Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has d...Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has driven continuous upgrading and optimization of intelligent train control technology,thanks to its enhanced computational capabilities derived from advanced algorithms and models,as well as its role in improving safety performance.Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale.It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology,elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.Findings–The application of AI technology in the train driving and control field is still in its infancy.While a large number of AI technologies have been widely adopted,there remains significant room for further optimization and improvement of these technologies.Additionally,a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.Originality/value–The research findings provide references and guidance for advancing train control technology,promoting the digital transformation of railways,accelerating the overall optimization and upgrading of railway industry technologies,and facilitating the accelerated development of global railways.展开更多
This paper reports a case of cerebral stem infarction with quadriplegia and complete dependence on daily life.The course of the disease lasted more than 7 months.Frenchay's improved articulation Disorder Assessmen...This paper reports a case of cerebral stem infarction with quadriplegia and complete dependence on daily life.The course of the disease lasted more than 7 months.Frenchay's improved articulation Disorder Assessment Form has been assessed as severe articulation disorder.The patient has significantly improved his speech function and quality of life after systematic head control training,respiratory function training,articulation motor training,and articulation training.In the course of treatment,emphasis was placed on head postural control training and respiratory function training,and emphasis was placed on the strength and coordination training of articulatory organs,and the results were remarkable.After the patient was discharged from the hospital,the follow-up of basic daily life communication was not limited.展开更多
With the integration of informatization and intelligence into the Communication-Based Train Control(CBTC)systems,the system is facing an increasing number of information security threats.As an important method of char...With the integration of informatization and intelligence into the Communication-Based Train Control(CBTC)systems,the system is facing an increasing number of information security threats.As an important method of characterizing the system security status,the security situation assessment is used to analyze the system security situation.However,existing situation assessment methods fail to integrate the coupling relationship between the physical layer and the information layer of the CBTC systems,and cannot dynamically characterize the real-time security situation changes under cyber attacks.In this paper,a hierarchical security situation assessment approach is proposed to address the security challenges of CBTC systems,which can perceive cyber attacks,quantify the security situation,and characterize the security situation changes under cyber attacks.Specifically,for the physical layer ofCBTC systems,the impact of cyber attacks is evaluated with the train punctuality rate and train departure interval indicators.For the information layer of CBTC systems,the system vulnerabilities and system threats are selected as static level indicators,and the critical network characteristics are selected as dynamic level indicators to quantify the real-time security situation.Finally,the comprehensive security situation assessment value of the CBTC systems is obtained by integrating the physical and information layer indicators.Simulation results illustrate that the proposed approach can dynamically characterize the real-time security situation of CBTC systems,enhancing the ability to perceive and assess information security risks.展开更多
Background Evidence on the effects of different exercise interventions on cognitive function is insufficient.Aims To evaluate the feasibility and effects of remotely supervised aerobic exercise(AE)and resistance exerc...Background Evidence on the effects of different exercise interventions on cognitive function is insufficient.Aims To evaluate the feasibility and effects of remotely supervised aerobic exercise(AE)and resistance exercise(RE)interventions in older adults with mild cognitive impairment(MCI).Methods This study is a 6-month pilot three-arm randomised controlled trial.Eligible participants(n=108)were recruited and randomised to the AE group,RE group or control(CON)group with a 1:1:1 ratio.Interventions were delivered at home with remote supervision.We evaluated participants’global cognition,memory,executive function,attention,physical activity levels,physical performance and muscle strength of limbs at baseline,3 months(T1)and 6 months(T2)after randomisation.A linear mixed-effects model was adopted for data analyses after controlling for covariates.Tukey’s method was used for adjusting for multiple comparisons.Sensitivity analyses were performed after excluding individuals with low compliance rates.Results 15(13.89%)participants dropped out.The median compliance rates in the AE group and RE group were 67.31%and 93.27%,respectively.After adjusting for covariates,the scores of the Alzheimer’s Disease Assessment Scale-Cognitive subscale in the AE group decreased by 2.04(95%confidence interval(CI)−3.41 to−0.67,t=−2.94,p=0.004)and 1.53(95%CI−2.88 to−0.17,t=−2.22,p=0.028)points more than those in the CON group at T1 and T2,respectively.The effects of AE were still significant at T1(estimate=−1.70,95%CI−3.20 to−0.21,t=−2.69,p=0.021),but lost statistical significance at T2 after adjusting for multiple comparisons.As for executive function,the Stroop time interference in the RE group decreased by 11.76 s(95%CI−21.62 to−1.90,t=−2.81,p=0.015)more than that in the AE group at T2 after Tukey’s adjustment.No other significant effects on cognitive functions were found.Conclusions Both remotely supervised AE and RE programmes are feasible in older adults with MCI.AE has positive effects on global cognition,and RE improves executive function.展开更多
The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calcula...The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.展开更多
Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these...Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface electromyography.In this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord injury.Eleven patients with chronic complete thoracic spinal cord injury were recruited.Surface electromyography data from eight major leg muscles were acquired and compared before and after the passive activity protocol.The results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of activation.Although the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically significant.These findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.展开更多
The reduction of energy consumption is an increasingly important topic of the railway system.Energy-efficient train control(EETC)is one solution,which refers to mathematically computing when to accelerate,which cruisi...The reduction of energy consumption is an increasingly important topic of the railway system.Energy-efficient train control(EETC)is one solution,which refers to mathematically computing when to accelerate,which cruising speed to hold,how long one should coast over a suitable space,and when to brake.Most approaches in literature and industry greatly simplify a lot of nonlinear effects,such that they ignore mostly the losses due to energy conversion in traction components and auxiliaries.To fill this research gap,a series of increasingly detailed nonlinear losses is described and modelled.We categorize an increasing detail in this representation as four levels.We study the impact of those levels of detail on the energy optimal speed trajectory.To do this,a standard approach based on dynamic programming is used,given constraints on total travel time.This evaluation of multiple test cases highlights the influence of the dynamic losses and the power consumption of auxiliary components on railway trajectories,also compared to multiple benchmarks.The results show how the losses can make up 50%of the total energy consumption for an exemplary trip.Ignoring them would though result in consistent but limited errors in the optimal trajectory.Overall,more complex trajectories can result in less energy consumption when including the complexity of nonlinear losses than when a simpler model is considered.Those effects are stronger when the trajectory includes many acceleration and braking phases.展开更多
软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一...软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一种基于时差的多输出tri-training异构软测量方法。通过构建一种新的tri-training框架,采用多输出的高斯过程回归(multi-output Gaussian process regression,MGPR)、相关向量机(multi-output relevance vector machine,MRVM)、最小二乘支持向量机(multi-output least squares support vector machine,MLSSVM)三种模型作为基线监督回归器,使用标记数据进行训练和迭代;同时,引入时间差分(time difference,TD)改进模型的动态特性,并通过卡尔曼滤波(Kalman filtering,KF)优化模型的参数,提高其预测性能;最后通过模拟污水处理平台(benchmark simulation model 1,BSM1)和实际污水处理厂对该模型进行了验证。结果表明,与传统的软测量建模方法相比,该模型能显著提高数据分布不平衡下软测量模型的自适应性和预测性能。展开更多
Magnetic levitation control technology plays a significant role in maglev trains.Designing a controller for the levitation system is challenging due to the strong nonlinearity,open-loop instability,and the need for fa...Magnetic levitation control technology plays a significant role in maglev trains.Designing a controller for the levitation system is challenging due to the strong nonlinearity,open-loop instability,and the need for fast response and security.In this paper,we propose a Disturbance-Observe-based Tube Model Predictive Levitation Control(DO-TMPLC)scheme combined with a feedback linearization strategy for the levitation system.The proposed strategy incorporates state constraints and control input constraints,i.e.,the air gap,the vertical velocity,and the current applied to the coil.A feedback linearization strategy is used to cancel the nonlinearity of the tracking error system.Then,a disturbance observer is implemented to actively compensate for disturbances while a TMPLC controller is employed to alleviate the remaining disturbances.Furthermore,we analyze the recursive feasibility and input-to-state stability of the closed-loop system.The simulation results indicate the efficacy of the proposed control strategy.展开更多
Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’bala...Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’balance function and gait.Methods:Fifty-two cases of hemiplegic stroke patients were randomly divided into two groups,26 in the control group and 26 in the observation group,using computer-generated random grouping.All participants underwent conventional treatment and rehabilitation training.In addition to these,the control group received repetitive transcranial magnetic pseudo-stimulation therapy+motor control training,while the observation group received repetitive transcranial magnetic stimulation therapy+motor control training.The balance function and gait parameters of both groups were compared before and after the interventions and assessed the satisfaction of the interventions in both groups.Results:Before the invention,there were no significant differences in balance function scores and each gait parameter between the two groups(P>0.05).However,after the intervention,the observation group showed higher balance function scores compared to the control group(P<0.05).The observation group also exhibited higher step speed and step frequency,longer step length,and a higher overall satisfaction level with the intervention compared to the control group(P<0.05).Conclusion:The combination of repetitive transcranial magnetic stimulation and motor control training in the treatment of stroke-induced hemiplegia has demonstrated positive effects.It not only improves the patient’s balance function and gait but also contributes to overall physical rehabilitation.展开更多
Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The gr...Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The growing threat to information security posed by spoofing attacks has received limited attention.This study investigates the impact of GNSS spoofing attacks on train positioning,emphasizing their detrimental effects on the accuracy and availability of train location report functions for train operation control.To explore the antispoofing performance of typical GNSS-based train positioning schemes,specific approaches,and system architectures are designed under two GNSS-alone and two GNSS-integrated train positioning schemes.Field data are utilized to establish spoofing attack scenarios for GNSS-based train positioning,with which the anti-spoofing capabilities of different train positioning schemes are evaluated.Experimental results indicate that under specific conditions,the GNSS-integrated positioning schemes demonstrate superior GNSS spoofing suppression capabilities.Results of the tests present valuable guidance for designers and manufacturers in developing more advanced and resilient train positioning solutions and equipment for the next generation of train control systems,thereby promoting the applications of GNSS technology in railway systems.展开更多
In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based po...In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.展开更多
Objective:In the Radiology Department of Mzuzu Central Hospital(MCH),daily training for radiographers now includes content on Computed Tomography(CT)image quality control and equipment maintenance to ensure the normal...Objective:In the Radiology Department of Mzuzu Central Hospital(MCH),daily training for radiographers now includes content on Computed Tomography(CT)image quality control and equipment maintenance to ensure the normal,continuous,and stable operation of the 16-slice spiral CT scanner.Methods:Through comprehensive analysis of relevant equipment,we have identified key parameters that significantly impact CT image quality.Innovative optimization strategies and solutions targeting these parameters have been developed and integrated into daily training programs.Furthermore,starting from an examination of prevalent failure modes observed in CT equipment,we delve into essential maintenance and preservation techniques that CT technologists must master to ensure optimal system performance.Results:(1)Crucial factors affecting CT image quality include artifacts,noise,partial volume effects,and surrounding gap phenomena,alongside spatial and density resolutions,CT dose,reconstruction algorithms,and human factors during the scanning process.In the daily training for radiographers,emphasis is placed on strictly implementing image quality control measures at every stage of the CT scanning process and skillfully applying advanced scanning and image processing techniques.By doing so,we can provide clinicians with accurate and reliable imaging references for diagnosis and treatment.(2)Strategies for CT equipment maintenance:①Environmental inspection of the CT room to ensure cleanliness and hygiene.②Rational and accurate operation,including calibration software proficiency.③Regular maintenance and servicing for minimizing machine downtime.④Maintenance of the CT X-ray tube.CT technicians can become proficient in equipment maintenance and upkeep techniques through training,which can significantly extend the service life of CT systems and reduce the occurrence of malfunctions.Conclusion:Through the regular implementation of rigorous CT image quality control training for radiology technicians,coupled with diligent and proactive CT equipment maintenance,we have observed profound and beneficial impacts on improving image quality.The accuracy and fidelity of radiological data ultimately leads to more accurate diagnoses and effective treatments.展开更多
This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the tem...This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the temporary speed limit on the railway line and the communication delay between trains,and it uses a VCTS consisting of three trains as an experimental object.It creates the virtual coupling train tracking and control process by improving the driving strategy of the leader train and using the leader-follower model.The follower train uses the improved speed curve of the leader train as its speed refer-ence curve through knowledge migration,and this completes the multi-objective optimization of the driving strategy for the VCTS.The experimental results confirm that the deep reinforcement learning algorithm effectively achieves the optimization goal of the train driving strategy.They also reveal that the intrinsic curiosity module prioritized experience replay dueling double deep Q-network(ICM-PER-D3QN)algorithm outperforms the deep Q-network(DQN)algorithm in optimizing the driving strategy of the leader train.The ICM-PER-D3QN algorithm enhances the leader train driving strategy by an average of 57%when compared to the DQN algorithm.Furthermore,the particle swarm optimization(PSO)-based model predictive control(MPC)algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation,with an average increase of 37.7%in tracking accuracy compared to the traditional MPC algorithm.展开更多
With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powere...With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powered aerobics training robot featuring an adaptive energy management system designed for sustainability and efficiency.The robot integrates machine vision with an enhanced Dynamic Cheetah Optimizer and Bayesian Neural Network(DynCO-BNN)to enable precise exercise monitoring and real-time feedback.Solar tracking technology ensures optimal energy absorption,while a microcontroller-based regulator manages power distribution and robotic movement.Dual-battery switching ensures uninterrupted operation,aided by light and I/V sensors for energy optimization.Using the INSIGHT-LME IMU dataset,which includes motion data from 76 individuals performing Local Muscular Endurance(LME)exercises,the system detects activities,counts repetitions,and recognizes human movements.To minimize energy use during data processing,Min-Max normalization and two-dimensional Discrete Fourier Transform(2D-DFT)are applied,boosting computational efficiency.The robot accurately identifies upper and lower limb movements,delivering effective exercise guidance.The DynCO-BNN model achieved a high tracking accuracy of 96.8%.Results confirm improved solar utilization,ecological sustainability,and reduced dependence on fossil fuels—positioning the robot as a smart,energy-efficient solution for next-generation fitness technology.展开更多
This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,...This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,China.Based on randomly generated 40 NTDs,the study developed models for the geologic hazard susceptibility assessment using the random forest algorithm and evaluated their performances using the area under the receiver operating characteristic curve(AUC).Specifically,the means and standard deviations of the AUC values from all models were then utilized to assess the overall spatial correlation between the conditioning factors and the susceptibility assessment,as well as the uncertainty introduced by the NTDs.A risk and return methodology was thus employed to quantify and mitigate the uncertainty,with log odds ratios used to characterize the susceptibility assessment levels.The risk and return values were calculated based on the standard deviations and means of the log odds ratios of various locations.After the mean log odds ratios were converted into probability values,the final susceptibility map was plotted,which accounts for the uncertainty induced by random NTDs.The results indicate that the AUC values of the models ranged from 0.810 to 0.963,with an average of 0.852 and a standard deviation of 0.035,indicating encouraging prediction effects and certain uncertainty.The risk and return analysis reveals that low-risk and high-return areas suggest lower standard deviations and higher means across multiple model-derived assessments.Overall,this study introduces a new framework for quantifying the uncertainty of multiple training and evaluation models,aimed at improving their robustness and reliability.Additionally,by identifying low-risk and high-return areas,resource allocation for geologic hazard prevention and control can be optimized,thus ensuring that limited resources are directed toward the most effective prevention and control measures.展开更多
Objective To observe the clinical efficacy of acupuncture combined with speech rehabilitation training for post-stroke spasmodic dysphonia and compare the differences in efficacy among the therapy of acupuncture combi...Objective To observe the clinical efficacy of acupuncture combined with speech rehabilitation training for post-stroke spasmodic dysphonia and compare the differences in efficacy among the therapy of acupuncture combined with speech rehabilitation training and the monotherapy.Methods Two hundred and seventy cases of patients with post-stroke spasmodic dysarthria were randomly divided into three groups with the ratio of 1：1：1.Group A：acupuncture combined with speech rehabilitation training group（90 cases）,group B：acupuncture group（90 cases）,group C：speech rehabilitation training group（90 cases）.In the group B,acupuncture treatment was given at Baihui（百会 GV 20）,JTnjin（金津 EX-HN 12） and Yuye（玉液 EX-HN13） as well as tongue-three needles.In the group C,the treatment of speech rehabilitation training was provided.The two treatments mentioned above were combined in the group A.Patients were treated once a day for a month with improved Frenchay dysarthria rating scale as the indices of therapeutic effect evaluation.Results ① Group A：the cured and markedly effective rate was 88.7%,and total effective rate was 94.3%;group B：the cured and markedly effective rate was 44.2%and total effective rate was 81.4%;group C：the cured and markedly effective rate was 23.5%and total effective rate was 61.2%.Both the cured and markedly effective rate and the total effective rate in the group A were significantly higher than those in the group B or group C（all P0.05）;both the cured and markedly effective rate and the total effective rate in the group B were higher than those of group C（both P0.05）;② In comparison of functional recovery of tongue in accordance with the Frenchay dysarthria rating scale,the recovery rate of the tongue-stationary state was 71.74%in the group A,18.87%in the group B and 4.44%in the group C;the recovery rate of tongue lolling out was 66.23%in the group A,27.63%in the group B and 1.59%in the group C;the recovery rate of tongue up and down motion was 44.19%in the group A,4.94%in the group B and 1.35%in the group C;the recovery rate of lateral motion was 40.24%in the group A,7.59%in the group B and 0.00%in the group C;the recovery rate of alternating motion was 29.07%in the group A,7.14%in the group B and 1.23%in the group C;the recovery rate of speech was 29.07%in the group A,5.88%in the group B and 1.22%in the group C.In the three groups,the recovery rates of stationary state and tongue lolling out were superior to those of up and down movement,lateral movement,alternating movement and speech（all P0.05）.Conclusion The clinical efficacy of acupuncture combined with speech rehabilitation training for patients with post-stroke spasmodic dysarthria is significant,and the efficacy of acupuncture is superior to that of speech rehabilitation training;as for functional recovery of tongue like stationary state and tongue out,the therapy of acupuncture combined with speech rehabilitation training is effective.展开更多
This paper proposes cooperative adaptive control schemes for a train platoon to improve efficient utility and guarantee string stability. The control schemes are developed based on a bidirectional strategy, i.e., the ...This paper proposes cooperative adaptive control schemes for a train platoon to improve efficient utility and guarantee string stability. The control schemes are developed based on a bidirectional strategy, i.e., the information of proximal（preceding and following） trains is used in the controller design. Based on available proximal information（prox-info） of location, speed, and acceleration, a direct adaptive control is designed to maintain the tracking interval at the minimum safe distance. Based on available prox-info of location, an observer-based adaptive control is designed to achieve the same target, which alleviates the requirements of equipped sensors to measure prox-info of speed and acceleration. The developed schemes are capable of on-line estimating of the unknown system parameters and stabilizing the closed-loop system, the string stability of train platoon is guaranteed on the basis of Lyapunov stability theorem. Numerical simulation results are presented to verify the effectiveness of the proposed control laws.展开更多
In modern trains wheelset skidding leads to the deterioration of braking behavior,the degradation of comfort,as well as a boost in system hazards.Because of the nonlinearity and unknown characteristics of wheelset adh...In modern trains wheelset skidding leads to the deterioration of braking behavior,the degradation of comfort,as well as a boost in system hazards.Because of the nonlinearity and unknown characteristics of wheelset adhesion,simplifications are widely adopted in the modeling process of conventional antiskid controllers.Therefore,conventional antiskid controllers usually cannot perform satisfactorily.In this paper,systematic computer simulation and field tests for railway antiskid control system are introduced.The operating principal of antiskid control system is explained,which is fundamental to the simulation of antiskid brakes,and the simulation model is introduced,which incorporates both the adhesion creep curve and a pneumatic submodel of antiskid control system.In addition,the characteristics of adhesion curves and the simulation target are also provided.Using DHSplus,the pneumatic submodel is created to analyze the performance of the different control strategies of antiskid valves.Then the system simulation is realized by combining the kinematical characteristics of railway trains and the pneumatic submodel.The simulation is performed iteratively to obtain the optimized design of the antiskid control system.The design result is incorporated in the hardware design of the antiskid control system and is evaluated in the field tests in Shanghai Subway Line 1.Judging by the antiskid efficiency,the antiskid braking performance observed in the field tests shows the superiority of the optimized design.Therefore,the proposed simulation method,especially in view of its ease of application,appears to be a useful one for designing railway antiskid control systems.展开更多
This paper presents an adaptive terminal sliding mode control(ATSMC) method for automatic train operation. The criterion for the design is keeping high-precision tracking with relatively less adjustment of the control...This paper presents an adaptive terminal sliding mode control(ATSMC) method for automatic train operation. The criterion for the design is keeping high-precision tracking with relatively less adjustment of the control input. The ATSMC structure is designed by considering the nonlinear characteristics of the dynamic model and the parametric uncertainties of the train operation in real time. A nonsingular terminal sliding mode control is employed to make the system quickly reach a stable state within a finite time, which makes the control input less adjust to guarantee the riding comfort. An adaptive mechanism is used to estimate controller parameters to get rid of the need of the prior knowledge about the bounds of system uncertainty. Simulations are presented to demonstrate the effectiveness of the proposed controller, which has robust performance to deal with the external disturbance and system parametric uncertainties. Thereby, the system guarantees the train operation to be accurate and comfortable.展开更多
文摘Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has driven continuous upgrading and optimization of intelligent train control technology,thanks to its enhanced computational capabilities derived from advanced algorithms and models,as well as its role in improving safety performance.Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale.It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology,elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.Findings–The application of AI technology in the train driving and control field is still in its infancy.While a large number of AI technologies have been widely adopted,there remains significant room for further optimization and improvement of these technologies.Additionally,a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.Originality/value–The research findings provide references and guidance for advancing train control technology,promoting the digital transformation of railways,accelerating the overall optimization and upgrading of railway industry technologies,and facilitating the accelerated development of global railways.
基金Teaching and Research Project of Anhui Urban Management Vocational College(Project No.:2024kfkc001)。
文摘This paper reports a case of cerebral stem infarction with quadriplegia and complete dependence on daily life.The course of the disease lasted more than 7 months.Frenchay's improved articulation Disorder Assessment Form has been assessed as severe articulation disorder.The patient has significantly improved his speech function and quality of life after systematic head control training,respiratory function training,articulation motor training,and articulation training.In the course of treatment,emphasis was placed on head postural control training and respiratory function training,and emphasis was placed on the strength and coordination training of articulatory organs,and the results were remarkable.After the patient was discharged from the hospital,the follow-up of basic daily life communication was not limited.
基金supported in part by the project of the State Key Laboratory of Advanced Rail Autonomous Operation(RAO2023ZZ004)in part by the Beijing Natural Science Foundation-Fengtai Rail Transit Frontier Research Joint Fund(L211002)+2 种基金in part by the Foundation of China State Railway Group Corporation Limited under Grant L2021G003in part by the Scientific and Technical Research Fund of China Academy of Railway Sciences Corporation Limited under Grant 2021YJ094in part by the Project I23L00200 and Project I24F00010.
文摘With the integration of informatization and intelligence into the Communication-Based Train Control(CBTC)systems,the system is facing an increasing number of information security threats.As an important method of characterizing the system security status,the security situation assessment is used to analyze the system security situation.However,existing situation assessment methods fail to integrate the coupling relationship between the physical layer and the information layer of the CBTC systems,and cannot dynamically characterize the real-time security situation changes under cyber attacks.In this paper,a hierarchical security situation assessment approach is proposed to address the security challenges of CBTC systems,which can perceive cyber attacks,quantify the security situation,and characterize the security situation changes under cyber attacks.Specifically,for the physical layer ofCBTC systems,the impact of cyber attacks is evaluated with the train punctuality rate and train departure interval indicators.For the information layer of CBTC systems,the system vulnerabilities and system threats are selected as static level indicators,and the critical network characteristics are selected as dynamic level indicators to quantify the real-time security situation.Finally,the comprehensive security situation assessment value of the CBTC systems is obtained by integrating the physical and information layer indicators.Simulation results illustrate that the proposed approach can dynamically characterize the real-time security situation of CBTC systems,enhancing the ability to perceive and assess information security risks.
基金funded by the National Natural Science Foundation of China(81871854,72374014)the National Key R&D Program of China(2020YFC2008804)+1 种基金the Shanghai Jiao Tong University Young Talent Cultivation Program in Liberal Arts(2024QN041)the Shanghai Jiao Tong University School of Medicine:Nursing Development Program(SJTUHLXK2024).
文摘Background Evidence on the effects of different exercise interventions on cognitive function is insufficient.Aims To evaluate the feasibility and effects of remotely supervised aerobic exercise(AE)and resistance exercise(RE)interventions in older adults with mild cognitive impairment(MCI).Methods This study is a 6-month pilot three-arm randomised controlled trial.Eligible participants(n=108)were recruited and randomised to the AE group,RE group or control(CON)group with a 1:1:1 ratio.Interventions were delivered at home with remote supervision.We evaluated participants’global cognition,memory,executive function,attention,physical activity levels,physical performance and muscle strength of limbs at baseline,3 months(T1)and 6 months(T2)after randomisation.A linear mixed-effects model was adopted for data analyses after controlling for covariates.Tukey’s method was used for adjusting for multiple comparisons.Sensitivity analyses were performed after excluding individuals with low compliance rates.Results 15(13.89%)participants dropped out.The median compliance rates in the AE group and RE group were 67.31%and 93.27%,respectively.After adjusting for covariates,the scores of the Alzheimer’s Disease Assessment Scale-Cognitive subscale in the AE group decreased by 2.04(95%confidence interval(CI)−3.41 to−0.67,t=−2.94,p=0.004)and 1.53(95%CI−2.88 to−0.17,t=−2.22,p=0.028)points more than those in the CON group at T1 and T2,respectively.The effects of AE were still significant at T1(estimate=−1.70,95%CI−3.20 to−0.21,t=−2.69,p=0.021),but lost statistical significance at T2 after adjusting for multiple comparisons.As for executive function,the Stroop time interference in the RE group decreased by 11.76 s(95%CI−21.62 to−1.90,t=−2.81,p=0.015)more than that in the AE group at T2 after Tukey’s adjustment.No other significant effects on cognitive functions were found.Conclusions Both remotely supervised AE and RE programmes are feasible in older adults with MCI.AE has positive effects on global cognition,and RE improves executive function.
基金supported by the National Natural Science Foundation of China(52372310)the State Key Laboratory of Advanced Rail Autonomous Operation(RAO2023ZZ001)+1 种基金the Fundamental Research Funds for the Central Universities(2022JBQY001)Beijing Laboratory of Urban Rail Transit.
文摘The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.
基金supported by the Fundamental Research Funds for Central Public Welfare Research Institute,No.2020CZ-5(to WS and GS)the National Natural Science Foundation of China,No.31970970(to JSR)Fundamental Research Funds for the Central Universities,No.YWF-23-YG-QB-010(to JSR)。
文摘Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface electromyography.In this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord injury.Eleven patients with chronic complete thoracic spinal cord injury were recruited.Surface electromyography data from eight major leg muscles were acquired and compared before and after the passive activity protocol.The results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of activation.Although the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically significant.These findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.
基金supported by Swiss Federal Office of Transport,the ETH foundation and via the grant RAILPOWER.
文摘The reduction of energy consumption is an increasingly important topic of the railway system.Energy-efficient train control(EETC)is one solution,which refers to mathematically computing when to accelerate,which cruising speed to hold,how long one should coast over a suitable space,and when to brake.Most approaches in literature and industry greatly simplify a lot of nonlinear effects,such that they ignore mostly the losses due to energy conversion in traction components and auxiliaries.To fill this research gap,a series of increasingly detailed nonlinear losses is described and modelled.We categorize an increasing detail in this representation as four levels.We study the impact of those levels of detail on the energy optimal speed trajectory.To do this,a standard approach based on dynamic programming is used,given constraints on total travel time.This evaluation of multiple test cases highlights the influence of the dynamic losses and the power consumption of auxiliary components on railway trajectories,also compared to multiple benchmarks.The results show how the losses can make up 50%of the total energy consumption for an exemplary trip.Ignoring them would though result in consistent but limited errors in the optimal trajectory.Overall,more complex trajectories can result in less energy consumption when including the complexity of nonlinear losses than when a simpler model is considered.Those effects are stronger when the trajectory includes many acceleration and braking phases.
文摘软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一种基于时差的多输出tri-training异构软测量方法。通过构建一种新的tri-training框架,采用多输出的高斯过程回归(multi-output Gaussian process regression,MGPR)、相关向量机(multi-output relevance vector machine,MRVM)、最小二乘支持向量机(multi-output least squares support vector machine,MLSSVM)三种模型作为基线监督回归器,使用标记数据进行训练和迭代;同时,引入时间差分(time difference,TD)改进模型的动态特性,并通过卡尔曼滤波(Kalman filtering,KF)优化模型的参数,提高其预测性能;最后通过模拟污水处理平台(benchmark simulation model 1,BSM1)和实际污水处理厂对该模型进行了验证。结果表明,与传统的软测量建模方法相比,该模型能显著提高数据分布不平衡下软测量模型的自适应性和预测性能。
基金supported by the National Natural Science Foundationof China(62273029).
文摘Magnetic levitation control technology plays a significant role in maglev trains.Designing a controller for the levitation system is challenging due to the strong nonlinearity,open-loop instability,and the need for fast response and security.In this paper,we propose a Disturbance-Observe-based Tube Model Predictive Levitation Control(DO-TMPLC)scheme combined with a feedback linearization strategy for the levitation system.The proposed strategy incorporates state constraints and control input constraints,i.e.,the air gap,the vertical velocity,and the current applied to the coil.A feedback linearization strategy is used to cancel the nonlinearity of the tracking error system.Then,a disturbance observer is implemented to actively compensate for disturbances while a TMPLC controller is employed to alleviate the remaining disturbances.Furthermore,we analyze the recursive feasibility and input-to-state stability of the closed-loop system.The simulation results indicate the efficacy of the proposed control strategy.
文摘Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’balance function and gait.Methods:Fifty-two cases of hemiplegic stroke patients were randomly divided into two groups,26 in the control group and 26 in the observation group,using computer-generated random grouping.All participants underwent conventional treatment and rehabilitation training.In addition to these,the control group received repetitive transcranial magnetic pseudo-stimulation therapy+motor control training,while the observation group received repetitive transcranial magnetic stimulation therapy+motor control training.The balance function and gait parameters of both groups were compared before and after the interventions and assessed the satisfaction of the interventions in both groups.Results:Before the invention,there were no significant differences in balance function scores and each gait parameter between the two groups(P>0.05).However,after the intervention,the observation group showed higher balance function scores compared to the control group(P<0.05).The observation group also exhibited higher step speed and step frequency,longer step length,and a higher overall satisfaction level with the intervention compared to the control group(P<0.05).Conclusion:The combination of repetitive transcranial magnetic stimulation and motor control training in the treatment of stroke-induced hemiplegia has demonstrated positive effects.It not only improves the patient’s balance function and gait but also contributes to overall physical rehabilitation.
基金the National Key Research and Development Program of China(2023YFB3907300)the National Natural Science Foundation of China(U2268206,T2222015)the Beijing Natural Science Foundation(4232031).
文摘Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The growing threat to information security posed by spoofing attacks has received limited attention.This study investigates the impact of GNSS spoofing attacks on train positioning,emphasizing their detrimental effects on the accuracy and availability of train location report functions for train operation control.To explore the antispoofing performance of typical GNSS-based train positioning schemes,specific approaches,and system architectures are designed under two GNSS-alone and two GNSS-integrated train positioning schemes.Field data are utilized to establish spoofing attack scenarios for GNSS-based train positioning,with which the anti-spoofing capabilities of different train positioning schemes are evaluated.Experimental results indicate that under specific conditions,the GNSS-integrated positioning schemes demonstrate superior GNSS spoofing suppression capabilities.Results of the tests present valuable guidance for designers and manufacturers in developing more advanced and resilient train positioning solutions and equipment for the next generation of train control systems,thereby promoting the applications of GNSS technology in railway systems.
基金Project(52272339)supported by the National Natural Science Foundation of ChinaProject(2023YFB390730303)supported by the National Key Research and Development Program of China+2 种基金Project(L2023G004)supported by the Science and Technology Research and Development Program of China State Railway Group Co.,Ltd.Project(QZKFKT2023-005)supported by the State Key Laboratory of Heavy-duty and Express High-power Electric Locomotive,ChinaProject(2022JZZ05)supported by the Open Foundation of MOE Key Laboratory of Engineering Structures of Heavy Haul Railway(Central South University),China。
文摘In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.
基金supported by the First Affiliated Hospital of Xi’an Jiaotong University Teaching Reform Project(Grant No.JG2023-0206 and JG2022-0324).
文摘Objective:In the Radiology Department of Mzuzu Central Hospital(MCH),daily training for radiographers now includes content on Computed Tomography(CT)image quality control and equipment maintenance to ensure the normal,continuous,and stable operation of the 16-slice spiral CT scanner.Methods:Through comprehensive analysis of relevant equipment,we have identified key parameters that significantly impact CT image quality.Innovative optimization strategies and solutions targeting these parameters have been developed and integrated into daily training programs.Furthermore,starting from an examination of prevalent failure modes observed in CT equipment,we delve into essential maintenance and preservation techniques that CT technologists must master to ensure optimal system performance.Results:(1)Crucial factors affecting CT image quality include artifacts,noise,partial volume effects,and surrounding gap phenomena,alongside spatial and density resolutions,CT dose,reconstruction algorithms,and human factors during the scanning process.In the daily training for radiographers,emphasis is placed on strictly implementing image quality control measures at every stage of the CT scanning process and skillfully applying advanced scanning and image processing techniques.By doing so,we can provide clinicians with accurate and reliable imaging references for diagnosis and treatment.(2)Strategies for CT equipment maintenance:①Environmental inspection of the CT room to ensure cleanliness and hygiene.②Rational and accurate operation,including calibration software proficiency.③Regular maintenance and servicing for minimizing machine downtime.④Maintenance of the CT X-ray tube.CT technicians can become proficient in equipment maintenance and upkeep techniques through training,which can significantly extend the service life of CT systems and reduce the occurrence of malfunctions.Conclusion:Through the regular implementation of rigorous CT image quality control training for radiology technicians,coupled with diligent and proactive CT equipment maintenance,we have observed profound and beneficial impacts on improving image quality.The accuracy and fidelity of radiological data ultimately leads to more accurate diagnoses and effective treatments.
基金supported by the National Natural Science Foundation of China under Grant 52162050.
文摘This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the temporary speed limit on the railway line and the communication delay between trains,and it uses a VCTS consisting of three trains as an experimental object.It creates the virtual coupling train tracking and control process by improving the driving strategy of the leader train and using the leader-follower model.The follower train uses the improved speed curve of the leader train as its speed refer-ence curve through knowledge migration,and this completes the multi-objective optimization of the driving strategy for the VCTS.The experimental results confirm that the deep reinforcement learning algorithm effectively achieves the optimization goal of the train driving strategy.They also reveal that the intrinsic curiosity module prioritized experience replay dueling double deep Q-network(ICM-PER-D3QN)algorithm outperforms the deep Q-network(DQN)algorithm in optimizing the driving strategy of the leader train.The ICM-PER-D3QN algorithm enhances the leader train driving strategy by an average of 57%when compared to the DQN algorithm.Furthermore,the particle swarm optimization(PSO)-based model predictive control(MPC)algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation,with an average increase of 37.7%in tracking accuracy compared to the traditional MPC algorithm.
文摘With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powered aerobics training robot featuring an adaptive energy management system designed for sustainability and efficiency.The robot integrates machine vision with an enhanced Dynamic Cheetah Optimizer and Bayesian Neural Network(DynCO-BNN)to enable precise exercise monitoring and real-time feedback.Solar tracking technology ensures optimal energy absorption,while a microcontroller-based regulator manages power distribution and robotic movement.Dual-battery switching ensures uninterrupted operation,aided by light and I/V sensors for energy optimization.Using the INSIGHT-LME IMU dataset,which includes motion data from 76 individuals performing Local Muscular Endurance(LME)exercises,the system detects activities,counts repetitions,and recognizes human movements.To minimize energy use during data processing,Min-Max normalization and two-dimensional Discrete Fourier Transform(2D-DFT)are applied,boosting computational efficiency.The robot accurately identifies upper and lower limb movements,delivering effective exercise guidance.The DynCO-BNN model achieved a high tracking accuracy of 96.8%.Results confirm improved solar utilization,ecological sustainability,and reduced dependence on fossil fuels—positioning the robot as a smart,energy-efficient solution for next-generation fitness technology.
基金supported by a project entitled Loess Plateau Region-Watershed-Slope Geological Hazard Multi-Scale Collaborative Intelligent Early Warning System of the National Key R&D Program of China(2022YFC3003404)a project of the Shaanxi Youth Science and Technology Star(2021KJXX-87)public welfare geological survey projects of Shaanxi Institute of Geologic Survey(20180301,201918,202103,and 202413).
文摘This study investigated the impacts of random negative training datasets(NTDs)on the uncertainty of machine learning models for geologic hazard susceptibility assessment of the Loess Plateau,northern Shaanxi Province,China.Based on randomly generated 40 NTDs,the study developed models for the geologic hazard susceptibility assessment using the random forest algorithm and evaluated their performances using the area under the receiver operating characteristic curve(AUC).Specifically,the means and standard deviations of the AUC values from all models were then utilized to assess the overall spatial correlation between the conditioning factors and the susceptibility assessment,as well as the uncertainty introduced by the NTDs.A risk and return methodology was thus employed to quantify and mitigate the uncertainty,with log odds ratios used to characterize the susceptibility assessment levels.The risk and return values were calculated based on the standard deviations and means of the log odds ratios of various locations.After the mean log odds ratios were converted into probability values,the final susceptibility map was plotted,which accounts for the uncertainty induced by random NTDs.The results indicate that the AUC values of the models ranged from 0.810 to 0.963,with an average of 0.852 and a standard deviation of 0.035,indicating encouraging prediction effects and certain uncertainty.The risk and return analysis reveals that low-risk and high-return areas suggest lower standard deviations and higher means across multiple model-derived assessments.Overall,this study introduces a new framework for quantifying the uncertainty of multiple training and evaluation models,aimed at improving their robustness and reliability.Additionally,by identifying low-risk and high-return areas,resource allocation for geologic hazard prevention and control can be optimized,thus ensuring that limited resources are directed toward the most effective prevention and control measures.
文摘Objective To observe the clinical efficacy of acupuncture combined with speech rehabilitation training for post-stroke spasmodic dysphonia and compare the differences in efficacy among the therapy of acupuncture combined with speech rehabilitation training and the monotherapy.Methods Two hundred and seventy cases of patients with post-stroke spasmodic dysarthria were randomly divided into three groups with the ratio of 1：1：1.Group A：acupuncture combined with speech rehabilitation training group（90 cases）,group B：acupuncture group（90 cases）,group C：speech rehabilitation training group（90 cases）.In the group B,acupuncture treatment was given at Baihui（百会 GV 20）,JTnjin（金津 EX-HN 12） and Yuye（玉液 EX-HN13） as well as tongue-three needles.In the group C,the treatment of speech rehabilitation training was provided.The two treatments mentioned above were combined in the group A.Patients were treated once a day for a month with improved Frenchay dysarthria rating scale as the indices of therapeutic effect evaluation.Results ① Group A：the cured and markedly effective rate was 88.7%,and total effective rate was 94.3%;group B：the cured and markedly effective rate was 44.2%and total effective rate was 81.4%;group C：the cured and markedly effective rate was 23.5%and total effective rate was 61.2%.Both the cured and markedly effective rate and the total effective rate in the group A were significantly higher than those in the group B or group C（all P0.05）;both the cured and markedly effective rate and the total effective rate in the group B were higher than those of group C（both P0.05）;② In comparison of functional recovery of tongue in accordance with the Frenchay dysarthria rating scale,the recovery rate of the tongue-stationary state was 71.74%in the group A,18.87%in the group B and 4.44%in the group C;the recovery rate of tongue lolling out was 66.23%in the group A,27.63%in the group B and 1.59%in the group C;the recovery rate of tongue up and down motion was 44.19%in the group A,4.94%in the group B and 1.35%in the group C;the recovery rate of lateral motion was 40.24%in the group A,7.59%in the group B and 0.00%in the group C;the recovery rate of alternating motion was 29.07%in the group A,7.14%in the group B and 1.23%in the group C;the recovery rate of speech was 29.07%in the group A,5.88%in the group B and 1.22%in the group C.In the three groups,the recovery rates of stationary state and tongue lolling out were superior to those of up and down movement,lateral movement,alternating movement and speech（all P0.05）.Conclusion The clinical efficacy of acupuncture combined with speech rehabilitation training for patients with post-stroke spasmodic dysarthria is significant,and the efficacy of acupuncture is superior to that of speech rehabilitation training;as for functional recovery of tongue like stationary state and tongue out,the therapy of acupuncture combined with speech rehabilitation training is effective.
基金Project supported by the Beijing Jiaotong University Research Program,China(Grant No.RCS2014ZT18)the Fundamental Research Funds for Central Universities,China(Grant No.2015JBZ007)the National Natural Science Foundation of China(Grant Nos.61233001,61322307,and 61304196)
文摘This paper proposes cooperative adaptive control schemes for a train platoon to improve efficient utility and guarantee string stability. The control schemes are developed based on a bidirectional strategy, i.e., the information of proximal（preceding and following） trains is used in the controller design. Based on available proximal information（prox-info） of location, speed, and acceleration, a direct adaptive control is designed to maintain the tracking interval at the minimum safe distance. Based on available prox-info of location, an observer-based adaptive control is designed to achieve the same target, which alleviates the requirements of equipped sensors to measure prox-info of speed and acceleration. The developed schemes are capable of on-line estimating of the unknown system parameters and stabilizing the closed-loop system, the string stability of train platoon is guaranteed on the basis of Lyapunov stability theorem. Numerical simulation results are presented to verify the effectiveness of the proposed control laws.
基金supported by National Natural Science Foundation of China (Grant No. 61004077)National Key Technology R&D Program of the 11th Five Year Plan of China (Grant No. 2009BAG11B02)Foundation of Traction Power State Key Laboratory of Southwest Jiaotong University,China (Grant No. TPL1107)
文摘In modern trains wheelset skidding leads to the deterioration of braking behavior,the degradation of comfort,as well as a boost in system hazards.Because of the nonlinearity and unknown characteristics of wheelset adhesion,simplifications are widely adopted in the modeling process of conventional antiskid controllers.Therefore,conventional antiskid controllers usually cannot perform satisfactorily.In this paper,systematic computer simulation and field tests for railway antiskid control system are introduced.The operating principal of antiskid control system is explained,which is fundamental to the simulation of antiskid brakes,and the simulation model is introduced,which incorporates both the adhesion creep curve and a pneumatic submodel of antiskid control system.In addition,the characteristics of adhesion curves and the simulation target are also provided.Using DHSplus,the pneumatic submodel is created to analyze the performance of the different control strategies of antiskid valves.Then the system simulation is realized by combining the kinematical characteristics of railway trains and the pneumatic submodel.The simulation is performed iteratively to obtain the optimized design of the antiskid control system.The design result is incorporated in the hardware design of the antiskid control system and is evaluated in the field tests in Shanghai Subway Line 1.Judging by the antiskid efficiency,the antiskid braking performance observed in the field tests shows the superiority of the optimized design.Therefore,the proposed simulation method,especially in view of its ease of application,appears to be a useful one for designing railway antiskid control systems.
基金supported by National Natural Science Foundation of China and High Speed Railway Union Foundation of China(No.U11344205)
文摘This paper presents an adaptive terminal sliding mode control(ATSMC) method for automatic train operation. The criterion for the design is keeping high-precision tracking with relatively less adjustment of the control input. The ATSMC structure is designed by considering the nonlinear characteristics of the dynamic model and the parametric uncertainties of the train operation in real time. A nonsingular terminal sliding mode control is employed to make the system quickly reach a stable state within a finite time, which makes the control input less adjust to guarantee the riding comfort. An adaptive mechanism is used to estimate controller parameters to get rid of the need of the prior knowledge about the bounds of system uncertainty. Simulations are presented to demonstrate the effectiveness of the proposed controller, which has robust performance to deal with the external disturbance and system parametric uncertainties. Thereby, the system guarantees the train operation to be accurate and comfortable.
