Compressive near-field millimeter wave imaging algorithm based on Gini index and total variation mixed regularization

A compressive near-field millimeter wave(MMW)imaging algorithm is proposed.From the compressed sensing(CS)theory,the compressive near-field MMW imaging process can be considered to reconstruct an image from the under-sampled sparse data.The Gini index(GI)has been founded that it is the only sparsity measure that has all sparsity attributes that are called Robin Hood,Scaling,Rising Tide,Cloning,Bill Gates,and Babies.By combining the total variation(TV)operator,the GI-TV mixed regularization introduced compressive near-field MMW imaging model is proposed.In addition,the corresponding algorithm based on a primal-dual framework is also proposed.Experimental results demonstrate that the proposed GI-TV mixed regularization algorithm has superior convergence and stability performance compared with the widely used l1-TV mixed regularization algorithm.

Metric of Carbon Equity:Carbon Gini Index Based on Historical Cumulative Emission per Capita

This paper uses Lorenz curve and Gini index with adjustment to per capita historical cumulative emission to construct carbon Gini index to measure inequality in climate change area. The analysis shows that 70% of carbon space in the atmosphere has been used for unequal distribution, which is almost the same as that of incomes in a country with the biggest gap between the rich and the poor in the world. The carbon equity should be an urgency and priority in the climate agenda. Carbon Gini index established in this paper can be used to measure inequality in the distribution of carbon space and provide a quantified indicator for measurement of carbon equity among different proposals.

Gini Index for Cities: A Preliminary Study on Regional Differences of Chinese City Size Distribution

City size distribution is of interest because of a number of key stylized facts, including notably Zipf's law for cities and the importance of urban primacy. But a new and more efficient method Gini index can be used for calculating regional city size distribution. This paper begins by developing a calculation method for the Gini index, dividing the whole country into 26 areas and then calculating each area's Gini index value. Based on these calculation results, this paper gives a preliminary study on regional differences of its city size distribution and the dynamics.

Compressive Sensing Inverse Synthetic Aperture Radar Imaging Based on Gini Index Regularization

In compressive sensing(CS) based inverse synthetic aperture radar(ISAR) imaging approaches, the quality of final image significantly depends on the number of measurements and the noise level. In this paper, we propose an improved version of CSbased method for inverse synthetic aperture radar(ISAR) imaging. Different from the traditional l1 norm based CS ISAR imaging method, our method explores the use of Gini index to measure the sparsity of ISAR images to improve the imaging quality. Instead of simultaneous perturbation stochastic approximation(SPSA), we use weighted l1 norm as the surrogate functional and successfully develop an iteratively re-weighted algorithm to reconstruct ISAR images from compressed echo samples. Experimental results show that our approach significantly reduces the number of measurements needed for exact reconstruction and effectively suppresses the noise. Both the peak sidelobe ratio(PSLR) and the reconstruction relative error(RE) indicate that the proposed method outperforms the l1 norm based method.

MedGini:Gini index based sustainable health monitoring system using dew computing

Monitoring biosignals is crucial for intelligent health applications.Internet of Health Things(IoHT)provides a new path for monitoring the biosignals.Environment adaptive data dissemination is the primary requirement for the deployment of time and space-efficient monitoring systems.Existing dew-based systems lack an opportunistic architecture of data-synchronization with the cloud.This paper proposes a model that makes efficient use of IoT and cloud-dew architecture for a sustainable health monitoring system.Wireless sensor nodes are used to monitor the biosignals dynamically.All accrued data is temporarily stored in the dew layer.It is synchronized with the cloud at a subsequent phase to achieve seamless accessibility and optimal scalability of the data.Data synchronization plays an essential role in the cloud dew framework.We have used the Gini index and Shannon entropy to ensure intelligent data synchronization with the cloud.Sometimes sensors produce erroneous data,which poses a significant threat to the sustainable health monitoring system.Fuzzy normal distribution with a triangular membership function has been used to clean up the data and filter out the outliers.Further,we compared the proposed MedGini model with the existing models and analyzed the system performance.MedGini is found to outperform others concerning cost and power consumption.

基于GINI-PCC分析方法的批判性思维培养的探索

批判性思维是当代学生必须具备的一种思维方式,能够促进学生从辩证的角度对待多元化的信息,提高学生的问题思辨能力。以高校计算机专业的研究生为研究对象,采用基尼指数分析学生批判性思维特征的重要性,利用皮尔逊相关系数分析各个特征相关性,来确定侧重培养的特征。研究发现,通过侧重培养这些特征,学生的批判性思维有明显提高。

The Rich-Gini-Simpson quadratic index of biodiversity

The Gini-Simpson quadratic index is a classic measure of diversity, widely used by ecologists. As shown recently, however, this index is not suitable for the measurement of beta diversity when the number of species is very large. The objective of this paper is to introduce the Rich- Gini-Simpson quadratic index which preserves all the qualities of the classic Gini-Simpson index but behaves very well even when the number of species is very large. The additive partitioning of species diversity using the Rich-Gini- Simpson quadratic index and an application from island biogeography are analyzed.

Weighted Gini-Simpson Quadratic Index of Biodiversity for Interdependent Species

The weighted Gini-Simpson quadratic index is the simplest measure of biodiversity which takes into account the relative abundance of species and some weights assigned to the species. These weights could be assigned based on factors such as the phylogenetic distance between species, or their relative conservation values, or even the species richness or vulnerability of the habitats where these species live. In the vast majority of cases where the biodiversity is measured the species are supposed to be independent, which means that the relative proportion of a pair of species is the product of the relative proportions of the component species making up the respective pair. In the first section of the paper, the main versions of the weighted Gini-Simpson index of biodiversity for the pairs and triads of independent species are presented. In the second section of the paper, the weighted Gini-Simpson quadratic index is calculated for the general case when the species are interdependent. In this instance, the weights reflect the conservation values of the species and the distribution pattern variability of the subsets of species in the respective habitat induced by the inter-dependence between species. The third section contains a numerical example.

中国新质生产力水平、区域差异与时空演进特征

文章构建新质生产力水平测度指标体系,运用熵值法测算2012—2021年中国31个省份的新质生产力水平,通过Dagum基尼系数法分析其差异及来源,最后采用空间相关性检验探索中国新质生产力的时空集聚特征和动态跃迁情况。研究发现:中国新质生产力水平逐年上升,但整体水平不高且存在区域差异;劳动者维度和劳动对象维度中的新质产业发展是制约新质生产力水平提升的主要因素;四大地区新质生产力水平差异较大,区域差异的主要来源始终是区域间差异;中国新质生产力水平明显集聚于高效型和低效型,且具有较强的空间稳定性;中国新质生产力水平跃迁更多转向极化型和空心型,较少转向高效型,区域协调发展战略效果不同,虹吸效应与带动效应并存。

西部地区区域经济差异的时空演变特征

运用泰尔指数和基尼系数对西部地区12省2010-2021年区域经济差异进行相对差异的测定,通过莫兰指数对其进行全局空间自相关和局部自相关的分析。结果表明:2010-2021年一阶段泰尔指数分解结果中区域内差异的变化趋势和区域总体差异的变化趋势基本相同,基尼系数和泰尔指数的变化趋势一致;从贡献率来看,西南地区的贡献率均大于西北地区的贡献率,这表明西南地区的区域协调更需要重视;全局和局部空间自相关结果表明西部地区区域经济具有空间相关性且整体异质性范围小,H-H集聚区集中在陕西、重庆、宁夏等地区,L-L集聚区集中在青海、云南、西藏、广西等地区。

黄河流域关中平原城市群水资源利用效率与公平性评价

为提高黄河流域城市群水资源利用效率与公平性,推动黄河流域生态保护与高质量发展,以关中平原城市群为例,在采用水足迹与水行星边界方法分析水资源可持续利用水平的基础上,运用超效率SBM模型与GML指数探讨了城市群的水资源利用效率,并利用基尼系数与贡献系数评价了用水公平程度对城市群的影响。结果表明:2010—2019年,关中平原城市群水足迹、水赤字和灰水足迹分别下降了4.52%、3.62%和59.79%,水资源的不可持续性和水污染状况得到改善;水资源利用效率不高且未呈现增长趋势,技术效率与技术进步之间未实现良性互动;水资源占用相对公平,但水污染同城市发展及水资源承载能力之间的公平程度均有明显下降。

New indices to balanceα-diversity against tree size inequality

The number and composition of species in a community can be quantified withα-diversity indices,including species richness(R),Simpson’s index(D),and the Shannon-Wiener index(H΄).In forest communities,there are large variations in tree size among species and individu-als of the same species,which result in differences in eco-logical processes and ecosystem functions.However,tree size inequality(TSI)has been largely neglected in studies using the available diversity indices.The TSI in the diameter at breast height(DBH)data for each of 99920 m×20 m forest census quadrats was quantified using the Gini index(GI),a measure of the inequality of size distribution.The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat.We also examined the relationships ofα-diversity indices with the GI using correlation tests.The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions,with most root-mean-square errors(990 out of 999 quadrats)being<0.0030.There were significant positive correlations between each of threeα-diversity indices(i.e.,R,D,and H’)and the GI.Nevertheless,the total abundance of trees in each quadrat did not significantly influence the GI.This means that the TSI increased with increasing spe-cies diversity.Thus,two new indices are proposed that can balanceα-diversity against the extent of TSI in the com-munity:(1−GI)×D,and(1−GI)×H’.These new indices were significantly correlated with the original D and H΄,and did not increase the extent of variation within each group of indices.This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities,especially in the face of cumulative species loss under global climate change.

高职专科助产专业设置现状及区域差异性分析

目的分析我国高职专科助产专业设置现状及区域差异性。方法筛选2023年开设高职专科助产专业的院校,提取其专业、院校信息。同时,获取各省份地理面积、2023年各省份常住人口、出生人口数量、普通高等学校数量数据。采用描述性分析法分析我国当前高职专科助产专业设置基本情况、不同区域下我国高职专科助产专业设置现状。运用洛伦兹曲线、基尼系数和泰尔指数对高职专科助产专业布点院校分布的区域差异性进行分析。结果2023年高职专科助产专业布点院校共282所,其中280所(99.3%)开设高职专科3年制助产专业;200所(70.9%)为公办院校;259所(91.8%)为高职专科院校;93所(33.0%)为公办综合类高职专科院校。2023年我国每千万常住人口、每十万出生人口、每十万平方千米高职专科助产专业布点院校数依次为2.00所、3.13所和2.93所。2023年高职专科助产专业设置在地理面积、常住人口、出生人口维度上的基尼系数依次为0.618、0.212、0.230,总泰尔指数依次为0.319、0.042、0.041。结论高职专科助产专业学制以3年制为主,布点院校类型多样,在地理面积维度上的分布极不均衡,且分布差异主要来自地区内部。应积极推进职普融通,以提升助产专业从业人员整体学历层次;通过尽快将高职专科助产专业纳入国家控制的高职专业,健全和落实专业预警和动态调整机制等举措,科学调整、优化专业布局。

基于β收敛法的绿色技术创新产出演变规律研究

以绿色低碳转型为研究背景,从空间差异、空间交互与空间收敛3个维度分析了绿色技术创新产出的动态演变及收敛性。首先,利用Dagum基尼系数法识别绿色技术创新产出的空间差异程度,再进一步将其分解为群内差异、群间差异和超变密度因素的影响,从而发现空间差异的主要来源;然后,运用莫兰指数和散点图探究空间交互特征与集聚类型;最后,以β收敛模型分析空间收敛趋势。以我国绿色技术创新产出实际情况为例进行分析研究,发现:空间差异程度处于中高水平,东中西地区间差异是主要原因;空间互动从“微弱”转变为“显著”,“高–高”类型集聚于长三角地区,“低–低”集聚以中西部省份为主;省域间表现出明显的条件β收敛态势。相关建议为:注重长三角和京津地区“创新发动机”功能,加速溢出通道建设,为释放绿色技术创新的空间协同潜力提供方向。

长三角城市群新型工业化发展效率测度及收敛性分析

中国政府提出的全面实施创新驱动发展战略和推进供给侧结构性改革的重要举措之一是推进新型工业化,而提高长三角城市群新型工业化发展效率有利于推动经济转型升级、提升区域竞争力和实现可持续发展。基于2005—2021年长三角城市群41个城市的面板数据,运用超效率SBM-ML模型、Dagum基尼系数、核密度分析以及收敛模型对新型工业化发展效率进行测度并分析其动态演变趋势和收敛特征。结果表明,新型工业化发展效率总体呈现出增长的趋势,增长动力主要来自规模效率变化和技术进步变化;新型工业化发展效率差异总体在缩小,区域间差异是效率差异的主要部分;新型工业化发展效率的空间差距在逐步扩大,存在多级分化现象;四大规模城市均存在σ收敛和β收敛,收敛速度呈Ⅰ型城市、Ⅱ型城市、特大城市、长三角城市群依次减弱。

2011-2021年宁夏护理人力资源配置公平性分析

目的分析2011-2021年宁夏护理人力资源配置现状,为合理分配卫生资源提供有益参考。方法运用洛伦兹曲线、基尼系数和泰尔指数3个卫生经济学指标,评估宁夏护理人力资源配置的公平性。结果宁夏护理人力资源实现稳步增长,基尼系数和泰尔指数整体呈减小趋势,泰尔指数组间贡献率高于组内贡献率。结论宁夏护理人力资源配置逐年改善,但仍存在不公平现象,以人口分布为基础的公平性较按地理面积分布更为优越,各城市间的不平等是影响护理人力资源配置公平性的主要因素。

基于参数优化特征模态分解的强背景噪声下滚动轴承故障诊断

为准确提取被强背景噪声掩盖的滚动轴承故障信息,提出一种参数优化特征模态分解(parameter-optimized feature mode decomposition,POFMD)方法。首先,为解决特征模态分解(feature mode decomposition,FMD)方法的输入参数依赖人工经验选取的问题,以平方包络谱峭度(kurtosis of the square envelope spectrum,KSES)为权值,结合平方包络谱基尼系数(Gini index of the square envelope spectrum,GISES)构建加权平方包络谱基尼系数(weighted Gini index of the square envelope spectrum,WGISES)作为目标函数,通过优化算法确定FMD的最优参数组合;其次,为解决FMD的主模态分量难以选取的问题,通过计算所分解模态分量的KSES值选取主模态分量;最后,通过包络谱分析实现故障诊断。经仿真信号和实测信号分析,验证了POFMD在强背景噪声下滚动轴承故障诊断中的有效性。与变分模态分解、最大相关峭度解卷积和谱峭度相比,POFMD有更优越的故障特征提取性能。

面向土地覆盖精准分类的遥感特征参数优选方法

在显著气候变化叠加人类活动干扰的背景下,可持续的自然资源管理对于精准掌握土地覆盖信息的需求不断提升。为应对地表形态的复杂性、地物类型的多样性、遥感图像特征的非线性给传统遥感图像分类方法带来的挑战,本文基于随机森林Gini指数,提出了一种10%阈值决策的遥感特征参数优选方法,旨在筛选出最优的遥感特征参数组合,达到最佳土地覆盖分类效果。首先,选择光谱特征、纹理特征、温热特征、高程特征、主成分特征组成遥感影像堆栈。然后,设置多组决策树对特征贡献度进行交叉验证,并根据特征重要性的归一化均值确定特征排序。最后,设定阈值,筛选出符合要求的遥感特征参数,并迭代过程。选择覆盖江苏盐城自然保护区的Sentinel-2遥感图像开展试验,结果表明,本文方法筛选出的遥感特征参数代表性好,与CART、SVM、KNN和只使用波段信息的RF相比,分类结果地物边界清晰,类别属性准确,总体精度和Kappa系数分别为96.20%和0.9556。本文研究能够为区域空间规划和可持续发展提供技术支持。

改进融合指标的新型盲解卷积算法在轴承故障诊断中的应用

为解决现有盲解卷积算法易受随机脉冲影响的问题,综合时域特征和频域特征,提出一个新的故障敏感指标,即包络谱峭度-包络基尼系数融合指标(Envelope Spectral Kurtosis-envelope Gini Index,ESKEG)。该指标对周期性脉冲更敏感,不易受随机脉冲的影响。基于该指标,提出一个新的解卷积算法,即基于最大ESKEG的盲解卷积,并采用粒子群算法(Particle Swarm Optimization,PSO)求解滤波器系数。通过仿真振动信号和实验仿真信号进行验证,结果表明相比于其他盲解卷积算法,所提出的PSO-ESKEG算法在故障先验知识未知的情况下,能更有效避免受到随机脉冲信号的影响。

中国数字产业链发展水平、时空特征与区域差异

文章基于2009—2021年中国30个省份的面板数据,利用熵值法对中国数字产业链发展水平进行测算,运用莫兰指数、Dagum基尼系数法考察时空演进趋势和区域差异。结果表明:中国数字产业链发展水平呈波动上升趋势,但总体发展水平较低;中国数字产业链发展水平在空间上呈现高度相关性,且大多数省份分布在第一和第三象限;中国数字化产业链发展水平存在绝对差异和相对差异,其中绝对差异逐渐扩大,相对差异整体上呈现逐步缩小趋势,且地区间差异是造成中国数字化产业链发展水平空间非均衡的主要原因。提出打造现代化数字产业链新业态、建立协同联动数字产业链系统、因地制宜实施数字产业链创新战略的建议,以期为提高数字产业链发展水平提供经验借鉴。