Research on the Integrated Training Path of Secondary Vocational,Vocational,and Undergraduate Talents Based on Modern Vocational Education Group

Accelerating the construction of modern vocational education groups and promoting the integrated training of secondary vocational,vocational,and undergraduate talents,providing talent support for regional economic development,are inevitable choices to enhance the adaptability of vocational education.Based on the new development and requirements in the new situation,vocational colleges actively explore the path of connecting and cultivating secondary vocational,vocational,and undergraduate talents in accordance with the talent needs of local economic development and industrial system development.The linkage between government,school,and enterprise is established to build a modern vocational education group,aiming to build a professional chain in the industrial chain and promote innovative development of the new industrial system.Relying on the development needs of professional clusters,a multi-level system of connecting and cultivating secondary vocational,vocational,and undergraduate talents is constructed,which is in line with industry and enterprise standards.It is also necessary to build a“post-course competition certification”talent training model for connecting secondary vocational,vocational,and undergraduate students,rely on the advantages of multiple schools and enterprises,establish a platform for integrating industry and education,and innovate the evaluation system for connecting secondary vocational,vocational,and undergraduate students.

Study on key technologies of GNSS-based train state perception for traincentric railway signaling

The application of Global Navigation Satellite Systems(GNSSs)in the intelligent railway systems is rapidly developing all over the world.With the GNSs-based train positioning and moving state perception,the autonomy and flexibility of a novel train control system can be greatly enhanced over the existing solutions relying on the track-side facilities.Considering the safety critical features of the railway signaling applications,the GNSS stand-alone mode may not be sufficient to satisfy the practical requirements.In this paper,the key technologies for applying GNSS in novel train-centric railway signaling systems are investigated,including the multi-sensor data fusion,Virtual Balise(VB)capturing and messaging,train integrity monitoring and system performance evaluation.According to the practical characteristics of the novel train control system under the moving block mode,the details of the key technologies are introduced.Field demonstration results of a novel train control system using the presented technologies under the practical railway operation conditions are presented to illustrate the achievable performance feature of autonomous train state perception using BeiDou Navigation Satellite System(BDS)and related solutions.It reveals the great potentials of these key technologies in the next generation train control system and other GNSS-based railway implementations.

A train timetable rescheduling approach based on multi-train tracking optimization of high-speed railways

Purpose–This paper aims to propose a train timetable rescheduling(TTR)approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.Design/methodology/approach–Firstly,a single-train trajectory optimization(STTO)model is constructed based on train dynamics and operating conditions.The train kinematics parameters,including acceleration,speed and time at each position,are calculated to predict the arrival times in the train timetable.A STTO algorithm is developed to optimize a single-train time-efficient driving strategy.Then,a TTR approach based on multi-train tracking optimization(TTR-MTTO)is proposed with mutual information.The constraints of temporary speed restriction(TSR)and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train.The multi-train trajectories at each position are optimized to generate a timeefficient train timetable.Findings–The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF.The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay(TTD).As for the TSR scenario,the proposed TTR-MTTO can reduce TTD by 60.60%compared with the traditional TTR approach with dispatchers’experience.Moreover,TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.Originality/value–With the cooperative relationship and mutual information between train rescheduling and control,the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

Trains of Thought in Treating Infectious Atypical Pneumonia with Integrative Chinese and Western Medicine Approach

EDITORIAL Severe Acute Respiratory Syndrome(SARS)is a new intractable disease worldwide,itsonset is acute,its infectivity and mortality is high,the knowledge about its etiology and pathogenesis is in-sufficient,the experience on SARS treatment awaits accumulation.Following pilot experiences of applyingICWM in fighting SARS is most valuable with scientific significance.

Mechanism of Integrative Body-Mind Training

Integrative Body-Mind Training（IBMT） originates from ancient Eastern tradition.The method stresses no effort to control thoughts,but instead a state of restful alertness that allows a high degree of awareness of the body,breathing,and external instructions.A series of studies indicates that IBMT improves attention and self-regulation through interaction between the central（brain） and the autonomic（body） nervous systems.The present review mainly summarizes the recent results of IBMT studies and proposes how it changes the state of brain and body to lead to positive outcomes.Future directions in this field are also discussed.

Particle Filter and Its Application in the Integrated Train Speed Measurement

Particle filter(PF) can solve the problem of state estimation under strong non-linear non-Gaussian noise condition with respect to traditional Kalman filter(KF) and those improved KFs such as extended KF(EKF) and unscented KF(UKF). However, problems such as particle depletion and particle degradation affect the performance of PF. Optimizing the particle set to high likelihood region with intelligent optimization algorithm results in a more reasonable distribution of the sampling particles and more accurate state estimation. In this paper, a novel bird swarm algorithm based PF(BSAPF) is presented. Firstly, different behavior models are established by emulating the predation, flight, vigilance and follower behavior of the birds. Then, the observation information is introduced into the optimization process of the proposal distribution with the design of fitness function. In order to prevent particles from getting premature(being stuck into local optimum) and increase the diversity of particles, Lévy flight is designed to increase the randomness of particle's movement. Finally,the proposed algorithm is applied to estimate the speed of the train under the condition that the measurement noise of the wheel sensor is non-Gaussian distribution. Simulation study and experimental results both show that BSAPF is more accurate and has more effective particle number as compared with PF and UKF, demonstrating the promising performance of the method.