LIC color texture enhancement algorithm for ocean vector field data based on HSV color mapping and cumulative distribution function

Texture-based visualization method is a common method in the visualization of vector field data.Aiming at adding color mapping to the texture of ocean vector field and solving the ambiguity of vector direction in texture image,a new color texture enhancement algorithm based on the Line Integral Convolution(LIC)for the vector field data is proposed,which combines the HSV color mapping and cumulative distribution function calculation of vector field data.This algorithm can be summarized as follows:firstly,the vector field data is convoluted twice by line integration to get the gray texture image.Secondly,the method of mapping vector data to each component of the HSV color space is established.And then,the vector field data is mapped into HSV color space and converted from HSV to RGB values to get the color image.Thirdly,the cumulative distribution function of the RGB color components of the gray texture image and the color image is constructed to enhance the gray texture and RGB color values.Finally,both the gray texture image and the color image are fused to get the color texture.The experimental results show that the proposed LIC color texture enhancement algorithm is capable of generating a better display of vector field data.Furthermore,the ambiguity of vector direction in the texture images is solved and the direction information of the vector field is expressed more accurately.

Morphological Structure and Genetic Mapping of New Leaf-Color Mutant Gene in Rice (Oryza sativa)

Leaf-color mutations are a widely-observed class of mutations, playing an important role in the study of chlorophyll biosynthesis and plant chloroplast structure, function, genetics and development. A naturally-occurring leaf-color rice mutant, Baihuaidao 7, was analyzed. Mutant plants typically exhibited a green-white-green leaf-color progression, but this phenotype was only expressed in the presence of a stress signal induced by mechanical scarification such as transplantation. Prior to the appearance of white ~eaves, mutant plant growth, leaf color, chlorophyll content, and chloroplast ultrastructure appeared to be identical to those of the wild type. After the changeover to white leaf color, an examination of the mutated leaves revealed a decrease in total chlorophyll, chlorophyll a, chlorophyll b, and carotenoid content, a reduction in the number of chloroplast grana lamella and grana, and a gradual degradation of the thylakoid lamellas. At maturity, the mutant plant was etiolated and dwarfed compared with wild-type plants. Genetic analysis indicated that the leaf mutant character is controlled by a recessive nuclear gene. Genetic mapping of the mutant gene was performed using an F2 population derived from a Baihuaidao 7 ~ Jiangxi 1587 cross. The mutant gene was mapped to rice chromosome 11, positioned between InDel markers L59.2-7 and L64.8-11, which are separated by approximately 740.5 kb. The mutant gene is believed to be a new leaf-color mutant gene in rice, and is tentatively designated as gwgl.

The Role of Color Doppler Ultrasound Arterial Mapping for Decision Making in the Treatment of Patients with Lower Extremity Peripheral Arterial Disease

Purpose: To assess the efficacy of color Doppler imaging for decision making in the treatment of patients with lower extremity peripheral arterial disease (PAD) compared to digital subtraction angiography (DSA). Materials and Methods: Color Doppler scan was done on patients suspected for lower limb PAD, a day prior to the DSA which was done by a vascular surgeon. Also, for the patients who were candidates for endovascular intervention based on the color Doppler arterial mapping results, endovascular interventions were performed at the same time if the DSA findings are correlated with the color Doppler map. The grading for evaluated segments was normal, insignificant stenosis (<50%), hemodynamically significant stenosis (≥50%) and occlusion. We yielded the diagnostic efficacy indices of Doppler for detecting arterial stenosis in each 18 different arterial segments below the renal arteries including, infrarenal aorta, common and external iliac, common femoral, superficial femoral (proximal, middle and distal segments), deep femoral, popliteal artery, tibioperoneal trunk, anterior and posterior tibial arteries (proximal, middle and distal segments) and peroneal artery (proximal and distal segments). Then, we yielded the kappa agreement between Doppler and DSA findings considering the grade of stenosis in 18 arterial segments separately. Results: Totally 115 lower extremities (2045 arterial segments) were evaluated in 90 patients [mean age: 60.8 ± 8.9 (range: 47 - 84 years old)] of which 68 (75.6%) were men. The sensitivity of color Doppler for all arterial segments was 90% or higher except for common iliac artery, distal segment of superficial femoral artery and proximal segments of anterior and posterior tibialis and peroneal arteries. However, the specificity was 89% or higher, in all arterial segments. Kappa agreement was 0.72 or higher in all segments (All P-Values 0.001). Conclusion: This study suggests that considering excellent capability of color Doppler sonography in the evaluation of lower extremity arterial disease, color Doppler arterial mapping is sufficient for decision making in the treatment of these patients and can reduce the rate of diagnostic angiography.

APPLYING OONN TO SOLVE MAP-COLORING PROBLEM

For solving the map-coloring problems,this paper presents an energy function,amore effective dynamic equation and a more simple convergence condition.For the first time westudy the map-coloring problems in the way of connecting discrete Hopfield neural network withthe orthogonal optimization,and as a practical example,a color map of China is given.

A Map Coloring Method

Different vertices are colored in a plan. Adjacent vertices are colored dif-ferently from nonadjacent vertices, which are colored the same color. One color is used for a single point, two colors are used for points without a loop, and a maximum of four colors are used for points with a loop. A maximum of four colors are used to color all points. .

利用Surfer实现自动绘制渐变色平剖图及其在MAPGIS中的应用

提出利用Surfer绘制渐变色剖面平面图的构想,阐述了绘图数据格式及渐变色填充方法,编制程序自动调用Surfer 8.0软件,实现了自动绘图功能,制作出渐变色剖面平面图,并实现了MAPGIS环境的图形转换。实现的剖面图具有层次分明,立体感强,与MAPGIS转换操作简单容易等优点。

基于MAPGIS的等高线矢量化研究

论述了基于MAPGIS平台的等高线矢量化方法,并对矢量化过程中出现的彩色地形图、等高线与图廓相交、断线及等高线方向不清等问题作了适当的方法论述。

Homδ-Jordan李color代数的Hom-Nijienhuis算子

通过给出Homδ-Jordan李color代数的定义,研究其代数结构及Hom-Nijienhuis算子.结果表明,一个Hom-Nijienhuis算子与一个双线性算子在满足适当条件下能得到一个正则Homδ-Jordan李color代数形变,且该形变是平凡的.

基于特征图像组合与改进ResNet-18的电能质量扰动识别方法

针对传统电能质量扰动(power quality disturbance,PQD)识别体系中单一图像特征信息受限与算法识别能力不足等问题,依据特征融合的思想,提出一种基于特征图像组合与改进ResNet-18的PQD识别方法。首先,对PQD信号进行变分模态分解(variational mode decomposition,VMD)得到一系列固有模态函数(intrinsic mode functions,IMFs)与残差分量;其次,将IMFs、残差分量、原始扰动信号与Subtract分量纵向拼接成分量矩阵,利用信号-图像转化方法生成特征分量彩色图;再次,对原始扰动信号进行连续小波变换(continuous wavelet transform,CWT)生成小波时-频图;最后,将特征分量彩色图与小波时-频图组合输入改进的六通道ResNet-18中训练学习并完成扰动识别。通过仿真对PQD识别方法进行分析并将其与目前常用识别体系进行比较。结果表明,所提方法具有较好的抗噪性能并且能够更好地提取PQD特征信息,达到更高的识别准确率。

Genetic Analysis and Gene Mapping of Light Brown Spotted Leaf Mutant in Rice

A light brown spotted-leaf mutant of rice was isolated from an ethane methyl sulfonate （EMS）- induced IR64 mutant bank. The mutant, designated as Ibsll （light brown spotted-leaf 1）, displayed light brown spot in the whole growth period from the first leaf to the flag leaf under natural summer field conditions. Agronomic traits including plant height, growth duration, number of filled grains per panicle, seed-setting rate and 1000-grain weight of the mutant were significantly affected. Genetic analysis showed that the mutation was controlled by a single recessive gene, tentatively named Ibsll（t）, which was mapped to the short arm of chromosome 6. By developing simple sequence repeat （SSR） markers, the gene was finally delimited to an interval of 130 kb between markers RM586 and RM588. The Ibsll（t） gene is likely a novel rice spotted-leaf gene since no other similar genes have been identified near the chromosomal region. The genetic data and recombination populations provided will facilitate further fine-mapping and cloning of the gene.

Four Color Theorem and Applied Geophysics

A selection of a number of geophysical methods to solve different geological, geodynamical, environmental, archaeological and other problems usually has no theoretical substantiation. The solution to this “four color” mathematical problem is able to assume that two independent geophysical methods are sufficient theoretically to characterize the geological-geophysical peculiarities of the area under study.

基于BSA-seq的大豆棕色荚皮L2基因定位

大豆荚皮的颜色是重要的驯化性状和表型特征,与炸荚习性和躲避捕食关系紧密。大豆荚皮颜色主要由2对等位基因控制,其中棕色荚皮L2基因尚未被鉴定。为了在大豆基因组上对该基因进行鉴定,为大豆棕色荚皮相关基因功能解析和育种应用提供一定的理论基础。以栽培大豆中龙优203(黄色荚皮)和野生大豆FF1235(黑色荚皮)为亲本构建F 2分离群体进行遗传分析。利用F 2群体棕色豆荚和黄色豆荚单株构建混池进行BSA-seq定位分析,并在此基础上进行重组交换单株分析。结果表明,大豆棕色荚皮性状为1对等位基因控制的质量性状。棕色荚皮L2基因关联区域位于3号染色体0~0.75 Mb的区段。进一步开发InDel分子标记进行精细定位,获得具有多态性的InDel引物7对。最终将棕色荚皮位点定位于3号染色体上的Indel-L2-3~Indel-L2-6,物理距离为344 kb。定位区间内共有候选基因32个,其中Glyma.03G005700基因注释为异丙基苹果酸聚合酶,与已发现的黑色荚皮基因L1(Glyma.19G120400)高度同源,其功能为将4-羟基丙酮酸转化为红果酸和番石榴酸,可能是调控大豆棕色荚皮形成的关键基因。

长城色彩折射的建造技艺、管理制度与民族智慧

与宫殿、寺庙、石窟等建筑遗产相比,长城在材料色彩方面“乏善可陈”,甚至还出现专有名词“长城灰”,将长城的色彩特征固化。本文通过无人机采集明长城全线图像并引入图像类人工智能提取其主色调,首次量化各段长城色彩、绘制全线色彩地图,证明长城“富彩”;并结合材料成分分析、史料挖掘,首次揭示色彩背后蕴含的长城材料色彩法则、色彩质量评价标准与奖励办法,以及以色立威、以建止战的核心意图。这一成果尝试填补古代建筑色彩研究的长城缺环、揭示长城作为军事遗产的材料色彩艺术造诣,挖掘出未开发长城段新的遗产景观资源,从全新的视角助推长城国家文化公园建设。

段状管道轴向数据可视化的颜色映射函数优化方法研究与应用

轴向数据经常以伪色彩方式在三维管道模型上进行可视化,颜色映射函数对可视化效果有决定性影响。虽然现在已有很多颜色映射函数,且其对符合常见分布特点的数据有较好效果,但它们对分布比较特殊的数据还是难以取得理想效果,所以人们针对各种特殊分布数据研究颜色映射函数。如果三维管道轴向数据由若干段组成,并且呈现“段内差别小,段间差距大”的分布特点,那么常见映射函数难以同时表现段内的细微差异和段之间的显著差别,从而影响可视化效果。针对这个问题,提出一种基于控制点的映射函数优化方法,以改善段状数据的可视化效果。实验分析使用了合成数据来验证方法的有效性,且使用了聚变堆冷却管的辐射量数据验证方法的有效性,两种数据均验证了该方法的有效性。

四色问题与跨境贸易区块链去中心化设计研究

区块链技术的去中心化特征为解决商业生态中“缺乏信任”这一核心问题提出新思路,通过“四色猜想”,归纳出“4+1”跨境贸易区块链应用基本模式和扩展模式,并且采用平行进口实际场景对上述内容进行验证。结果表明,该模式不仅能够构建安全可信的跨境区块链数字机制,满足平行进口这一新型贸易业态要求,而且可以有效促进贸易便利,可以为区块链技术应用、跨境贸易机制设计提供一定参考。

茶树品种‘白鸡冠’与‘福云6号’遗传连锁图谱构建

【目的】近年来对茶树白化性状调控机理的研究逐渐增多,但到目前为止白化性状的基因调控机制仍然未知。通过构建‘白鸡冠’与‘福云6号’高密度遗传连锁图谱,为后续白鸡冠叶色基因定位奠定基础。【方法】创建白鸡冠(♀)与福云6号(♂)F1代遗传分离群体,采用SLAF-seq技术和HighMap软件开发SNP分子标记,构建高密度遗传连锁图。【结果】用茶树参考基因组作电子酶切预测,选用HaeIII酶切方案。SLAF标签长度选择314~364 bp,预测到230000个SLAF标签。SLAF标签在基因组各染色体上分布基本均匀,酶切方案可行。建库准确性评估发现,对照样数据的双端比对效率为85.98%,酶切效率为91.82%,说明SLAF建库正常。本实验共获得828 448 417条reads(165.67 Gb)测序数据,测序平均Q30为93.94%,平均GC含量为43.67%,样本GC分布正常。获得SNP标记5 975 507个,成功分型的有643 601个,用于遗传图谱构建的标记有500 988个,最终上图标记有7 967个,总图距为2 754.59 cM,上图标记完整度为99.84%,共构建出15个高密度遗传连锁群。【结论】利用白鸡冠与福云6号F1代遗传分离群体构建出含15个连锁群的高密度遗传连锁图谱。

基于数据映射和胶囊网络的轴承故障诊断方法

传统深度学习模型自适应提取振动信号故障特征,实现端到端轴承故障诊断。然而,振动监测信号为非常复杂的非稳态时序信号,若深度网络直接以原始振动信号为输入,数据之间的非线性耦合作用会极大影响模型对故障特征的提取效率。目的为降低故障信号之间强非线性耦合作用,解决卷积神经网络对空间约束信息丢失的问题,提升轴承故障诊断性能,方法本文提出一种基于数据映射和胶囊网络(capsule network,CapsNet)的轴承故障诊断方法。首先,将图像处理领域中具有细化颜色特征能力的颜色空间模型(color names,CN)引入故障数据预处理中,将原始低维空间数据映射至高维空间,提升故障数据空间区分度;其次,针对映射后数据维度较高且具有一定冗余,影响故障诊断效率的问题,引入主成分分析(principal compo⁃nent analysis,PCA)法提取故障数据主元信息,降低数据维度;最后,考虑到胶囊网络有效提取空间约束信息的能力,将CapsNet作为故障诊断的骨干网络对故障特征进行识别和分类。结果使用CWRU、XJTU-SY数据集对该方法进行验证,实验结果表明,该方法在两种数据集上故障诊断准确率均达98%以上,与其他基于深度学习的故障诊断方法进行对比,该方法的诊断性能具有一定优势。结论本文方法可对故障数据进行有效解耦,提升数据之间的空间区分度,获得较高的轴承故障诊断精度。

基于颜色–耳标参数映射的时空信息可听化方法

随着时空信息的爆炸式增长,如何在保留地图可视化传统优势的基础上实现时空信息可听化是一个值得研究的方向。因此,首先以2022年纽约市PM_(2.5)污染情况为例,采用通用克里金法对PM_(2.5)污染浓度数据进行插值,得到纽约市2022年365幅PM_(2.5)浓度专题地图;其次,提取每张专题地图的色相、饱和度、明度平均值,并将它们与PM_(2.5)浓度数据的标准差分别映射为音色、音高、音强、音长四个维度的耳标参数,使用Sibelius编排创建乐曲,实现纽约市2022年PM_(2.5)数据的可听化;最后,对可听化的污染意象信息传递效果进行评估。结果显示:(1)污染浓度最严重比最不严重和不严重信息的传递效果好;(2)污染浓度变化最大和变化较大比变化最小信息的传递效果好;(3)污染浓度地域差异变化最大比变化最小信息的传递效果好;(4)音强和音高传递污染浓度信息的效果最佳,被试者的认可度也最高,而音长传递污染地域差异的效果最差;(5)被试者对于使用以上可听化形式来传递污染信息的态度持中立到同意的态度,但在理解上存在一定难度。实验拓展了时空信息可听化的研究内容,丰富了对于地图可听化技术的探索。

基于云模型的煤矿安全风险四色图动态管控系统研究

四色图是一种规范的、新型的安全可视化管理方法。针对井下工作环境复杂多变、隐患排查不到位、煤矿安全风险防范四色图科学性与指导性不强等问题,为提高风险辨识评估的准确性及煤矿安全管理水平,紧跟煤矿安全管理信息化、智能化的发展趋势,建立了基于云模型的煤矿安全风险四色图动态管控系统。该系统主要由硬件和软件构成,利用内嵌于系统的云模型对煤矿各风险点进行风险等级评估,并根据结果展现对应的风险等级颜色,克服了传统煤矿安全风险调控效率较低的弊端,将风险评价等级和防控措施相结合,实现了煤矿安全风险的实时评估和动态管理。云模型-四色图的组合通过云模型解决分级过程中系统的模糊性和不确定性,并利用四色图对风险分级进行直观展示,为科学的煤矿风险管理提供理论支撑。该系统在山西潞安五阳矿井成功应用,为更多煤矿安全管理信息化、智能化发展提供支持。

面向海岛海岸带区域的高分遥感影像智能化色彩增强方法

原始高空间分辨率海岛海岸带遥感影像往往存在影像灰暗、偏色、地物信息较难辨识的现象。为及时获取清晰、信息丰富、反差适中、亮度均匀的海岛礁遥感影像,满足日益强烈的海岛海岸带地理信息保障需求,针对海岛海岸带高空间分辨率遥感影像,该文提出一种深度学习结合改进直方图匹配的智能化调色方法。首先,进行数据重采样与自适应分块获取抽稀影像;其次,应用MBLLEN网络对抽稀影像进行真彩色增强;最后,采用改进直方图匹配的方法对原始影像进行色彩映射,最终得到符合人眼视觉、色彩一致、细节丰富的遥感影像。采用主客观相结合的方式综合评价调色效果,结果表明:相较于Retinex,HE和MASK等常用调色方法,该文算法结果更符合人眼视觉、色彩一致、细节丰富,可有效改善海岛海岸带高空间分辨率遥感影像视觉效果,较好地保留原始地物的细节信息,大幅提升调色效率。