resolution,ego-motion intensity,jitter,and reference depth,and are combined with dual/single triggering and hysteresis to achieve robust switching.When an object is considered static,its feature points are reused.On the Bonn RGB-D Dynamic Dataset(BONN)and TUM RGB-D SLAM Dataset and Benchmark(TUM),the proposed method matches or exceeds baselines:In intermittent-motion-dominated BONN sequences Placing_non_box,it re-duces the root-mean-square of the absolute trajectory error(ATE-RMSE)by 27%relative to the baseline,remains comparable to Ellipsoid-SLAM on TUM,and consistently outperforms ORB-SLAM3 in dynamic scenes.The hysteresis counter reading on Placing_non_box2 shows that the proposed method can reduce the motion-state misclassification rate by nearly 40%.From the ablation experiment results,we confirm that adaptive thresholds yield the most significant optimisation effect.The approach improves robustness and map completeness in dynamic environments without degrading performance in low-dynamic settings.展开更多
How to select the adequate real strong earthquake ground motion for seismic analysis and design of structures is an essential problem in earthquake engineering research and practice. In the paper the concept of the se...How to select the adequate real strong earthquake ground motion for seismic analysis and design of structures is an essential problem in earthquake engineering research and practice. In the paper the concept of the severest design ground motion is proposed and a method is developed for comparing the severity of the recorded strong ground motions. By using this method the severest earthquake ground motions are selected out as seismic inputs to the structures to be designed from a database that consists of more than five thousand significant strong ground motion records collected over the world. The selected severest ground motions are very likely to be able to drive the structures to their critical response and thereby result in the highest damage potential. It is noted that for different structures with different predominant natural periods and at different sites where structures are located the severest design ground motions are usually different. Finally, two examples are illustrated to demonstrate the rationality of the concept and the reliability of the selected design motion.展开更多
In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):104...In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].展开更多
The plastic deformation of semiconductors,a process critical to their mechanical and electronic properties,involves various mechanisms such as dislocation motion and phase transition.Here,we systematically examined th...The plastic deformation of semiconductors,a process critical to their mechanical and electronic properties,involves various mechanisms such as dislocation motion and phase transition.Here,we systematically examined the temperature-dependent Peierls stress for 30°and 90°partial dislocations in cadmium telluride(CdTe),using a combination of molecular statics and molecular dynamics simulations with a machine-learning force field,as well as density functional theory simulations.Our findings reveal that the 0 K Peierls stresses for these partial dislocations in CdTe are relatively low,ranging from 0.52 GPa to 1.46 GPa,due to its significant ionic bonding characteristics.Notably,in the CdTe system containing either a 30°Cd-core or 90°Te-core partial dislocation,a phase transition from the zinc-blende phase to theβ-Sn-like phase is favored over dislocation motion.This suggests a competitive relationship between these two mechanisms,driven by the bonding characteristics within the dislocation core and the relatively low phase transition stress of∼1.00 GPa.Furthermore,we observed a general trend wherein the Peierls stress for partial dislocations in CdTe exhibits a temperature dependence,which decreases with increasing temperature,becoming lower than the phase transition stress at elevated temperatures.Consequently,the dominant deformation mechanism in CdTe shifts from solid-state phase transition at low temperatures to dislocation motion at high temperatures.This investigation uncovers a compelling interplay between dislocation motion and phase transition in the plastic deformation of CdTe,offering profound insights into the mechanical behavior and electronic performance of CdTe and other II-VI semiconductors.展开更多
Internal learning-based video inpainting methods have shown promising results by exploiting the intrinsic properties of the video to fill in the missing region without external dataset supervision.However,existing int...Internal learning-based video inpainting methods have shown promising results by exploiting the intrinsic properties of the video to fill in the missing region without external dataset supervision.However,existing internal learning-based video inpainting methods would produce inconsistent structures or blurry textures due to the insufficient utilisation of motion priors within the video sequence.In this paper,the authors propose a new internal learning-based video inpainting model called appearance consistency and motion coherence network(ACMC-Net),which can not only learn the recurrence of appearance prior but can also capture motion coherence prior to improve the quality of the inpainting results.In ACMC-Net,a transformer-based appearance network is developed to capture global context information within the video frame for representing appearance consistency accurately.Additionally,a novel motion coherence learning scheme is proposed to learn the motion prior in a video sequence effectively.Finally,the learnt internal appearance consistency and motion coherence are implicitly propagated to the missing regions to achieve inpainting well.Extensive experiments conducted on the DAVIS dataset show that the proposed model obtains the superior performance in terms of quantitative measurements and produces more visually plausible results compared with the state-of-the-art methods.展开更多
With the rapid development of wearable electronic skin technology, flexible strain sensors have shown great application prospects in the fields of human motion and physiological signal detection, medical diagnostics, ...With the rapid development of wearable electronic skin technology, flexible strain sensors have shown great application prospects in the fields of human motion and physiological signal detection, medical diagnostics, and human-computer interaction owing to their outstanding sensing performance. This paper reports a strain sensor with synergistic conductive network, consisting of stable carbon nanotube dispersion (CNT) layer and brittle MXene layer by dip-coating and electrostatic self-assembly method, and breathable three-dimensional (3D) flexible substrate of thermoplastic polyurethane (TPU) fibrous membrane prepared through electrospinning technology. The MXene/CNT@PDA-TPU (MC@p-TPU) flexible strain sensor had excellent air permeability, wide operating range (0–450 %), high sensitivity (Gauge Factor, GFmax = 8089.7), ultra-low detection limit (0.05 %), rapid response and recovery times (40 ms/60 ms), and excellent cycle stability and durability (10,000 cycles). Given its superior strain sensing capabilities, this sensor can be applied in physiological signals detection, human motion pattern recognition, and driving exoskeleton robots. In addition, MC@p-TPU fibrous membrane also exhibited excellent photothermal conversion performance and can be used as a wearable photo-heater, which has far-reaching application potential in the photothermal therapy of human joint diseases.展开更多
This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain fie...This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain field.The impact of rainfall on aerodynamic performance was initially examined using a stationary turbine model in both wind and wind–rain conditions.Subsequently,the study compared the FOWT’s performance under various single degree-of-freedom(DOF)motions,including surge,pitch,heave,and yaw.Finally,the combined effects of wind–rain fields and platform motions involving two DOFs on the FOWT’s aerodynamics were analyzed and compared.The results demonstrate that rain negatively impacts the aerodynamic performance of both the stationary turbines and FOWTs.Pitch-dominated motions,whether involving single or multiple DOFs,caused significant fluctuations in the FOWT aerodynamics.The combination of surge and pitch motions created the most challenging operational environment for the FOWT in all tested scenarios.These findings highlighted the need for stronger construction materials and greater ultimate bearing capacity for FOWTs,as well as the importance of optimizing designs to mitigate excessive pitch and surge.展开更多
The side information quality has an immense effect on the compression efficiency of the distributed video coding (DVC) sys- tem. This article, based on the hierarchical motion estimation (HME), proposes a new side inf...The side information quality has an immense effect on the compression efficiency of the distributed video coding (DVC) sys- tem. This article, based on the hierarchical motion estimation (HME), proposes a new side information generation algorithm which is integrated into DVC system. First, forward motion estimation (FME) and bidirectional motion estimation (BME) on the basis of variable block size HME algorithm are used to acquire relatively accurate motion vectors. Second, a motion vector filter (MVF) is i...展开更多
Piezoelectric actuators are widely utilized in positioning systems to realize nano-scale resolution. However, the backward motion always generates for some piezoelectric actuators, which reduces the working efficiency...Piezoelectric actuators are widely utilized in positioning systems to realize nano-scale resolution. However, the backward motion always generates for some piezoelectric actuators, which reduces the working efficiency. Bionic motions have already been employed in the field of piezoelectric actuators to realize better performance. By imitating the movement form of seals, seal type piezoelectric actuator is capable to realize large operating strokes easily. Nevertheless, the conventional seal type piezoelectric actuator has a complicated structure and control system, which limits further applications. Hence, an improved bionic piezoelectric actuator is proposed to realize a long motion stroke and eliminate backward movement with a simplified structure and control method in this study. The composition and motion principle of the designed actuator are discussed, and the performance is investigated with simulations and experiments. Results confirm that the presented actuator effectively realizes the linear movement that has a large working stroke stably without backward motion. The smallest stepping displacement ΔL is 0.2 μm under 1 Hz and 50 V. The largest motion speed is 900 μm/s with 900 Hz and 120 V. The largest vertical and horizontal load are 250 g and 12 g, respectively. This work shows that the improved bionic piezoelectric actuator is feasible for eliminating backward motion and has a great working ability.展开更多
This article centers on The Call of the Wild,an English novel by American author Jack London,alongside two Chinese translations by Dajie Liu and Menglin Zhang,and Rongyue Liu.Seventy sentences containing motion events...This article centers on The Call of the Wild,an English novel by American author Jack London,alongside two Chinese translations by Dajie Liu and Menglin Zhang,and Rongyue Liu.Seventy sentences containing motion events and their corresponding translations were randomly selected for analysis.The study focuses on the primary elements of motion events-manner,path,and ground-and examines their Chinese translations through the lens of Skopos theory.Skopos theory emphasizes whether translators can adopt appropriate translation strategies according to various contextual factors during the translation process.Compared to verb-framed languages,satellite-framed languages possess a richer vocabulary for manner verbs,express more detailed manner information,use more satellite words to indicate paths,and incorporate more background information.Verb-framed languages,by contrast,typically express manner information only when necessary and tend to include less background information.The analysis reveals that both Chinese translations embody the core principle of Skopos theory:translation strategies are determined by their purpose.To fulfill the novel’s translation objectives,the translators adeptly adjust their strategies for motion event components based on different contextual needs.It is noted that the Chinese translations do not fully retain the characteristics of English as a typical satellite-framed language.This observation aligns with Skopos theory’s purpose-oriented approach,which prioritizes translation goals over strict adherence to source text characteristics.展开更多
Backswimmers exhibit a high degree of mobility in water,and their different motion patterns have important implications for the design of micro-biomimetic underwater robots.This paper used three-dimensional high-speed...Backswimmers exhibit a high degree of mobility in water,and their different motion patterns have important implications for the design of micro-biomimetic underwater robots.This paper used three-dimensional high-speed cameras to extract the key points on the hind legs.The hind leg motion laws and the deformation laws of the setae were obtained in four motion patterns:rapid forward,cruising,in-motion turning,and in-place turning.The motion laws of each joint on the hind leg are modeled using a Fourier series.A kinematic model of hind legs was established based on the DH method,and the motion characteristics of hind legs under different motion patterns were analyzed.This paper provides basic data and theoretical models for micro-biomimetic robots.展开更多
An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algor...An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.展开更多
Motion recognition refers to the intelligent recognition of human motion using data collected from wearable sensors,which exceedingly has gained significant interest from both academic and industrial fields.However,te...Motion recognition refers to the intelligent recognition of human motion using data collected from wearable sensors,which exceedingly has gained significant interest from both academic and industrial fields.However,temporary-sudden activities caused by accidental behavior pose a major challenge to motion recognition and have been largely overlooked in existing works.To address this problem,the multi-dimensional time series of motion data is modeled as a Time-Frequency(TF)tensor,and the original challenge is transformed into a problem of outlier-corrupted tensor pattern recognition,where transient sudden activity data are considered as outliers.Since the TF tensor can capture the latent spatio-temporal correlations of the motion data,the tensor MPCA is used to derive the principal spatio-temporal pattern of the motion data.However,traditional MPCA uses the squared F-norm as the projection distance measure,which makes it sensitive to the presence of outlier motion data.Therefore,in the proposed outlier-robust MPCA scheme,the F-norm with the desirable geometric properties is used as the distance measure to simultaneously mitigate the interference of outlier motion data while preserving rotational invariance.Moreover,to reduce the complexity of outlier-robust motion recognition,we impose the proposed outlier-robust MPCA scheme on the traditional MPCANet which is a low-complexity deep learning network.The experimental results show that our proposed outlier-robust MPCANet can simultaneously improve motion recognition performance and reduce the complexity,especially in practical scenarios where the real-time data is corrupted by temporary-sudden activities.展开更多
Shape memory alloy(SMA)bars are currently preferred over elastomeric seismic isolators due to the elimination of degradation within effective damping and stiffness factors during the cyclic response of an isolation sy...Shape memory alloy(SMA)bars are currently preferred over elastomeric seismic isolators due to the elimination of degradation within effective damping and stiffness factors during the cyclic response of an isolation system.These bars could also be used to prevent the functionality of the isolator units from failing due to large deformations.This study aims to investigate the performance of a high damping rubber bearing(HDRB)isolator that is combined with two different types of SMA bars,i.e.,Nickel-Titanium(Ni-Ti)and Copper-Aluminum-Beryllium(Cu-Al-Be),subjected to near-fault ground motions that are characterized with forward directivity and fling step effects.To achieve this objective,a self-centering material with flag-shape,force-deformation hysteresis was utilized to simulate the behavior of SMA bars in OpenSees.A single degree of freedom(SDOF)system representing an isolated one-story shear building was developed to conduct nonlinear analysis under selected ground motions.The SMA bars were introduced as an X-shape within the model and were connected diagonally to the top and bottom of the isolator.Results showed that the HDRB system’s hysteretic response under near-fault ground accelerations experiences significant degradation,especially when near-fault motions involve the fling step effect.It was demonstrated that SMA bars effectively reduce large displacement observed in HDRB systems under near-fault earthquakes.Comparing the results of the base-isolated HDRB and SMA-HDRB subjected to selected ground motions demonstrated that maximum displacement was found to be significantly reduced by an average of 79%when SMA bars were used.Incorporating SMA bars with a larger diameter significantly improves the efficiency of SMA HDRB systems,and a reduction in maximum displacements is more pronounced for fling step,near-fault ground motions.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
基金supported by the Basic Science Research Program(2023R1A2C3004336,RS-202300243807)&Regional Leading Research Center(RS-202400405278)through the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)。
文摘Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.
基金Project(60801053) supported by the National Natural Science Foundation of ChinaProject(4082025) supported by the Beijing Natural Science Foundation,China+4 种基金Project(20070004037) supported by the Doctoral Foundation of ChinaProject(2009JBM135,2011JBM023) supported by the Fundamental Research Funds for the Central Universities of ChinaProject(151139522) supported by the Hongguoyuan Innovative Talent Program of Beijing Jiaotong University,ChinaProject(YB20081000401) supported by the Beijing Excellent Doctoral Thesis Program,ChinaProject (2006CB303105) supported by the National Basic Research Program of China
文摘To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.
文摘In dynamic scenes,the pose estimation and map consistency of visual simultaneous localisation and mapping(visual SLAM)are affected by intermittent changes in object motion states.An adaptive motion-state estimation and feature-reuse mechanism is proposed which restores features once objects become stationary.Camera ego-motion is com-pensated via projection-based point-to-point red-green-blue-depth(RGB-D)Iterative Closest Point;the alignment residual yields a short-term jitter score.An Extended Kalman Filter fuses the centre-pixel trajectory and depth of the object,using depth innovation as strong evidence to suppress false triggers.Applied adaptive decision thresholds involve resolution,ego-motion intensity,jitter,and reference depth,and are combined with dual/single triggering and hysteresis to achieve robust switching.When an object is considered static,its feature points are reused.On the Bonn RGB-D Dynamic Dataset(BONN)and TUM RGB-D SLAM Dataset and Benchmark(TUM),the proposed method matches or exceeds baselines:In intermittent-motion-dominated BONN sequences Placing_non_box,it re-duces the root-mean-square of the absolute trajectory error(ATE-RMSE)by 27%relative to the baseline,remains comparable to Ellipsoid-SLAM on TUM,and consistently outperforms ORB-SLAM3 in dynamic scenes.The hysteresis counter reading on Placing_non_box2 shows that the proposed method can reduce the motion-state misclassification rate by nearly 40%.From the ablation experiment results,we confirm that adaptive thresholds yield the most significant optimisation effect.The approach improves robustness and map completeness in dynamic environments without degrading performance in low-dynamic settings.
基金National Natural Science Foundation of China (59895410)Natural Science Foundation of Heilongjiang Province (E0228) Joint Seismological Foundation of China (95-07-444).
文摘How to select the adequate real strong earthquake ground motion for seismic analysis and design of structures is an essential problem in earthquake engineering research and practice. In the paper the concept of the severest design ground motion is proposed and a method is developed for comparing the severity of the recorded strong ground motions. By using this method the severest earthquake ground motions are selected out as seismic inputs to the structures to be designed from a database that consists of more than five thousand significant strong ground motion records collected over the world. The selected severest ground motions are very likely to be able to drive the structures to their critical response and thereby result in the highest damage potential. It is noted that for different structures with different predominant natural periods and at different sites where structures are located the severest design ground motions are usually different. Finally, two examples are illustrated to demonstrate the rationality of the concept and the reliability of the selected design motion.
基金Supported by NSFC(Nos.11661025,12161024)Natural Science Foundation of Guangxi(Nos.2020GXNSFAA159118,2021GXNSFAA196045)+2 种基金Guangxi Science and Technology Project(No.Guike AD20297006)Training Program for 1000 Young and Middle-aged Cadre Teachers in Universities of GuangxiNational College Student's Innovation and Entrepreneurship Training Program(No.202110595049)。
文摘In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].
基金supported by the National Science Foundation(No.CMMI-2019459).
文摘The plastic deformation of semiconductors,a process critical to their mechanical and electronic properties,involves various mechanisms such as dislocation motion and phase transition.Here,we systematically examined the temperature-dependent Peierls stress for 30°and 90°partial dislocations in cadmium telluride(CdTe),using a combination of molecular statics and molecular dynamics simulations with a machine-learning force field,as well as density functional theory simulations.Our findings reveal that the 0 K Peierls stresses for these partial dislocations in CdTe are relatively low,ranging from 0.52 GPa to 1.46 GPa,due to its significant ionic bonding characteristics.Notably,in the CdTe system containing either a 30°Cd-core or 90°Te-core partial dislocation,a phase transition from the zinc-blende phase to theβ-Sn-like phase is favored over dislocation motion.This suggests a competitive relationship between these two mechanisms,driven by the bonding characteristics within the dislocation core and the relatively low phase transition stress of∼1.00 GPa.Furthermore,we observed a general trend wherein the Peierls stress for partial dislocations in CdTe exhibits a temperature dependence,which decreases with increasing temperature,becoming lower than the phase transition stress at elevated temperatures.Consequently,the dominant deformation mechanism in CdTe shifts from solid-state phase transition at low temperatures to dislocation motion at high temperatures.This investigation uncovers a compelling interplay between dislocation motion and phase transition in the plastic deformation of CdTe,offering profound insights into the mechanical behavior and electronic performance of CdTe and other II-VI semiconductors.
基金Shenzhen Science and Technology Programme,Grant/Award Number:JCYJ202308071208000012023 Shenzhen sustainable supporting funds for colleges and universities,Grant/Award Number:20231121165240001Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology,Grant/Award Number:2024B1212010006。
文摘Internal learning-based video inpainting methods have shown promising results by exploiting the intrinsic properties of the video to fill in the missing region without external dataset supervision.However,existing internal learning-based video inpainting methods would produce inconsistent structures or blurry textures due to the insufficient utilisation of motion priors within the video sequence.In this paper,the authors propose a new internal learning-based video inpainting model called appearance consistency and motion coherence network(ACMC-Net),which can not only learn the recurrence of appearance prior but can also capture motion coherence prior to improve the quality of the inpainting results.In ACMC-Net,a transformer-based appearance network is developed to capture global context information within the video frame for representing appearance consistency accurately.Additionally,a novel motion coherence learning scheme is proposed to learn the motion prior in a video sequence effectively.Finally,the learnt internal appearance consistency and motion coherence are implicitly propagated to the missing regions to achieve inpainting well.Extensive experiments conducted on the DAVIS dataset show that the proposed model obtains the superior performance in terms of quantitative measurements and produces more visually plausible results compared with the state-of-the-art methods.
基金supported by the National Natural Science Foundation of China(Nos.52373093 and 12072325)the Outstanding Youth Fund of Henan Province(No.242300421062)+1 种基金National Key R&D Program of China(No.2019YFA0706802)the 111 project(No.D18023).
文摘With the rapid development of wearable electronic skin technology, flexible strain sensors have shown great application prospects in the fields of human motion and physiological signal detection, medical diagnostics, and human-computer interaction owing to their outstanding sensing performance. This paper reports a strain sensor with synergistic conductive network, consisting of stable carbon nanotube dispersion (CNT) layer and brittle MXene layer by dip-coating and electrostatic self-assembly method, and breathable three-dimensional (3D) flexible substrate of thermoplastic polyurethane (TPU) fibrous membrane prepared through electrospinning technology. The MXene/CNT@PDA-TPU (MC@p-TPU) flexible strain sensor had excellent air permeability, wide operating range (0–450 %), high sensitivity (Gauge Factor, GFmax = 8089.7), ultra-low detection limit (0.05 %), rapid response and recovery times (40 ms/60 ms), and excellent cycle stability and durability (10,000 cycles). Given its superior strain sensing capabilities, this sensor can be applied in physiological signals detection, human motion pattern recognition, and driving exoskeleton robots. In addition, MC@p-TPU fibrous membrane also exhibited excellent photothermal conversion performance and can be used as a wearable photo-heater, which has far-reaching application potential in the photothermal therapy of human joint diseases.
基金Supported by the National Natural Science Foundation of China(51679080 and 51379073)the Fundamental Research Funds for the Central Universities(B230205020).
文摘This study employed a computational fluid dynamics model with an overset mesh technique to investigate the thrust and power of a floating offshore wind turbine(FOWT)under platform floating motion in the wind–rain field.The impact of rainfall on aerodynamic performance was initially examined using a stationary turbine model in both wind and wind–rain conditions.Subsequently,the study compared the FOWT’s performance under various single degree-of-freedom(DOF)motions,including surge,pitch,heave,and yaw.Finally,the combined effects of wind–rain fields and platform motions involving two DOFs on the FOWT’s aerodynamics were analyzed and compared.The results demonstrate that rain negatively impacts the aerodynamic performance of both the stationary turbines and FOWTs.Pitch-dominated motions,whether involving single or multiple DOFs,caused significant fluctuations in the FOWT aerodynamics.The combination of surge and pitch motions created the most challenging operational environment for the FOWT in all tested scenarios.These findings highlighted the need for stronger construction materials and greater ultimate bearing capacity for FOWTs,as well as the importance of optimizing designs to mitigate excessive pitch and surge.
基金National Natural Science Foundation of China (60702012)
文摘The side information quality has an immense effect on the compression efficiency of the distributed video coding (DVC) sys- tem. This article, based on the hierarchical motion estimation (HME), proposes a new side information generation algorithm which is integrated into DVC system. First, forward motion estimation (FME) and bidirectional motion estimation (BME) on the basis of variable block size HME algorithm are used to acquire relatively accurate motion vectors. Second, a motion vector filter (MVF) is i...
基金supported by The Key Science and Technology Plan Project of Jinhua City,China:2023-3-084,2023-2-011Zhejiang Provincial"Revealing the list and taking command"Project of China KYH06Y22349Open Fund Project of Key Laboratory of CNC Equipment reliability,Ministry of Education JLU-cncr-202407.
文摘Piezoelectric actuators are widely utilized in positioning systems to realize nano-scale resolution. However, the backward motion always generates for some piezoelectric actuators, which reduces the working efficiency. Bionic motions have already been employed in the field of piezoelectric actuators to realize better performance. By imitating the movement form of seals, seal type piezoelectric actuator is capable to realize large operating strokes easily. Nevertheless, the conventional seal type piezoelectric actuator has a complicated structure and control system, which limits further applications. Hence, an improved bionic piezoelectric actuator is proposed to realize a long motion stroke and eliminate backward movement with a simplified structure and control method in this study. The composition and motion principle of the designed actuator are discussed, and the performance is investigated with simulations and experiments. Results confirm that the presented actuator effectively realizes the linear movement that has a large working stroke stably without backward motion. The smallest stepping displacement ΔL is 0.2 μm under 1 Hz and 50 V. The largest motion speed is 900 μm/s with 900 Hz and 120 V. The largest vertical and horizontal load are 250 g and 12 g, respectively. This work shows that the improved bionic piezoelectric actuator is feasible for eliminating backward motion and has a great working ability.
基金Humanities and Social Sciences Research Project of China’s Ministry of Education(23YJCZH242)Major Humanities and Social Sciences Research Projects in Zhejiang Higher Education Institutions(2024QN069)Hangzhou Collaborative Innovation Institute of Language Services,Hangzhou City University,China。
文摘This article centers on The Call of the Wild,an English novel by American author Jack London,alongside two Chinese translations by Dajie Liu and Menglin Zhang,and Rongyue Liu.Seventy sentences containing motion events and their corresponding translations were randomly selected for analysis.The study focuses on the primary elements of motion events-manner,path,and ground-and examines their Chinese translations through the lens of Skopos theory.Skopos theory emphasizes whether translators can adopt appropriate translation strategies according to various contextual factors during the translation process.Compared to verb-framed languages,satellite-framed languages possess a richer vocabulary for manner verbs,express more detailed manner information,use more satellite words to indicate paths,and incorporate more background information.Verb-framed languages,by contrast,typically express manner information only when necessary and tend to include less background information.The analysis reveals that both Chinese translations embody the core principle of Skopos theory:translation strategies are determined by their purpose.To fulfill the novel’s translation objectives,the translators adeptly adjust their strategies for motion event components based on different contextual needs.It is noted that the Chinese translations do not fully retain the characteristics of English as a typical satellite-framed language.This observation aligns with Skopos theory’s purpose-oriented approach,which prioritizes translation goals over strict adherence to source text characteristics.
基金supported by the National Natural Science Foundation of China(52475307)the Shandong Provincial Natural Science Foundation(ZR2023ME041).
文摘Backswimmers exhibit a high degree of mobility in water,and their different motion patterns have important implications for the design of micro-biomimetic underwater robots.This paper used three-dimensional high-speed cameras to extract the key points on the hind legs.The hind leg motion laws and the deformation laws of the setae were obtained in four motion patterns:rapid forward,cruising,in-motion turning,and in-place turning.The motion laws of each joint on the hind leg are modeled using a Fourier series.A kinematic model of hind legs was established based on the DH method,and the motion characteristics of hind legs under different motion patterns were analyzed.This paper provides basic data and theoretical models for micro-biomimetic robots.
文摘An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.
基金supported by the National Science Foundation of China under Grant No.62101467。
文摘Motion recognition refers to the intelligent recognition of human motion using data collected from wearable sensors,which exceedingly has gained significant interest from both academic and industrial fields.However,temporary-sudden activities caused by accidental behavior pose a major challenge to motion recognition and have been largely overlooked in existing works.To address this problem,the multi-dimensional time series of motion data is modeled as a Time-Frequency(TF)tensor,and the original challenge is transformed into a problem of outlier-corrupted tensor pattern recognition,where transient sudden activity data are considered as outliers.Since the TF tensor can capture the latent spatio-temporal correlations of the motion data,the tensor MPCA is used to derive the principal spatio-temporal pattern of the motion data.However,traditional MPCA uses the squared F-norm as the projection distance measure,which makes it sensitive to the presence of outlier motion data.Therefore,in the proposed outlier-robust MPCA scheme,the F-norm with the desirable geometric properties is used as the distance measure to simultaneously mitigate the interference of outlier motion data while preserving rotational invariance.Moreover,to reduce the complexity of outlier-robust motion recognition,we impose the proposed outlier-robust MPCA scheme on the traditional MPCANet which is a low-complexity deep learning network.The experimental results show that our proposed outlier-robust MPCANet can simultaneously improve motion recognition performance and reduce the complexity,especially in practical scenarios where the real-time data is corrupted by temporary-sudden activities.
基金Open Access funding enabled and organized by CAUL and its Member Institutions。
文摘Shape memory alloy(SMA)bars are currently preferred over elastomeric seismic isolators due to the elimination of degradation within effective damping and stiffness factors during the cyclic response of an isolation system.These bars could also be used to prevent the functionality of the isolator units from failing due to large deformations.This study aims to investigate the performance of a high damping rubber bearing(HDRB)isolator that is combined with two different types of SMA bars,i.e.,Nickel-Titanium(Ni-Ti)and Copper-Aluminum-Beryllium(Cu-Al-Be),subjected to near-fault ground motions that are characterized with forward directivity and fling step effects.To achieve this objective,a self-centering material with flag-shape,force-deformation hysteresis was utilized to simulate the behavior of SMA bars in OpenSees.A single degree of freedom(SDOF)system representing an isolated one-story shear building was developed to conduct nonlinear analysis under selected ground motions.The SMA bars were introduced as an X-shape within the model and were connected diagonally to the top and bottom of the isolator.Results showed that the HDRB system’s hysteretic response under near-fault ground accelerations experiences significant degradation,especially when near-fault motions involve the fling step effect.It was demonstrated that SMA bars effectively reduce large displacement observed in HDRB systems under near-fault earthquakes.Comparing the results of the base-isolated HDRB and SMA-HDRB subjected to selected ground motions demonstrated that maximum displacement was found to be significantly reduced by an average of 79%when SMA bars were used.Incorporating SMA bars with a larger diameter significantly improves the efficiency of SMA HDRB systems,and a reduction in maximum displacements is more pronounced for fling step,near-fault ground motions.
