Low-dimensional multi-spectral space for color reproduction based on nonnegative constrained principal component analysis

In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.

Wide-Band Multi-spectral Space for Color Representation

This paper develops a wide-band multi-spectral space for color representationwith Aitken PCA algorithm. This novel mathematical space using the broad-band spectra matchingmethod aims at improving the accuracy of color representation as well as reducing costs forprocessing and storing multi-spectral images. The results show that the space can present ourexperimental original spectral spaces (i. e. Munsell color matt and DIN-6164 color chips) with highefficiency, and that the spanning space with three eigenvectors can present the original space atmore than 98% CSCR, and when 5 eigenvectors are used it can cover almost the whole o-riginal spaces.

Extraction of Soil Organic Matter Information by Multi-spectral Remote Sensing Based on Diverse Landforms

Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil organic matter content in different landforms. The results showed that the spectral reflectance was nega- tively related to soil organic matter content; linear regression analysis of remove was performed throughout the bands using SPSS. When the inversion models were built based on all the bands, better fitting effect was obtained. The precision of in- version models built based on different landforms was higher than those built re- gardless landforms. Compared with the actual value, the identification level of soil organic matter content was 91 65% under the allowable error was 7%. It indicated that the extraction of soil organic matter with inversion model that was built based on different landforrrs was feasible with higher precision.

Extracting Feature Bands for Damaged Rice Leaves by Planthoppers Using Multi-spectral Imaging Technology

[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] The experiment, using multi-spectral imaging system, acquired the multi-spectral images of damaged rice leaves from band 400 to 720 nm by interval of 5 nm. [Result] According to the principle of band index, it was calculated that the bands at 515, 510, 710, 555, 630, 535, 505, 530 and 595 nm were having high band index value with rich information and little correlation. Furthermore, the experiment used two classification methods and calcu-lated the classification accuracy higher than 90.00% for feature bands and ful bands of damaged rice leaves by planthoppers respectively. [Conclusion] It can be con-cluded that these bands can be considered as effective feature bands to identify damaged rice leaves by planthoppers quickly from a large scale of crops.

3D MERGE与3D SPACE STIR序列在腰椎间盘突出症检查中的应用比较

目的:对比三维多回波恢复梯度回波(3D MERGE)、三维可变反转角快速自旋回波(3D SPACE STIR)序列在腰椎间盘突出症(LDH)检查中的应用效果。方法:选择2020年1月~2022年11月收治的135例LDH患者,回顾性分析患者临床和磁共振成像(MRI)资料,所有患者均接受常规MRI扫描及3D MERGE、3D SPACE STIR序列扫描,对比3D MERGE、3D SPACE STIR序列测量神经根直径的一致性,评价两种序列的图像质量参数[信噪比(SNR)、对比噪声比(CNR)]、图像清晰度评分。结果:3D MERGE和3D SPACE STIR序列测量的L3~S1神经根直径比较差异无统计学意义(P>0.05),且两组序列测量的L3、L4、L5和S1直径均显示出较高相关性(r=0.957,0.986,0.975,0.972,P<0.05);3D MERGE序列的SNR及CNR均高于3D SPACE STIR序列,神经根显示分级、图像清晰度评分优于3D SPACE STIR序列,差异有统计学意义(P<0.05)。结论:3D MERGE、3D SPACE STIR序列在LDH神经根直径测量中具有极高一致性,3D MERGE序列较3D SPACE STIR序列能够更清晰显示神经跟的解剖形态,图像质量更好。

我国研究生学术素养研究热点分析(2013—2023年)——基于Cite Space的可视化分析研究

从中国知网数据库检索2013—2023年底国内发表的研究生学术素养研究相关文献,共筛选出259篇相关文献。将文献纳入Cite Space中,分别对作者、机构、关键词等进行可视化分析,并通过Excel绘制年发文量折线图,发现年发文量总体呈现下降趋势。发文作者为教育学领域的居多,发文机构大部分来自于各学校研究所等。高频关键词有研究生、学术道德、学术不端、学术规范、学术素养,并形成了“研究生”“学术道德”“学术不端”“治理”“学术规范”“学术素养”“博士生”“道德理论”“中心和导向”9个聚类。研究者近年来对学术素养相关研究整体呈现下降状态;研究机构以及研究人员结构单一,国家机构对学术素养相关研究较少;但关于“研究生”“学术道德”“学术不端”以及“学术理论”的研究仍有较高热度。

国内“大思政课”研究的现状、热点与展望--基于CiteSpace的核心期刊论文可视化分析

“大思政课”是近年的一个新议题。自习近平总书记作出关于“大思政课”的重要论述以来,“大思政课”建设在全国积极推进,成为新时代用党的创新理论铸魂育人的重要抓手。学界对这一领域的研究成果持续涌现。借助Cite Space文献计量软件对中国知网CNKI数据库中2021-2023年间350篇核心期刊论文的发文量、作者、机构、关键词进行可视化分析,近三年学界的研究热点聚焦“大思政课”的本体论、认识论、价值论、方法论以及一体化等方面。未来,学界还应以多学科交叉和多主体融合实现“大思政课”研究的系统化,以理论和实践结合提升“大思政课”研究的科学化,以破解技术遮蔽与AI赋能强化“大思政课”研究的数字化,以研究反哺教学,不断增强“大思政课”立德树人实效。

基于Cite Space对螺旋藻藻蓝蛋白的研究进展与热点分析

螺旋藻(Spirulina)藻蓝蛋白具有独特的理化特性及生理功能,是药物、食品和化妆品的天然原料,具有较大的开发潜力。为探讨螺旋藻藻蓝蛋白的研究现状与发展前景,对中国知网和Web of Science数据库中1990—2023年发表的文献进行检索并筛选,使用Cite Space软件对文章发文量、研究团队及研究热点进行图谱分析。综合分析可知,国内年发文量偏少,呈平稳趋势;国外年发文量持续上升,尤其近几年发文量迅速增长,且发文量超过了100篇;国外研究热点集中于藻蓝蛋白在食品、医药行业的应用方面,而国内研究热点集中在提取纯化、稳定性、功能活性的研究与应用,下一步应结合研究现状开发适合规模化生产的提取纯化工艺,进一步加强藻蓝蛋白研究的广度与深度;国内外研究群体主要是高校的相关生物技术学院或研究机构等,总体来讲,学者间存在较为密切的合作,但研究机构间尚未形成紧密的合作关系,在地域上比较分散,各大高校和研究机构应突破地区或机构间的各种限制,促进该研究领域的深度融合和快速发展,深入挖掘藻蓝蛋白在各个领域的潜在应用。

基于CiteSpace的红色文创设计可视化分析与方法研究

目的基于CiteSpace概述国内红色文创设计的发展状况,梳理关于红色文创设计的相关方法与理论模型,探讨未来红色文创设计发展的趋势,为研究者提供相关设计思路与发展动向。方法通过对国内相关文献的研究,梳理了红色文创设计的概念与发展现状,归纳了当前红色文创设计中包括文化转译维度、文化层次理论、叙事性设计的三种主要方法与理论模型。结论目前红色文创设计方法较为单一,很难满足用户的不同需求,且缺乏具体针对性的完整理论体系与设计方法。在今后的红色文创设计中,可以综合运用叙事性及文化转译维度等设计理论和手段,对红色文创设计和方法加以探究和创新,打造具有中国特色的红色文创产品,使红色文化得到更好的普及和弘扬。

Robust key point descriptor for multi-spectral image matching

Histogram of collinear gradient-enhanced coding （HCGEC）, a robust key point descriptor for multi-spectral image matching, is proposed. The HCGEC mainly encodes rough structures within an image and suppresses detailed textural information, which is desirable in multi-spectral image matching. Experiments on two multi-spectral data sets demonstrate that the proposed descriptor can yield significantly better results than some state-of- the-art descriptors.

MULTI-SPECTRAL AND HYPERSPECTRAL IMAGE FUSION USING 3-D WAVELET TRANSFORM

Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional （3-D） feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures： Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling （RIBSR）method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution （A＆S） rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A＆S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.

Chlorophyll Content Retrieval of Rice Canopy with Multi-spectral Inversion Based on LS-SVR Algorithm

To monitor growth and predict the yield of rice over a large area, the chlorophyll contents in the rice canopy were estimated using the unmanned aerial vehicle(UAV) remote sensing technology. In this work, multi-spectral image information of the rice crop was obtained using a 6-channel multi-spectral camera mounted on a fixed wing UAV, which was flown 600 m above the ground, between 11: 00-14: 00 on a sunny day in summer. The measured chlorophyll values were collected as sample sets. The s-REP index was screened out to estimate chlorophyll contents through the analysis of six kinds of spectral indexes of chlorophyll estimated capacity. An inversion model of the chlorophyll contents was then built using the least square support vector regression(LS-SVR)algorithm, with calibration and prediction R-square values of 0.89 and 0.83, respectively. Finally, remote sensing mapping for a UAV image of the Fangzheng County Dexter Rice Planting Park was accomplished using the inversion model. The inversion and measured values were then compared using regression fitting. R-square and root-mean-square error of the fitting model were 0.79 and 2.39,respectively. The results demonstrated that accurate estimation of rice-canopy chlorophyll contents was feasible using the LS-SVR inversion model developed using the s-REP vegetation index.

基于Cite Space可视化分析我国多发伤急救研究热点及趋势

目的梳理国内多发伤急救相关研究文献,分析研究现状、热点和趋势,为我国多发伤急救研究提供借鉴和指导。方法检索中国知网数据库中2011—2021年关于多发伤急救的相关文献,使用Cite Space 6.1.R3可视化软件对该领域的年发文量、机构、作者、关键词进行分析。结果最终纳入多发伤急救研究文献2519篇,整体发文数量较平稳,以2016年为小高峰;发文量最高的机构是华中科技大学附属同济医院。多发伤急救研究热点包括院前急救、并发症护理、风险因素分析和预后效果评估,研究前沿包括不同多发伤人群的诊断、治疗、手术和护理体会等方面。结论本文通过可视化分析国内多发伤急救研究的热点及趋势,指明了多发伤目前研究存在的问题和未来研究发展的方向,为进一步完善多发伤急救卫生服务和管理体系提供指导。

基于CiteSpace知识图谱的智慧养老领域研究文献综述

“十四五”规划将发展智慧养老产业上升为国家战略高度。文章借助Cite Space和Vosviewer绘图软件对2012-2022年国内外智慧养老领域研究的发文量、突现词等进行可视化分析。发现国内外研究都经历了三个发展阶段,国外研究起步早,研究成果丰富;国内研究虽然起步较晚,但进展快速。总结出“智慧养老内涵”“智慧养老模式”“智慧养老产业”“智慧养老平台”“智慧养老产品”“智慧养老用户”六大国内外都重点关注的研究议题,发现技术赋能智慧养老发展是近年来国内外共同关注的研究热点,大数据、物联网、养老金融、数字技术、区块链等成为围绕智慧养老文献的关键词。

Multi-Spectral and Fluorescence Imaging in Prevention of Overdose of Herbicides: The Case of Maize

Evaluation of the impact of herbicides on maize was done through multi- spectral and multi-modal imaging and multi-spectral fluorescence imaging combined with statistical methods. Spectra containing 13 wavelengths ranging from 375 nm to 940 nm were derived from multi-spectral images in transmission, reflection and scattering mode and fluorescence images obtained using high-pass filters (F450 nm, F500 nm, F550 nm, F600 nm, F650 nm) on control maize samples and maize samples treated with Herbextra herbicide were used. The appearance of the spectra allowed us to characterize the effect of the herbicide on the maize pigment concentration. The fluorescence images allowed us to track the fate of absorbed energy and through PLS-DA and SVM-DA to discriminate the two leaf categories with very low error rates for the test, i.e. 4.9% and 2% respectively. The results of this technique can be used in the context of precision agriculture.

中国人才政策研究的现状与趋势——基于Cite Space的可视化分析

科学的人才政策是实现人才强国和科教兴国战略的重要保障。借助Cite Space量化分析软件,分别从发文作者、发文机构、高被引文献、关键词等方面对人才政策研究情况进行可视化分析,在整合既有研究基础上展望未来。研究表明:我国人才政策研究主要聚焦于人才政策本身、实施存在的问题、可行性路径三个维度。当前的研究热点主题为人才战略、人才开发、人才培养,已有关键词之间关联性不强,机构合作密度不高,缺少系统研究框架和强大理论支持。据此,今后人才政策的研究应该加强跨学科融合思考,建构具有中国特色的本土化研究架构,注重人才培养的硬环境和软环境建设。

中国近代教科书研究的可视化计量分析与展望——基于CiteSpace知识图谱

运用经验总结法,借助CiteSpace软件,对近30年收录在CNKI中文核心期刊和CSSCI来源期刊的中国近代教科书研究文献分析发现:研究时序上,可分为萌芽、高速发展、深入研究三个阶段;研究空间上,核心研究者以个别代表性学者为主,机构以师范院校为领军,密切的研究合作网络与群体尚未形成;研究视角与方法上,主观性单一视角研究为主,定量及定性定量相结合的多学科融合研究不足;研究内容上,由宏观概括的梳理渐转到微观深入的探究,集中于中国近代教科书编审出版、文本合理性、中国化历程三个方面,所涉科目类属逐渐增多但仍不均衡。今后,需强化教材专业研究机构的核心地位,搭建专业力量协作的研究群体;丰富中国近代教科书研究视角,建立有针对性的方法论体系;细化中国近代教科书的研究范围,深化教科书研究内容;强化教科书编审研究,拓展中国近代教科书审定制度研究。

基于Cite Space的氮沉降对全球草地生态系统碳、氮和磷化学计量特征影响的可视化分析

【目的】全面分析氮沉降对全球天然草地生态系统碳、氮和磷化学计量学影响的现状、发展趋势和研究热点。【方法】基于文献计量分析方法,利用Cite Space可视化软件对Web of Science Core Collection数据库2000-2021年收录的14912篇有关氮沉降的论文进行分析。【结果】2000-2021年该领域的研究成果在国外期刊的发文量逐年上升;美国的论文数量位居前列(4199篇),中国发文量排名第2(3831篇);文献作者聚类分析参数为Q=0.4380(>0.3)、S=0.7865(>0.7),表明存在重要的聚类结构;共同引用的参考文献网络分析的模块化Q值和平均轮廓值均大于0.6,第1个大规模聚类被命名为"#0 nitrogen deposition",同时,Q=0.6792(>0.3)和S=0.8705(>0.7)。【结论】土壤温度敏感性和碳汇等主要内容是未来的研究热点。日后的研究应关注氮沉降驱动土壤微生物活动、制约土壤碳循环、多层网络稳定性机制、土壤微生物碳利用效率等方面。

基于CiteSpace对近10年国内外护理不良事件的可视化分析

为了解国内外近10年护理不良事件的研究热点与前沿,为医院管理和临床护士提供参考,保障患者安全,通过检索中国期刊全文数据库(CNKI)和Web of Science(WOS)数据库,检索时限为2012年1月—2022年8月,导入CiteSpace进行可视化分析。研究显示,从发文量看,国内外学者对护理不良事件的关注度整体较高,可视化分析结果并未发现作者之间、机构之间的联系。未来减少护理不良事件的方法一定会越来越紧贴科学技术,越来越多的新型信息化平台、App等会用于医疗行业,降低护理不良事件预防的难度,但护理人员仍要重视护理安全。

New Abnormal Cervical Cell Detection Method of Multi-Spectral Pap Smears

Considering the problem of traditional cervical cancer detection method that brings high false negative rate （FNR） and high false positive rate （FPR）, a new abnormal cervical cells detection method of multi-spectral Pap smear is proposed in this thesis, on the basis of multi-spectral microscopic imaging technology and computer automotive recognition technology. At first, image in a specific wave band is segmented according to the relationship between intensity and spectrum of each pixel. Then, multi-spectral features of each pixel are extracted making use of improved cosine correlation analysis （CCA） algorithm. Combined with the characteristic of each cell＇s area, final definition is made. Experiments have proved the new approach could identify abnormal cells efficiently as well as lower FNR and FPR.