Clinical Value of the Quantitative Flow Ratio to Predict Long-term Target Vessel Failure in Patients with In-stent Restenosis after Drug-coated Balloon Angioplasty

Objective The study sought to investigate the clinical predictive value of quantitative flow ratio(QFR)for the long-term target vessel failure(TVF)outcome in patients with in-stent restenosis(ISR)by using drug-coated balloon(DCB)treatment after a long-term follow-up.Methods This was a retrospective study.A total of 186 patients who underwent DCB angioplasty for ISR in two hospitals from March 2014 to September 2019 were enrolled.The QFR of the entire target vessel was measured offline.The primary endpoint was TVF,including target vessel-cardiac death(TV-CD),target vessel-myocardial infarction(TV-MI),and clinically driven-target vessel revascularization(CD-TVR).Results The follow-up time was 3.09±1.53 years,and 50 patients had TVF.The QFR immediately after percutaneous coronary intervention(PCI)was significantly lower in the TVF group than in the no-TVF group.Multivariable Cox regression analysis indicated that the QFR immediately after PCI was an excellent predictor for TVF after the long-term follow-up[hazard ratio(HR):5.15×10−5(6.13×10−8−0.043);P<0.01].Receiver-operating characteristic(ROC)curve analysis demonstrated that the optimal cut-off value of the QFR immediately after PCI for predicting the long-term TVF was 0.925(area under the curve:0.886,95%confidence interval:0.834–0.938;sensitivity:83.40%,specificity:88.00;P<0.01).In addition,QFR≤0.925 post-PCI was strongly correlated with the TVF,including TV-MI and CD-TVR(P<0.01).Conclusion The QFR immediately after PCI showed a high predictive value of TVF after a long-term follow-up in ISR patients who underwent DCB angioplasty.A lower QFR immediately after PCI was associated with a worse TVF outcome.

Measurements of NO_2 mixing ratios with topographic target light scattering-differential optical absorption spectroscopy system and comparisons to point monitoring technique

A topographic target light scattering-differential optical absorption spectroscopy （＇IbTaL-DOA~） system is de- veloped for measuring average concentrations along a known optical path and studying surface-near distributions of atmospheric trace gases. The telescope of the ToTaL-DOAS system points to targets which are located at known dis- tances from the measurement device and illuminated by sunlight. Average concentrations with high spatial resolution can be retrieved by receiving sunlight reflected from the targets, A filed measurement of NO2 concentration is performed with the ToTaL-DOAS system in Shijiazhuang in the autumn of 2011. The measurement data are compared with con- centrations measured by the point monitoring technique at the same site. The results show that the ToTaL-DOAS system is sensitive to the variation of NO2 concentrations along the optical path.

Robust Broadband Beam-Forming Based on the Feature of Underwater Target Radiated Noise

To the problem of the unknown underwater target detection, according to the feature that the underwater target radiated noise contains the stable line spectrum, a weighted method based on the main-to-side lobe ratio （MSLR） is proposed for broadband beam-forming. This weighted method can be implemented by using the following steps. Firstly, optimize the spatial spectrum of each frequency unit by the second-order cone programming （SOCP）, and obtain the optimized spatial spectrum with lower side lobe. Secondly, construct weighting factors based on the MSLR of the optimized spatial spectrums to from weight factors. Lastly, cumulate the spatial spectrum of each frequency unit via the weight statistical method of this paper. This method can restrain the disturbance of background noise, enhance the output signal-to-noise ratio （SNR）, and overcome the difficulty of traditional four-dimensional display. The theoretical analysis and simulation results both verify that this method can well enhance the spatial spectrum of line spectrum units, restrain the spatial spectrum of background noise units, and improve the performance of the broadband beam-forming.

Flexible Calibration Method for 3D Laser Scanner System

In this paper, a flexible high-precision calibration method suitable for industrial field was proposed. The complexity of the coordinate transformation was simplified by choosing the camera coordinate system as the unified reference coordinate system. A flexible planar calibration pattern was introduced to the calibration process, which can be arbitrarily placed and from which the known feature points can be extracted to construct other unknown feature points. With the known intrinsic parameters, the laser projector plane equation was fitted by the multi-noncollinear points, which were acquired through the principle of triangulation and the projective invariance of cross ratio. With this method, the strict alignment and multiple times of coordinate transformation can be avoided. Experimental results showed that the arithmetic mean of the root mean square(RMS) error of distance was 0.000 7 mm.

Transmission Degradation of Femtosecond Laser Pulses in Opened Cone Targets

Irradiated by femtosecond laser pulses with different energies, opened cone targets behave very differently in the transmission of incident laser pulses. The targets, each with an opening angle of 71° and an opening of 5 μm, are fabricated using standard semiconductor technology. When the incident laser energy is low and no pre-plasma is generated on the side walls of the cones, the cone target acts like an optical device to reflect the laser pulse, and 15% of the laser energy can be transmitted through the cones. In contrast, when the incident laser energy is high enough to generate pre-plasmas by the pre-pulse of the main pulse that fills the inner cone, the cone with the plasmas will block the transmission of the laser, which leads to a decrease in laser transmission compared with the low-energy case with no plasma. Simulation results using optical software in the low-energy case, and using the particle-in-cell code in the high-energy case, are primarily in agreement with the experimental results.

Improved AR-Based GLRT Detector for Range-Spread Targets in Compound-Gaussian Clutter without Secondary Data

The problem of adaptive radar detection in compound-Gaussian clutter without secondary data is considered in this paper.In most practical applications,the number of training data is limited.To overcome the lack of training data,an autoregressive（AR）-process-based covariance matrix estimator is proposed.Then,with the estimated covariance matrix the one-step generalized likelihood ratio test（GLRT） detector is designed without training data.Finally,detection performance of our proposed detector is assessed.

Calibration of LRFD Format for Steel Jacket OffshorePlatform in China Offshore Area(2): Load, Resistance and Load Combination Factors

Adopting the load and resistance factor design format, the design method for steel jaeket platform structures is developed. Firstly, the limit state equations and design format for steel jacket platform structures are introduced. Then, the ratio of live load effect to dead load effect is estimated. The target reliabilities for design of offshore structures in China offshore area are calibrated by past practice in API RP2A-WSD code. The load and resistance factors are optimized by minimizing the difference within the target reliability and the resulting reliability over the range of load effect ratios. Considering the concurrence of different loads, load combination factors are obtained through an optimization process, and the relation between the load combination factor and load correlation coefficient is established. Finally, the design formulae for steel jacket structures in China offshore area are recommended.

A method of line spectrum extraction based on target radiated spectrum feature and its post-processing

To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum that the high intense and stable line spectrum is superimposed on the wide continuous spectrum.This method modifies the traditional beam forming algorithm by calculating and fusing the beam forming results at multi-frequency band and multi-azimuth interval,showing an excellent way to extract the line spectrum when the interference and the target are not in the same azimuth interval simultaneously.Statistical efficiency of the estimated azimuth variance and corresponding power of the line spectrum band depends on the line spectra ratio(LSR)of the line spectrum.The change laws of the output signal to noise ratio(SNR)with the LSR,the input SNR,the integration time and the filtering bandwidth of different algorithms bring the selection principle of the critical LSR.As the basis,the detection gain of wideband energy integration and the narrowband line spectrum algorithm are theoretically analyzed.The simulation detection gain demonstrates a good match with the theoretical model.The application conditions of all methods are verified by the receiver operating characteristic(ROC)curve and experimental data from Qiandao Lake.In fact,combining the two methods for target detection reduces the missed detection rate.The proposed post-processing method in2-dimension with the Kalman filter in the time dimension and the background equalization algorithm in the azimuth dimension makes use of the strong correlation between adjacent frames,could further remove background fluctuation and improve the display effect.

A spawning particle filter for defocused moving target detection in GNSS-based passive radar

Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooperative target motion is usually difficult to be compensated,as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective.Consequently,the moving target in GBPR image is usually defocused,which aggravates the difficulty of target detection even further.In this paper,a spawning particle filter(SPF)is proposed for defocused MTD.Firstly,the measurement model and the likelihood ratio function(LRF)of the defocused point-like target image are deduced.Then,a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF)as their parent.After that,based on the PF estimator,the SPF algorithm and its sequential Monte Carlo(SMC)implementation are proposed with a novel amplitude estimation method to decrease the target state dimension.Finally,the effectiveness of the proposed SPF is demonstrated by numerical simulations and pre-liminary experimental results,showing that the target range and Doppler can be estimated accurately.

Waveform Design for Cognitive Radar with Deterministic Extended Targets in the Presence of Clutter

Adjusting radar transmitted waveform to its environment is one of the most important roles in cognitive radar;having the capability of updating transmitted waveforms in different applications is a key point. It has been shown in many studies that if the waveform is designed according to the target and clutter characteristics, the detection performance will improve significantly. The uncertainty of the target radar signatures decreases via maximizing MI and the probability of extended target detection is increases via maximizing SNR. In this paper, a waveform design approach based on maximizing both SNR and MI and with regard to target and clutter shape is presented. The detection performance for proposed waveform is compared with previous proposed waveforms. The present paper compares different scenarios of target and clutter and using the probability of detection as a cost function to investigate the advantages and disadvantages of each waveform in different scenarios which are mainly discussed in this text. The desired waveform for cognitive radar is selected based on simultaneously making compromises between SNR and MI, which plays an important role in cognitive radar systems and based on the assumption addressed in the text, the best waveform transmitted into the environment.

滚仰式光电吊舱对地目标的平移运动补偿

由于挂载于某无人飞行平台上的滚仰式光电吊舱具有极大的速高比,因此在对地观测时,会在光电传感器的曝光时间内产生较大像移,使图像变得模糊不清,从而影响成像质量;同时,快速刷新的视频场景使操作手很难发现感兴趣的目标,也给跟踪捕获带来困难。针对此情况,本文提出利用惯导及光电吊舱信息求取相对目标运动的角速度,并通过设备的反向运动补偿来消除载体平移运动的不利影响。同时,本文还给出了补偿的应用条件限制及误差分析,并就目标距离、补偿角速度与观测角度、飞行高度的关系进行了仿真,接着对惯导测量误差及框架角误差对补偿角速度误差的影响进行了仿真分析。经过实际的挂飞试验验证表明:在不考虑光电吊舱运动范围受限情况下,光电视轴可长时间持续稳定地指向任一目标区域,输出清晰稳定的图像而不受载体平移运动的影响,从而给操作手的观测及操作带来极大便利。

双重响应异常约束的无人机目标跟踪

针对无人机跟踪目标易受视角变化、部分遮挡、背景杂波等因素影响而难以完成对目标的鲁棒跟踪问题,提出一种双重响应异常约束的无人机目标跟踪算法。首先,通过计算局部响应变化向量和全局响应峰值旁瓣比,在线动态更新空间正则化参数,降低边界效应的影响;其次,针对STRCF算法中的时间正则项的参数固定的问题,提出响应异常峰值判断机制,计算次峰响应系数,并将其融合到时间正则化参数上进行实时更新,避免目标模板变异造成跟踪漂移问题;目标函数通过交替方向乘子法迭代求解最优解。在UAV123、UAV20L和DTB70三个无人机数据集上与代表性的目标跟踪算法进行大量实验,结果表明,在UAV123数据集上的精确度达到71.7%,在DTB70数据集上的跟踪平均速度达到48.3帧/s。本文结果与现有相关滤波类无人机目标跟踪算法相比表现较好,具有较高的实时性和鲁棒性。

基于分层强化学习的低过载比拦截制导律

为解决低过载比和纯角度量测等约束下的三维机动目标拦截制导问题,提出了一种基于分层强化学习的拦截制导律。首先将问题建模为马尔科夫决策过程模型,并考虑拦截能量消耗与弹目视线角速率,设计了一种启发式奖赏函数。其次通过构建具有双层结构的策略网络,并利用上层策略规划阶段性子目标来指导下层策略生成所需的制导指令,实现了拦截交战过程中的视线角速率收敛,以保证能成功拦截机动目标。仿真结果验证了所提出的方法较增强比例导引具有更高的拦截精度和拦截概率,且拦截过程的需用过载更低。

距离像先验引导的扩展目标检测方法

扩展目标检测通常采用距离像能量积累检测的方法,由于距离像信息掌握不完备,陷落损失会降低检测性能。本文提出一种距离像先验引导的扩展目标检测方法,通过利用距离像包络模先验,对信号进行积累以提升检测性能。该方法考虑了复距离像与复高斯白噪声的相干叠加与相位预测不准的因素,采用将观测数据取模的检测模型,基于似然比检测(Likelihood Ratio Test,LRT)理论推导了低信噪比下的特征平方匹配检测器。该检测器将目标复距离像的包络模与观测数据的包络模进行平方匹配,并通过门限判决来判断目标是否存在。包络模先验的获取是通过从ISAR图像提取二维散射中心,向对应姿态角下的雷达视线方向进行投影,来获得目标近似的一维散射中心模型,再由该模型进一步生成目标距离像的包络模先验。同时,本文从理论与实验两方面分析了能量检测器和特征平方匹配检测器之间的关系,通过散射中心模型重构与暗室测量的方法获取数据进行了实验验证。实验结果表明:在低信噪比下,距离像先验引导的特征平方匹配检测器能有效提升目标的检测性能,并且对先验模型失配的情况具有良好的适应性。

基于贝叶斯滤波理论的目标命中概率估计与判决方法研究

为了降低兵器试验中目标命中概率指标的判决错误率,提出了基于贝叶斯滤波理论的目标命中概率估计和判决方法。该方法构建了目标命中概率与试验观测数据的统计数学模型,依据贝叶斯滤波理论推导了目标命中概率后验概率密度函数、后验均值估计以及均方误差的解析表达式,并给出了基于目标命中概率后验均值估计的判决方法。依据不同的真实目标命中概率生成观测数据,分别利用传统方法和所提方法进行了估计和判决试验。结果表明:所提方法判决错误率仅为传统方法的1/3,证明所提方法具有可行性。

基于流形变换的信息几何雷达目标检测方法

基于信息几何的目标检测方法为解决雷达目标检测问题提供了新的技术途径。该文以矩阵信息几何理论为基础,考虑复杂非均匀环境下,回波信杂比低,目标与杂波在矩阵流形上区分性差,导致传统信息几何检测器性能受限的问题,提出一种基于流形变换的信息几何检测器。具体地,该文建立了流形到流形映射变换,并提出待检测单元与杂波中心的几何距离联合优化方法,从而增强变换后流形上目标与杂波的区分性。通过仿真和实测数据验证,所提方法具有较好检测性能。基于仿真数据实验,当信杂比高于1 dB时,所提方法的检测概率可以达到60%以上,同时,实测数据验证结果表明,当检测概率达到80%时,相较于传统信息几何检测器,该文所提检测器能够提升检测信杂比为3~6 dB。

基于随机共振的水下目标微弱回波信号增强检测

针对低信噪比下主动声呐探测水下目标的微弱回波信号检测难题,本文提出了一种基于随机共振的微弱回波信号增强检测方法。该方法通过建立频移变尺度随机共振系统,与输入高频微弱回波信号、随机噪声相匹配,实现微弱回波信号的共振增强;进而利用乘积谱与谱峭度构建目标回波亮点增强检测指标,有效提升微弱回波亮点的能量集中程度,抑制杂波及虚假成分干扰。仿真结果表明:在低信噪比下,随机共振系统输出信噪比增益可达5 dB以上,微弱目标回波亮点检测结果更加直观便捷,杂波干扰得到大幅抑制。海试数据处理结果进一步验证了所提方法的有效性和可靠性。

基于双波段LiTaO_(3)热释电探测器的目标温度识别研究

针对热释电红外探测器在温度识别领域的难题,本文设计了一种基于长/中波双波段钽酸锂(LiTaO_(3))热释电多元探测器,建立了基于机器学习算法的目标温度识别模型。分析了不同黑体温度下的两波段辐射量与双波段比值的变化趋势,测试了双波段比值与黑体温度的关系以及分析了双波段比值在仿真与实测中的误差,研究了基于热释电数据的决策树、随机森林算法的最优参数选择以及所搭建的模型识别准确率。研究结果表明:基于该探测器构建的温度识别系统的识别准确率最高可大于90%,为基于热释电的目标温度识别提供了一种新的技术路径,拓宽了热释电红外探测器的应用范围。

基于沥青混凝土搅拌站的配合比设计与实践

针对当前沥青混合料目标配合比与生产配合比相互独立、脱节的情况,提出基于沥青混凝土搅拌站的配合比设计理念。弱化目标配合比设计流程,强调以目标配合比在沥青混凝土搅拌站进行试生产,从而得出各档热料比例,以此作为生产配比进行配合比设计。然后以此设计结果在沥青混凝土搅拌站进行联调联试,最终通过微调目标配合比来实现目标配合比与生产配合比在沥青混凝土搅拌站上的协调统一。

复杂背景下小样本声呐图像目标检测

水下目标检测具有重要意义,在军事和民用领域都发挥着重要作用。实际场景中可以获得的声呐图像非常有限,且声呐图像的信噪比较低,无法得到较好的检测结果。因此,本文引入小样本学习,基于Faster RCNN两阶段目标检测算法,选择不同的策略对模型进行优化,得到了较好的检测结果并验证了小样本目标检测在声呐图像领域的可行性。根据混响对声呐图像的影响进行仿真实验,得到不同混响背景下的声呐图像,对比分析了不同数据集下训练模型的检测性能。实验结果表明,在训练样本中增加混响信号可以提高低信噪比条件下的目标检测精度。