Experimental Model and Analytic Solution for Real-time Observation of Vehicle's Additional Steer Angle

The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle＇s roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ε-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system（ESC）. The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model＇s generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal （the magnitude up to 1°）, followed by the longitudinal acceleration-deceleration and the road wave amplitude （the magnitude up to 0.3°）. Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.

Real-time observation of integrin bending/unbending conformational changes on living cells

Introduction Integrins are a large family of adhesion molecules broadly expressed on the surface of a wide variety of cells as heterodimers. Binding of integrins to ligands provides not only mechanical anchorage for the cell to another cell or

High Resolution Radar Real-Time Signal and Information Processing

Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. Real-time signal and information processor is an important module for real-time positioning, imaging, detection and recognition of targets. With the development of ultra-wideband technology, synthetic aperture technology, signal and information processing technology, the radar coverage, detection accuracy and resolution have been greatly improved, especially in terms of one-dimensional(1D) high-resolution radar detection, tracking, recognition, and two-dimensional(2D) synthetic aperture radar imaging technology. Meanwhile, for the application of radar detection and remote sensing with high resolution and wide swath, the amount of data has been greatly increased. Therefore, the radar is required to have low-latency and real-time processing capability under the constraints of size, weight and power consumption. This paper systematically introduces the new technology of high resolution radar and real-time signal and information processing. The key problems and solutions are discussed, including the detection and tracking of 1D high-resolution radar, the accurate signal modeling and wide-swath imaging for geosynchronous orbit synthetic aperture radar, and real-time signal and information processing architecture and efficient algorithms. Finally, the latest research progress and representative results are presented, and the development trends are prospected.

Machine learning for parameters diagnosis of spark discharge by electro-acoustic signal

Discharge plasma parameter measurement is a key focus in low-temperature plasma research.Traditional diagnostics often require costly equipment,whereas electro-acoustic signals provide a rich,non-invasive,and less complex source of discharge information.This study harnesses machine learning to decode these signals.It establishes links between electro-acoustic signals and gas discharge parameters,such as power and distance,thus streamlining the prediction process.By building a spark discharge platform to collect electro-acoustic signals and implementing a series of acoustic signal processing techniques,the Mel-Frequency Cepstral Coefficients(MFCCs)of the acoustic signals are extracted to construct the predictors.Three machine learning models(Linear Regression,k-Nearest Neighbors,and Random Forest)are introduced and applied to the predictors to achieve real-time rapid diagnostic measurement of typical spark discharge power and discharge distance.All models display impressive performance in prediction precision and fitting abilities.Among them,the k-Nearest Neighbors model shows the best performance on discharge power prediction with the lowest mean square error(MSE=0.00571)and the highest R-squared value(R^(2)=0.93877).The experimental results show that the relationship between the electro-acoustic signal and the gas discharge power and distance can be effectively constructed based on the machine learning algorithm,which provides a new idea and basis for the online monitoring and real-time diagnosis of plasma parameters.

Low-Power Operational Amplifier for Real-Time Signal Processing System of Micro Air Vehicle

A low-power complementary metal oxide semiconductor（CMOS） operational amplifier （op-amp） for real-time signal processing of micro air vehicle （MAV） is designed in this paper.Traditional folded cascode architecture with positive channel metal oxide semiconductor（PMOS） differential input transistors and sub-threshold technology are applied under the low supply voltage.Simulation results show that this amplifier has significantly low power,while maintaining almost the same gain,bandwidth and other key performances.The power required is only 0.12 mW,which is applicable to low-power and low-voltage real-time signal acquisition and processing system.

Real-Time Traffic Signal Timing for Urban Road Multi-Intersection

this paper develops a real-time traffic signal timing model which is to be integrated into a single intersection for urban road, thereby solving the problem of traffic congestion. We analyze the current situation of the traffic flow with release matrix firstly, and then put forward the basic models to minimize total delay time of vehicles at the intersection. The optimal real-time signal timing model (non-fixed cycle and non-fixed split) is built with the Webster split optimal model. At last, the simulated results, which are compared with conventional model, manifest the promising properties of proposed model.

Real-Time Discrete Adaptive Control of Robot Arm Based on Digital Signal Processing

A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.

Mooring System of Ocean Turbulence Observation Based on Submerged Buoy

A comparison experiment has been taken in the Kiaochow Bay between a newly designed mooring turbulence observation instrument （MTOI） and microstructure profiler MSS60 made by Sea ＆ Sun. The whole observing system is based on a submerged buoy, in which the turbulence observation instrument is embedded, with a streamline-shape floating body, which is made of buoyancy material of glass microsphere. For the movement of seawater and the cable shaking strongly anytime influence the behaviors of the floating body, the accelerate sensors are used for the vibration measurement in the instrument together with the shear probe sensor. Both the vibration data and the shear data are acquired by the instrument at the same time. During data processing, the vibration signals can be removed and leave the shear data which we really need. In order to prove the reliability of the new turbulence instrument MTOI, a comparison experiment was designed. The measuring conditions are the same both in time and space. By this way, the two groups of data are comparable. In this paper, the conclusion gives a good similarity of 0.93 for the two groups of shear data in dissipation rate. The processing of the data acquired by MTOI is based on the cross-spectrum analysis, and the dissipation rate of it matches the Nasmyth spectrum well.

Simulation of large-scale numerical substructure in real-time dynamic hybrid testing

A solution scheme is proposed in this paper for an existing RTDHT system to simulate large-scale finite element （FE） numerical substructures. The analysis of the FE numerical substructure is split into response analysis and signal generation tasks, and executed in two different target computers in real-time. One target computer implements the response analysis task, wherein a large time-step is used to solve the FE substructure, and another target computer implements the signal generation task, wherein an interpolation program is used to generate control signals in a small time-step to meet the input demand of the controller. By using this strategy, the scale of the FE numerical substructure simulation may be increased significantly. The proposed scheme is initially verified by two FE numerical substructure models with 98 and 1240 degrees of freedom （DOFs）. Thereafter, RTDHTs of a single frame-foundation structure are implemented where the foundation, considered as the numerical substructure, is simulated by the FE model with 1240 DOFs. Good agreements between the results of the RTDHT and those from the FE analysis in ABAQUS are obtained.

A Comparison Study of the Contributions of Additional Observations in the Sensitive Regions Identified by CNOP and FSV to Reducing Forecast Error Variance for the Typhoon Morakot

The sensitive regions of conditional nonlinear optimal perturbations (CNOPs) and the first singular vector (FSV) for a northwest Pacific typhoon case are reported in this paper. A large number of probes have been designed in the above regions and the ensemble transform Kalman filter (ETKF) techniques are utilized to examine which approach can locate more appropriate regions for typhoon adaptive observations. The results show that, in general, the majority of the probes in the sensitive regions of CNOPs can reduce more forecast error variance than the probes in the sensitive regions of FSV. This implies that adaptive observations in the sensitive regions of CNOPs are more effective than in the sensitive regions of FSV. Furthermore, the reduction of the forecast error variance obtained by the best probe identified by CNOPs is twice the reduction of the forecast error variance obtained by FSV. This implies that dropping sondes, which is the best probe identified by CNOPs, can improve the forecast more than the best probe identified by FSV. These results indicate that the sensitive regions identified by CNOPs are more appropriate for adaptive observations than those identified by FSV.

Analyses on normal background characteristics about deformation observation data on the basis of wavelet transform method

Wavelet transform method is applied to measure time-frequency distribution characteristics of digital deformation data and noise. Based on the characteristics of primary modulus and stochastic white noise discrimination factor of wavelet decomposition, we analyze the variation rule of normal background and noise data from Shandong digital deformation observation data. The research results indicate that: a) 1/4 daily wave, semi-diurnal tide wave, daily wave and half lunar wave and so on quasi-periodic signal exist in the detail decomposing signal of wavelet when scale are equal to 2, 3 and 4; b) The amplitude of detail decomposing signal is the biggest when scale is equal to 3; c) The detail decomposing signal contains mainly noise corresponding to scale 1 and 5, respectively; d) We may trace the abnormal precursory which is related to earthquake by analyzing non-earthquake wavelet decomposing signal whose scale is specified from digital deformation observation data.

Atmospheric Observation under Sampling Problem: The Impact of Unresolved Micro-Scale Boundary Layer Eddies on Climate Trends

The observed basic weather variables are the main representative of climate trends and the atmosphere. The unresolved meteorological scale in weather observation such as micro scale, can produce a noticeable bias in amplitude, frequency, phase and climate trend of each observed variable time series. The bias in climate trend due to a small scale eddy can be as high as the amplitude of the eddy which could be greater than 1°C in a temperature trend. Such biased measurements of the state of the atmosphere limit all climate related studies.

A Novel Method for Real-Time Monitoring of Channel Siltation Based on Bistatic Scattering Theory

Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging, This paper presents a novel method for realizing the field monitoring of channel siltation in real time. The method is based on the bistatic scattering theory and concerned more with the receiving and processing of multipath signal at high-frequency and small grazing angle. By use of the multipath propagation structure of underwater acoustic channel, the method obtains the silt thickness by calculating the relative time delay of acoustic signals between the direct and the shortest bottom reflected paths. Bistatic transducer pairs are employed to transmit and receive the acoustic signals, and the GPS time synchronization technology is introduced to synchronize the transmitter and receiver, The WRELAX （Weighted Fourier transforul and RELAX） algorithm is used to obtain the high resolution estimation of muhipath time delay. To examine the feasibility of the presented method and the accuracy and precision of the developed system, a series of sea trials are conducted in the southwest coast area of Dalian City, north of the Yellow Sea. The experimental results are compared with that using high-resolution dual echo sounder HydroBoxTM, and the uncertainty is smaller than ＋ 0.06 m. Compared with the existing means for measuring the silt thickness, the present method is innovative, and the system is stable, efficient and provides a better real-time performance. It especially suits monitoring the narrow channel with rapid changes of siltation.

Real-time measurement of high rotational projectile axial acceleration based on 2-axis acceleration sensor

The real-time measurement principle of high rotational projectile＇s angular velocity based on 2-axis acceleration sensor and the axial acceleration measurement error caused by the installation error are discussed.The 2-axis acceleration sensor is applied to measure the high rotational projectile＇s angular velocity and the measurement value of axial acceleration,the axial acceleration of the high rotational projectile equals the measurement value of axial acceleration subtracting the centrifugal acceleration component,so that the high-accuracy real-time measurement of axial acceleration is realized.The memory test has confirmed the strike tally of the theoretical analysis and the test result.The measurement technique can satisfy the high-accuracy measurement of the high rotational projectile axial acceleration in the self-determination course correction fuze projectile.

Real-Time Maqam Estimation Model in Max/MSP Configured for the Nāy

Automatic maqam estimation is considered significant toward improving multimedia live music performances and automatic accompaniment. This contribution proposed a real-time maqam estimation model developed in the visual programming language MAX/MSP and configured for the nāydukah. The model’s design stood on basic formulas of Arab music maqamat as explained in theory and applied in practice. The model consisted of different layers of competition;the first was for the identification of the instant tonic of the melodic figure, and the second was for the recognition of its identifying E (E, E half-flat and E flat). Those two competitions were used to estimate the maqam in real-time. Then, accumulated estimation results were used to estimate the maqam in longer durations;five-second and full duration. The model was evaluated using professionally performed nāy improvisations. Results reflected a success in estimating all the studied maqamat when the full improvisation was considered. In addition, results were very good for real-time and five-second estimation where average estimation confidence was 75.98% and 80.04%, respectively.

一种优化高频注入法PMSM无位置传感器控制

传统高频信号注入法采用带通滤波器分离信号,龙伯格观测器利用所得信号计算出转子位置,考虑到带通滤波器设计复杂且使高频信号幅值产生衰减,同时龙伯格观测器需要电机转矩反馈、转动惯量等多种机械参数,这些因素干扰电机控制系统的动态性能等。采用基于低通滤波器的信号分离方法可在不损失高频信号得到含转子位置信号;利用电机的转速、转子位置角以及其角加速度之间关系构建扩张状态观测器,可以避免测量负载转矩和对不确定扰动的估计。仿真及实验结果表明,该优化策略能够使电机在低速控制时稳定运行,且具有更好的低速动态性能。

基于不同模糊度固定产品的PPP-AR定位性能评估

基于CODE、GFZ、CNES、武汉大学PRIDE实验室和内部估计的模糊度固定产品,从收敛时间、首次固定时间及定位精度等方面进行PPP-AR固定性能的研究。实验选用2022年40个IGS测站7 d的观测数据和各模糊度固定产品配套使用的精密产品,结果表明,在置信度为95%的静态解算模式下,5种产品在解算时间为1 h时固定解较浮点解定位精度提升最明显,分别提升46.58%(3.4 cm)、41.10%(3.0 cm)、45.21%(3.3 cm)、34.25%(2.5 cm)和41.10%(3.0 cm)。仿动态解算模式下,5种产品E、N方向的定位精度都能达到mm级,U方向较浮点解精度提升较小,其中使用GBM产品的精度提升最小,E、N、U方向分别提高72.73%(2.4 cm)、47.37%(0.9 cm)、5.41%(0.2 cm);提升效果较好的是WUM和COM产品,分别为81.82%(2.7 cm)、63.16%(1.2 cm)、24.32%(1.1 cm)和81.82%(2.7 cm)、63.16%(1.2 cm)、15.58%(0.8 cm)。

两种地电场仪数据形态的对比分析

选取应城地震监测站ZD9A-2B和GEF-2地电场仪的数据进行对比分析,发现二者记录的地电场正常日变化和各种干扰的形态基本一致。GEF-2地电场仪量程更广,包含的高频信息更丰富,抵抗雷电干扰的能力更强,运行更稳定。由两种仪器观测数据计算得到的地电场优势方位角差别不大。研究结果表明,使用高采样率的仪器或有助于发现更多地震孕育过程中产生的脉冲电信号。

Inhibition of Ehrlich ascites carcinoma growth by melatonin:Studies with micro-CT

Melatonin is a versatile indolamine synthesized and secreted by the pineal gland in response to the photoperiodic information received by the retinohypothalamic signaling pathway.Melatonin has many benefits,such as organizing circadian rhythms and acting as a powerful hormone.We aimed to show the antitumor effects of melatonin in both in vivo and in vitro models through the mammalian target of rapamycin(mTOR)signaling pathway and the Argyrophilic Nucleolar Regulatory Region(AgNOR),using the Microcomputed Tomography(Micro CT).Ehrlich ascites carcinoma(EAC)cells were administered into the mice by subcutaneous injection.Animals with solid tumors were injected intraperitoneally with 50 and 100 mg/kg melatonin for 14 days.Volumetric measurements for the taken tumors were made with micro-CT imaging,immunohistochemistry(IHC),real-time polymerase chain reaction(PCR)and AgNOR.Statistically,the tumor tissue volume in the Tumor+100 mg/kg melatonin group was significantly lower than that in the other groups in the data obtained from micro-CT images.In the IHC analysis,the groups treated with Tumor+100 mg/kg melatonin were compared when the mTOR signaling pathway and factor 8(F8)expression were compared with the control group.It was determined that there was a significant decrease(p<0.05).Significant differences were found in the total AgNOR area/nuclear area(TAA/NA)ratio in the treatment groups(p<0.05).Furthermore,there were significant differences between the amount of mTOR mRNA for the phosphatidylinositol 3-kinase(PI3K),AKT Serine/Threonine Kinase(PKB/AKT)genes(p<0.05).Cell apoptosis was evaluated with Annexin V in an in vitro study with different doses of melatonin;It was observed that 100µg/mL melatonin dose caused an increase in the apoptotic cell death.In this study,we have reported anti-tumor effects of melatonin in cell culture studies as well as in mice models.Comprehensive characterization of the melatonin-mediated cancer inhibitory effects will be valuable in advancing our fundamental molecular understanding and translatability of pre-clinical findings to earlier phases of clinical trials.

已知波形信号的时差频差估计方法研究与性能分析

借助深入分析和长期积累,非合作定位系统可以获得关于电视、广播、导航等电磁信号波形的丰富先验信息,对这些信息加以利用有望大幅提高对信号参数的估计精度。该文针对导航、通信等欺骗干扰源及非法用户的无源定位需求,在观测站与辐射源之间存在相对运动的场景下,围绕已知波形信号开展时差频差估计问题研究。首先,通过引入已知的信号波形信息对观测站接收数据进行建模,直观呈现了观测数据与不同观测站信号相对于原始信号时延、频移的关系。随后,充分利用入射信号波形已知这一有利条件,通过估计两个观测站各自的时延和频移,并对不同观测站上的估计结果进行差分,提出了一种针对已知波形信号的双站时差、频差估计方法。在此基础上,该文分析了已知波形信号时频差估计精度的理论下界,揭示了时频差估计精度受观测站接收信号幅度等因素的影响情况,并进一步分析了双站时频差估计精度与单通道时延、频移估计精度之间的关系。最后,借助仿真实验验证了论文所提出的时频差估计方法在不同环境中的参数估计性能,以及信号波形先验信息的利用给时频差参数估计精度带来的提升情况。仿真结果表明,在所设定的信号环境中,该文所提出的方法对低信噪比的适应能力比基于互模糊函数的传统方法增强了15 dB左右;当该方法的参数估计性能达到收敛之后,其时差频差估计精度与CRLB非常吻合。