Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narr...Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT^(*)-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT^(*),the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT^(*).Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications.展开更多
Artificial Intelligence(AI)in healthcare enables predicting diabetes using data-driven methods instead of the traditional ways of screening the disease,which include hemoglobin A1c(HbA1c),oral glucose tolerance test(O...Artificial Intelligence(AI)in healthcare enables predicting diabetes using data-driven methods instead of the traditional ways of screening the disease,which include hemoglobin A1c(HbA1c),oral glucose tolerance test(OGTT),and fasting plasma glucose(FPG)screening techniques,which are invasive and limited in scale.Machine learning(ML)and deep neural network(DNN)models that use large datasets to learn the complex,nonlinear feature interactions,but the conventional ML algorithms are data sensitive and often show unstable predictive accuracy.Conversely,DNN models are more robust,though the ability to reach a high accuracy rate consistently on heterogeneous datasets is still an open challenge.For predicting diabetes,this work proposed a hybrid DNN approach by integrating a bidirectional long short-term memory(BiLSTM)network with a bidirectional gated recurrent unit(BiGRU).A robust DL model,developed by combining various datasets with weighted coefficients,dense operations in the connection of deep layers,and the output aggregation using batch normalization and dropout functions to avoid overfitting.The goal of this hybrid model is better generalization and consistency among various datasets,which facilitates the effective management and early intervention.The proposed DNN model exhibits an excellent predictive performance as compared to the state-of-the-art and baseline ML and DNN models for diabetes prediction tasks.The robust performance indicates the possible usefulness of DL-based models in the development of disease prediction in healthcare and other areas that demand high-quality analytics.展开更多
Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-...Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-attention modeling of global temporal dependency has problems of high computational overhead and feature similarity.On the other hand,fixed-size convolution kernels are often used,which have weak perception ability for emotional regions of different scales.Therefore,this paper proposes a video emotion recognition model that combines multi-scale region-aware convolution with temporal interactive sampling.In terms of space,multi-branch large-kernel stripe convolution is used to perceive emotional region features at different scales,and attention weights are generated for each scale feature.In terms of time,multi-layer odd-even down-sampling is performed on the time series,and oddeven sub-sequence interaction is performed to solve the problem of feature similarity,while reducing computational costs due to the linear relationship between sampling and convolution overhead.This paper was tested on CMU-MOSI,CMU-MOSEI,and Hume Reaction.The Acc-2 reached 83.4%,85.2%,and 81.2%,respectively.The experimental results show that the model can significantly improve the accuracy of emotion recognition.展开更多
Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either re...Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either require trusted setups or suffer from high communication overhead and low verification efficiency.This paper presents ISTIRDA,a DAS scheme that lets light clients certify availability by sampling small random codeword symbols.Built on ISTIR,an improved Reed–Solomon interactive oracle proof of proximity,ISTIRDA combines adaptive folding with dynamic code rate adjustment to preserve soundness while lowering communication.This paper formalizes opening consistency and prove security with bounded error in the random oracle model,giving polylogarithmic verifier queries and no trusted setup.In a prototype compared with FRIDA under equal soundness,ISTIRDA reduces communication by 40.65%to 80%.For data larger than 16 MB,ISTIRDA verifies faster and the advantage widens;at 128 MB,proofs are about 60%smaller and verification time is roughly 25%shorter,while prover overhead remains modest.In peer-to-peer emulation under injected latency and loss,ISTIRDA reaches confidence more quickly and is less sensitive to packet loss and load.These results indicate that ISTIRDA is a scalable and provably secure DAS scheme suitable for high-throughput,large-block public blockchains,substantially easing bandwidth and latency pressure on lightweight nodes.展开更多
The condensation tracking algorithm uses a prior transition probability as the proposal distribution, which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking...The condensation tracking algorithm uses a prior transition probability as the proposal distribution, which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking algorithm based on particle filter with mean shift importance sampling is proposed. First, the coarse location of the face target is attained by the efficient mean shift tracker, and then the result is used to construct the proposal distribution for particle propagation. Because the particles obtained with this method can cluster around the true state region, particle efficiency is improved greatly. The experimental results show that the performance of the proposed algorithm is better than that of the standard condensation tracking algorithm.展开更多
A novel data streams partitioning method is proposed to resolve problems of range-aggregation continuous queries over parallel streams for power industry.The first step of this method is to parallel sample the data,wh...A novel data streams partitioning method is proposed to resolve problems of range-aggregation continuous queries over parallel streams for power industry.The first step of this method is to parallel sample the data,which is implemented as an extended reservoir-sampling algorithm.A skip factor based on the change ratio of data-values is introduced to describe the distribution characteristics of data-values adaptively.The second step of this method is to partition the fluxes of data streams averagely,which is implemented with two alternative equal-depth histogram generating algorithms that fit the different cases：one for incremental maintenance based on heuristics and the other for periodical updates to generate an approximate partition vector.The experimental results on actual data prove that the method is efficient,practical and suitable for time-varying data streams processing.展开更多
We consider solving the forward and inverse partial differential equations(PDEs)which have sharp solutions with physics-informed neural networks(PINNs)in this work.In particular,to better capture the sharpness of the ...We consider solving the forward and inverse partial differential equations(PDEs)which have sharp solutions with physics-informed neural networks(PINNs)in this work.In particular,to better capture the sharpness of the solution,we propose the adaptive sampling methods(ASMs)based on the residual and the gradient of the solution.We first present a residual only-based ASM denoted by ASMⅠ.In this approach,we first train the neural network using a small number of residual points and divide the computational domain into a certain number of sub-domains,then we add new residual points in the sub-domain which has the largest mean absolute value of the residual,and those points which have the largest absolute values of the residual in this sub-domain as new residual points.We further develop a second type of ASM(denoted by ASMⅡ)based on both the residual and the gradient of the solution due to the fact that only the residual may not be able to efficiently capture the sharpness of the solution.The procedure of ASMⅡis almost the same as that of ASMⅠ,and we add new residual points which have not only large residuals but also large gradients.To demonstrate the effectiveness of the present methods,we use both ASMⅠand ASMⅡto solve a number of PDEs,including the Burger equation,the compressible Euler equation,the Poisson equation over an Lshape domain as well as the high-dimensional Poisson equation.It has been shown from the numerical results that the sharp solutions can be well approximated by using either ASMⅠor ASMⅡ,and both methods deliver much more accurate solutions than the original PINNs with the same number of residual points.Moreover,the ASMⅡalgorithm has better performance in terms of accuracy,efficiency,and stability compared with the ASMⅠalgorithm.This means that the gradient of the solution improves the stability and efficiency of the adaptive sampling procedure as well as the accuracy of the solution.Furthermore,we also employ the similar adaptive sampling technique for the data points of boundary conditions(BCs)if the sharpness of the solution is near the boundary.The result of the L-shape Poisson problem indicates that the present method can significantly improve the efficiency,stability,and accuracy.展开更多
Based on previous research, the sampling and analysis methods for phthalate esters （PAEs） were improved by increasing the sampling flow of indoor air from 1 to 4 L/min, shortening the sampling duration from 8 to 2 h...Based on previous research, the sampling and analysis methods for phthalate esters （PAEs） were improved by increasing the sampling flow of indoor air from 1 to 4 L/min, shortening the sampling duration from 8 to 2 hr. Meanwhile, through the optimization of chromatographic conditions, the concentrations of 9 additional PAE pollutants in indoor air were measured. The optimized chromatographic conditions required a similar amount of time for analysis as before, but gave high responsivity, the capability of simultaneously distinguishing 15 kinds of PAEs, and a high level of discrimination between individual sample peaks, as well as stable peak generation. The recovery rate of all gas-phase and particle-phase samples of the 15 kinds of PAEs ranged from 91.26% to 109.42%, meeting the quantitative analysis requirements for indoor and outdoor air sampling and analysis. For the first time, investigation of the concentration levels as well as characteristics of 15 kinds of PAEs in the indoor air from four different traffic micro-environments （private vehicles, busses, taxis and subways） was carried out, along with validation of the optimized sampling and analytical method. The results show that all the 9 additional PAEs could be detected at relatively high pollution levels in the indoor air from the four traffic micro-environments. As none of the pollution levels of the 15 kinds of PAEs in the indoor air from the 4 traffic micro-environments should be neglected, it is of great significance to increase the types of PAEs able to be detected in indoor air.展开更多
There exists a great variety of posturographic parameters which complicates the evaluation of center of pressure (COP) data. Hence, recommendations were given to use a set of complementary parameters to explain most o...There exists a great variety of posturographic parameters which complicates the evaluation of center of pressure (COP) data. Hence, recommendations were given to use a set of complementary parameters to explain most of the variance. However, it is unknown whether a dual task paradigm leads to different parametrization sets. On account of this problem an exploratory factor analysis approach was conducted in a dual task experiment. 16 healthy subjects stood on a force plate performing a posture-cognition dual task (DT, focus of attention on a secondary task) with respect to different sampling durations. The subjects were not aware of being measured in contrast to a baseline task condition (BT, internal focus of attention) in the previously published part I. In compareson to BT a different factor loading pattern appears. In addition, factor loadings are strongly affected by different sampling durations. DT reveals a change of factor loading structure with longer sampling durations compared to BT. Specific recommendations concerning a framework of posturographic parametrization are given.展开更多
Low-density polyethylene(LDPE)has been widely used as a sorbent for passive sampling of hydrophobic organic contaminants(HOCs)in aquatic environments.However,it has seen only limited application in passive sampling fo...Low-density polyethylene(LDPE)has been widely used as a sorbent for passive sampling of hydrophobic organic contaminants(HOCs)in aquatic environments.However,it has seen only limited application in passive sampling for measurement of freely dissolved concentrations of parent and substituted PAHs(SPAHs),which are known to be toxic,mutagenic and carcinogenic.Here,the 16 priority PAHs and some typical PAHs were selected as target compounds and were simultaneously determined by gas chromatography–mass spectrometer(GC–MS).Some batch experiments were conducted in the laboratory to explore the adsorption kinetics of the target compounds in LDPE membranes.The results showed that both PAHs and SPAHs could reach equilibrium status within19–38 days in sorption kinetic experiments.The coefficients of partitioning between LDPE film(50μm thickness)and water(KLDPE)for the 16 priority PAHs were in good agreement with previously reported values,and the values of KLDPEfor the 9 SPAHs are reported in this study for the first time.Significant linear relationships were observed,i.e.,log KLDPE=0.705×log KOW+1.534 for PAHs(R^2=0.8361,p<0.001)and log KLDPE=0.458×log KOW+3.092 for SPAHs(R^2=0.5609,p=0.0077).The selected LDPE film was also proven to meet the condition of"zero sink"for the selected target compounds.These results could provide basic support for the configuration and in situ application of passive samplers.展开更多
The SARS–CoV–2 virus is released from an infectious source(such as a sick person)and adsorbed on aerosols,which can form pathogenic microorganism aerosols,which can affect human health through airborne transmission....The SARS–CoV–2 virus is released from an infectious source(such as a sick person)and adsorbed on aerosols,which can form pathogenic microorganism aerosols,which can affect human health through airborne transmission.Efficient sampling and accurate detection of microorganisms in aerosols are the premise and basis for studying their properties and evaluating their hazard.In this study,we built a set of sub-micron aerosol detection platform,and carried out a simulation experiment on the SARS–CoV–2 aerosol in the air by wet-wall cyclone combined with immunomagnetic nanoparticle adsorption sampling and ddPCR.The feasibility of the system in aerosol detection was verified,and the influencing factors in the detection process were experimentally tested.As a result,the sampling efficiency was 29.77%,and extraction efficiency was 98.57%.The minimum detection limit per unit volume of aerosols was 250 copies(102copies/m L,concentration factor 2.5).展开更多
This is the second part of our series works on failure-informed adaptive sampling for physic-informed neural networks(PINNs).In our previous work(SIAM J.Sci.Comput.45:A1971–A1994),we have presented an adaptive sampli...This is the second part of our series works on failure-informed adaptive sampling for physic-informed neural networks(PINNs).In our previous work(SIAM J.Sci.Comput.45:A1971–A1994),we have presented an adaptive sampling framework by using the failure probability as the posterior error indicator,where the truncated Gaussian model has been adopted for estimating the indicator.Here,we present two extensions of that work.The first extension consists in combining with a re-sampling technique,so that the new algorithm can maintain a constant training size.This is achieved through a cosine-annealing,which gradually transforms the sampling of collocation points from uniform to adaptive via the training progress.The second extension is to present the subset simulation(SS)algorithm as the posterior model(instead of the truncated Gaussian model)for estimating the error indicator,which can more effectively estimate the failure probability and generate new effective training points in the failure region.We investigate the performance of the new approach using several challenging problems,and numerical experiments demonstrate a significant improvement over the original algorithm.展开更多
After reading the above mentioned article of [1], we identified a mistake considering the results of the paragraph “3.6. Nonlinear Parameters AP” and the related Table 5 (both on p. 512). Unfortunately, published Ta...After reading the above mentioned article of [1], we identified a mistake considering the results of the paragraph “3.6. Nonlinear Parameters AP” and the related Table 5 (both on p. 512). Unfortunately, published Table 5 is a duplicate of Table 4, and therefore it is not possible for the reader to comprehend any underlying interrelations. To correct this mistake, we would like to offer the corrected table (Table 5) as follows.展开更多
This study investigates the choice of posturographic parameter sets with respect to the influence of different sampling durations (30 s, 60 s, 300 s). Center of pressure (COP) data are derived from 16 healthy subjects...This study investigates the choice of posturographic parameter sets with respect to the influence of different sampling durations (30 s, 60 s, 300 s). Center of pressure (COP) data are derived from 16 healthy subjects standing quietly on a force plate. They were advised to focus on the postural control process ( i.e. internal focus of attention). 33 common linear and 10 nonlinear parameters are calculated and grouped into five classes. Component structure in each group is obtained via exploratory factor analysis. We demonstrate that COP evaluation—irrespective of sampling duration—necessitates a set of diverse parameters to explain more variance of the data. Further more, parameter sets are uniformly invariant towards sampling durations and display a consistent factor loading pattern. These findings pose a structure for COP parametrization. Hence, specific recommendations are preserved in order to avoid redundancy or misleading basis for inter-study comparisons. The choice of 11 parameters from the groups is recommended as a framework for future research in posturography.展开更多
Nonperiodic interrupted sampling repeater jamming(ISRJ)against inverse synthetic aperture radar(ISAR)can obtain two-dimensional blanket jamming performance by joint fast and slow time domain interrupted modulation,whi...Nonperiodic interrupted sampling repeater jamming(ISRJ)against inverse synthetic aperture radar(ISAR)can obtain two-dimensional blanket jamming performance by joint fast and slow time domain interrupted modulation,which is obviously dif-ferent from the conventional multi-false-target deception jam-ming.In this paper,a suppression method against this kind of novel jamming is proposed based on inter-pulse energy function and compressed sensing theory.By utilizing the discontinuous property of the jamming in slow time domain,the unjammed pulse is separated using the intra-pulse energy function diffe-rence.Based on this,the two-dimensional orthogonal matching pursuit(2D-OMP)algorithm is proposed.Further,it is proposed to reconstruct the ISAR image with the obtained unjammed pulse sequence.The validity of the proposed method is demon-strated via the Yake-42 plane data simulations.展开更多
Point-based surface has been widely used in computer graphics for modeling, animation, visualization, simulation of liq- uid and so on. Furthermore, particle-based approach can distribute the surface sampling points a...Point-based surface has been widely used in computer graphics for modeling, animation, visualization, simulation of liq- uid and so on. Furthermore, particle-based approach can distribute the surface sampling points and control its parameters according to the needs of the application. In this paper, we examine several kinds of algorithms presented over the last decades, with the main focus on particle sampling technologies for implicit surface. Therefore, we classify various algorithms into categories, describe main ideas behind each categories, and compare the advantages and shortcomings of the algorithms in each category.展开更多
One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific object...One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.展开更多
Electro-Optic Sampling(EOS)detection technique has been widely used in terahertz science and tech⁃nology,and it also can measure the field time waveform of the few-cycle laser pulse.Its frequency response and band lim...Electro-Optic Sampling(EOS)detection technique has been widely used in terahertz science and tech⁃nology,and it also can measure the field time waveform of the few-cycle laser pulse.Its frequency response and band limitation are determined directly by the electro-optic crystal and duration of the probe laser pulse.Here,we investigate the performance of the EOS with thin GaSe crystal in the measurement of the mid-infrared few-cycle la⁃ser pulse.The shift of the central frequency and change of the bandwidth induced by the EOS detection are calcu⁃lated,and then the pulse distortions induced in this detection process are discussed.It is found that this technique produces a red-shift of the central frequency and narrowing of the bandwidth.These changings decrease when the laser wavelength increases from 2μm to 10μm.This work can help to estimate the performance of the EOS de⁃tection technique in the mid-infrared band and offer a reference for the related experiment as well.展开更多
Critical Height Sampling(CHS)estimates stand volume free from any model and tree form assumptions.Despite its introduction more than four decades ago,CHS has not been widely applied in the field due to perceived chall...Critical Height Sampling(CHS)estimates stand volume free from any model and tree form assumptions.Despite its introduction more than four decades ago,CHS has not been widely applied in the field due to perceived challenges in measurement.The objectives of this study were to compare estimated stand volume between CHS and sampling methods that used volume or taper models,the equivalence of the sampling methods,and their relative efficiency.We established 65 field plots in planted forests of two coniferous tree species.We estimated stand volume for a range of Basal Area Factors(BAFs).Results showed that CHS produced the most similar mean stand volume across BAFs and tree species with maximum differences between BAFs of 5-18m^(3)·ha^(−1).Horizontal Point Sampling(HPS)using volume models produced very large variability in mean stand volume across BAFs with the differences up to 126m^(3)·ha^(−1).However,CHS was less precise and less efficient than HPS.Furthermore,none of the sampling methods were statistically interchangeable with CHS at an allowable tolerance of≤55m^(3)·ha^(−1).About 72%of critical height measurements were below crown base indicating that critical height was more accessible to measurement than expected.Our study suggests that the consistency in the mean estimates of CHS is a major advantage when planning a forest inventory.When checking against CHS,results hint that HPS estimates might contain potential model bias.These strengths of CHS could outweigh its lower precision.Our study also implies serious implications in financial terms when choosing a sampling method.Lastly,CHS could potentially benefit forest management as an alternate option of estimating stand volume when volume or taper models are lacking or are not reliable.展开更多
Optical solitons,as self-sustaining waveforms in a nonlinear medium where dispersion and nonlinear effects are balanced,have key applications in ultrafast laser systems and optical communications.Physics-informed neur...Optical solitons,as self-sustaining waveforms in a nonlinear medium where dispersion and nonlinear effects are balanced,have key applications in ultrafast laser systems and optical communications.Physics-informed neural networks(PINN)provide a new way to solve the nonlinear Schrodinger equation describing the soliton evolution by fusing data-driven and physical constraints.However,the grid point sampling strategy of traditional PINN suffers from high computational complexity and unstable gradient flow,which makes it difficult to capture the physical details efficiently.In this paper,we propose a residual-based adaptive multi-distribution(RAMD)sampling method to optimize the PINN training process by dynamically constructing a multi-modal loss distribution.With a 50%reduction in the number of grid points,RAMD significantly reduces the relative error of PINN and,in particular,optimizes the solution error of the(2+1)Ginzburg–Landau equation from 4.55%to 1.98%.RAMD breaks through the lack of physical constraints in the purely data-driven model by the innovative combination of multi-modal distribution modeling and autonomous sampling control for the design of all-optical communication devices.RAMD provides a high-precision numerical simulation tool for the design of all-optical communication devices,optimization of nonlinear laser devices,and other studies.展开更多
基金National Natural Science Foundation of China(32301712)Natural Science Foundation of Jiangsu Province(BK20230548,BK20250876)+2 种基金Project of Faculty of Agricultural Equipment of Jiangsu University(NGXB20240203)A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD-2023-87)Open Funding Project of the Key Laboratory of Modern Agricultural Equipment and Technology(Jiangsu University),Ministry of Education(MAET202101)。
文摘Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT^(*)-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT^(*),the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT^(*).Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications.
基金supported by the School of Digital Science,Universiti Brunei Darussalam,Brunei.
文摘Artificial Intelligence(AI)in healthcare enables predicting diabetes using data-driven methods instead of the traditional ways of screening the disease,which include hemoglobin A1c(HbA1c),oral glucose tolerance test(OGTT),and fasting plasma glucose(FPG)screening techniques,which are invasive and limited in scale.Machine learning(ML)and deep neural network(DNN)models that use large datasets to learn the complex,nonlinear feature interactions,but the conventional ML algorithms are data sensitive and often show unstable predictive accuracy.Conversely,DNN models are more robust,though the ability to reach a high accuracy rate consistently on heterogeneous datasets is still an open challenge.For predicting diabetes,this work proposed a hybrid DNN approach by integrating a bidirectional long short-term memory(BiLSTM)network with a bidirectional gated recurrent unit(BiGRU).A robust DL model,developed by combining various datasets with weighted coefficients,dense operations in the connection of deep layers,and the output aggregation using batch normalization and dropout functions to avoid overfitting.The goal of this hybrid model is better generalization and consistency among various datasets,which facilitates the effective management and early intervention.The proposed DNN model exhibits an excellent predictive performance as compared to the state-of-the-art and baseline ML and DNN models for diabetes prediction tasks.The robust performance indicates the possible usefulness of DL-based models in the development of disease prediction in healthcare and other areas that demand high-quality analytics.
基金supported,in part,by the National Nature Science Foundation of China under Grant 62272236,62376128in part,by the Natural Science Foundation of Jiangsu Province under Grant BK20201136,BK20191401.
文摘Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-attention modeling of global temporal dependency has problems of high computational overhead and feature similarity.On the other hand,fixed-size convolution kernels are often used,which have weak perception ability for emotional regions of different scales.Therefore,this paper proposes a video emotion recognition model that combines multi-scale region-aware convolution with temporal interactive sampling.In terms of space,multi-branch large-kernel stripe convolution is used to perceive emotional region features at different scales,and attention weights are generated for each scale feature.In terms of time,multi-layer odd-even down-sampling is performed on the time series,and oddeven sub-sequence interaction is performed to solve the problem of feature similarity,while reducing computational costs due to the linear relationship between sampling and convolution overhead.This paper was tested on CMU-MOSI,CMU-MOSEI,and Hume Reaction.The Acc-2 reached 83.4%,85.2%,and 81.2%,respectively.The experimental results show that the model can significantly improve the accuracy of emotion recognition.
基金supported in part by the Research Fund of Key Lab of Education Blockchain and Intelligent Technology,Ministry of Education(EBME25-F-08).
文摘Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either require trusted setups or suffer from high communication overhead and low verification efficiency.This paper presents ISTIRDA,a DAS scheme that lets light clients certify availability by sampling small random codeword symbols.Built on ISTIR,an improved Reed–Solomon interactive oracle proof of proximity,ISTIRDA combines adaptive folding with dynamic code rate adjustment to preserve soundness while lowering communication.This paper formalizes opening consistency and prove security with bounded error in the random oracle model,giving polylogarithmic verifier queries and no trusted setup.In a prototype compared with FRIDA under equal soundness,ISTIRDA reduces communication by 40.65%to 80%.For data larger than 16 MB,ISTIRDA verifies faster and the advantage widens;at 128 MB,proofs are about 60%smaller and verification time is roughly 25%shorter,while prover overhead remains modest.In peer-to-peer emulation under injected latency and loss,ISTIRDA reaches confidence more quickly and is less sensitive to packet loss and load.These results indicate that ISTIRDA is a scalable and provably secure DAS scheme suitable for high-throughput,large-block public blockchains,substantially easing bandwidth and latency pressure on lightweight nodes.
基金The National Natural Science Foundation of China(No60672094)
文摘The condensation tracking algorithm uses a prior transition probability as the proposal distribution, which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking algorithm based on particle filter with mean shift importance sampling is proposed. First, the coarse location of the face target is attained by the efficient mean shift tracker, and then the result is used to construct the proposal distribution for particle propagation. Because the particles obtained with this method can cluster around the true state region, particle efficiency is improved greatly. The experimental results show that the performance of the proposed algorithm is better than that of the standard condensation tracking algorithm.
基金The High Technology Research Plan of Jiangsu Prov-ince (No.BG2004034)the Foundation of Graduate Creative Program ofJiangsu Province (No.xm04-36).
文摘A novel data streams partitioning method is proposed to resolve problems of range-aggregation continuous queries over parallel streams for power industry.The first step of this method is to parallel sample the data,which is implemented as an extended reservoir-sampling algorithm.A skip factor based on the change ratio of data-values is introduced to describe the distribution characteristics of data-values adaptively.The second step of this method is to partition the fluxes of data streams averagely,which is implemented with two alternative equal-depth histogram generating algorithms that fit the different cases：one for incremental maintenance based on heuristics and the other for periodical updates to generate an approximate partition vector.The experimental results on actual data prove that the method is efficient,practical and suitable for time-varying data streams processing.
基金Project supported by the National Key R&D Program of China(No.2022YFA1004504)the National Natural Science Foundation of China(Nos.12171404 and 12201229)the Fundamental Research Funds for Central Universities of China(No.20720210037)。
文摘We consider solving the forward and inverse partial differential equations(PDEs)which have sharp solutions with physics-informed neural networks(PINNs)in this work.In particular,to better capture the sharpness of the solution,we propose the adaptive sampling methods(ASMs)based on the residual and the gradient of the solution.We first present a residual only-based ASM denoted by ASMⅠ.In this approach,we first train the neural network using a small number of residual points and divide the computational domain into a certain number of sub-domains,then we add new residual points in the sub-domain which has the largest mean absolute value of the residual,and those points which have the largest absolute values of the residual in this sub-domain as new residual points.We further develop a second type of ASM(denoted by ASMⅡ)based on both the residual and the gradient of the solution due to the fact that only the residual may not be able to efficiently capture the sharpness of the solution.The procedure of ASMⅡis almost the same as that of ASMⅠ,and we add new residual points which have not only large residuals but also large gradients.To demonstrate the effectiveness of the present methods,we use both ASMⅠand ASMⅡto solve a number of PDEs,including the Burger equation,the compressible Euler equation,the Poisson equation over an Lshape domain as well as the high-dimensional Poisson equation.It has been shown from the numerical results that the sharp solutions can be well approximated by using either ASMⅠor ASMⅡ,and both methods deliver much more accurate solutions than the original PINNs with the same number of residual points.Moreover,the ASMⅡalgorithm has better performance in terms of accuracy,efficiency,and stability compared with the ASMⅠalgorithm.This means that the gradient of the solution improves the stability and efficiency of the adaptive sampling procedure as well as the accuracy of the solution.Furthermore,we also employ the similar adaptive sampling technique for the data points of boundary conditions(BCs)if the sharpness of the solution is near the boundary.The result of the L-shape Poisson problem indicates that the present method can significantly improve the efficiency,stability,and accuracy.
基金support by the Hi-Tech Research and Development Program(863) of China(No.2010AA064902)the National Key Technologies R&D Program(No.2016YFC0207100)+1 种基金the National Natural Science Foundation of China(No.21207116)the Brain Bridge project with Philips(No.BB3-2016-01)
文摘Based on previous research, the sampling and analysis methods for phthalate esters （PAEs） were improved by increasing the sampling flow of indoor air from 1 to 4 L/min, shortening the sampling duration from 8 to 2 hr. Meanwhile, through the optimization of chromatographic conditions, the concentrations of 9 additional PAE pollutants in indoor air were measured. The optimized chromatographic conditions required a similar amount of time for analysis as before, but gave high responsivity, the capability of simultaneously distinguishing 15 kinds of PAEs, and a high level of discrimination between individual sample peaks, as well as stable peak generation. The recovery rate of all gas-phase and particle-phase samples of the 15 kinds of PAEs ranged from 91.26% to 109.42%, meeting the quantitative analysis requirements for indoor and outdoor air sampling and analysis. For the first time, investigation of the concentration levels as well as characteristics of 15 kinds of PAEs in the indoor air from four different traffic micro-environments （private vehicles, busses, taxis and subways） was carried out, along with validation of the optimized sampling and analytical method. The results show that all the 9 additional PAEs could be detected at relatively high pollution levels in the indoor air from the four traffic micro-environments. As none of the pollution levels of the 15 kinds of PAEs in the indoor air from the 4 traffic micro-environments should be neglected, it is of great significance to increase the types of PAEs able to be detected in indoor air.
文摘There exists a great variety of posturographic parameters which complicates the evaluation of center of pressure (COP) data. Hence, recommendations were given to use a set of complementary parameters to explain most of the variance. However, it is unknown whether a dual task paradigm leads to different parametrization sets. On account of this problem an exploratory factor analysis approach was conducted in a dual task experiment. 16 healthy subjects stood on a force plate performing a posture-cognition dual task (DT, focus of attention on a secondary task) with respect to different sampling durations. The subjects were not aware of being measured in contrast to a baseline task condition (BT, internal focus of attention) in the previously published part I. In compareson to BT a different factor loading pattern appears. In addition, factor loadings are strongly affected by different sampling durations. DT reveals a change of factor loading structure with longer sampling durations compared to BT. Specific recommendations concerning a framework of posturographic parametrization are given.
基金supported by the National Natural Science Foundation of China(Nos.41877471 and 41676095)the China Postdoctoral Science Foundation,China(No.2017M622782)+1 种基金the Open Foundation of Key Laboratory of Tropical Marine Bio-resources and Ecology(LMB),Chinese Academy of Sciences,China(No.LMB20191004)the Science and Technology Innovation Commission of Shenzhen,China(No.JCYJ20180507182227257)
文摘Low-density polyethylene(LDPE)has been widely used as a sorbent for passive sampling of hydrophobic organic contaminants(HOCs)in aquatic environments.However,it has seen only limited application in passive sampling for measurement of freely dissolved concentrations of parent and substituted PAHs(SPAHs),which are known to be toxic,mutagenic and carcinogenic.Here,the 16 priority PAHs and some typical PAHs were selected as target compounds and were simultaneously determined by gas chromatography–mass spectrometer(GC–MS).Some batch experiments were conducted in the laboratory to explore the adsorption kinetics of the target compounds in LDPE membranes.The results showed that both PAHs and SPAHs could reach equilibrium status within19–38 days in sorption kinetic experiments.The coefficients of partitioning between LDPE film(50μm thickness)and water(KLDPE)for the 16 priority PAHs were in good agreement with previously reported values,and the values of KLDPEfor the 9 SPAHs are reported in this study for the first time.Significant linear relationships were observed,i.e.,log KLDPE=0.705×log KOW+1.534 for PAHs(R^2=0.8361,p<0.001)and log KLDPE=0.458×log KOW+3.092 for SPAHs(R^2=0.5609,p=0.0077).The selected LDPE film was also proven to meet the condition of"zero sink"for the selected target compounds.These results could provide basic support for the configuration and in situ application of passive samplers.
基金supported by the NSFC(Nos.61701176 and 62071119)Macao FDCT(No.0065/2020/A2)+4 种基金Natural Science Foundation of Hunan Province of China(Nos.2022JJ50052,2018JJ3130 and 2020JJ5145)Hunan Key R&D Projects(No.2021SK2003)Nanjing Important Science&Technology Specific Projects(No.2021-11005)2022 Special Project for the Construction of Innovative Provinces to Fight the COVID-19 Outbreak(No.2022SK2115)Open Funding of State Key Laboratory of Oral Diseases(No.SKLOD2022OF05)。
文摘The SARS–CoV–2 virus is released from an infectious source(such as a sick person)and adsorbed on aerosols,which can form pathogenic microorganism aerosols,which can affect human health through airborne transmission.Efficient sampling and accurate detection of microorganisms in aerosols are the premise and basis for studying their properties and evaluating their hazard.In this study,we built a set of sub-micron aerosol detection platform,and carried out a simulation experiment on the SARS–CoV–2 aerosol in the air by wet-wall cyclone combined with immunomagnetic nanoparticle adsorption sampling and ddPCR.The feasibility of the system in aerosol detection was verified,and the influencing factors in the detection process were experimentally tested.As a result,the sampling efficiency was 29.77%,and extraction efficiency was 98.57%.The minimum detection limit per unit volume of aerosols was 250 copies(102copies/m L,concentration factor 2.5).
基金supported by the NSF of China(No.12171085)This work was supported by the National Key R&D Program of China(2020YFA0712000)+2 种基金the NSF of China(No.12288201)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA25010404)and the Youth Innovation Promotion Association(CAS).
文摘This is the second part of our series works on failure-informed adaptive sampling for physic-informed neural networks(PINNs).In our previous work(SIAM J.Sci.Comput.45:A1971–A1994),we have presented an adaptive sampling framework by using the failure probability as the posterior error indicator,where the truncated Gaussian model has been adopted for estimating the indicator.Here,we present two extensions of that work.The first extension consists in combining with a re-sampling technique,so that the new algorithm can maintain a constant training size.This is achieved through a cosine-annealing,which gradually transforms the sampling of collocation points from uniform to adaptive via the training progress.The second extension is to present the subset simulation(SS)algorithm as the posterior model(instead of the truncated Gaussian model)for estimating the error indicator,which can more effectively estimate the failure probability and generate new effective training points in the failure region.We investigate the performance of the new approach using several challenging problems,and numerical experiments demonstrate a significant improvement over the original algorithm.
文摘After reading the above mentioned article of [1], we identified a mistake considering the results of the paragraph “3.6. Nonlinear Parameters AP” and the related Table 5 (both on p. 512). Unfortunately, published Table 5 is a duplicate of Table 4, and therefore it is not possible for the reader to comprehend any underlying interrelations. To correct this mistake, we would like to offer the corrected table (Table 5) as follows.
文摘This study investigates the choice of posturographic parameter sets with respect to the influence of different sampling durations (30 s, 60 s, 300 s). Center of pressure (COP) data are derived from 16 healthy subjects standing quietly on a force plate. They were advised to focus on the postural control process ( i.e. internal focus of attention). 33 common linear and 10 nonlinear parameters are calculated and grouped into five classes. Component structure in each group is obtained via exploratory factor analysis. We demonstrate that COP evaluation—irrespective of sampling duration—necessitates a set of diverse parameters to explain more variance of the data. Further more, parameter sets are uniformly invariant towards sampling durations and display a consistent factor loading pattern. These findings pose a structure for COP parametrization. Hence, specific recommendations are preserved in order to avoid redundancy or misleading basis for inter-study comparisons. The choice of 11 parameters from the groups is recommended as a framework for future research in posturography.
基金supported by the National Natural Science Foundation of China(62001481,61890542,62071475)the Natural Science Foundation of Hunan Province(2022JJ40561)the Research Program of National University of Defense Technology(ZK22-46).
文摘Nonperiodic interrupted sampling repeater jamming(ISRJ)against inverse synthetic aperture radar(ISAR)can obtain two-dimensional blanket jamming performance by joint fast and slow time domain interrupted modulation,which is obviously dif-ferent from the conventional multi-false-target deception jam-ming.In this paper,a suppression method against this kind of novel jamming is proposed based on inter-pulse energy function and compressed sensing theory.By utilizing the discontinuous property of the jamming in slow time domain,the unjammed pulse is separated using the intra-pulse energy function diffe-rence.Based on this,the two-dimensional orthogonal matching pursuit(2D-OMP)algorithm is proposed.Further,it is proposed to reconstruct the ISAR image with the obtained unjammed pulse sequence.The validity of the proposed method is demon-strated via the Yake-42 plane data simulations.
基金supported by the National Nature Science Foundation of China (61020106001,60903109,61103150)National Research Foundation for the Doctoral Program of Higher Education of China (20110131130004)
文摘Point-based surface has been widely used in computer graphics for modeling, animation, visualization, simulation of liq- uid and so on. Furthermore, particle-based approach can distribute the surface sampling points and control its parameters according to the needs of the application. In this paper, we examine several kinds of algorithms presented over the last decades, with the main focus on particle sampling technologies for implicit surface. Therefore, we classify various algorithms into categories, describe main ideas behind each categories, and compare the advantages and shortcomings of the algorithms in each category.
基金Supported by the National Natural Science Foundation of China(42474239,41204128)China National Space Administration(Pre-research project on Civil Aerospace Technologies No.D010301)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA17010303)。
文摘One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.
基金Supported by the National Natural Science Foundation of China(12064028)Jiangxi Provincial Natural Science Foundation(20232BAB201045).
文摘Electro-Optic Sampling(EOS)detection technique has been widely used in terahertz science and tech⁃nology,and it also can measure the field time waveform of the few-cycle laser pulse.Its frequency response and band limitation are determined directly by the electro-optic crystal and duration of the probe laser pulse.Here,we investigate the performance of the EOS with thin GaSe crystal in the measurement of the mid-infrared few-cycle la⁃ser pulse.The shift of the central frequency and change of the bandwidth induced by the EOS detection are calcu⁃lated,and then the pulse distortions induced in this detection process are discussed.It is found that this technique produces a red-shift of the central frequency and narrowing of the bandwidth.These changings decrease when the laser wavelength increases from 2μm to 10μm.This work can help to estimate the performance of the EOS de⁃tection technique in the mid-infrared band and offer a reference for the related experiment as well.
文摘Critical Height Sampling(CHS)estimates stand volume free from any model and tree form assumptions.Despite its introduction more than four decades ago,CHS has not been widely applied in the field due to perceived challenges in measurement.The objectives of this study were to compare estimated stand volume between CHS and sampling methods that used volume or taper models,the equivalence of the sampling methods,and their relative efficiency.We established 65 field plots in planted forests of two coniferous tree species.We estimated stand volume for a range of Basal Area Factors(BAFs).Results showed that CHS produced the most similar mean stand volume across BAFs and tree species with maximum differences between BAFs of 5-18m^(3)·ha^(−1).Horizontal Point Sampling(HPS)using volume models produced very large variability in mean stand volume across BAFs with the differences up to 126m^(3)·ha^(−1).However,CHS was less precise and less efficient than HPS.Furthermore,none of the sampling methods were statistically interchangeable with CHS at an allowable tolerance of≤55m^(3)·ha^(−1).About 72%of critical height measurements were below crown base indicating that critical height was more accessible to measurement than expected.Our study suggests that the consistency in the mean estimates of CHS is a major advantage when planning a forest inventory.When checking against CHS,results hint that HPS estimates might contain potential model bias.These strengths of CHS could outweigh its lower precision.Our study also implies serious implications in financial terms when choosing a sampling method.Lastly,CHS could potentially benefit forest management as an alternate option of estimating stand volume when volume or taper models are lacking or are not reliable.
基金supported by the National Key R&D Program of China(Grant No.2022YFA1604200)National Natural Science Foundation of China(Grant No.12261131495)+1 种基金Beijing Municipal Science and Technology Commission,Adminitrative Commission of Zhongguancun Science Park(Grant No.Z231100006623006)Institute of Systems Science,Beijing Wuzi University(Grant No.BWUISS21)。
文摘Optical solitons,as self-sustaining waveforms in a nonlinear medium where dispersion and nonlinear effects are balanced,have key applications in ultrafast laser systems and optical communications.Physics-informed neural networks(PINN)provide a new way to solve the nonlinear Schrodinger equation describing the soliton evolution by fusing data-driven and physical constraints.However,the grid point sampling strategy of traditional PINN suffers from high computational complexity and unstable gradient flow,which makes it difficult to capture the physical details efficiently.In this paper,we propose a residual-based adaptive multi-distribution(RAMD)sampling method to optimize the PINN training process by dynamically constructing a multi-modal loss distribution.With a 50%reduction in the number of grid points,RAMD significantly reduces the relative error of PINN and,in particular,optimizes the solution error of the(2+1)Ginzburg–Landau equation from 4.55%to 1.98%.RAMD breaks through the lack of physical constraints in the purely data-driven model by the innovative combination of multi-modal distribution modeling and autonomous sampling control for the design of all-optical communication devices.RAMD provides a high-precision numerical simulation tool for the design of all-optical communication devices,optimization of nonlinear laser devices,and other studies.
