Analysis of identification methods of key nodes in transportation network

The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.     

Composition and antioxidant activity of anthocyanins from Aronia melanocarpa extracted using an ultrasonic-microwave-assisted natural deep eutectic solvent extraction method

A time-saving, efficient, and environmentally friendly ultrasonic-microwave-assisted natural deep eutectic solvent (UMAE-NADES) extraction method was developed for the extraction of anthocyanins from Aronia melanocarpa. Eight different natural eutectic solvents were screened initially, and choline chloride-glycerol was selected as the extraction solvent. The extraction conditions were optimized using the response surface methodology, and the extraction rate of anthocyanins was higher than those achieved using the traditional ethanol method, natural deep eutectic solvent extraction method, and ultrasonic-microwave-assisted ethanol method. Six anthocyanins, including cyanidin-3-O-galactoside, cyanidin-3-O-glucoside, cyanidin-3-O-arabinoside, cyanidin-3-O-xyloside, cyanidin-3,5-O-dihexoside, and the dimer of cyanidin-hexoside were identified and extracted at a purity of 448.873 mg/g using high performance liquid chromatography-mass spectrometry (HPLC-MS). The compounds extracted using UMAE-NADES had higher antioxidant capacities than those extracted by the other three methods. The UMAE-NADES demonstrated significant efficiency toward the extraction of bioactive substances and has potential utility in the food and pharmaceutical industries.     

A method for automatic identification of water and fat images from a symmetrically sampled dual-echo Dixon technique

Sampling water and fat signals symmetrically (i.e., at 0° and 180° relative phase angles) in a dual-echo Dixon technique offers high intrinsic tolerance to phase fluctuations in postprocessing and maximum signal-to-noise performance for the separated water and fat images. However, identification of which image is water and which image is fat after their separation is not possible based on the phase information alone. In this work, we proposed a semiempirical automatic image identification method that is based on the intrinsic asymmetry between the water and fat chemical shift spectra. Specifically, the approximately bimodal feature of the fat spectra and the observation that most in vivo tissues are either predominantly water or predominantly fat are used to construct a spectrum-based algorithm. Additional refinement is accomplished by considering the spatial distribution of the tissues that may have a coexistence of water and fat. The final improved algorithm was tested on a total of 131 three-dimensional patient datasets collected from different scanners and found to yield correct water and fat identification in all datasets.     

Carbon K‐edge spectra of carbonate minerals

Carbon K‐edge X‐ray spectroscopy has been applied to the study of a wide range of organic samples, from polymers and coals to interstellar dust particles. Identification of carbonaceous materials within these samples is accomplished by the pattern of resonances in the 280–320 eV energy region. Carbonate minerals are often encountered in the study of natural samples, and have been identified by a distinctive resonance at 290.3 eV. Here C K‐edge and Ca L‐edge spectra from a range of carbonate minerals are presented. Although all carbonates exhibit a sharp 290 eV resonance, both the precise position of this resonance and the positions of other resonances vary among minerals. The relative strengths of the different carbonate resonances also vary with crystal orientation to the linearly polarized X‐ray beam. Intriguingly, several carbonate minerals also exhibit a strong 288.6 eV resonance, consistent with the position of a carbonyl resonance rather than carbonate. Calcite and aragonite, although indistinguishable spectrally at the C K‐edge, exhibited significantly different spectra at the Ca L‐edge. The distinctive spectral fingerprints of carbonates provide an identification tool, allowing for the examination of such processes as carbon sequestration in minerals, Mn substitution in marine calcium carbonates (dolomitization) and serpentinization of basalts.     

在BES实验中用神经元网络法鉴别e,μ,π

研究了两种不同的神经元网络法,BP网络和LVQ网络,对北京谱仪(BES)实验中e,μ,π粒子的鉴别,取得了较常规方法要好的结果.用于训练和检验的μ子样本来自宇宙线事例,e和π粒子则是由真实实验数据精选的,虽然样本本身具有非均匀的动量谱,但BP网络的检验结果给出的粒子选择效率在整个动量区间却仍然具有相当均匀的分布,LVQ网络稍逊之.至少是在我们研究的这一课题中证明了BP网络的模式识别功能要优于LVQ网络.     

光谱成像检测法鉴别中药材

使用基于液晶可调谐滤光器的光谱成像检测系统,对西洋参及市面上常用做假冒西洋参的伪品桔梗进行了在体检测.该系统能对检品进行连续光谱成像,光谱分辨率可达0.5 nm,配合使用Matlab软件对图像信号进行处理和分析.获取了400 nm～680 nm之间的连续荧光光谱图像,通过对比西洋参、桔梗的特征光谱曲线,及进行相关系数的计算,有效地区分了西洋参及桔梗.为西洋参的真伪鉴别提供了一定的帮助.     

矿物组分快速定量提取模型及其应用

矿物成分快速鉴定是提高遥感矿产勘探、遥感矿物填图以及诸多地学研究等工作效率的关键。由于技术等各方面的限制,国内外针对矿物快速分析的模型和软件较少。20世纪90年代以来近红外光谱仪在技术上的突破和计算机的发展使得近红外光谱技术在矿物快速识别领域的应用变得可行,先后出现了基于吸收位置的反演模型(模型一)和基于波形匹配的反演模型(模型二)。文章提出了特征光谱线性反演模型。经美国地质调查局矿物光谱库(USGS)端元混合实验数据验证,该模型精度接近100%,远优于模型一和二。对新疆包古图地区地表随机所采23个样本分析,该模型平均精度为64.6%,另外两模型分别为：33.8%和8.1%,优于模型一和二。虽精度尚低于传统镜下鉴定方法,该模型具有高效、方便、工作量小、人为误差小等优点,已初步应用于新疆包古图地区遥感矿产勘探工作,有较好的推广前景。     

用丝电流方法快速识别HL-2A等离子体边界

利用等离子体外部测量的磁场信号,使用丝电流方法对HL-2A等离子体边界进行了快速识别。介绍了该方法的原理、相关的测量系统配置和该程序的研制进展。对识别结果进行了讨论。     

一种基于三角形几何结构的星图识别算法

提出了一种新的以星三角形为基本识别单元的几何结构星图识别算法。通过对观测误差的预处理,将该算法星三角形的匹配过程转换为一个没有误差的三角形识别问题。引入一个能部分描述三角形结构的特征量,将导航三角形的识别所需的特征匹配数量降低,而多三角形的组合有效地提高了正确识别率。仿真实验表明,该算法所需导航星库容量小,识别效率高,误识率低,实时性和鲁棒性优于传统的三角形星图识别算法。     

A new technique for the identification of ultrasonic flaw signals using deconvolution

The identification of ultrasonic flaw signals is a difficult task in the angle beam ultrasonic testing of welded joints due to the presence of non-relevant signals from the geometric reflectors such as weld-roots and counter-bores. This paper describes a new approach to identify ultrasonic flaw signals in such a problematic situation. A similarity function is defined as the deconvolution of a target signal by a reference signal. The similarity functions for the same type of flaws/references are symmetric bandlimited impulse-like patterns with larger amplitudes while those for different types of flaws/references are asymmetrical broad patterns with relatively smaller amplitudes. Therefore, ultrasonic signals could be identified by the pattern of the similarity function. In the initial experiments, the proposed technique showed great potential for identifying ultrasonic flaw signals in the inspection of weld joints.