基于Gram-Schmidt正交化算法的水下目标回波检测

提出了一种基于Gram-Schmidt正交化算法的水下目标回波检测方法.该方法利用Gram-Schmidt正交化算法实现对干扰背景的预白化,通过归一化匹配滤波器可完成对水下目标回波的检测.对仿真数据和实验数据的处理验证了该方法的有效性.

当归六黄汤加减联合化痰祛瘀调瘿方对甲状腺功能亢进症患者TR-Ab、TPOAb表达的影响

目的研究当归六黄汤加减联合化痰祛瘀调瘿方对甲状腺功能亢进症患者促甲状腺激素受体抗体(TR-Ab)、甲状腺过氧化物酶抗体(TPOAb)表达的影响。方法选取2019年1月—2021年1月在医院就诊的甲状腺功能亢进症患者148例,根据治疗方法的不同分为当归六黄汤组和联合组,各74例。当归六黄汤组给予当归六黄汤加减治疗,联合组在当归六黄汤组用药的基础上给予化痰祛瘀调瘿方治疗,两组均持续治疗8周。检测患者在治疗前及治疗4周、8周后TR-Ab、TPOAb表达水平。结果两组治疗后4周、8周TR-Ab、TPOAb、T_(3)、T_(4)、FT_(3)、FT_(4)、Vm水平及甲状腺肿大、突眼、心悸心慌、多食易饥评分低于两组治疗前,RI、PI水平高于两组治疗前(P<0.05)。联合组治疗后4周、8周TR-Ab、TPOAb、T_(3)、T_(4)、FT_(3)、FT_(4)、Vm水平及甲状腺肿大、突眼、心悸心慌、多食易饥评分低于当归六黄汤组4周、8周,RI、PI水平高于当归六黄汤组4周、8周(P<0.05)。与当归六黄汤组相比,联合组治疗总有效率升高(P<0.05)。结论当归六黄汤加减联合化痰祛瘀调瘿方能够改善甲状腺功能亢进症患者TR-Ab、TPOAb表达水平,缓解患者临床症状,疗效显著。

佩兰挥发油化学成分的分析(英文)

本实验采用同时蒸馏萃取法(SDE)提取佩兰挥发性成分,测得佩兰挥发油的含量为2.73%,利用气相色谱-质谱(GC-MS)联用方法从佩兰挥发油中分离并确认出33种化学成分,用峰面积归一化法通过G1710BA化学站数据处理系统得出各化学成分在挥发油中的百分含量,其中主要成分为2H-1-苯并吡喃-2-酮(12.58%)、麝香草酚(4.38%)、2,4,5,6,7,8-羟基-1,4,9,9-四甲基-3H-3a,7桥亚甲基甘菊环(4.50%)、氧化石竹烯(5.27%)、1-甲基-4-(1-丙基)-酚(3.97%)、1,1a,4,5,6,7,7b,8-八氢-1,1,7,7a四甲基-2H-环丙基[a]萘-2-酮(3.62%)。

基于反对称双正交小波变换的多尺度归一化分割方法

针对工业检测现场拍摄的微电子元件图像产生的模糊和噪声叠加现象,提出基于反对称双正交小波变换的多尺度归一化分割方法.首先通过反对称双正交小波的多尺度边缘检测方法对待处理图像进行平滑、去噪及轮廓提取;然后利用重构后的边缘轮廓、强度值和图像的约束矩阵求得权重矩阵;最后利用谱分割技术得出图像的特征向量,并离散化后得到最终的分割结果。对工业显微镜采集的电路板零件和部分故障图像以及PASCAL VOC2012分割数据集中的图像进行测试,并与归一化割方法、多尺度归一化割方法、最小割/最大流方法和基于约束参数的最小化割方法在精确率、查全率、F-测量、平均绝对误差和运行时间上进行了对比,结果表明,该算法的分割质量更理想.

基于统计模型和GVF-Snake的彩色目标检测与跟踪

为了能使传统监视系统具备目标自动检测与跟踪能力,提出了一种基于统计模型和GVF(grad ient vectorflow)-Snake的彩色目标检测与跟踪算法。该算法可用于解决在静态背景下通过彩色视频信息来对运动目标进行自动检测与跟踪的问题,同时可直接给出目标轮廓的数学表示,并可简化后续目标识别算法的设计。该算法首先采用归一化RGB空间与灰度空间相结合的模型取代单一灰度模型来消除阴影对目标检测的影响;接着在此模型的基础上对差分图像进行GMM(Gaussian m ixture model)建模,并构造运动边界图像,然后将静态图像轮廓提取算法GVF-Snake引入运动图像中,并通过修改能量项,使其能够跟踪运动目标的轮廓,最后针对Snake初始轮廓需要手工设定的问题,提出一种根据目标区域自动初始化轮廓的方法,为加快GVF-Snake的收敛速度,还采用一阶差分算法来预测下一时刻目标轮廓的位置。实验结果证明,该算法对刚性和非刚性两类目标都有较好的跟踪效果,可应用于智能监视和交通监控等领域。

极大似然优化EM算法的汉语分词认知模型

针对标准EM算法在汉语分词的应用中还存在收敛性能不好、分词准确性不高的问题,本文提出了一种基于极大似然估计规则优化EM算法的汉语分词认知模型,首先使用当前词的概率值计算每个可能切分的可能性,对切分可能性进行"归一化"处理,并对每种切分进行词计数,然后针对标准EM算法得到的估计值只能保证收敛到似然函数的一个稳定点,并不能使其保证收敛到全局最大值点或者局部最大值点的问题,采用极大似然估计规则对其进行优化,从而可以使用非线性最优化中的有效方法进行求解达到加速收敛的目的。仿真试验结果表明,本文提出的基于极大似然估计规则优化EM算法的汉语分词认知模型收敛性能更好,且在汉语分词的精确性较高。

通用微处理器等效老化试验方法

针对不同工艺、不同设计的功能全兼容集成电路等效老化的需要,提取出了集成电路等效老化的特征参数—“归一化老化电流”指标α,并讨论了等效老化信号的确定方法。结合集成电路等效老化信号确定方法,以CPU486为研究对象,给出通用CPU等效老化试验方案,为评估和比较不同CPU的质量和可靠性提供了统一的试验平台。

2000—2014年疏勒河流域植被覆盖时空变化

基于MODIS NDVI数据,借助Arc GIS和Matlab软件,采用线性趋势分析、M-K检验法和Hurst指数等方法,对2000—2014年疏勒河流域植被覆盖时空变化进行研究。结果表明,近15 a来,疏勒河中下游平均植被覆盖呈快速、平稳增加趋势,上游呈波动性轻微上升态势;整个流域植被覆盖明显改善,显著和极显著改善区占30.86%,集中于坡度小于20°的上游山区以及中下游灌区周边,显著和极显著退化区不足1%,集中在中下游的自然植被区;整个流域在2004年后进入相对暖湿期,6—8月降水量和均温对上游植被生长影响最大,呈显著正相关关系,且降水的影响大于均温,中下游植被受气候要素的影响明显小于上游;流域未来植被改善区占18.63%,主要为持续改善区,集中在移民安置点周边、疏勒河中下游自然保护区以及祁连—阿尔金山北部山麓西段;退化区占14.25%,主要是由现在的改善区转化而来,集中于党河南山、野马山、照壁山等坡度小于20°的上游山区。

邯郸粉质黏土归一化性状分析

在固结不排水试验基础上,用两种归一化方法分析了邯郸粉质黏土的性状,得到了归一化参数,指出土的应力—应变关系存在归一化性状,且此性状是由归一化应力来体现的,从而为土的本构关系研究提供参考资料。

奇异积分方程关于归一化条件的稳定性

探讨了奇异积分方程关于归一化条件的稳定性 ,得到了关于稳定性的更广泛的结果 .

家庭农场数字化系统研究——以宿州市埇桥区国家现代农业示范区为例

以安徽省宿州市埇桥区国家现代农业示范区为研究对象,构建了符合地理国情监测和作物生长监测的数字化农场系统。该系统具有数据处理、空间分析、农情监测、预报预测等主要功能模块,为家庭农场的精准化管理和智能农业应用奠定了理论基础。

A normalized wavefield separation cross-correlation imaging condition for reverse time migration based on Poynting vector

Prestack reverse time migration（PSTM） is a common imaging method; however low-frequency noises reduce the structural imaging precision. Thus, the suppression of migration noises must be considered. The generation mechanism of low-frequency noises is analyzed and the up-, down-, left-, and right-going waves are separated using the Poynting vector of the acoustic wave equation. The computational complexity and memory capacitance of the proposed method are far smaller than that required when using the conventional separation algorithm of 2D Fourier transform. The normalized wavefield separation crosscorrelation imaging condition is used to suppress low-frequency noises in reverse time migration and improve the imaging precision. Numerical experiments using the Marmousi model are performed and the results show that the up-, down-, left-, and right-going waves are well separated in the continuation of the wavefield using the Poynting vector. We compared the imaging results with the conventional method, Laplacian filtering, and wavefield separation with the 2D Fourier transform. The comparison shows that the migration noises are well suppressed using the normalized wavefield separation cross-correlation imaging condition and higher precision imaging results are obtained.

DAMAGE CLASSIFICATION BY PROBABILISTIC NEURAL NETWORKS BASED ON LATENT COMPONENTS FOR TIME-VARYING SYSTEM

A new approach to damage classification for health monitoring of a time-varylng system is presented. The functional-series time-dependent auto regressive moving average （FS-TARMA） time series model is applied to the vibration signal observed in the time-varying system for estimating the TAR/TMA parameters and the innovation variance. These parameters are the functions of the time, represented by a group of projection coefficients on the certain functional subspace with specific basis functions. The estimated TAR/TMA parameters and the innovation variance are further used to calculate the latent components （LCs） as the more informative data for health monitoring evaluation, based on an eigenvalue decomposition technique. LCs are then combined and reduced to numerical values （NVs） as feature sets, which are input to a probabilistic neural network （PNN） for the damage classification. For the evaluation of the proposed method, numerical simulations of the damage classification for a tlme-varylng system are used, in which different classes of damage are modeled by the mass or stiffness reductions. It is demonstrated that the method can identify the damages in the course of operation and the change of parameters on the time-varying background of the system.

钍归—化在盆地γ能谱资料处理中的应用

在应用γ能谱资料寻找砂岩型铀矿的过程中,要尽可能地消除非矿化因素引起的干扰,提取与铀矿化有关的信息。介绍了钍归一化的原理及特点,采用与矿化有关的元素迁移信息的钍归一化方法,分析了二连盆地东部的γ能谱资料,揭示了该区放射性元素的分布特征、地球化学作用和后期铀元素的迁移与富集。结合其他地质资料,分析了钾剩差的变异区(正、负高值区)及铀剩差正高值区形成的原因,同时指出了经过钍归一化处理所得到的铀剩差正高值区应为氧化与还原作用过渡带的直接指示,也是该区进一步寻找砂岩型铀矿的重要标志。

Characteristics of Spatial and Temporal Vegetation Index Variability and Its Responses to Temperature and Precipitation in Mongolia

The Mongolian Plateau,a vital ecological barrier in northern China,is of great importance for studying vegetation dynamics in Mongolia against the background of climate warming.Such studies can enhance our understanding of regional vegetation responses to global warming and contribute to the establishment of a stronger ecological barrier in northern China.Here,we analyzed the spatial and temporal characteristics of the NDVI(normalized difference vegetation index)in Mongolia using 8 km resolution GIMMS NDVI3g data from 1990 to 2022,along with temperature,precipitation,and elevation data.Trend analysis and correlation methods were used to examine the relationships between the NDVI and temperature,as well as precipitation.The results showed four important aspects of these relationships.(1)The NDVI in Mongolia increased significantly from 1990 to 2022 at a rate of 0.0015 yr^(-1)(P<0.05).(2)Mongolia’s NDVI increased from 1990 to 2022 in 60.73%of the country.Of this total,the area with a significant increase accounted for 31.67%and was concentrated on the eastern and western edges.The area experiencing a significant decrease accounted for 15.67%and was mainly located on the southwestern edges.(3)The NDVI analysis revealed significant increasing trends in all regions except for those at elevations of 1500-2000 m.The greatest rate of increase was observed between 500 and 1000 m,and the increasing trend weakened as elevation continued to increase before gradually becoming significant again.Additionally,the NDVI increased significantly across different slopes,and the rate of increase decreased as the slope increased.(4)From 1990 to 2022,Mongolia’s NDVI was mostly negatively correlated with temperature.This occurred over 66.75%of the total land area,with 17.21%of the region exhibiting a significant negative correlation,mainly in the southwest.Conversely,the NDVI demonstrated a positive correlation with precipitation,encompassing 86.71%of the total land area.Approximately 40.44%of the region had a significant positive correlation,primarily in the southwest.In conclusion,throughout the experimental period,the vegetation state in Mongolia improved.However,due to the warming and drying climate,more attention should be paid to vegetation degradation in the south-central region.

Prediction of pre-oxidation efficiency of refractory gold concentrate by ozone in ferric sulfate solution using artificial neural networks

An artificial neural network model was developed to predict the oxidation of refractory gold concentrate （RGC） by ozone and ferric ions. The concentration of ozone and ferric ions, pulp density, oxygen amount, leaching time and temperature were employed as inputs to the network; the output of the network was the percentage of the ferric extraction iron from RGC. The multilayered feed-forward networks were trained by 33 sets of input-output patterns using a back propagation algorithm; a three-layer network with 8 neurons in the hidden layer gave optimal results. The model gave good predictions of high correlation coefficient （R2=0.966）. The predictions by ANN are more accurate when compared with conventional multivariate regression analysis （MVRA）. In addition, calculation with ANN model indicates that temperature is the predominant parameter and ozone concentration is the lesser influential parameter in the pre-oxidation process of refractory gold ore. The ANN neural network model accurately estimates the ferric extraction during pretreatment process of RGC in gold smelter plants and can be used to optimize the process parameters.

On the naturalization of lexical choices in Sino-English translator training

Through analyzing the difference between British lexis and Americanism and the translation teaching status quo related with lexical choices, the author elaborates on translator competence training in the lexical choice of Sino-English translation, and who puts forwards several suggestions on how to facilitate the effective communication between the business persons through naturalizing the lexical choices in Sino-English translation.

Spline-based multi-regime traffic stream models

In order to develop optimal multi-regime traffic stream models, a new method that integrates cluster analysis and B-spline regression is presented. First, for identifying the proper number of regimes, the K-means and the fuzzy c-means methods are applied in cluster analysis to actual traffic data, which suggests that dividing the traffic flow into two or three clusters can best reflect intrinsic patterns of traffic flows. Such information is then taken as guidance in spline regression, thus significantly reducing the computational burden of estimating spline models. Spline regression is used to estimate the locations of knots and the coefficients of the model so that the global error can be minimized. Model analysis results demonstrate that the proposed spline models have better fitting and generalization capability than the conventional models. In addition, the new method is more flexible in terms of data fitting and can provide smoother traffic stream models.

Five-year major clinical outcomes between first-generation ana second- generation drug-eluting stents in acute myocardial infarction patients underwent percutaneous coronary intervention

Background There were limited data comparing the major clinical outcomes between first-generation （1G）-drug eluting stentts （DES） and second-generation （2G）-DES in patients with acute myocardial infarction （AMI） after percutaneous coronary intervention （PCI） during very long follow-up periods. We thought to investigate the comparative efficacy and safety of 2G-DES compared with 1G-DES in AMI patients during 5-year follow-up periods. Method A total of 1016 eligible AMI patients who underwent PCI with 1G-DES [paclitaxel-, sirolimus-, 1G-zotarolimus-eluting stent （endeavor~ or endeavor sprintS）, n = 554] or 2G-DES [2G-zotarolimus （endeavor resolute~）- or everolimus-eluting stent, n = 462] were enrolled. The primary endpoint was the occurrence of major adverse cardiac events （MACE） defined as total death, non-fatal myocardial infarction （MI）, target lesion revascularization （TLR）, target vessel revascularization （TVR）, non-target vessel revascularization （Non-TVR） and the secondary endpoint was stem thrombosis （ST） at 5 years. Results Two propensity score-ma- tched （PSM） groups （232 pairs, n = 464, C-statistic = 0.802） were generated. During the 5-year follow-up period, the cumulative incidence of TLR [hazard ratio （HR）： 3.133; 95% confidence interval （CI）： 1.539-6.376; P = 0.002], TVR （HR： 3.144; 95% CI： 1.59645.192; P = 0.001） and total revascularization rate （FIR： 1.874; 95% CI： 1.086-3.140; P = 0.023） were significantly higher in 1G-DES compared with 2G-DES after PSM. However, the incidence of total death, non-fatal MI and ST were similar between the two groups. Conclusion In this single-center and all-comers registry, 2G-DES＇s superiorities for TLR, TVP, and total revascularization in AMI patients suggested during 5-year clinical follow-up periods.