BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelations...BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelationship remains unclear.In this study,we applied a dual-trajectory model to assess how neck pain and emotional state evolve together over time and how clinical interventions,particularly acupuncture,influence these trajectories.AIM To investigate the longitudinal relationship between neck pain and emotional state in patients with cervical spondylosis.METHODS This prospective cohort study included 472 patients with cervical spondylosis from eight Chinese hospitals.Participants received acupuncture or medication and were followed up at baseline,and at 1,2,4,6,and 8 weeks.Neck pain and emotional distress were assessed using the Northwick Park Neck Pain Questionnaire(NPQ)and the affective subscale of the Short-Form McGill Pain Questionnaire(SF-MPQ),respectively.Group-based trajectory models and dual trajectory analysis were used to identify and correlate pain-emotion trajectories.Multivariate logistic regression identified predictors of group membership.RESULTS Three trajectory groups were identified for NPQ and SF-MPQ scores(low,medium,and high).Higher NPQ trajectory was associated with older age(OR=1.058,P<0.001)and was significantly reduced by acupuncture(OR=0.382,P<0.001).Similarly,acupuncture lowered the odds of high SF-MPQ trajectory membership(OR=0.336,P<0.001),while age increased it(OR=1.037,P<0.001).Dual-trajectory analysis revealed bidirectional associations:69.1%of patients with low NPQ had low SF-MPQ scores,and 42.6%of patients with high SF-MPQ also had high NPQ scores.Gender was a predictor for medium SF-MPQ trajectory(OR=1.629,P=0.094).Occupation and education levels differed significantly across the trajectory groups(P<0.05).CONCLUSION Over time,neck pain and emotional distress are closely associated in patients with cervical spondylosis.Acupuncture alleviates both outcomes significantly,while age is a risk factor.Integrated approaches to pain and emotional management are encouraged.展开更多
In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat...In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat’s launch speed,ejection direction,ejection angle,altitude of the aircraft,distance/height from the aircraft rudder and canopy,pilot and ejection seat weight.With the model algorithm proposed,the ejection seat trajectory model was developed on MATLAB.The ejection seat trajectory model is based on point mass trajectory mathematical model.In this study,an analytical study of the problem has been made for modeling the flight trajectory of the ejection seat after it has been ejected.Past studies were used as a basis for validation and simulation.By writing a generic MATLAB code,a user interface was developed and presented to the user as a module.This generic code that has been developed could be used for simulations by users in the future by revising it in accordance with their own job descriptions.展开更多
To accurately reconstruct the tomographic gamma scanning(TGS)transmission measurement image,this study optimized the transmission reconstruction equation based on the actual situation of TGS transmission measurement.U...To accurately reconstruct the tomographic gamma scanning(TGS)transmission measurement image,this study optimized the transmission reconstruction equation based on the actual situation of TGS transmission measurement.Using the transmission reconstruction equation and the Monte Carlo program Geant4,an innovative virtual trajectory length model was constructed.This model integrated the solving process for the trajectory length and detection efficiency within the same model.To mitigate the influence of the angular distribution ofγ-rays emitted by the transmitted source at the detector,the transport processes of numerous particles traversing a virtual nuclear waste barrel with a density of zero were simulated.Consequently,a certain amount of information was captured at each step of particle transport.Simultaneously,the model addressed the nonuniform detection efficiency of the detector end face by considering whether the energy deposition of particles in the detector equaled their initial energy.Two models were established to validate the accuracy and reliability of the virtual trajectory length model.Model 1 was a simplified nuclear waste barrel,whereas Model 2 closely resembled the actual structure of a nuclear waste barrel.The results indicated that the proposed virtual trajectory length model significantly enhanced the precision of the trajectory length determination,substantially increasing the quality of the reconstructed images.For example,the reconstructed images of Model 2 using the“point-to-point”and average trajectory models revealed a signalto-noise ratio increase of 375.0%and 112.7%,respectively.Thus,the virtual trajectory length model proposed in this study holds paramount significance for the precise reconstruction of transmission images.Moreover,it can provide support for the accurate detection of radioactive activity in nuclear waste barrels.展开更多
To mill fine and well-defined micro-dimpled structures,a machining manner of spiral trajectory tool reciprocating motion,where the tool repeats the process of‘feed milling–retract–cutting feed–feed milling again’...To mill fine and well-defined micro-dimpled structures,a machining manner of spiral trajectory tool reciprocating motion,where the tool repeats the process of‘feed milling–retract–cutting feed–feed milling again’along the spiral trajectory,was proposed.From the kinematics analysis,it is found that the machining quality of micro-dimpled structures is highly dependent on the machining trajectory using spiral trajectory tool reciprocating motion.To reveal this causation,simulation modelling and experimental studies were carried out.A simulation model was developed to quantitatively and qualitatively investigate the influence of the trajectory discretization strategies(constant-angle and constant-arc length)and parameters(discrete angle,discrete arc length,and pitch)on surface texture and residual height of micro-dimpled structures.Subsequently,micro-dimpled structures were milled under different trajectory discretization strategies and parameters with spiral trajectory tool reciprocating motion.A comprehensive comparison between the milled results and simulation analysis was made based on geometry accuracy,surface morphology and surface roughness of milled dimples.Meanwhile,the errors and factors affecting the above three aspects were analyzed.The results demonstrate both the feasibility of the established simulation model and the machining capability of this machining way in milling high-quality micro-dimpled structures.Spiral trajectory tool reciprocating motion provides a new machining way for milling micro-dimpled structures and micro-dimpled functional surfaces.And an appropriate machining trajectory can be generated based on the optimized trajectory parameters,thus contributing to the improvement of machining quality and efficiency.展开更多
Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The s...Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.展开更多
This paper studies the trajectory tracking problem of flapping-wing micro aerial vehicles(FWMAVs)in the longitudinal plane.First of all,the kinematics and dynamics of the FWMAV are established,wherein the aerodynamic ...This paper studies the trajectory tracking problem of flapping-wing micro aerial vehicles(FWMAVs)in the longitudinal plane.First of all,the kinematics and dynamics of the FWMAV are established,wherein the aerodynamic force and torque generated by flapping wings and the tail wing are explicitly formulated with respect to the flapping frequency of the wings and the degree of tail wing inclination.To achieve autonomous tracking,an adaptive control scheme is proposed under the hierarchical framework.Specifically,a bounded position controller with hyperbolic tangent functions is designed to produce the desired aerodynamic force,and a pitch command is extracted from the designed position controller.Next,an adaptive attitude controller is designed to track the extracted pitch command,where a radial basis function neural network is introduced to approximate the unknown aerodynamic perturbation torque.Finally,the flapping frequency of the wings and the degree of tail wing inclination are calculated from the designed position and attitude controllers,respectively.In terms of Lyapunov's direct method,it is shown that the tracking errors are bounded and ultimately converge to a small neighborhood around the origin.Simulations are carried out to verify the effectiveness of the proposed control scheme.展开更多
This is the first of a three-part series of pape rs which introduces a general background of building trajectory-oriented road net work data models, including motivation, related works, and basic concepts. The p urpos...This is the first of a three-part series of pape rs which introduces a general background of building trajectory-oriented road net work data models, including motivation, related works, and basic concepts. The p urpose of the series is to develop a trajectory-oriented road network data mode l, namely carriageway-based road network data model (CRNM). Part 1 deals with t he modeling background. Part 2 proposes the principle and architecture of the CR NM. Part 3 investigates the implementation of the CRNM in a case study. In the p resent paper, the challenges of managing trajectory data are discussed. Then, de veloping trajectory-oriented road network data models is proposed as a solution and existing road network data models are reviewed. Basic representation approa ches of a road network are introduced as well as its constitution.展开更多
In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from mo...In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network（NN）-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function（RBF） NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.展开更多
This is the second of a three-part series of papers which presents the principle and architecture of the CRNM, a trajectory-oriented, carriageway-based road network data model. The first part of the series has introdu...This is the second of a three-part series of papers which presents the principle and architecture of the CRNM, a trajectory-oriented, carriageway-based road network data model. The first part of the series has introduced a general background of building trajectory-oriented road network data models, including motivation, related works, and basic concepts. Based on it, this paper describs the CRNM in detail. At first, the notion of basic roadway entity is proposed and discussed. Secondly, carriageway is selected as the basic roadway entity after compared with other kinds of roadway, and approaches to representing other roadways with carriageways are introduced. At last, an overall architecture of the CRNM is proposed.展开更多
Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Cons...Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Considering that the motion trajectory of a vehicle at an intersection partly obeys the statistical law of historical data once its driving intention is determined,this paper proposes a long short-term memory based(LSTM-based)framework that combines intention prediction and trajectory prediction together.First,we build an intersection prior trajectories model(IPTM)by clustering and statistically analyzing a large number of prior traffic flow trajectories.The prior trajectories model with fitted probabilistic density is used to approximate the distribution of the predicted trajectory,and also serves as a reference for credibility evaluation.Second,we conduct the intention prediction through another LSTM model and regard it as a crucial cue for a trajectory forecast at the early stage.Furthermore,the predicted intention is also a key that is associated with the prior trajectories model.The proposed framework is validated on two publically released datasets,next generation simulation(NGSIM)and INTERACTION.Compared with other prediction methods,our framework is able to sample a trajectory from the estimated distribution,with its accuracy improved by about 20%.Finally,the credibility evaluation,which is based on the prior trajectories model,makes the framework more practical in the real-world applications.展开更多
A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC co...A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC controllers’performance in tracking predefined trajectory under different scenarios.MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire,which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode.RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison.Then,three test cases are built in CarSim-Simulink joint platform.Specifically,the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions.Besides,the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability.Furthermore,an extreme curve test is built where the road adhesion changes suddenly,in order to test the performance of both controllers under extreme conditions.Finally,the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.展开更多
This is the final of a three-part series of papers which mainly discusses the implementation issues of the CRNM. The first two papers in the series have introduced the modeling background and methodology, respectively...This is the final of a three-part series of papers which mainly discusses the implementation issues of the CRNM. The first two papers in the series have introduced the modeling background and methodology, respectively. An overall architecture of the CRNM has been proposed in the last paper. On the basis of the above discusses, a linear reference method (LRM) for providing spatial references for location points of a trajectory is developed. A case study is introduced to illustrate the application of the CRNM for modeling a road network in the real world is given. A comprehensive conclusion is given for the series of papers.展开更多
One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish au...One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish autonomous tasks. The characteristic model(CM) based all-coefficient adaptive control(ACAC) designed for PPF systems in horizontal and vertical trajectory control is proposed. The method is easy to use and convenient to adjust and test. Just a few parameters are adapted during the control process. In application, vertical and horizontal CMs are designed and ACAC controllers are constructed to control vertical altitude and horizontal trajectory of PPF based on the proposed CMs, respectively. Result analysis of different simulations shows that the applied ACAC control method is effective for trajectory tracking of the PPF systems and the approach guarantees the transient performance of the PPF systems with better disturbance rejection ability.展开更多
Human trajectory prediction is essential and promising in many related applications. This is challenging due to the uncertainty of human behaviors, which can be influenced not only by himself, but also by the surround...Human trajectory prediction is essential and promising in many related applications. This is challenging due to the uncertainty of human behaviors, which can be influenced not only by himself, but also by the surrounding environment. Recent works based on long-short term memory(LSTM) models have brought tremendous improvements on the task of trajectory prediction. However, most of them focus on the spatial influence of humans but ignore the temporal influence. In this paper, we propose a novel spatial-temporal attention(ST-Attention) model,which studies spatial and temporal affinities jointly. Specifically,we introduce an attention mechanism to extract temporal affinity,learning the importance for historical trajectory information at different time instants. To explore spatial affinity, a deep neural network is employed to measure different importance of the neighbors. Experimental results show that our method achieves competitive performance compared with state-of-the-art methods on publicly available datasets.展开更多
The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the laneexchanging scenario.The nearby vehicle trajectory needs to be predicted,from which the autonomous vehi...The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the laneexchanging scenario.The nearby vehicle trajectory needs to be predicted,from which the autonomous vehicle is controlled to prevent possible collisions.This paper proposes a lane-exchanging driving strategy for the autonomous vehicle to cooperate with the nearby vehicle by integrating vehicle trajectory prediction and motion control.A trajectory prediction method is developed to anticipate the nearby vehicle trajectory.The Gaussian mixture model(GMM),together with the vehicle kinematic model,are synthesized to predict the nearby vehicle trajectory.A potential-feldbased model predictive control(MPC)approach is utilized by the autonomous vehicle to conduct the lane-exchanging maneuver.The potential feld of the nearby vehicle is considered in the controller design for collision avoidance.On-road driving data verifcation shows that the nearby vehicle trajectory can be predicted by the proposed method.CarSim®simulations validate that the autonomous vehicle can perform the lane-exchanging maneuver and avoid the nearby vehicle using the proposed driving strategy.The autonomous vehicle can thus safely perform the laneexchanging maneuver and avoid the nearby vehicle.展开更多
Aircraft ground movement plays a key role in improving airport efficiency,as it acts as a link to all other ground operations.Finding novel approaches to coordinate the movements of a fleet of aircraft at an airport i...Aircraft ground movement plays a key role in improving airport efficiency,as it acts as a link to all other ground operations.Finding novel approaches to coordinate the movements of a fleet of aircraft at an airport in order to improve system resilience to disruptions with increasing autonomy is at the center of many key studies for airport airside operations.Moreover,autonomous taxiing is envisioned as a key component in future digitalized airports.However,state-of-the-art routing and scheduling algorithms for airport ground movements do not consider high-fidelity aircraft models at both the proactive and reactive planning phases.The majority of such algorithms do not actively seek to optimize fuel efficiency and reduce harmful greenhouse gas emissions.This paper proposes a new approach for generating efficient four-dimensional trajectories(4DTs)on the basis of a high-fidelity aircraft model and gainscheduling control strategy.Working in conjunction with a routing and scheduling algorithm that determines the taxi route,waypoints,and time deadlines,the proposed approach generates fuel-efficient 4DTs in real time,while respecting operational constraints.The proposed approach can be used in two contexts:①as a reactive decision support tool to generate new trajectories that can resolve unprecedented events;and②as an autopilot system for both partial and fully autonomous taxiing.The proposed methodology is realistic and simple to implement.Moreover,simulation studies show that the proposed approach is capable of providing an up to 11%reduction in the fuel consumed during the taxiing of a large Boeing 747-100 jumbo jet.展开更多
The movement of pedestrians involves temporal continuity,spatial interactivity,and random diversity.As a result,pedestrian trajectory prediction is rather challenging.Most existing trajectory prediction methods tend t...The movement of pedestrians involves temporal continuity,spatial interactivity,and random diversity.As a result,pedestrian trajectory prediction is rather challenging.Most existing trajectory prediction methods tend to focus on just one aspect of these challenges,ignoring the temporal information of the trajectory and making too many assumptions.In this paper,we propose a recurrent attention and interaction(RAI)model to predict pedestrian trajectories.The RAI model consists of a temporal attention module,spatial pooling module,and randomness modeling module.The temporal attention module is proposed to assign different weights to the input sequence of a target,and reduce the speed deviation of different pedestrians.The spatial pooling module is proposed to model not only the social information of neighbors in historical frames,but also the intention of neighbors in the current time.The randomness modeling module is proposed to model the uncertainty and diversity of trajectories by introducing random noise.We conduct extensive experiments on several public datasets.The results demonstrate that our method outperforms many that are state-ofthe-art.展开更多
A huge amount of sensitive personal data is being collected by various online health monitoring applications.Although the data is anonymous,the personal trajectories(e.g.,the chronological access records of small cell...A huge amount of sensitive personal data is being collected by various online health monitoring applications.Although the data is anonymous,the personal trajectories(e.g.,the chronological access records of small cells)could become the anchor of linkage attacks to re-identify the users.Focusing on trajectory privacy in online health monitoring,we propose the User Trajectory Model(UTM),a generic trajectory re-identification risk predicting model to reveal the underlying relationship between trajectory uniqueness and aggregated data(e.g.,number of individuals covered by each small cell),and using the parameter combination of aggregated data to further mathematically derive the statistical characteristics of uniqueness(i.e.,the expectation and the variance).Eventually,exhaustive simulations validate the effectiveness of the UTM in privacy risk evaluation,confirm our theoretical deductions and present counter-intuitive insights.展开更多
To deploy sensor nodes over the area of interest,a scheme,named node scattering manipulation,was proposed.It adopted the following method:during node scattering,the initial states of every node,including the velocity ...To deploy sensor nodes over the area of interest,a scheme,named node scattering manipulation,was proposed.It adopted the following method:during node scattering,the initial states of every node,including the velocity and direction,were manipulated so that it would land in a region with a certain probability;every sensor was relocated in order to improve the coverage and connectivity.Simultaneously,to easily analyze the process of scattering sensors,a trajectory model was also proposed.Integrating node scattering manipulation with trajectory model,the node deployment in wireless sensor network was thoroughly renovated,that is,this scheme can scatter sensors.In practice,the scheme was operable compared with the previous achievements.The simulation results demonstrate the superiority and feasibility of the scheme,and also show that the energy consumption for sensors relocation is reduced.展开更多
Wellbore instability is one of the concerns in the field of drilling engineering.This phenomenon is affected by several factors such as azimuth,inclination angle,in-situ stress,mud weight,and rock strength parameters....Wellbore instability is one of the concerns in the field of drilling engineering.This phenomenon is affected by several factors such as azimuth,inclination angle,in-situ stress,mud weight,and rock strength parameters.Among these factors,azimuth,inclination angle,and mud weight are controllable.The objective of this paper is to introduce a new procedure based on elastoplastic theory in wellbore stability solution to determine the optimum well trajectory and global minimum mud pressure required(GMMPR).Genetic algorithm(GA) was applied as a main optimization engine that employs proportional feedback controller to obtain the minimum mud pressure required(MMPR).The feedback function repeatedly calculated and updated the error between the simulated and set point of normalized yielded zone area(NYZA).To reduce computation expenses,an artificial neural network(ANN) was used as a proxy(surrogate model) to approximate the behavior of the actual wellbore model.The methodology was applied to a directional well in southwestern Iranian oilfield.The results demonstrated that the error between the predicted GMMPR and practical safe mud pressure was 4%for elastoplastic method,and 22%for conventional elastic solution.展开更多
基金Supported by 2022 Chinese Medicine Scientific Research Project of Hebei Administration of Traditional Chinese Medicine,No.20221572025 Annual Scientific Research Project of Higher Education Institutions in Hebei Province,No.QN2025654.
文摘BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelationship remains unclear.In this study,we applied a dual-trajectory model to assess how neck pain and emotional state evolve together over time and how clinical interventions,particularly acupuncture,influence these trajectories.AIM To investigate the longitudinal relationship between neck pain and emotional state in patients with cervical spondylosis.METHODS This prospective cohort study included 472 patients with cervical spondylosis from eight Chinese hospitals.Participants received acupuncture or medication and were followed up at baseline,and at 1,2,4,6,and 8 weeks.Neck pain and emotional distress were assessed using the Northwick Park Neck Pain Questionnaire(NPQ)and the affective subscale of the Short-Form McGill Pain Questionnaire(SF-MPQ),respectively.Group-based trajectory models and dual trajectory analysis were used to identify and correlate pain-emotion trajectories.Multivariate logistic regression identified predictors of group membership.RESULTS Three trajectory groups were identified for NPQ and SF-MPQ scores(low,medium,and high).Higher NPQ trajectory was associated with older age(OR=1.058,P<0.001)and was significantly reduced by acupuncture(OR=0.382,P<0.001).Similarly,acupuncture lowered the odds of high SF-MPQ trajectory membership(OR=0.336,P<0.001),while age increased it(OR=1.037,P<0.001).Dual-trajectory analysis revealed bidirectional associations:69.1%of patients with low NPQ had low SF-MPQ scores,and 42.6%of patients with high SF-MPQ also had high NPQ scores.Gender was a predictor for medium SF-MPQ trajectory(OR=1.629,P=0.094).Occupation and education levels differed significantly across the trajectory groups(P<0.05).CONCLUSION Over time,neck pain and emotional distress are closely associated in patients with cervical spondylosis.Acupuncture alleviates both outcomes significantly,while age is a risk factor.Integrated approaches to pain and emotional management are encouraged.
文摘In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat’s launch speed,ejection direction,ejection angle,altitude of the aircraft,distance/height from the aircraft rudder and canopy,pilot and ejection seat weight.With the model algorithm proposed,the ejection seat trajectory model was developed on MATLAB.The ejection seat trajectory model is based on point mass trajectory mathematical model.In this study,an analytical study of the problem has been made for modeling the flight trajectory of the ejection seat after it has been ejected.Past studies were used as a basis for validation and simulation.By writing a generic MATLAB code,a user interface was developed and presented to the user as a module.This generic code that has been developed could be used for simulations by users in the future by revising it in accordance with their own job descriptions.
基金supported by The Youth Science Foundation of Sichuan Province(Nos.2022NSFSC1230,2022NSFSC1231,and 23NSFSC5321)the Science and Technology Innovation Seedling Project of Sichuan Province(No.MZGC20230080)+2 种基金the General project of national Natural Science Foundation of China(No.12075039)the Youth Science Foundation of China(No.12105030)the Key project of the National Natural Science Foundation of China(No.U19A2086)。
文摘To accurately reconstruct the tomographic gamma scanning(TGS)transmission measurement image,this study optimized the transmission reconstruction equation based on the actual situation of TGS transmission measurement.Using the transmission reconstruction equation and the Monte Carlo program Geant4,an innovative virtual trajectory length model was constructed.This model integrated the solving process for the trajectory length and detection efficiency within the same model.To mitigate the influence of the angular distribution ofγ-rays emitted by the transmitted source at the detector,the transport processes of numerous particles traversing a virtual nuclear waste barrel with a density of zero were simulated.Consequently,a certain amount of information was captured at each step of particle transport.Simultaneously,the model addressed the nonuniform detection efficiency of the detector end face by considering whether the energy deposition of particles in the detector equaled their initial energy.Two models were established to validate the accuracy and reliability of the virtual trajectory length model.Model 1 was a simplified nuclear waste barrel,whereas Model 2 closely resembled the actual structure of a nuclear waste barrel.The results indicated that the proposed virtual trajectory length model significantly enhanced the precision of the trajectory length determination,substantially increasing the quality of the reconstructed images.For example,the reconstructed images of Model 2 using the“point-to-point”and average trajectory models revealed a signalto-noise ratio increase of 375.0%and 112.7%,respectively.Thus,the virtual trajectory length model proposed in this study holds paramount significance for the precise reconstruction of transmission images.Moreover,it can provide support for the accurate detection of radioactive activity in nuclear waste barrels.
基金co-supported the National Natural Science Foundation of China(No.52235010)the Heilongjiang Postdoctoral Fund(No.LBH-Z22136)the New Era Longjiang Excellent Master and Doctoral Dissertation Fund(No.LJYXL2022-057).
文摘To mill fine and well-defined micro-dimpled structures,a machining manner of spiral trajectory tool reciprocating motion,where the tool repeats the process of‘feed milling–retract–cutting feed–feed milling again’along the spiral trajectory,was proposed.From the kinematics analysis,it is found that the machining quality of micro-dimpled structures is highly dependent on the machining trajectory using spiral trajectory tool reciprocating motion.To reveal this causation,simulation modelling and experimental studies were carried out.A simulation model was developed to quantitatively and qualitatively investigate the influence of the trajectory discretization strategies(constant-angle and constant-arc length)and parameters(discrete angle,discrete arc length,and pitch)on surface texture and residual height of micro-dimpled structures.Subsequently,micro-dimpled structures were milled under different trajectory discretization strategies and parameters with spiral trajectory tool reciprocating motion.A comprehensive comparison between the milled results and simulation analysis was made based on geometry accuracy,surface morphology and surface roughness of milled dimples.Meanwhile,the errors and factors affecting the above three aspects were analyzed.The results demonstrate both the feasibility of the established simulation model and the machining capability of this machining way in milling high-quality micro-dimpled structures.Spiral trajectory tool reciprocating motion provides a new machining way for milling micro-dimpled structures and micro-dimpled functional surfaces.And an appropriate machining trajectory can be generated based on the optimized trajectory parameters,thus contributing to the improvement of machining quality and efficiency.
基金supported by the Key Research and Development Program of the Ministry of Science and Technology of China(grant number:2016YF0900605)the Key Research and Development Program of Hebei Province(grant number:192777129D)+1 种基金the Joint Fund for Iron and Steel of the Natural Science Foundation of Hebei Province(grant number:H2016209058)the National Natural Science Foundation for Regional Joint Fund of China(grant number:U22A20364)。
文摘Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.
基金supported in part by the National Natural Science Foundation of China(61933001,62061160371)Joint Funds of Equipment Pre-Research and Ministry of Education of China(6141A02033339)Beijing Top Discipline for Artificial Intelligent Science and Engineering,University of Science and Technology Beijing。
文摘This paper studies the trajectory tracking problem of flapping-wing micro aerial vehicles(FWMAVs)in the longitudinal plane.First of all,the kinematics and dynamics of the FWMAV are established,wherein the aerodynamic force and torque generated by flapping wings and the tail wing are explicitly formulated with respect to the flapping frequency of the wings and the degree of tail wing inclination.To achieve autonomous tracking,an adaptive control scheme is proposed under the hierarchical framework.Specifically,a bounded position controller with hyperbolic tangent functions is designed to produce the desired aerodynamic force,and a pitch command is extracted from the designed position controller.Next,an adaptive attitude controller is designed to track the extracted pitch command,where a radial basis function neural network is introduced to approximate the unknown aerodynamic perturbation torque.Finally,the flapping frequency of the wings and the degree of tail wing inclination are calculated from the designed position and attitude controllers,respectively.In terms of Lyapunov's direct method,it is shown that the tracking errors are bounded and ultimately converge to a small neighborhood around the origin.Simulations are carried out to verify the effectiveness of the proposed control scheme.
文摘This is the first of a three-part series of pape rs which introduces a general background of building trajectory-oriented road net work data models, including motivation, related works, and basic concepts. The p urpose of the series is to develop a trajectory-oriented road network data mode l, namely carriageway-based road network data model (CRNM). Part 1 deals with t he modeling background. Part 2 proposes the principle and architecture of the CR NM. Part 3 investigates the implementation of the CRNM in a case study. In the p resent paper, the challenges of managing trajectory data are discussed. Then, de veloping trajectory-oriented road network data models is proposed as a solution and existing road network data models are reviewed. Basic representation approa ches of a road network are introduced as well as its constitution.
基金supported by National Basic Research and Development Program of China (973 Program, Grant No. 2006CB705402)
文摘In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network（NN）-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function（RBF） NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.
文摘This is the second of a three-part series of papers which presents the principle and architecture of the CRNM, a trajectory-oriented, carriageway-based road network data model. The first part of the series has introduced a general background of building trajectory-oriented road network data models, including motivation, related works, and basic concepts. Based on it, this paper describs the CRNM in detail. At first, the notion of basic roadway entity is proposed and discussed. Secondly, carriageway is selected as the basic roadway entity after compared with other kinds of roadway, and approaches to representing other roadways with carriageways are introduced. At last, an overall architecture of the CRNM is proposed.
基金partly supported by the National Natural Science Foundation of China(61903034,U1913203,61973034,91120003)the Program for Changjiang Scholars and Innovative Research Team in University(IRT-16R06,T2014224)+1 种基金China Postdoctoral Science Foundation funded project(2019TQ0035)Beijing Institute of Technology Research Fund Program for Young Scholars。
文摘Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Considering that the motion trajectory of a vehicle at an intersection partly obeys the statistical law of historical data once its driving intention is determined,this paper proposes a long short-term memory based(LSTM-based)framework that combines intention prediction and trajectory prediction together.First,we build an intersection prior trajectories model(IPTM)by clustering and statistically analyzing a large number of prior traffic flow trajectories.The prior trajectories model with fitted probabilistic density is used to approximate the distribution of the predicted trajectory,and also serves as a reference for credibility evaluation.Second,we conduct the intention prediction through another LSTM model and regard it as a crucial cue for a trajectory forecast at the early stage.Furthermore,the predicted intention is also a key that is associated with the prior trajectories model.The proposed framework is validated on two publically released datasets,next generation simulation(NGSIM)and INTERACTION.Compared with other prediction methods,our framework is able to sample a trajectory from the estimated distribution,with its accuracy improved by about 20%.Finally,the credibility evaluation,which is based on the prior trajectories model,makes the framework more practical in the real-world applications.
基金Supported by Natural Science Foundation of China(Grant Nos.52072051,51705044)Chongqing Municipal Natural Science Foundation of China(Grant No.cstc2020jcyj-msxmX0956)+1 种基金State Key Laboratory of Mechanical System and Vibration(Grant No.MSV202016)State Key Laboratory of Mechanical Transmissions(Grant No.SKLMT-KFKT-201806).
文摘A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC controllers’performance in tracking predefined trajectory under different scenarios.MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire,which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode.RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison.Then,three test cases are built in CarSim-Simulink joint platform.Specifically,the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions.Besides,the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability.Furthermore,an extreme curve test is built where the road adhesion changes suddenly,in order to test the performance of both controllers under extreme conditions.Finally,the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.
文摘This is the final of a three-part series of papers which mainly discusses the implementation issues of the CRNM. The first two papers in the series have introduced the modeling background and methodology, respectively. An overall architecture of the CRNM has been proposed in the last paper. On the basis of the above discusses, a linear reference method (LRM) for providing spatial references for location points of a trajectory is developed. A case study is introduced to illustrate the application of the CRNM for modeling a road network in the real world is given. A comprehensive conclusion is given for the series of papers.
基金Project(61273138)supported by the National Natural Science Foundation of ChinaProject(14JCZDJC39300)supported by the Key Fund of Tianjin,China
文摘One of the primary difficulties in using powered parafoil(PPF) systems is the lack of effective trajectory tracking controllers since the trajectory tracking control is the essential operation for PPF to accomplish autonomous tasks. The characteristic model(CM) based all-coefficient adaptive control(ACAC) designed for PPF systems in horizontal and vertical trajectory control is proposed. The method is easy to use and convenient to adjust and test. Just a few parameters are adapted during the control process. In application, vertical and horizontal CMs are designed and ACAC controllers are constructed to control vertical altitude and horizontal trajectory of PPF based on the proposed CMs, respectively. Result analysis of different simulations shows that the applied ACAC control method is effective for trajectory tracking of the PPF systems and the approach guarantees the transient performance of the PPF systems with better disturbance rejection ability.
基金supported by the National Key Research and Development Program of China(2018AAA0101005,2018AAA0102404)the Program of the Huawei Technologies Co.Ltd.(FA2018111061SOW12)+1 种基金the National Natural Science Foundation of China(61773054)the Youth Research Fund of the State Key Laboratory of Complex Systems Management and Control(20190213)。
文摘Human trajectory prediction is essential and promising in many related applications. This is challenging due to the uncertainty of human behaviors, which can be influenced not only by himself, but also by the surrounding environment. Recent works based on long-short term memory(LSTM) models have brought tremendous improvements on the task of trajectory prediction. However, most of them focus on the spatial influence of humans but ignore the temporal influence. In this paper, we propose a novel spatial-temporal attention(ST-Attention) model,which studies spatial and temporal affinities jointly. Specifically,we introduce an attention mechanism to extract temporal affinity,learning the importance for historical trajectory information at different time instants. To explore spatial affinity, a deep neural network is employed to measure different importance of the neighbors. Experimental results show that our method achieves competitive performance compared with state-of-the-art methods on publicly available datasets.
基金Supported by Project of National Natural Science Foundation of China(Grand No.52102469)Science and Technology Major Project of Guangxi(Grant Nos.AB21196029 and AA18242033)State Key Laboratory of Automotive Safety and Energy(Grant No.KF2014).
文摘The cooperation between an autonomous vehicle and a nearby vehicle is critical to ensure driving safety in the laneexchanging scenario.The nearby vehicle trajectory needs to be predicted,from which the autonomous vehicle is controlled to prevent possible collisions.This paper proposes a lane-exchanging driving strategy for the autonomous vehicle to cooperate with the nearby vehicle by integrating vehicle trajectory prediction and motion control.A trajectory prediction method is developed to anticipate the nearby vehicle trajectory.The Gaussian mixture model(GMM),together with the vehicle kinematic model,are synthesized to predict the nearby vehicle trajectory.A potential-feldbased model predictive control(MPC)approach is utilized by the autonomous vehicle to conduct the lane-exchanging maneuver.The potential feld of the nearby vehicle is considered in the controller design for collision avoidance.On-road driving data verifcation shows that the nearby vehicle trajectory can be predicted by the proposed method.CarSim®simulations validate that the autonomous vehicle can perform the lane-exchanging maneuver and avoid the nearby vehicle using the proposed driving strategy.The autonomous vehicle can thus safely perform the laneexchanging maneuver and avoid the nearby vehicle.
基金This work was funded by the UK Engineering and Physical Sciences Research Council(EP/N029496/1,EP/N029496/2,EP/N029356/1,EP/N029577/1,and EP/N029577/2).
文摘Aircraft ground movement plays a key role in improving airport efficiency,as it acts as a link to all other ground operations.Finding novel approaches to coordinate the movements of a fleet of aircraft at an airport in order to improve system resilience to disruptions with increasing autonomy is at the center of many key studies for airport airside operations.Moreover,autonomous taxiing is envisioned as a key component in future digitalized airports.However,state-of-the-art routing and scheduling algorithms for airport ground movements do not consider high-fidelity aircraft models at both the proactive and reactive planning phases.The majority of such algorithms do not actively seek to optimize fuel efficiency and reduce harmful greenhouse gas emissions.This paper proposes a new approach for generating efficient four-dimensional trajectories(4DTs)on the basis of a high-fidelity aircraft model and gainscheduling control strategy.Working in conjunction with a routing and scheduling algorithm that determines the taxi route,waypoints,and time deadlines,the proposed approach generates fuel-efficient 4DTs in real time,while respecting operational constraints.The proposed approach can be used in two contexts:①as a reactive decision support tool to generate new trajectories that can resolve unprecedented events;and②as an autopilot system for both partial and fully autonomous taxiing.The proposed methodology is realistic and simple to implement.Moreover,simulation studies show that the proposed approach is capable of providing an up to 11%reduction in the fuel consumed during the taxiing of a large Boeing 747-100 jumbo jet.
基金supported by the National NaturalScience Foundation of China(U1811463)the Fundamental Research Funds for the Central Universities(12060093192)。
文摘The movement of pedestrians involves temporal continuity,spatial interactivity,and random diversity.As a result,pedestrian trajectory prediction is rather challenging.Most existing trajectory prediction methods tend to focus on just one aspect of these challenges,ignoring the temporal information of the trajectory and making too many assumptions.In this paper,we propose a recurrent attention and interaction(RAI)model to predict pedestrian trajectories.The RAI model consists of a temporal attention module,spatial pooling module,and randomness modeling module.The temporal attention module is proposed to assign different weights to the input sequence of a target,and reduce the speed deviation of different pedestrians.The spatial pooling module is proposed to model not only the social information of neighbors in historical frames,but also the intention of neighbors in the current time.The randomness modeling module is proposed to model the uncertainty and diversity of trajectories by introducing random noise.We conduct extensive experiments on several public datasets.The results demonstrate that our method outperforms many that are state-ofthe-art.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61871062and Grant 61771082the Natural Science Foundation of Chongqing of China under Grant cstc2013jcyjA40066+3 种基金the Program for Innovation Team Building at Institutions of Higher Education in Chongqing under Grant CXTDX201601020the Science and Technology Research Program of Chongqing Municipal Education Commission under Grant KJQN201801316the Key Industrial Technology Development Project of Chongqing of China Development and Reform Commission under Grant 2018148208the Innovation and Entrepreneurship Demonstration Team of Yingcai Program of Chongqing of China under Grant CQYC201903167.
文摘A huge amount of sensitive personal data is being collected by various online health monitoring applications.Although the data is anonymous,the personal trajectories(e.g.,the chronological access records of small cells)could become the anchor of linkage attacks to re-identify the users.Focusing on trajectory privacy in online health monitoring,we propose the User Trajectory Model(UTM),a generic trajectory re-identification risk predicting model to reveal the underlying relationship between trajectory uniqueness and aggregated data(e.g.,number of individuals covered by each small cell),and using the parameter combination of aggregated data to further mathematically derive the statistical characteristics of uniqueness(i.e.,the expectation and the variance).Eventually,exhaustive simulations validate the effectiveness of the UTM in privacy risk evaluation,confirm our theoretical deductions and present counter-intuitive insights.
基金Project(2007AA01Z224) supported by National High-Tech Research and Development Program of China
文摘To deploy sensor nodes over the area of interest,a scheme,named node scattering manipulation,was proposed.It adopted the following method:during node scattering,the initial states of every node,including the velocity and direction,were manipulated so that it would land in a region with a certain probability;every sensor was relocated in order to improve the coverage and connectivity.Simultaneously,to easily analyze the process of scattering sensors,a trajectory model was also proposed.Integrating node scattering manipulation with trajectory model,the node deployment in wireless sensor network was thoroughly renovated,that is,this scheme can scatter sensors.In practice,the scheme was operable compared with the previous achievements.The simulation results demonstrate the superiority and feasibility of the scheme,and also show that the energy consumption for sensors relocation is reduced.
文摘Wellbore instability is one of the concerns in the field of drilling engineering.This phenomenon is affected by several factors such as azimuth,inclination angle,in-situ stress,mud weight,and rock strength parameters.Among these factors,azimuth,inclination angle,and mud weight are controllable.The objective of this paper is to introduce a new procedure based on elastoplastic theory in wellbore stability solution to determine the optimum well trajectory and global minimum mud pressure required(GMMPR).Genetic algorithm(GA) was applied as a main optimization engine that employs proportional feedback controller to obtain the minimum mud pressure required(MMPR).The feedback function repeatedly calculated and updated the error between the simulated and set point of normalized yielded zone area(NYZA).To reduce computation expenses,an artificial neural network(ANN) was used as a proxy(surrogate model) to approximate the behavior of the actual wellbore model.The methodology was applied to a directional well in southwestern Iranian oilfield.The results demonstrated that the error between the predicted GMMPR and practical safe mud pressure was 4%for elastoplastic method,and 22%for conventional elastic solution.
