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.

Multi-Stage Pedestrian Crossings and Two-Stage Bicycle Turns: Delay Estimation and Signal Timing Techniques for Limiting Pedestrian and Bicycle Delay

Signalized intersections sometimes involve multistage pedestrian crossings, in which pedestrians cross to one or more islands and then wait there for a signal to continue. When signals are timed without attention to pedestrian progression, pedestrian delay at multistage crossings can be very long. This paper addresses two issues. First, pedestrian delay at multistage crossings is rarely evaluated because there are no tools in the industry for that purpose except microsimulation. We present a numerical method for determining crossing delay with any number of stages and with the possibility of multiple WALK intervals per cycle. The same method can be applied to single stage crossings, to diagonal two-stage crossings where pedestrians may have path choice, and bicycle two-stage turns. This method has been implemented in a freely available online tool. Second, we describe several signal timing techniques for improving pedestrian and bicyclist progression, and thus reducing their delay, through multistage crossings. They include reservice for selected crossing phases, left turn overlaps, having pedestrian phases overlap each other, and bidirectional bicycle crossings which create path options for two-stage turns. Examples show the potential for large reductions in pedestrian delay, often with little or no increase in vehicular delay. In one example, the addition of a short pedestrian overlap phase reduced average pedestrian delay at a 3-stage crossing by 82 s while average vehicular delay increased by only 0.5 s.

LED Applications in Railway Signals: Wavelength and Intensity vs Temperature Variation

In recent years, light emitting diodes (LEDs) have entered the lighting market, offering consumers performance and features exceeding those of traditional lighting technologies. LEDs (light-emitting diodes) are becoming more common in safety signals for railroad, highway, automotive, and many other applications. In addition to having a longer life and greater durability than incandescent bulbs, LEDs are much more energy efficient than their incandescent counterparts. Since the heat from the junction must be dissipated into the ambient somehow, changing the ambient temperature affects the junction temperature and hence the emitted light. When the LEDs are used in the railway or traffic signals, the optical proprieties of these have to maintain more rigorous specifications. Therefore the development of signals using LED as light source, able to respect intensity specifications, is not simple. In this paper, we describe problems of the temperature dependent changes of LED intensity and color shift. Besides we will introduce an innovative technique, that we have developed, to allow the use of the LEDs in applications with rigorous specifications.

Optimization of Crosswalk Width Based on Bi-Directional Pedestrian Crossing Time at Signalized Intersections

The effects of the interactions between bi-directional pedestrians on the crossing time and the crosswalk width are studied. Firstly,the crossing process of bi-directional pedestrians is analyzed.The total crosswalk time is divided into a discharge time and a crossing time. The interactions between bi-directional pedestrians are quantified with the drag force theory. Then,a model is developed to study the crossing time based on the kinetic energy theory and momentum theory. Subsequently,the related parameters of the proposed model are calibrated with observed information. The relationships among crosswalk width,signal time,pedestrian volume and level of service are simulated with the proposed model. The results are verified and compared with other models. The proposed model has an absolute value of relative error of 9. 38%,which is smaller than that of the Alhajyaseen model（ 15. 26%） and Highway Capacity Manual（ HCM） model（ 12. 42%）. Finally,suggested crosswalk widths at different conditions are successfully estimated with the proposed crossing time model.

Wideband Signal Detection Based on MWC Discrete Compressed Sampling Structure

In order to solve the cross-channel signal problem caused by the uniform channelized wideband digital receiver when processing wideband signal and the problem that the sensitivity of the system greatly decreases when the bandwidth of wideband digital receiver increases,which both decrease the wideband radar signal detection performance,a new wideband digital receiver based on the modulated wideband converter(MWC)discrete compressed sampling structure and an energy detection method based on the new receiver are proposed.Firstly,the proposed receiver utilizes periodic pseudo-random sequences to mix wideband signals with baseband and other sub-bands.Then the mixed signals are low-pass filtered and downsampled to obtain the baseband compressed sampling data,which can increase the sensitivity of the system.Meanwhile,the cross-channel signal will all appear in any subbands,so the cross-channel signal problem can be solved easily by processing the baseband compressed sampling data.Secondly,we establish the signal detection model and formulate the criterion of the energy detection method.And we directly utilize the baseband compressed sampling data to carry out signal detection without signal reconstruction,which decreases the complexity of the algorithm and reduces the computational burden.Finally,simulation experiments demonstrate the effectiveness of the proposed receiver and show that the proposed signal detection method is effective in low signal-to-noise ratio(SNR)compared with the conventional energy detection and the probability of detection increases significantly when SNR increases.

Optimal multi-sensor Kalman smoothing fusion for discrete multichannel ARMA signals

Based on the multi-sensor optimal information fusion criterion weighted by matrices in the linear minimum variance sense, using white noise estimators, an optimal fusion distributed Kalman smoother is given for discrete multi-channel ARMA （autoregressive moving average） signals. The smoothing error cross-covanance matrices between any two sensors are given for measurement noises. Furthermore, the fusion smoother gives higher precision than any local smoother does.

Measuring Acoustic Wave Transit Time in Furnace Based on Active Acoustic Source Signal

Accurate measurement of transit time for acoustic wave between two sensors installed on two sides of a furnace is a key to implementing the temperature field measurement technique based on acoustical method. A new method for measuring transit time of acoustic wave based on active acoustic source signal is proposed in this paper, which includes the followings： the time when the acoustic source signal arrives at the two sensors is measured first; then, the difference of two arriving time arguments is computed, thereby we get the transit time of the acoustic wave between two sensors installed on the two sides of the furnace. Avoiding the restriction on acoustic source signal and background noise, the new method can get the transit time of acoustic wave with higher precision and stronger ability of resisting noise interference.

Radar emitter signal recognition method based on improved collaborative semi-supervised learning

Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition method based on a small amount of labeled data is developed.First,a small amount of labeled data are randomly sampled by using the bootstrap method,loss functions for three common deep learning net-works are improved,the uniform distribution and cross-entropy function are combined to reduce the overconfidence of softmax classification.Subsequently,the dataset obtained after sam-pling is adopted to train three improved networks so as to build the initial model.In addition,the unlabeled data are preliminarily screened through dynamic time warping(DTW)and then input into the initial model trained previously for judgment.If the judg-ment results of two or more networks are consistent,the unla-beled data are labeled and put into the labeled data set.Lastly,the three network models are input into the labeled dataset for training,and the final model is built.As revealed by the simula-tion results,the semi-supervised learning method adopted in this paper is capable of exploiting a small amount of labeled data and basically achieving the accuracy of labeled data recognition.

Analysis of frequency shifting in seismic signals using Gabor-Wigner transform

A hybrid time-frequency method known as Gabor-Wigner transform (GWT) is introduced in this paper for examining the time-frequency patterns of earthquake damaged buildings. GWT is developed by combining the Gabor transform (GT) and Wigner-Ville distribution (WVD). GT and WVD have been used separately on synthetic and recorded earthquake data to identify frequency shifting due to earthquake damages, but GT is prone to windowing effect and WVD involves ambiguity function. Hence to obtain better clarity and to remove the cross terms (frequency interference), GT and WVD are judiciously combined and the resultant GWT used to identify frequency shifting. Synthetic seismic response of an instrumented building and real-time earthquake data recorded on the building were investigated using GWT. It is found that GWT offers good accuracy for even slow variations in frequency, good time-frequency resolution, and localized response. Presented results confirm the efficacy of GWT when compared with GT and WVD used separately. Simulation results were quantified by the Renyi entropy measures and GWT shown to be an adequate technique in identifying localized response for structural damage detection.

Design and Simulation of an Audio Signal Alerting and Automatic Control System

A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.

Stochastic resonance in a gain-noise model of a single-mode laser driven by pump noise and quantum noise with cross-correlation between real and imaginary parts under direct signal modulation

Stochastic resonance （SR） is studied in a gain-noise model of a single-mode laser driven by a coloured pump noise and a quantum noise with cross-correlation between real and imaginary parts under a direct signal modulation. By using a linear approximation method, we find that the SR appears during the variation of signal-to-noise ratio （SNR） separately with the pump noise self-correlation time τ, the noise correlation coefficient between the real part and the imaginary part of the quantum noise λq, the attenuation coefficient γ＇ and the deterministic steady-state intensity I0. In addition, it is found that the SR can be characterized not only by the dependence of SNR on the noise variables of and λq, but also by the dependence of SNR on the laser system variables of γ and I0. Thus our investigation extends the characteristic quantity of SR proposed before.

RESEARCH ON PERFORMANCE INFLUENCE OF DIRECT-PATH SIGNAL FOR DVB-S BASED PASSIVE RADAR

Passive radar detects moving targets by Cross Ambiguity Function (CAF), which is based on the cross correlation process of the direct-path signal in reference channel and echo signal in receive channel. Thus, the performance of direct-path signal is important to system performance for this type of radar. While the Signal to Noise Ratio (SNR) of direct-path signal is low, it will deteriorate the detection performance. In this paper, how SNR of direct-path signal induces degradation on the SNR of CAF, and how the integration gain affects by integration time are analyzed, both with theoretical analysis and numerical simulation, which are valuable for the R&D of passive radar.

Reconstruction of sub cross-correlation cancellation technique for unambiguous acquisition of BOC(kn, n) signals

In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(RSCCT)for BOC(kn,n)signals is proposed.In this paper,the principle of signal decomposition is combined with the traditional acquisition algorithm structure,and then based on the method of reconstructing the correlation function.The method firstly gets the sub-pseudorandom noise(PRN)code by decomposing the local PRN code,then uses BOC(kn,n)and the sub-PRN code cross-correlation to get the sub cross-correlation function.Finally,the correlation peak with a single peak is obtained by reconstructing the sub cross-correlation function so that the ambiguities of BOC acquisition are removed.The simulation shows that RSCCT can completely eliminate the side peaks of BOC(kn,n)group signals while maintaining the narrow correlation of BOC,and its computational complexity is equivalent to sub carrier phase cancellation(SCPC)and autocorrelation side-peak cancellation technique(ASPeCT),and it reduces the computational complexity relative to BPSK-like.For BOC(n,n),the acquisition sensitivity of RSCCT is 3.25 dB,0.81 dB and 0.25 dB higher than binary phase shift keying(BPSK)-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.91,3.0 and 3.7 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.For BOC(2n,n),the acquisition sensitivity of RSCCT is 5.5 dB,1.25 dB and 2.69 dB higher than BPSK-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.02,1.68 and 2.12 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.

Emodin regulating excision repair cross-complementation group 1 through fibroblast growth factor receptor 2 signaling

AIM: To investigate the molecular mechanisms underlying the reversal effect of emodin on platinum resistance in hepatocellular carcinoma. METHODS: After the addition of 10 μmol/L emodin to HepG2/oxaliplatin (OXA) cells, the inhibition rate (IR), 50% inhibitory concentration (IC 50 ) and reversal index (IC 50 in experimental group/IC 50 in control group) were calculated. For HepG2, HepG2/OXA, HepG2/OXA/T, each cell line was divided into a control group, OXA group, OXA + fibroblast growth factor 7 (FGF7) group and OXA + emodin group, and the final concentrations of FGF7, emodin and OXA in each group were 5 ng/mL, 10 μg/mL and 10 μmol/L, respectively. Single-cell gel electrophoresis was conducted to detect DNA damage, and the fibroblast growth factor receptor 2 (FGFR2), phosphorylated extracellular signal-regulated kinase 1/2 (p-ERK1/2) and excision repair cross-complementing gene 1 (ERCC1) protein expression levels in each group were examined by Western blotting. RESULTS: Compared with the IC50 of 120.78 μmol/L in HepG2/OXA cells, the IC 50 decreased to 39.65 μmol/L after treatment with 10 μmol/L emodin; thus, the reversal index was 3.05. Compared with the control group, the tail length and Olive tail length in the OXA group, OXA + FGF7 group and OXA + emodin group were significantly increased, and the differences were statistically significant (P < 0.01). The tail length and Olive tail length were lower in the OXA + FGF7 group than in the OXA group, and this difference was also statistically significant. Compared with the OXA + FGF7 group, the tail extent, the Olive tail moment and the percentage of tail DNA were significantly increased in the OXA + emodin group, and these differences were statistically significant (P < 0.01). In comparison with its parental cell line HepG2, the HepG2/OXA cells demonstrated significantly increased FGFR2, p-ERK1/2 and ERCC1 expression levels, whereas the expression of all three molecules was significantly inhibited in HepG2/ OXA/T cells, in which FGFR2 was silenced by FGFR2 shRNA. In the examined HepG2 cells, the FGFR2, p-ERK1/2 and ERCC1 expression levels demonstrated increasing trends in the OXA group and OXA + FGF7 group. Compared with the OXA group and OXA + FGF7 group, the FGFR2, p-ERK1/2, and ERCC1 expression levels were significantly lower in the OXA + emodin group, and these differences were statistically significant. In the HepG2/OXA/T cell line that was transfected with FGFR2 shRNA, the FGFR2, p-ERK1/2 and ERCC1 expression levels were significantly inhibited, but there were no significant differences in these expression levels among the OXA, OXA + FGF7 and OXA + emodin groups. CONCLUSION: Emodin markedly reversed OXA resistance by enhancing OXA DNA damage in HepG2/OXA cells, and the molecular mechanism was related to the inhibitory effect on ERCC1 expression being mediated by the FGFR2/ERK1/2 signaling pathway.

Research on time-frequency cross mutual of motor imagination data based on multichannel EEG signal

At present,multi-channel electroencephalogram(EEG)signal acquisition equipment is used to collect motor imagery EEG data,and there is a problem with selecting multiple acquisition channels.Choosing too many channels will result in a large amount of calculation.Components irrelevant to the task will interfere with the required features,which is not conducive to the real-time processing of EEG data.Using too few channels will result in the loss of useful information and low robustness.A method of selecting data channels for motion imagination is proposed based on the time-frequency cross mutual information(TFCMI).This method determines the required data channels in a targeted manner,uses the common spatial pattern mode for feature extraction,and uses support vector ma-chine(SVM)for feature classification.An experiment is designed to collect motor imagery EEG da-ta with four experimenters and adds brain-computer interface(BCI)Competition IV public motor imagery experimental data to verify the method.The data demonstrates that compared with the meth-od of selecting too many or too few data channels,the time-frequency cross mutual information meth-od using motor imagery can improve the recognition accuracy and reduce the amount of calculation.

The Regulating Effect of the nm23-H1 Gene for PKA Signal Pathway of Lung Cancer Cell and Its Molecular Mechanism

Backgroud and Objective Lung cancer has become the most frenquent malignant tumor in the world which its mortality and morbidity is increasing fastest among all the cancers。

Effects of signal modulation and coloured cross-correlation of coloured noises on the diffusion of a harmonic oscillator

The diffusion in a harmonic oscillator driven by coloured noises ξ（t） and η（t） with coloured cross-correlation in which one of the noises is modulated by a biased periodic signal is investigated. The exact expression of diffusion coefficient d as a function of noise parameter, signal parameter, and oscillator frequency is derived. The findings in this paper are as follows. 1） The curves of d versus noise intensity D and d versus noises cross-correlation time z3 exist as two different phases. The transition between the two phases arises from the change of the cross-correlation coefficient A of the two Ornstein-Uhlenbeck （O-U） noises. 2） Changing the value of T3, the curves of d versus Q, the intensity of colored noise that is modulated by the signal, can transform from a phase having a minimum to a monotonic phase. 3） Changing the value of signal amplitude A, d versus Q curves can transform from a phase having a minimum to a monotonic phase. The above-mentioned results demonstrate that a like noise-induced transition appears in the model.

Performance Comparison of Three Algorithms Applied to UM2000 Signal Demodulation

UM2000 signal is a type of multi-audio frequency-modulated signal which is widely used for railway blocking. Principles of three typical demodulating algorithms are presented in details in this paper. Bit error rates of the three methods at different SNRs are achieved by Monte Carlo simulation experiments. Among the three algorithms, the quadrature demodulation has the best performance at the real working environment. However, the three methods have the same problem of phase hopping when noise is too strong.

Interference mechanism analysis and mitigation measures with railway signalling equipment from harmonics in the traction system

With the development of high-speed railway and heavy-haul rail transport in China,a large number of new types of electric locomotives and electric multiple units have been put into operation,improving the efficiency and equipment quality of railway transportation.However,harmonics emitted from the traction system and locomotives often interfere with the railway signalling equipment,which can lead to critical malfunction of the equipment.Based on field test data,this paper analyses the interference coupling mechanism and magnitude of traction harmonics to the signalling equipment using a three-element method of interference.It examines the three essential elements of electromagnetic interference,studies harmonic mitigation measures and proposes to solve the problem of inteference with signalling equipment by installing a passive high-pass filter in the coupling path.After comparing the effects of several types of filters using simulation tests,this paper verified the validity of the method and concluded that a second-order passive filter is the optimal solution for harmonic interference mitigation.