Transverse Zeeman background correction method for air mercury measurement

By utilizing a natural mercury lamp, the transverse Zeeman background correction method, which is used for trace mercury measurement in air, is studied. In this paper, a natural mercury lamp is used as a light source, and is placed in a 1.78-T magnetic field. The lamp emits two linearly polarized light beams σ± and π of 253.65-nm resonance line, which are used as bias light and absorbing light, respectively. A polarization modulation system is used to allow σ± and π light beams to pass through alternately with a certain frequency. A multipath optical cell with 12-m optical path is used to increase optical distance. Based on the system described above, the influence caused by UV absorbing gases, such as NO2, SO2, acetone, benzene, and O3, is analyzed. The results show that it may reduce the detection limit when the concentrations of these gases exceed 83.4 ppm, 20.3 ppm, 142.3 ppm, 0.85 ppm, and 0.55 ppm, respectively. The detection limit of the system is calculated and can achieve up to 1.44 ng/m3 in 10 minutes. Measurements on mercury sample gas and air are carded out, and the measured data are compared with the data of RA-915 mercury analyzer （Russia）. The result shows that the correlation coefficient reaches up to 0.967. The experimental results indicate that the transverse Zeeman background correction method can be used to quantify trace mercury in air with high-precision.

Background correction in near-infrared spectra of plant extracts by orthogonal signal correction

In near-infrared (NIR) analysis of plant extracts, excessive background often exists in near-infrared spectra. The detection of active constituents is difficult because of excessive background, and correction of this problem remains difficult. In this work, the orthogonal signal correction (OSC) method was used to correct excessive background. The method was also compared with several classical background correction methods, such as offset correction, multiplicative scatter correction (MSC), standard normal variate (SNV) transformation, de-trending (DT), first derivative, second derivative and wavelet methods. A simulated dataset and a real NIR spectral dataset were used to test the efficiency of different background correction methods. The results showed that OSC is the only effective method for correcting excessive background.

Correction of cosine oscillation to the improved correlation method of estimating the amplitude of gravitational background signal

In the measurement of G with the angular acceleration method,the improved correlation method developed by Wu et al.（Wu W H,Tian Y,Luo J,Shao C G,Xu J H and Wang DH 2016 Rev.Sci.Instrum.87 094501） is used to accurately estimate the amplitudes of the prominent harmonic components of the gravitational background signal with time-varying frequency.Except the quadratic slow drift,the angular frequency of the gravitational background signal also includes a cosine oscillation coming from the useful angular acceleration signal,which leads to a deviation from the estimated amplitude.We calculate the correction of the cosine oscillation to the amplitude estimation.The result shows that the corrections of the cosine oscillation to the amplitudes of the fundamental frequency and second harmonic components obtained by the improved correlation method are within respective errors.

Study on element detection and its correction in iron ore concentrate based on a prompt gamma-neutron activation analysis system

A prompt gamma-neutron activation analysis(PGNAA) system was developed to detect the iron content of iron ore concentrate. Because of the self-absorption effect of gamma-rays and neutrons, and the interference of chlorine in the neutron field, the linear relationship between the iron analytical coefficient and total iron content was poor, increasing the error in the quantitative analysis. To solve this problem, gamma-ray self-absorption compensation and a neutron field correction algorithm were proposed, and the experimental results have been corrected using this algorithm. The results show that the linear relationship between the iron analytical coefficient and total iron content was considerably improved after the correction. The linear correlation coefficients reached 0.99 or more.

CODING-ORIENTED MULTI-VIEW VIDEO COLOR CORRECTION

Color inconsistency between views is an important problem to be solved in multi-view video applications, such as free viewpoint television and other three-dimensional video systems. In this paper, by combining with multi-view video coding, a coding-oriented multi-view video color correction method is proposed. We first separate foreground and background in first Ggroup Oof Ppictures (GOP) by using SKIP coding mode. Then by transferring means and standard deviations in backgrounds, color correction is performed for each frame in GOP, and multi-view video coding is performed and used to renew the backgrounds. Experimental results show the proposed method can obtain better perform-ances in color correction and multi-view video coding.

基于背景抑制和分类校正的小样本目标检测方法

为进一步提升小样本条件下对空中来袭目标的检测识别成功率,提出一种基于背景抑制和分类校正的小样本目标检测方法。首先,针对空中来袭目标背景前景易混淆问题,在区域候选网络前端引入背景抑制模块,通过抑制背景特征和增强前景特征来减轻目标背景对检测的影响;其次,在背景抑制模块后插入特征聚合模块,聚焦目标特征,通过缓解小样本条件导致目标特征难提取、不明显的问题,校正网络模型的分类参数;最后,在检测头网络中引入对比分支,增强了类别内相似性和类别间独特性,缓解来袭目标“类间相似性高,类内差异性大”的问题,实现了对网络分类的进一步校正。实验结果表明,所提出的算法在1、2、3、5、10 shot实验中均表现最佳,平均精度分别达到28.3%、32.8%、39.9%、42.9%和56.2%,提升了小样本空中来袭目标的检测性能。

基于自适应伽马校正的异常驾驶行为检测方法

针对低照度条件下重型卡车司机异常驾驶行为检测方法存在检测准确率低、检测速度慢等问题,结合图像自适应增强方法和轮廓定位检测思想,提出一种基于自适应伽马校正的异常驾驶行为检测方法。对传入视频图像进行自适应伽马校正,通过抑制噪声、改善暗部和提升信息熵来提高识别准确率。基于图像灰度值和信息熵对双阈值伽马函数进行自适应调节,从而获得更丰富的边缘信息和色彩信息。利用K-近邻背景建模法将驾驶员前景图像分离以确定检测区域,通过边缘检测进行驾驶员头部和手部轮廓识别,获得关键定位点间的欧氏距离,并进行异常驾驶行为判断。在此基础上,结合异常行为次数和时间阈值,解决环境干扰和图像噪声的问题。实验结果表明,与单尺度Retinex、多尺度Retinex以及自适应直方图均衡方法相比,所提方法在提高检测准确率的同时有效提高了检测速度,能在不同环境下有效检测异常驾驶行为。

基于Voigt线型的尿液中芬太尼类表面增强拉曼光谱解析

在全球范围内频繁发生芬太尼类物质滥用与致死案件,人体中芬太尼类物质的检测与识别愈发重要。芬太尼类物质在经过人体一段时间后,仍有一部分原体随着尿液排出,因此可通过检测尿液中芬太尼类物质反映其毒品滥用史。表面增强拉曼光谱(SERS)具有快速、高灵敏、易操作等特点,适合尿液中芬太尼类物质的现场检测与分析。但尿液中尿素等物质的背景峰与芬太尼类物质SERS特征峰高度重合,芬太尼类物质特征峰被尿液背景峰所掩盖,这对尿液中芬太尼类的光谱识别造成了很大的干扰。结合Voigt线型建立谱峰解析模型,对尿液与芬太尼类物质重叠部分进行谱峰分析。针对SERS光谱噪声与荧光等因素对谱峰解析模型的干扰,采用无约束Nelder-Mead算法对模型进行优化与计算,利用该算法对迭代参数初始值不敏感的特点,提高谱峰解析模型的准确度。根据SERS光谱半峰宽的特征对解析峰集合进行筛选,对SERS光谱的尿液背景峰进行扣除,以还原芬太尼类SERS光谱1000与1030 cm^(-1)处谱峰特征。实验结果与现象表明,利用Voigt线型建立的谱峰解析模型对尿液中芬太尼类SERS光谱拟合度均达到99%以上,能够通过解峰集合的筛选还原尿液中芬太尼类SERS光谱特征,还原光谱与芬太尼类特征峰的半峰宽与峰比例等特点均高度一致。在空白尿液SERS光谱进行解析时,其解析峰集合中不含有芬太尼类物质的特征谱峰,可以有效区分空白尿液与含芬太尼类物质尿液。利用相似系数(HQI)对还原光谱片段(935~1100 cm^(-1))进行识别,能有效区分尿液中奥芬太尼、呋喃芬太尼、乙酰芬太尼三种芬太尼,并提升光谱之间的区分度。该解析模型有望为尿液中芬太尼类的识别与判断提供解决实际问题的途径。

高压密闭消解-电感耦合等离子体质谱(ICP-MS)法测定土壤背景点样品中的29种元素

土壤环境背景值监测样品的检测工作特点是分析项目多、前处理方法和分析方法复杂,缺乏简便多元素同时测定的分析方法。采用氢氟酸-硝酸体系高压密闭消解方法处理土壤样品,采用电感耦合等离子体质谱(ICP-MS)法同时测定锂、铍、硼、锗、钼、银、镉、铟、锡、碲、锑、铯、镨、钕、钐、铕、钆、铽、镝、钬、铒、铥、镱、镥、钽、钨、铊、铋和铀元素。系统研究了不同消解体系、质谱干扰和消除方法并选择了合适的测定同位素,采用土壤标准物质对方法适用性进行了考察,29种元素的检出限在0.003~0.469 mg/kg,测定值的相对标准偏差在1.0%~9.3%,测定值与标准值的相对误差在-14%~17%。方法满足土壤环境背景值监测工作的测试需求,可实现一次前处理多元素同时测定,提高了工作效率。

基于局部梯度的红外线列扫描图像小目标检测

线列探测器受外界环境中不同像素点特性的影响,导致红外线列扫描到的图像存在一定误差。为了提升红外线列扫描图像中小目标检测的准确性,提出基于局部梯度的红外线列扫描图像小目标检测方法。首先分析红外线列扫描小目标的成像原理,获取小目标及其周围环境的像素特点,校正线列探测器的误差,得到理想光强下的小目标图像。结合灰度值和梯度方向一致法抑制图像背景,突出小目标本身,再利用特征分解的方法减少边缘背景对小目标的影响,最后,利用阈值对小目标实施分离,实现小目标检测的目的。实验结果表明,所提方法的信噪比增益高、背景抑制效果好、虚警率低,小目标的检测精度高。

Single-element Anomaly Mapping from Stream Sediment Geochemical Landscapes Aided by Digital Terrain Analysis

The identification of anomalies within stream sediment geochemical data is one of the fastest developing areas in mineral exploration.The various means used to achieve this objective make use of either continuous or discrete field models of stream sediment geochemical data.To map anomalies in a discrete field model of such data,two corrections are required:background correction and downstream dilution correction.Topography and geomorphology are important factors in variations of element content in stream sediments.However,few studies have considered,through the use of digital terrain analysis,the influence of geomorphic features in downstream dilution correction of stream sediment geochemical data.This study proposes and demonstrates an improvement to the traditional downstream dilution correction equation,based on the use of digital terrain analysis to map single-element anomalies in stream sediment geochemical landscapes.Moreover,this study compares the results of analyses using discrete and continuous field models of stream sediment geochemical data from the Xincang area,Tibet.The efficiency of the proposed methodology was validated against known mineral occurrences.The results indicate that catchment-based analysis outperforms interpolation-based analysis of stream sediment geochemical data for anomaly mapping.Meanwhile,the proposed modified downstream dilution correction equation proved more effective than the original equation.However,further testing of this modified downstream dilution correction is needed in other areas,in order to investigate its efficiency further.

Underwater image enhancement by maximum-likelihood based adaptive color correction and robust scattering removal

Underwater images often exhibit severe color deviations and degraded visibility,which limits many practical applications in ocean engineering.Although extensive research has been conducted into underwater image enhancement,little of which demonstrates the significant robustness and generalization for diverse real-world underwater scenes.In this paper,we propose an adaptive color correction algorithm based on the maximum likelihood estimation of Gaussian parameters,which effectively removes color casts of a variety of underwater images.A novel algorithm using weighted combination of gradient maps in HSV color space and absolute difference of intensity for accurate background light estimation is proposed,which circumvents the influence of white or bright regions that challenges existing physical model-based methods.To enhance contrast of resultant images,a piece-wise affine transform is applied to the transmission map estimated via background light differential.Finally,with the estimated background light and transmission map,the scene radiance is recovered by addressing an inverse problem of image formation model.Extensive experiments reveal that our results are characterized by natural appearance and genuine color,and our method achieves competitive performance with the state-of-the-art methods in terms of objective evaluation metrics,which further validates the better robustness and higher generalization ability of our enhancement model.

5G背景下中职生网络沉迷隐患及矫正策略刍议

5G背景又称信息时代背景,5G技术是目前最新的通讯技术,与之前的4G和3G技术相比,5G技术更加快速,数据传输更加便捷。中职学生在初中阶段由于学习成绩较差,不得不选择进入中职学校学习,以获得一定的劳动技能。目前,部分中职学生沉迷于网络,导致思想观念和行为意识被误导,养成许多不好的生活和学习习惯,严重影响身心健康。文章论述5G的概念和特征,分析中职学生网络沉迷的原因,指出中职学生网络沉迷的不良影响,探究矫正中职学生网络沉迷的策略。

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塞曼背景校正石墨炉原子吸收光谱法直接测定尿中铬

目的建立直接测定尿中铬的塞曼背景校正石墨炉原子吸收光谱方法。方法尿样经2%硝酸对倍稀释,以磷酸二氢铵-硝酸镁为基体改进剂,通过对实验条件的探究,使用塞曼背景校正石墨炉原子吸收光谱法直接进样测定其中的铬,标准曲线法定量。结果该方法在质量浓度0~50.0μg/L浓度范围内,线性关系良好,相关系数r为0.9996,检出限为0.14μg/L,相对标准偏差(RSD)1.24%~4.51%,加标回收率91.5%~104.5%,冻干人尿中铬标准物质测定结果在标准值允许范围内。结论该方法操作便捷、准确度好、灵敏度高、检出限低,可应用于尿中铬含量的测定。

基于地球化学背景的多图幅系统误差校正——以区域地球化学调查数据Au元素为例

针对区域地球化学图件中出现的含量等值线环绕子区边界现象,以Au的多个图幅拼接为例,使用了分幅标准化法、衬度返回法及定和化法3种方法对地质大调查以来新方法获得的某成矿带区域地球化学数据进行系统误差校正,校正后编制地球化学等量线图显示,所采用的3种校正方法对于研究区数据存在的系统误差都不能达到较好的调平效果。针对研究区数据特点,尝试在分幅标准化法和衬度返回法基础上提出基于地球化学背景的误差校正方法,进一步对4种方法校正后数据参数特征及编制地球化学等量线图进行对比。基于地球化学背景的误差校正方法对研究区达到了较好的数据校正效果,并对校正前后数据进行相关对比和检验,满足化探数据中存在的系统误差属于线性误差这一基本假设,在实际应用中,可供地球化学数据系统误差校正灵活地使用,以取得更好的应用效果。

基于改进灰色模型的能源消费预测研究

为提高灰色模型的预测精度,在一次累加生成序列呈指数增长趋势的前提下,利用预估-校正技术对灰色模型的背景值进行了改进.数值实验表明,改进模型有效地改善了模型的预测精度,并拓展了模型的适用范围.最后,结合等维递补技术,利用提出的改进模型,对到2015年中国能源消费需求进行了预测.预测结果表明,到2010年和2015年,中国能源需求总量将高达31.9和36.3亿吨标准煤,这将为中国能源供应安全带来巨大挑战.

拉曼光谱的荧光背景扣除及其用于药物聚类分析

拉曼光谱分析中,由于有机分子或样品中污染物的荧光影响,常会使拉曼光谱产生高背景信号,以致其拉曼光谱吸收信号被淹没。利用自行开发的软件包baselineWavelet,本文对醋酸泼尼松片和格列本脲片的拉曼光谱进行了荧光背景扣除研究,采用主成分分析和随机森林算法对它们进行聚类分析,得到了较好的结果。通过这2种药物的拉曼光谱聚类分析结果,检验了该背景扣除算法的有效性和准确性,并讨论了荧光背景对拉曼光谱聚类分析的影响。结果说明,荧光背景对拉曼光谱聚类分析影响很大,在分析前必须预先扣除。

悬浮液进样自吸扣背景石墨炉原子吸收光谱法测定高纯氧化铝中铜、铁和钠含量

采用悬浮液-自吸扣背景石墨炉原子吸收法测定了高纯氧化铝中痕量元素铜、铁、钠含量。实验对灰化温度、原子化温度和自吸扣背景灯电流等石墨炉原子吸收工作条件等进行了优化,确定了最佳测定条件。样品测试采用标准水溶液进行校正,方法准确性采用氧化铝AKP-30在高温高压和浓硫酸密闭条件下溶解样品进样分析测定结果与文献报道的其他测定方法结果进行了对比。研究表明本方法简单,结果可靠,适用于氧化铝中痕量元素的快速测定。校正曲线的线性相关性大于0.9990,方法对铜、铁、钠的检出限分别为0.66,2.5,0.13ng·g-1,相对标准偏差小于5.2%。

基于模板匹配和边缘检测的车标定位方法

车标定位在车标识别系统中具有关键作用,为解决倾斜的车辆图像及多种车标背景纹理的车标定位问题,提出了一种新的车标定位方法。先进行车辆图像的倾斜校正,再通过三绝对值最大梯度方法定位出车灯带区域,利用车标与车牌、车灯的位置先验知识进行车标粗定位,并根据车标背景纹理特征利用模板匹配和边缘检测方法进行车标精定位。该方法充分利用了车标的先验知识和背景纹理特征,并将模板匹配与边缘检测技术相结合,提高了车标定位的准确率。实验结果表明,该方法既适用于倾斜的车辆图像又适用于多种车标背景纹理,具有很好的车标定位效果。